Search results for: negative data

Authors: M. J. Pourvaghar, M. E. Bahram

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Obesity and overweight is one of the most common metabolic disorders in industrialized countries and in developing countries. One consequence of pathological obesity is cardiovascular disease and metabolic syndrome. Chemerin is an adipocyne that plays a role in the regulation of the adipocyte function and the metabolism of glucose in the liver and musculoskeletal system. Most likely, chemerin is involved in obesity-related disorders such as type 2 diabetes and cardiovascular disease. Aerobic exercises reduce the level of chemerin and cause macrophage penetration into fat cells and inflammatory factors. Several efforts have been made to clarify the cellular and molecular mechanisms of hypertrophy and muscular atrophy. Myostatin, a new member of the TGF-β family, is a transforming growth factor β that its expression negatively regulates the growth of the skeletal muscle; and the increase of this hormone has been observed in conditions of muscular atrophy. While in response to muscle overload, its levels decrease after the atrophy period, TGF-β is the most important cytokine in the development of skeletal muscle. Myostatin plays an important role in muscle control, and animal and human studies show a negative role of myostatin in the growth of skeletal muscle. Separation of myostatin from Golgi begins on the ninth day of the onset period and continues until birth at all times of muscle growth. Higher levels of myostatin are found in obese people. Resistance training for 10 weeks could reduce levels of plasma myostatin.

Keywords: chemerin, myostatin, obesity, physical activity

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Authors: Aline Giardin

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Introduction: This review addresses the relationship between physical education and mental health and its main objective is to discuss the meanings that circulate in Psychiatric Hospitalization Units and Psychosocial Care Centers (CAPS) about the presence of physical education teachers and the practices developed by Them within these services. Material and methods: It is based on the theoretical contribution of the Psychiatric Reform and is methodologically inspired by the Bibliographic Review. Objectives: The objective of this review was to identify the main scientific evidence on the effects of physical activity on the main psychological aspects associated with mental health during the hospitalization process. Results: It was observed that physical activity has beneficial effects in the psychological, social and cognitive aspects, being thus a fundamental aspect of the lifestyle in promoting a healthy and successful treatment. In studies evaluating the effects of physical activity on mental health, the most frequently evaluated outcomes include anxiety, depression, and health-related quality of life (eg, self-esteem and self-efficacy). Evidence from epistemological studies indicates that the level of physical activity is positively associated with good mental health, when mental health is defined as good mood, general well-being and decreased symptoms. Conclusion: It is necessary to intervene and a greater interest of the professionals of physical education in the treatment with the people with mental disorders so that the negative symptoms are modified, through the aid of the physical activity, by better quality of life, physical condition, nutritional state and A healthy emotional appearance.

Keywords: health mental, physical activity, benefits, treatment

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Authors: Salina Yahya Saddik

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The present study is designed to demonstrate the Ovarian Surface Epithelial cells (OSE) Estrogen Receptor α (ERα) and Progesterone Receptor (PR) during pregnancy and estrous cycle in rat. Moreover, determination of the levels of plasma progesterone, estradiol, FSH and LH were also made. The levels of plasma progesterone, estradiol, FSH and LH concentrations were determined on days 7 (n=5), 14 (n=5), and 21(n=5) of pregnancy in three groups of rats and during the estrous cycle (n=5) using ELISA kit. Immunohistochemical method for PR and ERα expression was also made on the ovary. During pregnancy, FSH and LH remained low except at term when LH levels began to increase from 16 ng/ml to 47 ng/ml. Progesterone levels significantly exceeded estradiol values in all pregnant rats with a peak value of 202 ng/ml on day 14. Elevated progesterone levels were associated negatively with LH and estradiol levels during pregnancy. The levels of estradiol surged significantly on day 21. Immunohistochemistry of the ovary showed low levels of OSE cells staining positive for ERα expression. ERα positive cells were absent on day 7 and 14 of pregnancy, only day 21 recorded a very low percentage of immunostaining (0.5%) within the nuclei of OSE cells. On the contrary, immunostaining of PR was not observed within the nuclei of OSE cells in all groups of study. In conclusions, these results may suggest that progesterone effect during pregnancy seems to be overriding the positive effect of estrogens on OSE cells. High progesterone levels may have a direct negative effect on gonadotropin production and thereby it might inhibit events leading to both follicular development and OSE proliferation. Understanding the factors affecting OSE proliferation may help elucidating the mechanism(s) of assisted diseases such as ovarian cancer.

Keywords: ovarian surface, pregnancy, gonadotropins, steroids

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Authors: Zachary Blanks, Solomon Sonya

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Poaching presents a serious threat to endangered animal species, environment conservations, and human life. Additionally, some poaching activity has even been linked to supplying funds to support terrorist networks elsewhere around the world. Consequently, agencies dedicated to protecting wildlife habitats have a near intractable task of adequately patrolling an entire area (spanning several thousand kilometers) given limited resources, funds, and personnel at their disposal. Thus, agencies need predictive tools that are both high-performing and easily implementable by the user to help in learning how the significant features (e.g. animal population densities, topography, behavior patterns of the criminals within the area, etc) interact with each other in hopes of abating poaching. This research develops a classification model using machine learning algorithms to aid in forecasting future attacks that is both easy to train and performs well when compared to other models. In this research, we demonstrate how data imputation methods (specifically predictive mean matching, gradient boosting, and random forest multiple imputation) can be applied to analyze data and create significant predictions across a varied data set. Specifically, we apply these methods to improve the accuracy of adopted prediction models (Logistic Regression, Support Vector Machine, etc). Finally, we assess the performance of the model and the accuracy of our data imputation methods by learning on a real-world data set constituting four years of imputed data and testing on one year of non-imputed data. This paper provides three main contributions. First, we extend work done by the Teamcore and CREATE (Center for Risk and Economic Analysis of Terrorism Events) research group at the University of Southern California (USC) working in conjunction with the Department of Homeland Security to apply game theory and machine learning algorithms to develop more efficient ways of reducing poaching. This research introduces ensemble methods (Random Forests and Stochastic Gradient Boosting) and applies it to real-world poaching data gathered from the Ugandan rain forest park rangers. Next, we consider the effect of data imputation on both the performance of various algorithms and the general accuracy of the method itself when applied to a dependent variable where a large number of observations are missing. Third, we provide an alternate approach to predict the probability of observing poaching both by season and by month. The results from this research are very promising. We conclude that by using Stochastic Gradient Boosting to predict observations for non-commercial poaching by season, we are able to produce statistically equivalent results while being orders of magnitude faster in computation time and complexity. Additionally, when predicting potential poaching incidents by individual month vice entire seasons, boosting techniques produce a mean area under the curve increase of approximately 3% relative to previous prediction schedules by entire seasons.

Keywords: ensemble methods, imputation, machine learning, random forests, statistical analysis, stochastic gradient boosting, wildlife protection

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Authors: Katja Ignatieva, Patrick Wong

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We investigated the dynamics of high frequency energy prices, including crude oil and electricity prices. The returns of underlying quantities are modelled using various parametric models such as stochastic framework with jumps and stochastic volatility (SVCJ) as well as non-parametric alternatives, which are purely data driven and do not require specification of the drift or the diffusion coefficient function. Using different statistical criteria, we investigate the performance of considered parametric and nonparametric models in their ability to forecast price series and volatilities. Our models incorporate possible seasonalities in the underlying dynamics and utilise advanced estimation techniques for the dynamics of energy prices.

Keywords: stochastic volatility, affine jump-diffusion models, high frequency data, model specification, markov chain monte carlo

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Authors: Sohail Ahmed, Ahmad Raza

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Physical properties of maize grains were correlated with levels of the life history of Sitotroga cerealella (Oliv.) (Gelechiidae: Lepidoptera) in no choice test to find out relative resistance in different varieties. Eight maize varieties /lines (EV-6089, Sahiwal-2002, Golden, 34N43, EV-1098, Sultan, China-1, EV-20) including seven yellow and one white were obtained from Maize and Millet Research Institute, Yousaf Wala, Sahiwal, Punjab, Pakistan. Freshly laid eggs (one day old) of S. cerealella were obtained and cultured on a susceptible maize variety for two generations for later on shifting to test varieties. Results showed that maximum moth emergence (10.33), fecundity (35.66), hatching (87.66%), moth weight (5.05 mg), development time (36.0 days) damage (93.35%) and grain weight loss (38.84%) was found in varieties, 34N43 and Golden, Sultan, Sahiwal 2002, 34N43, EV-6089, 34N43 and EV-1089, respectively. Varieties had significant difference with other varieties in these parameters (P<0.05). The varieties had positive as well as negative correlation between hardness index, grain weight and bulk density with the biological parameters of S. cerealella, percent grain damage and weight loss. Possible involvement of these grain properties in the resistance of maize grains towards S. cerealella is discussed.

Keywords: sitotroga cerealella, hardness index, grain damage, maize, varieties

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Authors: Chantell Gouws, Lourens Millard, Anne Naude, Jan-Wessel Meyer, Brandon Stuwart Shaw, Ina Shaw

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Background: Millions of South African youths participate in team sports, with netball and rugby being two of the largest worldwide. This increased participation and professionalism have resulted in an increase in the number of musculoskeletal injuries. Objective: This study examined the extent to which sport coaching knowledge translates to the injuries and prevention of injuries in adolescents participating in netball and rugby. Methods: Thirty-four South African sports coaches participated in the study. Eighteen netball coaches and 16 rugby coaches with varying levels of coaching experience were selected to participate. An adapted version of Nash and Sproule’s questionnaire was used to investigate the coaches’ knowledge with regards to sport-specific common injuries, injury prevention, fitness/conditioning, individual technique development, training programs, mental training, and preparation of players. The analysis of data was carried out using a number of different techniques outlined by Nash and Sproule (2012). These techniques were determined by the type of data. Descriptive data was used to provide statistical analysis. Quantitative data was used to determine the educational framework and knowledge of sports coaches on injury prevention. Numerical data was obtained through questions on sports injuries, as well as coaches’ sports knowledge levels. Participants’ knowledge was measured using a standardized scoring system. Results: For the 0-4 years of netball coaching experience, 76.4% of the coaches had knowledge and experience and 33.3% appropriate first aid knowledge, while for the 9-12 years and 13-16 years, 100% of the coaches had knowledge and experience and first aid knowledge. For the 0-4 years in rugby coaching experience, 59.1% had knowledge and experience and 71% the appropriate first aid knowledge; for the 17-20 years, 100% had knowledge and experience and first aid, while for higher or equal to 25 years, 45.5% had knowledge and experience. In netball, 90% of injuries consisted of ankle injuries, followed by 70% for knee, 50% for shoulder, 20% for lower leg, and 15% for finger injuries. In rugby, 81% of the injuries occurred at the knee, followed by 50% for the shoulder, 40% for the ankle, 31% for the head and neck, and 25% for hamstring injuries. Six hours of training resulted in a 13% chance of injuries in netball and a 32% chance in rugby. For 10 hours of training, the injury prevalence was 10% in netball and 17% in rugby, while 15 hours resulted in an injury incidence of 58% in netball players and a 25% chance in rugby players. Conclusion: This study highlights the need for coaches to improve their knowledge in relation to injuries and injury prevention, along with factors that act as a preventative measure and promotes players’ well-being.

Keywords: musculoskeletal injury, sport coaching, sport trauma

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Authors: Yina Donald Orga

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Osun Osogbo festival is one of the biggest art festivals in Nigeria with over 235, 518 tourist visits in 2014. The purpose of this study is to generate data on the tourists’ perception of Osun Osogbo Festival in Osogbo, Osun State Nigeria. Based on the population of 199, 860 tourist visits at Osun Osogbo festival in 2013, Krejcie and Morgan sample size table was used to select 768 tourists/respondents. Likert questionnaire were used to elicit data from the respondents. Descriptive statistic was used to describe the characteristics of respondents and analyse the tourists’ perception of the festival. The findings from data analysed suggest that the trend of domestic and international tourist visits in the past ten years for the festival had shown a consistent increase since 2004 except in 2007 and 2008 and continue to increase up to 2013. This is an indication that the tourists are satisfied with traditional, historical and authenticity features of the festival. Also, findings from the study revealed that the tourists are not satisfied with the number of toilets at Osun Sacred Grove, crowd control of visitors during the festival, medical personnel to cater for visitors during the festival, etc. In view of the findings of the study, the following recommendations are suggested; provision of more toilets at Osun Sacred grove, Osogbo Heritage Council to recruit festival guides to help control the huge crowd at the festival, the Government of State of Osun in conjunction with Red Cross Society should engage adequate medical personnel to cater for medical needs of visitors at the festival, etc.

Keywords: festival, perception, positive, tourists

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Authors: Nagmani Lnu

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Often, Quality Engineering refers to testing the applications that either have a User Interface (UI) or an Application Programming Interface (API). We often find mature test practices, standards, and automation regarding UI or API testing. However, another kind is present in almost all types of industries that deal with data in bulk and often get handled through something called a Batch Application. This is primarily an offline application companies develop to process large data sets that often deal with multiple business rules. The challenge gets more prominent when we try to automate batch testing. This paper describes the approaches taken to test a Batch application from a Financial Industry to test the payment settlement process (a critical use case in all kinds of FinTech companies), resulting in 100% test automation in Test Creation and Test execution. One can follow this approach for any other batch use cases to achieve a higher efficiency in their testing process.

Keywords: batch testing, batch test automation, batch test strategy, payments testing, payments settlement testing

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Authors: Atikah Nurhayati, Asep A. Handaka

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Indonesia is a world’s major fish producer which can feed not only its citizens but also the people of the world. Currently, the total annual production is 11 tons and expected to double by the year of 2050. Given the potential, fishery has been an important part of the national food security system in Indonesia. Despite such a potential, a big challenge is facing the Indonesians in making fish the reliable source for their food, more specifically source of protein intake. The long geographic distance between the fish production centers and the consumer concentrations has prevented effective supply chain from producers to consumers and therefore demands a good logistic system. This paper is based on our research, which aimed at analyzing the fish supply chain and is to suggest relevant improvement to the chain. The research was conducted in the Year of 2016 in selected locations of Java Island, where intensive transaction on fishery commodities occur. Data used in this research comprises secondary data of time series reports on production and distribution and primary data regarding distribution aspects which were collected through interviews with purposively selected 100 respondents representing fishers, traders and processors. The data were analyzed following the supply chain management framework and processed following logistic regression and validity tests. The main findings of the research are as follows. Firstly, it was found that improperly managed connectivity and logistic chain is the main cause for insecurity of availability and affordability for the consumers. Secondly, lack of quality of most local processed products is a major obstacle for improving affordability and connectivity. The paper concluded with a number of recommended strategies to tackle the problem. These include rationalization of the length of the existing supply chain, intensification of processing activities, and improvement of distribution infrastructure and facilities.

Keywords: fishery, food security, logistic, supply chain

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Authors: S. Ali, R. Yunus, A. Arif, Y. Ayaz, M. Baber Sial, R. Asif, N. Naseer, M. Jawad Khan

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In this study, we have proposed a gesture to emotion recognition method using flex sensors mounted on metacarpophalangeal joints. The flex sensors are fixed in a wearable glove. The data from the glove are sent to PC using Wi-Fi. Four gestures: finger pointing, thumbs up, fist open and fist close are performed by five subjects. Each gesture is categorized into sad, happy, and excited class based on the velocity and acceleration of the hand gesture. Seventeen inspectors observed the emotions and hand gestures of the five subjects. The emotional state based on the investigators assessment and acquired movement speed data is compared. Overall, we achieved 77% accurate results. Therefore, the proposed design can be used for emotional state detection applications.

Keywords: emotion identification, emotion models, gesture recognition, user perception

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Authors: Yu-Wen Chen, Szu-Wei Huang, Chung-Hsiang Mu, Kelvin Cheng

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This paper developed a data-driven based model to deal with the causality between the Continuous Emission Monitoring System (CEMS, by Environmental Protection Administration, Taiwan) in industrial factories, and the air quality around environment. Compared to the heavy burden of traditional numerical models of regional weather and air pollution simulation, the lightweight burden of the proposed model can provide forecasting hourly with current observations of weather, air pollution and emissions from factories. The observation data are included wind speed, wind direction, relative humidity, temperature and others. The observations can be collected real time from Open APIs of civil IoT Taiwan, which are sourced from 439 weather stations, 10,193 qualitative air stations, 77 national quantitative stations and 140 CEMS quantitative industrial factories. This study completed a causal inference engine and gave an air pollution forecasting for the next 12 hours related to local industrial factories. The outcomes of the pollution forecasting are produced hourly with a grid resolution of 1km*1km on IIoTC (Industrial Internet of Things Cloud) and saved in netCDF4 format. The elaborated procedures to generate forecasts comprise data recalibrating, outlier elimination, Kriging Interpolation and particle tracking and random walk techniques for the mechanisms of diffusion and advection. The solution of these equations reveals the causality between factories emission and the associated air pollution. Further, with the aid of installed real-time flue emission (Total Suspension Emission, TSP) sensors and the mentioned forecasted air pollution map, this study also disclosed the converting mechanism between the TSP and PM2.5/PM10 for different region and industrial characteristics, according to the long-term data observation and calibration. These different time-series qualitative and quantitative data which successfully achieved a causal inference engine in cloud for factory management control in practicable. Once the forecasted air quality for a region is marked as harmful, the correlated factories are notified and asked to suppress its operation and reduces emission in advance.

Keywords: continuous emission monitoring system, total suspension particulates, causal inference, air pollution forecast, IoT

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Authors: Fatima Z. Cherhabil, Mammar Sedrati, Sonia-Sabrina Bendib‎

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In order to support the continued growth, critical latency of ‎IoT ‎applications, and ‎various obstacles of traditional data centers, ‎mobile edge ‎computing (MEC) has ‎emerged as a promising solution that extends cloud data-processing and decision-making to edge devices. ‎By adopting a MEC structure, IoT applications could be executed ‎locally, on ‎an edge server, different fog nodes, or distant cloud ‎data centers. However, we are ‎often ‎faced with wanting to optimize conflicting criteria such as ‎minimizing energy ‎consumption of limited local capabilities (in terms of CPU, RAM, storage, bandwidth) of mobile edge ‎devices and trying to ‎keep ‎high performance (reducing ‎response time, increasing throughput and service availability) ‎at the same ‎time‎. Achieving one goal may affect the other, making task offloading (TO), ‎resource allocation (RA), and service placement (SP) complex ‎processes. ‎It is a nontrivial multi-objective optimization ‎problem ‎to study the trade-off between conflicting criteria. ‎The paper provides a survey on different TO, SP, and RA recent multi-‎objective optimization (MOO) approaches used in edge computing environments, particularly artificial intelligent (AI) ones, to satisfy various objectives, constraints, and dynamic conditions related to IoT applications‎.

Keywords: mobile edge computing, multi-objective optimization, artificial ‎intelligence ‎approaches, task offloading, resource allocation, ‎ service placement

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Authors: Steven Sam, Ximena Schmidt, Hugh Dickinson, Jens Jensen

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The goal of this study is to explore the potential of data science and citizen science approaches to develop an interactive, digital, open infrastructure that pulls together African indigenous agriculture and food systems data from multiple sources, making it accessible and reusable for policy, research and practice in modern food production efforts. The World Bank has recognised that African Indigenous Knowledge (AIK) is innovative and unique among local and subsistent smallholder farmers, and it is central to sustainable food production and enhancing biodiversity and natural resources in many poor, rural societies. AIK refers to tacit knowledge held in different languages, cultures and skills passed down from generation to generation by word of mouth. AIK is a key driver of food production, preservation, and consumption for more than 80% of citizens in Africa, and can therefore assist modern efforts of reducing food insecurity and hunger. However, the documentation and dissemination of AIK remain a big challenge confronting librarians and other information professionals in Africa, and there is a risk of losing AIK owing to urban migration, modernisation, land grabbing, and the emergence of relatively small-scale commercial farming businesses. There is also a clear disconnect between the AIK and scientific knowledge and modern efforts for sustainable food production. The study combines data science and citizen science approaches through active community participation to generate and share AIK for facilitating learning and promoting knowledge that is relevant for policy intervention and sustainable food production through a curated digital platform based on FAIR principles. The study adopts key informant interviews along with participatory photo and video elicitation approach, where farmers are given digital devices (mobile phones) to record and document their every practice involving agriculture, food production, processing, and consumption by traditional means. Data collected are analysed using the UK Science and Technology Facilities Council’s proven methodology of citizen science (Zooniverse) and data science. Outcomes are presented in participatory stakeholder workshops, where the researchers outline plans for creating the platform and developing the knowledge sharing standard framework and copyrights agreement. Overall, the study shows that learning from AIK, by investigating what local communities know and have, can improve understanding of food production and consumption, in particular in times of stress or shocks affecting the food systems and communities. Thus, the platform can be useful for local populations, research, and policy-makers, and it could lead to transformative innovation in the food system, creating a fundamental shift in the way the North supports sustainable, modern food production efforts in Africa.

Keywords: Africa indigenous agriculture knowledge, citizen science, data science, sustainable food production, traditional food system

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Authors: W. Schellong

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Industry accounts for one-third of global final energy demand. Crossover technologies (e.g. motors, pumps, process heat, and air conditioning) play an important role in improving energy efficiency. These technologies are used in many applications independent of the production branch. Especially electrical power is used by drives, pumps, compressors, and lightning. The paper demonstrates the algorithm of the energy analysis by some selected case studies for typical industrial processes. The energy analysis represents an essential part of energy management systems (EMS). Generally, process control system (PCS) can support EMS. They provide information about the production process, and they organize the maintenance actions. Combining these tools into an integrated process allows the development of an energy critical equipment strategy. Thus, asset and energy management can use the same common data to improve the energy efficiency.

Keywords: crossover technologies, data management, energy analysis, energy efficiency, process control

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Authors: Jing Hu, Dong Yang

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With the increasingly difficult development and operating environment of exploration, there are many new challenges and difficulties in developing and exploiting oil and gas resources. These include the ability to dynamically monitor wells and provide data and assurance for the completion and production of high-cost and complex wells. A key technology in providing these assurances and maximizing oilfield profitability is real-time permanent reservoir monitoring. The emergence of optical fiber sensing systems has gradually begun to replace traditional electronic systems. Traditional temperature sensors can only achieve single-point temperature monitoring, but fiber optic sensing systems based on the Bragg grating principle have a high level of reliability, accuracy, stability, and resolution, enabling cost-effective monitoring, which can be done in real-time, anytime, and without well intervention. Continuous data acquisition is performed along the entire wellbore. The integrated package with the downhole pressure gauge, packer, and surface system can also realize real-time dynamic monitoring of the pressure in some sections of the downhole, avoiding oil well intervention and eliminating the production delay and operational risks of conventional surveys. Real-time information obtained through permanent optical fibers can also provide critical reservoir monitoring data for production and recovery optimization.

Keywords: PDHM, optical fiber, coiled tubing, photoelectric composite cable, digital-oilfield

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Authors: G. Fitzpatrick, S. O. Chonghaile, D. Harmon

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Objective: Chronic pain patients represent a unique challenge in the Emergency Department. Very little literature has been published regarding this group of patients. Our aim was to determine the attitude of patients with chronic pain to the Emergency Department in order to improve and streamline their future visits. Methods: A two-year survey was carried out on Chronic Pain Patients regarding their Emergency Department Attendances. Patients attending the Pain Clinic in Croom Hospital, Co. Limerick were asked to complete a 20-part questionnaire regarding their experiences of visiting the Emergency Department in the preceding year. 46 questionnaires were completed. Results: Unbearable breakthrough pain was the main reason for visiting the Emergency Department. More than half (54%) of those surveyed were not satisfied with the treatment received. Problems indicated included under-treatment of pain (59%), a sense of being under undue suspicion of drug-seeking behaviour (33%) and a perception that the patient themselves understood their condition better than the treating doctor (76%). Paracetamol, NSAIDs, or time off work comprised 72% of the treatments offered – all of which could have been provided by their General Practitioner. Only 4% were offered a nerve block. 67% felt that the creation of personalised Patient Plans, consisting of an agreed plan between the patient, their pain specialist, and the Emergency Department, would expedite their trip through the Emergency Department. Conclusions: Chronic pain patients generally have a negative experience in the ED. Possible future solutions include increasing our empathy and levels of knowledge, provision of nerve blocks in the ED, and use of personalised “Patient Plans” to streamline the treatment pathway for this group of patients.

Keywords: chronic pain, survey, patients, emergency department

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Authors: Getenet Shumet Birhan, Biruk Lelisa Eticha, Gizachew Tilahun Belete, Fisseha Admassu Ayele

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Context: Glaucoma is a significant public health concern globally, being the second leading cause of blindness. This study focuses on adult glaucoma patients in Ethiopia, specifically at the University of Gondar. Research Aim: The main objective is to assess the prevalence of visual impairment and identify associated factors among adult glaucoma patients at the University of Gondar. Methodology: The study used an institution-based cross-sectional design, collecting data from 423 glaucoma patients through interviews and medical chart reviews. Descriptive statistics and logistic regression were employed for analysis. Findings: The study found a high prevalence of visual impairment (77.6%) among adult glaucoma patients, with factors such as female sex, rural residence, glaucoma type, disease stage, and duration of diagnosis significantly associated with visual impairment. Theoretical Importance: This research adds valuable insights into the prevalence and determinants of visual impairment among glaucoma patients in Ethiopia, contributing to the existing literature on eye health in low-resource settings. Data Collection: Data were collected through face-to-face interviews and medical chart reviews at the University of Gondar, utilizing a structured questionnaire. Analysis Procedures: Descriptive statistics, frequency analysis, and binary logistic regression were employed to analyze the data and identify factors associated with visual impairment in adult glaucoma patients. Question Addressed: The study sought to answer the question of the prevalence of visual impairment and its associated factors among adult glaucoma patients at the University of Gondar in Northwest Ethiopia. Conclusion: The research concludes that visual impairment is significantly high among adult glaucoma patients in this setting, with several factors playing a role in its occurrence.

Keywords: visual impairment, glaucoma, Ethiopia, Gondar

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Authors: Iris Alkaher, Nurit Carmi

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It is widely agreed among scientists that population growth (PG) is a major factor that drives the global environmental crisis. Many researchers recognize that explicitly addressing the impact of PG on the environment and human quality of life through education systems worldwide could play a significant role in improving understanding regarding the links between rapid PG and environmental degradation and changing perceptions, attitudes, and behaviors concerning the necessity to reduce the fertility rate. However, the issue of PG is still rarely included in schools' curricula, mainly because of its complexity and controversiality. This study aims to explore the perspectives of teachers with an academic background in environmental and sustainability education (ESEteachers) and teachers with no such background (non-ESE teachers) regarding PG as an environmental risk. The study also explores the teachers’ willingness to include PG in their teaching and identifies what predicts their inclusion of it. In this mixed-methods research study, data were collected using questionnaires and interviews. The findings portray a complex picture concerning the debate aboutPG as a major factor that drives the global environmental crisis in the Israeli context. Consistent with other countries, we found that the deep-rooted pronatalist culture in the Israeli society, as well as a robust national pronatalist agenda and policies, have a tremendous impact on the education system. Therefore, we found that an academic background in ESE had a limited impact on teachers' perceptions concerning PG as a problem and on their willingness to include it in their teaching and discuss its controversiality. Teachers' attitudes related to PG demonstrated social, cultural, and politically oriented disavowal justification regarding the negative impacts of rapid PG, identified in the literature as population-skepticism and population-fatalism. Specifically, factors such as the ongoing Israeli-Palestinian conflict, the Jewish anxiety of destruction, and the religious command to“be fruitful and multiply”influenced the perceptions of both ESE and non-ESE teachers. While these arguments are unique to the Israeli context, pronatalist policies are international. In accordance with the pronatalist policy, we also found that the absence of PG from both school curricula and the Israeli public discourse was reported by ESE and non-ESE teachers as major reasons for their disregarding PG in their teaching. Under these circumstances, the role of the education system to bring the population question to the front stage in Israel and elsewhere is more challenging. To encourage science and social studies teachers to incorporate the controversial issue of PG in their teaching and successfully confront dominant pronatalist cultures, they need strong and ongoing scaffolding and support. In accordance with scientists' agreement regarding the role of PG as a major factor that drives the global environmental crisis, we call on stakeholders and policymakers in the education system to bring the population debate into schools' curricula, the sooner, the better. And not only as part of human efforts to mitigate environmental degradation but also to use this controversial topic as a platform for shaping critical learners and responsible and active citizens who are tolerant of different people’s opinions.

Keywords: population growth, environmental and sustainability education, controversial environmental sustainability issues, pronatalism

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Authors: Halefom Kidane

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This study aims to assess the wind resource potential and characterize the urban area wind patterns in Hawassa City, Ethiopia. The estimation and characterization of wind resources are crucial for sustainable urban planning, renewable energy development, and climate change mitigation strategies. A secondary data collection method was used to carry out the study. The collected data at 2 meters was analyzed statistically and extrapolated to the standard heights of 10-meter and 30-meter heights using the power law equation. The standard deviation method was used to calculate the value of scale and shape factors. From the analysis presented, the maximum and minimum mean daily wind speed at 2 meters in 2016 was 1.33 m/s and 0.05 m/s in 2017, 1.67 m/s and 0.14 m/s in 2018, 1.61m and 0.07 m/s, respectively. The maximum monthly average wind speed of Hawassa City in 2016 at 2 meters was noticed in the month of December, which is around 0.78 m/s, while in 2017, the maximum wind speed was recorded in the month of January with a wind speed magnitude of 0.80 m/s and in 2018 June was maximum speed which is 0.76 m/s. On the other hand, October was the month with the minimum mean wind speed in all years, with a value of 0.47 m/s in 2016,0.47 in 2017 and 0.34 in 2018. The annual mean wind speed was 0.61 m/s in 2016,0.64, m/s in 2017 and 0.57 m/s in 2018 at a height of 2 meters. From extrapolation, the annual mean wind speeds for the years 2016,2017 and 2018 at 10 heights were 1.17 m/s,1.22 m/s, and 1.11 m/s, and at the height of 30 meters, were 3.34m/s,3.78 m/s, and 3.01 m/s respectively/Thus, the site consists mainly primarily classes-I of wind speed even at the extrapolated heights.

Keywords: artificial neural networks, forecasting, min-max normalization, wind speed

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Authors: Chinaza Uleanya, Martin Duma, Bongani Gamede

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The research investigated pedagogic malpractices by lecturers in sub-Sahara African universities. The population of the study consisted of undergraduates and lecturers in selected universities in Nigeria and South Africa. Mixed method approach was adopted for data collection. The sample population of the study was 480 undergraduate students and 16 lecturers. Questionnaires with 4 point Likert-scale were administered to 480 respondents while interviews were conducted with 6 lecturers. In addition, the teaching strategies of 10 lecturers were observed. Data analyses indicated that poor work environment demotivates lecturers and makes them involved in pedagogic malpractice which is one of the causes of learning challenges faced by undergraduates. The finding of the study also shows that pedagogic malpractice contributes to the high rate of dropout in sub-Sahara African universities. Based on the results, it was recommended that qualified lecturers be employed and given conducive environments to work.

Keywords: malpractice, pedagogy, pedagogic malpractice, correlates

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Authors: Shima Behzadi

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Background: In many human malignant tumors, microRNA expression is aberrant. This study investigates miR-141 as a prognostic marker in colorectal cancer with K-Ras mutation. Materials and methods: In this case-control study, 100 patients, mostly over the age of 50, who were diagnosed with colorectal cancer were selected. The pathology department of the Mostoufi Pathobiology and Genetics Laboratory in Tehran confirmed the presence of colorectal cancer in samples of paraffin-embedded colon tissue. The case group was composed of patients with codon 12 and 13 mutations in exon 2 of the K-Ras gene, while tumor samples of individuals without these mutations in exon 2 of the K-Ras gene were selected as the control group, with patient consent. The changes in the expression of miR-141 were examined in both groups. Results: The study found that 20% of the patients tested positive for codon 12 mutation, and 10% of patients had codon 13 mutation. As a result, in 30 cases, there was a higher level of miR-141 expression. The miR-141 gene expression level in K-Ras positive tumor samples was 1.5 times higher than its expression level in K-Ras negative samples. This increase in expression was statistically significant, with a p-value of less than 0.001, indicating that the observed results are highly statistically significant. Conclusion: The study revealed that the incidence of typical K-Ras gene mutations among the colorectal cancer patients in the sample matches the national average in Iran. Additionally, the expression of miR-141 can serve as a useful biomarker to aid in the prognosis of colorectal cancer.

Keywords: colorectal cancer, K-Ras gene, miR-141 marker, real time PCR, electrophoresis

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Authors: Rubaiat S. Ahmed, Jemer Garrido, Sergey M. Motov

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Clinical informatics (CI) enables the transformation of data into a systematic organization that improves the quality of care and the generation of positive health outcomes.Innovative technology through informatics that compiles accurate data on analgesic utilization in the emergency department can enhance pain management in this important clinical setting. We aim to establish a simplified reporting system through CI to examine and assess the analgesic prescribing practices in the EDthrough executing a U.S. federal grant project on opioid reduction initiatives. Queried data points of interest from a level-one trauma ED’s electronic medical records were used to create data sets and develop informational/visual reporting dashboards (on Microsoft Excel and Google Sheets) concerning analgesic usage across several pre-defined parameters and performance metrics using CI. The data was then qualitatively analyzed to evaluate ED analgesic prescribing trends by departmental clinicians and leadership. During a 12-month reporting period (Dec. 1, 2020 – Nov. 30, 2021) for the ongoing project, about 41% of all ED patient visits (N = 91,747) were for pain conditions, of which 81.6% received analgesics in the ED and at discharge (D/C). Of those treated with analgesics, 24.3% received opioids compared to 75.7% receiving opioid alternatives in the ED and at D/C, including non-pharmacological modalities. Demographics showed among patients receiving analgesics, 56.7% were aged between 18-64, 51.8% were male, 51.7% were white, and 66.2% had government funded health insurance. Ninety-one percent of all opioids prescribed were in the ED, with intravenous (IV) morphine, IV fentanyl, and morphine sulfate immediate release (MSIR) tablets accounting for 88.0% of ED dispensed opioids. With 9.3% of all opioids prescribed at D/C, MSIR was dispensed 72.1% of the time. Hydrocodone, oxycodone, and tramadol usage to only 10-15% of the time, and hydromorphone at 0%. Of opioid alternatives, non-steroidal anti-inflammatory drugs were utilized 60.3% of the time, 23.5% with local anesthetics and ultrasound-guided nerve blocks, and 7.9% with acetaminophen as the primary non-opioid drug categories prescribed by ED providers. Non-pharmacological analgesia included virtual reality and other modalities. An average of 18.5 ED opioid orders and 1.9 opioid D/C prescriptions per 102.4 daily ED patient visits was observed for the period. Compared to other specialties within our institution, 2.0% of opioid D/C prescriptions are given by ED providers, compared to the national average of 4.8%. Opioid alternatives accounted for 69.7% and 30.3% usage, versus 90.7% and 9.3% for opioids in the ED and D/C, respectively.There is a pressing need for concise, relevant, and reliable clinical data on analgesic utilization for ED providers and leadership to evaluate prescribing practices and make data-driven decisions. Basic computer software can be used to create effective visual reporting dashboards with indicators that convey relevant and timely information in an easy-to-digest manner. We accurately examined our ED's analgesic prescribing practices using CI through dashboard reporting. Such reporting tools can quickly identify key performance indicators and prioritize data to enhance pain management and promote safe prescribing practices in the emergency setting.

Keywords: clinical informatics, dashboards, emergency department, health informatics, healthcare informatics, medical informatics, opioids, pain management, technology

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Authors: Shayla He

Abstract:

Background and Purpose: According to Chamie (2017), it’s estimated that no less than 150 million people, or about 2 percent of the world’s population, are homeless. The homeless population in the United States has grown rapidly in the past four decades. In New York City, the sheltered homeless population has increased from 12,830 in 1983 to 62,679 in 2020. Knowing the trend on the homeless population is crucial at helping the states and the cities make affordable housing plans, and other community service plans ahead of time to better prepare for the situation. This study utilized the data from New York City, examined the key factors associated with the homelessness, and developed systematic modeling to predict homeless populations of the future. Using the best model developed, named HP-RNN, an analysis on the homeless population change during the months of 2020 and 2021, which were impacted by the COVID-19 pandemic, was conducted. Moreover, HP-RNN was tested on the data from Seattle. Methods: The methodology involves four phases in developing robust prediction methods. Phase 1 gathered and analyzed raw data of homeless population and demographic conditions from five urban centers. Phase 2 identified the key factors that contribute to the rate of homelessness. In Phase 3, three models were built using Linear Regression, Random Forest, and Recurrent Neural Network (RNN), respectively, to predict the future trend of society's homeless population. Each model was trained and tuned based on the dataset from New York City for its accuracy measured by Mean Squared Error (MSE). In Phase 4, the final phase, the best model from Phase 3 was evaluated using the data from Seattle that was not part of the model training and tuning process in Phase 3. Results: Compared to the Linear Regression based model used by HUD et al (2019), HP-RNN significantly improved the prediction metrics of Coefficient of Determination (R2) from -11.73 to 0.88 and MSE by 99%. HP-RNN was then validated on the data from Seattle, WA, which showed a peak %error of 14.5% between the actual and the predicted count. Finally, the modeling results were collected to predict the trend during the COVID-19 pandemic. It shows a good correlation between the actual and the predicted homeless population, with the peak %error less than 8.6%. Conclusions and Implications: This work is the first work to apply RNN to model the time series of the homeless related data. The Model shows a close correlation between the actual and the predicted homeless population. There are two major implications of this result. First, the model can be used to predict the homeless population for the next several years, and the prediction can help the states and the cities plan ahead on affordable housing allocation and other community service to better prepare for the future. Moreover, this prediction can serve as a reference to policy makers and legislators as they seek to make changes that may impact the factors closely associated with the future homeless population trend.

Keywords: homeless, prediction, model, RNN

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Authors: Mathinee Khongsatid, Phusit Phukamchanoad, Sakapas Saengchai

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This research aims to study the democratic political socialization of the 5th and 6th Graders under the Authority of Dusit District Office, Bangkok by using stratified sampling for probability sampling and using purposive sampling for non-probability sampling to collect data toward the distribution of questionnaires to 300 respondents. This covers all of the schools under the authority of Dusit District Office. The researcher analyzed the data by using descriptive statistics which include arithmetic mean and standard deviation. The result shows that 5th and 6th graders under the authority of Dusit District Office, Bangkok, have displayed some characteristics following democratic political socialization both inside and outside classroom as well as outside school. However, the democratic political socialization in classroom through grouping and class participation is much more emphasized.

Keywords: democratic, political socialization, students grades 5-6, descriptive statistics

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Authors: Ali Alotaibi, Francis Edum-Fotwe, Andrew Price /

Abstract:

Mega construction projects create buildings and major infrastructure to respond to work and life requirements while playing a vital role in promoting any nation’s economy. However, the industry is often criticised for not balancing economic, environmental and social dimensions of their projects, with emphasis typically on one aspect to the detriment of the others. This has resulted in many negative impacts including environmental pollution, waste throughout the project lifecycle, low productivity, and avoidable accidents. The identification of comprehensive Social Responsibility (SR) indicators, which combine social, environmental and economic aspects, is urgently needed. This is particularly the case in the context of the Kingdom of Saudi Arabia (KSA), which often has mega public construction projects. The aim of this paper is to develop a set of wide-ranging SR indicators which encompass social, economic and environmental aspects unique to the KSA. A qualitative approach was applied to explore relevant indicators through a review of the existing literature, international standards and reports. A list of appropriate indicators was developed, and its comprehensiveness was corroborated by interviews with experts on mega construction projects working with SR concepts in the KSA. The findings present 39 indicators and their metrics, covering 10 economic, 12 environmental and 17 social aspects of SR mapped against their references. These indicators are a valuable reference for decision-makers and academics in the KSA to understand factors related to SR in mega construction projects. The indicators are related to mega construction projects within the KSA and require validation in a real case scenario or within a different industry to demonstrate their generalisability.

Keywords: social responsibility, construction projects, economic, social, environmental, indicators

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Authors: Matheus Müller, Delma Vidal

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The present paper aims to expose two techniques of dewatering for sludge, analyzing its operations and dewatering processes, aiming at improving the conditions of disposal of residues with high liquid content. It describes the field tests performed on two geotextile systems, a closed geotextile tube and an open geotextile drying bed, both of which are submitted to two filling cycles. The sludge used in the filling cycles for the field trials is from the water treatment plant of the Technological Center of Aeronautics – CTA, in São José dos Campos, Brazil. Data about volume and height abatement due to the dewatering and consolidation were collected per time, until it was observed constancy. With the laboratory analysis of the sludge allied to the data collected in the field, it was possible to perform a critical comparative study between the observed and the scientific literature, in this way, this paper expresses the data obtained and compares them with the bibliography. The tests were carried out on three fronts: field tests, including the filling cycles of the systems with the sludge from CTA, taking measurements of filling time per cycle and maximum filling height per cycle, heights against the abatement by dewatering of the systems over time; tests carried out in the laboratory, including the characterization of the sludge and removal of material samples from the systems to ascertain the solids content within the systems per time and; comparing the data obtained in the field and laboratory tests with the scientific literature. Through the study, it was possible to perceive that the process of densification of the material inside a closed system, such as the geotextile tube, occurs faster than the observed in the drying bed system. This process of accelerated densification can be brought about by the pumping pressure of the sludge in its filling and by the confinement of the residue through the permeable geotextile membrane (allowing water to pass through), accelerating the process of densification and dewatering by its own weight after the filling with sludge.

Keywords: consolidation, dewatering, geotextile drying bed, geotextile tube

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Authors: Cristian Matti, Valerie Fowles, Eva Enyedi, Piotr Pogorzelski

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The system mapping process can be defined as a knowledge service where a team of facilitators, experts and practitioners facilitate a guided conversation, enable the exchange of information and support an iterative curation process. System mapping processes rely on science-based tools to introduce and simplify a variety of components and concepts of socio-technical systems through metaphors while facilitating an interactive dialogue process to enable the design of co-created maps. System maps work then as “artifacts” to provide information and focus the conversation into specific areas around the defined challenge and related decision-making process. Knowledge management facilitates the curation of that data gathered during the system mapping sessions through practices of documentation and subsequent knowledge co-production for which common practices from data science are applied to identify new patterns, hidden insights, recurrent loops and unexpected elements. This study presents empirical evidence on the application of these techniques to explore mechanisms by which visual tools provide guiding principles to portray system components, key variables and types of data through the lens of climate change. In addition, data science facilitates the structuring of elements that allow the analysis of layers of information through affinity and clustering analysis and, therefore, develop simple indicators for supporting the decision-making process. This paper addresses methodological and empirical elements on the horizontal learning process that integrate system mapping through visual tools, interpretation, cognitive transformation and analysis. The process is designed to introduce practitioners to simple iterative and inclusive processes that create actionable knowledge and enable a shared understanding of the system in which they are embedded.

Keywords: indicators, knowledge management, system mapping, visual tools

Procedia PDF Downloads 189

Authors: Evgenia Papathanasiou, Georgios Kokkotis, Georgios Axiaris, Theodoros Argyropoulos, Nikos Viazis, Olga Giouleme, Konstantinos Gkoumas, Αnthia Gatopoulou, Αggelos Theodoulou, Georgios Theocharis, Αngeliki Theodoropoulou, Μaria Κalogirou, Pantelis Karatzas, Κonstantinos Κatsanos, Theodora Kafetzi, Κonstantinos Κarmiris, Αnastasia Κourikou, Ιoannis E Κoutroubakis, Christos Liatsos, Gerassimos J. Mantzaris, Νicoletta Μathou, Georgia Bellou, George Michalopoulos Αikaterini Μantaka, Penelope Nikolaou, Μichael Oikonomou, Dimitrios Polymeros, George Papatheodoridis, Εvdoxia Stergiou, Κonstantinos Soufleris, Εpameinondas Skouloudis, Μaria Tzouvala, Georgia Tsiolakidou, Εftychia Tsironi, Styliani Tsafaraki, Kalliopi Foteinogiannopoulou, Konstantina Chalakatevaki, Αngeliki Christidou, Dimitrios K. Christodoulou, Giorgos Bamias, Spyridon Michopoulos, Εvanthia Zampeli

Abstract:

Background: Inflammatory bowel disease (IBD) commonly affects female patients of reproductive age, making the interaction between fertility, pregnancy and IBD an important issue in disease management. The effect of disease activity on the outcome of pregnancy and its impact on neonatal growth is a field of intense research. Close follow-up of pregnant IBD patients by a multidisciplinary team improves maternal and neonatal outcomes. Aim – Methods: Α national retrospective study of pregnancies in women with IBD between 2010-2020 was carried out in 22 IBD reference centers in Greece. Patient characteristics such as disease profile, type of treatment, and disease activity during gestation were analyzed in correlation to the method of delivery, pregnancy outcomes, as well as breastfeeding and offspring health. Results: Two-hundred and twenty-three pregnancies in 175 IBD patients were registered in the study. 122 with Crohn’s disease (CD). Median age during diagnosis was 25.6 years (12-44), with median disease duration of 7.4 years (0-23). One-hundred and twenty-nine patients (58%) were recorded during their first pregnancy. Early pregnancy termination was reported by 48 patients (22%). Pregnancy as a result of in vitro fertilization (IVF) occurred in 15 cases (6.7%). At the beginning of gestation, 165 patients (74%) were under treatment: 48 with anti-TNF agents (29%), 43 with azathioprine (26%), 101 with 5-aminosalicylic acid formulations (61%) and 12 with steroids (7%). We recorded 49 cases of IBD flares (22%) during pregnancy. Two-thirds of them (n=30) were in remission at the onset of the pregnancy. Almost half of them (n=22) required corticosteroid treatment. Patients with ulcerative colitis (UC) were in greater risk of disease flare during pregnancy (p<0.001). All but 3 pregnancies (99.1%) resulted in uncomplicated delivery. In 147 cases (67.1%), cesarean delivery was performed. Two late fetal deaths (0.9%) were reported, both in patients with continuously active disease since the beginning of pregnancy. After delivery, 75 patients (34%) presented with a disease flare, which was associated with active disease at the beginning of pregnancy (p <0.001). Conclusion: The majority of female, Greek IBD patients, had a favorable pregnancy outcome. Active inflammation during gestation and UC diagnosis were associated with a negative impact on pregnancy outcomes. The results of this study are in favor of the continuation of IBD treatment during pregnancy.

Keywords: pregnancy, ulcerative colitis, Crohn disease, flare

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Authors: Shankar Kambhampaty, Harish Rohan Kambhampaty

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Data in IT systems in enterprises has been growing at a phenomenal pace. This has provided opportunities to run analytics to gather intelligence on key business parameters that enable them to provide better products and services to customers. While there are several artificial intelligence (AI/ML) and business intelligence (BI) tools and technologies available in the marketplace to run analytics, there is a need for an integrated view when developing intelligent solutions in enterprises. This paper progressively elaborates a reference model for enterprise solutions, builds an integrated view of data, information, and intelligence components, and presents a reference architecture for intelligent enterprise solutions. Finally, it applies the reference architecture to an insurance organization. The reference architecture is the outcome of experience and insights gathered from developing intelligent solutions for several organizations.

Keywords: architecture, model, intelligence, artificial intelligence, business intelligence, AI, BI, ML, analytics, enterprise

Procedia PDF Downloads 137