Search results for: robust estimators

Authors: Mai A. Ibrahim, Mohammed El-Beltagy, Motaz Khorshid

Abstract:

Emerging Markets return distributions have shown significance departure from normality were they are characterized by fatter tails relative to the normal distribution and exhibit levels of skewness and kurtosis that constitute a significant departure from normality. Therefore, the classical Markowitz Mean-Variance is not applicable for emerging markets since it assumes normally-distributed returns (with zero skewness and kurtosis) and a quadratic utility function. Moreover, the Markowitz mean-variance analysis can be used in cases of moderate non-normality and it still provides a good approximation of the expected utility, but it may be ineffective under large departure from normality. Higher moments models and median models have been suggested in the literature for asset allocation in this case. Higher moments models have been introduced to account for the insufficiency of the description of a portfolio by only its first two moments while the median model has been introduced as a robust statistic which is less affected by outliers than the mean. Tail risk measures such as Value-at Risk (VaR) and Conditional Value-at-Risk (CVaR) have been introduced instead of Variance to capture the effect of risk. In this research, higher moment models including the Mean-Variance-Skewness (MVS) and Mean-Variance-Skewness-Kurtosis (MVSK) are formulated as single-objective non-linear programming problems (NLP) and median models including the Median-Value at Risk (MedVaR) and Median-Mean Absolute Deviation (MedMAD) are formulated as a single-objective mixed-integer linear programming (MILP) problems. The higher moment models and median models are compared to some benchmark portfolios and tested on real financial data in the Egyptian main Index EGX30. The results show that all the median models outperform the higher moment models were they provide higher final wealth for the investor over the entire period of study. In addition, the results have confirmed the inapplicability of the classical Markowitz Mean-Variance to the Egyptian stock market as it resulted in very low realized profits.

Keywords: Egyptian stock exchange, emerging markets, higher moment models, median models, mixed-integer linear programming, non-linear programming

Procedia PDF Downloads 315

Authors: Aasim Siddiqui

Abstract:

In a country where 45.6 per cent of the total population lives below the poverty line, according to the Human Development Report 2014 by UNDP, an increasing number of private companies are now dedicating their resources to remedy this situation of chronic poverty. Most corporations in Pakistan now have a separate and dedicated department for Corporate Social Responsibility (CSR), albeit with varying goals and hence different strategies for achieving those goals. Similarly, Marine Group of Companies (MRGC) also has a robust CSR policy which the group implements through a Non-Government Organization (NGO) called Organization for Social Development Initiatives (OSDI). This organization, which operates under the ambit of MRGC’s CSR division, has a concentrated focus on helping the poorest communities in the rural areas of Pakistan to break out of intergenerational poverty. This paper maps the theoretical strategies as well as practical activities undertaken by OSDI for poverty alleviation via rural development in Pakistan. To obtain in-depth information of demographics, livelihood and socio-economic indicators in OSDI’s focused districts; a combination of quantitative and qualitative research methodologies was used during the course of this research. The paper highlights and explains OSDI’s unique three-pronged approach which aims at reducing poverty through income generation via the livelihood assistance program and through the provision of access to the most basic services (including health and education) via the community development and food security programs. Modeled on the concept of capacity building, OSDI’s modus operandi is centered on disbursing timely microcredit facilities to farmers who can benefit from these funds by investing in productive assets to foster financial capability for the future. With a focus on increasing the income of poor farmers, OSDI’s approach is to integrate all the socio-economic facets: education, health and sanitation and food security, to induce a sustained positive impact on their living standards.

Keywords: CSR, poverty, rural, sustainability

Procedia PDF Downloads 246

Authors: Zahid Ullah, Atlas Khan

Abstract:

In today's data-driven world, the role of mathematics in bridging the gap between theory and applications is becoming increasingly vital. This abstract highlights the significance of mathematics as a powerful tool for analyzing, interpreting, and extracting meaningful insights from vast amounts of data. By integrating mathematical principles with real-world applications, researchers can unlock the full potential of data-driven decision-making processes. This abstract delves into the various ways mathematics acts as a bridge connecting theoretical frameworks to practical applications. It explores the utilization of mathematical models, algorithms, and statistical techniques to uncover hidden patterns, trends, and correlations within complex datasets. Furthermore, it investigates the role of mathematics in enhancing predictive modeling, optimization, and risk assessment methodologies for improved decision-making in diverse fields such as finance, healthcare, engineering, and social sciences. The abstract also emphasizes the need for interdisciplinary collaboration between mathematicians, statisticians, computer scientists, and domain experts to tackle the challenges posed by the data-driven landscape. By fostering synergies between these disciplines, novel approaches can be developed to address complex problems and make data-driven insights accessible and actionable. Moreover, this abstract underscores the importance of robust mathematical foundations for ensuring the reliability and validity of data analysis. Rigorous mathematical frameworks not only provide a solid basis for understanding and interpreting results but also contribute to the development of innovative methodologies and techniques. In summary, this abstract advocates for the pivotal role of mathematics in bridging theory and applications in a data-driven world. By harnessing mathematical principles, researchers can unlock the transformative potential of data analysis, paving the way for evidence-based decision-making, optimized processes, and innovative solutions to the challenges of our rapidly evolving society.

Keywords: mathematics, bridging theory and applications, data-driven world, mathematical models

Procedia PDF Downloads 75

Authors: Innocent Uzougbo Onwuegbuzie

Abstract:

Healthcare delivery in low-income markets is fraught with numerous challenges, including limited access to essential medical resources, inadequate healthcare infrastructure, and a significant shortage of trained healthcare professionals. These constraints lead to suboptimal health outcomes and a higher incidence of preventable diseases. This paper explores the application of Wireless Sensor Networks (WSNs) as a transformative solution to enhance healthcare delivery in these underserved regions. WSNs, comprising spatially distributed sensor nodes that collect and transmit health-related data, present opportunities to address critical healthcare needs. Leveraging WSN technology facilitates real-time health monitoring and remote diagnostics, enabling continuous patient observation and early detection of medical issues, especially in areas with limited healthcare facilities and professionals. The implementation of WSNs can enhance the overall efficiency of healthcare systems by enabling timely interventions, reducing the strain on healthcare facilities, and optimizing resource allocation. This paper highlights the potential benefits of WSNs in low-income markets, such as cost-effectiveness, increased accessibility, and data-driven decision-making. However, deploying WSNs involves significant challenges, including technical barriers like limited internet connectivity and power supply, alongside concerns about data privacy and security. Moreover, robust infrastructure and adequate training for local healthcare providers are essential for successful implementation. It further examines future directions for WSNs, emphasizing innovation, scalable solutions, and public-private partnerships. By addressing these challenges and harnessing the potential of WSNs, it is possible to revolutionize healthcare delivery and improve health outcomes in low-income markets.

Keywords: wireless sensor networks (WSNs), healthcare delivery, low-Income markets, remote patient monitoring, health data security

Procedia PDF Downloads 36

Authors: Peter Fornaro, Lothar Schmitt

Abstract:

The Digital Humanities Lab and the Institute of Art History at the University of Basel are collaborating in the SNSF research project ‘Digital Materiality’. Its goal is to develop and enhance existing methods for the digital reproduction of cultural heritage objects in order to support art historical research. One part of the project focuses on the visualization of a small eye-catching group of early prints that are noteworthy for their subtle reliefs and glossy surfaces. Additionally, this group of objects – known as ‘paste prints’ – is characterized by its fragile state of preservation. Because of the brittle substances that were used for their production, most paste prints are heavily damaged and thus very hard to examine. These specific material properties make a photographic reproduction extremely difficult. To obtain better results we are working with Reflectance Transformation Imaging (RTI), a computational photographic method that is already used in archaeological and cultural heritage research. This technique allows documenting how three-dimensional surfaces respond to changing lighting situations. Our first results show that RTI can capture the material properties of paste prints and their current state of preservation more accurately than conventional photographs, although there are limitations with glossy surfaces because the mathematical models that are included in RTI are kept simple in order to keep the software robust and easy to use. To improve the method, we are currently developing tools for a more detailed analysis and simulation of the reflectance behavior. An enhanced analytical model for the representation and visualization of gloss will increase the significance of digital representations of cultural heritage objects. For collaborative efforts, we are working on a web-based viewer application for RTI images based on WebGL in order to make acquired data accessible to a broader international research community. At the ICDH Conference, we would like to present unpublished results of our work and discuss the implications of our concept for art history, computational photography and heritage science.

Keywords: art history, computational photography, paste prints, reflectance transformation imaging

Procedia PDF Downloads 276

Authors: Sohaib Raza, Parvez Mantry

Abstract:

Frailty is a multi-system impairment associated with stressors such as age, disease, and invasive surgical procedures. This multi-system impairment can lead to increased post-transplant mortality and functional decline. Additionally, the prevalence and/or severity of frailty increases when patient pre-habilitation is unsatisfactory or lacking. We conducted a retrospective study to examine whether the COVID-19 Pandemic, and subsequent lack of patient access to pre-habilitation and physical therapy resources, led to an increase in the prevalence and severity of frailty, sarcopenia, and other comorbidities including diabetes, hypertension, and COPD. Secondarily, we examined the correlation between patient survival rate and liver frailty index as well as muscle wasting/sarcopenia. Data were analyzed in order to correlate variables associated with these parameters. Three hundred sixty-nine liver transplant candidates at Methodist Dallas Medical Center were administered pre-transplant frailty assessments, which consisted of chair stands, grip strength, and position balance time. A frailty score less than 3.2 indicated a robust condition, a score from 3.3 to 4.4 indicated a pre-frail condition, and a score greater than 4.5 indicated a frail condition. Greater than 50 percent of patients were found to have muscle wasting in the COVID-19 period (March 13, 2020 to February 28, 2022), an increase of 16.5 percent from the pre-COVID period (April 1st, 2018 to March 12, 2020). Additionally, sarcopenia was associated with a two-fold increase in patient mortality rate. Furthermore, high liver frailty index scores were associated with increased patient mortality. However, there was no significant difference in liver frailty index or number of comorbidities between patients in the two cohorts. Conclusion: The COVID-19 Pandemic exacerbated sarcopenia-related muscle wasting in liver transplant candidates, and patient survival rate was directly correlated with liver frailty index score and the presence of sarcopenia.

Keywords: frailty, sarcopenia, covid-19, patient mortality, pre-habilitation, liver transplant candidates

Procedia PDF Downloads 119

Authors: Sumanta Meher, Gaurav Shukla

Abstract:

The torments of the victims of terrorism have not only confined to loss of life and limp but also includes the physiological trauma to the innocent victims. The physical wounds may heal, but the trauma remains in the mind and heart of the victims and their loved ones; however, one should not deny that these terrorist activities affect to a major extent to their livelihood. To protect their human rights and restore the shattered lives of the victims of terrorism all the Nations beyond their differences have to show solidarity and frame a comprehensive restorative policy with an effective implementing mechanism. The General Assembly of United Nations, through its several resolutions, has appealed Nations to show solidarity and also committed to helping the Members State to frame the law and policy to support the victims of terrorism. To achieve the objectives of the resolutions adopted by the United Nations, the Indian legislators in 2008 amended the Code of Criminal Procedure, 1973 and incorporated Section 357A to provide financial assistance to the victims of terrorism. In India, the contemporary developments in the victims’ oriented studies have increased the dimension of the traditional criminal justice systems to protect the rights of the victims. In this regard, the paper has ascertained the Indian legal framework in respect to the restorative justice to the victims of terrorism and also addressed the question as to whether the statutory provisions and enforcement mechanisms are efficient enough to protect the human rights of the victims of terrorism. For that purpose, the paper has analyzed the International instruments and the reports with regard to the compensation to the victims of terrorist attacks, with that, the article also evaluates the initiatives of United Nations to help Members State to frame the law and policies to support the victims of terrorism. The study also made an attempt to critically analyze the legal provisions of compensation and rehabilitation of the victims of terrorist attacks in India and whether they are in alignment with the International standards. While concluding, the paper has made an endeavor for a robust legal framework towards the restorative justice for the victims of terrorism in India.

Keywords: victims of terrorism, restorative justice, human rights, criminal justice system of India

Procedia PDF Downloads 160

Authors: Vishal Das, Tianyi Mao, Zhicheng Geng, Carmen Flores, Diego Pelloso, Fang Wang

Abstract:

Accurate sell-in and sell-out forecasting is a ubiquitous problem in the retail industry. It is an important element of any demand planning activity. As a global food and beverage company, Nestlé has hundreds of products in each geographical location that they operate in. Each product has its sell-in and sell-out time series data, which are forecasted on a weekly and monthly scale for demand and financial planning. To address this challenge, Nestlé Chilein collaboration with Amazon Machine Learning Solutions Labhas developed their in-house solution of using machine learning models for forecasting. Similar products are combined together such that there is one model for each product category. In this way, the models learn from a larger set of data, and there are fewer models to maintain. The solution is scalable to all product categories and is developed to be flexible enough to include any new product or eliminate any existing product in a product category based on requirements. We show how we can use the machine learning development environment on Amazon Web Services (AWS) to explore a set of forecasting models and create business intelligence dashboards that can be used with the existing demand planning tools in Nestlé. We explored recent deep learning networks (DNN), which show promising results for a variety of time series forecasting problems. Specifically, we used a DeepAR autoregressive model that can group similar time series together and provide robust predictions. To further enhance the accuracy of the predictions and include domain-specific knowledge, we designed an ensemble approach using DeepAR and XGBoost regression model. As part of the ensemble approach, we interlinked the sell-out and sell-in information to ensure that a future sell-out influences the current sell-in predictions. Our approach outperforms the benchmark statistical models by more than 50%. The machine learning (ML) pipeline implemented in the cloud is currently being extended for other product categories and is getting adopted by other geomarkets.

Keywords: sell-in and sell-out forecasting, demand planning, DeepAR, retail, ensemble machine learning, time-series

Procedia PDF Downloads 274

Authors: Shishay Kidanu, Abdullah Alhaj

Abstract:

Sinkholes in the karst terrain of Greene County, Missouri, pose significant geohazards, imposing challenges on construction and infrastructure development, with potential threats to lives and property. To address these issues, understanding the influencing factors and modeling sinkhole susceptibility is crucial for effective mitigation through strategic changes in land use planning and practices. This study utilizes geographic information system (GIS) software to collect and process diverse data, including topographic, geologic, hydrogeologic, and anthropogenic information. Nine key sinkhole influencing factors, ranging from slope characteristics to proximity to geological structures, were carefully analyzed. The Frequency Ratio method establishes relationships between attribute classes of these factors and sinkhole events, deriving class weights to indicate their relative importance. Weighted integration of these factors is accomplished using the Analytic Hierarchy Process (AHP) and the Weighted Linear Combination (WLC) method in a GIS environment, resulting in a comprehensive sinkhole susceptibility index (SSI) model for the study area. Employing Jenk's natural break classifier method, the SSI values are categorized into five distinct sinkhole susceptibility zones: very low, low, moderate, high, and very high. Validation of the model, conducted through the Area Under Curve (AUC) and Sinkhole Density Index (SDI) methods, demonstrates a robust correlation with sinkhole inventory data. The prediction rate curve yields an AUC value of 74%, indicating a 74% validation accuracy. The SDI result further supports the success of the sinkhole susceptibility model. This model offers reliable predictions for the future distribution of sinkholes, providing valuable insights for planners and engineers in the formulation of development plans and land-use strategies. Its application extends to enhancing preparedness and minimizing the impact of sinkhole-related geohazards on both infrastructure and the community.

Keywords: sinkhole, GIS, analytical hierarchy process, frequency ratio, susceptibility, Missouri

Procedia PDF Downloads 74

Authors: R. Meier, M. Pander

Abstract:

In accordance with the industry 4.0 concept, manufacturing process steps as well as the materials themselves are going to be more and more digitalized within the next years. The “digital twin” representing the simulated and measured dataset of the (semi-finished) product can be used to control and optimize the individual processing steps and help to reduce costs and expenditure of time in product development, manufacturing, and recycling. In the present work, two material characterization methods based on Lamb waves were evaluated and compared. For demonstration purpose, both methods were shown at a standard industrial product - copper ribbons, often used in photovoltaic modules as well as in high-current microelectronic devices. By numerical approximation of the Rayleigh-Lamb dispersion model on measured phase velocities second order elastic constants (Young’s modulus, Poisson’s ratio) were determined. Furthermore, the effective third order elastic constants were evaluated by applying elastic, “non-destructive”, mechanical stress on the samples. In this way, small microstructural variations due to mechanical preconditioning could be detected for the first time. Both methods were compared with respect to precision and inline application capabilities. Microstructure of the samples was systematically varied by mechanical loading and annealing. Changes in the elastic ultrasound transport properties were correlated with results from microstructural analysis and mechanical testing. In summary, monitoring the elastic material properties of plate-like structures using Lamb waves is valuable for inline and non-destructive material characterization and manufacturing process control. Second order elastic constants analysis is robust over wide environmental and sample conditions, whereas the effective third order elastic constants highly increase the sensitivity with respect to small microstructural changes. Both Lamb wave based characterization methods are fitting perfectly into the industry 4.0 concept.

Keywords: lamb waves, industry 4.0, process control, elasticity, acoustoelasticity, microstructure

Procedia PDF Downloads 227

Authors: Viktor Müller, Ulman Lindenberger

Abstract:

Neurophysiological evidence suggests that the physiological states of the system are characterized by specific network structures and network topology dynamics, demonstrating a robust interplay between network topology and function. It is also evident that interpersonal action coordination or social interaction (e.g., playing music in duets or groups) requires strong intra- and interbrain synchronization resulting in a specific hyper brain network activity across two or more brains to support such coordination or interaction. Such complex hyper brain networks can be described as multiplex or multilayer networks that have a specific multidimensional or multilayer network organization characteristic for superordinate systems and their constituents. The aim of the study was to describe multilayer hyper brain networks and synchronization patterns of guitarists playing guitar in a quartet by using electroencephalography (EEG) hyper scanning (simultaneous EEG recording from multiple brains) and following time-frequency decomposition and multilayer network construction, where within-frequency coupling (WFC) represents communication within different layers, and cross-frequency coupling (CFC) depicts communication between these layers. Results indicate that communication or coupling dynamics, both within and between the layers across the brains of the guitarists, play an essential role in action coordination and are particularly enhanced during periods of high demands on musical coordination. Moreover, multilayer hyper brain network topology and dynamical structure of guitar sounds showed specific guitar-guitar, brain-brain, and guitar-brain causal associations, indicating multilevel dynamics with upward and downward causation, contributing to the superordinate system dynamics and hyper brain functioning. It is concluded that the neuronal dynamics during interpersonal interaction are brain-wide and frequency-specific with the fine-tuned balance between WFC and CFC and can best be described in terms of multilayer multi-brain networks with specific network topology and connectivity strengths. Further sophisticated research is needed to deepen our understanding of these highly interesting and complex phenomena.

Keywords: EEG hyper scanning, intra- and interbrain coupling, multilayer hyper brain networks, social interaction, within- and cross-frequency coupling

Procedia PDF Downloads 72

Authors: Kgolagano Mpejane

Abstract:

The study applies a New Institutional Economics (NIE) analytical framework to trade in developing economies by assessing the impacts of institutional quality and institutional quality distance on agricultural trade using a panel data of 15 Southern African Development Community (SADC) countries from the years 1991-2010. The issue of institutions on agricultural trade has not been accorded the necessary attention in the literature, particularly in developing economies. Therefore, the paper empirically tests the gravity model of international trade by measuring the impact of political, economic and legal institutions on intra SADC agricultural trade. The gravity model is noted for its exploratory power and strong theoretical foundation. However, the model has statistical shortcomings in dealing with zero trade values and heteroscedasticity residuals leading to biased results. Therefore, this study employs a two stage Heckman selection model with a Probit equation to estimate the influence of institutions on agricultural trade. The selection stages include the inverse Mills ratio to account for the variable bias of the gravity model. The Heckman model accounts for zero trade values and is robust in the presence of heteroscedasticity. The empirical results of the study support the NIE theory premise that institutions matter in trade. The results demonstrate that institutions determine bilateral agricultural trade on different margins with political institutions having positive and significant influence on bilateral agricultural trade flows within the SADC region. Legal and economic institutions have significant and negative effects on SADC trade. Furthermore, the results of this study confirm that institutional quality distance influences agricultural trade. Legal and political institutional distance have a positive and significant influence on bilateral agricultural trade while the influence of economic, institutional quality is negative and insignificant. The results imply that nontrade barriers, in the form of institutional quality and institutional quality distance, are significant factors limiting intra SADC agricultural trade. Therefore, gains from intra SADC agricultural trade can be attained through the improvement of institutions within the region.

Keywords: agricultural trade, institutions, gravity model, SADC

Procedia PDF Downloads 148

Authors: Jorge Rodriguez-Guerra, Carlos Calleja, Aron Pujana, Iker Elorza, Ana Maria Macarulla

Abstract:

Society demands more reliable manufacturing processes capable of producing high quality products in shorter production cycles. New control algorithms have been studied to satisfy this paradigm, in which Fault-Tolerant Control (FTC) plays a significant role. It is suitable to detect, isolate and adapt a system when a harmful or faulty situation appears. In this paper, a general overview about FTC characteristics are exposed; highlighting the properties a system must ensure to be considered faultless. In addition, a research to identify which are the main FTC techniques and a classification based on their characteristics is presented in two main groups: Active Fault-Tolerant Controllers (AFTCs) and Passive Fault-Tolerant Controllers (PFTCs). AFTC encompasses the techniques capable of re-configuring the process control algorithm after the fault has been detected, while PFTC comprehends the algorithms robust enough to bypass the fault without further modifications. The mentioned re-configuration requires two stages, one focused on detection, isolation and identification of the fault source and the other one in charge of re-designing the control algorithm by two approaches: fault accommodation and control re-design. From the algorithms studied, one has been selected and applied to a case study based on an industrial hydraulic-press. The developed model has been embedded under a real-time validation platform, which allows testing the FTC algorithms and analyse how the system will respond when a fault arises in similar conditions as a machine will have on factory. One AFTC approach has been picked up as the methodology the system will follow in the fault recovery process. In a first instance, the fault will be detected, isolated and identified by means of a neural network. In a second instance, the control algorithm will be re-configured to overcome the fault and continue working without human interaction.

Keywords: fault-tolerant control, electro-hydraulic actuator, fault detection and isolation, control re-design, real-time

Procedia PDF Downloads 177

Authors: Mohamed Abdalla, Ruixue Cheng, Jianyong Zhang

Abstract:

In pneumatic conveying, the solids are mixed with air or gas. In industries such as coal fired power stations, blast furnaces for iron making, cement and flour processing, the mass flow rate of solids needs to be monitored or controlled. However the current gas-solids two-phase flow measurement techniques are not as accurate as the flow meters available for the single phase flow. One of the problems that the multi-phase flow meters to face is that the flow profiles vary with measurement locations and conditions of pipe routing, bends, elbows and other restriction devices in conveying system as well as conveying velocity and concentration. To measure solids flow rate or concentration with non-even distribution of solids in gas, a uniform spatial sensitivity is required for a multi-phase flow meter. However, there are not many meters inherently have such property. The circular electrostatic meter is a popular choice for gas-solids flow measurement with its high sensitivity to flow, robust construction, low cost for installation and non-intrusive nature. However such meters have the inherent non-uniform spatial sensitivity. This paper first analyses the spatial sensitivity of circular electrostatic meter in general and then by combining the effect of the sensitivity to a single particle and the sensing volume for a given electrode geometry, the paper reveals first time how a circular electrostatic meter responds to a roping flow stream, which is much more complex than what is believed at present. The paper will provide the recent research findings on spatial sensitivity investigation at the University of Tees side based on Finite element analysis using Ansys Fluent software, including time and frequency domain characteristics and the effect of electrode geometry. The simulation results will be compared tothe experimental results obtained on a large scale (14” diameter) rig. The purpose of this research is paving a way to achieve a uniform spatial sensitivity for the circular electrostatic sensor by mean of compensation so as to improve overall accuracy of gas-solids flow measurement.

Keywords: spatial sensitivity, electrostatic sensor, pneumatic conveying, Ansys Fluent software

Procedia PDF Downloads 367

Authors: Sungmin Park, Gyungmok Nam, Seungpyo Woo, Young Choi, Sangheon Park, Sang-Hee Yoon

Abstract:

Puncturing human skin with microneedles is critically important for microneedle-mediate drug delivery. Despite of extensive efforts in the past decades, the scale-up fabrication of sharp-tipped and high-aspect-ratio microneedles, especially made of biodegradable polymers, is still a long way off. Here, we present a UV dose insensitive and cost-effective microfabrication method for the biodegradable polymer microneedles with sharp tips and long lengths which can pierce human skin with low insertion force. The biodegradable polymer microneedles are fabricated with the polymer solution casting where a poly(lactic-co-glycolic acid) (PLGA, 50:50) solution is coated onto a SU-8 mold prepared with a reverse, ramped, and rotational (R3) UV exposure. The R3 UV exposure is modified from the multidirectional UV exposure both to suppress UV reflection from the bottom surface without anti-reflection layers and to optimize solvent concentration in the SU-8 photoresist, therefore achieving robust (i.e., highly insensitive to UV dose) and cost-effective fabrication of biodegradable polymer microneedles. An optical model for describing the spatial distribution of UV irradiation dose of the R3 UV exposure is also developed to theoretically predict the microneedle geometry fabricated with the R3 UV exposure and also to demonstrate the insensitiveness of microneedle geometry to UV dose. In the experimental characterization, the microneedles fabricated with the R3 UV exposure are compared with those fabricated with a conventional method (i.e., multidirectional UV exposure). The R3 UV exposure-based microfabrication reduces the end-tip radius by a factor of 5.8 and the deviation from ideal aspect ratio by 74.8%, compared with conventional method-based microfabrication. The PLGA microneedles fabricated with the R3 UV exposure pierce full-thickness porcine skins successfully and are demonstrated to completely dissolve in PBS (phosphate-buffered saline). The findings of this study will lead to an explosive growth of the microneedle-mediated drug delivery market.

Keywords: R³ UV exposure, optical model, UV dose, reflection, solvent concentration, biodegradable polymer microneedle

Procedia PDF Downloads 167

Authors: Katharina Fellnhofer, Kaisu Puumalainen

Abstract:

Despite the current worldwide increasing interest in entrepreneurship education (EE), little attention has been paid to innovative web-based ways such as the narrative approach by telling individual stories of entrepreneurs via multimedia for demonstrating the impact on individuals towards entrepreneurship. In addition, this research discipline is faced with no consensus regarding its effective content of teaching materials and tools. Therefore, a qualitative hypothesis-generating research contribution is required to aim at drawing new insights from published works in the EE field of research to serve for future research related to multimedia entrepreneurial narratives. Based on this background, our effort will focus on finding support regarding following introductory statement: Multimedia success and failure stories of real entrepreneurs show potential to change perceptions towards entrepreneurship in a positive way. The proposed qualitative conceptual paper will introduce the underlying background for this research framework. Therefore, as a qualitative hypothesis-generating research contribution it aims at drawing new insights from published works in the EE field of research related to entrepreneurial narratives to serve for future research. With the means of the triangulation of multiple theories, we will utilize the foundation for multimedia-based entrepreneurial narratives applying a learning-through-multimedia-real-entrepreneurial-narratives pedagogical tool to facilitate entrepreneurship. Our effort will help to demystify how value-oriented entrepreneurs telling their stories multimedia can simultaneously enhance EE. Therefore, the paper will build new-fangled bridges between well-cited theoretical constructs to build a robust research framework. Overall, the intended contribution seeks to emphasize future research of currently under-researched issues in the EE sphere, which are considered to be essential not only to academia, as well as to business and society having future jobs-providing growth-oriented entrepreneurs in mind. The Authors would like to thank the Austrian Science Fund FWF: [J3740 – G27].

Keywords: entrepreneurship education, entrepreneurial attitudes and perceptions, entrepreneurial intention, entrepreneurial narratives

Procedia PDF Downloads 259

Authors: Joy Cao, Min Zhou

Abstract:

Purpose: Acute Type A aortic dissection is a well-known cause of extremely high mortality rate. A highly accurate and cost-effective non-invasive predictor is critically needed so that the patient can be treated at earlier stage. Although various CFD approaches have been tried to establish some prediction frameworks, they are sensitive to uncertainty in both image segmentation and boundary conditions. Tedious pre-processing and demanding calibration procedures requirement further compound the issue, thus hampering their clinical applicability. Using the latest physics informed deep learning methods to establish an accurate and cost-effective predictor framework are amongst the main goals for a better Type A aortic dissection treatment. Methods: Via training a novel physics-informed deep residual network, with non-invasive 4D MRI displacement vectors as inputs, the trained model can cost-effectively calculate all these biomarkers: aortic blood pressure, WSS, and OSI, which are used to predict potential type A aortic dissection to avoid the high mortality events down the road. Results: The proposed deep learning method has been successfully trained and tested with both synthetic 3D aneurysm dataset and a clinical dataset in the aortic dissection context using Google colab environment. In both cases, the model has generated aortic blood pressure, WSS, and OSI results matching the expected patient’s health status. Conclusion: The proposed novel physics-informed deep residual network shows great potential to create a cost-effective, non-invasive predictor framework. Additional physics-based de-noising algorithm will be added to make the model more robust to clinical data noises. Further studies will be conducted in collaboration with big institutions such as Cleveland Clinic with more clinical samples to further improve the model’s clinical applicability.

Keywords: type-a aortic dissection, deep residual networks, blood flow modeling, data-driven modeling, non-invasive diagnostics, deep learning, artificial intelligence.

Procedia PDF Downloads 89

Authors: Garreth Kestell, Lukah Dykes, Danielle Zerk, Kyla Trewartha, Rhianon Marshall, Elena Rudnik

Abstract:

Adolescent mental health is an international priority and the impact of innovative service models must be evaluated. Secondary school-based mental health services (SBMHS) involving private general practitioners and psychologists are a model of care being trialed in South Australia. Measures of depression, anxiety, and stress are routinely collected throughout psychotherapy sessions. This research set out to quantify the impact of psychotherapy for rural adolescents in a school setting and explore the importance of session frequency. Methods: Demographics, session date and DASS21 scores from students (n=65) seen in 2016 by three psychologists working at the SBMHS were recorded. Students were aged 13-18 years (M=15.43, SD= 1.24), mostly female (F=51, M=14), attended between 1 and 23 sessions with a median of 6 sessions (MAD 5.93) in one-year. The treating psychologist collected self-administered DASS21 scores. A mixed model analysis was used with age, sex, treating psychologist, months from first session, and session number as fixed effects, with response variables of DASS depression, anxiety, and stress scores. Results: 71.5% were classified as having extreme or severe anxiety and half had extreme or severe depression and/or stress scores. On average males had a greater increase in DASS scores over time but males attending more sessions benefited most from therapy. Discussion: Psychologists are treating rural adolescents in schools for severe anxiety, depression, and stress. This pilot study indicates that a predictive model combining demographics, session frequency, and DASS scores may help identify who is most likely to benefit from individual psychotherapy. Variations in DAS scores of individuals over time indicate the need for the collection of information such as living situation and exposure to alcohol. A larger sample size and additional data are currently being collected to allow for a more robust analysis.

Keywords: adolescent health, psychotherapy, school based mental health services, DAS21

Procedia PDF Downloads 166

Authors: Iyabode A. Kehinde, Joshua O. Oyekanmi, Jumoke T. Abimbola, Olajumoke E. Ayanda

Abstract:

African yam bean (AYB), (Sphenostylis stenocarpa) is a leguminous crop that provides nutritionally rich seeds, tubers and leaves for human consumption. AYB potentials as an important food security crop is yet to be realized and thus classified as underutilized crop. Underutilization of the crop has been partly associated with scarce information on the incidence and characterization of fungal endophytes infecting vascular parts of AYB. Accurate and robust detection of these endophytic fungi is essential for diagnosis, modeling, surveillance and protection of germplasm (seed) health. This work aimed at isolating and identifying fungal endophytes associated with leaves, stems and roots of AYB in Ogun State, Nigeria. This study investigated both cultural and molecular properties of endophytic fungi in AYB for its characterization and diversity. Fungal endophytes were isolated and culturally identified. DNA extraction, PCR amplification using ITS primers and analyses of nucleotide sequences of ribosomal DNA fragments were conducted on selected isolates. BLAST analysis was conducted on consensus nucleotide sequences of 28 out of 30 isolates and results showed similar homology with genera of Rhizopus, Cunninghamella, Fusarium, Aspergillus, Penicillium, Alternaria, Diaporthe, Nigrospora, Purpureocillium, Corynespora, Magnaporthe, Macrophomina, Curvularia, Acrocalymma, Talaromyces and Simplicillium. Slight similarity was found with endophytes associated with soybean. Phylogenetic analysis by maximum likelihood method showed high diversity among the general. These organisms have high economic importance in crop improvement. For an instance, Purpureocillium lilacinum showed high potential in control of root rot caused by nematodes in tomatoes. Though some can be pathogens, but many of the fungal endophytes have beneficial attributes to plant in host health, uptake of nutrients, disease suppression, and host immunity.

Keywords: molecular characterization, African Yam Bean, fungal endophyte, plant parts

Procedia PDF Downloads 213

Authors: Oktay Celenk, Ugur Karanfil, Iskender Demir, Samir Lamrini, Jorg Neumann, Arif Demir

Abstract:

Due to its favourable material characteristics, fiber reinforced plastics are amongst the main topics of all actual lightweight construction megatrends. Especially in transportation trends ranging from aeronautics over the automotive industry to naval transportation (yachts, cruise liners) the expected economic and environmental impact is huge. In naval transportation components like yacht bodies, antenna masts, decorative structures like deck lamps, light houses and pool areas represent cheap and robust solutions. Commercially available laser tools like carbon dioxide gas lasers (CO₂), frequency tripled solid state UV lasers, and Neodymium-YAG (Nd:YAG) lasers can be used. These tools have emission wavelengths of 10 µm, 0.355 µm, and 1.064 µm, respectively. The scientific goal is first of all the generation of a parameter matrix for laser processing of each used material for a Tm-fiber laser system (wavelength 2 µm). These parameters are the heat affected zone, process gas pressure, work piece feed velocity, intensity, irradiation time etc. The results are compared with results obtained with well-known material processing lasers, such as a Yb-fiber lasers (wavelength 1 µm). Compared to the CO₂-laser, the Tm-laser offers essential advantages for future laser processes like cutting, welding, ablating for repair and drilling in composite part manufacturing (components of cruise liners, marine pipelines). Some of these are the possibility of beam delivery in a standard fused silica fiber which enables hand guided processing, eye safety which results from the wavelength, excellent beam quality and brilliance due to the fiber nature. There is one more feature that is economically absolutely important for boat, automotive and military projects manufacturing that the wavelength of 2 µm is highly absorbed by the plastic matrix and thus enables selective removal of it for repair procedures.

Keywords: Thulium (Tm) fiber laser, laser processing of fiber-reinforced plastics (FRP), composite, heat affected zone

Procedia PDF Downloads 193

Authors: Sandeep Mehmi, Harsh Verma, A. L. Sangal

Abstract:

Ever since the idea of using computing services as commodity that can be delivered like other utilities e.g. electric and telephone has been floated, the scientific fraternity has diverted their research towards a new area called utility computing. New paradigms like cluster computing and grid computing came into existence while edging closer to utility computing. With the advent of internet the demand of anytime, anywhere access of the resources that could be provisioned dynamically as a service, gave rise to the next generation computing paradigm known as cloud computing. Today, cloud computing has become one of the most aggressively growing computer paradigm, resulting in growing rate of applications in area of IT outsourcing. Besides catering the computational and storage demands, cloud computing has economically benefitted almost all the fields, education, research, entertainment, medical, banking, military operations, weather forecasting, business and finance to name a few. Smart grid is another discipline that direly needs to be benefitted from the cloud computing advantages. Smart grid system is a new technology that has revolutionized the power sector by automating the transmission and distribution system and integration of smart devices. Cloud based smart grid can fulfill the storage requirement of unstructured and uncorrelated data generated by smart sensors as well as computational needs for self-healing, load balancing and demand response features. But, security issues such as confidentiality, integrity, availability, accountability and privacy need to be resolved for the development of smart grid cloud. In recent years, a number of intrusion prevention techniques have been proposed in the cloud, but hackers/intruders still manage to bypass the security of the cloud. Therefore, precise intrusion detection systems need to be developed in order to secure the critical information infrastructure like smart grid cloud. Considering the success of artificial neural networks in building robust intrusion detection, this research proposes an artificial neural network based model for detecting attacks in smart grid cloud.

Keywords: artificial neural networks, cloud computing, intrusion detection systems, security issues, smart grid

Procedia PDF Downloads 318

Authors: Md. Abdul Aziz

Abstract:

Sulfide ion is water soluble, highly corrosive, toxic and harmful to the human beings. As a result, knowing the exact concentration of sulfide in water is very important. However, the existing detection and quantification methods have several shortcomings, such as high cost, low sensitivity, and massive instrumentation. Consequently, the development of novel sulfide sensor is relevant. Nevertheless, electrochemical methods gained enormous popularity due to a vast improvement in the technique and instrumentation, portability, low cost, rapid analysis and simplicity of design. Successful field application of electrochemical devices still requires vast improvement, which depends on the physical, chemical and electrochemical aspects of the working electrode. The working electrode made of bulk gold (Au) and platinum (Pt) are quite common, being very robust and endowed with good electrocatalytic properties. High cost, and electrode poisoning, however, have so far hindered their practical application in many industries. To overcome these obstacles, we developed a sulfide sensor based on an indium tin oxide nanoparticle (ITONP)-modified ITO electrode. To prepare ITONP-modified ITO, various methods were tested. Drop-drying of ITONPs (aq.) on aminopropyltrimethoxysilane-functionalized ITO (APTMS/ITO) was found to be the best method on the basis of voltammetric analysis of the sulfide ion. ITONP-modified APTMS/ITO (ITONP/APTMS/ITO) yielded much better electrocatalytic properties toward sulfide electro-οxidation than did bare or APTMS/ITO electrodes. The ITONPs and ITONP-modified ITO were also characterized using transmission electron microscopy and field emission scanning electron microscopy, respectively. Optimization of the type of inert electrolyte and pH yielded an ITONP/APTMS/ITO detector whose amperometrically and chronocoulοmetrically determined limits of detection for sulfide in aqueous solution were 3.0 µM and 0.90 µM, respectively. ITONP/APTMS/ITO electrodes which displayed reproducible performances were highly stable and were not susceptible to interference by common contaminants. Thus, the developed electrode can be considered as a promising tool for sensing sulfide.

Keywords: amperometry, chronocoulometry, electrocatalytic properties, ITO-nanoparticle-modified ITO, sulfide sensor

Procedia PDF Downloads 131

Authors: Yunfeng Shan, Xiaoliang Wang, Youjun Zhou

Abstract:

Whole-genome data from two lungfish species, along with other species, present a valuable opportunity to reassess the longstanding debate regarding the evolutionary relationships among tetrapods, lungfishes, and coelacanths. However, the use of bootstrap support has become outdated for large-scale phylogenomic data. Without robust phylogenetic support, the phylogenetic trees become meaningless. Therefore, it is necessary to re-evaluate the phylogenies of tetrapods, lungfishes, and coelacanths using novel measures of phylogenetic support specifically designed for phylogenomic data, as the previous phylogenies were based on 100% bootstrap support. Our findings consistently provide strong evidence favoring lungfish as the closest living relative of tetrapods. This conclusion is based on high gene support confidence with confidence intervals exceeding 95%, high internode certainty, and high gene concordance factor. The evidence stems from two datasets containing recently deciphered whole genomes of two lungfish species, as well as five previous datasets derived from lungfish transcriptomes. These results yield fresh insights into the three hypotheses regarding the phylogenies of tetrapods, lungfishes, and coelacanths. Importantly, these hypotheses are not mere conjectures but are substantiated by a significant number of genes. Analyzing real biological data further demonstrates that the inclusion of additional taxa diminishes the number of orthologues and leads to more diverse tree topologies. Consequently, gene trees and species trees may not be identical even when whole-genome sequencing data is utilized. However, it is worth noting that many gene trees can accurately reflect the species tree if an appropriate number of taxa, typically ranging from six to ten, are sampled. Therefore, it is crucial to carefully select the number of taxa and an appropriate outgroup while excluding fast-evolving taxa as outgroups to mitigate the adverse effects of long-branch attraction (LBA) and achieve an accurate reconstruction of the species tree. This is particularly important as more whole-genome sequencing data becomes available.

Keywords: gene support confidence (GSC), origin of land vertebrates, coelacanth, two whole genomes of lungfishes, confidence intervals

Procedia PDF Downloads 87

Authors: Afrouz Yousefi, Mohtada Sadrzadeh

Abstract:

The widespread presence of poly- and perfluoroalkyl substances (PFAS) poses a significant concern due to their ability to accumulate in living organisms and their persistence in the environment, thanks to their robust carbon-fluorine (C-F) bonds, which require substantial energy to break (485 kJ/mol). The prevalence of toxic PFAS compounds can be highly detrimental to ecosystems, wildlife, and human health. Ongoing efforts are dedicated to investigating methods for fully breaking down and eliminating PFAS from the environment. Among the various techniques employed, advanced oxidation processes have shown promise in completely breaking down emerging contaminants in wastewater. However, the drawback lies in the relatively slow reaction rates of these processes and the substantial energy input required, which currently impedes their widespread commercial adoption. We developed a hybrid process, comprising electro-Fenton as an advanced oxidation process and membrane distillation, to simultaneously degrade organic PFAS pollutants and extract pure water from the mixture. In this study, environmentally persistent perfluorooctanoic acid (PFOA), as an emerging contaminant, was used to study the effectiveness of the electro-Fenton/membrane distillation hybrid system. The PFOA degradation studies were conducted in two modes: electro-Fenton and electro-Fenton coupled with membrane distillation. High-performance liquid chromatography with ultraviolet detection (HPLC-UV), ion-chromatography (measuring fluoride ion concentration), total organic carbon (TOC) decay, mineralization current efficiency (MCE), and specific energy consumption (SEC) were evaluated for a single EF and hybrid EF-MD processes. In contrast to a single EF reaction, TOC decay improved significantly in the EF-MD process. Overall, the MCE of hybrid processes surpassed 100% while it remained under 50% for a single EF reaction. Calculations of specific energy consumption (SEC) demonstrated a substantial decrease of nearly one-third in energy usage when integrating the EF reaction with the MD process.

Keywords: water treatment, PFAS, membrane distillation, electro-Fenton, advanced oxidation

Procedia PDF Downloads 63

Authors: Bruno Nascimento, Cristina Wanzeller, Jorge Silva, João A. Dias, André Barbosa, José Ribeiro

Abstract:

The increasing complexity of logistics operations stems from evolving business needs, such as the shift from mass production to mass customization, which demands greater efficiency and flexibility. In response, Industry 4.0 and 5.0 technologies provide improved solutions to enhance operational agility and better meet market demands. The management of kitting zones, combined with the use of Autonomous Mobile Robots, faces challenges related to coordination, resource optimization, and rapid response to customer demand fluctuations. Additionally, implementing lean manufacturing practices in this context must be carefully orchestrated by intelligent systems and human operators to maximize efficiency without sacrificing the agility required in an advanced production environment. This paper proposes and implements a microservices-based architecture integrating principles from Industry 4.0 and 5.0 with lean manufacturing practices. The architecture enhances communication and coordination between autonomous vehicles and kitting management systems, allowing more efficient resource utilization and increased scalability. The proposed architecture focuses on the modularity and flexibility of operations, enabling seamless flexibility to change demands and the efficient allocation of resources in realtime. Conducting this approach is expected to significantly improve logistics operations’ efficiency and scalability by reducing waste and optimizing resource use while improving responsiveness to demand changes. The implementation of this architecture provides a robust foundation for the continuous evolution of kitting management and process optimization. It is designed to adapt to dynamic environments marked by rapid shifts in production demands and real-time decision-making. It also ensures seamless integration with automated systems, aligning with Industry 4.0 and 5.0 needs while reinforcing Lean Manufacturing principles.

Keywords: microservices, event-driven, kitting, AMR, lean manufacturing, industry 4.0, industry 5.0

Procedia PDF Downloads 24

Authors: Ming-Jyh Chen, Wen-Ming Huang, Yi-Chu Liu, Li-Hui Yang

Abstract:

Introduction: Social responsibility is the key to sustainable organizational development. Under the ground Green Health Hospital Declaration signed by our superintendent, we have launched comprehensive energy conservation management in medical services, the community, and the staff’s life. To execute environment-friendly promotion with robust strategies, we build up a low-carbon medical system and community with smart green public construction promotion as well as intensifying energy conservation education and communication. Purpose/Methods: With the support of the board and the superintendent, we construct an energy management team, commencing with an environment-friendly system, management, education, and ISO 50001 energy management system; we have ameliorated energy performance and energy efficiency and continuing. Results: In the year 2021, we have achieved multiple goals. The energy management system efficiently controls diesel, natural gas, and electricity usage. About 5% of the consumption is saved when compared to the numbers from 2018 and 2021. Our company develops intelligent services and promotes various paperless electronic operations to provide people with a vibrant and environmentally friendly lifestyle. The goal is to save 68.6% on printing and photocopying by reducing 35.15 million sheets of paper yearly. We strengthen the concept of environmental protection classification among colleagues. In the past two years, the amount of resource recycling has reached more than 650 tons, and the resource recycling rate has reached 70%. The annual growth rate of waste recycling is about 28 metric tons. Conclusions: To build a green medical system with “high efficacy, high value, low carbon, low reliance,” energy stewardship, economic prosperity, and social responsibility are our principles when it comes to formulation of energy conservation management strategies, converting limited sources to efficient usage, developing clean energy, and continuing with sustainable energy.

Keywords: energy efficiency, environmental education, green hospital, sustainable development

Procedia PDF Downloads 79

Authors: Cenza Rhoda, Falone Sunda, Elvis Kidzeru, Nonhlanhla P. Khumalo, Afolake Arowolo

Abstract:

Introduction: The human FAM111B gene mutations are associated with POIKTMP, a rare multi-organ fibrosing disease. Recent studies also reported the overexpression of FAM111B in specific cancers. However, the role of FAM111B in these pathologies, particularly fibrosarcoma, remains unknown. Materials and Methods: FAM111B RNA expression in some cancer cell lines was assessed in silico and validated in vitro in these cell lines and skin fibroblasts derived from the South African family member affected by POIKTMP with the heterozygous FAM111B gene mutation: NM_198947.4: c.1861T>G (p. Tyr621Asp or Y621D) by qPCR and western blot. The cellular function of FAM111B was also studied in HT1080 using various cell-based functional assays and a simple and cost-effective PCR-RFLP method for genotyping/screening FAM111B gene mutations described. Results: Expression studies showed upregulated FAM111B mRNA and protein in the cancer cells. High FAM111B expression with robust nuclear localization occurred in HT1080. Additionally, expression data and cell-based assays indicated that FAM111B led to the upregulation of cell migration and decreased cell apoptosis and cell proliferation modulation. FAM111B Y621D mutation showed similar effects on cell migration but minimal impact on cell apoptosis. FAM111B mRNA and protein expression were markedly downregulated (p ≤ 0.05) in the patient's skin-derived fibroblasts. Lastly, the PCR-RFLP method successfully genotyped FAM111B Y621D gene mutation. Discussion: FAM111B is a cancer-associated nuclear protein: Its modulation by mutations may enhance cell migration and proliferation and decrease apoptosis, as seen in cancers and POIKTMP/fibrosis, thus representing a viable therapeutic target in these disorders. Furthermore, the PCR-RFLP method could prove a valuable tool for FAM111B mutation validation or screening in resource-constrained laboratories.

Keywords: FAM111B, POIKTMP, cancer, fibrosis, PCR-RFLP

Procedia PDF Downloads 121

Authors: Abdulbaset Mazarzaei

Abstract:

Natural killer (NK) cells are innate immune effectors that play a pivotal role in combating tumors and infected cells. In recent years, the therapeutic potential of NK cells has gained significant attention due to their remarkable cytotoxic ability. This study focuses on investigating the cytotoxic effect of expanded NK cells enriched with interleukin 12 (IL12) and interleukin 15 (IL15), derived from the leukoreduction filter, on the K562 cell line. Firstly, NK cells were isolated from whole blood samples obtained from healthy volunteers. These cells were subsequently expanded ex vivo using a combination of feeder cells, IL12, and IL15. The expanded NK cells were then harvested and assessed for their cytotoxicity against K562, a well-established human chronic myelogenous leukemia cell line. The cytotoxicity was evaluated using flow cytometry assay. Results demonstrate that the expanded NK cells significantly exhibited enhanced cytotoxicity against K562 cells compared to non-expanded NK cells. Interestingly, the expanded NK cells derived specifically from IL12 and IL15-enriched leukoreduction filters showed a robust cytotoxic effect similar to the whole blood-derived NK cells. These findings suggest that IL12 and IL15 in the leukoreduction filter are crucial in promoting NK cell cytotoxicity. Furthermore, the expanded NK cells displayed relatively similar cytotoxicity profiles to whole blood-derived NK cells, indicating their comparable capability in targeting and eliminating tumor cells. This observation is of significant relevance as expanded NK cells from the leukoreduction filter could potentially serve as a readily accessible and efficient source for adoptive immunotherapy. In conclusion, this study highlights the significant cytotoxic effect of expanded NK cells enriched with IL12 and IL15 obtained from the leukoreduction filter on the K562 cell line. Moreover, it emphasizes that these expanded NK cells exhibit comparable cytotoxicity to whole blood-derived NK cells. These findings reinforce the potential clinical utility of using expanded NK cells from the leukoreduction filter as an effective strategy in adoptive immunotherapy for the treatment of cancer. Further studies are warranted to explore the broader implications of this approach in clinical settings.

Keywords: natural killer (NK) cells, Cytotoxicity, Leukoreduction filter, IL-12 and IL-15 Cytokines

Procedia PDF Downloads 65

Authors: Benbiao Song, Yan Gao, Zhuo Liu

Abstract:

Geostatistical modeling is the key technic for reservoir characterization, the quality of geological models will influence the prediction of reservoir performance greatly, but few studies have been done to quantify the factors impacting geostatistical reservoir modeling accuracy. In this study, 16 fluvial prototype models have been established to represent different geological complexity, 6 cases range from 16 to 361 wells were defined to reproduce all those 16 prototype models by different methodologies including SIS, object-based and MPFS algorithms accompany with different constraint parameters. Modeling accuracy ratio was defined to quantify the influence of each factor, and ten realizations were averaged to represent each accuracy ratio under the same modeling condition and parameters association. Totally 5760 simulations were done to quantify the relative contribution of each factor to the simulation accuracy, and the results can be used as strategy guide for facies modeling in the similar condition. It is founded that data density, geological trend and geological complexity have great impact on modeling accuracy. Modeling accuracy may up to 90% when channel sand width reaches up to 1.5 times of well space under whatever condition by SIS and MPFS methods. When well density is low, the contribution of geological trend may increase the modeling accuracy from 40% to 70%, while the use of proper variogram may have very limited contribution for SIS method. It can be implied that when well data are dense enough to cover simple geobodies, few efforts were needed to construct an acceptable model, when geobodies are complex with insufficient data group, it is better to construct a set of robust geological trend than rely on a reliable variogram function. For object-based method, the modeling accuracy does not increase obviously as SIS method by the increase of data density, but kept rational appearance when data density is low. MPFS methods have the similar trend with SIS method, but the use of proper geological trend accompany with rational variogram may have better modeling accuracy than MPFS method. It implies that the geological modeling strategy for a real reservoir case needs to be optimized by evaluation of dataset, geological complexity, geological constraint information and the modeling objective.

Keywords: fluvial facies, geostatistics, geological trend, modeling strategy, modeling accuracy, variogram

Procedia PDF Downloads 264

Authors: Nadwah Onwi, Puspa Maniam, Azmawanie A. Aziz, Fairus Mukhtar, Nor Azrita Mohamed Zin, Nurul Haslina Mohd Zin, Nurul Fatehah Ismail, Mohamad Safwan Yusoff, Susilidianamanalu Abd Rahman, Siti Munirah Harris, Maryam Aizuddin

Abstract:

Objective: Malaysia has a growing number of individuals with complex communication needs (CCN). The initiation of augmentative and alternative communication (AAC) intervention may facilitate individuals with CCN to understand and express themselves optimally and actively participate in activities in their daily life. AAC is defined as multimodal use of communication ability to allow individuals to use every mode possible to communicate with others using a set of symbols or systems that may include the symbols, aids, techniques, and strategies. It is consequently critical to evaluate the deficits to inform treatment for AAC intervention. However, no known measurement tools are available to evaluate the user with CCN available locally. Design: A systematic review (SR) is designed to analyze the psychometric properties of AAC assessment for adolescents with CCN published in peer-reviewed journals. Tools are rated by the methodological quality of studies and the psychometric measurement qualities of each tool. Method: A literature search identifying AAC assessment tools with psychometrically robust properties and conceptual framework was considered. Two independent reviewers screened the abstracts and full-text articles and review bibliographies for further references. Data were extracted using standardized forms and study risk of bias was assessed. Result: The review highlights the psychometric properties of AAC assessment tools that can be used by speech-language therapists applicable to be used in the Malaysian context. The work outlines how systematic review methods may be applied to the consideration of published material that provides valuable data to initiate the development of Malay Language AAC assessment tools. Conclusion: The synthesis of evidence has provided a framework for Malaysia Speech-Language therapists in making an informed decision for AAC intervention in our standard operating procedure in the Ministry of Health, Malaysia.

Keywords: augmentative and alternative communication, assessment, adolescents, complex communication needs

Procedia PDF Downloads 152