Search results for: common vector approach

Authors: Benmansour Nassima, Benmansour Souheyla

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The appropriate integration of reward processing and decision making provided by the environment is vital for behavioural success and individuals’ well being in everyday life. Functional neurological investigation has already provided an inclusive image on affective and emotional (motivational) processing in the healthy human brain and has recently focused its interest also on the assessment of brain function in anxious and depressed individuals. This article offers an overview on the theoretical approaches that relate emotion and decision-making, and spotlights investigation with anxious or depressed individuals to reveal how emotions can interfere with decision-making. This research aims at incorporating the emotional structure based on response and stimulation with a Bayesian approach to decision-making in terms of probability and value processing. It seeks to show how studies of individuals with emotional dysfunctions bear out that alterations of decision-making can be considered in terms of altered probability and value subtraction. The utmost objective is to critically determine if the probabilistic representation of belief affords could be a critical approach to scrutinize alterations in probability and value representation in subjective with anxiety and depression, and draw round the general implications of this approach.

Keywords: decision-making, motivation, alteration, reward processing, response selection

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Authors: Hervice Roméo Fogno Fotsoa, Germaine Djuidje Kenmoe, Claude Vidal Aloyem Kazé

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One of the main applications of machine learning is the prediction of time series. But a more accurate prediction requires a more optimal model of machine learning. Several optimization techniques have been developed, but without considering the input variables disposition of the system. Thus, this work aims to present a new machine learning architecture optimization technique based on their optimal input variables disposition. The validations are done on the prediction of wind time series, using data collected in Cameroon. The number of possible dispositions with four input variables is determined, i.e., twenty-four. Each of the dispositions is used to perform the prediction, with the main criteria being the training and prediction performances. The results obtained from a static architecture and a dynamic architecture of neural networks have shown that these performances are a function of the input variable's disposition, and this is in a different way from the architectures. This analysis revealed that it is necessary to take into account the input variable's disposition for the development of a more optimal neural network model. Thus, a new neural network training algorithm is proposed by introducing the search for the optimal input variables disposition in the traditional back-propagation algorithm. The results of the application of this new optimization approach on the two single neural network architectures are compared with the previously obtained results step by step. Moreover, this proposed approach is validated in a collaborative optimization method with a single objective optimization technique, i.e., genetic algorithm back-propagation neural networks. From these comparisons, it is concluded that each proposed model outperforms its traditional model in terms of training and prediction performance of time series. Thus the proposed optimization approach can be useful in improving the accuracy of time series forecasts. This proves that the proposed optimization approach can be useful in improving the accuracy of time series prediction based on machine learning.

Keywords: input variable disposition, machine learning, optimization, performance, time series prediction

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Authors: Nuhu Bitrus Mailabari

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Nigeria is a highly multifarious nation trapped between affluence and affliction. On one hand, the state has vast territorial size, economic strength, relative internal cohesion, and good external linkages. On the other, it is bedeviled with enormous challenges. It is common knowledge that the North-East geo-political zone has suffered colossal destruction for the most part of the last ten years due to the activities of the insurgent group Boko Haram. Several factors (political, economic, religious, socio-cultural) have been credited with the heightened insecurity in the region. Without a doubt, the security crisis in the region has rekindled several discussions critical to Nigeria’s security architecture. However, the debate on finding an enduring solution to the devastation in the North East continually neglects the nexus between cross border migration and national security. Using content analysis, this paper debates two main issues that continue to affect security in the North East. One, the cumulative impact of the Economic Community of West African States (ECOWAS) protocol on the free movement of people and goods. Two, the porous nature of Nigeria’s borders. Theoretically, the paper will rely on the systems theory because of its broad focus on structure, linkage, and process. The work concludes in twofold. First, that cross border migration and poor border management processes further worsened the political and socio-economic conditions of a region that is already in a bad state. Secondly, in addition to the existing strategies, Nigeria must develop a holistic approach including new methods of handling cross border movements in solving the security issues.

Keywords: border, cross border, migration, Nigeria, northeast region, security

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Authors: Shittu Bashirat, Shittu Mujeeb, Oluremi Adeolu, Orisadare Olayiwola, Jikeme Osameke, Bello Lateef

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Septicemia in neonates refers to generalized bacterial infection documented by positive blood culture in the first 28 days of life and is one of the leading causes of neonatal mortality in sub-Sahara Africa. Thrombocytopenia in newborns is a result of increased platelet consumption; sepsis was found to be the most common risk factor. The objective of the study was to determine if there are organism-specific platelet responses among the 2 groups of bacterial agents: Gram-positive and Gram-negative bacteria, and also to examine the association of platelet count and prothrombin time with neonatal septicemia. 232 blood samples were collected for this study. The blood culture was performed using Bactec 9050, an instrumented blood culture system. The platelet count and prothrombin time were performed using Abacus Junior 5 hematology analyzer and i-STAT 1 analyzer respectively. Of the 231 neonates hospitalized with clinical sepsis, blood culture reports were positive in 51 cases (21.4%). Klebsiella spp. (35.3%) and Staphylococcus aureus (27.5%) were the most common Gram-negative and Gram-positive isolates respectively. Thrombocytopenia was observed in 30 (58.8%) of the neonates with septicemia. Of the 9 (17.6%) patients with severe thrombocytopenia, seven (77.8%) had Klebsiella spp. septicemia. Out of the 21(63.6%) of thrombocytopenia produced by Gram-negative isolate, 17 (80.9) had increased prothrombin time. In conclusion, Gram-negative organisms showed the highest cases of severe thrombocytopenia and prolonged PT. This study has helped to establish a disturbance in hemostatic systems in neonates with septicemia. Further studies, however, may be required to assess other hemostasis parameters in order to understand their interaction with the infectious organisms in neonates.

Keywords: neonates, septicemia, thrombocytopenia, prolonged prothrombin time, platelet count

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Authors: K. D. R. Jagath-Kumara, D. D. Dias

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The sea waves carry thousands of GWs of power globally. Although there are a number of different approaches to harness offshore energy, they are likely to be expensive, practically challenging and vulnerable to storms. Therefore, this paper considers using the near shore waves for generating mechanical and electrical power. It introduces two new approaches, the wave manipulation and using a variable duct turbine, for intercepting very wide wave fronts and coping with the fluctuations of the wave height and the sea level, respectively. The first approach effectively allows capturing much more energy yet with a much narrower turbine rotor. The second approach allows using a rotor with a smaller radius but captures energy of higher wave fronts at higher sea levels yet preventing it from totally submerging. To illustrate the effectiveness of the approach, the paper contains a description and the simulation results of a scale model of a wave manipulator. Then, it includes the results of testing a physical model of the manipulator and a single duct, axial flow turbine, in a wave flume in the laboratory. The paper also includes comparisons of theoretical predictions, simulation results and wave flume tests with respect to the incident energy, loss in wave manipulation, minimal loss, brake torque and the angular velocity.

Keywords: near-shore sea waves, renewable energy, wave energy conversion, wave manipulation

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Authors: Nejah Ben Mabrouk, Bassem Jarboui, Habib Chabchoub

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Production and distribution planning is the most important part in supply chain management. In this paper, a NP-hard production-distribution problem for one product over a multi-period horizon is investigated. The aim is to minimize the sum of costs of three items: production setups, inventories and distribution, while determining, for each period, the amount produced, the inventory levels and the delivery trips. To solve this difficult problem, we propose a bi-phase approach based on a Variable Neighbourhood Search (VNS). This heuristic is tested on 90 randomly generated instances from the literature, with 20 periods and 50, 100, 200 customers. Computational results show that our approach outperforms existing solution procedures available in the literature

Keywords: logistic, production, distribution, variable neighbourhood search

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Authors: Jonah Kenei, Elisha Opiyo

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Electronic health records, as a repository of patient information, is nowadays the most commonly used technology to record, store and review patient clinical records and perform other clinical tasks. However, the accurate identification and retrieval of relevant information from clinical records is a difficult task due to the unstructured nature of clinical documents, characterized in particular by a lack of clear structure. Therefore, medical practice is facing a challenge thanks to the rapid growth of health information in electronic health records (EHRs), mostly in narrative text form. As a result, it's becoming important to effectively manage the growing amount of data for a single patient. As a result, there is currently a requirement to visualize electronic health records (EHRs) in a way that aids physicians in clinical tasks and medical decision-making. Leveraging text visualization techniques to unstructured clinical narrative texts is a new area of research that aims to provide better information extraction and retrieval to support clinical decision support in scenarios where data generated continues to grow. Clinical datasets in electronic health records (EHR) offer a lot of potential for training accurate statistical models to classify facets of information which can then be used to improve patient care and outcomes. However, in many clinical note datasets, the unstructured nature of clinical texts is a common problem. This paper examines the very issue of getting raw clinical texts and mapping them into meaningful structures that can support healthcare professionals utilizing narrative texts. Our work is the result of a collaborative design process that was aided by empirical data collected through formal usability testing.

Keywords: classification, electronic health records, narrative texts, visualization

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Authors: Jamaludin Sallim, Rozlina Mohamed, Roslina Abdul Hamid

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In this paper, we proposed an Ant Colony Optimization (ACO) algorithm together with Traveling Salesman Problem (TSP) approach to investigate the clustering problem in Protein Interaction Networks (PIN). We named this combination as ACOPIN. The purpose of this work is two-fold. First, to test the efficacy of ACO in clustering PIN and second, to propose the simple generalization of the ACO algorithm that might allow its application in clustering proteins in PIN. We split this paper to three main sections. First, we describe the PIN and clustering proteins in PIN. Second, we discuss the steps involved in each phase of ACO algorithm. Finally, we present some results of the investigation with the clustering patterns.

Keywords: ant colony optimization algorithm, searching algorithm, protein functional module, protein interaction network

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Authors: Lloyd A. Taylor

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An increase in the prevalence of Attention Deficit-Hyperactivity Disorder (ADHD) highlights the need to consider factors that may be exacerbating symptom presentation. Traditional diagnostic criteria provide a little framework for healthcare providers to consider as they attempt to diagnose and treat children with behavioral problems. In fact, aside from exclusion criteria, limited alternative considerations are available, and approaches fail to consider the impact of outside factors that could increase or decrease the likelihood of appropriate diagnosis and success of interventions. This paper will consider specific systems-based factors that influence behavior and intervention successes that, when not considered, could account for the upsurge of diagnoses. These include understanding (1) challenges in the healthcare system, (2) the influence and impact of educators and the educational system, (3) technology use, and (4) patient and parental attitudes about the diagnosis of ADHD. These factors must be considered both individually and as a whole when considering both the increase in diagnoses and the subsequent increases in prescriptions for psychostimulant medication. A theoretical model based on a risk management approach will be presented. Finally, data will be presented that demonstrates pediatric provider satisfaction with this approach to diagnoses and treatment of ADHD as it relates to practice trends.

Keywords: ADHD, diagnostic criteria, risk management model, pediatricians

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Authors: Ming-Dong Wang, Abigail F. Ruby, Michelle E. Ross

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Methylphenidate is a first-line treatment drug for attention deficit hyperactivity disorder (ADHD), a common mental health disorder in children and adolescents. Over the last several decades, the rate of children and adolescents using ADHD medication has been increasing in many countries. A recent study found that the prevalence of ADHD medication use among children aged 3-18 years increased in 13 different world regions between 2001 and 2015, where the absolute increase ranged from 0.02 to 0.26% per year. The goal of this study was to examine the use of methylphenidate in Canadian children and its associated adverse reactions. Methylphenidate use information among young Canadians aged 0-14 years was extracted from IQVIA data on prescriptions dispensed by pharmacies between April 2014 and June 2020. The adverse reaction information associated with methylphenidate use was extracted from the Canada Vigilance database for the same time period. Methylphenidate use trends were analyzed based on sex, age group (0-4 years, 5-9 years, and 10-14 years), and geographical location (province). The common classes of adverse reactions associated with methylphenidate use were sorted, and the relative risks associated with methylphenidate use as compared with two second-line amphetamine medications for ADHD were estimated. This study revealed that among Canadians aged 0-14 years, every 100 people used about 25 prescriptions (or 23,000 mg) of methylphenidate per year during the study period, and the use increased with time. Boys used almost three times more methylphenidate than girls. The amount of drug used was inversely associated with age: Canadians aged 10-14 years used nearly three times as many drugs compared to those aged 5-9 years. Seasonal methylphenidate use patterns were apparent among young Canadians, but the seasonal trends differed among the three age groups. Methylphenidate use varied from region to region, and the highest methylphenidate use was observed in Quebec, where the use of methylphenidate was at least double that of any other province. During the study period, Health Canada received 304 adverse reaction reports associated with the use of methylphenidate for Canadians aged 0-14 years. The number of adverse reaction reports received for boys was 3.5 times higher than that for girls. The three most common adverse reaction classes were psychiatric disorders, nervous system disorders and injury, poisoning procedural complications. The number one commonly reported adverse reaction for boys was aggression (11.2%), while for girls, it was a tremor (9.6%). The safety profile in terms of adverse reaction classes associated with methylphenidate use was similar to that of the selected control products. Methylphenidate is a commonly used pharmaceutical product in young Canadians, particularly in the province of Quebec. Boys used approximately three times more of this product as compared to girls. Future investigation is needed to determine what factors are associated with the observed geographic variations in Canada.

Keywords: adverse reaction risk, methylphenidate, prescription trend, use variation

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Authors: Pushpendra Kumar, Sanjeev Kumar, R. Balasubramanian

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Estimation of optical flow from a sequence of images using variational methods is one of the most successful approach. Discontinuity between different motions is one of the challenging problem in flow estimation. In this paper, we design a new anisotropic diffusion operator, which is able to provide smooth flow over a region and efficiently preserve discontinuity in optical flow. This operator is designed on the basis of intensity differences of the pixels and isotropic operator using exponential function. The combination of these are used to control the propagation of flow. Experimental results on the different datasets verify the robustness and accuracy of the algorithm and also validate the effect of anisotropic operator in the discontinuity preserving.

Keywords: optical flow, variational methods, computer vision, anisotropic operator

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Authors: Kawalpreet Kaur, Panagiotis Mitropoulos

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The division of the project scope into work packages is the most important step in the preconstruction phase of construction projects. The work division determines the scope and complexity of each bid package, resulting in dependencies between project participants performing these work packages. The coordination between project participants is necessary because of these dependencies. Excessive dependencies between the bid packages create coordination difficulties, leading to delays, added costs, and contractual friction among project participants. However, the literature on construction provides limited knowledge regarding work structuring approaches, issues, and challenges. Manufacturing industry literature provides a systematic approach to defining the project scope into work packages, and the implementation of social network analysis (SNA) in manufacturing is an effective approach to defining and analyzing the divided scope of work at the dependencies level. This paper presents a case study of implementing a similar approach using SNA in construction bid packages. The study uses SNA to analyze the scope of bid packages and determine the dependency between scope elements. The method successfully identifies the bid package with the maximum interaction with other trade contractors and the scope elements that are crucial for project performance. The analysis provided graphical and quantitative information on bid package dependencies. The study can be helpful in performing an analysis to determine the dependencies between bid packages and their scope elements and how these scope elements are critical for project performance. The study illustrates the potential use of SNA as a systematic approach to analyzing bid package dependencies in construction projects, which can guide the division of crucial scope elements to minimize negative impacts on project performance.

Keywords: work structuring, bid packages, work breakdown, project participants

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Authors: Misagh Faezipour

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System dynamics is a systems engineering approach that can help address the complex challenges in different systems. Little is known about how the brain represents people to predict behavior. This work is based on how the brain simulates different personal behavior and responds to them in the case of young children ages one to five. As we know, children’s minds/brains are just as clean as a crystal, and throughout time, in their surroundings, families, and education center, they grow to develop and have different kinds of behavior towards the world and the society they live in. Hence, this work aims to identify how young children respond to various personality behavior and observes their reactions towards them from a system dynamics perspective. We will be exploring the Big Five personality traits in young children. A causal model is developed in support of the system dynamics approach. These models graphically present the factors and factor relationships that contribute to the big five personality traits and provide a better understanding of the entire behavior model. A simulator will be developed that includes a set of causal model factors and factor relationships. The simulator models the behavior of different factors related to personality traits and their impacts and can help make more informed decisions in a risk-free environment.

Keywords: personality traits, systems engineering, system dynamics, causal model, behavior model

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Authors: Guru Prakash, Revanth Dugalam

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A road’s condition often deteriorates due to harsh loading such as overload due to trucks, and severe environmental conditions such as heavy rain, snow load, and cyclic loading. In absence of proper maintenance planning, this results in potholes, wide cracks, bumps, and increased roughness of roads. In this paper, a data-driven model will be developed to detect these damages using vibration and image signals. The key idea of the proposed methodology is that the road anomaly manifests in these signals, which can be detected by training a machine learning algorithm. The use of various machine learning techniques such as the support vector machine and Radom Forest method will be investigated. The proposed model will first be trained and tested with artificially simulated data, and the model architecture will be finalized by comparing the accuracies of various models. Once a model is fixed, the field study will be performed, and data will be collected. The field data will be used to validate the proposed model and to predict the future road’s health condition. The proposed will help to automate the road condition monitoring process, repair cost estimation, and maintenance planning process.

Keywords: SVM, data-driven, road health monitoring, pot-hole

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Authors: Kehinde Peter Oyeduntan, Kayode Oshinubi

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Nigeria is referred as the ‘Giant of Africa’ due to high population, land mass and large economy. However, it still trails far behind many smaller economies in the continent in terms of maritime operations. As we have seen that the maritime industry is the spark plug for national growth, because it houses the most crucial infrastructure that generates wealth for a nation, it is worrisome that a nation with six seaports lag in maritime activities. In this research, we have studied how the Gross Domestic Product (GDP) of the maritime transport influences the Nigerian economy. To do this, we applied Simple Linear Regression (SLR), Support Vector Machine (SVM), Polynomial Regression Model (PRM), Generalized Additive Model (GAM) and Generalized Linear Mixed Model (GLMM) to model the relationship between the nation’s Total GDP (TGDP) and the Maritime Transport GDP (MGDP) using a time series data of 20 years. The result showed that the MGDP is statistically significant to the Nigerian economy. Amongst the statistical tool applied, the PRM of order 4 describes the relationship better when compared to other methods. The recommendations presented in this study will guide policy makers and help improve the economy of Nigeria in terms of its GDP.

Keywords: maritime transport, economy, GDP, regression, port

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Authors: Sarojini Imran, Riza Firmansyah, Aula Ramadhan, Chudamul Furqon, Achfriyatama Oktariflandi

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This article delves into the participatory approach in formulating a master plan for the development of pioneer village tourism in Cibubuan, Sumedang. We explore the process of participatory mapping that involves the active participation of the local community in planning and envisioning the future of village tourism. This research considers the positive impact that arises when the community takes an active role in designing a master plan that benefits the local economy while preserving culture and the environment. The results of this research reveal that the participatory approach can create a more accurate and community-responsive mapping that aligns with the aspirations of the people in Cibubuan Village. It also provides a deep insight into how community-developed mapping can guide the development of sustainable tourism. By offering a deeper understanding of the participatory role in village tourism development planning, this article provides essential insights for stakeholders and researchers in this field. We hope this article will inspire more communities to adopt a participatory approach in planning the future of their village tourism.

Keywords: participatory masterplan, pioneer village tourism, sustainable tourism, community engagement, Cibubuan Village

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Authors: Shidvash Vakilipour, Scott Ormiston, Masoud Mohammadi, Rouzbeh Riazi, Kimia Amiri, Sahar Barati

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Two-phase and multi-phase flows are common flow types in fluid mechanics engineering. Among the basic and applied problems of these flow types, two-phase parallel flow is the one that two immiscible fluids flow in the vicinity of each other. In this type of flow, fluid properties (e.g. density, viscosity, and temperature) are different at the two sides of the interface of the two fluids. The most challenging part of the numerical simulation of two-phase flow is to determine the location of interface accurately. In the present work, a coupled interface tracking algorithm is developed based on Arbitrary Lagrangian-Eulerian (ALE) approach using a cell-centered, pressure-based, coupled solver. To validate this algorithm, an analytical solution for fully developed two-phase flow in presence of gravity is derived, and then, the results of the numerical simulation of this flow are compared with analytical solution at various flow conditions. The results of the simulations show good accuracy of the algorithm despite using a nearly coarse and uniform grid. Temporal variations of interface profile toward the steady-state solution show that a greater difference between fluids properties (especially dynamic viscosity) will result in larger traveling waves. Gravity effect studies also show that favorable gravity will result in a reduction of heavier fluid thickness and adverse gravity leads to increasing it with respect to the zero gravity condition. However, the magnitude of variation in favorable gravity is much more than adverse gravity.

Keywords: coupled solver, gravitational force, interface tracking, Reynolds number to Froude number, two-phase flow

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

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The widespread use of machine learning applications in production is significantly accelerated by improved computing power and increasing data availability. Predictive quality enables the assurance of product quality by using machine learning models as a basis for decisions on test results. The use of real Bosch production data based on geometric gauge blocks from machining, mating data from assembly and hydraulic measurement data from final testing of directional valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: machine learning, classification, predictive quality, hydraulics, supervised learning

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Authors: Mohammed AL-Hasani

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The Pandemic COVID-19 altered the daily habits and affected the functional performance of the cities after this crisis leaving remarkable impacts on many metropolises worldwide. It is so obvious that having more densification in the city leads to more threats altering this main approach that was called for achieving sustainable development. The main goal to achieve resiliency in the cities, especially in forcing risks, is to deal with a planning system that is able to resist, absorb, accommodate and recover from the impacts that had been affected. Many Cities in London, Wuhan, New York, and others worldwide carried different planning approaches and varied in reaction to safeguard the impacts of the pandemic. The cities globally varied from the radiant pattern predicted by Le Corbusier, or having multi urban centers more like the approach of Frank Lloyd Wright’s Broadacre City, or having linear growth or gridiron expansion that was common by Doxiadis, compact pattern, and many other hygiene patterns. These urban patterns shape the spatial distribution and Identify both open and natural spaces with gentrified and gentrifying areas. This crisis paid attention to reassess many planning approaches and examine the existing urban patterns focusing more on the aim of continuity and resiliency in managing the crises within the rapid transformation and the power of market forces. According to that, this paper hypothesized that those urban planning patterns determine the method of reaction in assuring quarantine for the inhabitance and the performance of public services and need to be updated through carrying out an innovative urban management system and adopt further resilience patterns in prospective urban planning approaches. This paper investigates the adaptivity and resiliency of variant urban planning patterns regarding selected cities worldwide that affected by COVID-19 and their role in applying certain management strategies in controlling the pandemic spread, finding out the main potentials that should be included in prospective planning approaches. The examination encompasses the spatial arrangement, blocks definition, plots arrangement, and urban space typologies. This paper aims to investigate the urban patterns to deliberate also the debate between densification as one of the more sustainable planning approaches and disaggregation tendency that was followed after the pandemic by restructuring and managing its application according to the assessment of the spatial distribution and urban patterns. The biggest long-term threat to dense cities proves the need to shift to online working and telecommuting, creating a mixture between using cyber and urban spaces to remobilize the city. Reassessing spatial design and growth, open spaces, urban population density, and public awareness are the main solutions that should be carried out to face the outbreak in our current cities that should be managed from global to tertiary levels and could develop criteria for designing the prospective cities

Keywords: COVID-19, densification, resiliency, urban patterns

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Authors: Yasin Akgül, Yusuf Polat, Emine Canbay, Ali Kılıç

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Electrospinning is the most common method to produce nanofibers. However, low production rate is still a big challenge for industrial applications of this method. In this study, morphology of nanofibers obtained from namely centrifugal spinning was investigated. Dominant process parameters acting on the fiber diameter and fiber orientation were discussed.

Keywords: centrifugal spinning, electrospinning, nanofiber, TPU nanofibers

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Authors: Mathumalar Loganathan, Lina Syazana, Bryony Dean Franklin

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Background: The therapeutic benefit of self-administered medication for long-term use is limited by an average 50% non-adherence rate. Patient forgetfulness is a common factor in unintentional non-adherence. With a growing ageing population, strategies to improve self-administration of medication adherence are essential. Our aim was to review systematically the effects of interventions to optimise self-administration of medication. Method: Database searched were MEDLINE, EMBASE, PsynINFO, CINAHL from 1980 to 31 October 2013. Search terms included were ‘self-administration’, ‘self-care’, ‘medication adherence’, and ‘intervention’. Two independent reviewers undertook screening and methodological quality assessment, using the Downs and Black rating scale. Results: The search strategy retrieved 6 studies that met the inclusion and exclusion criteria. Three intervention strategies were identified: self-administration medication programme (SAMP), nursing education and medication packaging (pill calendar). A nursing education programme focused on improving patients’ behavioural self-management of drug prescribing. This was the most studied area and three studies highlighting an improvement in self-administration of medication. Conclusion: Results are mixed and there is no one interventional strategy that has proved to be effective. Nevertheless, self-administration of medication programme seems to show most promise. A multi-faceted approach and clearer policy guideline are likely to be required to improve prescribing for these vulnerable patients. Mixed results were found for SAMP. Medication packaging (pill calendar) was evaluated in one study showing a significant improvement in self-administration of medication. A meta-analysis could not be performed due to heterogeneity in the outcome measures.

Keywords: self-administered medication, intervention, prescribing, older patients

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Authors: Nikita Valluri, Vatcharaporn Esichaikul

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With the popularity of data-driven decision making on the rise, this study focuses on providing an alternative outlook towards the process of decision-making. Combining quantitative and qualitative methods rooted in the social sciences, an integrated framework is presented with a focus on delivering a much more robust and efficient approach towards the concept of data-driven decision-making with respect to not only Big data but also 'Thick data', a new form of qualitative data. In support of this, an example from the retail sector has been illustrated where the framework is put into action to yield insights and leverage business intelligence. An interpretive approach to analyze findings from both kinds of quantitative and qualitative data has been used to glean insights. Using traditional Point-of-sale data as well as an understanding of customer psychographics and preferences, techniques of data mining along with qualitative methods (such as grounded theory, ethnomethodology, etc.) are applied. This study’s final goal is to establish the framework as a basis for providing a holistic solution encompassing both the Big and Thick aspects of any business need. The proposed framework is a modified enhancement in lieu of traditional data-driven decision-making approach, which is mainly dependent on quantitative data for decision-making.

Keywords: big data, customer behavior, customer experience, data mining, qualitative methods, quantitative methods, thick data

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Authors: Ashwani Kumar, Jitender Kumar

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In this paper, an optimal power flow based approach has been applied for multi-transactions deregulated environment for ATC determination with SVC and STATCOM. The main contribution of the paper is (i) OPF based approach for evaluation of ATC with multi-transactions, (ii) ATC enhancement with FACTS devices viz. SVC and STATCOM for intact and line contingency cases, (iii) impact of ZIP load on ATC determination and comparison of ATC obtained with SVC and STATCOM. The results have been determined for intact and line contingency cases taking simultaneous as well as single transaction cases for IEEE 24 bus RTS.

Keywords: available transfer capability, FACTS devices, line contingency, multi-transactions, ZIP load model

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Authors: Fahad Hanash Alzahrani

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This paper describes some recent advances in a quickly developing area of data storing and processing based on Data Warehouses and Data Mining techniques, which are associated with software, hardware, data mining algorithms and visualisation techniques having common features for any specific problems and tasks of their implementation.

Keywords: data warehouse, data mining, knowledge discovery in databases, on-line analytical processing

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Authors: Pampita Chakraborty, Sukumar Mukherjee

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The study was done to determine the microbiological profile and changing pattern of the pathogens causing UTI in the ICU patients. All the patients admitted to the ICU with urinary catheter insertion for more than 48hours were included in the study. Urine samples were collected in a sterile container with aseptic precaution using disposable syringe and was processed as per standards. Antimicrobial susceptibility test was done by Disc Diffusion method as per CLSI guidelines. A total of 100 urine samples were collected from ICU patients, out of which 30% showed significant bacterial growth and 7% showed growth of candida spp. Prevalence of UTI was more in female (73%) than male (27.%). Gram-negative bacilli 26(86.67%) were more common in our study followed by gram-positive cocci 4(13.33%). The most common uropathogens isolated were Escherichia coli 14 (46.67%), followed by Klebsiella spp 7(23.33%), Staphylococcus aureus 4(13.33%), Acinetobacter spp 3(10%), Enterococcus faecalis 1(3.33%) and Pseudomonas aeruginosa 1(3.33%). Most of the Gram-negative bacilli were sensitive to amikacin (80%) and nitrofurantoin (80%), where as all gram-positive organisms were sensitive to Vancomycin. A large number ESBL producers were also observed in this study. The study finding showed that E.coli is the predominant pathogen and has increasing resistance pattern to the commonly used antibiotics. The study proposes that the adherence to antibiotic policy is the key ingredients for successful outcome in ICU patients and also emphasizes that repeated evaluation of microbial characteristics and continuous surveillance of resistant bacteria is required for selection of appropriate antibiotic therapy.

Keywords: antimicrobial sensitivity, intensive care unit, nosocomial infection, urinary tract infection

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Authors: Florian Lienert, Peter Costa, Caroline Aurensan, Elaine Melander

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Introduction: Rabies pre-exposure prophylaxis (PrEP) can be given before travel and simplifies post-exposure prophylaxis (PEP). We studied the knowledge about rabies, the uptake of PrEP, and reasons for deciding for or against PrEP in at-risk travelers. We also examined how healthcare professionals (HCPs) counsel on rabies prevention. Methods: On behalf of Bavarian Nordic, Ipsos MORI conducted two online surveys in the USA. Fieldwork from February 24th to April 23rd, 2021, 689 participants aged 18-85 years, visited one of 91 endemic rabies countries in the past 3 years for at least one week, involved in at least 1 of 7 at-risk activities, heard of rabies, positive towards vaccination and chose to take part (surveyed travelers). Secondly, 76 HCPs, with responsibility for advising/ making decisions about vaccination requirements for their patients, personally recommend or prescribe vaccines for rabies, positive towards vaccination and chose to take part (surveyed HCPs). Results: A minority (36%) of surveyed travelers classified rabies as a life-threatening disease. A third of surveyed HCPs (37%) did not discuss rabies vaccination with at-risk travelers, 18% discussed only PEP, 23% only PrEP and 22% both. A minority (21%) of surveyed travelers reported having received rabies vaccination since they were 18. Among those participants (n=145), the most common reasons for deciding to get PrEP were for their own peace of mind (35%) and following an HCP recommendation (32%). Of those who decided not to receive the rabies vaccine (n=319), the most common reasons were that they did not think their risk of rabies was sufficient (23%) and that the HCP did not suggest it (23%). Conclusions: The survey demonstrated knowledge gaps around rabies and low PrEP coverage among surveyed travelers. It also highlighted the role of HCP recommendations and showed that most HCPs did not discuss PrEP with at-risk travelers.

Keywords: rabies, pre-exposure prophylaxis, travel, travel health, post-travel care, rabies treatment, vaccine, post-exposure, prophylaxis, at-risk, education, PrEP, PEP

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Authors: Ali Akbar

Abstract:

The importance of advancing women’s rights is closely intertwined with the development of civil society and the institutionalization of democracy in Middle Eastern countries. There is indeed an intimate relationship between the process of democratization and promoting gender equality, since democracy necessitates equality between men and women. In order to advance the issue of gender equality, what is required is a solid theoretical framework which has its roots in the reexamination of pre-modern interpretation of certain Qurʾānic passages that seem to have given men more rights than it gives women. This paper suggests that those Muslim scholars who adopt a contextualist approach to the Qurʾānic text and its interpretation provide a solid theoretical background for improving women’s rights. Indeed, the aim of the paper is to discuss how the contextualist approach to the Qurʾānic text and its interpretation given by a number of prominent scholars is capable of promoting the issue of gender equality. The paper concludes that since (1) much of the gender inequality found in the primary sources of Islam as well as pre-modern Muslim writings is rooted in the natural cultural norms and standards of early Islamic societies and (2) since the context of today’s world is so different from that of the pre-modern era, the proposed models provide a solid theoretical framework for promoting women’s rights and gender equality.

Keywords: contextualism, gender equality, Islam, the rights of women

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Authors: Roman Khanferyan, Levon Gevorkyan, Ivan Radysh

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Skin barrier dysfunction induces multiple inflammatory skin diseases. Epidemiological studies clearly support the link between most dermatological pathologies, immune disorders and metabolic disorders. Among them most common are psoriasis (PS) and Atopic dermatitis (AD). Psoriasis is a chronic immune-mediated inflammatory skin disease that affects 1.5 to 3.0% of the world's population. Comorbid metabolic disorders play an important role in the progression of PS and AD, as well. It is well known that PS, AD and overweight/obesity are associated with common pathophysiological mechanisms of mild chronic inflammation. The goal of the study was to study the immune disturbances in patients with PS, AD and comorbid metabolic disorders. To study the prevalence of comorbidity of PS and AD (data from 1406 patient’s histories of diseases) were analyzed. The severity of the disease is assessed using the PASI index (Psoriasis Area and Severity Index). 59 patients with psoriasis of different localizations of lesions and severity, as well as with different body mass index (BMI), were examined. The determination of the concentration of pro-inflammatory cytokines (IL-6, IL-8, IFNγ, IL-17, L-18 and TNFa) and chemokines (RANTES, IP-10, MCP-1 and Eotaxin) in sera and supernatants of 48h-cultivated peripheral blood mononuclear cell (PBMC) of psoriasis patients and healthy volunteers (36 adults) have been carried out by multiplex assay (Luminex Corporation, USA). It has been demonstrated that 42% of PS patients had comorbidity with different types of atopies. The most common was bronchial asthma and allergic rhinitis. At the same time, the prevalence of AD in PS patients was determined in 8.7% of patients. It has been shown that serum levels of all studied cytokines (IL-6, IL-8, IFNγ, IL-17, L-18 and TNF) in most of the studied patients were higher in PS patients than in those with AD and healthy controls (p<0.05). An in vitro synthesis of the IL-6 and IFNγ by PBMC demonstrated similar results to those determined in blood sera. There was a high correlation between BMI, immune mediators and the concentrations of adipokines and chemokines (p<0.05). The concentrations of Leptin and Resistin in obese psoriatic patients were greater by 28.6% and 17%, respectively, compared to non-obese psoriatic patients. In obese patients with psoriasis the serum levels of adiponectin were decreased up to 1.3-fold. The mean serum RANTES, IP-10, MCP-1, EOTAXIN levels in obese psoriatic patients were decreased by up to 13.1%, 21.9%, 40.4% and 28.2%, respectively. Similar results have been demonstrated in AD patients with comorbid overweight and obesity. Thus, the study demonstrated the important role of cytokines and chemokines dysregulation in inflammatory skin diseases, especially in patients with comorbid obesity and overweight. Metabolic disorders promote the severity of PS and AD, highly increase immune dysregulation, and synthesis of adipokines, which correlates with the production of proinflammatory immune mediators in comorbid obesity and overweight.

Keywords: psoriasis, atopic dermatitis, pro-inflammatory cytokines, chemokines, comorbid obesity

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Authors: J. Fernandez de Canete, S. Fernandez-Calvo, I. García-Moral

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This paper presents and discusses the application of the object-oriented modelling software SIMSCAPE to hydraulic systems, with particular reference to multivariable proportional-integral-derivative (PID) control. As a result, a particular modelling approach of a double cylinder-piston coupled system is proposed and motivated, and the SIMULINK based PID tuning tool has also been used to select the proper controller parameters. The paper demonstrates the usefulness of the object-oriented approach when both physical modelling and control are tackled.

Keywords: object-oriented modeling, multivariable hydraulic system, multivariable PID control, computer simulation

Procedia PDF Downloads 347

Authors: Jovana M. Ćirković, Aleksandar M. Radojković, Sanja Z. Perać, Jelena N. Jovanović, Zorica M. Branković, Slobodan D. Milanović, Ivan Lj. Milenković, Jovan N. Dobrosavljević, Nemanja V. Simović, Vanja M. Tadić, Ana R. Žugić, Goran O. Branković

Abstract:

The protection of forests is a national interest and of strategic importance in every country. The spongy moth (Lymantria dispar) is a damaging invasive pest that can weaken and destroy trees by defoliating them. Chemical pesticides commonly used to protect forests against spongy moths not only have a negative impact on terrestrial and aquatic organisms/ecosystems but also often fail to provide significant protection. Therefore, many eco-friendly alternatives have been considered. Within this research, a new biopesticide was developed based on the method of nanoencapsulation of plant extracts in a biopolymer matrix, which provides a slow release of the active components during a substantial time period. The antifeedant activity of plant extracts of common (Fraxinus excelsior L.), manna (F. ornus L.) ash tree, and the tree of heaven Ailanthus altissima (Mill.) was tested on the spongy moth (Lymantria dispar L, 1758) larvae. To test the antifeedant activity of these compounds, the choice and non-choice tests in laboratory conditions for different plant extract concentrations (0.01, 0.1, 0.5, and 1 % v/v) were carried out. In both cases, the best results showed formulations based on the tree of heaven and common ash for the concentration of 1%, with deterioration indices of 163 and 132, respectively. The main benefit of these formulations is their versatility, effectiveness, prolonged effect, and because they are completely environmentally acceptable. Therefore, they can be considered for suppression of the spongy moth in forest ecosystems.

Keywords: Ailanthus altissima (Mill.), Fraxinus excelsior L., encapsulation, Lymantria dispar

Procedia PDF Downloads 76