Search results for: automated external defibrillator
395 The Role of the Child's Previous Inventory in Verb Overgeneralization in Spanish Child Language: A Case Study
Authors: Mary Rosa Espinosa-Ochoa
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The study of overgeneralization in inflectional morphology provides evidence for understanding how a child's mind works when applying linguistic patterns in a novel way. High-frequency inflectional forms in the input cause inappropriate use in contexts related to lower-frequency forms. Children learn verbs as lexical items and new forms develop only gradually, around their second year: most of the utterances that children produce are closely related to what they have previously produced. Spanish has a complex verbal system that inflects for person, mood, and tense. Approximately 200 verbs are irregular, and bare roots always require an inflected form, which represents a challenge for the memory. The aim of this research is to investigate i) what kinds of overgeneralization errors children make in verb production, ii) to what extent these errors are related to verb forms previously produced, and iii) whether the overgeneralized verb components are also frequent in children’s linguistic inventory. It consists of a high-density longitudinal study of a middle-class girl (1;11,24-2;02,24) from Mexico City, whose utterances were recorded almost daily for three months to compile a unique corpus in the Spanish language. Of the 358 types of inflected verbs produced by the child, 9.11% are overgeneralizations. Not only are inflected forms (verbal and pronominal clitics) overgeneralized, but also verbal roots. Each of the forms can be traced to previous utterances, and they show that the child is detecting morphological patterns. Neither verbal roots nor inflected forms are associated with high frequency patterns in her own speech. For example, the child alternates the bare roots of an irregular verb, cáye-te* and cáiga-te* (“fall down”), to express the imperative of the verb cá-e-te (fall down.IMPERATIVE-PRONOMINAL.CLITIC), although cay-ó (PAST.PERF.3SG) is the most frequent form of her previous complete inventory, and the combined frequency of caer (INF), cae (PRES.INDICATIVE.3SG), and caes (PRES.INDICATIVE.2SG) is the same as that of as caiga (PRES.SUBJ.1SG and 3SG). These results provide evidence that a) two forms of the same verb compete in the child’s memory, and b) although the child uses her own inventory to create new forms, these forms are not necessarily frequent in her memory storage, which means that her mind is more sensitive to external stimuli. Language acquisition is a developing process, given the sensitivity of the human mind to linguistic interaction with the outside world.Keywords: inflection, morphology, child language acquisition, Spanish
Procedia PDF Downloads 101394 Tiebout and Crime: How Crime Affect the Income Tax Capacity
Authors: Nik Smits, Stijn Goeminne
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Despite the extensive literature on the relation between crime and migration, not much is known about how crime affects the tax capacity of local communities. This paper empirically investigates whether the Flemish local income tax base yield is sensitive to changes in the local crime level. The underlying assumptions are threefold. In a Tiebout world, rational voters holding the local government accountable for the safety of its citizens, move out when the local level of security gets too much alienated from what they want it to be (first assumption). If migration is due to crime, then the more wealthy citizens are expected to move first (second assumption). Looking for a place elsewhere implies transaction costs, which the more wealthy citizens are more likely to be able to pay. As a consequence, the average income per capita and so the income distribution will be affected, which in turn, will influence the local income tax base yield (third assumption). The decreasing average income per capita, if not compensated by increasing earnings by the citizens that are staying or by the new citizens entering the locality, must result in a decreasing local income tax base yield. In the absence of a higher level governments’ compensation, decreasing local tax revenues could prove to be disastrous for a crime-ridden municipality. When communities do not succeed in forcing back the number of offences, this can be the onset of a cumulative process of urban deterioration. A spatial panel data model containing several proxies for the local level of crime in 306 Flemish municipalities covering the period 2000-2014 is used to test the relation between crime and the local income tax base yield. In addition to this direct relation, the underlying assumptions are investigated as well. Preliminary results show a modest, but positive relation between local violent crime rates and the efflux of citizens, persistent up until a 2 year lag. This positive effect is dampened by possible increasing crime rates in neighboring municipalities. The change in violent crimes -and to a lesser extent- thefts and extortions reduce the influx of citizens with a one year lag. Again this effect is diminished by external effects from neighboring municipalities, meaning that increasing crime rates in neighboring municipalities (especially violent crimes) have a positive effect on the local influx of citizens. Crime also has a depressing effect on the average income per capita within a municipality, whereas increasing crime rates in neighboring municipalities increase it. Notwithstanding the previous results, crime does not seem to significantly affect the local tax base yield. The results suggest that the depressing effect of crime on the income basis has to be compensated by a limited, but a wealthier influx of new citizens.Keywords: crime, local taxes, migration, Tiebout mobility
Procedia PDF Downloads 307393 Predicting Costs in Construction Projects with Machine Learning: A Detailed Study Based on Activity-Level Data
Authors: Soheila Sadeghi
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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.Keywords: cost prediction, machine learning, project management, random forest, neural networks
Procedia PDF Downloads 54392 Hydrological Benefits Sharing Concepts in Constructing Friendship Dams on Transboundary Tigris River Between Iraq and Turkey
Authors: Thair Mahmood Altaiee
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Because of the increasing population and the growing water requirements from the transboundary water resources within riparian countries in addition to un-proper management of these transboundary water resources, it is likely that a conflicts on the water will be occurred. So it is mandatory to search solutions to mitigate the action and probabilities of these undesired conflicts. One of the solutions for these crises may be sharing the riparian countries in the management of their transboundary water resources and share benefit. Effective cooperation on a transboundary river is any action by the riparian countries that lead to improve management of the river to their mutual acceptance. In principle, friendship dams constructed by riparian countries may play an important role in preventing conflicts like the Turkish-Syrian friendship dam on Asi river (Orontes), Iranian-Tukmenistan dam on Hariroud river, Bulgarian-Turkish dam on Tundzha river, Brazil-Paraguay dam on Parana river, and Aras dam between Iran and Azerbaijan. The objective of this study is to focus the light on the hydrological aspects of cooperation in constructing dams on the transboundary rivers, which may consider an option to prevent conflicts on water between the riparian countries. The various kinds of benefits and external impacts associated with cooperation in dams construction on the transboundary rivers with a real examples will be presented and analyzed. The hydrological benefit sharing from cooperation in dams construction, which type of benefit sharing mechanisms are applicable to dams, and how they vary were discussed. The study considered the cooperative applicability to dams on shared rivers according to selected case study of friendship dams in the world to illustrate the relevance of the cooperation concepts and the feasibility of such propose cooperation between Turkey and Iraq within the Tigris river. It is found that the opportunities of getting benefit from cooperation depend mainly on the hydrological boundary and location of the dam in relation to them. The desire to cooperate on dams construction on transboundary rivers exists if the location of a dam upstream will increase aggregate net benefits. The case studies show that various benefit sharing mechanisms due to cooperation in constructing friendship dams on the riparian countries border are possible for example when the downstream state (Iraq) convinces the upstream state (Turkey) to share building a dam on Tigris river across the Iraqi –Turkish border covering the cost and sharing the net benefit derived from this dam. These initial findings may provide guidance for riparian states engaged in and donors facilitating negotiation on dam projects on transboundary rivers.Keywords: friendship dams, transboundary rivers, water cooperation, benefit sharing
Procedia PDF Downloads 141391 Temperature Dependent Magneto-Transport Properties of MnAl Binary Alloy Thin Films
Authors: Vineet Barwal, Sajid Husain, Nanhe Kumar Gupta, Soumyarup Hait, Sujeet Chaudhary
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High perpendicular magnetic anisotropy (PMA) and low damping constant (α) in ferromagnets are one of the few necessary requirements for their potential applications in the field of spintronics. In this regards, ferromagnetic τ-phase of MnAl possesses the highest PMA (Ku > 107 erg/cc) at room temperature, high saturation magnetization (Ms~800 emu/cc) and a Curie temperature of ~395K. In this work, we have investigated the magnetotransport behaviour of this potentially useful binary system MnₓAl₁₋ₓ films were synthesized by co-sputtering (pulsed DC magnetron sputtering) on Si/SiO₂ (where SiO₂ is native oxide layer) substrate using 99.99% pure Mn and Al sputtering targets. Films of constant thickness (~25 nm) were deposited at the different growth temperature (Tₛ) viz. 30, 300, 400, 500, and 600 ºC with a deposition rate of ~5 nm/min. Prior to deposition, the chamber was pumped down to a base pressure of 2×10⁻⁷ Torr. During sputtering, the chamber was maintained at a pressure of 3.5×10⁻³ Torr with the 55 sccm Ar flow rate. Films were not capped for the purpose of electronic transport measurement, which leaves a possibility of metal oxide formation on the surface of MnAl (both Mn and Al have an affinity towards oxide formation). In-plane and out-of-plane transverse magnetoresistance (MR) measurements on films sputtered under optimized growth conditions revealed non-saturating behavior with MR values ~6% and 40% at 9T, respectively at 275 K. Resistivity shows a parabolic dependence on the field H, when the H is weak. At higher H, non-saturating positive MR that increases exponentially with the strength of magnetic field is observed, a typical character of hopping type conduction mechanism. An anomalous decrease in MR is observed on lowering the temperature. From the temperature dependence of reistivity, it is inferred that the two competing states are metallic and semiconducting, respectively and the energy scale of the phenomenon produces the most interesting effects, i.e., the metal-insulator transition and hence the maximum sensitivity to external fields, at room temperature. Theory of disordered 3D systems effectively explains the crossover temperature coefficient of resistivity from positive to negative with lowering of temperature. These preliminary findings on the MR behavior of MnAl thin films will be presented in detail. The anomalous large MR in mixed phase MnAl system is evidently useful for future spintronic applications.Keywords: magnetoresistance, perpendicular magnetic anisotropy, spintronics, thin films
Procedia PDF Downloads 124390 The Role of an Independent Children’s Lawyer in Child Inclusive Mediation in Complex Parenting Disputes
Authors: Neisha Shepherd
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In Australia, an independent children's lawyer is appointed to represent a child in parenting disputes in the Federal Circuit and Family Court of Australia, where there are complex issues such as child protection, family violence, high conflict, relocation, and parental alienation. The appointment of an Independent Children's Lawyer is to give effect in the family law proceedings of the United Nations Convention on the Rights of the Child, in particular Article 3.1, 12.1, and 12.2. There is a strong focus on alternative dispute resolution in the Australian Family Law jurisdiction in matters that are before the Court that has formed part of the case management pathways. An Independent Children's Lawyer's role is even more crucial in assisting families in resolving the most complex parenting disputes through mediation as they are required to act impartial and be independent of the Court and the parties. A child has the right to establish a professional relationship with the Independent Children's Lawyer. This relationship is usually established over a period of time, and the child is afforded the opportunity to talk about their views and wishes and participate in decisions that affect them. In considering the views and wishes of the child, the Independent Children's lawyer takes into account the different emotional, cognitive, and intellectual developmental levels, family structures, family dynamics, sibling relationships, religious and cultural backgrounds; and that children are vulnerable to external pressures when caught in disputes involving their parents. With the increase of child-inclusive mediations being used to resolve family disputes in the best interests of a child, an Independent Children's Lawyer can have a critical role in this process with the specialised skills that they have working with children in the family law jurisdiction. This paper will discuss how inclusive child mediation with the assistance of an Independent Children's Lawyer can assist in the resolution of some of the most complex parenting disputes by examining through case studies: the effectiveness and challenges of such an approach; strategies to work with child clients, adolescents, and sibling groups; ways to provide feedback regarding a child's views and wishes and express a child's understanding, actual experiences and perspective to parties in a mediation and whether it is appropriate to do so; strategies and examples to assist in developing parenting plans or orders that are in the best interest of a child that is workable and achievable; how to deal with cases that involve serious child protection and family violence and strategies to ensure that child safety is paramount; the importance of feedback to the child client. Finally this paper will explore some of the challenges for Independent Children's Lawyers in relation to child-inclusive mediations where matters do not resolve.Keywords: child inclusive mediation, independent children's lawyer, family violence, child protection
Procedia PDF Downloads 122389 A Machine Learning Approach for Efficient Resource Management in Construction Projects
Authors: Soheila Sadeghi
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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management
Procedia PDF Downloads 38388 Human Insecurity and Migration in the Horn of Africa: Causes and Decision Processes
Authors: Belachew Gebrewold
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The Horn of Africa is marred by complex and systematic internal and external political, economic and social-cultural causes of conflict that result in internal displacement and migration. This paper engages with them and shows how such a study can help us to understand migration, both in this region and more generally. The conflict has occurred within states, between states, among proxies, between armies. Human insecurities as a result of the state collapse of Somalia, the rise of Islamic fundamentalism in the whole region, recurrent drought affecting the livelihoods of subsistence farmers as well as nomads, exposure to hunger, environmental degradation, youth unemployment, rapid growth of slums around big cities, and political repression (especially in Eritrea) have been driving various segments of the regional population into regional and international migration. Eritrea has been going through a brutal dictatorship which pushes many Eritreans to flee their country and be exposed to human trafficking, torture, detention, and agony on their way to Europe mainly through Egypt, Libya and Israel. Similarly, Somalia has been devastated since 1991 by unending civil war, state collapse, and radical Islamists. There are some important aspects to highlight in the conflict-migration nexus in the Horn of Africa: first, the main push factor for the Somalis and Eritreans to leave their countries and risk their lives is the physical insecurity they have been facing in their countries. Secondly, as a result of the conflict the economic infrastructure is massively destroyed. Investment is rare; job opportunities are out of sight. Thirdly, in such a grim situation the politically and economically induced decision to migrate is a household decision, not only an individual decision. Based on this third point this research study took place in the Horn of Africa between 2014 and 2016 during different occasions. The main objective of the research was to understanding how the increasing migration is affecting the socio-economic and socio-political environment, and conversely how the socio-economic and socio-political environments are increasing migration decisions; and whether and how these decisions are individual or family decisions. The main finding is the higher the human insecurity, the higher the family decision; the lower the human insecurity, the higher the individual decision. These findings apply not only to the Eritrean, Somali migrants but also to Ethiopian migrants. But the general impacts of migration on sending countries’ human security is quite mixed and complex.Keywords: Eritrea, Ethiopia, Horn of Africa, insecurity, migration, Somalia
Procedia PDF Downloads 277387 Efficient Estimation of Maximum Theoretical Productivity from Batch Cultures via Dynamic Optimization of Flux Balance Models
Authors: Peter C. St. John, Michael F. Crowley, Yannick J. Bomble
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Production of chemicals from engineered organisms in a batch culture typically involves a trade-off between productivity, yield, and titer. However, strategies for strain design typically involve designing mutations to achieve the highest yield possible while maintaining growth viability. Such approaches tend to follow the principle of designing static networks with minimum metabolic functionality to achieve desired yields. While these methods are computationally tractable, optimum productivity is likely achieved by a dynamic strategy, in which intracellular fluxes change their distribution over time. One can use multi-stage fermentations to increase either productivity or yield. Such strategies would range from simple manipulations (aerobic growth phase, anaerobic production phase), to more complex genetic toggle switches. Additionally, some computational methods can also be developed to aid in optimizing two-stage fermentation systems. One can assume an initial control strategy (i.e., a single reaction target) in maximizing productivity - but it is unclear how close this productivity would come to a global optimum. The calculation of maximum theoretical yield in metabolic engineering can help guide strain and pathway selection for static strain design efforts. Here, we present a method for the calculation of a maximum theoretical productivity of a batch culture system. This method follows the traditional assumptions of dynamic flux balance analysis: that internal metabolite fluxes are governed by a pseudo-steady state and external metabolite fluxes are represented by dynamic system including Michealis-Menten or hill-type regulation. The productivity optimization is achieved via dynamic programming, and accounts explicitly for an arbitrary number of fermentation stages and flux variable changes. We have applied our method to succinate production in two common microbial hosts: E. coli and A. succinogenes. The method can be further extended to calculate the complete productivity versus yield Pareto surface. Our results demonstrate that nearly optimal yields and productivities can indeed be achieved with only two discrete flux stages.Keywords: A. succinogenes, E. coli, metabolic engineering, metabolite fluxes, multi-stage fermentations, succinate
Procedia PDF Downloads 215386 The Psychological Effects of Nature on Subjective Well-Being: An Experimental Approach
Authors: Tatjana Kochetkova
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This paper explores the pivotal role of environmental education, specifically outdoor education, in facilitating a psychological connection to nature among young adults. This research aims to contribute to building an empirical and conceptual basis of ecopsychology by providing a picture of psyche-nature interaction. It presents the results of the four-day connection-to-nature workshop. It intends to find out the effects of the awareness of nature on subjective well-being and perception of the meaning of life. This led to finding a battery-recharging effect of nature and the influence of nature at four levels of awareness: external physical perception, internal (bodily) sensation, emotions, and existential meaning. The research on the psychological bond of humans with the natural environment, the subject of ecopsychology, is still in its infancy. However, despite several courageous and fruitful attempts, there are still no direct answers to the fundamental questions about the way in which the natural environment influences humans and the specific role of nature in the human psyche. The urge to address this question was the primary reason for the current experiment. The methodology of this study was taken from the study of Patterson, and from White and Hendee. The methodology included a series of assignments on the perception of nature (the exercises are described in the attachment). Experiences were noted in a personal diary, which we used later for analysis. There are many trustworthy claims that contact with nature has positive effects on human subjective well-being and that it is of essential psychological and spiritual value. But, there is a need for more support and theoretical explanation for this phenomenon. As a contribution to filling these gaps, this qualitative study was conducted. The aim of this study is to explore the psychological effects of short-term awareness of wilderness on one’s subjective well-being and on one’s sense of the meaning of life. This specific study is based on the more general hypothesis that there are positive relationships between the experience of wilderness and the development of the self, feelings of community, and spiritual development. It restricted the study of the psychological effects of short term stay in nature to two variables (subjective well-being and the sense of meaning of life). The study aimed at (i) testing the hypothesis that there are positive effects of the awareness of wilderness on the subjective sense of well-being and meaning in life, (ii) understanding the nature of the psychological need for wilderness. Although there is a substantial amount of data on the psychological benefits of nature, we still lack a theory that explains the findings. The present research aims to contribute to such a theory. This is an experiment aimed specifically at the effects of nature on the sense of well-being and meaning in life.Keywords: environmental education, psychological connection to nature, subjective well-being, symbolic meaning of nature, emotional reaction to nature, meaning of life
Procedia PDF Downloads 72385 Use of Machine Learning Algorithms to Pediatric MR Images for Tumor Classification
Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos
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Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology
Procedia PDF Downloads 149384 Feminising Football and Its Fandom: The Ideological Construction of Women's Super League
Authors: Donna Woodhouse, Beth Fielding-Lloyd, Ruth Sequerra
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This paper explores the structure and culture of the English Football Association (FA) the governing body of soccer in England, in relation to the development of the FA Women’s Super League (WSL). In doing so, it examines the organisation’s journey from banning the sport in 1921 to establishing the country’s first semi professional female soccer league in 2011. As the FA has a virtual monopoly on defining the structures of the elite game, we attempted to understand its behaviour in the context of broader issues of power, control and resistance by giving voice to the experiences of those affected by its decisions. Observations were carried out at 39 matches over three years. Semi structured interviews with 17 people involved in the women’s game, identified via snowball sampling, were also carried out. Transcripts accompanied detailed field notes and were inductively coded to identify themes. What emerged was the governing body’s desire to create a new product, jettisoning the long history of the women’s game in order to shape and control the sport in a way it is no longer able to, with the elite male club game. The League created was also shaped by traditional conceptualisations of gender, in terms of the portrayal of its style of play and target audience, setting increased participation and spectatorship targets as measures of ‘success’. The national governing body has demonstrated pseudo inclusion and a lack of enthusiasm for the implementation of equity reforms, driven by a belief that the organisation is already representative, fair and accessible. Despite a consistent external pressure, the Football Association is still dominated at its most senior levels by males. Via claiming to hold a monopoly on expertise around the sport, maintaining complex committee structures and procedures, and with membership rules rooted in the amateur game, it remains a deeply gendered organisation, resistant to structural and cultural change. In WSL, the FA's structure and culture have created a franchise over which it retains almost complete control, dictating the terms of conditions of entry and marginalising alternative voices. The organisation presents a feminised version of both play and spectatorship, portraying the sport as a distinct, and lesser, version of soccer.Keywords: football association, organisational culture, soccer, women’s super league
Procedia PDF Downloads 352383 Significant Factor of Magnetic Resonance for Survival Outcome in Rectal Cancer Patients Following Neoadjuvant Combined Chemotherapy and Radiation Therapy: Stratification of Lateral Pelvic Lymph Node
Authors: Min Ju Kim, Beom Jin Park, Deuk Jae Sung, Na Yeon Han, Kichoon Sim
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Purpose: The purpose of this study is to determine the significant magnetic resonance (MR) imaging factors of lateral pelvic lymph node (LPLN) on the assessment of survival outcomes of neoadjuvant combined chemotherapy and radiation therapy (CRT) in patients with mid/low rectal cancer. Materials and Methods: The institutional review board approved this retrospective study of 63 patients with mid/low rectal cancer who underwent MR before and after CRT and patient consent was not required. Surgery performed within 4 weeks after CRT. The location of LPLNs was divided into following four groups; 1) common iliac, 2) external iliac, 3) obturator, and 4) internal iliac lymph nodes. The short and long axis diameters, numbers, shape (ovoid vs round), signal intensity (homogenous vs heterogenous), margin (smooth vs irregular), and diffusion-weighted restriction of LPLN were analyzed on pre- and post-CRT images. For treatment response using size, lymph node groups were defined as group 1) short axis diameter ≤ 5mm on both MR, group 2) > 5mm change into ≤ 5mm after CRT, and group 3) persistent size > 5mm before and after CRT. Clinical findings were also evaluated. The disease-free survival and overall survival rate were evaluated and the risk factors for survival outcomes were analyzed using cox regression analysis. Results: Patients in the group 3 (persistent size >5mm) showed significantly lower survival rates than the group 1 and 2 (Disease-free survival rates of 36.1% and 78.8, 88.8%, p < 0.001). The size response (group 1-3), multiplicity of LPLN, the level of carcinoembryonic antigen (CEA), patient’s age, T and N stage, vessel invasion, perineural invasion were significant factors affecting disease-free survival rate or overall survival rate using univariate analysis (p < 0.05). The persistent size (group 3) and multiplicity of LPLN were independent risk factors among MR imaging features influencing disease-free survival rate (HR = 10.087, p < 0.05; HR = 4.808, p < 0.05). Perineural invasion and T stage were shown as independent histologic risk factors (HR = 16.594, p < 0.05; HR = 15.891, p < 0.05). Conclusion: The persistent size greater than 5mm and multiplicity of LPLN on both pre- and post-MR after CRT were significant MR factors affecting survival outcomes in the patients with mid/low rectal cancer.Keywords: rectal cancer, MRI, lymph node, combined chemoradiotherapy
Procedia PDF Downloads 150382 Investigations into the in situ Enterococcus faecalis Biofilm Removal Efficacies of Passive and Active Sodium Hypochlorite Irrigant Delivered into Lateral Canal of a Simulated Root Canal Model
Authors: Saifalarab A. Mohmmed, Morgana E. Vianna, Jonathan C. Knowles
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The issue of apical periodontitis has received considerable critical attention. Bacteria is integrated into communities, attached to surfaces and consequently form biofilm. The biofilm structure provides bacteria with a series protection skills against, antimicrobial agents and enhances pathogenicity (e.g. apical periodontitis). Sodium hypochlorite (NaOCl) has become the irrigant of choice for elimination of bacteria from the root canal system based on its antimicrobial findings. The aim of the study was to investigate the effect of different agitation techniques on the efficacy of 2.5% NaOCl to eliminate the biofilm from the surface of the lateral canal using the residual biofilm, and removal rate of biofilm as outcome measures. The effect of canal complexity (lateral canal) on the efficacy of the irrigation procedure was also assessed. Forty root canal models (n = 10 per group) were manufactured using 3D printing and resin materials. Each model consisted of two halves of an 18 mm length root canal with apical size 30 and taper 0.06, and a lateral canal of 3 mm length, 0.3 mm diameter located at 3 mm from the apical terminus. E. faecalis biofilms were grown on the apical 3 mm and lateral canal of the models for 10 days in Brain Heart Infusion broth. Biofilms were stained using crystal violet for visualisation. The model halves were reassembled, attached to an apparatus and tested under a fluorescence microscope. Syringe and needle irrigation protocol was performed using 9 mL of 2.5% NaOCl irrigant for 60 seconds. The irrigant was either left stagnant in the canal or activated for 30 seconds using manual (gutta-percha), sonic and ultrasonic methods. Images were then captured every second using an external camera. The percentages of residual biofilm were measured using image analysis software. The data were analysed using generalised linear mixed models. The greatest removal was associated with the ultrasonic group (66.76%) followed by sonic (45.49%), manual (43.97%), and passive irrigation group (control) (38.67%) respectively. No marked reduction in the efficiency of NaOCl to remove biofilm was found between the simple and complex anatomy models (p = 0.098). The removal efficacy of NaOCl on the biofilm was limited to the 1 mm level of the lateral canal. The agitation of NaOCl results in better penetration of the irrigant into the lateral canals. Ultrasonic agitation of NaOCl improved the removal of bacterial biofilm.Keywords: 3D printing, biofilm, root canal irrigation, sodium hypochlorite
Procedia PDF Downloads 227381 System Devices to Reduce Particulate Matter Concentrations in Railway Metro Systems
Authors: Armando Cartenì
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Within the design of sustainable transportation engineering, the problem of reducing particulate matter (PM) concentrations in railways metro system was not much discussed. It is well known that PM levels in railways metro system are mainly produced by mechanical friction at the rail-wheel-brake interactions and by the PM re-suspension caused by the turbulence generated by the train passage, which causes dangerous problems for passenger health. Starting from these considerations, the aim of this research was twofold: i) to investigate the particulate matter concentrations in a ‘traditional’ railways metro system; ii) to investigate the particulate matter concentrations of a ‘high quality’ metro system equipped with design devices useful for reducing PM concentrations: platform screen doors, rubber-tyred and an advanced ventilation system. Two measurement surveys were performed: one in the ‘traditional’ metro system of Naples (Italy) and onother in the ‘high quality’ rubber-tyred metro system of Turin (Italy). Experimental results regarding the ‘traditional’ metro system of Naples, show that the average PM10 concentrations measured in the underground station platforms are very high and range between 172 and 262 µg/m3 whilst the average PM2,5 concentrations range between 45 and 60 µg/m3, with dangerous problems for passenger health. By contrast the measurements results regarding the ‘high quality’ metro system of Turin show that: i) the average PM10 (PM2.5) concentrations measured in the underground station platform is 22.7 µg/m3 (16.0 µg/m3) with a standard deviation of 9.6 µg/m3 (7.6 µg/m3); ii) the indoor concentrations (both for PM10 and for PM2.5) are statistically lower from those measured in outdoors (with a ratio equal to 0.9-0.8), meaning that the indoor air quality is greater than those in urban ambient; iii) that PM concentrations in underground stations are correlated to the trains passage; iv) the inside trains concentrations (both for PM10 and for PM2.5) are statistically lower from those measured at station platform (with a ratio equal to 0.7-0.8), meaning that inside trains the use of air conditioning system could promote a greater circulation that clean the air. The comparison among the two case studies allow to conclude that the metro system designed with PM reduction devices allow to reduce PM concentration up to 11 times against a ‘traditional’ one. From these results, it is possible to conclude that PM concentrations measured in a ‘high quality’ metro system are significantly lower than the ones measured in a ‘traditional’ railway metro systems. This result allows possessing the bases for the design of useful devices for retrofitting metro systems all around the world.Keywords: air quality, pollutant emission, quality in public transport, underground railway, external cost reduction, transportation planning
Procedia PDF Downloads 210380 Redirecting Photosynthetic Electron Flux in the Engineered Cyanobacterium synechocystis Sp. Pcc 6803 by the Deletion of Flavodiiron Protein Flv3
Authors: K. Thiel, P. Patrikainen, C. Nagy, D. Fitzpatrick, E.-M. Aro, P. Kallio
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Photosynthetic cyanobacteria have been recognized as potential future biotechnological hosts for the direct conversion of CO₂ into chemicals of interest using sunlight as the solar energy source. However, in order to develop commercially viable systems, the flux of electrons from the photosynthetic light reactions towards specified target chemicals must be significantly improved. The objective of the study was to investigate whether the autotrophic production efficiency of specified end-metabolites can be improved in engineered cyanobacterial cells by rescuing excited electrons that are normally lost to molecular oxygen due to the cyanobacterial flavodiiron protein Flv1/3. Natively Flv1/3 dissipates excess electrons in the photosynthetic electron transfer chain by directing them to molecular oxygen in Mehler-like reaction to protect photosystem I. To evaluate the effect of flavodiiron inactivation on autotrophic production efficiency in the cyanobacterial host Synechocystis sp. PCC 6803 (Synechocystis), sucrose was selected as the quantitative reporter and a representative of a potential end-product of interest. The concept is based on the native property of Synechocystis to produce sucrose as an intracellular osmoprotectant when exposed to high external ion concentrations, in combination with the introduction of a heterologous sucrose permease (CscB from Escherichia coli), which transports the sucrose out from the cell. In addition, cell growth, photosynthetic gas fluxes using membrane inlet mass spectrometry and endogenous storage compounds were analysed to illustrate the consequent effects of flv deletion on pathway flux distributions. The results indicate that a significant proportion of the electrons can be lost to molecular oxygen via Flv1/3 even when the cells are grown under high CO₂ and that the inactivation of flavodiiron activity can enhance the photosynthetic electron flux towards optionally available sinks. The flux distribution is dependent on the light conditions and the genetic context of the Δflv mutants, and favors the production of either sucrose or one of the two storage compounds, glycogen or polyhydroxybutyrate. As a conclusion, elimination of the native Flv1/3 reaction and concomitant introduction of an engineered product pathway as an alternative sink for excited electrons could enhance the photosynthetic electron flux towards the target endproduct without compromising the fitness of the host.Keywords: cyanobacterial engineering, flavodiiron proteins, redirecting electron flux, sucrose
Procedia PDF Downloads 125379 Features of Formation and Development of Possessory Risk Management Systems of Organization in the Russian Economy
Authors: Mikhail V. Khachaturyan, Inga A. Koryagina, Maria Nikishova
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The study investigates the impact of the ongoing financial crisis, started in the 2nd half of 2014, on marketing budgets spent by Fast-moving consumer goods companies. In these conditions, special importance is given to efficient possessory risk management systems. The main objective for establishing and developing possessory risk management systems for FMCG companies in a crisis is to analyze the data relating to the external environment and consumer behavior in a crisis. Another important objective for possessory risk management systems of FMCG companies is to develop measures and mechanisms to maintain and stimulate sales. In this regard, analysis of risks and threats which consumers define as the main reasons affecting their level of consumption become important. It is obvious that in crisis conditions the effective risk management systems responsible for development and implementation of strategies for consumer demand stimulation, as well as the identification, analysis, assessment and management of other types of risks of economic security will be the key to sustainability of a company. In terms of financial and economic crisis, the problem of forming and developing possessory risk management systems becomes critical not only in the context of management models of FMCG companies, but for all the companies operating in other sectors of the Russian economy. This study attempts to analyze the specifics of formation and development of company possessory risk management systems. In the modern economy, special importance among all the types of owner’s risks has the risk of reduction in consumer activity. This type of risk is common not only for the consumer goods trade. Study of consumer activity decline is especially important for Russia due to domestic market of consumer goods being still in the development stage, despite its significant growth. In this regard, it is especially important to form and develop possessory risk management systems for FMCG companies. The authors offer their own interpretation of the process of forming and developing possessory risk management systems within owner’s management models of FMCG companies as well as in Russian economy in general. Proposed methods and mechanisms of problem analysis of formation and development of possessory risk management systems in FMCG companies and the results received can be helpful for researchers interested in problems of consumer goods market development in Russia and overseas.Keywords: FMCG companies, marketing budget, risk management, owner, Russian economy, organization, formation, development, system
Procedia PDF Downloads 376378 Predicting Personality and Psychological Distress Using Natural Language Processing
Authors: Jihee Jang, Seowon Yoon, Gaeun Son, Minjung Kang, Joon Yeon Choeh, Kee-Hong Choi
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Background: Self-report multiple choice questionnaires have been widely utilized to quantitatively measure one’s personality and psychological constructs. Despite several strengths (e.g., brevity and utility), self-report multiple-choice questionnaires have considerable limitations in nature. With the rise of machine learning (ML) and Natural language processing (NLP), researchers in the field of psychology are widely adopting NLP to assess psychological constructs to predict human behaviors. However, there is a lack of connections between the work being performed in computer science and that psychology due to small data sets and unvalidated modeling practices. Aims: The current article introduces the study method and procedure of phase II, which includes the interview questions for the five-factor model (FFM) of personality developed in phase I. This study aims to develop the interview (semi-structured) and open-ended questions for the FFM-based personality assessments, specifically designed with experts in the field of clinical and personality psychology (phase 1), and to collect the personality-related text data using the interview questions and self-report measures on personality and psychological distress (phase 2). The purpose of the study includes examining the relationship between natural language data obtained from the interview questions, measuring the FFM personality constructs, and psychological distress to demonstrate the validity of the natural language-based personality prediction. Methods: The phase I (pilot) study was conducted on fifty-nine native Korean adults to acquire the personality-related text data from the interview (semi-structured) and open-ended questions based on the FFM of personality. The interview questions were revised and finalized with the feedback from the external expert committee, consisting of personality and clinical psychologists. Based on the established interview questions, a total of 425 Korean adults were recruited using a convenience sampling method via an online survey. The text data collected from interviews were analyzed using natural language processing. The results of the online survey, including demographic data, depression, anxiety, and personality inventories, were analyzed together in the model to predict individuals’ FFM of personality and the level of psychological distress (phase 2).Keywords: personality prediction, psychological distress prediction, natural language processing, machine learning, the five-factor model of personality
Procedia PDF Downloads 78377 The Outcome of Using Machine Learning in Medical Imaging
Authors: Adel Edwar Waheeb Louka
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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery
Procedia PDF Downloads 73376 Methodology for Temporary Analysis of Production and Logistic Systems on the Basis of Distance Data
Authors: M. Mueller, M. Kuehn, M. Voelker
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In small and medium-sized enterprises (SMEs), the challenge is to create a well-grounded and reliable basis for process analysis, optimization and planning due to a lack of data. SMEs have limited access to methods with which they can effectively and efficiently analyse processes and identify cause-and-effect relationships in order to generate the necessary database and derive optimization potential from it. The implementation of digitalization within the framework of Industry 4.0 thus becomes a particular necessity for SMEs. For these reasons, the abstract presents an analysis methodology that is subject to the objective of developing an SME-appropriate methodology for efficient, temporarily feasible data collection and evaluation in flexible production and logistics systems as a basis for process analysis and optimization. The overall methodology focuses on retrospective, event-based tracing and analysis of material flow objects. The technological basis consists of Bluetooth low energy (BLE)-based transmitters, so-called beacons, and smart mobile devices (SMD), e.g. smartphones as receivers, between which distance data can be measured and derived motion profiles. The distance is determined using the Received Signal Strength Indicator (RSSI), which is a measure of signal field strength between transmitter and receiver. The focus is the development of a software-based methodology for interpretation of relative movements of transmitters and receivers based on distance data. The main research is on selection and implementation of pattern recognition methods for automatic process recognition as well as methods for the visualization of relative distance data. Due to an existing categorization of the database regarding process types, classification methods (e.g. Support Vector Machine) from the field of supervised learning are used. The necessary data quality requires selection of suitable methods as well as filters for smoothing occurring signal variations of the RSSI, the integration of methods for determination of correction factors depending on possible signal interference sources (columns, pallets) as well as the configuration of the used technology. The parameter settings on which respective algorithms are based have a further significant influence on result quality of the classification methods, correction models and methods for visualizing the position profiles used. The accuracy of classification algorithms can be improved up to 30% by selected parameter variation; this has already been proven in studies. Similar potentials can be observed with parameter variation of methods and filters for signal smoothing. Thus, there is increased interest in obtaining detailed results on the influence of parameter and factor combinations on data quality in this area. The overall methodology is realized with a modular software architecture consisting of independently modules for data acquisition, data preparation and data storage. The demonstrator for initialization and data acquisition is available as mobile Java-based application. The data preparation, including methods for signal smoothing, are Python-based with the possibility to vary parameter settings and to store them in the database (SQLite). The evaluation is divided into two separate software modules with database connection: the achievement of an automated assignment of defined process classes to distance data using selected classification algorithms and the visualization as well as reporting in terms of a graphical user interface (GUI).Keywords: event-based tracing, machine learning, process classification, parameter settings, RSSI, signal smoothing
Procedia PDF Downloads 131375 Impinging Acoustics Induced Combustion: An Alternative Technique to Prevent Thermoacoustic Instabilities
Authors: Sayantan Saha, Sambit Supriya Dash, Vinayak Malhotra
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Efficient propulsive systems development is an area of major interest and concern in aerospace industry. Combustion forms the most reliable and basic form of propulsion for ground and space applications. The generation of large amount of energy from a small volume relates mostly to the flaming combustion. This study deals with instabilities associated with flaming combustion. Combustion is always accompanied by acoustics be it external or internal. Chemical propulsion oriented rockets and space systems are well known to encounter acoustic instabilities. Acoustic brings in changes in inter-energy conversion and alter the reaction rates. The modified heat fluxes, owing to wall temperature, reaction rates, and non-linear heat transfer are observed. The thermoacoustic instabilities significantly result in reduced combustion efficiency leading to uncontrolled liquid rocket engine performance, serious hazards to systems, assisted testing facilities, enormous loss of resources and every year a substantial amount of money is spent to prevent them. Present work attempts to fundamentally understand the mechanisms governing the thermoacoustic combustion in liquid rocket engine using a simplified experimental setup comprising a butane cylinder and an impinging acoustic source. Rocket engine produces sound pressure level in excess of 153 Db. The RL-10 engine generates noise of 180 Db at its base. Systematic studies are carried out for varying fuel flow rates, acoustic levels and observations are made on the flames. The work is expected to yield a good physical insight into the development of acoustic devices that when coupled with the present propulsive devices could effectively enhance combustion efficiency leading to better and safer missions. The results would be utilized to develop impinging acoustic devices that impinge sound on the combustion chambers leading to stable combustion thus, improving specific fuel consumption, specific impulse, reducing emissions, enhanced performance and fire safety. The results can be effectively applied to terrestrial and space application.Keywords: combustion instability, fire safety, improved performance, liquid rocket engines, thermoacoustics
Procedia PDF Downloads 143374 Anti-Inflammatory Studies on Chungpye-Tang in Asthmatic Human Lung Tissue
Authors: J. H. Bang, H. J. Baek, K. I. Kim, B. J. Lee, H. J. Jung, H. J. Jang, S. K. Jung
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Asthma is a chronic inflammatory lung disease characterized by airway hyper responsiveness (AHR), airway obstruction and airway wall remodeling responsible for significant morbidity and mortality worldwide. Genetic and environment factors may result in asthma, but there are no the exact causes of asthma. Chungpye-tang (CPT) has been prescribed as a representative aerosol agent for patients with dyspnea, cough and phlegm in the respiratory clinic at Kyung Hee Korean Medicine Hospital. This Korean herbal medicines have the effect of dispelling external pathogen and dampness pattern. CPT is composed of 4 species of herbal medicines. The 4 species of herbal medicines are Ephedrae herba, Pogostemonis(Agatachis) herba, Caryophylli flos and Zingiberis rhizoma crudus. CPT suppresses neutrophil infiltration and the production of pro-inflammatory cytokines in lipopolysaccharide (LPS)-induced acute lung injury (ALI) mouse model. Moreover, the anti-inflammatory effects of CPT on a mouse model of Chronic Obstructive Pulmonary Disease (COPD) was proved. Activation of the NF-κB has been proven that it plays an important role in inflammation via inducing transcription of pro-inflammatory genes. Over-expression of NF-κB has been believed be related to many inflammatory diseases such as arthritis, gastritis, asthma and COPD. So we firstly hypothesize whether CPT has an anti-inflammatory effect on asthmatic human airway epithelial tissue via inhibiting NF-κB pathway. In this study, CPT was extracted with distilled water for 3 hours at 100°C. After process of filtration and evaporation, it was freeze dried. And asthmatic human lung tissues were provided by MatTek Corp. We investigated the precise mechanism of the anti-inflammatory effect of CPT by western blotting analysis. We observed whether the decoction extracts could reduce NF-κB activation, COX-2 protein expression and NF-κB-mediated pro-inflammatory cytokines such as TNF-α, eotaxin, IL-4, IL-9 and IL-13 in asthmatic human lung tissue. As results of this study, there was a trend toward decreased NF-κB expression in asthmatic human airway epithelial tissue. We found that the inhibition effects of CPT on COX-2 expression was not determined. IL-9 and IL-13 secretion was significantly reduced in the asthmatic human lung tissue treated with CPT. Overall, our results indicate that CPT has an anti-inflammatory effect through blocking the signaling pathway of NF-κB, thereby CPT may be a potential remedial agent for allergic asthma.Keywords: Chungpye-tang, allergic asthma, asthmatic human airway epithelial tissue, nuclear factor kappa B (NF-κB) pathway, COX-2
Procedia PDF Downloads 334373 Demographic Shrinkage and Reshaping Regional Policy of Lithuania in Economic Geographic Context
Authors: Eduardas Spiriajevas
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Since the end of the 20th century, when Lithuania regained its independence, a process of demographic shrinkage started. Recently, it affects the efficiency of implementation of actions related to regional development policy and geographic scopes of created value added in the regions. The demographic structures of human resources reflect onto the regions and their economic geographic environment. Due to reshaping economies and state reforms on restructuration of economic branches such as agriculture and industry, it affects the economic significance of services’ sector. These processes influence the competitiveness of labor market and its demographic characteristics. Such vivid consequences are appropriate for the structures of human migrations, which affected the processes of demographic ageing of human resources in the regions, especially in peripheral ones. These phenomena of modern times induce the demographic shrinkage of society and its economic geographic characteristics in the actions of regional development and in regional policy. The internal and external migrations of population captured numerous regional economic disparities, and influenced on territorial density and concentration of population of the country and created the economies of spatial unevenness in such small geographically compact country as Lithuania. The processes of territorial reshaping of distribution of population create new regions and their economic environment, which is not corresponding to the main principles of regional policy and its power to create the well-being and to promote the attractiveness for economic development. These are the new challenges of national regional policy and it should be researched in a systematic way of taking into consideration the analytical approaches of regional economy in the context of economic geographic research methods. A comparative territorial analysis according to administrative division of Lithuania in relation to retrospective approach and introduction of method of location quotients, both give the results of economic geographic character with cartographic representations using the tools of spatial analysis provided by technologies of Geographic Information Systems. A set of these research methods provide the new spatially evidenced based results, which must be taken into consideration in reshaping of national regional policy in economic geographic context. Due to demographic shrinkage and increasing differentiation of economic developments within the regions, an input of economic geographic dimension is inevitable. In order to sustain territorial balanced economic development, there is a need to strengthen the roles of regional centers (towns) and to empower them with new economic functionalities for revitalization of peripheral regions, and to increase their economic competitiveness and social capacities on national scale.Keywords: demographic shrinkage, economic geography, Lithuania, regions
Procedia PDF Downloads 160372 The Determination of Pb and Zn Phytoremediation Potential and Effect of Interaction between Cadmium and Zinc on Metabolism of Buckwheat (Fagopyrum Esculentum)
Authors: Nurdan Olguncelik Kaplan, Aysen Akay
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Nowadays soil pollution has become a global problem. External added polluters to the soil are destroying and changing the structure of the soil and the problems are becoming more complex and in this sense the correction of these problems is going to be harder and more costly. Cadmium has got a fast mobility in the soil and plant system because of that cadmium can interfere very easily to the human and animal food chain and in the same time this can be very dangerous. The cadmium which is absorbed and stored by the plants is causing to many metabolic changes of the plants like; protein synthesis, nitrogen and carbohydrate metabolism, enzyme (nitrate reductase) activation, photo and chlorophyll synthesis. The biological function of cadmium is not known over the plants and it is not a necessary element. The plant is generally taking in small amounts the cadmium and this element is competing with the zinc. Cadmium is causing root damages. Buckwheat (Fagopyrum esculentum) is an important nutraceutical because of its high content of flavonoids, minerals and vitamins, and their nutritionally balanced amino-acid composition. Buckwheat has relatively high biomass productivity, is adapted to many areas of the world, and can flourish in sterile fields; therefore buckwheat plants are widely used for the phytoremediation process.The aim of this study were to evaluate the phytoremediation capacity of the high-yielding plant Buckwheat (Fagopyrum esculentum) in soils contaminated with Cd and Zn. The soils were applied to differrent doses cd(0-12.5-25-50-100 mg Cd kg−1 soil in the form of 3CdSO4.8H2O ) and Zn (0-10-30 mg Zn kg−1 soil in the form of ZnSO4.7H2O) and incubated about 60 days. Later buckwheat seeds were sown and grown for three mounth under greenhouse conditions. The test plants were irrigated by using pure water after the planting process. Buckwheat seeds (Gunes and Aktas species) were taken from Bahri Dagdas International Agricultural Research. After harvest, Cd and Zn concentrations of plant biomass and grain, yield and translocation factors (TFs) for Cd and Cd were determined. Cadmium accumulation in biomass and grain significantly increased in dose-dependent manner. Long term field trials are required to further investigate the potential of buckwheat to reclaimed the soil. But this could be undertaken in conjunction with actual remediation schemes. However, the differences in element accumulation among the genotypes were affected more by the properties of genotypes than by the soil properties. Gunes genotype accumulated higher lead than Aktas genotypes.Keywords: buckwheat, cadmium, phytoremediation, zinc
Procedia PDF Downloads 417371 Setting up a Prototype for the Artificial Interactive Reality Unified System to Transform Psychosocial Intervention in Occupational Therapy
Authors: Tsang K. L. V., Lewis L. A., Griffith S., Tucker P.
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Background: Many children with high incidence disabilities, such as autism spectrum disorder (ASD), struggle to participate in the community in a socially acceptable manner. There are limitations for clinical settings to provide natural, real-life scenarios for them to practice the life skills needed to meet their real-life challenges. Virtual reality (VR) offers potential solutions to resolve the existing limitations faced by clinicians to create simulated natural environments for their clients to generalize the facilitated skills. Research design: The research aimed to develop a prototype of an interactive VR system to provide realistic and immersive environments for clients to practice skills. The descriptive qualitative methodology is employed to design and develop the Artificial Interactive Reality Unified System (AIRUS) prototype, which provided insights on how to use advanced VR technology to create simulated real-life social scenarios and enable users to interact with the objects and people inside the virtual environment using natural eye-gazes, hand and body movements. The eye tracking (e.g., selective or joint attention), hand- or body-tracking (e.g., repetitive stimming or fidgeting), and facial tracking (e.g., emotion recognition) functions allowed behavioral data to be captured and managed in the AIRUS architecture. Impact of project: Instead of using external controllers or sensors, hand tracking software enabled the users to interact naturally with the simulated environment using daily life behavior such as handshaking and waving to control and interact with the virtual objects and people. The AIRUS protocol offers opportunities for breakthroughs in future VR-based psychosocial assessment and intervention in occupational therapy. Implications for future projects: AI technology can allow more efficient data capturing and interpretation of object identification and human facial emotion recognition at any given moment. The data points captured can be used to pinpoint our users’ focus and where their interests lie. AI can further help advance the data interpretation system.Keywords: occupational therapy, psychosocial assessment and intervention, simulated interactive environment, virtual reality
Procedia PDF Downloads 35370 Theoretical Framework and Empirical Simulation of Policy Design on Trans-Dimensional Resource Recycling
Authors: Yufeng Wu, Yifan Gu, Bin Li, Wei Wang
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Resource recycling process contains a subsystem with interactions of three dimensions including coupling allocation of primary and secondary resources, responsibility coordination of stakeholders in forward and reverse supply chains, and trans-boundary transfer of hidden resource and environmental responsibilities between regions. Overlap or lack of responsibilities is easy to appear at the intersection of the three management dimensions. It is urgent to make an overall design of the policy system for recycling resources. From theoretical perspective, this paper analyzes the unique external differences of resource and environment in various dimensions and explores the reason why the effects of trans-dimensional policies are strongly correlated. Taking the example of the copper resources contained in the waste electrical and electronic equipment, this paper constructs reduction effect accounting model of resources recycling and set four trans-dimensional policy scenarios including resources tax and environmental tax reform of the raw and secondary resources, application of extended producer responsibility system, promotion of clean development mechanism, and strict entry barriers of imported wastes. In these ways, the paper simulates the impact effect of resources recycling process on resource deduction and emission reduction of waste water and gas, and constructs trans-dimensional policy mix scenario through integrating dominant strategy. The results show that combined application of various dimensional policies can achieve incentive compatibility and the trans-dimensional policy mix scenario can reach a better effect. Compared with baseline scenario, this scenario will increase 91.06% copper resources reduction effect and improve emission reduction of waste water and gas by eight times from 2010 to 2030. This paper further analyzes the development orientation of policies in various dimension. In resource dimension, the combined application of compulsory, market and authentication methods should be promoted to improve the use ratio of secondary resources. In supply chain dimension, resource value, residual functional value and potential information value contained in waste products should be fully excavated to construct a circular business system. In regional dimension, it should give full play to the comparative advantages of manufacturing power to improve China’s voice in resource recycling in the world.Keywords: resource recycling, trans-dimension, policy design, incentive compatibility, life cycle
Procedia PDF Downloads 126369 Parents’ Perspectives on After-School Educational Service from a Cross-Cultural Background: A Comparative Semi-Structured Interview Approach Based in China and Ireland
Authors: Xining Wang
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After-school educational service has been proven that it could benefit children’s academic performance, socio-emotional skills, and physical health level. However, there is little research demonstrating parents’ perspectives on the choice of after-school educational service from a level of cross-cultural backgrounds. China and Ireland are typical representatives of collectivist countries (e.g., estimated individualism score is 20) and individualist countries (e.g., estimated individualism score is 70) according to Hofstede's cultural dimensions theory. Living in countries with distinguished cultural backgrounds, there is an evident discrepancy in parents’ attitudes towards domestic after-school education and parents’ motivations for choosing after-school educational services. Through conducting a semi-structured interview with 15 parents from China and 15 parents from Ireland, using thematic analysis software (ATLAS) to extract the key information, and applying a comparative approach to process data analysis; results present polarization of Chinese and Irish parents' perspectives and motivations on after-school educational service. For example, Chinese parents tend to view after-school education as a complement to school education. It is a service they purchased for their children to acquire extra knowledge and skills so that they could adapt to the highly competitive educational setting. Given the fact that children’s education is a priority for Chinese families, most parents believe that their children would succeed in the future through massive learning. This attitude reflects that Chinese parents are more likely to apply authoritarian parenting methods and having a strong expectations for their children. Conversely, Irish parents' choice of after-school educational service is a consideration that primarily based on their own situation, secondly, for their family. For instance, with the expansion of the labor market, there is a change in household structure. Irish mothers are more likely to seek working opportunities instead of looking after the family. Irish parents view that after-school educational service is an essential need for themselves and a beneficial component for their family due to the external pressure (e.g., the growing work intensity and extended working hours, increasing numbers of separated families, as well as parents’ pursuit of higher education and promotion). These factors are fundamental agents that encourage Irish parents to choose after-school educational services. To conclude, the findings could provide readers with a better understanding of parents’ disparate and contrasting perspectives on after-school educational services from a multi-culture level.Keywords: after-school, China, family studies, Ireland, parents
Procedia PDF Downloads 183368 Acceptability Process of a Congestion Charge
Authors: Amira Mabrouk
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This paper deals with the acceptability of urban toll in Tunisia. The price-based regulation, i.e. urban toll, is the outcome of a political process hampered by three-fold objectives: effectiveness, equity and social acceptability. This produces both economic interest groups and functions that are of incongruent preferences. The plausibility of this speculation goes hand in hand with the fact that these economic interest groups are also taxpayers who undeniably perceive urban toll as an additional charge. This wariness is coupled with an inquiry about the conditions of usage, the redistribution of the collected tax revenue and the idea of the leviathan state completes the picture. In a nutshell, if researches related to road congestion proliferate, no de facto legitimacy can be pleaded. Nonetheless, the theory on urban tolls engenders economists’ questioning of ways to reduce negative external effects linked to it. Only then does the urban toll appear to bear an answer to these issues. Undeniably, the urban toll suggests inherent conflicts due to the apparent no-payment principal of a public asset as well as to the social perception of the new measure as a mere additional charge. However, when the main concern is effectiveness is its broad sense and the social well-being, the main factors that determine the acceptability of such a tariff measure along with the type of incentives should be the object of a thorough, in-depth analysis. Before adopting this economic role, one has to recognize the factors that intervene in the acceptability of a congestion toll which brought about a copious number of articles and reports that lacked mostly solid theoretical content. It is noticeable that nowadays uncertainties float over the exact nature of the acceptability process. Accepting a congestion tariff could differ from one era to another, from one region to another and from one population to another, etc. Notably, this article, within a convenient time frame, attempts at bringing into focus a link between the social acceptability of the urban congestion toll and the value of time through a survey method barely employed in Tunisia, that of stated preference method. How can the urban toll, as a tax, be defined, justified and made acceptable? How can an equitable and effective tariff of congestion toll be reached? How can the costs of this urban toll be covered? In what way can we make the redistribution of the urban toll revenue visible and economically equitable? How can the redistribution of the revenue of urban toll compensate the disadvantaged while introducing such a tariff measure? This paper will offer answers to these research questions and it follows the line of contribution of JULES DUPUIT in 1844.Keywords: congestion charge, social perception, acceptability, stated preferences
Procedia PDF Downloads 285367 Virtual Team Performance: A Transactive Memory System Perspective
Authors: Belbaly Nassim
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Virtual teams (VT) initiatives, in which teams are geographically dispersed and communicate via modern computer-driven technologies, have attracted increasing attention from researchers and professionals. The growing need to examine how to balance and optimize VT is particularly important given the exposure experienced by companies when their employees encounter globalization and decentralization pressures to monitor VT performance. Hence, organization is regularly limited due to misalignment between the behavioral capabilities of the team’s dispersed competences and knowledge capabilities and how trust issues interplay and influence these VT dimensions and the effects of such exchanges. In fact, the future success of business depends on the extent to which VTs are managing efficiently their dispersed expertise, skills and knowledge to stimulate VT creativity. Transactive memory system (TMS) may enhance VT creativity using its three dimensons: knowledge specialization, credibility and knowledge coordination. TMS can be understood as a composition of both a structural component residing of individual knowledge and a set of communication processes among individuals. The individual knowledge is shared while being retrieved, applied and the learning is coordinated. TMS is driven by the central concept that the system is built on the distinction between internal and external memory encoding. A VT learns something new and catalogs it in memory for future retrieval and use. TMS uses the role of information technology to explain VT behaviors by offering VT members the possibility to encode, store, and retrieve information. TMS considers the members of a team as a processing system in which the location of expertise both enhances knowledge coordination and builds trust among members over time. We build on TMS dimensions to hypothesize the effects of specialization, coordination, and credibility on VT creativity. In fact, VTs consist of dispersed expertise, skills and knowledge that can positively enhance coordination and collaboration. Ultimately, this team composition may lead to recognition of both who has expertise and where that expertise is located; over time, the team composition may also build trust among VT members over time developing the ability to coordinate their knowledge which can stimulate creativity. We also assess the reciprocal relationship between TMS dimensions and VT creativity. We wish to use TMS to provide researchers with a theoretically driven model that is empirically validated through survey evidence. We propose that TMS provides a new way to enhance and balance VT creativity. This study also provides researchers insight into the use of TMS to influence positively VT creativity. In addition to our research contributions, we provide several managerial insights into how TMS components can be used to increase performance within dispersed VTs.Keywords: virtual team creativity, transactive memory systems, specialization, credibility, coordination
Procedia PDF Downloads 172366 Power Recovery from Waste Air of Mine Ventilation Fans Using Wind Turbines
Authors: Soumyadip Banerjee, Tanmoy Maity
Abstract:
The recovery of power from waste air generated by mine ventilation fans presents a promising avenue for enhancing energy efficiency in mining operations. This abstract explores the feasibility and benefits of utilizing turbine generators to capture the kinetic energy present in waste air and convert it into electrical power. By integrating turbine generator systems into mine ventilation infrastructures, the potential to harness and utilize the previously untapped energy within the waste air stream is realized. This study examines the principles underlying turbine generator technology and its application within the context of mine ventilation systems. The process involves directing waste air from ventilation fans through specially designed turbines, where the kinetic energy of the moving air is converted into rotational motion. This mechanical energy is then transferred to connected generators, which convert it into electrical power. The recovered electricity can be employed for various on-site applications, including powering mining equipment, lighting, and control systems. The benefits of power recovery from waste air using turbine generators are manifold. Improved energy efficiency within the mining environment results in reduced dependence on external power sources and associated cost savings. Additionally, this approach contributes to environmental sustainability by utilizing a previously wasted resource for power generation. Resource conservation is further enhanced, aligning with modern principles of sustainable mining practices. However, successful implementation requires careful consideration of factors such as waste air characteristics, turbine design, generator efficiency, and integration into existing mine infrastructure. Maintenance and monitoring protocols are necessary to ensure consistent performance and longevity of the turbine generator systems. While there is an initial investment associated with equipment procurement, installation, and integration, the long-term benefits of reduced energy costs and environmental impact make this approach economically viable. In conclusion, the recovery of power from waste air from mine ventilation fans using turbine generators offers a tangible solution to enhance energy efficiency and sustainability within mining operations. By capturing and converting the kinetic energy of waste air into usable electrical power, mines can optimize resource utilization, reduce operational costs, and contribute to a greener future for the mining industry.Keywords: waste to energy, wind power generation, exhaust air, power recovery
Procedia PDF Downloads 33