Search results for: Random Data Generation

Authors: Gwo-Hwa Wan, Tai-Ho Hung, Fen-Fang Chung, Wan-Ying Lee, Hui-Ching Yang

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Air pollutant exposure results in elevated concentrations of oxidative stress and inflammatory biomarkers in general populations. Increased concentrations of inflammatory biomarkers in pregnant women would be associated with preterm labor and low birth weight. To our best knowledge, the associations between air pollutants exposure and inflammation in pregnant women and fetuses are unknown, as well as their effects on fetal growth. This study aimed to evaluate the influences of outdoor air pollutants in northern Taiwan areas on the inflammatory biomarker (high sensitivity C-reactive protein, hs-CRP) concentration in the blood of healthy pregnant women and how the biomarker impacts fetal growth. In this study, 38 healthy pregnant women who are in their first trimester and live in northern Taiwan area were recruited from the Taipei Chang Gung Memorial Hospital. Personal characteristics and prenatal examination data (e.g., blood pressure) were obtained from recruited subjects. The concentrations of inflammatory mediators, hs-CRP, in the blood of healthy pregnant women were analyzed. Additionally, hourly data of air pollutants (PM10, SO2, NO2, O3, CO) concentrations were obtained from air quality monitoring stations in Taipei area, established by the Taiwan Environmental Protection Administration. The definition of lag 0 and lag 01 are the exposure to air pollutants on the day of blood withdrawal, and the average exposure to air pollutants one day before and on the day of blood withdrawal, respectively. The statistical analyses were conducted using SPSS software version 22.0 (SPSS, Inc., Chicago, IL, USA). This analytical result indicates that the healthy pregnant women aged between 28 and 42 years old. The body mass index before pregnancy averaged 21.51 (sd = 2.51) kg/m2. Around 90% of the pregnant women had never smoking habit, and 28.95% of them had allergic diseases. Approximately around 84% and 5.26% of the pregnant women worked at indoor and outdoor environments, respectively. The mean hematocrit level of the pregnant women was 37.10%, and the hemoglobin levels were ranged between 10.1 and 14.7 g/dL with 12.47 g/dL of mean value. The blood hs-CRP concentrations of healthy pregnant women in the first trimester ranged between 0.32 and 32.5 mg/L with 2.83 (sd = 5.69) mg/L of mean value. The blood hs-CRP concentrations were positively associated with ozone concentrations at lag 0-14 (r = 0.481, p = 0.017) in healthy pregnant women. Significant lag effects were identified in ozone at lag 0-14 with a positive excess concentration of blood hs-CRP.

Keywords: air pollutant, hs-CRP, pregnant woman, ozone, first trimester

Procedia PDF Downloads 251

Authors: Jean Patrick Mve

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The increasing quest for efficiency, accountability, and transparency has led to the implementation of massive governance reforms among higher education systems worldwide. This is causing many changes in the governance of higher education institutions. Governments over the world are trying to adopt business-like organizational strategies to enhance the performance of higher education institutions. This study explores the changes that have taken place in the Cameroonian higher education sector. It also attempts to draw a picture of the likely future of higher education governance and the actions to be taken for the promotion of institutional effectiveness among higher education institutions. The “governance equalizer” is used as an analytical tool to this end. It covers the five dimensions of the New Public Management (NPM), namely: state regulation, stakeholder guidance, academic self-governance, managerial self-governance, and competition. Qualitative data are used, including semi-structured interviews with key informants at the organizational level and other academic stakeholders, documents and archival data from the university and from the ministry of higher education. It has been found that state regulation among higher education institutions in Cameroon is excessively high, causing the institutional autonomy to be very low, especially at the level of financial management, staffing and promotion, and other internal administrative affairs; at the level of stakeholder guidance there is a higher degree of stakeholders consideration in the academic and research activities among universities, though the government’s interest to keep its hands in most management activities is still high; academic self-governance is also very weak as the assignment of academics is done more on the basis of political considerations than competence; there is no real managerial self-governance among higher education institutions due to the lack of institutional capacity and insufficient autonomy at the level of decision making; there is a plan to promote competition among universities but a real competitive environment is not yet put into place. The study concludes that the government’s policy should make state control more relaxed and concentrate on steering and supervision. As well, real institutional autonomy, professional competence building for top management and stakeholder participation should be considered to guarantee competition and institutional effectiveness.

Keywords: Cameroon higher education, effective institutional governance, governance equalizer, institutional autonomy, institutional effectiveness

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Authors: Tiberiu Boros, Angela Ionita, Maria Visan

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Wildfires are one of the frequent and uncontrollable phenomena that currently affect large areas of the world where the climate, geographic and social conditions make it impossible to prevent and control such events. In this paper we introduce the ground concepts that lie behind the SIAFIM (Satellite Image Analysis for Fire Monitoring) project in order to create a context and we introduce a set of newly created tools that are external to the project but inherently in interventions and complex decision making based on geospatial information and spatial data infrastructures.

Keywords: wildfire, forest fire, natural language processing, mobile applications, communication, GPS

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

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

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

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Authors: Dimuthu Manage

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Introduction: The prevalence of obesity and obesity-related non-communicable diseases are becoming a massive health concern in the whole world. Physical activity is recognized as an effective solution for this matter. The published data on the effectiveness of High-Intensity Interval Training (HIIT) in improving health parameters in overweight and obese individuals in Sri Lanka is sparse. Hence this study is conducted. Methodology: This is a quasi-experimental study that was conducted at the Sports medicine clinic, General Hospital, Kalutara. Participants have engaged in a programme of HIIT three times per week for six weeks. Data collection was based on precise measurements by using structured and validated methods. Ethical clearance was obtained. Results: Registered number for the study was 48, and only 52% have completed the study. The mean age was 32 (SD=6.397) years, with 64% males. All the anthropometric measurements which were assessed (i.e. waist circumference(P<0.001), weight(P<0.001) and BMI(P<0.001)), body fat percentage(P<0.001), VO2 max(P<0.001), and lipid profile (ie. HDL(P=0.016), LDL(P<0.001), cholesterol(P<0.001), triglycerides(P<0.010) and LDL: HDL(P<0.001)) had shown statistically significant improvement after the intervention with the HIIT programme. Conclusions: This study confirms HIIT as a time-saving and effective exercise method, which helps in preventing obesity as well as non-communicable diseases. HIIT ameliorates body anthropometry, fat percentage, cardiopulmonary status, and lipid profile in overweight and obese individuals markedly. As with the majority of studies, the design of the current study is subject to some limitations. The first is the study focused on a correlational study. If it is a comparative study, comparing it with other methods of training programs would have given more validity. Although the validated tools used to measure variables and the same tools used in pre and post-exercise occasions with the available facilities, it would have been better to measure some of them using gold-standard methods. However, this evidence should be further assessed in larger-scale trials using comparative groups to generalize the efficacy of the HIIT exercise program.

Keywords: HIIT, lipid profile, BMI, VO2 max

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Authors: Shishay Kidanu, Abdullah Alhaj

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

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

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Authors: Satya Narayan

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India, a rapidly growing economy with a burgeoning population, grapples with the dual challenge of meeting rising energy demands and reducing its carbon footprint. Geothermal energy, an often overlooked and underutilized renewable source, holds immense potential for addressing this challenge. Geothermal resources offer a valuable, consistent, and sustainable energy source, and may significantly contribute to India's energy. This paper discusses the importance of geothermal exploration in India, emphasizing its role in achieving sustainable energy production while mitigating environmental impacts. It also delves into the methodology employed to assess geothermal resource feasibility, including geophysical surveys and borehole drilling. The results and discussion sections highlight promising geothermal sites across India, illuminating the nation's vast geothermal potential. It detects potential geothermal reservoirs, characterizes subsurface structures, maps temperature gradients, monitors fluid flow, and estimates key reservoir parameters. Globally, geothermal energy falls into high and low enthalpy categories, with India mainly having low enthalpy resources, especially in hot springs. The northwestern Himalayan region boasts high-temperature geothermal resources due to geological factors. Promising sites, like Puga Valley, Chhumthang, and others, feature hot springs suitable for various applications. The Son-Narmada-Tapti lineament intersects regions rich in geological history, contributing to geothermal resources. Southern India, including the Godavari Valley, has thermal springs suitable for power generation. The Andaman-Nicobar region, linked to subduction and volcanic activity, holds high-temperature geothermal potential. Geophysical surveys, utilizing gravity, magnetic, seismic, magnetotelluric, and electrical resistivity techniques, offer vital information on subsurface conditions essential for detecting, evaluating, and exploiting geothermal resources. The gravity and magnetic methods map the depth of the mantle boundary (high-temperature) and later accurately determine the Curie depth. Electrical methods indicate the presence of subsurface fluids. Seismic surveys create detailed sub-surface images, revealing faults and fractures and establishing possible connections to aquifers. Borehole drilling is crucial for assessing geothermal parameters at different depths. Detailed geochemical analysis and geophysical surveys in Dholera, Gujarat, reveal untapped geothermal potential in India, aligning with renewable energy goals. In conclusion, geophysical surveys and borehole drilling play a pivotal role in economically viable geothermal site selection and feasibility assessments. With ongoing exploration and innovative technology, these surveys effectively minimize drilling risks, optimize borehole placement, aid in environmental impact evaluations, and facilitate remote resource exploration. Their cost-effectiveness informs decisions regarding geothermal resource location and extent, ultimately promoting sustainable energy and reducing India's reliance on conventional fossil fuels.

Keywords: geothermal resources, geophysical methods, exploration, exploitation

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Authors: Andrew N. Saylor, James R. Peters

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Scoliosis is a complex 3D deformity of the thoracic and lumbar spines, clinically diagnosed by measurement of a Cobb angle of 10 degrees or more on a coronal X-ray. The Cobb angle is the angle made by the lines drawn along the proximal and distal endplates of the respective proximal and distal vertebrae comprising the curve. Traditionally, Cobb angles are measured manually using either a marker, straight edge, and protractor or image measurement software. The task of measuring the Cobb angle can also be represented by a function taking the spine geometry rendered using X-ray imaging as input and returning the approximate angle. Although the form of such a function may be unknown, it can be approximated using artificial neural networks (ANNs). The performance of ANNs is affected by many factors, including the choice of activation function and network architecture; however, the effects of these parameters on the accuracy of scoliotic deformity measurements are poorly understood. Therefore, the objective of this study was to systematically investigate the effect of ANN architecture and activation function on Cobb angle measurement from the coronal X-rays of scoliotic subjects. The data set for this study consisted of 609 coronal chest X-rays of scoliotic subjects divided into 481 training images and 128 test images. These data, which included labeled Cobb angle measurements, were obtained from the SpineWeb online database. In order to normalize the input data, each image was resized using bi-linear interpolation to a size of 500 × 187 pixels, and the pixel intensities were scaled to be between 0 and 1. A fully connected (dense) ANN with a fixed cost function (mean squared error), batch size (10), and learning rate (0.01) was developed using Python Version 3.7.3 and TensorFlow 1.13.1. The activation functions (sigmoid, hyperbolic tangent [tanh], or rectified linear units [ReLU]), number of hidden layers (1, 3, 5, or 10), and number of neurons per layer (10, 100, or 1000) were varied systematically to generate a total of 36 network conditions. Stochastic gradient descent with early stopping was used to train each network. Three trials were run per condition, and the final mean squared errors and mean absolute errors were averaged to quantify the network response for each condition. The network that performed the best used ReLU neurons had three hidden layers, and 100 neurons per layer. The average mean squared error of this network was 222.28 ± 30 degrees2, and the average mean absolute error was 11.96 ± 0.64 degrees. It is also notable that while most of the networks performed similarly, the networks using ReLU neurons, 10 hidden layers, and 1000 neurons per layer, and those using Tanh neurons, one hidden layer, and 10 neurons per layer performed markedly worse with average mean squared errors greater than 400 degrees2 and average mean absolute errors greater than 16 degrees. From the results of this study, it can be seen that the choice of ANN architecture and activation function has a clear impact on Cobb angle inference from coronal X-rays of scoliotic subjects.

Keywords: scoliosis, artificial neural networks, cobb angle, medical imaging

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Authors: Ilias A. Makris

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In this work, we attempt to analyse the contribution of innovative activities to firm performance and growth. We examine economic data from some of the economies that were heavily affected by current economic crisis: the countries of southern Europe (Portugal, Italy, Greece, and Spain) and Ireland. Following literature, an appropriate econometric model is developed and several indicators are tested in order to disclose possible relation with innovative activity. Findings confirm the crucial effect of innovative process in economic activity, in firm and country level.

Keywords: Eurozone periphery, firm performance, innovative activity, R&D

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Authors: A. Brunel, A. Kernevez, F. Leclere, J. Trenteseaux

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Today, wine quality is only evaluated by wine experts with their own different personal tastes, even if they may agree on some common features. So producers do not have any unbiased way to independently assess the quality of their products. A tool is here proposed to evaluate wine quality by an objective ranking based upon the variables entering wine elaboration, and analysed through principal component analysis (PCA) method. Actual climatic data are compared by measuring the relative distance between each considered wine, out of which the general ranking is performed.

Keywords: wine, grape, weather conditions, rating, climate, principal component analysis, metric analysis

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Authors: Ehsan K. Hazaveh

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This research project explores creative methods of storytelling through photography to portray a vulnerable and marginalised community: former refugees living in Wellington, New Zealand. The project explores photographic representational techniques that can not only empower and give voice to those communities but also challenge dominant stereotypes about refugees and support humanitarian actions. The aims of this study are to develop insights surrounding issues associated with the photographic representation of refugees and to explore the collaborative construction of possible counter-narratives that might lead to the formulation of a practice framework for representing refugees using photography. In other words, the goal of this study is to explore representational and narrative strategies that frame refugees as active community members and as individuals with specific histories and expertise. These counter-narratives will bring the diversity of refugees to the surface by offering personal stories, contextualising their experience, raising awareness about the plight and human rights of the refugee community in New Zealand, evoking empathy and, therefore, facilitating the process of social change. The study has designed a photographic narrative framework by determining effective methods of photo storytelling, framing, and aesthetic techniques, focusing on different ways of taking, selecting, editing and curating photographs. Photo elicitation interviews have been used to ‘explore’, ‘produce’ and ‘co-curate’ the counter-narrative along with participants. Photo elicitation is a qualitative research method that employs images to evoke data in order to find out how other people experience their world - the researcher shows photographs to the participant and asks open-ended questions to get them to talk about their life experiences and the world around them. The qualitative data have been collected and produced through interactions with four former refugees living in Wellington, New Zealand. In this way, this project offers a unique account of their conditions and basic knowledge about their living experience and their stories. The participants of this study have engaged with PhotoVoice, a photo elicitation methodology that employs photography and storytelling, to share activities, emotions, hopes, and aspects of their lived experiences. PhotoVoice was designed to empower members of marginalised populations. It involves a series of meeting sessions, in which participants share photographs they have taken and discuss stories about the photographs to identify, represent, and enhance the issues important to their lives and communities. Finally, the data provide a basis for systematically producing visual counter-narratives that highlight the experiences of former- refugees. By employing these methods, refugees can represent their world as well as interpret it. The process of developing this research framing has enabled the development of powerful counter-narratives that challenge prevailing stereotypical depictions which in turn have the potential to shape improved humanitarian outcomes, shifts in public attitudes and political perspectives in New Zealand.

Keywords: media, photography, refugees, photo-elicitation, storytelling

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Authors: Thi Phuong Pham

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This paper explores the intricate relationships between Sustainable Supply Chain Management (SSCM) practices, digital transformation (DT), and enterprise performance within the context of Vietnam. Over the past two decades, there has been a paradigm shift in supply chain management, with sustainability gaining prominence due to increasing concerns about climate change, labor practices, and the environmental impact of business operations. In the ever-evolving realm of global business, sustainability and digital transformation (DT) intersecting dynamics have become pivotal catalysts for organizational success. This research investigates how integrating SSCM with DT can enhance enterprise performance, a subject of significant relevance as Vietnam undergoes rapid economic growth and digital transformation. The primary objectives of this research are twofold: (1) to examine the effects of SSCM practices on enterprise performance in three critical aspects: economic, environmental, and social performance in Vietnam and (2) to explore the mediating role of DT in this relationship. By analyzing these dynamics, the study aims to provide valuable insights for policymakers and the academic community regarding the potential benefits of aligning SSCM principles with digital technologies. To achieve these objectives, the research employs a robust mixed-method approach. The research begins with a comprehensive literature review to establish a theoretical framework that underpins the empirical analysis. Data collection was conducted through a structured survey targeting Vietnamese enterprises, with the survey instrument designed to measure SSCM practices, DT, and enterprise performance using a five-point Likert scale. The reliability and validity of the survey were ensured by pre-testing with industry practitioners and refining the questionnaire based on their feedback. For data analysis, structural equation modeling (SEM) was employed to quantify the direct effects of SSCM on enterprise performance, while mediation analysis using the PROCESS Macro 4.0 in SPSS was conducted to assess the mediating role of DT. The findings reveal that SSCM practices positively influence enterprise performance by enhancing operational efficiency, reducing costs, and improving sustainability metrics. Furthermore, DT acts as a significant mediator, amplifying the positive impacts of SSCM practices through improved data management, enhanced communication, and more agile supply chain processes. These results underscore the critical role of DT in maximizing the benefits of SSCM practices, particularly in a developing economy like Vietnam. This research contributes to the existing body of knowledge by highlighting the synergistic effects of SSCM and DT on enterprise performance. It offers practical implications for businesses that enhance their sustainability and digital capabilities, providing a roadmap for integrating these two pivotal aspects to achieve competitive advantage. The study's insights can also inform governmental policies designed to foster sustainable economic growth and digital innovation in Vietnam.

Keywords: sustainable supply chain management, digital transformation, enterprise performance, Vietnam

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Authors: Komal Niazi, He Guoqiang

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This paper is focused on ‘CPEC (China Pakistan Economic Corridor) a changing mechanism in Pakistan’. China Pakistan Economic Corridor (CPEC) activity under OBOR (One Belt One Road (OBOR) CPEC is a piece of the bigger umbrella and goes for giving another hallway of exchange for China and Pakistan and is relied upon to profit the entire of South Asian area. But this study reveals that significance of acculturation can never be overemphasized in the investigation of diverse impacts and the routes people groups of various ethnic personalities figure out how to adjust and acknowledge the social attributes of a larger part group in a multiethnic culture. This study also deals with the effects of acculturation which can be seen at multiple levels through CPEC for both Pakistani and Chinese people, who were working on this project. China and Pakistan exchanged the cultural and social patterns with each other. Probably the most perceptible gathering level impacts of cultural assimilation regularly incorporate changes in sustenance (food), clothing, and language. At the individual level, the procedure of cultural assimilation alludes to the socialization procedure by which the Pakistani local people and Chinese who were working in Pakistan adopted values, traditions, attitudes, states of mind, and practices. But China has imposed discourse through economic power and language. CPEC dominates Pakistan’s poor area’s and changes their living, social and cultural values. People also claimed this acculturation was a great threat to their cultural values and religious beliefs. Main findings of the study clearly ascertained that research was to find out the conceptual understanding of people about the acculturation process through CPEC. At the cultural level, aggregate activities and social organizations end up plainly adjusted, and at the behavioral level, there are changes in a person's day by day behavioral collection and some of the time in experienced anxiety. Anthropological data methods were used to collect data, like snowball and judgmental sampling, case studied methods.

Keywords: CPEC, acculturation process, language discourse, social norms, cultural values, religious beliefs

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Authors: Usoro Anthony E., Udoh Emediong

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Diagonal Vector Autoregressive Models are special classes of the general vector autoregressive models identified under certain conditions, where parameters are restricted to the diagonal elements in the coefficient matrices. Variance, autocovariance, and autocorrelation properties of the upper and lower diagonal VAR models are derived. The new set of VAR models is verified with empirical data and is found to perform favourably with the general VAR models. The advantage of the diagonal models over the existing models is that the new models are parsimonious, given the reduction in the interactive coefficients of the general VAR models.

Keywords: VAR models, diagonal VAR models, variance, autocovariance, autocorrelations

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Authors: Warnakulasuriya Arachichige Malisha Ann Rosary Fernando, Udalamatta Gamage Omila Chalanka Jinadasa, Bihini Pabasara Amandi Amarasinghe, Manul Thisuraka Mandalawatta, Uthpala Samarakoon, Manori Gamage

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The surge in sexually transmitted diseases (STDs) has become a critical public health crisis demanding urgent attention and action. Like many other nations, Sri Lanka is grappling with a significant increase in STDs due to a lack of education and awareness regarding their dangers. Presently, the available applications for tracking and managing STDs cover only a limited number of easily detectable infections, resulting in a significant gap in effectively controlling their spread. To address this gap and combat the rising STD rates, it is essential to leverage technology and data. Employing technology to enhance the tracking and management of STDs is vital to prevent their further propagation and to enable early intervention and treatment. This requires adopting a comprehensive approach that involves raising public awareness about the perils of STDs, improving access to affordable healthcare services for early detection and treatment, and utilizing advanced technology and data analysis. The proposed mobile application aims to cater to a broad range of users, including STD patients, recovered individuals, and those unaware of their STD status. By harnessing cutting-edge technologies like image detection, symptom-based identification, prevention methods, doctor and clinic recommendations, and virtual counselor chat, the application offers a holistic approach to STD management. In conclusion, the escalating STD rates in Sri Lanka and across the globe require immediate action. The integration of technology-driven solutions, along with comprehensive education and healthcare accessibility, is the key to curbing the spread of STDs and promoting better overall public health.

Keywords: STD, machine learning, NLP, artificial intelligence

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Authors: Maria Cristina Tommaso, Maria Das Graças L. Silva, Carlos Jose Pacheco

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Have the advances of the Brazilian legislation reflected or have been consonant with the inclusion of PwD in higher education? In 1990 the World Declaration on Education for All, a document organized by the United Nations Educational, Scientific and Cultural Organization (UNESCO), stated that the basic learning needs of people with disabilities, as they were called, required special attention. Since then, legislation in signatory countries such as Brazil has made considerable progress in guaranteeing, in a gradual and increasing manner, the rights of persons with disabilities to education. Principles, policies, and practices of special educational needs were created and guided action at the regional, national and international levels on the structure of action in Special Education such as administration, recruitment of educators and community involvement. Brazilian Education Law No. 3.284 of 2003 ensures inclusion of people with disabilities in Brazilian higher education institutions and also in 2015 the Law 13,146/2015 - Brazilian Law on the Inclusion of Persons with Disabilities (Statute of the Person with Disabilities) regulates the inclusion of PwD by the guarantee of their rights. This study analyses data related to people with disability inclusion in High Education in the south region of Rio de Janeiro State - Brazil during the period between 2008 and 2018, based in its correlation with the changes in the Brazilian legislation in the last ten years that were subjected by PwD inclusion processes in the Brazilian High Education Systems. The region studied is composed by sixteen cities and this research refers to the largest one, Volta Redonda that represents 25 percent of the total regional population. The PwD reception process had the dicing data at the Volta Redonda University Center with 35 percent of high education students in this territorial area. The research methodology analyzed the changes occurring in the legislation about the inclusion of people with disability in High Education in the last ten years and its impacts on the samples of this study during the period between 2008 and 2018. It was verified an expressive increasing of the number of PwD students, from two in 2008 to 190 PwD students in 2018. The data conclusions are presented in quantitative terms and the aim of this study was to verify the effectiveness of the PwD inclusion in High Education, allowing visibility of this social group. This study verified that the fundamental human rights guarantees have a strong relation to the advances of legislation and the State as a guarantor instance of the rights of the people with disability and must be considered a mean of consolidation of their education opportunities isonomy. The recognition of full rights and the inclusion of people with disabilities requires the efforts of those who have decision-making power. This study aimed to demonstrate that legislative evolution is an effective instrument in the social integration of people with disabilities. The study confirms the fundamental role of the state in guaranteeing human rights and demonstrates that legislation not only protects the interests of vulnerable social groups, but can also, and this is perhaps its main mission, to change behavior patterns and provoke the social transformation necessary to the reduction of inequality of opportunity.

Keywords: high education, inclusion, legislation, people with disability

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Authors: Karisma Karisma, Pardis Moslemzadeh Tehrani

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This study aims to conduct a high-level strategic dialogue on the lack of consensus, consistency, and legal certainty regarding blockchain-based energy prosumerism so that appropriate institutional and governance structures can be put in place to address the inadequacies and gaps in the legal and regulatory framework. The drive to achieve national and global decarbonization targets is a driving force behind climate goals and policies under the Paris Agreement. In recent years, efforts to ‘demonopolize’ and ‘decentralize’ energy generation and distribution have driven the energy transition toward decentralized systems, invoking concepts such as ownership, sovereignty, and autonomy of RE sources. The emergence of individual and collective forms of prosumerism and the rapid diffusion of blockchain is expected to play a critical role in the decarbonization and democratization of energy systems. However, there is a ‘regulatory void’ relating to individual and collective forms of prosumerism that could prevent the rapid deployment of blockchain systems and potentially stagnate the operationalization of blockchain-enabled energy sharing and trading activities. The application of broad and facile regulatory fixes may be insufficient to address the major regulatory gaps. First, to the authors’ best knowledge, the concepts and elements circumjacent to individual and collective forms of prosumerism have not been adequately described in the legal frameworks of many countries. Second, there is a lack of legal certainty regarding the creation and adaptation of business models in a highly regulated and centralized energy system, which inhibits the emergence of prosumer-driven niche markets. There are also current and prospective challenges relating to the legal status of blockchain-based platforms for facilitating energy transactions, anticipated with the diffusion of blockchain technology. With the rise of prosumerism in the energy sector, the areas of (a) network charges, (b) energy market access, (c) incentive schemes, (d) taxes and levies, and (e) licensing requirements are still uncharted territories in many countries. The uncertainties emanating from this area pose a significant hurdle to the widespread adoption of blockchain technology, a complementary technology that offers added value and competitive advantages for energy systems. The authors undertake a conceptual and theoretical investigation to elucidate the lack of consensus, consistency, and legal certainty in the study of blockchain-based prosumerism. In addition, the authors set an exploratory tone to the discussion by taking an analytically eclectic approach that builds on multiple sources and theories to delve deeper into this topic. As an interdisciplinary study, this research accounts for the convergence of regulation, technology, and the energy sector. The study primarily adopts desk research, which examines regulatory frameworks and conceptual models for crucial policies at the international level to foster an all-inclusive discussion. With their reflections and insights into the interaction of blockchain and prosumerism in the energy sector, the authors do not aim to develop definitive regulatory models or instrument designs, but to contribute to the theoretical dialogue to navigate seminal issues and explore different nuances and pathways. Given the emergence of blockchain-based energy prosumerism, identifying the challenges, gaps and fragmentation of governance regimes is key to facilitating global regulatory transitions.

Keywords: blockchain technology, energy sector, prosumer, legal and regulatory.

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Authors: Jonghyuk Yoon, Hyoungwoon Song

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Recently, there are lots of increasing interest in a smart farming that represents application of modern Information and Communication Technologies (ICT) into agriculture since it provides a methodology to optimize production efficiencies by managing growing conditions of crops automatically. In order to obtain high performance and stability for smart greenhouse, it is important to identify the effect of various working parameters such as capacity of ventilation fan, vent opening area and etc. In the present study, a 3-dimensional CFD (Computational Fluid Dynamics) simulation for single-span greenhouse was conducted using the commercial program, Ansys CFX 18.0. The numerical simulation for single-span greenhouse was implemented to figure out the internal thermal and flow characteristics. In order to numerically model solar radiation that spread over a wide range of wavelengths, the multiband model that discretizes the spectrum into finite bands of wavelength based on Wien’s law is applied to the simulation. In addition, absorption coefficient of vinyl varied with the wavelength bands is also applied based on Beer-Lambert Law. To validate the numerical method applied herein, the numerical results of the temperature at specific monitoring points were compared with the experimental data. The average error rates (12.2~14.2%) between them was shown and numerical results of temperature distribution are in good agreement with the experimental data. The results of the present study can be useful information for the design of various greenhouses. This work was supported by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries (IPET) through Advanced Production Technology Development Program, funded by Ministry of Agriculture, Food and Rural Affairs (MAFRA)(315093-03).

Keywords: single-span greenhouse, CFD (computational fluid dynamics), solar radiation, multiband model, absorption coefficient

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Authors: Yenny Paola Morales Cortés, Fabián Rico Rodríguez, Juan Carlos Serrato Bermúdez, Carlos Arturo Martínez Riascos

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Numerous benefits of galactooligosaccharides (GOS) as prebiotics have motivated the study of enzymatic processes for their production. These processes have special complexities due to several factors that make difficult high productivity, such as enzyme type, reaction medium pH, substrate concentrations and presence of inhibitors, among others. In the present work the production of galactooligosaccharides (with different degrees of polymerization: two, three and four) from lactose was studied. The study considers the formulation of a mathematical model that predicts the production of GOS from lactose using the enzyme β-galactosidase. The effect of pH in the reaction was studied. For that, phosphate buffer was used and with this was evaluated three pH values (6.0.6.5 and 7.0). Thus it was observed that at pH 6.0 the enzymatic activity insignificant. On the other hand, at pH 7.0 the enzymatic activity was approximately 27 times greater than at 6.5. The last result differs from previously reported results. Therefore, pH 7.0 was chosen as working pH. Additionally, the enzyme concentration was analyzed, which allowed observing that the effect of the concentration depends on the pH and the concentration was set for the following studies in 0.272 mM. Afterwards, experiments were performed varying the lactose concentration to evaluate its effects on the process and to generate the data for the adjustment of the mathematical model parameters. The mathematical model considers the reactions of lactose hydrolysis and transgalactosylation for the production of disaccharides and trisaccharides, with their inverse reactions. The production of tetrasaccharides was negligible and, because of that, it was not included in the model. The reaction was monitored by HPLC and for the quantitative analysis of the experimental data the Matlab programming language was used, including solvers for differential equations systems integration (ode15s) and nonlinear problems optimization (fminunc). The results confirm that the transgalactosylation and hydrolysis reactions are reversible, additionally inhibition by glucose and galactose is observed on the production of GOS. In relation to the production process of galactooligosaccharides, the results show that it is necessary to have high initial concentrations of lactose considering that favors the transgalactosylation reaction, while low concentrations favor hydrolysis reactions.

Keywords: β-galactosidase, galactooligosaccharides, inhibition, lactose, Matlab, modeling

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Authors: Mamert Mbonimpa, Ousseynou Kanteye, Élysée Tshibangu Ngabu, Rachid Amrou, Abdelkabir Maqsoud, Tikou Belem

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The management of mine wastes (waste rocks and tailings) containing sulphide minerals such as pyrite and pyrrhotite represents the main environmental challenge for the mining industry. Indeed, acid mine drainage (AMD) can be generated when these wastes are exposed to water and air. AMD is characterized by low pH and high concentrations of heavy metals, which are toxic to plants, animals, and humans. It affects the quality of the ecosystem through water and soil pollution. Different techniques involving soil materials can be used to control AMD generation, including impermeable covers (compacted clays) and oxygen barriers. The latter group includes covers with capillary barrier effects (CCBE), a multilayered cover that include the moisture retention layer playing the role of an oxygen barrier. Once AMD is produced at a mine site, it must be treated so that the final effluent at the mine site complies with regulations and can be discharged into the environment. Active neutralization with lime is one of the treatment methods used. This treatment produces sludge that is usually stored in sedimentation ponds. Other sludge management alternatives have been examined in recent years, including sludge co-disposal with tailings or waste rocks, disposal in underground mine excavations, and storage in technical landfill sites. Considering the ability of AMD neutralization sludge to maintain an alkaline to neutral pH for decades or even centuries, due to the excess alkalinity induced by residual lime within the sludge, valorization of sludge in specific applications could be an interesting management option. If done efficiently, the reuse of sludge could free up storage ponds and thus reduce the environmental impact. It should be noted that mixtures of sludge and soils could potentially constitute usable materials in CCBE for the rehabilitation of acid-generating mine sites, while sludge alone is not suitable for this purpose. The high sludge water content (up to 300%), even after sedimentation, can, however, constitute a geotechnical challenge. Adding lime to the mixtures can reduce the water content and improve the geotechnical properties. The objective of this paper is to investigate the impact of the sludge content (30, 40 and 50%) in sand-sludge mixtures (SSM) on their hydrogeotechnical properties (compaction, shrinkage behaviour, saturated hydraulic conductivity, and water retention curve). The impact of lime addition (dosages from 2% to 6%) on the moisture content, dry density after compaction and saturated hydraulic conductivity of SSM was also investigated. Results showed that sludge adding to sand significantly improves the saturated hydraulic conductivity and water retention capacity, but the shrinkage increased with sludge content. The dry density after compaction of lime-treated SSM increases with the lime dosage but remains lower than the optimal dry density of the untreated mixtures. The saturated hydraulic conductivity of lime-treated SSM after 24 hours of cure decreases by 3 orders of magnitude. Considering the hydrogeotechnical properties obtained with these mixtures, it would be possible to design CCBE whose moisture retention layer is made of SSM. Physical laboratory models confirmed the performance of such CCBE.

Keywords: mine waste, AMD neutralization sludge, sand-sludge mixture, hydrogeotechnical properties, mine site reclamation, CCBE

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Authors: Thomas Monahan, Nicolas Gorius, Thanh Nguyen

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Exoplanet atmospheric parameters retrieval is a complex, computationally intensive, inverse modeling problem in which an exoplanet’s atmospheric composition is extracted from an observed spectrum. Traditional Bayesian sampling methods require extensive time and computation, involving algorithms that compare large numbers of known atmospheric models to the input spectral data. Runtimes are directly proportional to the number of parameters under consideration. These increased power and runtime requirements are difficult to accommodate in space missions where model size, speed, and power consumption are of particular importance. The use of traditional Bayesian sampling methods, therefore, compromise model complexity or sampling accuracy. The Atmospheric Retrievals conditional Generative Adversarial Network (ARcGAN) is a deep convolutional generative adversarial network that improves on the previous model’s speed and accuracy. We demonstrate the efficacy of artificial intelligence to quickly and reliably predict atmospheric parameters and present it as a viable alternative to slow and computationally heavy Bayesian methods. In addition to its broad applicability across instruments and planetary types, ARcGAN has been designed to function on low power application-specific integrated circuits. The application of edge computing to atmospheric retrievals allows for real or near-real-time quantification of atmospheric constituents at the instrument level. Additionally, edge computing provides both high-performance and power-efficient computing for AI applications, both of which are critical for space missions. With the edge computing chip implementation, ArcGAN serves as a strong basis for the development of a similar machine-learning algorithm to reduce the downlinked data volume from the Compact Ultraviolet to Visible Imaging Spectrometer (CUVIS) onboard the DAVINCI mission to Venus.

Keywords: deep learning, generative adversarial network, edge computing, atmospheric parameters retrieval

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Authors: Hakimeh Masoudigavgani

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Since manufacturing firms deplete non-renewable resources and pollute air, soil, and water in greatly unsustainable manner, industrial activities or production of products are considered to be a key contributor to adverse environmental impacts. Hence, management strategies and approaches that involve an effective supply chain decision process in a manufacturing sector could be extremely significant to the application of environmental initiatives. Green manufacturing (GM) is one of these strategies which minimises negative effects on the environment through reducing greenhouse gas emissions, waste, and the consumption of energy and natural resources. This paper aims to explore what greening methods and mechanisms could be applied in the manufacturing supply chain and what are the outcomes of adopting these methods in terms of abating environmental burdens? The study is an interpretive research with an exploratory approach, using thematic analysis by coding text, breaking down and grouping the content of collected literature into various themes and categories. It is found that green supply chain could be attained through execution of some pre-production strategies including green building, eco-design, and green procurement as well as a number of in-production and post-production strategies involving green manufacturing and green logistics. To achieve an effective GM, the pre-production strategies are suggested to be employed. This paper defines GM as (1) the analysis of the ecological impacts generated by practices, products, production processes, and operational functions, and (2) the implementation of greening methods to reduce damaging influences of them on the natural environment. Analysis means assessing, monitoring, and auditing of practices in order to measure and pinpoint their harmful impacts. Moreover, greening methods involved within GM (arranged in order from the least to the most level of environmental compliance and techniques) consist of: •product stewardship (e.g. less use of toxic, non-renewable, and hazardous materials in the manufacture of the product; and stewardship of the environmental problems with regard to the product in all production, use, and end-of-life stages); •process stewardship (e.g. controlling carbon emission, energy and resources usage, transportation method, and disposal; reengineering polluting processes; recycling waste materials generated in production); •lean and clean production practices (e.g. elimination of waste, materials replacement, materials reduction, resource-efficient consumption, energy-efficient usage, emission reduction, managerial assessment, waste re-use); •use of eco-industrial parks (e.g. a shared warehouse, shared logistics management system, energy co-generation plant, effluent treatment). However, the focus of this paper is only on methods related to the in-production phase and needs further research on both pre-production and post-production environmental innovations. The outlined methods in this investigation may possibly be taken into account by policy/decision makers. Additionally, the proposed future research direction and identified gaps can be filled by scholars and researchers. The paper compares and contrasts a variety of viewpoints and enhances the body of knowledge by building a definition for GM through synthesising literature and categorising the strategic concept of greening methods, drivers, barriers, and successful implementing tactics.

Keywords: green manufacturing (GM), product stewardship, process stewardship, clean production, eco-industrial parks (EIPs)

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Authors: Amanina Iymia Jeffree, Reena Thriumani, Mohammad Iqbal Omar, Ammar Zakaria, Yumi Zuhanis Has-Yun Hashim, Ali Yeon Md Shakaff

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Metabolite profiling is a strategy to be approached in the pattern recognition method focused on three types of cancer cell line that driving the most to death specifically lung, breast, and colon cancer. The purpose of this study was to discriminate the VOCs pattern among cancerous and control group based on metabolite profiling. The sampling was executed utilizing the cell culture technique. All culture flasks were incubated till 72 hours and data collection started after 24 hours. Every running sample took 24 minutes to be completed accordingly. The comparative metabolite patterns were identified by the implementation of headspace-solid phase micro-extraction (HS-SPME) sampling coupled with gas chromatography-mass spectrometry (GCMS). The optimizations of the main experimental variables such as oven temperature and time were evaluated by response surface methodology (RSM) to get the optimal condition. Volatiles were acknowledged through the National Institute of Standards and Technology (NIST) mass spectral database and retention time libraries. To improve the reliability of significance, it is of crucial importance to eliminate background noise which data from 3rd minutes to 17th minutes were selected for statistical analysis. Targeted metabolites, of which were annotated as known compounds with the peak area greater than 0.5 percent were highlighted and subsequently treated statistically. Volatiles produced contain hundreds to thousands of compounds; therefore, it will be optimized by chemometric analysis, such as principal component analysis (PCA) as a preliminary analysis before subjected to a pattern classifier for identification of VOC samples. The volatile organic compound profiling has shown to be significantly distinguished among cancerous and control group based on metabolite profiling.

Keywords: in vitro cancer cell line, metabolite profiling, pattern recognition, volatile organic compounds

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Authors: Ibrahim Yerima Gwalem, Jamila Ahmed Buhari

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In recent years, there has been an alarming rate of increase in the costs of building materials in Nigeria, and this ugly phenomenon threatens the contributions of the construction industry in national development. The purpose of this study was to assess the effects of the rising cost of building materials in Adamawa State Nigeria. Four research questions in line with the purpose of the study were raised to guide the study. Two null hypotheses were formulated and tested at 0.05 level of significance. The study adopted a survey research design. The population of the study comprises registered contractors, registered builders, selected merchants, and consultants in Adamawa state. Data were collected using researcher designed instrument tagged effects of the rising cost of building materials questionnaire (ERCBMQ). The instrument was subjected to face and content validation by two experts, one from Modibbo Adama University of Technology Yola and the other from Federal Polytechnic Mubi. The reliability of the instrument was determined by the Cronbach Alpha method and yielded a reliability index of 0.85 high enough to ascertain the reliability. Data collected from a field survey of 2019 was analyzed using mean and percentage. The means of the prices were used in the calculations of price indices and rates of inflation on building materials. Findings revealed that factors responsible for the rising cost of building materials are the exchange rate of the Nigeria Naira with a mean rating (MR) = 4.4; cost of fuel and power supply, MR = 4.3; and changes in government policies and legislation, MR = 4.2, while fluctuations in the construction cost with MR = 2.8; reduced volume of construction output, MR = 2.52; and risk of project abandonment, MRA = 2.51, were the three effects. The study concluded that adverse effects could result in a downward effect on the contributions of the construction industries on the gross domestic product (GDP) in the nation’s economy. Among the recommendations proffered include that the government should formulate a policy that will play down the agitations on the use of imported building materials by encouraging research in the production of local building materials.

Keywords: effects, rising, cost, building, materials

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Authors: Douglas F. Prawitt, Nathan Y. Sharp, David A. Wood

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Consistent with prior experimental and survey studies, we find that IAFs that spend more time directly assisting the external auditor is associated with lower external audit fees. Interestingly, we do not find evidence that external auditors reduce fees based on work previously performed by the IAF. We also find that the time spent assisting the external auditor has a greater negative effect on external audit fees than the time spent performing tasks upon which the auditor may rely but that are not performed as direct assistance to the external audit. Our results also show that previous proxies used to measure this relation is either not associated with or are negatively associated with our direct measures of how the IAF can contribute to the external audit and are highly positively associated with the size and the complexity of the organization. Thus, we conclude the disparate experimental and archival results may be attributable to issues surrounding the construct validity of measures used in previous archival studies and that when measures similar to those used in experimental studies are employed in archival tests, the archival results are consistent with experimental findings. Our research makes four primary contributions to the literature. First, we provide evidence that internal auditing contributes to a reduction in external audit fees. Second, we replicate and provide an explanation for why previous archival studies find that internal auditing has either no association with external audit fees or is associated with an increase in those fees: prior studies generally use proxies of internal audit contribution that do not adequately capture the intended construct. Third, our research expands on survey-based research (e.g., Oil Libya sh.co.) by separately examining the impact on the audit fee of the internal auditors’ work, indirectly assisting external auditors and internal auditors’ prior work upon which external auditors can rely. Finally, we extend prior research by using a new, independent data source to validate and extend prior studies. This data set also allows for a sample of examining the impact of internal auditing on the external audit fee and the use of a more comprehensive external audit fee model that better controls for determinants of the external audit fee.

Keywords: internal audit, contribution, external audit, function

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Authors: Chedly Tizaoui, Hussain Mohammed, Lobna Mansouri, Nidal Hilal, Latifa Bousselmi

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The degradation of diethyl phthalate (DEP) was studied using heterogeneous catalytic ozonation. Activated carbon was used as a catalyst. The degradation of DEP with ozone alone was slow while catalytic ozonation increased degradation rates. Second-order reaction kinetics was used to describe the experimental data, and the corresponding rate constant values were 1.19 and 3.94 M-1.s-1 for ozone and ozone/activated carbon respectively.

Keywords: ozone, heterogeneous catalytic ozonation, diethyl phthalate, endocrine disrupting chemicals

Procedia PDF Downloads 341

Authors: Alex Rodriguez, Adam Guerrero

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Purpose: This study is designed to examine the institutions that comprise the Online Consortium of Independent Colleges and Universities (OCICU) to understand better the types of higher education institutions that comprise their membership. The literature on this topic is extensive in analyzing the current economic environment around higher education, which is largely considered to be negative for independent, tuition-driven institutions, and is forcing colleges and universities to reexamine how the college-attending population defines value and how institutions can best utilize their existing resources (and those of other institutions) to meet that value expectation. The results from this analysis are intended to give OCICU the ability to target their current customer base better, based on their most notable differences, and other institutions to see how to best approach consolidation within higher education. Design/Methodology: This study utilized k-means cluster analysis in order to explore the possibility that different segments exist within the seventy-one colleges and universities that have comprised OCICU. It analyzed fifty different variables, whose selection was based on the previous literature, collected by the Integrated Postsecondary Education Data System (IPEDS), whose data is self-reported by individual institutions. Findings: OCICU member institutions are partitioned into two clusters: "access institutions" and "conventional institutions” based largely on the student profile they target. Value: The methodology of the study is relatively unique as there are not many studies within the field of higher education marketing that have employed cluster analysis, and this type of analysis has never been conducted on OCICU members, specifically, or that of any higher education consolidated offering. OCICU can use the findings of this study to obtain a better grasp as to the specific needs of the two market segments OCICU currently serves and develop measurable marketing programs around how those segments are defined that communicate the value sought by current and potential OCICU members or those of similar institutions. Other consolidation efforts within higher education can also employ the same methodology to determine their own market segments.

Keywords: Consolidation, Colleges, Enrollment, Higher Education, Marketing, Strategy, Universities

Procedia PDF Downloads 128

Authors: Isabel Lopez-Oliva, Akshay Paropkari, Shweta Saraswat, Stefan Serban, Paola de Pablo, Karim Raza, Andrew Filer, Iain Chapple, Thomas Dietrich, Melissa Grant, Purnima Kumar

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Objective: We aimed to explicate the role of the subgingival microbiome in the causal link between rheumatoid arthritis (RA) and periodontitis (PD). Methods: Subjects with/without RA and with/without PD were randomized for treatment with scaling and root planing (SRP) or oral hygiene instructions. Subgingival biofilm, gingival crevicular fluid, and serum were collected at baseline and at 3- and 6-months post-operatively. Correlations were generated between 72 million 16S rDNA sequences, immuno-inflammatory mediators, circulating antibodies to oral microbial antigens, serum inflammatory molecules, and clinical metrics of RA. The dynamics of inter-microbial and host-microbial interactions were modeled using differential network analysis. Results: RA superseded periodontitis as a determinant of microbial composition, and DAS28 score superseded the severity of periodontitis as a driver of microbial assemblages (p=0.001, ANOSIM). RA subjects evidenced higher serum anti-PPAD (p=0.0013), anti-Pg-enolase (p=0.0031), anti-RPP3, anti- Pg-OMP and anti- Pi-OMP (p=0.001) antibodies than non-RA controls (with and without periodontitis). Following SRP, bacterial networks anchored by IL-1b, IL-4, IL-6, IL-10, IL-13, MIP-1b, and PDGF-b underwent ≥5-fold higher rewiring; and serum antibodies to microbial antigens decreased significantly. Conclusions: Our data suggest a circular relationship between RA and PD, beginning with an RA-influenced dysbiosis within the healthy subgingival microbiome that leads to exaggerated local inflammation in periodontitis and circulating antibodies to periodontal pathogens and positive correlation between severity of periodontitis and RA activity. Periodontal therapy restores host-microbial homeostasis, reduces local inflammation, and decreases circulating microbial antigens. Our data highlights the importance of integrating periodontal care into the management of RA patients.

Keywords: rheumatoid arthritis, periodontal, subgingival, DNA sequence analysis, oral microbiome

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Authors: Michelle W. T. Cheng, Yau Y.

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Hong Kong continues to be ranked as the least affordable housing market in the world, making co-living a feasible alternative in this high-density city. Although the number of co-living residences has increased in Hong Kong, co-living as a housing typology is still a new concept for many. Little research has been conducted on this new housing typology, let alone the co-living experience. To address this gap, this study targeted student residents in university residential halls as it is a more controlled environment (e.g., with established rules and guidelines regarding the use of communal facilitates and housing management) for studying co-living experiences in Hong Kong. To date, no research study has systematically identified anti-social behavior (ASB) in co-living spaces. Since ASB can be influenced by factors such as social norms and individual interpretation, it has an elastic definition that results in different levels of acceptance. Unlike other types of housing, co-living spaces can be potentially more influenced by the neighborhood as residents share more time and space. As a pilot study, this research targeted one university residential hall to examine student co-living experiences. To clarify, the research question is focused on identifying the social factors that impact the residential satisfaction of those who co-living in residential halls. Quantitative data (n=100) were collected via a structured questionnaire to measure the residential environment, including ASB, social neighboring, community attachment, and perceived hall management efficacy. The survey was distributed at the end of the academic year to ensure that respondents had at least one year of first-hand experience living in a co-living space. To gather qualitative data, follow-up focus group interviews were conducted with 16 participants who completed the survey. The semi-structured interviews aimed to elicit the participants' perspectives on their co-living experience. Through analyzing their co-living experiences, the researcher identified factors that affected their residential satisfaction and provided recommendations to enhance their co-living experience.

Keywords: co-living, university residential hall, anti-social behabiour, neighbour relationship, community attachement

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Authors: Violet Justine Mtonga, Cecilia Diaz

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this paper explores the prevalence of loyalty programs in the UK gambling industry and their association with unintended consequences and harm amongst program members. The use of loyalty programs within the UK gambling industry has risen significantly with over 40 million cards in circulation. Some research suggests that as of 2013-2014, nearly 95% of UK consumers have at least one loyalty card with 78% being members of two or more programs, and the average household possesses ‘22 loyalty programs’, nearly half of which tend to be used actively. The core design of loyalty programs is to create a relational ‘win-win’ approach where value is jointly created between the parties involved through repetitive engagement. However, main concern about the diffusion of gambling organisations’ loyalty programs amongst consumers, might be the use by the organisations within the gambling industry to over influence customer engagement and potentially cause unintended harm. To help understand the complex phenomena of the diffusions and adaptation of the use of loyalty programs in the gambling industry, and the potential unintended outcomes, this study is theoretically underpinned by the social exchange theory of relationships entrenched in the processes of social exchanges of resources, rewards, and costs for long-term interactions and mutual benefits. Qualitative data were collected via in-depth interviews from 14 customers and 12 employees within the UK land-based gambling firms. Data were analysed using a combination of thematic and clustering analysis to help reveal and discover the emerging themes regarding the use of loyalty cards for gambling companies and exploration of subgroups within the sample. The study’s results indicate that there are different unintended consequences and harm of loyalty program engagement and usage such as maladaptive gambling behaviours, risk of compulsiveness, and loyalty programs promoting gambling from home. Furthermore, there is a strong indication of a rite of passage among loyalty program members. There is also strong evidence to support other unfavorable behaviors such as amplified gambling habits and risk-taking practices. Additionally, in pursuit of rewards, loyalty program incentives effectuate overconsumption and heighten expenditure. Overall, the primary findings of this study show that loyalty programs in the gambling industry should be designed with an ethical perspective and practice.

Keywords: gambling, loyalty programs, social exchange theory, unintended harm

Procedia PDF Downloads 85