Search results for: forest inventory
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1623

Search results for: forest inventory

123 Advancing the Analysis of Physical Activity Behaviour in Diverse, Rapidly Evolving Populations: Using Unsupervised Machine Learning to Segment and Cluster Accelerometer Data

Authors: Christopher Thornton, Niina Kolehmainen, Kianoush Nazarpour

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Background: Accelerometers are widely used to measure physical activity behavior, including in children. The traditional method for processing acceleration data uses cut points, relying on calibration studies that relate the quantity of acceleration to energy expenditure. As these relationships do not generalise across diverse populations, they must be parametrised for each subpopulation, including different age groups, which is costly and makes studies across diverse populations difficult. A data-driven approach that allows physical activity intensity states to emerge from the data under study without relying on parameters derived from external populations offers a new perspective on this problem and potentially improved results. We evaluated the data-driven approach in a diverse population with a range of rapidly evolving physical and mental capabilities, namely very young children (9-38 months old), where this new approach may be particularly appropriate. Methods: We applied an unsupervised machine learning approach (a hidden semi-Markov model - HSMM) to segment and cluster the accelerometer data recorded from 275 children with a diverse range of physical and cognitive abilities. The HSMM was configured to identify a maximum of six physical activity intensity states and the output of the model was the time spent by each child in each of the states. For comparison, we also processed the accelerometer data using published cut points with available thresholds for the population. This provided us with time estimates for each child’s sedentary (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA). Data on the children’s physical and cognitive abilities were collected using the Paediatric Evaluation of Disability Inventory (PEDI-CAT). Results: The HSMM identified two inactive states (INS, comparable to SED), two lightly active long duration states (LAS, comparable to LPA), and two short-duration high-intensity states (HIS, comparable to MVPA). Overall, the children spent on average 237/392 minutes per day in INS/SED, 211/129 minutes per day in LAS/LPA, and 178/168 minutes in HIS/MVPA. We found that INS overlapped with 53% of SED, LAS overlapped with 37% of LPA and HIS overlapped with 60% of MVPA. We also looked at the correlation between the time spent by a child in either HIS or MVPA and their physical and cognitive abilities. We found that HIS was more strongly correlated with physical mobility (R²HIS =0.5, R²MVPA= 0.28), cognitive ability (R²HIS =0.31, R²MVPA= 0.15), and age (R²HIS =0.15, R²MVPA= 0.09), indicating increased sensitivity to key attributes associated with a child’s mobility. Conclusion: An unsupervised machine learning technique can segment and cluster accelerometer data according to the intensity of movement at a given time. It provides a potentially more sensitive, appropriate, and cost-effective approach to analysing physical activity behavior in diverse populations, compared to the current cut points approach. This, in turn, supports research that is more inclusive across diverse populations.

Keywords: physical activity, machine learning, under 5s, disability, accelerometer

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122 Pandemic-Related Disruption to the Home Environment and Early Vocabulary Acquisition

Authors: Matthew McArthur, Margaret Friend

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The COVID-19 pandemic disrupted the stability of the home environment for families across the world. Potential disruptions include parent work modality (in-person vs. remote), levels of health anxiety, family routines, and caregiving. These disruptions may have interfered with the processes of early vocabulary acquisition, carrying lasting effects over the life course. Our justification for this research is as follows: First, early, stable, caregiver-child reciprocal interactions, which may have been disrupted during the pandemic, contribute to the development of the brain architecture that supports language, cognitive, and social-emotional development. Second, early vocabulary predicts several cognitive outcomes, such as numeracy, literacy, and executive function. Further, disruption in the home is associated with adverse cognitive, academic, socio-emotional, behavioral, and communication outcomes in young children. We are interested in how disruptions related to the COVID-19 pandemic are associated with vocabulary acquisition in children born during the first two waves of the pandemic. We are conducting a moderated online experiment to assess this question. Participants are 16 children (10F) ranging in age from 19 to 39 months (M=25.27) and their caregivers. All child participants were screened for language background, health history, and history of language disorders, and were typically developing. Parents completed a modified version of the COVID-19 Family Stressor Scale (CoFaSS), a published measure of COVID-19-related family stressors. Thirteen items from the original scale were replaced to better capture change in family organization and stability specifically related to disruptions in income, anxiety, family relations, and childcare. Following completion of the modified CoFaSS, children completed a Web-Based version of the Computerized Comprehension Task and the Receptive One Word Picture Vocabulary if 24 months or older or the MacArthur-Bates Communicative Development Inventory if younger than 24 months. We report our preliminary data as a partial correlation analysis controlling for age. Raw vocabulary scores on the CCT, ROWPVT-4, and MCDI were all negatively associated with pandemic-related disruptions related to anxiety (r12=-.321; r1=-.332; r9=-.509), family relations (r12=-.590*; r1=-.155; r9=-.468), and childcare (r12=-.294; r1=-.468; r9=-.177). Although the small sample size for these preliminary data limits our power to detect significance, this trend is in the predicted direction, suggesting that increased pandemic-related disruption across multiple domains is associated with lower vocabulary scores. We anticipate presenting data on a full sample of 50 monolingual English participants. A sample of 50 participants would provide sufficient statistical power to detect a moderate effect size, adhering to a nominal alpha of 0.05 and ensuring a power level of 0.80.

Keywords: COVID-19, early vocabulary, home environment, language acquisition, multiple measures

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121 Predicting the Impact of Scope Changes on Project Cost and Schedule Using Machine Learning Techniques

Authors: Soheila Sadeghi

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In the dynamic landscape of project management, scope changes are an inevitable reality that can significantly impact project performance. These changes, whether initiated by stakeholders, external factors, or internal project dynamics, can lead to cost overruns and schedule delays. Accurately predicting the consequences of these changes is crucial for effective project control and informed decision-making. This study aims to develop predictive models to estimate the impact of scope changes on project cost and schedule using machine learning techniques. The research utilizes a comprehensive dataset containing detailed information on project tasks, including the Work Breakdown Structure (WBS), task type, productivity rate, estimated cost, actual cost, duration, task dependencies, scope change magnitude, and scope change timing. Multiple machine learning models are developed and evaluated to predict the impact of scope changes on project cost and schedule. These models include Linear Regression, Decision Tree, Ridge Regression, Random Forest, Gradient Boosting, and XGBoost. The dataset is split into training and testing sets, and the models are trained using the preprocessed data. Cross-validation techniques are employed to assess the robustness and generalization ability of the models. The performance of the models is evaluated using metrics such as Mean Squared Error (MSE) and R-squared. Residual plots are generated to assess the goodness of fit and identify any patterns or outliers. Hyperparameter tuning is performed to optimize the XGBoost model and improve its predictive accuracy. The feature importance analysis reveals the relative significance of different project attributes in predicting the impact on cost and schedule. Key factors such as productivity rate, scope change magnitude, task dependencies, estimated cost, actual cost, duration, and specific WBS elements are identified as influential predictors. The study highlights the importance of considering both cost and schedule implications when managing scope changes. The developed predictive models provide project managers with a data-driven tool to proactively assess the potential impact of scope changes on project cost and schedule. By leveraging these insights, project managers can make informed decisions, optimize resource allocation, and develop effective mitigation strategies. The findings of this research contribute to improved project planning, risk management, and overall project success.

Keywords: cost impact, machine learning, predictive modeling, schedule impact, scope changes

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120 Effect of Pollutions on Mangrove Forests of Nayband National Marine Park

Authors: Esmaeil Kouhgardi, Elaheh Shakerdargah

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The mangrove ecosystem is a complex of various inter-related elements in the land-sea interface zone which is linked with other natural systems of the coastal region such as corals, sea-grass, coastal fisheries and beach vegetation. The mangrove ecosystem consists of water, muddy soil, trees, shrubs, and their associated flora, fauna and microbes. It is a very productive ecosystem sustaining various forms of life. Its waters are nursery grounds for fish, crustacean, and mollusk and also provide habitat for a wide range of aquatic life, while the land supports a rich and diverse flora and fauna, but pollutions may affect these characteristics. Iran has the lowest share of Persian Gulf pollution among the eight littoral states; environmental experts are still deeply concerned about the serious consequences of the pollution in the oil-rich gulf. Prolongation of critical conditions in the Persian Gulf has endangered its aquatic ecosystem. Water purification equipment, refineries, wastewater emitted by onshore installations, especially petrochemical plans, urban sewage, population density and extensive oil operations of Arab states are factors contaminating the Persian Gulf waters. Population density has been the major cause of pollution and environmental degradation in the Persian Gulf. Persian Gulf is a closed marine environment which is connected to open waterways only from one way. It usually takes between three and four years for the gulf's water to be completely replaced. Therefore, any pollution entering the water will remain there for a relatively long time. Presently, the high temperature and excessive salt level in the water have exposed the marine creatures to extra threats, which mean they have to survive very tough conditions. The natural environment of the Persian Gulf is very rich with good fish grounds, extensive coral reefs and pearl oysters in abundance, but has become increasingly under pressure due to the heavy industrialization and in particular the repeated major oil spillages associated with the various recent wars fought in the region. Pollution may cause the mortality of mangrove forests by effect on root, leaf and soil of the area. Study was showed the high correlation between industrial pollution and mangrove forests health in south of Iran and increase of population, coupled with economic growth, inevitably caused the use of mangrove lands for various purposes such as construction of roads, ports and harbors, industries and urbanization.

Keywords: Mangrove forest, pollution, Persian Gulf, population, environment

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119 Investigating the Aerosol Load of Eastern Mediterranean Basin with Sentinel-5p Satellite

Authors: Deniz Yurtoğlu

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Aerosols directly affect the radiative balance of the earth by absorbing and/or scattering the sun rays reaching the atmosphere and indirectly affect the balance by acting as a nucleus in cloud formation. The composition, physical, and chemical properties of aerosols vary depending on their sources and the time spent in the atmosphere. The Eastern Mediterranean Basin has a high aerosol load that is formed from different sources; such as anthropogenic activities, desert dust outbreaks, and the spray of sea salt; and the area is subjected to atmospheric transport from other locations on the earth. This region, which includes the deserts of Africa, the Middle East, and the Mediterranean sea, is one of the most affected areas by climate change due to its location and the chemistry of the atmosphere. This study aims to investigate the spatiotemporal deviation of aerosol load in the Eastern Mediterranean Basin between the years 2018-2022 with the help of a new pioneer satellite of ESA (European Space Agency), Sentinel-5P. The TROPOMI (The TROPOspheric Monitoring Instrument) traveling on this low-Earth orbiting satellite is a UV (Ultraviolet)-sensing spectrometer with a resolution of 5.5 km x 3.5 km, which can make measurements even in a cloud-covered atmosphere. By using Absorbing Aerosol Index data produced by this spectrometer and special scripts written in Python language that transforms this data into images, it was seen that the majority of the aerosol load in the Eastern Mediterranean Basin is sourced from desert dust and anthropogenic activities. After retrieving the daily data, which was separated from the NaN values, seasonal analyses match with the normal aerosol variations expected, which are high in warm seasons and lower in cold seasons. Monthly analyses showed that in four years, there was an increase in the amount of Absorbing Aerosol Index in spring and winter by 92.27% (2019-2021) and 39.81% (2019-2022), respectively. On the other hand, in the summer and autumn seasons, a decrease has been observed by 20.99% (2018-2021) and 0.94% (2018-2021), respectively. The overall variation of the mean absorbing aerosol index from TROPOMI between April 2018 to April 2022 reflects a decrease of 115.87% by annual mean from 0.228 to -0.036. However, when the data is analyzed by the annual mean values of the years which have the data from January to December, meaning from 2019 to 2021, there was an increase of 57.82% increase (0.108-0.171). This result can be interpreted as the effect of climate change on the aerosol load and also, more specifically, the effect of forest fires that happened in the summer months of 2021.

Keywords: aerosols, eastern mediterranean basin, sentinel-5p, tropomi, aerosol index, remote sensing

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118 A Generation Outside: Afghan Refugees in Greece 2003-2016

Authors: Kristina Colovic, Mari Janikian, Nikolaos Takis, Fotini-Sonia Apergi

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A considerable number of Afghan asylum seekers in Greece are still waiting for answers about their future and status for personal, social and societal advancement. Most have been trapped in a stalemate of continuously postponed or temporarily progressed levels of integration into the EU/Greek process of asylum. Limited quantitative research exists investigating the psychological effects of long-term displacement among Afghans refugees in Greece. The purpose of this study is to investigate factors that are associated with and predict psychological distress symptoms among this population. Data from a sample of native Afghan nationals (N > 70) living in Greece for approximately the last ten years will be collected from May to July 2016. Criteria for participation include the following: being 18 years of age or older, and emigration from Afghanistan to Greece from 2003 onwards (i.e., long-term refugees or part of the 'old system of asylum'). Snowball sampling will be used to recruit participants, as this is considered the most effective option when attempting to study refugee populations. Participants will complete self-report questionnaires, consisting of the Afghan Symptom Checklist (ASCL), a culturally validated measure of psychological distress, the World Health Organization Quality of Life scale (WHOQOL-BREF), an adapted version of the Comprehensive Trauma Inventory-104 (CTI-104), and a modified Psychological Acculturation Scale. All instruments will be translated in Greek, through the use of forward- and back-translations by bilingual speakers of English and Greek, following WHO guidelines. A pilot study with 5 Afghan participants will take place to check for discrepancies in understanding and for further adapting the instruments as needed. Demographic data, including age, gender, year of arrival to Greece and current asylum status will be explored. Three different types of analyses (descriptive statistics, bivariate correlations, and multivariate linear regression) will be used in this study. Descriptive findings for respondent demographics, psychological distress symptoms, traumatic life events and quality of life will be reported. Zero-order correlations will assess the interrelationships among demographic, traumatic life events, psychological distress, and quality of life variables. Lastly, a multivariate linear regression model will be estimated. The findings from the study will contribute to understanding the determinants of acculturation, distress and trauma on daily functioning for Afghans in Greece. The main implications of the current study will be to advocate for capacity building and empower communities through effective program evaluation and design for mental health services for all refugee populations in Greece.

Keywords: Afghan refugees, evaluation, Greece, mental health, quality of life

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117 Comparing Deep Architectures for Selecting Optimal Machine Translation

Authors: Despoina Mouratidis, Katia Lida Kermanidis

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Machine translation (MT) is a very important task in Natural Language Processing (NLP). MT evaluation is crucial in MT development, as it constitutes the means to assess the success of an MT system, and also helps improve its performance. Several methods have been proposed for the evaluation of (MT) systems. Some of the most popular ones in automatic MT evaluation are score-based, such as the BLEU score, and others are based on lexical similarity or syntactic similarity between the MT outputs and the reference involving higher-level information like part of speech tagging (POS). This paper presents a language-independent machine learning framework for classifying pairwise translations. This framework uses vector representations of two machine-produced translations, one from a statistical machine translation model (SMT) and one from a neural machine translation model (NMT). The vector representations consist of automatically extracted word embeddings and string-like language-independent features. These vector representations used as an input to a multi-layer neural network (NN) that models the similarity between each MT output and the reference, as well as between the two MT outputs. To evaluate the proposed approach, a professional translation and a "ground-truth" annotation are used. The parallel corpora used are English-Greek (EN-GR) and English-Italian (EN-IT), in the educational domain and of informal genres (video lecture subtitles, course forum text, etc.) that are difficult to be reliably translated. They have tested three basic deep learning (DL) architectures to this schema: (i) fully-connected dense, (ii) Convolutional Neural Network (CNN), and (iii) Long Short-Term Memory (LSTM). Experiments show that all tested architectures achieved better results when compared against those of some of the well-known basic approaches, such as Random Forest (RF) and Support Vector Machine (SVM). Better accuracy results are obtained when LSTM layers are used in our schema. In terms of a balance between the results, better accuracy results are obtained when dense layers are used. The reason for this is that the model correctly classifies more sentences of the minority class (SMT). For a more integrated analysis of the accuracy results, a qualitative linguistic analysis is carried out. In this context, problems have been identified about some figures of speech, as the metaphors, or about certain linguistic phenomena, such as per etymology: paronyms. It is quite interesting to find out why all the classifiers led to worse accuracy results in Italian as compared to Greek, taking into account that the linguistic features employed are language independent.

Keywords: machine learning, machine translation evaluation, neural network architecture, pairwise classification

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116 Safety and Maternal Anxiety in Mother's and Baby's Sleep: Cross-sectional Study

Authors: Rayanne Branco Dos Santos Lima, Lorena Pinheiro Barbosa, Kamila Ferreira Lima, Victor Manuel Tegoma Ruiz, Monyka Brito Lima Dos Santos, Maria Wendiane Gueiros Gaspar, Luzia Camila Coelho Ferreira, Leandro Cardozo Dos Santos Brito, Deyse Maria Alves Rocha

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Introduction: The lack of regulation of the baby's sleep-wake pattern in the first years of life affects the health of thousands of women. Maternal sleep deprivation can trigger or aggravate psychosomatic problems such as depression, anxiety and stress that can directly influence maternal safety, with consequences for the baby's and mother's sleep. Such conditions can affect the family's quality of life and child development. Objective: To correlate maternal security with maternal state anxiety scores and the mother's and baby's total sleep time. Method: Cross-sectional study carried out with 96 mothers of babies aged 10 to 24 months, accompanied by nursing professionals linked to a Federal University in Northeast Brazil. Study variables were maternal security, maternal state anxiety scores, infant latency and sleep time, and total nocturnal sleep time of mother and infant. Maternal safety was calculated using a four-point Likert scale (1=not at all safe, 2=somewhat safe, 3=very safe, 4=completely safe). Maternal anxiety was measured by State-Trait Anxiety Inventory, state-anxiety subscale whose scores vary from 20 to 80 points, and the higher the score, the higher the anxiety levels. Scores below 33 are considered mild; from 33 to 49, moderate and above 49, high. As for the total nocturnal sleep time, values between 7-9 hours of sleep were considered adequate for mothers, and values between 9-12 hours for the baby, according to the guidelines of the National Sleep Foundation. For the sleep latency time, a time equal to or less than 20 min was considered adequate. It is noteworthy that the latency time and the time of night sleep of the mother and the baby were obtained by the mother's subjective report. To correlate the data, Spearman's correlation was used in the statistical package R version 3.6.3. Results: 96 women and babies participated, aged 22 to 38 years (mean 30.8) and 10 to 24 months (mean 14.7), respectively. The average of maternal security was 2.89 (unsafe); Mean maternal state anxiety scores were 43.75 (moderate anxiety). The babies' average sleep latency time was 39.6 min (>20 min). The mean sleep times of the mother and baby were, respectively, 6h and 42min and 8h and 19min, both less than the recommended nocturnal sleep time. Maternal security was positively correlated with maternal state anxiety scores (rh=266, p=0.009) and negatively correlated with infant sleep latency (rh= -0.30. P=0.003). Baby sleep time was positively correlated with maternal sleep time. (rh 0.46, p<0.001). Conclusion: The more secure the mothers considered themselves, the higher the anxiety scores and the shorter the baby's sleep latency. Also, the longer the baby sleeps, the longer the mother sleeps. Thus, interventions are needed to promote the quality and efficiency of sleep for both mother and baby.

Keywords: sleep, anxiety, infant, mother-child relations

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115 Biofiltration Odour Removal at Wastewater Treatment Plant Using Natural Materials: Pilot Scale Studies

Authors: D. Lopes, I. I. R. Baptista, R. F. Vieira, J. Vaz, H. Varela, O. M. Freitas, V. F. Domingues, R. Jorge, C. Delerue-Matos, S. A. Figueiredo

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Deodorization is nowadays a need in wastewater treatment plants. Nitrogen and sulphur compounds, volatile fatty acids, aldehydes and ketones are responsible for the unpleasant odours, being ammonia, hydrogen sulphide and mercaptans the most common pollutants. Although chemical treatments of the air extracted are efficient, these are more expensive than biological treatments, namely due the use of chemical reagents (commonly sulphuric acid, sodium hypochlorite and sodium hydroxide). Biofiltration offers the advantage of avoiding the use of reagents (only in some cases, nutrients are added in order to increase the treatment efficiency) and can be considered a sustainable process when the packing medium used is of natural origin. In this work the application of some natural materials locally available was studied both at laboratory and pilot scale, in a real wastewater treatment plant. The materials selected for this study were indigenous Portuguese forest materials derived from eucalyptus and pinewood, such as woodchips and bark, and coconut fiber was also used for comparison purposes. Their physico-chemical characterization was performed: density, moisture, pH, buffer and water retention capacity. Laboratory studies involved batch adsorption studies for ammonia and hydrogen sulphide removal and evaluation of microbiological activity. Four pilot-scale biofilters (1 cubic meter volume) were installed at a local wastewater treatment plant treating odours from the effluent receiving chamber. Each biofilter contained a different packing material consisting of mixtures of eucalyptus bark, pine woodchips and coconut fiber, with added buffering agents and nutrients. The odour treatment efficiency was monitored over time, as well as other operating parameters. The operation at pilot scale suggested that between the processes involved in biofiltration - adsorption, absorption and biodegradation - the first dominates at the beginning, while the biofilm is developing. When the biofilm is completely established, and the adsorption capacity of the material is reached, biodegradation becomes the most relevant odour removal mechanism. High odour and hydrogen sulphide removal efficiencies were achieved throughout the testing period (over 6 months), confirming the suitability of the materials selected, and mixtures thereof prepared, for biofiltration applications.

Keywords: ammonia hydrogen sulphide and removal, biofiltration, natural materials, odour control in wastewater treatment plants

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114 Urban Seismic Risk Reduction in Algeria: Adaptation and Application of the RADIUS Methodology

Authors: Mehdi Boukri, Mohammed Naboussi Farsi, Mounir Naili, Omar Amellal, Mohamed Belazougui, Ahmed Mebarki, Nabila Guessoum, Brahim Mezazigh, Mounir Ait-Belkacem, Nacim Yousfi, Mohamed Bouaoud, Ikram Boukal, Aboubakr Fettar, Asma Souki

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The seismic risk to which the urban centres are more and more exposed became a world concern. A co-operation on an international scale is necessary for an exchange of information and experiments for the prevention and the installation of action plans in the countries prone to this phenomenon. For that, the 1990s was designated as 'International Decade for Natural Disaster Reduction (IDNDR)' by the United Nations, whose interest was to promote the capacity to resist the various natural, industrial and environmental disasters. Within this framework, it was launched in 1996, the RADIUS project (Risk Assessment Tools for Diagnosis of Urban Areas Against Seismic Disaster), whose the main objective is to mitigate seismic risk in developing countries, through the development of a simple and fast methodological and operational approach, allowing to evaluate the vulnerability as well as the socio-economic losses, by probable earthquake scenarios in the exposed urban areas. In this paper, we will present the adaptation and application of this methodology to the Algerian context for the seismic risk evaluation in urban areas potentially exposed to earthquakes. This application consists to perform an earthquake scenario in the urban centre of Constantine city, located at the North-East of Algeria, which will allow the building seismic damage estimation of this city. For that, an inventory of 30706 building units was carried out by the National Earthquake Engineering Research Centre (CGS). These buildings were digitized in a data base which comprises their technical information by using a Geographical Information system (GIS), and then they were classified according to the RADIUS methodology. The study area was subdivided into 228 meshes of 500m on side and Ten (10) sectors of which each one contains a group of meshes. The results of this earthquake scenario highlights that the ratio of likely damage is about 23%. This severe damage results from the high concentration of old buildings and unfavourable soil conditions. This simulation of the probable seismic damage of the building and the GIS damage maps generated provide a predictive evaluation of the damage which can occur by a potential earthquake near to Constantine city. These theoretical forecasts are important for decision makers in order to take the adequate preventive measures and to develop suitable strategies, prevention and emergency management plans to reduce these losses. They can also help to take the adequate emergency measures in the most impacted areas in the early hours and days after an earthquake occurrence.

Keywords: seismic risk, mitigation, RADIUS, urban areas, Algeria, earthquake scenario, Constantine

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113 Carbon Sequestration in Spatio-Temporal Vegetation Dynamics

Authors: Nothando Gwazani, K. R. Marembo

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An increase in the atmospheric concentration of carbon dioxide (CO₂) from fossil fuel and land use change necessitates identification of strategies for mitigating threats associated with global warming. Oceans are insufficient to offset the accelerating rate of carbon emission. However, the challenges of oceans as a source of reducing carbon footprint can be effectively overcome by the storage of carbon in terrestrial carbon sinks. The gases with special optical properties that are responsible for climate warming include carbon dioxide (CO₂), water vapors, methane (CH₄), nitrous oxide (N₂O), nitrogen oxides (NOₓ), stratospheric ozone (O₃), carbon monoxide (CO) and chlorofluorocarbons (CFC’s). Amongst these, CO₂ plays a crucial role as it contributes to 50% of the total greenhouse effect and has been linked to climate change. Because plants act as carbon sinks, interest in terrestrial carbon sequestration has increased in an effort to explore opportunities for climate change mitigation. Removal of carbon from the atmosphere is a topical issue that addresses one important aspect of an overall strategy for carbon management namely to help mitigate the increasing emissions of CO₂. Thus, terrestrial ecosystems have gained importance for their potential to sequester carbon and reduce carbon sink in oceans, which have a substantial impact on the ocean species. Field data and electromagnetic spectrum bands were analyzed using ArcGIS 10.2, QGIS 2.8 and ERDAS IMAGINE 2015 to examine the vegetation distribution. Satellite remote sensing data coupled with Normalized Difference Vegetation Index (NDVI) was employed to assess future potential changes in vegetation distributions in Eastern Cape Province of South Africa. The observed 5-year interval analysis examines the amount of carbon absorbed using vegetation distribution. In 2015, the numerical results showed low vegetation distribution, therefore increased the acidity of the oceans and gravely affected fish species and corals. The outcomes suggest that the study area could be effectively utilized for carbon sequestration so as to mitigate ocean acidification. The vegetation changes measured through this investigation suggest an environmental shift and reduced vegetation carbon sink, and that threatens biodiversity and ecosystem. In order to sustain the amount of carbon in the terrestrial ecosystems, the identified ecological factors should be enhanced through the application of good land and forest management practices. This will increase the carbon stock of terrestrial ecosystems thereby reducing direct loss to the atmosphere.

Keywords: remote sensing, vegetation dynamics, carbon sequestration, terrestrial carbon sink

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112 Understanding the Dynamics of Human-Snake Negative Interactions: A Study of Indigenous Perceptions in Tamil Nadu, Southern India

Authors: Ramesh Chinnasamy, Srishti Semalty, Vishnu S. Nair, Thirumurugan Vedagiri, Mahesh Ganeshan, Gautam Talukdar, Karthy Sivapushanam, Abhijit Das

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Snakes form an integral component of ecological systems. Human population explosion and associated acceleration of habitat destruction and degradation, has led to a rapid increase in human-snake encounters. The study aims at understanding the level of awareness, knowledge, and attitude of the people towards human-snake negative interaction and role of awareness programmes in the Moyar river valley, Tamil Nadu. The study area is part of the Mudumalai and the Sathyamangalam Tiger Reserves, which are significant wildlife corridors between the Western Ghats and the Eastern Ghats in the Nilgiri Biosphere Reserve. The data was collected using questionnaire covering 644 respondents spread across 18 villages between 2018 and 2019. The study revealed that 86.5% of respondents had strong negative perceptions towards snakes which were propelled by fear, superstitions, and threat of snakebite which was common and did not vary among different villages (F=4.48; p = <0.05) and age groups (X2 = 1.946; p = 0.962). Cobra 27.8% (n = 294) and rat snake 21.3% (n = 225) were the most sighted species and most snake encounter occurred during the monsoon season i.e., July 35.6 (n = 218), June 19.1% (n = 117) and August 18.4% (n = 113). At least 1 out of 5 respondents was reportedly bitten by snakes during their lifetime. The most common species of snakes that were the cause of snakebite were Saw scaled viper (32.6%, n = 42) followed by Cobra 17.1% (n = 22). About 21.3% (n = 137) people reported livestock loss due to pythons and other snakes 21.3% (n = 137). Most people, preferred medical treatment for snakebite (87.3%), whereas 12.7%, still believed in traditional methods. The majority (82.3%) used precautionary measure by keeping traditional items such as garlic, kerosene, and snake plant to avoid snakes. About 30% of the respondents expressed need for technical and monetary support from the forest department that could aid in reducing the human-snake conflict. It is concluded that the general perception in the study area is driven by fear and negative attitude towards snakes. Though snakes such as Cobra were widely worshiped in the region, there are still widespread myths and misconceptions that have led to the irrational killing of snakes. Awareness and innovative education programs rooted in the local context and language should be integrated at the village level, to minimize risk and the associated threat of snakebite among the people. Results from this study shall help policy makers to devise appropriate conservation measures to reduce human-snake conflicts in India.

Keywords: Envenomation, Health-Education, Human-Wildlife Conflict, Neglected Tropical Disease, Snakebite Mitigation, Traditional Practitioners

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111 Grassland Development on Evacuated Sites for Wildlife Conservation in Satpura Tiger Reserve, India

Authors: Anjana Rajput, Sandeep Chouksey, Bhaskar Bhandari, Shimpi Chourasia

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Ecologically, grassland is any plant community dominated by grasses, whether they exist naturally or because of management practices. Most forest grasslands are anthropogenic and established plant communities planted for forage production, though some are established for soil and water conservation and wildlife habitat. In Satpura Tiger Reserve, Madhya Pradesh, India, most of the grasslands have been established on evacuated village sites. Total of 42 villages evacuated, and study was carried out in 23 sites to evaluate habitat improvement. Grasslands were classified into three categories, i.e., evacuated sites, established sites, and controlled sites. During the present study impact of various management interventions on grassland health was assessed. Grasslands assessment was done for its composition, status of palatable and non-palatable grasses, the status of herbs and legumes, status of weeds species, and carrying capacity of particular grassland. Presence of wild herbivore species in the grasslands with their abundance, availability of water resources was also assessed. Grassland productivity is dependent mainly on the biotic and abiotic components of the area, but management interventions may also play an important role in grassland composition and productivity. Variation in the status of palatable and non-palatable grasses, legumes, and weeds was recorded and found effected by management intervention practices. Overall in all the studied grasslands, the most dominant grasses recorded are Themeda quadrivalvis, Dichanthium annulatum, Ischaemum indicum, Oplismenus burmanii, Setaria pumilla, Cynodon dactylon, Heteropogon contortus, and Eragrostis tenella. Presence of wild herbivores, i.e., Chital, Sambar, Bison, Bluebull, Chinkara, Barking deer in the grassland area has been recorded through the installation of camera traps and estimated their abundance. Assessment of developed grasslands was done in terms of habitat suitability for Chital (Axis axis) and Sambar (Rusa unicolor). The parameters considered for suitability modeling are biotic and abiotic life requisite components existing in the area, i.e., density of grasses, density of legumes, availability of water, site elevation, site distance from human habitation. Findings of the present study would be useful for further grassland management and animal translocation programmes.

Keywords: carrying capacity, dominant grasses, grassland, habitat suitability, management intervention, wild herbivore

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110 The Evolution of Man through Cranial and Dental Remains: A Literature Review

Authors: Rishana Bilimoria

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Darwin’s insightful anthropological theory on the evolution drove mankind’s understanding of our existence in the natural world. Scientists consider analysis of dental and craniofacial remains to be pivotal in uncovering facts about our evolutionary journey. The resilient mineral content of enamel and dentine allow cranial and dental remains to be preserved for millions of years, making it an excellent resource not only in anthropology but other fields of research including forensic dentistry. This literature review aims to chronologically approach each ancestral species, reviewing Australopithecus, Paranthropus, Homo Habilis, Homo Rudolfensis, Homo Erectus, Homo Neanderthalis, and finally Homo Sapiens. Studies included in the review assess the features of cranio-dental remains that are of evolutionary importance, such as microstructure, microwear, morphology, and jaw biomechanics. The article discusses the plethora of analysis techniques employed to study dental remains including carbon dating, dental topography, confocal imaging, DPI scanning and light microscopy, in addition to microwear study and analysis of features such as coronal and root morphology, mandibular corpus shape, craniofacial anatomy and microstructure. Furthermore, results from these studies provide insight into the diet, lifestyle and consequently, ecological surroundings of each species. We can correlate dental fossil evidence with wider theories on pivotal global events, to help us contextualize each species in space and time. Examples include dietary adaptation during the period of global cooling converting the landscape of Africa from forest to grassland. Global migration ‘out of Africa’ can be demonstrated by enamel thickness variation, cranial vault variation over time demonstrates accommodation to larger brain sizes, and dental wear patterns can place the commencement of lithic technology in history. Conclusions from this literature review show that dental evidence plays a major role in painting a phenotypic and all rounded picture of species of the Homo genus, in particular, analysis of coronal morphology through carbon dating and dental wear analysis. With regards to analysis technique, whilst studies require larger sample sizes, this could be unrealistic since there are limitations in ability to retrieve fossil data. We cannot deny the reliability of carbon dating; however, there is certainly scope for the use of more recent techniques, and further evidence of their success is required.

Keywords: cranio-facial, dental remains, evolution, hominids

Procedia PDF Downloads 145
109 Effect of Climate Changing Pattern on Aquatic Biodiversity of Bhimtal Lake at Kumaun Himalaya (India)

Authors: Davendra S. Malik

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Bhimtal lake is located between 290 21’ N latitude and 790 24’ E longitude, at an elevation of 1332m above mean sea level in the Kumaun region of Uttarakhand of Indian subcontinent. The lake surface area is decreasing in water area, depth level in relation to ecological and biological characteristics due to climatic variations, invasive land use pattern, degraded forest zones and changed agriculture pattern in lake catchment basin. The present study is focused on long and short term effects of climate change on aquatic biodiversity and productivity of Bhimtal lake. The meteorological data of last fifteen years of Bhimtal lake catchment basin revealed that air temperature has been increased 1.5 to 2.1oC in summer, 0.2 to 0.8 C in winter, relative humidity increased 4 to 6% in summer and rainfall pattern changed erratically in rainy seasons. The surface water temperature of Bhimtal lake showed an increasing pattern as 0.8 to 2.6 C, pH value decreased 0.5 to 0.2 in winter and increased 0.4 to 0.6 in summer. Dissolved oxygen level in lake showed a decreasing trend as 0.7 to 0.4mg/l in winter months. The mesotrophic nature of Bhimtal lake is changing towards eutrophic conditions and contributed for decreasing biodiversity. The aquatic biodiversity of Bhimtal lake consisted mainly phytoplankton, zooplankton, benthos and fish species. In the present study, a total of 5 groups of phytoplankton, 3 groups of zooplankton, 11 groups of benthos and 15 fish species were recorded from Bhimtal lake. The comparative data of biodiversity of Bhimtal lake since January, 2000 indicated the changing pattern of phytoplankton biomass were decreasing as 1.99 and 1.08% of Chlorophyceae and Bacilleriophyceae families respectively. The biomass of Cynophyceae was increasing as 0.45% and contributing the algal blooms during summer season in lake. The biomass of zooplankton and benthos were found decreasing in winter season and increasing during summer season. The endemic fish species (18 no.) were found in year 2000-05, as while the fish species (15 no.) were recorded in present study. The relative fecundity of major fish species were observed decreasing trends during their breeding periods in lake. The natural and anthropogenic factors were identified as ecological threats for existing aquatic biodiversity of Bhimtal lake. The present research paper emphasized on the effect of changing pattern of different climatic variables on species composition, biomass of phytoplankton, zooplankton, benthos, and fishes in Bhimtal lake of Kumaun region. The present research data will be contributed significantly to assess the changing pattern of aquatic biodiversity and productivity of Bhimtal lake with different time scale.

Keywords: aquatic biodiversity, Bhimtal lake, climate change, lake ecology

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108 Predicting Growth of Eucalyptus Marginata in a Mediterranean Climate Using an Individual-Based Modelling Approach

Authors: S.K. Bhandari, E. Veneklaas, L. McCaw, R. Mazanec, K. Whitford, M. Renton

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Eucalyptus marginata, E. diversicolor and Corymbia calophylla form widespread forests in south-west Western Australia (SWWA). These forests have economic and ecological importance, and therefore, tree growth and sustainable management are of high priority. This paper aimed to analyse and model the growth of these species at both stand and individual levels, but this presentation will focus on predicting the growth of E. Marginata at the individual tree level. More specifically, the study wanted to investigate how well individual E. marginata tree growth could be predicted by considering the diameter and height of the tree at the start of the growth period, and whether this prediction could be improved by also accounting for the competition from neighbouring trees in different ways. The study also wanted to investigate how many neighbouring trees or what neighbourhood distance needed to be considered when accounting for competition. To achieve this aim, the Pearson correlation coefficient was examined among competition indices (CIs), between CIs and dbh growth, and selected the competition index that can best predict the diameter growth of individual trees of E. marginata forest managed under different thinning regimes at Inglehope in SWWA. Furthermore, individual tree growth models were developed using simple linear regression, multiple linear regression, and linear mixed effect modelling approaches. Individual tree growth models were developed for thinned and unthinned stand separately. The developed models were validated using two approaches. In the first approach, models were validated using a subset of data that was not used in model fitting. In the second approach, the model of the one growth period was validated with the data of another growth period. Tree size (diameter and height) was a significant predictor of growth. This prediction was improved when the competition was included in the model. The fit statistic (coefficient of determination) of the model ranged from 0.31 to 0.68. The model with spatial competition indices validated as being more accurate than with non-spatial indices. The model prediction can be optimized if 10 to 15 competitors (by number) or competitors within ~10 m (by distance) from the base of the subject tree are included in the model, which can reduce the time and cost of collecting the information about the competitors. As competition from neighbours was a significant predictor with a negative effect on growth, it is recommended including neighbourhood competition when predicting growth and considering thinning treatments to minimize the effect of competition on growth. These model approaches are likely to be useful tools for the conservations and sustainable management of forests of E. marginata in SWWA. As a next step in optimizing the number and distance of competitors, further studies in larger size plots and with a larger number of plots than those used in the present study are recommended.

Keywords: competition, growth, model, thinning

Procedia PDF Downloads 107
107 Home Environment and Self-Efficacy Beliefs among Native American, African American and Latino Adolescents

Authors: Robert H. Bradley

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Many minority adolescents in the United States live in adverse circumstances that pose long-term threats to their well-being. A strong sense of personal control and self-efficacy can help youth mitigate some of those risks and may help protect youth from influences connected with deviant peer groups. Accordingly, it is important to identify conditions that help foster feelings of efficacy in areas that seem critical for the accomplishment of developmental tasks during adolescence. The purpose of this study is to examine two aspects of the home environment (modeling and encouragement of maturity, family companionship and investment) and their relation to three components of self efficacy (self efficacy in enlisting social resources, self efficacy for engaging in independent learning, and self-efficacy for self-regulatory behavior) in three groups of minority adolescents (Native American, African American, Latino). The sample for this study included 54 Native American, 131 African American, and 159 Latino families, each with a child between 16 and 20 years old. The families were recruited from four states: Arizona, Arkansas, California, and Oklahoma. Each family was administered the Late Adolescence version of the Home Observation for Measurement of the Environment (HOME) Inventory and each adolescent completed a 30-item measure of perceived self-efficacy. Three areas of self-efficacy beliefs were examined for this study: enlisting social resources, independent learning, and self-regulation. Each of the three areas of self-efficacy was regressed on the two aspects of the home environment plus overall household risk. For Native Americans, modeling and encouragement were significant for self-efficacy pertaining to enlisting social resources and independent learning. For African Americans, companionship and investment was significant in all three models. For Latinos, modeling and encouragement was significant for self-efficacy pertaining to enlisting social resources and companionship and investment were significant for the other two areas of self-efficacy. The findings show that even as minority adolescents are becoming more individuated from their parents, the quality of experiences at home continues to be associated with their feelings of self-efficacy in areas important for adaptive functioning in adult life. Specifically, individuals can develop a sense that they are efficacious in performing key tasks relevant to work, social relationships, and management of their own behavior if they are guided in how to deal with key challenges and they have been exposed and supported by others who are competent in dealing with such challenges. The findings presented in this study would seem useful given that there is so little current research on home environmental factors connected to self-efficacy beliefs among adolescents in the three groups examined. It would seem worthwhile that personnel from health, human service and juvenile justice agencies give attention to supporting parents in communicating with adolescents, offering expectations to adolescents in mutually supportive ways, and in engaging with adolescents in productive activities. In comparison to programs for parents of young children, there are few specifically designed for parents of children in middle childhood and adolescence.

Keywords: family companionship, home environment, household income, modeling, self-efficacy

Procedia PDF Downloads 221
106 Exploring the Impact of Eye Movement Desensitization and Reprocessing (EMDR) And Mindfulness for Processing Trauma and Facilitating Healing During Ayahuasca Ceremonies

Authors: J. Hash, J. Converse, L. Gibson

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Plant medicines are of growing interest for addressing mental health concerns. Ayahuasca, a traditional plant-based medicine, has established itself as a powerful way of processing trauma and precipitating healing and mood stabilization. Eye Movement Desensitization and Reprocessing (EMDR) is another treatment modality that aids in the rapid processing and resolution of trauma. We investigated group EMDR therapy, G-TEP, as a preparatory practice before Ayahuasca ceremonies to determine if the combination of these modalities supports participants in their journeys of letting go of past experiences negatively impacting mental health, thereby accentuating the healing of the plant medicine. We surveyed 96 participants (51 experimental G-TEP, 45 control grounding prior to their ceremony; age M=38.6, SD=9.1; F=57, M=34; white=39, Hispanic/Latinx=23, multiracial=11, Asian/Pacific Islander=10, other=7) in a pre-post, mixed methods design. Participants were surveyed for demographic characteristics, symptoms of PTSD and cPTSD (International Trauma Questionnaire (ITQ), depression (Beck Depression Inventory, BDI), and stress (Perceived Stress Scale, PSS) before the ceremony and at the end of the ceremony weekend. Open-ended questions also inquired about their expectations of the ceremony and results at the end. No baseline differences existed between the control and experimental participants. Overall, participants reported a decrease in meeting the threshold for PTSD symptoms (p<0.01); surprisingly, the control group reported significantly fewer thresholds met for symptoms of affective dysregulation, 2(1)=6.776, p<.01, negative self-concept, 2 (1)=7.122, p<.01, and disturbance in relationships, 2 (1)=9.804, p<.01, on subscales of the ITQ as compared to the experimental group. All participants also experienced a significant decrease in scores on the BDI, t(94)=8.995, p<.001, and PSS, t(91)=6.892, p<.001. Similar to patterns of PTSD symptoms, the control group reported significantly lower scores on the BDI, t(65.115)=-2.587, p<.01, and a trend toward lower PSS, t(90)=-1.775, p=.079 (this was significant with a one-sided test at p<.05), compared to the experimental group following the ceremony. Qualitative interviews among participants revealed a potential explanation for these relatively higher levels of depression and stress in the experimental group following the ceremony. Many participants reported needing more time to process their experience to gain an understanding of the effects of the Ayahuasca medicine. Others reported a sense of hopefulness and understanding of the sources of their trauma and the necessary steps to heal moving forward. This suggests increased introspection and openness to processing trauma, therefore making them more receptive to their emotions. The integration process of an Ayahuasca ceremony is a week- to months-long process that was not accessible in this stage of research, yet it is an integral process to understanding the full effects of the Ayahuasca medicine following the closure of a ceremony. Our future research aims to assess participants weeks into their integration process to determine the effectiveness of EMDR, and if the higher levels of depression and stress indicate the initial reaction to greater awareness of trauma and receptivity to healing.

Keywords: ayahuasca, EMDR, PTSD, mental health

Procedia PDF Downloads 41
105 Gauging Floral Resources for Pollinators Using High Resolution Drone Imagery

Authors: Nicholas Anderson, Steven Petersen, Tom Bates, Val Anderson

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Under the multiple-use management regime established in the United States for federally owned lands, government agencies have come under pressure from commercial apiaries to grant permits for the summer pasturing of honeybees on government lands. Federal agencies have struggled to integrate honeybees into their management plans and have little information to make regulations that resolve how many colonies should be allowed in a single location and at what distance sets of hives should be placed. Many conservation groups have voiced their concerns regarding the introduction of honeybees to these natural lands, as they may outcompete and displace native pollinating species. Assessing the quality of an area in regard to its floral resources, pollen, and nectar can be important when attempting to create regulations for the integration of commercial honeybee operations into a native ecosystem. Areas with greater floral resources may be able to support larger numbers of honeybee colonies, while poorer resource areas may be less resilient to introduced disturbances. Attempts are made in this study to determine flower cover using high resolution drone imagery to help assess the floral resource availability to pollinators in high elevation, tall forb communities. This knowledge will help in determining the potential that different areas may have for honeybee pasturing and honey production. Roughly 700 images were captured at 23m above ground level using a drone equipped with a Sony QX1 RGB 20-megapixel camera. These images were stitched together using Pix4D, resulting in a 60m diameter high-resolution mosaic of a tall forb meadow. Using the program ENVI, a supervised maximum likelihood classification was conducted to calculate the percentage of total flower cover and flower cover by color (blue, white, and yellow). A complete vegetation inventory was taken on site, and the major flowers contributing to each color class were noted. An accuracy assessment was performed on the classification yielding an 89% overall accuracy and a Kappa Statistic of 0.855. With this level of accuracy, drones provide an affordable and time efficient method for the assessment of floral cover in large areas. The proximal step of this project will now be to determine the average pollen and nectar loads carried by each flower species. The addition of this knowledge will result in a quantifiable method of measuring pollen and nectar resources of entire landscapes. This information will not only help land managers determine stocking rates for honeybees on public lands but also has applications in the agricultural setting, aiding producers in the determination of the number of honeybee colonies necessary for proper pollination of fruit and nut crops.

Keywords: honeybee, flower, pollinator, remote sensing

Procedia PDF Downloads 112
104 Severe Infestation of Laspeyresia Koenigana Fab. and Alternaria Leaf Spot on Azadirachta Indica (Neem)

Authors: Shiwani Bhatnagar, K. K. Srivastava, Sangeeta Singh, Ameen Ullah Khan, Bundesh Kumar, Lokendra Singh Rathore

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From the instigation of the world medicinal plants are treated as part and parcel of human society to fight against diseases. Azadirachta indica (Neem) a herbal plant has been used as an Indian traditional medicine since ages and its products are acknowledged to solve agricultural, forestry and public health related problems, owing to its beneficial medicinal properties. Each part of the neem tree is known for its medicinal property. Bark & leaf extracts of neem have been used to control leprosy, respiratory disorders, constipation and also as blood purifier and a general health tonic. Neem is still regarded as ' rural community dispensary' in India or a tree for solving medical problems. Use of Neem as pesticides for the management of insect pest of agriculture crops and forestry has been seen as a shift in the use of synthetic pesticides to ecofriendly botanicals. Neem oil and seed extracts possess germicidal and anti-bacterial properties which when sprayed on the plant helps in protecting them from foliage pests. Azadirachtin, the main active ingredient found in neem tree, acts as an insect repellent and antifeedant. However the young plants are susceptible to many insect pest and foliar diseases. Recently, in the avenue plantation, planted by Arid Forest Research Institute, Jodhpur, around the premises of IIT Jodhpur, two years old neem plants were found to be severely infested with tip borer Laspeyresia koenigana (Family: Eucosmidae). The adult moth of L. koenigana lays eggs on the tender shoots and the young larvae tunnel into the shoot and feed inside. A small pinhole can be seen at the entrance point, from where the larva enters in to the stem. The severely attached apical shoots exhibit profuse gum exudation resulting in development of a callus structure. The internal feeding causes the stem to wilt and the leaves to dry up from the tips resulting in growth retardation. Alternaria Leaf spot and blight symptoms were also recorded on these neem plants. For the management of tip borer and Alternaria Leaf spot, foliar spray of monocrotophos @0.05% and Dithane M-45 @ 0.15% and powermin @ 2ml/lit were found efficient in managing the insect pest and foliar disease problem. No Further incidence of pest/diseases was noticed.

Keywords: azadirachta indica, alternaria leaf spot, laspeyresia koenigana, management

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103 Development of Infertility Prevention Psycho-Education Program for University Students and Evaluation of Its Effectiveness

Authors: Digdem M. Siyez, Bariscan Ozturk, Erol Esen, Ender Siyez, Yelda Kagnici, Bahar Baran

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Infertility is a reproductive disease identified with the absence of pregnancy after regular unprotected sexual intercourse that has been lasting for 12 months or more. Some of the factors that cause infertility, which has been considered as a social and societal issue since the first days of the humankind, are preventable. These are veneral diseases, age, the frequency of the intercourse and its timing, drug use, bodyweight, environmental and professional conditions. Having actual information about the reproductive health is essential to take protective and preventive measures, and it is accepted as the most effective way to reduce the rate of infertility. However, during the literature review, it has been observed that there are so few studies that focus on the prevention of the infertility. The aim of this study is to develop a psycho-education program to reduce infertility among university students and also to evaluate the program’s effectiveness. It is believed that this program will increase the information level about infertility among the university students, help them to adopt healthy attitudes, develop life skills, create awareness about the risk factors and also contribute to the literature. Throughout the study, first, the contents of sexual/reproductive health programs developed for university students were examined by the researches. Besides, “Views about Reproductive Health Psycho-education Program Survey” was developed and applied to 10221 university students from 21 universities. In accordance with the literature and the university students’ views about reproductive health psycho-education program consisting of 9 sessions each of which lasts for 90 minutes was developed. The pilot program was carried out with 16 volunteer undergraduate students attending to a state university. During the evaluation of the pilot study, at the end of each session “Session Evaluation Form” and at the end of the entire program “Program Evaluation Form” were administered to the participants. Besides, one week after the end of the program, a focus group with half of the group, and individual interviews with the rest were conducted. Based on the evaluations, it was determined that the session duration is enough, the teaching methods meet the expectation, the techniques applied are appropriate and clear, and the materials are adequate. Also, an extra session was added to psycho-education program based on the feedbacks of the participants. In order to evaluate program’s effectiveness, Solomon control group design will be used. According to this design, the research has 2 experiment groups and 2 control groups. The participants who voluntarily participated in the research after the announcement of the psycho-education program were divided into experiment and control groups. In the experiment 1 and control 1 groups, “Personal Information Test”, “Infertility Information Test” and “Infertility Attitude Scale”, “Self Identification Inventory” and “Melbourne Decision Scale” were administered as a preliminary test. Currently, at the present stage, psycho-education still continues. After this 10-week program, the same tests will be administered again as the post-tests. The decision upon which statistical method will be applied in the analysis will be made afterwards according to whether the data meets the presuppositions or not.

Keywords: infertility, prevention, psycho-education, reproductive health

Procedia PDF Downloads 204
102 Assessment of Rainfall Erosivity, Comparison among Methods: Case of Kakheti, Georgia

Authors: Mariam Tsitsagi, Ana Berdzenishvili

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Rainfall intensity change is one of the main indicators of climate change. It has a great influence on agriculture as one of the main factors causing soil erosion. Splash and sheet erosion are one of the most prevalence and harmful for agriculture. It is invisible for an eye at first stage, but the process will gradually move to stream cutting erosion. Our study provides the assessment of rainfall erosivity potential with the use of modern research methods in Kakheti region. The region is the major provider of wheat and wine in the country. Kakheti is located in the eastern part of Georgia and characterized quite a variety of natural conditions. The climate is dry subtropical. For assessment of the exact rate of rainfall erosion potential several year data of rainfall with short intervals are needed. Unfortunately, from 250 active metro stations running during the Soviet period only 55 of them are active now and 5 stations in Kakheti region respectively. Since 1936 we had data on rainfall intensity in this region, and rainfall erosive potential is assessed, in some old papers, but since 1990 we have no data about this factor, which in turn is a necessary parameter for determining the rainfall erosivity potential. On the other hand, researchers and local communities suppose that rainfall intensity has been changing and the number of haily days has also been increasing. However, finding a method that will allow us to determine rainfall erosivity potential as accurate as possible in Kakheti region is very important. The study period was divided into three sections: 1936-1963; 1963-1990 and 1990-2015. Rainfall erosivity potential was determined by the scientific literature and old meteorological stations’ data for the first two periods. And it is known that in eastern Georgia, at the boundary between steppe and forest zones, rainfall erosivity in 1963-1990 was 20-75% higher than that in 1936-1963. As for the third period (1990-2015), for which we do not have data of rainfall intensity. There are a variety of studies, where alternative ways of calculating the rainfall erosivity potential based on lack of data are discussed e.g.based on daily rainfall data, average annual rainfall data and the elevation of the area, etc. It should be noted that these methods give us a totally different results in case of different climatic conditions and sometimes huge errors in some cases. Three of the most common methods were selected for our research. Each of them was tested for the first two sections of the study period. According to the outcomes more suitable method for regional climatic conditions was selected, and after that, we determined rainfall erosivity potential for the third section of our study period with use of the most successful method. Outcome data like attribute tables and graphs was specially linked to the database of Kakheti, and appropriate thematic maps were created. The results allowed us to analyze the rainfall erosivity potential changes from 1936 to the present and make the future prospect. We have successfully implemented a method which can also be use for some another region of Georgia.

Keywords: erosivity potential, Georgia, GIS, Kakheti, rainfall

Procedia PDF Downloads 204
101 Influencing Factors and Mechanism of Patient Engagement in Healthcare: A Survey in China

Authors: Qing Wu, Xuchun Ye, Kirsten Corazzini

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Objective: It is increasingly recognized that patients’ rational and meaningful engagement in healthcare could make important contributions to their health care and safety management. However, recent evidence indicated that patients' actual roles in healthcare didn’t match their desired roles, and many patients reported a less active role than desired, which suggested that patient engagement in healthcare may be influenced by various factors. This study aimed to analyze influencing factors on patient engagement and explore the influence mechanism, which will be expected to contribute to the strategy development of patient engagement in healthcare. Methods: On the basis of analyzing the literature and theory study, the research framework was developed. According to the research framework, a cross-sectional survey was employed using the behavior and willingness of patient engagement in healthcare questionnaire, Chinese version All Aspects of Health Literacy Scale, Facilitation of Patient Involvement Scale and Wake Forest Physician Trust Scale, and other influencing factor related scales. A convenience sample of 580 patients was recruited from 8 general hospitals in Shanghai, Jiangsu Province, and Zhejiang Province. Results: The results of the cross-sectional survey indicated that the mean score for the patient engagement behavior was (4.146 ± 0.496), and the mean score for the willingness was (4.387 ± 0.459). The level of patient engagement behavior was inferior to their willingness to be involved in healthcare (t = 14.928, P < 0.01). The influencing mechanism model of patient engagement in healthcare was constructed by the path analysis. The path analysis revealed that patient attitude toward engagement, patients’ perception of facilitation of patient engagement and health literacy played direct prediction on the patients’ willingness of engagement, and standard estimated values of path coefficient were 0.341, 0.199, 0.291, respectively. Patients’ trust in physician and the willingness of engagement played direct prediction on the patient engagement, and standard estimated values of path coefficient were 0.211, 0.641, respectively. Patient attitude toward engagement, patients’ perception of facilitation and health literacy played indirect prediction on patient engagement, and standard estimated values of path coefficient were 0.219, 0.128, 0.187, respectively. Conclusions: Patients engagement behavior did not match their willingness to be involved in healthcare. The influencing mechanism model of patient engagement in healthcare was constructed. Patient attitude toward engagement, patients’ perception of facilitation of engagement and health literacy posed indirect positive influence on patient engagement through the patients’ willingness of engagement. Patients’ trust in physician and the willingness of engagement had direct positive influence on the patient engagement. Patient attitude toward engagement, patients’ perception of physician facilitation of engagement and health literacy were the factors influencing the patients’ willingness of engagement. The results of this study provided valuable evidence on guiding the development of strategies for promoting patient rational and meaningful engagement in healthcare.

Keywords: healthcare, patient engagement, influencing factor, the mechanism

Procedia PDF Downloads 132
100 Comparison of the Effectiveness of Tree Algorithms in Classification of Spongy Tissue Texture

Authors: Roza Dzierzak, Waldemar Wojcik, Piotr Kacejko

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Analysis of the texture of medical images consists of determining the parameters and characteristics of the examined tissue. The main goal is to assign the analyzed area to one of two basic groups: as a healthy tissue or a tissue with pathological changes. The CT images of the thoracic lumbar spine from 15 healthy patients and 15 with confirmed osteoporosis were used for the analysis. As a result, 120 samples with dimensions of 50x50 pixels were obtained. The set of features has been obtained based on the histogram, gradient, run-length matrix, co-occurrence matrix, autoregressive model, and Haar wavelet. As a result of the image analysis, 290 descriptors of textural features were obtained. The dimension of the space of features was reduced by the use of three selection methods: Fisher coefficient (FC), mutual information (MI), minimization of the classification error probability and average correlation coefficients between the chosen features minimization of classification error probability (POE) and average correlation coefficients (ACC). Each of them returned ten features occupying the initial place in the ranking devised according to its own coefficient. As a result of the Fisher coefficient and mutual information selections, the same features arranged in a different order were obtained. In both rankings, the 50% percentile (Perc.50%) was found in the first place. The next selected features come from the co-occurrence matrix. The sets of features selected in the selection process were evaluated using six classification tree methods. These were: decision stump (DS), Hoeffding tree (HT), logistic model trees (LMT), random forest (RF), random tree (RT) and reduced error pruning tree (REPT). In order to assess the accuracy of classifiers, the following parameters were used: overall classification accuracy (ACC), true positive rate (TPR, classification sensitivity), true negative rate (TNR, classification specificity), positive predictive value (PPV) and negative predictive value (NPV). Taking into account the classification results, it should be stated that the best results were obtained for the Hoeffding tree and logistic model trees classifiers, using the set of features selected by the POE + ACC method. In the case of the Hoeffding tree classifier, the highest values of three parameters were obtained: ACC = 90%, TPR = 93.3% and PPV = 93.3%. Additionally, the values of the other two parameters, i.e., TNR = 86.7% and NPV = 86.6% were close to the maximum values obtained for the LMT classifier. In the case of logistic model trees classifier, the same ACC value was obtained ACC=90% and the highest values for TNR=88.3% and NPV= 88.3%. The values of the other two parameters remained at a level close to the highest TPR = 91.7% and PPV = 91.6%. The results obtained in the experiment show that the use of classification trees is an effective method of classification of texture features. This allows identifying the conditions of the spongy tissue for healthy cases and those with the porosis.

Keywords: classification, feature selection, texture analysis, tree algorithms

Procedia PDF Downloads 150
99 Monitoring Soil Moisture Dynamic in Root Zone System of Argania spinosa Using Electrical Resistivity Imaging

Authors: F. Ainlhout, S. Boutaleb, M. C. Diaz-Barradas, M. Zunzunegui

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Argania spinosa is an endemic tree of the southwest of Morocco, occupying 828,000 Ha, distributed mainly between Mediterranean vegetation and the desert. This tree can grow in extremely arid regions in Morocco, where annual rainfall ranges between 100-300 mm where no other tree species can live. It has been designated as a UNESCO Biosphere reserve since 1998. Argania tree is of great importance in human and animal feeding of rural population as well as for oil production, it is considered as a multi-usage tree. Admine forest located in the suburbs of Agadir city, 5 km inland, was selected to conduct this work. The aim of the study was to investigate the temporal variation in root-zone moisture dynamic in response to variation in climatic conditions and vegetation water uptake, using a geophysical technique called Electrical resistivity imaging (ERI). This technique discriminates resistive woody roots, dry and moisture soil. Time-dependent measurements (from April till July) of resistivity sections were performed along the surface transect (94 m Length) at 2 m fixed electrode spacing. Transect included eight Argan trees. The interactions between the tree and soil moisture were estimated by following the tree water status variations accompanying the soil moisture deficit. For that purpose we measured midday leaf water potential and relative water content during each sampling day, and for the eight trees. The first results showed that ERI can be used to accurately quantify the spatiotemporal distribution of root-zone moisture content and woody root. The section obtained shows three different layers: middle conductive one (moistured); a moderately resistive layer corresponding to relatively dry soil (calcareous formation with intercalation of marly strata) on top, this layer is interspersed by very resistant layer corresponding to woody roots. Below the conductive layer, we find the moderately resistive layer. We note that throughout the experiment, there was a continuous decrease in soil moisture at the different layers. With the ERI, we can clearly estimate the depth of the woody roots, which does not exceed 4 meters. In previous work on the same species, analyzing the δ18O in water of xylem and in the range of possible water sources, we argued that rain is the main water source in winter and spring, but not in summer, trees are not exploiting deep water from the aquifer as the popular assessment, instead of this they are using soil water at few meter depth. The results of the present work confirm the idea that the roots of Argania spinosa are not growing very deep.

Keywords: Argania spinosa, electrical resistivity imaging, root system, soil moisture

Procedia PDF Downloads 314
98 Sustainable Mining Fulfilling Constitutional Responsibilities: A Case Study of NMDC Limited Bacheli in India

Authors: Bagam Venkateswarlu

Abstract:

NMDC Limited, Indian multinational mining company operates under administrative control of Ministry of Steel, Government of India. This study is undertaken to evaluate how sustainable mining practiced by the company fulfils the provisions of Indian Constitution to secure to its citizen – justice, equality of status and opportunity, promoting social, economic, political, and religious wellbeing. The Constitution of India lays down a road map as to how the goal of being a “Welfare State” shall be achieved. The vision of sustainable mining being practiced is oriented along the constitutional responsibilities on Indian Citizens and the Corporate World. This qualitative study shall be backed by quantitative studies of National Mineral Development Corporation performances in various domains of sustainable mining and ESG, that is, environment, social and governance parameters. For example, Five Star Rating of mine is a comprehensive evaluation system introduced by Ministry of Mines, Govt. of India is one of the methodologies. Corporate Social Responsibilities is one of the thrust areas for securing social well-being. Green energy initiatives in and around the mines has given the title of “Eco-Friendly Miner” to NMDC Limited. While operating fully mechanized large scale iron ore mine (18.8 million tonne per annum capacity) in Bacheli, Chhattisgarh, M/s NMDC Limited caters to the needs of mineral security of State of Chhattisgarh and Indian Union. It preserves forest, wild-life, and environment heritage of richly endowed State of Chhattisgarh. In the remote and far-flung interiors of Chhattisgarh, NMDC empowers the local population by providing world class educational & medical facilities, transportation network, drinking water facilities, irrigational agricultural supports, employment opportunities, establishing religious harmony. All this ultimately results in empowered, educated, and improved awareness in population. Thus, the basic tenets of constitution of India- secularism, democracy, welfare for all, socialism, humanism, decentralization, liberalism, mixed economy, and non-violence is fulfilled. Constitution declares India as a welfare state – for the people, of the people and by the people. The sustainable mining practices by NMDC are in line with the objective. Thus, the purpose of study is fully met with. The potential benefit of the study includes replicating this model in existing or new establishments in various parts of country – especially in the under-privileged interiors and far-flung areas which are yet to see the lights of development.

Keywords: ESG values, Indian constitution, NMDC limited, sustainable mining, CSR, green energy

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97 Homeless Population Modeling and Trend Prediction Through Identifying Key Factors and Machine Learning

Authors: Shayla He

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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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96 The Aspect of the Digital Formation in the Solar Community as One Prototype to Find the Algorithmic Sustainable Conditions in the Global Environment

Authors: Kunihisa Kakumoto

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Purpose: The global environmental problem is now raised in the global dimension. The sprawl phenomenon over the natural limitation is to be made a forecast beforehand in an algorithmic way so that the condition of our social life can hopefully be protected under the natural limitation. The sustainable condition in the globe is now to be found to keep the balance between the capacity of nature and the possibility of our social lives. The amount of water on the earth is limited. Therefore, on the reason, sustainable conditions are strongly dependent on the capacity of water. The amount of water can be considered in relation to the area of the green planting because a certain volume of the water can be obtained in the forest, where the green planting can be preserved. We can find the sustainable conditions of the water in relation to the green planting area. The reduction of CO₂ by green planting is also possible. Possible Measure and the Methods: Until now, by the opportunity of many international conferences, the concept of the solar community as one prototype has been introduced by technical papers. The algorithmic trial calculation on the basic concept of the solar community can be taken into consideration. The concept of the solar community is based on the collected data of the solar model house. According to the algorithmic results of the prototype, the simulation work in the globe can be performed as the algorithmic conversion results. This algorithmic study can be simulated by the amount of water, also in relation to the green planting area. Additionally, the submission of CO₂ in the solar community and the reduction of CO₂ by green planting can be calculated. On the base of these calculations in the solar community, the sustainable conditions on the globe can be simulated as the conversion results in an algorithmic way. The digital formation in the solar community can also be taken into consideration by this opportunity. Conclusion: For the finding of sustainable conditions around the globe, the solar community as one prototype has been taken into consideration. The role of the water is very important because the capacity of the water supply is very limited. But, at present, the cycle of the social community is not composed by the point of the natural mechanism. The simulative calculation of this study can be shown by the limitation of the total water supply. According to this process, the total capacity of the water supply and the capable residential number of the population and the areas can be taken into consideration by the algorithmic calculation. For keeping enough water, the green planting areas are very important. The planting area is also very important to keep the balance of CO₂. The simulative calculation can be performed by the relation between the submission and the reduction of CO₂ in the solar community. For the finding of this total balance and the sustainable conditions, the green planting area and the total amount of water can be recognized by the algorithmic simulative calculation. The study for the finding of sustainable conditions can be performed by the simulative calculations on the algorithmic model in the solar community as one prototype. The example of one prototype can be in balance. The activity of the social life must be in the capacity of the natural mechanism. The capable capacity of the natural environment in our world is very limited.

Keywords: the solar community, the sustainable condition, the natural limitation, the algorithmic calculation

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95 Influence of a High-Resolution Land Cover Classification on Air Quality Modelling

Authors: C. Silveira, A. Ascenso, J. Ferreira, A. I. Miranda, P. Tuccella, G. Curci

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Poor air quality is one of the main environmental causes of premature deaths worldwide, and mainly in cities, where the majority of the population lives. It is a consequence of successive land cover (LC) and use changes, as a result of the intensification of human activities. Knowing these landscape modifications in a comprehensive spatiotemporal dimension is, therefore, essential for understanding variations in air pollutant concentrations. In this sense, the use of air quality models is very useful to simulate the physical and chemical processes that affect the dispersion and reaction of chemical species into the atmosphere. However, the modelling performance should always be evaluated since the resolution of the input datasets largely dictates the reliability of the air quality outcomes. Among these data, the updated LC is an important parameter to be considered in atmospheric models, since it takes into account the Earth’s surface changes due to natural and anthropic actions, and regulates the exchanges of fluxes (emissions, heat, moisture, etc.) between the soil and the air. This work aims to evaluate the performance of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), when different LC classifications are used as an input. The influence of two LC classifications was tested: i) the 24-classes USGS (United States Geological Survey) LC database included by default in the model, and the ii) CLC (Corine Land Cover) and specific high-resolution LC data for Portugal, reclassified according to the new USGS nomenclature (33-classes). Two distinct WRF-Chem simulations were carried out to assess the influence of the LC on air quality over Europe and Portugal, as a case study, for the year 2015, using the nesting technique over three simulation domains (25 km2, 5 km2 and 1 km2 horizontal resolution). Based on the 33-classes LC approach, particular emphasis was attributed to Portugal, given the detail and higher LC spatial resolution (100 m x 100 m) than the CLC data (5000 m x 5000 m). As regards to the air quality, only the LC impacts on tropospheric ozone concentrations were evaluated, because ozone pollution episodes typically occur in Portugal, in particular during the spring/summer, and there are few research works relating to this pollutant with LC changes. The WRF-Chem results were validated by season and station typology using background measurements from the Portuguese air quality monitoring network. As expected, a better model performance was achieved in rural stations: moderate correlation (0.4 – 0.7), BIAS (10 – 21µg.m-3) and RMSE (20 – 30 µg.m-3), and where higher average ozone concentrations were estimated. Comparing both simulations, small differences grounded on the Leaf Area Index and air temperature values were found, although the high-resolution LC approach shows a slight enhancement in the model evaluation. This highlights the role of the LC on the exchange of atmospheric fluxes, and stresses the need to consider a high-resolution LC characterization combined with other detailed model inputs, such as the emission inventory, to improve air quality assessment.

Keywords: land use, spatial resolution, WRF-Chem, air quality assessment

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94 Development and Preliminary Testing of the Dutch Version of the Program for the Education and Enrichment of Relational Skills

Authors: Sakinah Idris, Gabrine Jagersma, Bjorn Jaime Van Pelt, Kirstin Greaves-Lord

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Background: The PEERS (Program for the Education and Enrichment of Relational Skills) intervention can be considered a well-established, evidence-based intervention in the USA. However, testing the efficacy of cultural adaptations of PEERS is still ongoing. More and more, the involvement of all stakeholders in the development and evaluation of interventions is acknowledged as crucial for the longer term implementation of interventions across settings. Therefore, in the current project, teens with ASD (Autism Spectrum Disorder), their neurotypical peers, parents, teachers, as well as clinicians were involved in the development and evaluation of the Dutch version of PEERS. Objectives: The current presentation covers (1) the formative phase and (2) the preliminary adaptation test phase of the cultural adaptation of evidence-based interventions. In the formative phase, we aim to describe the process of adaptation of the PEERS program to the Dutch culture and care system. In the preliminary adaptation phase, we will present results from the preliminary adaptation test among 32 adolescents with ASD. Methods: In phase 1, a group discussion on common vocabulary was conducted among 70 teenagers (and their teachers) from special and regular education aged 12-18 years old. This inventory concerned 14 key constructs from PEERS, e.g., areas of interests, locations for making friends, common peer groups and crowds inside and outside of school, activities with friends, commonly used ways for electronic communication, ways for handling disagreements, and common teasing comebacks. Also, 15 clinicians were involved in the translation and cultural adaptation process. The translation and cultural adaptation process were guided by the research team, and who included input and feedback from all stakeholders through an iterative feedback incorporation procedure. In phase 2, The parent-reported Social Responsiveness Scale (SRS), the Test of Adolescent Social Skills Knowledge (TASSK), and the Quality of Socialization Questionnaire (QSQ) were assessed pre- and post-intervention to evaluate potential treatment outcome. Results: The most striking cultural adaptation - reflecting the standpoints of all stakeholders - concerned the strategies for handling rumors and gossip, which were suggested to be taught using a similar approach as the teasing comebacks, more in line with ‘down-to-earth’ Dutch standards. The preliminary testing of this adapted version indicated that the adolescents with ASD significantly improved their social knowledge (TASSK; t₃₁ = -10.9, p < .01), social experience (QSQ-Parent; t₃₁ = -4.2, p < .01 and QSQ-Adolescent; t₃₂ = -3.8, p < .01), and in parent-reported social responsiveness (SRS; t₃₃ = 3.9, p < .01). In addition, subjective evaluations of teens with ASD, their parents and clinicians were positive. Conclusions: In order to further scrutinize the effectiveness of the Dutch version of the PEERS intervention, we recommended performing a larger scale randomized control trial (RCT) design, for which we provide several methodological considerations.

Keywords: cultural adaptation, PEERS, preliminary testing, translation

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