Search results for: shared/mental models

Authors: Jinshuo Zhang

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Lucid dreams(LD) are the mental states in which people are aware that they are dreaming, which is a rising interdisciplinary topic among psychologists, neuroscientists and spiritual practitioners. From a phenomenological perspective, this research explores the self-consciousness structure in lucid dreams, particularly focusing on the self-reference structure between lucidity(the observer) and the dream ego(the observed). The main argument of this paper is that the self-structure in lucid dreams is a single-level paradigm. In this paper, the phenomenological characteristics of lucidity in LD are carefully unfolded. The appearance of lucidity is the most significant part of understanding the self-structure and the consciousness in dreams, which is also related to the “Six Bardos practices” in Tibetan Buddhism. In the second section, this research investigates the referential relationship between"lucidity" and "the dream ego" using the phenomenological resource of subjectivity theory, as well as referring to many cases in the psychological labs. Despite the appearance of various consciousness layers in lucid dreams, according to this paper, they are all part of a single-level consciousness paradigm. Dream ego is transparent, and dream lucidity can grasp it directly and thoroughly during LD. This research also responds to some potential criticisms and engages in current debates about the self-structure issue in lucid dreams, as well as discussing some future research prospects for dreams and lucid dreams.

Keywords: lucid dream, self-awareness, phenomenological perspective, high-order theory, one-level consciousness

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Authors: T. Yılmaz, Ş. Tavman

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In this study, optimization of ultrasound assisted extraction (UAE) of hemicellulose based polysaccharides from plant waste material has been studied. Selected material is hazelnut skin. Extraction variables for the operation are extraction time, amplitude and application temperature. Optimum conditions have been evaluated depending on responses such as amount of wet crude polysaccharide, total carbohydrate content and dried sample. Pretreated hazelnut skin powders were used for the experiments. 10 grams of samples were suspended in 100 ml water in a jacketed vessel with additional magnetic stirring. Mixture was sonicated by immersing ultrasonic probe processor. After the extraction procedures, ethanol soluble and insoluble sides were separated for further examinations. The obtained experimental data were analyzed by analysis of variance (ANOVA). Second order polynomial models were developed using multiple regression analysis. The individual and interactive effects of applied variables were evaluated by Box Behnken Design. The models developed from the experimental design were predictive and good fit with the experimental data with high correlation coefficient value (R2 more than 0.95). Extracted polysaccharides from hazelnut skin are assumed to be pectic polysaccharides according to the literature survey of Fourier Transform Spectrometry (FTIR) analysis results. No more change can be observed between spectrums of different sonication times. Application of UAE at optimized condition has an important effect on extraction of hemicellulose from plant material by satisfying partial hydrolysis to break the bounds with other components in plant cell wall material. This effect can be summarized by varied intensity of microjets and microstreaming at varied sonication conditions.

Keywords: hazelnut skin, optimization, polysaccharide, ultrasound assisted extraction

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Authors: Malkin Valery, Rogaleva Liudmila

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During the last 50-60 years the sports psychology has become firmly established in sports. At the same time, the sport practice brings evidence that it is only beginning to solve some of the most important problems in sports. It is untimely to say that the sports psychology has become a compulsory and efficient part of the sportsman’s preparation. It seems that the further development of the sports psychology can be seen, on the one hand, in the re-orientation of the psychologists from the regulation of the sportsman’s mentality to the process of forming the subject of the sport activity able to take the overall responsibility for the result of the sport activity, able to independently set objectives and to overcome the psychological difficulties that arise in the process of attaining these objectives. In its turn, it will require the change in the very approach to the psychologist’s work. The psychologist and the couch will turn from the specialists in correcting the negative manifestations of the sportsman’s mentality to the specialists in forming the subjects of the sport activity. It will require the creation of the technologies that can form the subjects on all the age-specific stages of the sport activity, that can form the most important psychological qualities (psychological stability, mental reliability, etc.). Getting these technologies will enable the couch to change from the consumer of the psychological knowledge to the immediate participant of the psychological process.

Keywords: sports psychology, subject, sportsman’s preparation, psychological knowledge

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Authors: Beilei Xu, Wencheng Wu, Lei Lin, Rachel Melnyk, Ahmed Ghazi

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In operating rooms, excessive cognitive stress can impede the performance of a surgeon, while low engagement can lead to unavoidable mistakes due to complacency. As a consequence, there is a strong desire in the surgical community to be able to monitor and quantify the cognitive stress of a surgeon while performing surgical procedures. Quantitative cognitiveload-based feedback can also provide valuable insights during surgical training to optimize training efficiency and effectiveness. Various physiological measures have been evaluated for quantifying cognitive stress for different mental challenges. In this paper, we present a study using the cognitive stress measured by the task evoked pupillary response extracted from the time series eye-tracking measurements to predict task difficulties in a virtual reality based robotic surgery training environment. In particular, we proposed a differential-task-difficulty scale, utilized a comprehensive feature extraction approach, and implemented a multitask learning framework and compared the regression accuracy between the conventional single-task-based and three multitask approaches across subjects.

Keywords: surgical metric, task evoked pupillary response, multitask learning, TSFresh

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Authors: Norma Binti Alias, Che Rahim Che The, Norfarizan Mohd Said, Sakinah Abdul Hanan, Akhtar Ali

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This paper discusses on the transportation of magnetic drug targeting through blood within vessels, tissues and cells. There are three integrated mathematical models to be discussed and analyze the concentration of drug and blood flow through magnetic nanoparticles. The cell therapy brought advancement in the field of nanotechnology to fight against the tumors. The systematic therapeutic effect of Single Cells can reduce the growth of cancer tissue. The process of this nanoscale phenomena system is able to measure and to model, by identifying some parameters and applying fundamental principles of mathematical modeling and simulation. The mathematical modeling of single cell growth depends on three types of cell densities such as proliferative, quiescent and necrotic cells. The aim of this paper is to enhance the simulation of three types of models. The first model represents the transport of drugs by coupled partial differential equations (PDEs) with 3D parabolic type in a cylindrical coordinate system. This model is integrated by Non-Newtonian flow equations, leading to blood liquid flow as the medium for transportation system and the magnetic force on the magnetic nanoparticles. The interaction between the magnetic force on drug with magnetic properties produces induced currents and the applied magnetic field yields forces with tend to move slowly the movement of blood and bring the drug to the cancer cells. The devices of nanoscale allow the drug to discharge the blood vessels and even spread out through the tissue and access to the cancer cells. The second model is the transport of drug nanoparticles from the vascular system to a single cell. The treatment of the vascular system encounters some parameter identification such as magnetic nanoparticle targeted delivery, blood flow, momentum transport, density and viscosity for drug and blood medium, intensity of magnetic fields and the radius of the capillary. Based on two discretization techniques, finite difference method (FDM) and finite element method (FEM), the set of integrated models are transformed into a series of grid points to get a large system of equations. The third model is a single cell density model involving the three sets of first order PDEs equations for proliferating, quiescent and necrotic cells change over time and space in Cartesian coordinate which regulates under different rates of nutrients consumptions. The model presents the proliferative and quiescent cell growth depends on some parameter changes and the necrotic cells emerged as the tumor core. Some numerical schemes for solving the system of equations are compared and analyzed. Simulation and computation of the discretized model are supported by Matlab and C programming languages on a single processing unit. Some numerical results and analysis of the algorithms are presented in terms of informative presentation of tables, multiple graph and multidimensional visualization. As a conclusion, the integrated of three types mathematical modeling and the comparison of numerical performance indicates that the superior tool and analysis for solving the complete set of magnetic drug delivery system which give significant effects on the growth of the targeted cancer cell.

Keywords: mathematical modeling, visualization, PDE models, magnetic nanoparticle drug delivery model, drug release model, single cell effects, avascular tumor growth, numerical analysis

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Authors: Isaac Kayode Ogunlade

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Data acquisition (DAQ) is the process by which physical phenomena from the real world are transformed into an electrical signal(s) that are measured and converted into a digital format for processing, analysis, and storage by a computer. The DAQ is designed using PIC18F4550 microcontroller, communicating with Personal Computer (PC) through USB (Universal Serial Bus). The research deployed initial knowledge of data acquisition system and embedded system to develop a weather data acquisition device using LM35 sensor to measure weather parameters and the use of Artificial Intelligence(Artificial Neural Network - ANN)and statistical approach(Autoregressive Integrated Moving Average – ARIMA) to predict precipitation (rainfall). The device is placed by a standard device in the Department of Meteorology, Federal University of Technology, Akure (FUTA) to know the performance evaluation of the device. Both devices (standard and designed) were subjected to 180 days with the same atmospheric condition for data mining (temperature, relative humidity, and pressure). The acquired data is trained in MATLAB R2012b environment using ANN, and ARIMAto predict precipitation (rainfall). Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Correction Square (R2), and Mean Percentage Error (MPE) was deplored as standardize evaluation to know the performance of the models in the prediction of precipitation. The results from the working of the developed device show that the device has an efficiency of 96% and is also compatible with Personal Computer (PC) and laptops. The simulation result for acquired data shows that ANN models precipitation (rainfall) prediction for two months (May and June 2017) revealed a disparity error of 1.59%; while ARIMA is 2.63%, respectively. The device will be useful in research, practical laboratories, and industrial environments.

Keywords: data acquisition system, design device, weather development, predict precipitation and (FUTA) standard device

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Authors: Carol Anne Hargreaves

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A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market.

Keywords: machine learning, stock market trading, logistic regression, cluster analysis, factor analysis, decision trees, neural networks, automated stock investment system

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Authors: Lindie Grebe

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This paper reports on a study that explored the strategizing practices of professional accountants in the mining industry, based on Jarratt and Stiles’ dominant strategizing practice models framework. Drawing on a strategy-as-practice perspective, the paper recognises qualified professional accountants in strategic management such as Chief Executive Officers, as strategy practitioners that perform their strategizing practices and praxis within a specific context. The main findings of this paper were produced through semi-structured individual interviews with accountants that perform strategy on a business level in the South African mining industry. Qualitative data were analysed through conversation analysis over two coding-cycles. Findings describe accountant strategists as practitioners who challenge the dominant business model when a disconnect seems to exist between international corporate level strategy and business level strategy in the South African mining industry. Accountant strategy practitioners described their dominant strategizing practice model as incremental change during strategic planning and as a lived experience during strategy implementation. Findings portrayed these strategists as taking initiative as strategy leaders in a dynamic and volatile environment to combine their accounting background with strategic management and challenge the dominant business model. Understanding how accountant strategists perform strategizing offers insight into the social practice of strategic management. This understanding contributes to the body of knowledge on strategizing in the South African mining industry. In addition, knowledge on the transformation of accountants as strategists could provide valuable practice relevant insights for accounting educators and the accounting profession alike.

Keywords: accountant strategists, dominant strategizing practice models framework, mining industry, strategy-as-practice

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Authors: Anyaphat Srithanasuwan, Noppason Pangprasit, Montira Intanon, Phongsakorn Chuammitri, Witaya Suriyasathaporn, Ynte H. Schukken

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Streptococcus uberis is one of the most common mastitis-causing pathogens, with a wide range of intramammary infection (IMI) durations and pathogenicity. This study aimed to compare shared or unique virulence factor gene clusters distinguishing persistent and transient strains of S. uberis. A total of 139 S. uberis strains were isolated from three small-holder dairy herds with a high prevalence of S. uberis mastitis. The duration of IMI was used to categorize bacteria into two groups: transient and persistent strains with an IMI duration of less than 1 month and longer than 2 months, respectively. Six representative S. uberis strains, three from each group (transience and persistence) were selected for analysis. All transient strains exhibited multi-locus sequence types (MLST), indicating a highly diverse population of transient S. uberis. In contrast, MLST of persistent strains was available in an online database (pubMLST). Identification of virulence genes was performed using whole-genome sequencing (WGS) data. Differences in genomic size and number of virulent genes were found. For example, the BCA gene or alpha-c protein and the gene associated with capsule formation (hasAB), found in persistent strains, are important for attachment and invasion, as well as the evasion of the antimicrobial mechanisms and survival persistence, respectively. These findings suggest a genetic-level difference between the two strain types. Consequently, a comprehensive study of 139 S. uberis isolates will be conducted to perform an in-depth genetic assessment through WGS analysis on an Illumina platform.

Keywords: Streptococcus Uberis, mastitis, whole genome sequence, intramammary infection, persistent S. Uberis, transient s. Uberis

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Authors: Molly Pui Man Wong

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In this study, a blended and interactive e-learning Courseware that our team developed will be introduced, and our team’s experiences on how the e-learning Courseware and the flipped classroom benefit student learning in bioethics in the medical program will be shared. This study is a continuation of the previously established study, which provides a summary of the well-developed e-learning Courseware in a blended learning approach and an update on its efficiency and efficacy. First, a collection of animated videos capturing selected topics of bioethics and related ethical issues and dilemma will be introduced. Next, a selection of problem-based learning videos (“simulated doctor-patient role play”) with pop-up questions and discussions will be further discussed. Our recent findings demonstrated that these activities launched by the Courseware strongly engaged students in bioethics education and enhanced students’ critical thinking and creativity, which were consistent with the previous data in the preliminary studies. Moreover, the educational benefits of the online art exhibition, art jamming, and competition will be discussed, through which students could express bioethics through arts and enrich their learning in medical research in an interactive, fun, and entertaining way, strengthening their interests in bioethics. Furthermore, online survey questionnaires and focus group interviews were conducted. Consistent with the preliminary studies, our results indicated that implementing the e-learning Courseware with a flipped classroom in bioethics education enhanced both active learning and student engagement. In conclusion, our Courseware not only reinforces education in art, bioethics, and medicine but also benefits students in understanding and critical thinking in socio-ethical issues and serves as a valuable learning tool in bioethics teaching and learning.

Keywords: bioethics, courseware, e-learning, flipped classroom

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Authors: Julia Hoefer Martí

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While research has consistently found a significant motherhood wage penalty for heterosexual women, where homosexual women are concerned, evidence has appeared to suggest no effect, or possibly even a wage bonus. This paper presents a model of the household with a public good that requires both a monetary expense and a labour investment, and where the household budget is shared between partners. Lower-wage partners will do relatively more of the household labour while higher-wage partners will specialise in market labour, and the arrival of a child exacerbates this split, resulting in the lower-wage partner taking on even more of the household labour in relative terms. Employers take this gender-sexuality dyad as a signal for employees’ commitment to the labour market after having a child, and use the information when setting wages after employees become parents. Given that women empirically earn lower wages than men, in a heterosexual couple the female partner will often do more of the household labour. However, as not every female partner has a lower wage, this results in an over-adjustment of wages that manifests as an unexplained motherhood wage penalty. On the other hand, in homosexual couples wage distributions are ex ante identical, and gender is no longer a useful signal to employers as to whether the partner is likely to specialise in household labour or market labour. This model is then tested using longitudinal data from the EU Standards of Income and Living Conditions (EU-SILC) to investigate the hypothesis that women experience different wage effects of motherhood depending on their sexual orientation. While heterosexual women receive a significant motherhood wage penalty of 8-10%, homosexual mothers do not receive any significant wage bonus or penalty of motherhood, consistent with the hypothesis presented above.

Keywords: discrimination, gender, motherhood, sexual orientation, labor economics

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Authors: C. Galasso

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The ancestral relationship between humans and geographical environment has long been at the center of an interdisciplinary dialogue, which sees one of its main research nodes in the relationship between memory and places. Given its deep complexity, this symbiotic connection continues to look for a proper definition that appears increasingly negotiated by different disciplines. Numerous fields of knowledge are involved, from anthropology to semiotics of space, from photography to architecture, up to subjects traditionally far from these reasonings. This is the case of Design of Communication, a young discipline, now confident in itself and its objectives, aimed at finding and investigating original forms of visualization and representation, between sedimented knowledge and new technologies. In particular, Design of Communication for the Territory offers an alternative perspective to the debate, encouraging the reactivation and reconstruction of the memory of places. Recognizing mnemotopes as a cultural object of vertical interpretation of the memory-place relationship, design can become a real mediator of the territorial fixation of memories, making them increasingly accessible and perceptible, contributing to build a topography of memory. According to a mnemotopic vision, Communication Design can support the passage from a memory in which the observer participates only as an individual to a collective form of memory. A mnemotopic form of Communication Design can, through geolocation and content map-based systems, make chronology a topography rooted in the territory and practicable; it can be useful to understand how the perception of the memory of places changes over time, considering how to insert them in the contemporary world. Mnemotopes can be materialized in different format of translation, editing and narration and then involved in complex systems of communication. The memory of places, therefore, if stabilized by the tools offered by Communication Design, can make visible ruins and territorial stratifications, illuminating them with new communicative interests that can be shared and participated.

Keywords: memory of places, design of communication, territory, mnemotope, topography of memory

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Authors: D. Songpol, K. Taweesak, T. Sookyuen

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A social enterprise is an organization that operates commercial business as a source of income with the aim of addressing social and environmental issues. Though it is clear that this kind of organization will benefit society and environment but in practice, it is found that most of social enterprises’ goals cannot be achieved. The most success factors of social enterprises usually rely on individual characteristics of entrepreneurs, especially in educational business. This study aims to find out the magnitude of influence from the components of entrepreneur competencies to social enterprises in education. There are developmental models of research demonstrating that knowledge, skills and attributes affect the success of social enterprises in term of sustainability, social opportunities and innovation leadership. The 5-scale questionnaire was used to collect data from the social entrepreneurs in education who operates in the South East Asian region of 135 samples and then processed by the methods of structural equation models. The results show that the competency of entrepreneurs in attributes has the greatest impact on the success of social enterprises while the skills and knowledge have respectively impact on the social enterprises’ success as well. The reason why attributes of entrepreneurs have the greatest impact on social enterprise success is because, social enterprise is an organization that does not motivate or provide attractive financial incentives to the entrepreneur. Entrepreneurs, who succeed in developing their organizations, therefore need attribute factor higher than normal entrepreneurs, especially those in education sector that have somewhat few human resources to operate their businesses. More importantly, attribute’s traits such as entrepreneurial passion, self-efficacy, entrepreneurial identity and, innovativeness and perseverance will significantly affect the ideology and tolerance of the entrepreneurs once facing the problem in doing business. In conclusion, the education social enterprise would be successful depending on the performance of the entrepreneurs which derives from higher attributes competency.

Keywords: education, entrepreneur competencies, social enterprise, South East Asia

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Authors: Parisa Javid

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In architecture, daylight contributes to humans' mental and physical well-being and reduces the consumption of fossil fuels. Accordingly, Iran's rich architecture has valuable achievements and experiences that should be recognized and introduced to the Iranian and international architecture communities. There are many ways to reduce energy consumption in buildings, but electricity accounts for a large part of that consumption. Lighting up spaces with natural light is a significant factor in reducing energy consumption and preventing electricity dissipation. Aside from being expensive, electric lighting systems cause excessive heat and physical injury (eyes). This study is based on library records and documents. Modern lighting systems are used to reduce energy consumption in the interior of a building to allow for optimal transmission of natural light. It discusses how to use natural light in architecture and the benefits of natural light in buildings. Solar energy can be used more efficiently, and electrical power can be saved in residential, administrative, commercial, and educational buildings by using new methods such as light tubes and mirror directors. Modern lighting systems, natural light, and reduced energy consumption are keywords for these systems, which quickly return their investment.

Keywords: modern lighting systems, natural light, reduced energy consumption

Procedia PDF Downloads 100

Authors: Danielle Page

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Foregoing studies, statistics, and medical evaluations have established a relationship between Posttraumatic stress disorder (PTSD) and criminal justice involvement in Vietnam veterans. War is highly trauma inducing and can leave combat veterans with mental disorders ranging from psychopathic thoughts to suicidal ideation. The majority of those suffering are unaware that they have PTSD, and as a coping mechanism, they often turn to self isolation. Beyond isolation, many veterans with symptomatic PTSD turn to aggression and substance abuse to cope with their internal agony. The most common crimes committed by veterans with PTSD fall into the assault and drug/alcohol abuse categories. Thus, a relationship is established between veteran populations and the criminal justice system. This dissertation aims to define the relationship between PTSD and criminal justice involvement in veterans, explore the mediating factors in this relationship, and analyze numerous court cases in this subject area. Further, it will examine the ways in which crime rates can be reduced for veterans with symptoms of PTSD. This ranges from the improvement of healthcare systems to the implementation of special courts to handle veteran cases.

Keywords: psychotraumatology, forensic psychology, PTSD, vietnam veterans

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Authors: Hadda Krarcha, S. Messaasdi

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In order to investigate Hafnium transition metal alloys HfM (M= Co, Ir, Os,Pt, Rh, Ru) phase diagrams in the region of 50/50% atomic ratio, we performed ab initio Full-Potential Linearized Augmented Plane Waves calculations of the enthalpies of formation of HfM compounds at B2 (CsCl) structure type. The obtained enthalpies of formation are discussed and compared to some of the existing models and available experimental data.

Keywords: enthalpy of formation, transition metal, binarry compunds, hafnium

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Authors: Dong Wu, Michael Grenn

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Managing software projects effectively is crucial for meeting deadlines, ensuring quality, and managing resources well. Traditional methods often struggle with predicting project timelines accurately due to uncertain schedules and complex data. This study addresses these challenges by combining time prediction algorithms with Large Language Models (LLMs). It makes use of real-world software project data to construct and validate a model. The model takes detailed project progress data such as task completion dynamic, team Interaction and development metrics as its input and outputs predictions of project timelines. To evaluate the effectiveness of this model, a comprehensive methodology is employed, involving simulations and practical applications in a variety of real-world software project scenarios. This multifaceted evaluation strategy is designed to validate the model's significant role in enhancing forecast accuracy and elevating overall management efficiency, particularly in complex software project environments. The results indicate that the integration of time prediction algorithms with LLMs has the potential to optimize software project progress management. These quantitative results suggest the effectiveness of the method in practical applications. In conclusion, this study demonstrates that integrating time prediction algorithms with LLMs can significantly improve the predictive accuracy and efficiency of software project management. This offers an advanced project management tool for the industry, with the potential to improve operational efficiency, optimize resource allocation, and ensure timely project completion.

Keywords: software project management, time prediction algorithms, large language models (LLMS), forecast accuracy, project progress prediction

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Authors: Luo Jin China, Jin Fang

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Countryside has been generally recognized and regarded as a characteristic symbol which presents in human memory for a long time. As a result of the change of times, because of it’s failure to meet the growing needs of the growing life and mental decline, the vast rural area began to decline. But their history feature image which accumulated by the ancient tradition provides people with the origins of existence on the spiritual level, such as "identity" and "belonging", makes people closer to the others in the spiritual and psychological aspects of a common experience about the past, thus the sense of a lack of culture caused by the losing of memory symbols is weakened. So, in the modernization process, how to repair its vitality and transform and planning it in a sustainable way has become a hot topics in architectural and urban planning. This paper aims to break the constraints of disciplines, from the perspective of interdiscipline, using the research methods of systems science to analyze and discuss the theories and methods of rural form factors, which based on the viewpoint of memory in psychology. So, we can find a right way to transform the Rural to give full play to the role of the countryside in the actual use and the shape of history spirits.

Keywords: rural, sustainable renovation, restoration, psychology, memory

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Authors: Gabriel Wainer

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Modeling and Simulation methods have been used to better analyze the behavior of complex physical systems, and it is now common to use simulation as a part of the scientific and technological discovery process. M&S advanced thanks to the improvements in computer technology, which, in many cases, resulted in the development of simulation software using ad-hoc techniques. Formal M&S appeared in order to try to improve the development task of very complex simulation systems. Some of these techniques proved to be successful in providing a sound base for the development of discrete-event simulation models, improving the ease of model definition and enhancing the application development tasks; reducing costs and favoring reuse. The DEVS formalism is one of these techniques, which proved to be successful in providing means for modeling while reducing development complexity and costs. DEVS model development is based on a sound theoretical framework. The independence of M&S tasks made possible to run DEVS models on different environments (personal computers, parallel computers, real-time equipment, and distributed simulators) and middleware. We will present a historical perspective of discrete-event M&S methodologies, showing different modeling techniques. We will introduce DEVS origins and general ideas, and compare it with some of these techniques. We will then show the current status of DEVS M&S, and we will discuss a technological perspective to solve current M&S problems (including real-time simulation, interoperability, and model-centered development techniques). We will show some examples of the current use of DEVS, including applications in different fields. We will finally show current open topics in the area, which include advanced methods for centralized, parallel or distributed simulation, the need for real-time modeling techniques, and our view in these fields.

Keywords: modeling and simulation, discrete-event simulation, hybrid systems modeling, parallel and distributed simulation

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Authors: Jantakan Jullawateelert, Korakod Haonoo, Sutipong Sananseang, Sarun Torpaiboon, Thanunthon Bowornsakulwong, Lalintip Hocharoen

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Process scale-up is essential for the biological process to increase production capacity from bench-scale bioreactors to either pilot or commercial production. Scale-up based on constant volumetric oxygen mass transfer coefficient (KLa) is mostly used as a scale-up factor since oxygen supply is one of the key limiting factors for cell growth. However, to estimate KLa of culture vessels operated with different conditions are time-consuming since it is considerably influenced by a lot of factors. To overcome the issue, this study aimed to establish correlation equations of KLa and operating parameters in 0.5 L and 5 L bioreactor employed with pitched-blade impeller and gas sparger. Temperature, gas flow rate, agitation speed, and impeller position were selected as process parameters and equations were created using response surface methodology (RSM) based on central composite design (CCD). In addition, the effects of these parameters on KLa were also investigated. Based on RSM, second-order polynomial models for 0.5 L and 5 L bioreactor were obtained with an acceptable determination coefficient (R²) as 0.9736 and 0.9190, respectively. These models were validated, and experimental values showed differences less than 10% from the predicted values. Moreover, RSM revealed that gas flow rate is the most significant parameter while temperature and agitation speed were also found to greatly affect the KLa in both bioreactors. Nevertheless, impeller position was shown to influence KLa in only 5L system. To sum up, these modeled correlations can be used to accurately predict KLa within the specified range of process parameters of two different sizes of bioreactors for further scale-up application.

Keywords: response surface methodology, scale-up, stirred-tank bioreactor, volumetric oxygen mass transfer coefficient

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Authors: Ana Julia Acevedo Urquiaga, Jose A. Acevedo Suarez, Ana Julia Urquiaga Rodriguez, Neyfe Sablon Cossio

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Despite the progress made in logistics and supply chains fields, it is unavoidable the development of business models that use efficiently information to facilitate the integrated logistics flows management between partners. Collaborative management is an important tool for materializing the cooperation between companies, as a way to achieve the supply chain efficiency and effectiveness. The first face of this research was a comprehensive analysis of the collaborative planning on the Cuban companies. It is evident that they have difficulties in supply chains planning where production, supplies and replenishment planning are independent tasks, as well as logistics and distribution operations. Large inventories generate serious financial and organizational problems for entities, demanding increasing levels of working capital that cannot be financed. Problems were found in the efficient application of Information and Communication Technology on business management. The general objective of this work is to develop a methodology that allows the deployment of a planning and control system in a coordinated way on the medicine’s logistics system in Cuba. To achieve these objectives, several mechanisms of supply chain coordination, mathematical programming models, and other management techniques were analyzed to meet the requirements of collaborative logistics management in Cuba. One of the findings is the practical and theoretical inadequacies of the studied models to solve the current situation of the Cuban logistics systems management. To contribute to the tactical-operative management of logistics, the Collaborative Logistics Flow Management Model (CLFMM) is proposed as a tool for the balance of cycles, capacities, and inventories, always to meet the final customers’ demands in correspondence with the service level expected by these. The CLFMM has as center the supply chain planning and control system as a unique information system, which acts on the processes network. The development of the model is based on the empirical methods of analysis-synthesis and the study cases. Other finding is the demonstration of the use of a single information system to support the supply chain logistics management, allows determining the deadlines and quantities required in each process. This ensures that medications are always available to patients and there are no faults that put the population's health at risk. The simulation of planning and control with the CLFMM in medicines such as dipyrone and chlordiazepoxide, during 5 months of 2017, permitted to take measures to adjust the logistic flow, eliminate delayed processes and avoid shortages of the medicines studied. As a result, the logistics cycle efficiency can be increased to 91%, the inventory rotation would increase, and this results in a release of financial resources.

Keywords: collaborative management, medicine logistic system, supply chain planning, tactical-operative planning

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Authors: M. A. Brown, K. Hugill, D. Meredith

Abstract:

Since the establishment of midwifery, as a professional identity in its own right, in the early years of the 20th century, midwifery-led models of childbirth have prevailed in many parts of the world. However, in many locations midwives’ scope of practice remains underdeveloped or absent. In Qatar, all births take place in hospital and are under the professional jurisdiction of obstetricians, predominately supported by internationally trained nurse-midwives and obstetric nurses. The strategic vision for health services in Qatar endorsed a desire to provide women with the ‘Best Care Always’ and the introduction of midwifery was seen as a way to achieve this. In 2015 the process of recruiting postgraduate educated Clinical Midwife Specialists from international sources began. The midwives were brought together to initiate an in hospital and community service transformation plan. This plan set out a series of wide-ranging actions to transform maternity and neonatal services to make care safer and give women more health choices. Change in any organization is a complex and dynamic process. This is made even more complex when multifaceted professional and cross cultural factors are involved. This presentation reports upon the motivations and challenges that exist and the progress around introducing a multicultural midwifery model of childbirth care in the state of Qatar. The paper examines and reflects upon the drivers and unique features of childbirth in the country. Despite accomplishments, progress still needs to be made in order to fully implement sustainable changes to further improve care and ensure women and neonates get the ‘Best Care Always’. The progress within the transformation plan highlights how midwifery may coexist with competing models of maternity care to create an innovative, eclectic and culturally sensitive paradigm that can best serve women and neonatal health needs.

Keywords: culture, managing change, midwifery, neonatal, service transformation plan

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Authors: Syed Toqueer, Omer Younus

Abstract:

Terrorism, today, has emerged as a global menace with Pakistan being the most adversely affected state. Therefore, the motive behind this study is to empirically establish the linkage of terrorism with socio-economic (uneven income distribution, poverty and unemployment) and political nexuses so that a policy recommendation can be put forth to better approach this issue in Pakistan. For this purpose, the study employs two competing models, namely, the distributed lag model and OLS, so that findings of the model may be consolidated comprehensively, over the reference period of 1984-2012. The findings of both models are indicative of the fact that uneven income distribution of Pakistan is rather a contributing factor towards terrorism when measured through GDP per capita. This supports the hypothesis that immiserizing modernization theory is applicable for the state of Pakistan where the underprivileged are marginalized. Results also suggest that other socio-economic variables (poverty, unemployment and consumer confidence) can condense the brutality of terrorism once these conditions are catered to and improved. The rational of opportunity cost is at the base of this argument. Poor conditions of employment and poverty reduces the opportunity cost for individuals to be recruited by terrorist organizations as economic returns are considerably low and thus increasing the supply of volunteers and subsequently increasing the intensity of terrorism. The argument of political freedom as a means of lowering terrorism stands true. The more the people are politically repressed the more alternative and illegal means they will find to make their voice heard. Also, the argument that politically transitioning economy faces more terrorism is found applicable for Pakistan. Finally, the study contributes to an ongoing debate on which of the two set of factors are more significant with relation to terrorism by suggesting that socio-economic factors are found to be the primary causes of terrorism for Pakistan.

Keywords: terrorism, socioeconomic conditions, political freedom, distributed lag model, ordinary least square

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Authors: Kamel Malik Bensafta, Gervasio Semedo

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The purpose of this paper is to investigate the relationship between oil prices and socks markets. The empirical analysis in this paper is conducted within the context of Multivariate GARCH models, using a transform version of the so-called BEKK parameterization. We show that mean and uncertainty of US market are transmitted to oil market and European market. We also identify an important transmission from WTI prices to Brent Prices.

Keywords: oil volatility, stock markets, MGARCH, transmission, structural break

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Authors: Kehabtimer Shiferaw Kotiso, Getachew Hailemariam, Abiy Seifu Estifanos

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Introduction: Despite the highest share of low birth weight (LBW) for neonatal mortality and morbidity, predicting births with LBW for better intervention preparation is challenging. This study aims to predict LBW using a dataset encompassing 53,637 birth cohorts collected from 36 primary hospitals across seven regions in Ethiopia from February 2022 to June 2024. Methods: We identified ten explanatory variables related to maternal and neonatal characteristics, including maternal education, age, residence, history of miscarriage or abortion, history of preterm birth, type of pregnancy, number of livebirths, number of stillbirths, antenatal care frequency, and sex of the fetus to predict LBW. Using WEKA 3.8.2, we developed and compared seven machine learning algorithms. Data preprocessing included handling missing values, outlier detection, and ensuring data integrity in birth weight records. Model performance was evaluated through metrics such as accuracy, precision, recall, F1-score, and area under the Receiver Operating Characteristic curve (ROC AUC) using 10-fold cross-validation. Results: The results demonstrated that the decision tree, J48, logistic regression, and gradient boosted trees model achieved the highest accuracy (94.5% to 94.6%) with a precision of 93.1% to 93.3%, F1-score of 92.7% to 93.1%, and ROC AUC of 71.8% to 76.6%. Conclusion: This study demonstrates the effectiveness of machine learning models in predicting LBW. The high accuracy and recall rates achieved indicate that these models can serve as valuable tools for healthcare policymakers and providers in identifying at-risk newborns and implementing timely interventions to achieve the sustainable developmental goal (SDG) related to neonatal mortality.

Keywords: low birth weight, machine learning, classification, neonatal mortality, Ethiopia

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Authors: Melasurej C. Francisco, Sophia D. Rusit

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Old age is a record of one’s own life; this is the crucial phase for most. However, there are individuals who believe that old people retain self-efficacy and self-worth throughout their existence. Geriatric institutions focus on the health of elderly, in which they have been supported with medicines and therapies by clinician thus, indicating that these may suffice physical, emotional, and mental health of the elderly. This study focuses on (1) Describing the level or degree of self-efficacy; (2) Recognizing the extent of self-worth; (3) Determining the significant relationship between self-efficacy and self-worth. It is a mixed method design. A combination of correlational research and in-depth interview. Purposive sampling technique was used to select participants, considering that this assay focused on elderly in geriatric institutions, it follows that respondents and participants are at least sixty years of age and must be living inside the institution. 121 senior citizens took part in this study. Scores from both General Self-Efficacy Scale (GSE) and Rosenberg Self-Esteem Scale (RSES) showed varying levels of self-efficacy and self-worth. SE had μ=28.099, σ=6.6262, σ²=43.9067 while; SW had μ=14.9669, σ=5.3789, σ²28.9322 which denotes that rₒbₜ (121)=0.3164 is higher than rcᵢₜ which is 0.150. Although this exhibits the positive moderate correlation between SE and SW, the relationship between variables is weak. Likewise, the pᵥₐₗᵤₑ (pᵥₐₗᵤₑ=0.000406) is lower than the significance level alpha=0.01, thus, rejecting the null hypothesis, and accepting the alternative hypothesis.

Keywords: elderly, geriatric, self-efficacy, self-worth

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Authors: Shweta Jha, Nandita Chaube

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The concept of self has a major role to play in the study of personality which drives the current study in its present form. This is a case of Miss S, a 17-year-old Hindu, currently in eleventh standard, with no family history of mental illness but with a past history of inability to manage relationships, multiple emotional and sexual relationships, repeated self harming behaviour, and sexual abuse over a period of 2 months at the age of 10 years. She comes with a psychiatric history of one episode of dissociative fall followed by a stressful event which left the patient with many psychological disturbances matching the criterion of Cluster B and C traits. Current episode precipitated due to the relationship failure, predisposing factor is her personality traits, and poor social and family support. Considering the patient’s aspiration for positivity and demand of the therapy, ventilation sessions were carried out which made her capable of understanding and dealing with her negative emotions, also strengthened mother child bond, helped her maintain meaningful and healthy relationships, also helped her increase her problem solving ability and adaptive coping skills making her feel more positive and acceptable towards herself, family members and others.

Keywords: cluster B and C traits, personality, therapy, self

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Authors: Jessie Fazel, Kristen Smith

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Human trafficking is a multi-billion-dollar criminal industry that affects 24.9 million people around the world. There are several different types of trafficking, the most common being sex trafficking, labor trafficking, and domestic servitude. Survival sex is common in the pediatric population, as they engage in sex for food, a place to sleep, or other basic needs. Statistics show that health care workers are at a unique advantage to help identify victims and get them the help they need, as 88% of trafficked victims encounter a health care worker while being trafficked. Unfortunately, victims don’t usually self-identify that they are being trafficked and the situations they face can vary dramatically. It is imperative to remember that traditional red flags are not always present in the pediatric population. Risk factors and red flags with their history and physical exam are one of the best indicators that health care providers need to be vigilant in looking at. There are numerous barriers for disclosure in the healthcare setting. Periods of time before and after disclosure are often emotionally difficult and could be dangerous for the victim. It is extremely important to have a plan in place for intervention if the victim does disclose trafficking. A trauma informed approach to medical and mental health interventions, that focus on safety, are vital in this population. This is happening where you live and you can make a difference in their lives.

Keywords: human trafficking, public health, emergency medicine, sexual health

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Authors: Amos King'ori Githu

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Water safety is crucial for all ages, but particularly for children. In the past decade, preschool institutions in Sub-Saharan Africa have seen the inclusion of swimming as one of the co-curricular activities. However, these countries face challenges in adopting frameworks, staffing, and resources to heighten water safety, quality, and drowning prevention, hence the focus of this research. It is worth noting that drowning is a leading cause of injury-related deaths among children. Universally, the highest drowning rates occur among children aged 1-4 years and 5-9 years. Preschool children even stand a higher risk of drowning as they are active, eager, and curious to explore their environment. If not supervised closely around or in water, these children can drown quickly in just a few inches of water. Thus, this empirical review focuses on the identification, assessment, and analysis of water safety efforts to curb drowning among children and assess the quality of water to mitigate contamination that may eventually pose infection risks to the children. In addition, it outlines the use of behavioral theories and evaluation frameworks to guide the above. Notably, a search on ten databases was adopted for crucial peer-reviewed articles, and five were selected in the eventual review. This research relied extensively on secondary data to curb water infections and drowning-inflicted deaths among children. It suffices to say that interventions must be supported that adopt an array of strategies, are guided by planning and theory as well as evaluation frameworks, and are vast in intervention design, evaluation, and delivery methodology. Finally, this approach will offer solid evidence that can be shared to guide future practices and policies in preschools on child safety and drowning prevention.

Keywords: water quality and safety, drowning prevention, preschool children, sub-saharan Africa, supervision

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Authors: L. Melzerová, T. Janda, M. Šejnoha, J. Šejnoha

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Two finite element (FEM) models are presented in this paper to address the random nature of the response of glued timber structures made of wood segments with variable elastic moduli evaluated from 3600 indentation measurements. This total database served to create the same number of ensembles as was the number of segments in the tested beam. Statistics of these ensembles were then assigned to given segments of beams and the Latin Hypercube Sampling (LHS) method was called to perform 100 simulations resulting into the ensemble of 100 deflections subjected to statistical evaluation. Here, a detailed geometrical arrangement of individual segments in the laminated beam was considered in the construction of two-dimensional FEM model subjected to in four-point bending to comply with the laboratory tests. Since laboratory measurements of local elastic moduli may in general suffer from a significant experimental error, it appears advantageous to exploit the full scale measurements of timber beams, i.e. deflections, to improve their prior distributions with the help of the Bayesian statistical method. This, however, requires an efficient computational model when simulating the laboratory tests numerically. To this end, a simplified model based on Mindlin’s beam theory was established. The improved posterior distributions show that the most significant change of the Young’s modulus distribution takes place in laminae in the most strained zones, i.e. in the top and bottom layers within the beam center region. Posterior distributions of moduli of elasticity were subsequently utilized in the 2D FEM model and compared with the original simulations.

Keywords: Bayesian inference, FEM, four point bending test, laminated timber, parameter estimation, prior and posterior distribution, Young’s modulus

Procedia PDF Downloads 283