Search results for: sparse regression

Authors: Oscar Norman Nekesa, Yoshitaka Kajita

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Tom Mboya Street is a vital urban corridor within the spectrum of Nairobi city, it experiences high volumes of pedestrian and vehicular traffic. Despite past intervention measures to lessen this catastrophe, rates have remained high. This highlights significant safety concerns that need urgent attention. This study investigates the correlation and pedestrian accident predictability with significant independent variables using multiple linear regression to model to develop effective mobility management strategies for accident mitigation. The methodology involves collecting and analyzing data on pedestrian accidents and various related independent variables. Data sources include the National Transport and Safety Authority (NTSA), Kenya National Bureau of Statistics, and Nairobi City County records, covering five years. This study aims to investigate that traffic volumes (pedestrian and vehicle), Vehicular speed, human factors, illegal parking, policy issues, urban-land use, built environment, traffic signals conditions, inadequate lighting, and insufficient traffic control measures significantly have predictability with the rate of pedestrian accidents. Explanatory variables related to road design and geometry are significant in predictor models for the Tom Mboya Road link but less influential in junction along the 5 km stretch road models. The most impactful variable across all models was vehicular traffic flow. The study recommends infrastructural improvements, enhanced enforcement, and public awareness campaigns to reduce accidents and improve urban mobility. These insights can inform policy-making and urban planning to enhance pedestrian safety along the dense packed Tom Mboya Street and similar urban settings. The findings will inform evidence-based interventions to enhance pedestrian safety and improve urban mobility.

Keywords: multiple linear regression, urban mobility, traffic management, Nairobi, Tom Mboya street, infrastructure conditions., pedestrian safety, correlation and prediction

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Authors: D. S. Nagesh, G. L. Datta

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In the field of welding, various studies had been made by some of the previous investigators to predict as well as optimize weld bead geometric descriptors. Modeling of weld bead shape is important for predicting the quality of welds. In most of the cases, design of experiments technique to postulate multiple linear regression equations have been used. Nowadays, Genetic Algorithm (GA) an intelligent information treatment system with the characteristics of treating complex relationships as seen in welding processes used as a tool for inverse mapping/optimization of the process is attempted.

Keywords: smaw, genetic algorithm, bead geometry, optimization/inverse mapping

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Authors: D. S. Nagesh, G. L. Datta

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In the field of welding, various studies had been made by some of the previous investigators to predict as well as optimize weld bead geometric descriptors. Modeling of weld bead shape is important for predicting the quality of welds. In most of the cases design of experiments technique to postulate multiple linear regression equations have been used. Nowadays Genetic Algorithm (GA) an intelligent information treatment system with the characteristics of treating complex relationships as seen in welding processes used as a tool for inverse mapping/optimization of the process is attempted.

Keywords: SMAW, genetic algorithm, bead geometry, optimization/inverse mapping

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Authors: Kanokwan Tangchitnusorn, Patcharawalai Wongboonsin

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Following the ‘Golden Age of Welfare’ which enabled post-war prosperity to European citizens in 1950s, the world has witnessed the increasing mobility across borders of older citizens of First World countries. Then, in 1990s, the international retirement migration (IRM) of older persons has become a prominent trend, in which, it requires the integration of several fields of knowledge to explain, i.e. migration studies, tourism studies, as well as, social gerontology. However, while the studies of the IRM to developed destinations in Europe (e.g. Spain, Malta, Portugal, Italy), and the IRM to developing countries like Mexico, Panama, and Morocco have been largely studied in recent decades due to their massive migration volume, the study of the IRM to remoter destinations has been far more relatively sparse and incomplete. Developing countries in Southeast Asia have noticed the increasing number of retired expats, particularly to Thailand, where the number of foreigners applying for retirement visa increased from 10,709 in 2005 to 60,046 in 2014. Additionally, it was evident that the majority of Thailand’s retirement visa applicants were Westerners, i.e. citizens of the United Kingdom, the United States, Germany, and the Nordic countries, respectively. As such trend just becoming popular in Thailand in recent decades, little is known about the IRM populations, their well-being, and their future migration plans. This study aimed to examine the subjective wellbeing or the self-evaluations of own well-being among Western retirees in Thailand, as well as, their future migration plans as whether they planned to stay here for life or otherwise. The author employed a mixed method to obtain both quantitative and qualitative data during October 2015 – May 2016, including 330 self-administered questionnaires (246 online and 84 hard-copied responses), and 21 in-depth interviews of the Western residents in Nan (2), Pattaya (4), and Chiang Mai (15). As derived from the integration of previous subjective well-being measurements (i.e. Personal Wellbeing Index (PWI), Global AgeWatch Index, and OECD guideline on measuring subjective wellbeing), this study would measure the subjective well-being of Western retirees in Thailand in 7 dimensions, including standard of living, health status, personal relationships, social connections, environmental quality, personal security and local infrastructure.

Keywords: international retirement migration, ageing, mobility, wellbeing, Western, Thailand

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Authors: Yelin Zhao, Xinxiu Li, Martin Smelik, Oleg Sysoev, Firoj Mahmud, Dina Mansour Aly, Mikael Benson

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Background: Early diagnosis of pancreatic cancer is clinically challenging due to vague, or no symptoms, and lack of biomarkers. Polygenic risk score (PRS) scores may provide a valuable tool to assess increased or decreased risk of PC. This study aimed to develop such PRS by filtering genetic variants identified by GWAS using transcriptional programs identified by single-cell RNA sequencing (scRNA-seq). Methods: ScRNA-seq data from 24 pancreatic ductal adenocarcinoma (PDAC) tumor samples and 11 normal pancreases were analyzed to identify differentially expressed genes (DEGs) in in tumor and microenvironment cell types compared to healthy tissues. Pathway analysis showed that the DEGs were enriched for hundreds of significant pathways. These were clustered into 40 “programs” based on gene similarity, using the Jaccard index. Published genetic variants associated with PDAC were mapped to each program to generate program PRSs (pPRSs). These pPRSs, along with five previously published PRSs (PGS000083, PGS000725, PGS000663, PGS000159, and PGS002264), were evaluated in a European-origin population from the UK Biobank, consisting of 1,310 PDAC participants and 407,473 non-pancreatic cancer participants. Stepwise Cox regression analysis was performed to determine associations between pPRSs with the development of PC, with adjustments of sex and principal components of genetic ancestry. Results: The PDAC genetic variants were mapped to 23 programs and were used to generate pPRSs for these programs. Four distinct pPRSs (P1, P6, P11, and P16) and two published PRSs (PGS000663 and PGS002264) were significantly associated with an increased risk of developing PC. Among these, P6 exhibited the greatest hazard ratio (adjusted HR[95% CI] = 1.67[1.14-2.45], p = 0.008). In contrast, P10 and P4 were associated with lower risk of developing PC (adjusted HR[95% CI] = 0.58[0.42-0.81], p = 0.001, and adjusted HR[95% CI] = 0.75[0.59-0.96], p = 0.019). By comparison, two of the five published PRS exhibited an association with PDAC onset with HR (PGS000663: adjusted HR[95% CI] = 1.24[1.14-1.35], p < 0.001 and PGS002264: adjusted HR[95% CI] = 1.14[1.07-1.22], p < 0.001). Conclusion: Compared to published PRSs, scRNA-seq-based pPRSs may be used not only to assess increased but also decreased risk of PDAC.

Keywords: cox regression, pancreatic cancer, polygenic risk score, scRNA-seq, UK biobank

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Authors: Katherine Maurer

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Background and purpose: Violence that occurs within families is a global social problem. Children who are victims or witness to family violence are at risk for many negative effects both proximally and distally. One of the most disconcerting long-term effects occurs when child victims become adult perpetrators: the intergenerational transmission of family violence (ITFV). Early identification of those children most at risk for ITFV is needed to inform interventions to prevent future family violence perpetration and victimization. Only about 25-30% of child family violence victims become perpetrators of adult family violence (either child abuse, partner abuse, or both). Prior research has primarily been conducted using dichotomous measures of exposure (yes; no) to predict ITFV, given the low incidence rate in community samples. It is often assumed that exposure to greater amounts of violence predicts greater risk of ITFV. However, no previous longitudinal study with a community sample has tested a dose-response model of exposure to physical child abuse and parental physical intimate partner violence (IPV) using count data of frequency and severity of violence to predict adult ITFV. The current study used advanced statistical methods to test if increased childhood exposure would predict greater risk of ITFV. Methods: The study utilized 3 panels of prospective data from a cohort of 15 year olds (N=338) from the Project on Human Development in Chicago Neighborhoods longitudinal study. The data were comprised of a stratified probability sample of seven ethnic/racial categories and three socio-economic status levels. Structural equation modeling was employed to test a hurdle regression model of dose-response to predict ITFV. A version of the Conflict Tactics Scale was used to measure physical violence victimization, witnessing parental IPV and young adult IPV perpetration and victimization. Results: Consistent with previous findings, past 12 months incidence rates severity and frequency of interpersonal violence were highly skewed. While rates of parental and young adult IPV were about 40%, an unusually high rate of physical child abuse (57%) was reported. The vast majority of a number of acts of violence, whether minor or severe, were in the 1-3 range in the past 12 months. Reported frequencies of more than 5 times in the past year were rare, with less than 10% of those reporting more than six acts of minor or severe physical violence. As expected, minor acts of violence were much more common than acts of severe violence. Overall, regression analyses were not significant for the dose-response model of ITFV. Conclusions and implications: The results of the dose-response model were not significant due to a lack of power in the final sample (N=338). Nonetheless, the value of the approach was confirmed for the future research given the bi-modal nature of the distributions which suggest that in the context of both child physical abuse and physical IPV, there are at least two classes when frequency of acts is considered. Taking frequency into account in predictive models may help to better understand the relationship of exposure to ITFV outcomes. Further testing using hurdle regression models is suggested.

Keywords: intergenerational transmission of family violence, physical child abuse, intimate partner violence, structural equation modeling

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Authors: Desplanches Maxime

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Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

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Authors: Gabriel Legorreta Paulin, Marcus I. Bursik, Lilia Arana Salinas, Fernando Aceves Quesada

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In volcanic environments, landslides and debris flows occur continually along stream systems of large stratovolcanoes. This is the case on Pico de Orizaba volcano, the highest mountain in Mexico. The volcano has a great potential to impact and damage human settlements and economic activities by landslides. People living along the lower valleys of Pico de Orizaba volcano are in continuous hazard by the coalescence of upstream landslide sediments that increased the destructive power of debris flows. These debris flows not only produce floods, but also cause the loss of lives and property. Although the importance of assessing such process, there is few landslide inventory maps and landslide susceptibility assessment. As a result in México, no landslide susceptibility models assessment has been conducted to evaluate advantage and disadvantage of models. In this study, a comprehensive study of landslide susceptibility models assessment using GIS technology is carried out on the SE flank of Pico de Orizaba volcano. A detailed multi-temporal landslide inventory map in the watershed is used as framework for the quantitative comparison of two landslide susceptibility maps. The maps are created based on 1) the Stability Index MAPping (SINMAP) model by using default geotechnical parameters and 2) by using findings of volcanic soils geotechnical proprieties obtained in the field. SINMAP combines the factor of safety derived from the infinite slope stability model with the theory of a hydrologic model to produce the susceptibility map. It has been claimed that SINMAP analysis is reasonably successful in defining areas that intuitively appear to be susceptible to landsliding in regions with sparse information. The validations of the resulting susceptibility maps are performed by comparing them with the inventory map under LOGISNET system which provides tools to compare by using a histogram and a contingency table. Results of the experiment allow for establishing how the individual models predict the landslide location, advantages, and limitations. The results also show that although the model tends to improve with the use of calibrated field data, the landslide susceptibility map does not perfectly represent existing landslides.

Keywords: GIS, landslide, modeling, LOGISNET, SINMAP

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Authors: Diego Liberati

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Standard molecular modeling is traditionally done through Schroedinger equations via the help of powerful tools helping to manage them atom by atom, often needing High Performance Computing. Here, a full portfolio of new tools, conjugating statistical inference in the so called eXplainable Artificial Intelligence framework (in the form of Machine Learning of understandable rules) to the more traditional modeling and simulation control theory of mixed dynamic logic hybrid processes, is offered as quite a general purpose even if making an example to a popular chemical physics set of problems.

Keywords: understandable rules ML, k-means, PCA, PieceWise Affine Auto Regression with eXogenous input

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Authors: Georges Jabbour

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Background and aims: This two-year follow-up study explores the long-term sustainability of physical activity (PA) levels in young people with type 1 diabetes, focusing on the relationship between PA, hypoglycemia, and behavioral scores. The literature highlights the importance of PA and its health benefits, as well as the barriers to engaging in PA practices. Studies have shown that individuals with high levels of vigorous physical activity have higher fear of hypoglycemia (FOH) scores and more hypoglycemia episodes. Considering that hypoglycemia episodes are a major barrier to physical activity, and many studies reported a negative association between PA and high FOH scores, it cannot be guaranteed that those experiencing hypoglycemia over a long period will remain active. Building on that, the present work assesses whether high PA levels, despite elevated hypoglycemia risk, can be maintained over time. The study tracks PA levels at one and two years, correlating them with hypoglycemia instances and Fear of Hypoglycemia (FOH) scores. Materials and methods: A self-administered questionnaire was completed by 61 youth with T1D, and their PA was assessed. Hypoglycemia episodes, fear of hypoglycemia scores and HbA1C levels were collected. All assessments were realized at baseline (visit 0: V0), one year (V1) and two years later (V2). For the purpose of the present work, we explore the relationships between PA levels, hypoglycemia episodes, and FOH scores at each time point. We used multiple linear regression to model the mean outcomes for each exposure of interest. Results: Findings indicate no changes in total moderate to vigorous PA (MVPA) and VPA levels among visits, and HbA1c (%) was negatively correlated with the total amount of VPA per day in minutes (β= -0.44; p=0.01, β= -0.37; p=0.04, and β= -0.66; p=0.01 for V0, V1, and V2, respectively). Our linear regression model reported a significant negative correlation between VPA and FOH across the visits (β=-0.59, p=0.01; β= -0.44, p=0.01; and β= -0.34, p=0.03 for V0, V1, and V2, respectively), and HbA1c (%) was influenced by both the number of hypoglycemic episodes and FOH score at V2 (β=0.48; p=0.02 and β=0.38; p=0.03, respectively). Conclusion: The sustainability of PA levels and HbA1c (%) in young individuals with type 1 diabetes is influenced by various factors, including fear of hypoglycemia. Understanding these complex interactions is essential for developing effective interventions to promote sustained PA levels in this population. Our results underline the necessity of a multi-strategic approach to promoting active lifestyles among diabetic youths. This approach should synergize PA enhancement with vigilant glucose monitoring and effective FOH management.

Keywords: physical activity, hypoglycemia, fear of hypoglycemia, youth

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Authors: Yudia Mailani Putri, Martalena Purba, B. J. Istiti Kandarina

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Background: Obesity has been recognized as a global health problem. Individuals classified as overweight and obese are increasing at an alarming rate. This condition is associated with psychological and physiological problems. as a person reaches adulthood, somatic growth ceases. At this stage, the human body has developed fully, to a stable state. As the capital of Riau Province in Indonesia, Pekanbaru is dominated by Malay ethnic population habitually consuming cholesterol-rich fatty foods as a daily menu, a trigger to the onset of obesity resulting in high prevalence of degenerative diseases. Research objectives: The aim of this study is elaborating the relationship between high-fat consumption pattern, stress level, physical activity and the incidence of obesity in adult women in Pekanbaru city. Research Methods: Among the combined research methods applied in this study, the first stage is quantitative observational, analytical cross-sectional research design with adult women aged 20-40 living in Pekanbaru city. The sample consists of 200 women with BMI≥25. Sample data is processed with univariate, bivariate (correlation and simple linear regression) and multivariate (multiple linear regression) analysis. The second phase is qualitative descriptive study purposive sampling by in-depth interviews. six participants withdrew from the study. Results: According to the results of the bivariate analysis, there are relationships between the incidence of obesity and the pattern of high fat foods consumption (energy intake (p≤0.000; r = 0.536), protein intake (p≤0.000; r=0.307), fat intake (p≤0.000; r=0.416), carbohydrate intake (p≤0.000; r=0.430), frequency of fatty food consumption (p≤0.000; r=0.506) and frequency of viscera foods consumption (p≤0.000; r=0.535). There is a relationship between physical activity and incidence of obesity (p≤0.000; r=-0.631). However, there is no relationship between the level of stress (p=0.741; r=0.019-) and the incidence of obesity. Physical activity is a predominant factor in the incidence of obesity in adult women in Pekanbaru city. Conclusion: There are relationships between high-fat food consumption pattern, physical activity and the incidence of obesity in Pekanbaru city whereas physical activity is a predominant factor in the occurrence of obesity, supported by the unchangeable pattern of high-fat foods consumption.

Keywords: obesity, adult, high in fat, stress, physical activity, consumption pattern

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Authors: Nicola Colaninno, Eugenio Morello

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The urban environment affects local-to-global climate and, in turn, suffers global warming phenomena, with worrying impacts on human well-being, health, social and economic activities. Physic-morphological features of the built-up space affect urban air temperature, locally, causing the urban environment to be warmer compared to surrounding rural. This occurrence, typically known as the Urban Heat Island (UHI), is normally assessed by means of air temperature from fixed weather stations and/or traverse observations or based on remotely sensed Land Surface Temperatures (LST). The information provided by ground weather stations is key for assessing local air temperature. However, the spatial coverage is normally limited due to low density and uneven distribution of the stations. Although different interpolation techniques such as Inverse Distance Weighting (IDW), Ordinary Kriging (OK), or Multiple Linear Regression (MLR) are used to estimate air temperature from observed points, such an approach may not effectively reflect the real climatic conditions of an interpolated point. Quantifying local UHI for extensive areas based on weather stations’ observations only is not practicable. Alternatively, the use of thermal remote sensing has been widely investigated based on LST. Data from Landsat, ASTER, or MODIS have been extensively used. Indeed, LST has an indirect but significant influence on air temperatures. However, high-resolution near-surface air temperature (NSAT) is currently difficult to retrieve. Here we have experimented Geographically Weighted Regression (GWR) as an effective approach to enable NSAT estimation by accounting for spatial non-stationarity of the phenomenon. The model combines on-site measurements of air temperature, from fixed weather stations and satellite-derived LST. The approach is structured upon two main steps. First, a GWR model has been set to estimate NSAT at low resolution, by combining air temperature from discrete observations retrieved by weather stations (dependent variable) and the LST from satellite observations (predictor). At this step, MODIS data, from Terra satellite, at 1 kilometer of spatial resolution have been employed. Two time periods are considered according to satellite revisit period, i.e. 10:30 am and 9:30 pm. Afterward, the results have been downscaled at 30 meters of spatial resolution by setting a GWR model between the previously retrieved near-surface air temperature (dependent variable), the multispectral information as provided by the Landsat mission, in particular the albedo, and Digital Elevation Model (DEM) from the Shuttle Radar Topography Mission (SRTM), both at 30 meters. Albedo and DEM are now the predictors. The area under investigation is the Metropolitan City of Milan, which covers an area of approximately 1,575 km2 and encompasses a population of over 3 million inhabitants. Both models, low- (1 km) and high-resolution (30 meters), have been validated according to a cross-validation that relies on indicators such as R2, Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). All the employed indicators give evidence of highly efficient models. In addition, an alternative network of weather stations, available for the City of Milano only, has been employed for testing the accuracy of the predicted temperatures, giving and RMSE of 0.6 and 0.7 for daytime and night-time, respectively.

Keywords: urban climate, urban heat island, geographically weighted regression, remote sensing

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Authors: Yen Ling Liu, Shu-Fen Wu, Chen-Fuh Lam, I-Ling Tsai, Chia-Yu Chen

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Purpose: Nurse anesthetists are confronting extraordinarily high job stress in their daily practice, deriving from the fast-track anesthesia care, risk of perioperative complications, routine rotating shifts, teaching programs and interactions with the surgical team in the operating room. This study investigated the influence of work stress on the burnout and turnover intention of nurse anesthetists in a regional general hospital in Southern Taiwan. Methods: This was a descriptive correlational study carried out in 66 full-time nurse anesthetists. Data was collected from March 2017 to June 2017 by in-person interview, and a self-administered structured questionnaire was completed by the interviewee. Outcome measurements included the Practice Environment Scale of the Nursing Work Index (PES-NWI), Maslach Burnout Inventory (MBI) and nursing staff turnover intention. Numerical data were analyzed by descriptive statistics, independent t test, or one-way ANOVA. Categorical data were compared using the chi-square test (x²). Datasets were computed with Pearson product-moment correlation and linear regression. Data were analyzed by using SPSS 20.0 software. Results: The average score for job burnout was 68.7916.67 (out of 100). The three major components of burnout, including emotional depletion (mean score of 26.32), depersonalization (mean score of 13.65), and personal(mean score of 24.48). These average scores suggested that these nurse anesthetists were at high risk of burnout and inversely correlated with turnover intention (t = -4.048, P < 0.05). Using linear regression model, emotional exhaustion and depersonalization were the two independent factors that predicted turnover intention in the nurse anesthetists (19.1% in total variance). Conclusion/Implications for Practice: The study identifies that the high risk of job burnout in the nurse anesthetists is not simply derived from physical overload, but most likely resulted from the additional emotional and psychological stress. The occurrence of job burnout may affect the quality of nursing work, and also influence family harmony, in turn, may increase the turnover rate. Multimodal approach is warranted to reduce work stress and job burnout in nurse anesthetists to enhance their willingness to contribute in anesthesia care.

Keywords: anesthesia nurses, burnout, job, turnover intention

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Authors: Md Monoarul Haque

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Nutritional status is a sensitive indicator of community health and nutrition among preschool children, especially the prevalence of undernutrition that affects all dimensions of human development and leads to growth faltering in early life. The present study is an attempt to assess the food intake pattern and nutritional status of pre-school Chakma tribe children. It was a cross-sectional community based study. The subjects were selected purposively. This study was conducted at Savar Upazilla of Rangamati. Rangamati is located in the Chittagong Division. Anthropometric data height and weight of the study subjects were collected by standard techniques. Nutritional status was measured using Z score according WHO classification. χ2 test, independent t-test, Pearson’s correlation, multiple regression and logistic regression was performed as P<0.05 level of significance. Statistical analyses were performed by appropriate univariate and multivariate techniques using SPSS windows 11.5. Moderate (-3SD to <-2SD) to severe underweight (<-3SD) were 23.8% and 76.2% study subjects had normal weight for their age. Moderate (-3SD to <-2SD) to severe (<-3SD) stunted children were only 25.6% and 74.4% children were normal and moderate to severe wasting were 14.7% whereas normal child was 85.3%. Significant association had been found between child nutritional status and monthly family income, mother education and occupation of father and mother. Age, sex and incomes of the family, education of mother and occupation of father were significantly associated with WAZ and HAZ of the study subjects (P=0.0001, P=0.025, P=0.001 and P=0.0001, P=0.003, P=0.031, P=0.092, P=0.008). Maximum study subjects took local small fish and some traditional tribal food like bashrool, jhijhipoka and pork very much popular food among tribal children. Energy, carbohydrate and fat intake was significantly associated with HAZ, WAZ, BAZ and MUACZ. This study demonstrates that malnutrition among tribal children in Bangladesh is much better than national scenario in Bangladesh. Significant association was found between child nutritional status and family monthly income, mother education and occupation of father and mother. Most of the study subjects took local small fish and some traditional tribal food. Significant association was also found between child nutritional status and dietary intake of energy, carbohydrate and fat.

Keywords: food intake pattern, nutritional status, preschool children, Chakma ethnic community

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Authors: A. Saghatelyan, Sh. Asmaryan, G. Tepanosyan, V. Muradyan

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One of major concern to Armenia has been soil degradation emerged as a result of unsustainable management and use of grasslands, this in turn largely impacting environment, agriculture and finally human health. Hence, assessment of soil degradation is an essential and urgent objective set out to measure its possible consequences and develop a potential management strategy. Since recently, an essential tool for assessing pasture degradation has been remote sensing (RS) technologies. This research was done with an intention to measure preciseness of Linear spectral unmixing (LSU) and NDVI-SMA methods to estimate soil surface components related to degradation (fractional vegetation cover-FVC, bare soils fractions, surface rock cover) and determine appropriateness of these methods for mapping man-induced soil degradation in high mountain pastures. Taking into consideration a spatially complex and heterogeneous biogeophysical structure of the studied site, we used high resolution multispectral QuickBird imagery of a pasture site in one of Armenia’s rural communities - Nerkin Sasoonashen. The accuracy assessment was done by comparing between the land cover abundance data derived through RS methods and the ground truth land cover abundance data. A significant regression was established between ground truth FVC estimate and both NDVI-LSU and LSU - produced vegetation abundance data (R2=0.636, R2=0.625, respectively). For bare soil fractions linear regression produced a general coefficient of determination R2=0.708. Because of poor spectral resolution of the QuickBird imagery LSU failed with assessment of surface rock abundance (R2=0.015). It has been well documented by this particular research, that reduction in vegetation cover runs in parallel with increase in man-induced soil degradation, whereas in the absence of man-induced soil degradation a bare soil fraction does not exceed a certain level. The outcomes show that the proposed method of man-induced soil degradation assessment through FVC, bare soil fractions and field data adequately reflects the current status of soil degradation throughout the studied pasture site and may be employed as an alternate of more complicated models for soil degradation assessment.

Keywords: Armenia, linear spectral unmixing, remote sensing, soil degradation

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Authors: Shamie Kumar

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Background: Radiologists and radiographers (RR) need to educate themselves and their colleagues to ensure that AI is integrated safely, useful, and in a meaningful way with the direction it always benefits the patients. AI education and training are fundamental to the way RR work and interact with it, such that they feel confident using it as part of their clinical practice in a way they understand it. Methodology: This exploratory research will outline the current educational and training gaps for radiographers and radiologists in AI radiology diagnostics. It will review the status, skills, challenges of educating and teaching. Understanding the use of artificial intelligence within daily clinical practice, why it is fundamental, and justification on why learning about AI is essential for wider adoption. Results: The current knowledge among RR is very sparse, country dependent, and with radiologists being the majority of the end-users for AI, their targeted training and learning AI opportunities surpass the ones available to radiographers. There are many papers that suggest there is a lack of knowledge, understanding, and training of AI in radiology amongst RR, and because of this, they are unable to comprehend exactly how AI works, integrates, benefits of using it, and its limitations. There is an indication they wish to receive specific training; however, both professions need to actively engage in learning about it and develop the skills that enable them to effectively use it. There is expected variability amongst the profession on their degree of commitment to AI as most don’t understand its value; this only adds to the need to train and educate RR. Currently, there is little AI teaching in either undergraduate or postgraduate study programs, and it is not readily available. In addition to this, there are other training programs, courses, workshops, and seminars available; most of these are short and one session rather than a continuation of learning which cover a basic understanding of AI and peripheral topics such as ethics, legal, and potential of AI. There appears to be an obvious gap between the content of what the training program offers and what the RR needs and wants to learn. Due to this, there is a risk of ineffective learning outcomes and attendees feeling a lack of clarity and depth of understanding of the practicality of using AI in a clinical environment. Conclusion: Education, training, and courses need to have defined learning outcomes with relevant concepts, ensuring theory and practice are taught as a continuation of the learning process based on use cases specific to a clinical working environment. Undergraduate and postgraduate courses should be developed robustly, ensuring the delivery of it is with expertise within that field; in addition, training and other programs should be delivered as a way of continued professional development and aligned with accredited institutions for a degree of quality assurance.

Keywords: artificial intelligence, training, radiology, education, learning

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Authors: Caroline Nnokwe, Iheanyi Eneremadu

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Teachers and principals are vital and integral parts of the educational system. For educational objectives to be met, the role of teachers and the functions of the principals are not to be overlooked. However, the inability of teachers and principals to carry out their roles effectively has impacted the outcome of the students’ performance. The study, therefore, examined teachers’ roles and principal’s administrative functions as correlates of effective academic performance of public secondary school students in Imo state, Nigeria. Four research questions and two hypotheses guided the study. The study adopted a correlation research design. The sample size was 5,438 respondents via the Yaro-Yamane technique, which consists of 175 teachers, 13 principals and 5,250 students using the proportional stratified random sampling technique. The instruments for data collection were a researcher-made questionnaire titled Teachers’ Role/Principals’ Administrative Functions Questionnaire (TRPAFQ) with a Cronbach Alpha coefficient of .82 and student's internal results obtained from the school authorities. Data collected were analyzed using the Pearson product-moment correlation coefficient and simple linear regression. Research questions were answered using Pearson Product Moment Correlation statistics, while the hypotheses were tested at 0.05 level of significance using regression analysis. The findings of the study showed that the educational qualification of teachers, organizing, and planning correlated student’s academic performance to a great extent, while availability and proper use of instructional materials by teachers correlated the academic performance of students to a very high extent. The findings also revealed that there is a significant relationship between teachers’ role, principals’ administrative functions and student’s academic performance of public secondary schools in Imo State, The study recommended among others that there is the need for government, through the ministry of education, and education authorities to adequately staff their supervisory department in order to carry out proper supervision of secondary school teachers, and also provide adequate instructional materials to ensure greater academic performance among secondary school students of Imo state, Nigeria.

Keywords: instructional materials, principals’ administrative functions, students’ academic performance, teacher role

Procedia PDF Downloads 86

Authors: I. Rodionov, A. Semenov, E. Gosteva, O. Sokolova

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Currently, the venture capital becomes more and more advanced and effective source of the innovation project financing, connected with a high-risk level. In the developed countries, it plays a key role in transforming innovation projects into successful businesses and creating prosperity of the modern economy. Actually, in Russia there are many necessary preconditions for creation of the effective venture investment system: the network of the public institutes for innovation financing operates; there is a significant number of the small and medium-sized enterprises, capable to sell production with good market potential. However, the current system does not confirm the necessary level of efficiency in practice that can be substantially explained by the absence of the accurate plan of action to form the national venture model and by the lack of experience of successful venture deals with profitable exits in Russian economy. This paper studies the influence of various factors on the venture industry development by the example of the IT-sector in Russia. The choice of the sector is based on the fact, that this segment is the main driver of the venture capital market growth in Russia, and the necessary set of data exists. The size of investment of the second round is used as the dependent variable. To analyse the influence of the previous round such determinant as the volume of the previous (first) round investments is used. There is also used a dummy variable in regression to examine that the participation of an investor with high reputation and experience in the previous round can influence the size of the next investment round. The regression analysis of short-term interrelations between studied variables reveals prevailing influence of the volume of the first round investments on the venture investments volume of the second round. Because of the research, the participation of investors with first-class reputation has a small impact on an indicator of the value of investment of the second round. The expected positive dependence of the second round investments on the forecasted market growth rate now of the deal is also rejected. So, the most important determinant of the value of the second-round investment is the value of first–round investment, so it means that the most competitive on the Russian market are the start-up teams which can attract more money on the start, and the target market growth is not the factor of crucial importance.

Keywords: venture industry, venture investment, determinants of the venture sector development, IT-sector

Procedia PDF Downloads 353

Authors: Jamel Slaughter

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Father involvement across the development of a child has been linked to children’s psychological adjustment, fewer behavioral problems, and higher educational attainment. Conversely, there is much less research that highlights father involvement in relation to childhood development during early childhood period prior to preschool age (ages 1-3 years). Most research on fathers and child outcomes have been limited by its focus on the stages of adolescence, middle childhood, and infancy. This study examined the influence of father involvement, during the toddler stage, on 5th grade cognitive development, rule-breaking, and behavior outcomes measured by Child Behavior Checklist (CBCL) scores. Using data from the Early Head Start Research and Evaluation (EHSRE) Study, 1996-2010: United States, a total of 3,001 children and families were identified in 17 sites (cities), representing a diverse demographic sample. An independent samples t-test was run to compare cognitive development, aggressive, and rule-breaking behavior mean scores among children who had early continuous father involvement for the first 14 – 36 months to children who did not have early continuous father involvement for the first 14 – 36 months. Multiple linear regression was conducted to determine if continuous, or non-continuous father involvement (14 month-36 months), can be used to predict outcome scores on the Child Behavior Checklist in aggressive behavior, rule-breaking behavior, and cognitive development, at 5th grade. A statistically significant mean difference in cognitive development scores were found for children who had continuous father involvement (M=1.92, SD=2.41, t (1009) =2.81, p =.005, 95% CI=.146 to .828) compared to those who did not (M=2.60, SD=3.06, t (1009) =-2.38, p=.017, 95% CI= -1.08 to -.105). There was also a statistically significant mean difference in rule-breaking behavior scores between children who had early continuous father involvement (M=1.95, SD=2.33, t (1009) = 3.69, p <.001, 95% CI= .287 to .940), compared to those that did not (M=2.87, SD=2.93, t (1009) = -3.49, p =.001, 95% CI= -1.30 to -.364). No statistically significant difference was found in aggressive behavior scores. Multiple linear regression was performed using continuous father involvement to determine which has the largest relationship to rule-breaking behavior and cognitive development based on CBCL scores. Rule-breaking behavior was found to be significant (F (2, 1008) = 8.353, p<.001), with an R2 of .016. Cognitive development was also significant (F (2, 1008) = 4.44, p=.012), with an R2 of .009. Early continuous father involvement was a significant predictor of rule-breaking behavior and cognitive development at middle childhood. Findings suggest early continuous father involvement during the first 14 – 36 months of their children’s life, may lead to lower levels of rule-breaking behaviors and thought problems at 5th grade.

Keywords: cognitive development, early continuous father involvement, middle childhood, rule-breaking behavior

Procedia PDF Downloads 302

Authors: Olubukayo-Opeyemi Oyetayo, Oscar Mendez-Lucio, Andreas Bender, Hans Kiefer

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The thermal melting curve of a protein provides information on its conformational stability and could provide cues on its aggregation behavior. Naturally-occurring osmolytes have been shown to improve the thermal stability of most proteins in a concentration-dependent manner. They are therefore commonly employed as additives in therapeutic protein purification and formulation. A number of intertwined and seemingly conflicting mechanisms have been put forward to explain the observed stabilizing effects, the most prominent being the preferential exclusion mechanism. We attempted to probe and summarize molecular mechanisms for thermal stabilization of a monoclonal antibody (mAb) by developing quantitative structure-activity relationships using a rationally-selected library of 120 osmolyte-like compounds in the polyhydric alcohols, amino acids and methylamines classes. Thermal stabilization potencies were experimentally determined by thermal shift assays based on differential scanning fluorimetry. The cross-validated QSAR model was developed by partial least squares regression using descriptors generated from Molecular Operating Environment software. Careful evaluation of the results with the use of variable importance in projection parameter (VIP) and regression coefficients guided the selection of the most relevant descriptors influencing mAb thermal stability. For the mAb studied and at pH 7, the thermal stabilization effects of tested compounds correlated positively with their fractional polar surface area and inversely with their fractional hydrophobic surface area. We cannot claim that the observed trends are universal for osmolyte-protein interactions because of protein-specific effects, however this approach should guide the quick selection of (de)stabilizing compounds for a protein from a chemical library. Further work with a large variety of proteins and at different pH values would help the derivation of a solid explanation as to the nature of favorable osmolyte-protein interactions for improved thermal stability. This approach may be beneficial in the design of novel protein stabilizers with optimal property values, especially when the influence of solution conditions like the pH and buffer species and the protein properties are factored in.

Keywords: thermal stability, monoclonal antibodies, quantitative structure-activity relationships, osmolytes

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Authors: Bedilu Tafesse

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The diversity and ecological analysis of vascular epiphytes was studied in Gera Forest in southwestern Ethiopia at altitudes between 1600 and 2400 m.a.s.l. A total area of 4.5 ha was surveyed in coffee and non-coffee forest vegetation. Fifty sampling plots, each 30 m x 30 m (900 m2), were used for the purpose of data collection. A total of 59 species of vascular epiphytes were recorded, of which 34 (59%) were holo epiphytes, two (4%) were hemi epiphytes and 22 (37%) species were accidental vascular epiphytes. To study the altitudinal distribution of vascular epiphytes, altitudes were classified into higher >2000, middle 1800-2000 and lower 1600-1800 m.a.s.l. According to Shannon-Wiener Index (H/= 3.411) of alpha diversity the epiphyte community in the study area is medium. There was a statistically significant difference between host bark type and epiphyte richness as determined by one-way ANOVA p = 0.001 < 0.05. The post-hoc test shows that there is significant difference of vascular epiphytes richness between smooth bark with rough, flack and corky bark (P =0.001< 0.05), as well as rough and cork bark (p =0.43 <0.05). However, between rough and flack bark (p = 0.753 > 0.05) and between flack and corky bark (p = 0.854 > 0.05) no significant difference of epiphyte abundance was observed. Rough bark had 38%, corky 26%, flack 25%, and only 11% vascular epiphytes abundance occurred on smooth bark. The regression correlation test, (R2 = 0.773, p = 0.0001 < 0.05), showed that the number of species of vascular epiphytes and host DBH size are positively correlated. The regression correlation test (R2 = 0.28, p = 0.0001 < 0.05), showed that the number of species and host tree height positively correlated. The host tree preference of vascular epiphytes was recorded for only Vittaria volkensii species hosted on Syzygium guineense trees. The result of similarity analysis indicated that Gera Forest showed the highest vascular epiphytic similarity (0.35) with Yayu Forest and shared the least vascular epiphytic similarity (0.295) with Harenna Forest. It was concluded that horizontal stems and branches, large and rough, flack and corky bark type trees are more suitable for vascular epiphytes seedling attachments and growth. Conservation and protection of these phorophytes are important for the survival of vascular epiphytes and increase their ecological importance.

Keywords: accidental epiphytes, hemiepiphyte, holoepiphyte, phorophyte

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Authors: Rubi Alvarez-Rodriguez

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Traditionally, eco-centric and anthropocentric forms of environmentalism have been seen as mutually exclusive. While eco-centrism focuses on global environmental issues, anthropocentrism is concerned with local ones. The objective of this paper is to characterize the relationship between eco-centric and anthropocentric attitudes across 43 countries. This study analysed secondary data from the 2005 World Values Survey, using a standard linear regression approach. It is shown that eco-centric and anthropocentric attitudes are not mutually exclusive and that the predominance of one over the other is best predicted by a country’s level of wealth.

Keywords: anthropocentrism, eco-centrism, pro-environmental attitudes, wealth

Procedia PDF Downloads 360

Authors: Mdluli Fezile, Schmidt Stefan, Thamaga-Chitja Joyce

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In view of the frequently reported foodborne disease outbreaks caused by contaminated fresh produce, consumers have a preference for foods that meet requisite hygiene standards to reduce the risk of foodborne illnesses. Producing good quality fresh produce then becomes critical in improving market access and food security, especially for small-scale farmers. Questions of hygiene and subsequent microbiological quality in the rural small-scale farming sector of South Africa are even more crucial, given the policy drive to develop small-scale farming as a measure for reinforcement of household food security and reduction of poverty. Farming practices and methods, throughout the fresh produce value chain, influence the quality of the final product, which in turn determines its success in the market. This study’s aim was to therefore determine the extent to which training on organic farming methods, including modules such as Importance of Production Hygiene, influenced the hygienic farming practices employed by eTholeni small-scale organic farmers in uMbumbulu, KwaZulu-Natal- South Africa. Questionnaires were administered to 73 uncertified organic farmers and analysis showed that a total of 33 farmers were trained and supplied the local Agri-Hub while 40 had not received training. The questionnaire probed respondents’ attitudes, knowledge of hygiene and composting practices. Data analysis included descriptive statistics such as the Chi-square test and a logistic regression model. Descriptive analysis indicated that a majority of the farmers (60%) were female, most of which (73%) were above the age of 40. The logistic regression indicated that factors such as farmer training and prior experience in the farming sector had a significant influence on hygiene practices both at 5% significance levels. These results emphasize the importance of training, education and farming experience in implementing good hygiene practices in small-scale farming. It is therefore recommended that South African policies should advocate for small-scale farmer training, not only for subsistence purposes, but also with an aim of supplying produce markets with high fresh produce.

Keywords: small-scale farmers, leafy salad vegetables, organic produce, food safety, hygienic practices, food security

Procedia PDF Downloads 425

Authors: R. Joseph Raviselvan, K. Ramanathan, P. Perumal, M. R. Thansekhar

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Hard coatings are widely used in cutting and forming tool industries. Titanium Nitride (TiN) possesses good hardness, strength and corrosion resistant. The coating properties are influenced by many process parameters. The coatings were deposited on steel substrate by changing the process parameters such as substrate temperature, nitrogen flow rate and target power in a D.C planer magnetron sputtering. The structure of coatings were analysed using XRD. The hardness of coatings was found using Micro hardness tester. From the experimental data, a regression model was developed and the optimum response was determined using Response Surface Methodology (RSM).

Keywords: hardness, RSM, sputtering, TiN XRD

Procedia PDF Downloads 321

Authors: Sahar Elsaleh, Ghada Farhat, Shaikha Al-Derham, Fasih Alam

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Background: Cesarean section (CS) delivery is one of the major concerns both in developing and developed countries. The rate of CS deliveries are on the rise globally, and especially in Qatar. Many socio-economic, demographic, clinical and institutional factors play an important role for cesarean sections. This study aims to investigate factors affecting the prevalence of CS among women in Qatar using the UNICEF’s Multiple Indicator Cluster Survey (MICS) 2012 database. Methods: The study has focused on the women’s questionnaire of the MICS, which was successfully distributed to 5699 participants. Following study inclusion and exclusion criteria, a final sample of 761 women aged 19- 49 years who had at least one delivery of giving birth in their lifetime before the survey were included. A number of socio-economic, demographic, clinical and institutional factors, identified through literature review and available in the data, were considered for the analyses. Bivariate and multivariate logistic regression models, along with a multi-level modeling to investigate clustering effect, were undertaken to identify the factors that affect CS prevalence in Qatar. Results: From the bivariate analyses the study has shown that, a number of categorical factors are statistically significantly associated with the dependent variable (CS). When identifying the factors from a multivariate logistic regression, the study found that only three categorical factors -‘age of women’, ‘place at delivery’ and ‘baby weight’ appeared to be significantly affecting the CS among women in Qatar. Although the MICS dataset is based on a cluster survey, an exploratory multi-level analysis did not show any clustering effect, i.e. no significant variation in results at higher level (households), suggesting that all analyses at lower level (individual respondent) are valid without any significant bias in results. Conclusion: The study found a statistically significant association between the dependent variable (CS delivery) and age of women, frequency of TV watching, assistance at birth and place of birth. These results need to be interpreted cautiously; however, it can be used as evidence-base for further research on cesarean section delivery in Qatar.

Keywords: cesarean section, factors, multiple indicator cluster survey, MICS database, Qatar

Procedia PDF Downloads 116

Authors: S. A. N. Danushka, T. A. Weerasinghe

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The diverse necessities of instruction could be addressed effectively with the support of new dimensions of ICT integrated learning such as blended learning –which is a combination of face-to-face and online instruction which ensures greater flexibility in student learning and congruity of course delivery. As blended learning has been the ‘new normality' in education, many experimental and quasi-experimental research studies provide ample of evidence on its successful implementation in many fields of studies, but it is hard to justify whether blended learning could work similarly in the delivery of technology-teacher development programmes (TTDPs). The present study is bound with the particular research uncertainty, and having considered existing research approaches, the study methodology was set to decide the efficient instructional strategies for flipped classroom learning in TTDPs. In a quasi-experimental pre-test and post-test design with a mix-method research approach, the major study objective was tested with two heterogeneous samples (N=135) identified in a virtual learning environment in a Sri Lankan university. Non-randomized informal ‘before-and-after without control group’ design was employed, and two data collection methods, identical pre-test and post-test and Likert-scale questionnaires were used in the study. Selected two instructional strategies, self-directed learning (SDL) and self-regulated learning (SRL), were tested in an appropriate instructional framework with two heterogeneous samples (pre-service and in-service teachers). Data were statistically analyzed, and an efficient instructional strategy was decided via t-test, ANOVA, ANCOVA. The effectiveness of the two instructional strategy implementation models was decided via multiple linear regression analysis. ANOVA (p < 0.05) shows that age, prior-educational qualifications, gender, and work-experiences do not impact on learning achievements of the two diverse groups of learners through the instructional strategy is changed. ANCOVA (p < 0.05) analysis shows that SDL is efficient for two diverse groups of technology-teachers than SRL. Multiple linear regression (p < 0.05) analysis shows that the staged self-directed learning (SSDL) model and four-phased model of motivated self-regulated learning (COPES Model) are efficient in the delivery of course content in flipped classroom learning.

Keywords: COPES model, flipped classroom learning, self-directed learning, self-regulated learning, SSDL model

Procedia PDF Downloads 197

Authors: Abbas Ahmadi, Bijan Raie, Mohammad Reza Neyshabouri, Mohammad Ali Ghorbani, Farrokh Asadzadeh

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In recent years, vast areas of Urmia Lake in Dasht-e-Tabriz has dried up leading to saline sediments exposure on the surface lake coastal areas being highly susceptible to wind erosion. This study was conducted to investigate wind erosion and its relevance to soil physicochemical properties and also modeling of wind erodibility (WE) using artificial intelligence techniques. For this purpose, 96 soil samples were collected from 0-5 cm depth in 414000 hectares using stratified random sampling method. To measure the WE, all samples (<8 mm) were exposed to 5 different wind velocities (9.5, 11, 12.5, 14.1 and 15 m s-1 at the height of 20 cm) in wind tunnel and its relationship with soil physicochemical properties was evaluated. According to the results, WE varied within the range of 76.69-9.98 (g m-2 min-1)/(m s-1) with a mean of 10.21 and coefficient of variation of 94.5% showing a relatively high variation in the studied area. WE was significantly (P<0.01) affected by soil physical properties, including mean weight diameter, erodible fraction (secondary particles smaller than 0.85 mm) and percentage of the secondary particle size classes 2-4.75, 1.7-2 and 0.1-0.25 mm. Results showed that the mean weight diameter, erodible fraction and percentage of size class 0.1-0.25 mm demonstrated stronger relationship with WE (coefficients of determination were 0.69, 0.67 and 0.68, respectively). This study also compared efficiency of multiple linear regression (MLR), gene expression programming (GEP), artificial neural network (MLP), artificial neural network based on genetic algorithm (MLP-GA) and artificial neural network based on whale optimization algorithm (MLP-WOA) in predicting of soil wind erodibility in Dasht-e-Tabriz. Among 32 measured soil variable, percentages of fine sand, size classes of 1.7-2.0 and 0.1-0.25 mm (secondary particles) and organic carbon were selected as the model inputs by step-wise regression. Findings showed MLP-WOA as the most powerful artificial intelligence techniques (R2=0.87, NSE=0.87, ME=0.11 and RMSE=2.9) to predict soil wind erodibility in the study area; followed by MLP-GA, MLP, GEP and MLR and the difference between these methods were significant according to the MGN test. Based on the above finding MLP-WOA may be used as a promising method to predict soil wind erodibility in the study area.

Keywords: wind erosion, erodible fraction, gene expression programming, artificial neural network

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Authors: Lalit Kumar, Rashid Al Shidi

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Phoenix dactylifera (date palm) is a major crop in many middle-eastern countries, including Oman. The Dubas bug Ommatissus lybicus is the main pest that affects date palm crops. However not all plantations are infested. It is still uncertain why some plantations get infested while others are not. This research investigated whether tree density and the system of planting (random versus systematic) had any relationship with infestation and levels of infestation. Remote Sensing and Geographic Information Systems were used to determine the density of trees (number of trees per unit area) while infestation levels were determined by manual counting of insects on 40 leaflets from two fronds on each tree, with a total of 20-60 trees in each village. The infestation was recorded as the average number of insects per leaflet. For tree density estimation, WorldView-3 scenes, with eight bands and 2m spatial resolution, were used. The Local maxima method, which depends on locating of the pixel of highest brightness inside a certain exploration window, was used to identify the trees in the image and delineating individual trees. This information was then used to determine whether the plantation was random or systematic. The ordinary least square regression (OLS) was used to test the global correlation between tree density and infestation level and the Geographic Weight Regression (GWR) was used to find the local spatial relationship. The accuracy of detecting trees varied from 83–99% in agricultural lands with systematic planting patterns to 50–70% in natural forest areas. Results revealed that the density of the trees in most of the villages was higher than the recommended planting number (120–125 trees/hectare). For infestation correlations, the GWR model showed a good positive significant relationship between infestation and tree density in the spring season with R² = 0.60 and medium positive significant relationship in the autumn season, with R² = 0.30. In contrast, the OLS model results showed a weaker positive significant relationship in the spring season with R² = 0.02, p < 0.05 and insignificant relationship in the autumn season with R² = 0.01, p > 0.05. The results showed a positive correlation between infestation and tree density, which suggests the infestation severity increased as the density of date palm trees increased. The correlation result showed that the density alone was responsible for about 60% of the increase in the infestation. This information can be used by the relevant authorities to better control infestations as well as to manage their pesticide spraying programs.

Keywords: dubas bug, date palm, tree density, infestation levels

Procedia PDF Downloads 193

Authors: Dana El-Mughayyar, Neil Manson, Erin Bigney, Eden Richardson, Dean Tripp, Edward Abraham

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Use of narcotics to treat pain has increased over the past two decades and is a contributing factor to the current public health crisis. Understanding the pre-operative risks of chronic narcotic use may be aided through investigation of psychological measures. The objective of the reported study is to determine predictors of narcotic use two years post-surgery in a thoracolumbar spine surgery population, including an array of psychological factors. A prospective observational study of 191 consecutively enrolled adult patients having undergone thoracolumbar spine surgery is presented. Baseline measures of interest included the Pain Catastrophizing Scale (PCS), Tampa Scale for Kinesiophobia, Multidimensional Scale for Perceived Social Support (MSPSS), Chronic Pain Acceptance Questionnaire (CPAQ-8), Oswestry Disability Index (ODI), Numeric Rating Scales for back and leg pain (NRS-B/L), SF-12’s Mental Component Summary (MCS), narcotic use and demographic variables. The post-operative measure of interest is narcotic use at 2-year follow-up. Narcotic use is collapsed into binary categories of use and no use. Descriptive statistics are run. Chi Square analysis is used for categorical variables and an ANOVA for continuous variables. Significant variables are built into a hierarchical logistic regression to determine predictors of post-operative narcotic use. Significance is set at α < 0.05. Results: A total of 27.23% of the sample were using narcotics two years after surgery. The regression model included ODI, NRS-Leg, time with condition, chief complaint, pre-operative drug use, gender, MCS, PCS subscale helplessness, and CPAQ subscale pain willingness and was significant χ² (13, N=191)= 54.99; p = .000. The model accounted for 39.6% of the variance in narcotic use and correctly predicted in 79.7% of cases. Psychological variables accounted for 9.6% of the variance over and above the other predictors. Conclusions: Managing chronic narcotic usage is central to the patient’s overall health and quality of life. Psychological factors in the preoperative period are significant predictors of narcotic use 2 years post-operatively. The psychological variables are malleable, potentially allowing surgeons to direct their patients to preventative resources prior to surgery.

Keywords: narcotics, psychological factors, quality of life, spine surgery

Procedia PDF Downloads 144

Authors: Tausif A. Ishtiaque, Zarrin T. Tasin, Kazi S. Akter

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Current trend of urban expansion, especially in the developing countries has caused significant changes in land cover, which is generating great concern due to its widespread environmental degradation. Energy consumption of the cities is also increasing with the aggravated heat island effect. Distribution of land surface temperature (LST) is one of the most significant climatic parameters affected by urban land cover change. Recent increasing trend of LST is causing elevated temperature profile of the built up area with less vegetative cover. Gradual change in land cover, especially decrease in vegetative cover is enhancing the Urban Heat Island (UHI) effect in the developing cities around the world. Increase in the amount of urban vegetation cover can be a useful solution for the reduction of UHI intensity. LST and Normalized Difference Vegetation Index (NDVI) have widely been accepted as reliable indicators of UHI and vegetation abundance respectively. Chittagong, the second largest city of Bangladesh, has been a growth center due to rapid urbanization over the last several decades. This study assesses the intensity of UHI in Chittagong city by analyzing the relationship between LST and NDVI based on the type of land use/land cover (LULC) in the study area applying an integrated approach of Geographic Information System (GIS), remote sensing (RS), and regression analysis. Land cover map is prepared through an interactive supervised classification using remotely sensed data from Landsat ETM+ image along with NDVI differencing using ArcGIS. LST and NDVI values are extracted from the same image. The regression analysis between LST and NDVI indicates that within the study area, UHI is directly correlated with LST while negatively correlated with NDVI. It interprets that surface temperature reduces with increase in vegetation cover along with reduction in UHI intensity. Moreover, there are noticeable differences in the relationship between LST and NDVI based on the type of LULC. In other words, depending on the type of land usage, increase in vegetation cover has a varying impact on the UHI intensity. This analysis will contribute to the formulation of sustainable urban land use planning decisions as well as suggesting suitable actions for mitigation of UHI intensity within the study area.

Keywords: land cover change, land surface temperature, normalized difference vegetation index, urban heat island

Procedia PDF Downloads 272