Search results for: climatic classification

Authors: Kefi Rahmadio, Filipus Armando Ginting, Richard Nainggolan

Abstract:

This research shows the formation of the West Buru Basin and the potential utilization of this West Buru Basin as a geothermal potential. The research area is West Buru Island which is part of the West Buru Basin. The island is located in Maluku Province, with its capital city named Namlea. The island is divided into 10 districts, namely District Kepalamadan, Airbuaya District, Wapelau District, Namlea District, Waeapo District, Batabual District, Namrole District, Waesama District, Leksula District, and Ambalau District. The formation in this basin is Permian-Quarter. They start from the Formation Ghegan, Dalan Formation, Mefa Formation, Kuma Formation, Waeken Formation, Wakatin Formation, Ftau Formation and Leko Formation. These formations are composing this West Buru Basin. Determination of prospect area in the geothermal area with preliminary investigation stage through observation of manifestation, topographic shape and structure are found around prospect area. This is done because there is no data of earth that support the determination of prospect area more accurately. In Waepo area, electric power generated based on field observation and structural analysis, geothermal area of ​Waeapo was approximately 6 km², with reference to the SNI 'Classification of Geothermal Potential' (No.03-5012-1999), an area of ​​1 km² is assumed to be 12.5 MWe. The speculative potential of this area is (Q) = 6 x 12.5 MWe = 75 MWe. In the Bata Bual area, the geothermal prospect projected 4 km², the speculative potential of the Bata Bual area is worth (Q) = 4 x 12.5 MWe = 50 MWe. In Kepala Madan area, based on the estimation of manifestation area, there is a wide area of ​​prospect in Kepala Madan area about 4 km². The geothermal energy potential of the speculative level in Kepala Madan district is (Q) = 4 x 12.5 MWe = 50 MWe. These three areas are the largest geothermal potential on the island of West Buru. From the above research, it can be concluded that there is potential in West Buru Island. Further exploration is needed to find greater potential. Therefore, researchers want to explain the geothermal potential contained in the West Buru Basin, within the scope of West Buru Island. This potential can be utilized for the community of West Buru Island.

Keywords: West Buru basin, West Buru island, potential, Waepo, Bata Bual, Kepala Madan

Procedia PDF Downloads 197

Authors: Mustafa Al Sukar, Azzam Sleit, Abdullatif Abu-Dalhoum, Bassam Al-Kasasbeh

Abstract:

Use and abuse of drugs by teens is very common and can have dangerous consequences. The drugs contribute to physical and sexual aggression such as assault or rape. Some teenagers regularly use drugs to compensate for depression, anxiety or a lack of positive social skills. Teen resort to smoking should not be minimized because it can be "gateway drugs" for other drugs (marijuana, cocaine, hallucinogens, inhalants, and heroin). The combination of teenagers' curiosity, risk taking behavior, and social pressure make it very difficult to say no. This leads most teenagers to the questions: "Will it hurt to try once?" Nowadays, technological advances are changing our lives very rapidly and adding a lot of technologies that help us to track the risk of drug abuse such as smart phones, Wireless Sensor Networks (WSNs), Internet of Things (IoT), etc. This technique may help us to early discovery of drug abuse in order to prevent an aggravation of the influence of drugs on the abuser. In this paper, we have developed a Decision Support System (DSS) for detecting the drug abuse using Artificial Neural Network (ANN); we used a Multilayer Perceptron (MLP) feed-forward neural network in developing the system. The input layer includes 50 variables while the output layer contains one neuron which indicates whether the person is a drug addict. An iterative process is used to determine the number of hidden layers and the number of neurons in each one. We used multiple experiment models that have been completed with Log-Sigmoid transfer function. Particularly, 10-fold cross validation schemes are used to access the generalization of the proposed system. The experiment results have obtained 98.42% classification accuracy for correct diagnosis in our system. The data had been taken from 184 cases in Jordan according to a set of questions compiled from Specialists, and data have been obtained through the families of drug abusers.

Keywords: drug addiction, artificial neural networks, multilayer perceptron (MLP), decision support system

Procedia PDF Downloads 272

Authors: Alma Ramić, Mirjana Skočibušić, Renata Odžak, Tomica Hrenar, Ines Primožič

Abstract:

In an attempt to identify a new class of antimicrobial agents, the antimicrobial potential of Cinchona alkaloid derivatives was evaluated. The bark of the Cinchona trees is the source of a variety of alkaloids, among which the best known are quinine, quinidine, cinchonine and cinchonidine. They are very useful as organocatalysts in stereoselective synthesis. On the other hand, quinine is traditionally used in the treatment of malaria. Furthermore, Cinchona alkaloids possess various analgesic, anti-inflammatory and anti–arrhythmic properties as well. In this work we present the synthesis of twenty quaternary derivatives of pseudo−enantiomeric Cinchona alkaloid derivatives to evaluate their antibacterial activity. Quaternization of quinuclidine moiety was carried out with groups diverse in their size. The structures of compounds were systematically modified to obtain drug-like properties with proper physical and chemical properties and avoiding toxophore. All compounds were prepared in good yields and were characterized by standard analytical spectroscopy methods (1D and 2D NMR, IR, MS). The antibacterial activities of all compounds were evaluated against series of recent clinical isolates of antibiotic susceptible Gram-positive and resistant Gram-negative pathogens by determining their zone of inhibition and minimum inhibitory concentrations. All compounds showed good to strong broad-spectrum activity, equivalent or better in comparison with standard antibiotics used. Furthermore, seven compounds exhibited significant antibacterial efficiency against Gram-negative isolates. To visualize the results, principal component analysis was used as an additional classification tool. Cytotoxicity of compounds with different cell lines in human cell culture was determined. Based on these results, substituted quaternary Cinchona scaffold can be considered as promising new class of antimicrobials and further investigations should be performed. Supported by Croatian Science Foundation, Project No 3775 ADESIRE.

Keywords: antibacterial efficiency, cinchona alkaloids, cytotoxicity, pseudo‐enantiomers

Procedia PDF Downloads 133

Authors: Rashima Mahajan, Dipali Bansal, Shweta Singh

Abstract:

Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotive EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.

Keywords: brain computer interface, electroencephalogram, EEGLab, BCILab, emotive, emotions, interval features, spectral features, artificial neural network, control applications

Procedia PDF Downloads 299

Authors: Cristy Stagnar, Nina Hubig, Diana Ivankovic

Abstract:

The epigenome is a compelling candidate for mediating long-term responses to environmental effects modifying disease risk. The main goal of this research is to develop a machine learning-based DNA methylation score, which will be valuable in delineating the unique contribution of paternal epigenetic modifications to the germline impacting childhood health outcomes. It will also be a useful tool in validating self-reports of nonsmoking and in adjusting epigenome-wide DNA methylation association studies for this early-life exposure. Using secondary data from two population-based methylation profiling studies, our DNA methylation score is based on CpG DNA methylation measurements from cord blood gathered from children whose fathers smoked pre- and peri-conceptually. Each child’s mother and father fell into one of three class labels in the accompanying questionnaires -never smoker, former smoker, or current smoker. By applying different machine learning algorithms to the accessible resource for integrated epigenomic studies (ARIES) sub-study of the Avon longitudinal study of parents and children (ALSPAC) data set, which we used for training and testing of our model, the best-performing algorithm for classifying the father smoker and mother never smoker was selected based on Cohen’s κ. Error in the model was identified and optimized. The final DNA methylation score was further tested and validated in an independent data set. This resulted in a linear combination of methylation values of selected probes via a logistic link function that accurately classified each group and contributed the most towards classification. The result is a unique, robust DNA methylation score which combines information on DNA methylation and early life exposure of offspring to paternal smoking during pregnancy and which may be used to examine the paternal contribution to offspring health outcomes.

Keywords: epigenome, health outcomes, paternal preconception environmental exposures, supervised machine learning

Procedia PDF Downloads 168

Authors: Ranjit Kumar Sahu, Ramakar Jha

Abstract:

Urban Water Management is the practice of managing freshwater, waste water, and storm water as components of a basin-wide management plan. It builds on existing water supply and sanitation considerations within an urban settlement by incorporating urban water management within the scope of the entire river basin. The pervasive problems generated by urban development have prompted, in the present work, to study the spatial extent of urbanization in Golden Triangle of Odisha connecting the cities Bhubaneswar (20.2700° N, 85.8400° E), Puri (19.8106° N, 85.8314° E) and Konark (19.9000° N, 86.1200° E)., and patterns of periodic changes in urban development (systematic/random) in order to develop future plans for (i) urbanization promotion areas, and (ii) urbanization control areas. Remote Sensing, using USGS (U.S. Geological Survey) Landsat8 maps, supervised classification of the Urban Sprawl has been done for during 1980 - 2014, specifically after 2000. This Work presents the following: (i) Time series analysis of Hydrological data (ground water and rainfall), (ii) Application of SWMM (Storm Water Management Model) and other soft computing techniques for Urban Water Management, and (iii) Uncertainty analysis of model parameters (Urban Sprawl and correlation analysis). The outcome of the study shows drastic growth results in urbanization and depletion of ground water levels in the area that has been discussed briefly. Other relative outcomes like declining trend of rainfall and rise of sand mining in local vicinity has been also discussed. Research on this kind of work will (i) improve water supply and consumption efficiency (ii) Upgrade drinking water quality and waste water treatment (iii) Increase economic efficiency of services to sustain operations and investments for water, waste water, and storm water management, and (iv) engage communities to reflect their needs and knowledge for water management.

Keywords: Storm Water Management Model (SWMM), uncertainty analysis, urban sprawl, land use change

Procedia PDF Downloads 404

Authors: F. Fatoye, C. E. Mbada, T. Gebrye, A. O. Ogunsola, C. Fatoye, O. Oyewole

Abstract:

Musculoskeletal disorders (MSDs) such as low back pain (LBP), cervical spondylosis (CSPD), sprain, osteoarthritis (OA), and post immobilization stiffness (PIS) have a major impact on individuals, health systems and society in terms of morbidity, long-term disability, and economics. This study estimated the direct and indirect costs of common MSDs in Osun State, Nigeria. A review of medical charts for adult patients attending Physiotherapy Outpatient Clinic at the Obafemi Awolowo University Teaching Hospitals Complex, Osun State, Nigeria between 2009 and 2018 was carried out. The occupational class of the patients was determined using the International Labour Classification (ILO). The direct and indirect costs were estimated using a cost-of-illness approach. Physiotherapy related health resource use, and costs of the common MSDs, including consultation fee, total fee charge per session, costs of consumables were estimated. Data were summarised using descriptive statistics mean and standard deviation (SD). Overall, 1582 (Male = 47.5%, Female = 52.5%) patients with MSDs population with a mean age of 47.8 ± 25.7 years participated in this study. The mean (SD) direct costs estimate for LBP, CSPD, PIS, sprain, OA, and other conditions were $18.35 ($17.33), $34.76 ($17.33), $32.13 ($28.37), $35.14 ($44.16), $37.19 ($41.68), and $15.74 ($13.96), respectively. The mean (SD) indirect costs estimate of LBP, CSPD, PIS, sprain, OA, and other MSD conditions were $73.42 ($43.54), $140.57 ($69.31), $128.52 ($113.46), sprain $140.57 ($69.31), $148.77 ($166.71), and $62.98 ($55.84), respectively. Musculoskeletal disorders contribute a substantial economic burden to individuals with the condition and society. The unacceptable economic loss of MSDs should be reduced using appropriate strategies. Further research is required to determine the clinical and cost effectiveness of strategies to improve health outcomes of patients with MSDs. The findings of the present study may assist health policy and decision makers to understand the economic burden of MSDs and facilitate efficient allocation of healthcare resources to alleviate the burden associated with these conditions in Nigeria.

Keywords: economic burden, low back pain, musculoskeletal disorders, real-world

Procedia PDF Downloads 188

Authors: Adel Francis

Abstract:

Most of scheduling methods and software apply the critical path logic. This logic schedule activities, apply constraints between these activities and try to optimize and level the allocated resources. The extensive use of this logic produces a complex an erroneous network hard to present, follow and update. Planning and management building projects should tackle the coordination of works and the management of limited spaces, traffic, and supplies. Activities cannot be performed without the resources available and resources cannot be used beyond the capacity of workplaces. Otherwise, workspace congestion will negatively affect the flow of works. The objective of the space planning is to link the spatial and temporal aspects, promote efficient use of the site, define optimal site occupancy rates, and ensures suitable rotation of the workforce in the different spaces. The Chronographic scheduling modelling belongs to this category and models construction operations as well as their processes, logical constraints, association and organizational models, which help to better illustrate the schedule information using multiple flexible approaches. The model defined three categories of areas (punctual, surface and linear) and four different layers (space creation, systems, closing off space, finishing, and reduction of space). The Chronographical modelling is a more complete communication method, having the ability to alternate from one visual approach to another by manipulation of graphics via a set of parameters and their associated values. Each individual approach can help to schedule a certain project type or specialty. Visual communication can also be improved through layering, sheeting, juxtaposition, alterations, and permutations, allowing for groupings, hierarchies, and classification of project information. In this way, graphic representation becomes a living, transformable image, showing valuable information in a clear and comprehensible manner, simplifying the site management while simultaneously utilizing the visual space as efficiently as possible.

Keywords: building projects, chronographic modelling, CPM, critical path, precedence diagram, scheduling

Procedia PDF Downloads 130

Authors: Waldir Roque, Gustavo Oliveira, Moises Santos, Tatiana Simoes

Abstract:

Increasing the oil recovery factor of an oil reservoir has been a concern of the oil industry. Usually, the production placement zones are defined after some analysis of geological and petrophysical parameters, being the rock porosity, permeability and oil saturation of fundamental importance. In this context, the determination of hydraulic flow units (HFUs) renders an important step in the process of reservoir characterization since it may provide specific regions in the reservoir with similar petrophysical and fluid flow properties and, in particular, techniques supporting the placement of production zones that favour the tracing of directional wells. A HFU is defined as a representative volume of a total reservoir rock in which petrophysical and fluid flow properties are internally consistent and predictably distinct of other reservoir rocks. Technically, a HFU is characterized as a rock region that exhibit flow zone indicator (FZI) points lying on a straight line of the unit slope. The goal of this paper is to provide a trustful indication for oil production placement zones for the best-fit HFUs. The FZI cloud of points can be obtained from the reservoir quality index (RQI), a function of effective porosity and permeability. Considering log and core data the HFUs are identified and using the discrete rock type (DRT) classification, a set of connected cell clusters can be found and by means a graph centrality metric, the maximum closeness (MaxC) cell is obtained for each cluster. Considering the MaxC cells as production zones, an extensive analysis, based on several oil recovery factor and oil cumulative production simulations were done for the SPE Model 2 and the UNISIM-I-D synthetic fields, where the later was build up from public data available from the actual Namorado Field, Campos Basin, in Brazil. The results have shown that the MaxC is actually technically feasible and very reliable as high performance production placement zones.

Keywords: hydraulic flow unit, maximum closeness centrality, oil production simulation, production placement zone

Procedia PDF Downloads 302

Authors: Ezat Vahidian, Babak Eshrati

Abstract:

Introduction: Elder abuse, a very complex issue with diverse definitions and names, has been very slow to capture the public eye and public policy since it is manifested at many levels. It requires the involvement of different types of professionals. While elder abuse is not a new phenomenon, the speed of population ageing world-wide is likely to lead to an increase in its incidence and prevalence. Elder abuse has devastating consequences for older persons such as poor quality of life, psychological distress, and loss of property and security. It is also associated with increased mortality and morbidity. Elder abuse is a problem that manifests itself in both rich and poor countries and at all levels of society. Purpose: The purpose of this study is to determine the prevalence of elder abuse and effects of social factor on it in Markazi Province. Materials and methods: The society of the study was all of the elders in Markazi Province that were available by geographical address in the table of rural and urban household societies. The study was cross sectional and multi phases in sampling the first one was classification according rural and urban area and the second one was cluster sampling with equal cluster. Estimation of samples were 472 persons and increased by design effect to 1110 persons. Collection data was done by questionnaire and analyzed by SPSS and chi 2 exam. Results: This study showed 70 persons were abused (42/8% male and 57/2% female) mean of ages was 74/7 years. 64% were marred and 31% were widows. There were not any significant meaningful association between elder abuse and area of living (pv=0.299),occupation (p.v=0.104), education (pv=0.358) and age (P.value=0.104) there were significant meaningful association between physical impairment (pv=0.08), and movement impairment (P.value=0.008). Conclusion: Results verify that maltreatment occurred in the aged persons. Analysis of data indicated that elder abuse exist in every socioeconomic group with any context of education in urban area and rural area and in men and women. Prevalence of elder abuse was 6.3% (70 persons) that verify the data of developed countries with limited sample.

Keywords: elder abuse, education, occupation, area of living

Procedia PDF Downloads 384

Authors: Rajashree Naik, Laxmi Kant Sharma

Abstract:

Sambhar lake is the largest inland Salt Lake of India, declared as a Ramsar site on 23 March 1990. Due to high salinity and alkalinity condition its biodiversity richness is contributed by haloalkaliphilic flora and fauna along with the diverse land cover including waterbody, wetland, salt crust, saline soil, vegetation, scrub land and barren land which welcome large number of flamingos and other migratory birds for winter harboring. But with the gradual increase in the irrational salt extraction activities, the ecological diversity is at stake. There is an urgent need to assess the ecosystem. Advanced technology like remote sensing and GIS has enabled to look into the past, compare with the present for the future planning and management of the natural resources in a judicious way. This paper is a research work intended to present a vegetation in typical inland lake environment of Sambhar wetland using satellite data of NASA’s EO-1 Hyperion sensor launched in November 2000. With the spectral range of 0.4 to 2.5 micrometer at approximately 10nm spectral resolution with 242 bands 30m spatial resolution and 705km orbit was used to produce a vegetation map for a portion of the wetland. The vegetation map was tested for classification accuracy with a pre-existing detailed GIS wetland vegetation database. Though the accuracy varied greatly for different classes the algal communities were successfully identified which are the major sources of food for flamingo. The results from this study have practical implications for uses of spaceborne hyperspectral image data that are now becoming available. Practical limitations of using these satellite data for wetland vegetation mapping include inadequate spatial resolution, complexity of image processing procedures, and lack of stereo viewing.

Keywords: Algal community, NASA’s EO-1 Hyperion, salt-tolerant species, wetland vegetation mapping

Procedia PDF Downloads 104

Authors: Jenson George, Thoa Nguyen, Garth Sanewski, Craig Hardner, Heather Eunice Smyth

Abstract:

Pineapple (Ananas comosus), with its unique sweet flavour, is one of the most popular tropical, non-climacteric fruits consumed worldwide. It is also the third most important tropical fruit in world production. In Australia, 99% of the pineapple production is from the Queensland state due to the favourable subtropical climatic conditions. The flavourful fruit is known to contain around 500 volatile organic compounds (VOC) at varying concentrations and greatly contribute to the flavour quality of pineapple fruit by providing distinct aroma sensory properties that are sweet, fruity, tropical, pineapple-like, caramel-like, coconut-like, etc. The aroma of pineapple is one of the important factors attracting consumers and strengthening the marketplace. To better understand the aroma of Australian-grown pineapples, the matrix-matched Gas chromatography–mass spectrometry (GC-MS), Head Space - Solid-phase microextraction (HS-SPME), Stable-isotope dilution analysis (SIDA) method was developed and validated. The developed method represents a significant improvement over current methods with the incorporation of multiple external reference standards, multiple isotopes labeled internal standards, and a matching model system of pineapple fruit matrix. This method was employed to quantify 28 key aroma compounds in more than 200 genetically diverse pineapple varieties from a breeding program. The Australian pineapple cultivars varied in content and composition of free volatile compounds, which were predominantly comprised of esters, followed by terpenes, alcohols, aldehydes, and ketones. Using selected commercial cultivars grown in Australia, and by employing the sensorial analysis, the appearance (colour), aroma (intensity, sweet, vinegar/tang, tropical fruits, floral, coconut, green, metallic, vegetal, fresh, peppery, fermented, eggy/sulphurous) and texture (crunchiness, fibrousness, and juiciness) were obtained. Relationships between sensory descriptors and volatiles were explored by applying multivariate analysis (PCA) to the sensorial and chemical data. The key aroma compounds of pineapple exhibited a positive correlation with corresponding sensory properties. The sensory and volatile data were also used to explore genetic diversity in the breeding population. GWAS was employed to unravel the genetic control of the pineapple volatilome and its interplay with fruit sensory characteristics. This study enhances our understanding of pineapple aroma (flavour) compounds, their biosynthetic pathways and expands breeding option for pineapple cultivars. This research provides foundational knowledge to support breeding programs, post-harvest and target market studies, and efforts to optimise the flavour of commercial pineapple varieties and their parent lines to produce better tasting fruits for consumers.

Keywords: Ananas comosus, pineapple, flavour, volatile organic compounds, aroma, Gas chromatography–mass spectrometry (GC-MS), Head Space - Solid-phase microextraction (HS-SPME), Stable-isotope dilution analysis (SIDA).

Procedia PDF Downloads 20

Authors: Liang-Jen Wang, Sung-Chou Li, Yuan-Ming Yeh, Sheng-Yu Lee, Ho-Chang Kuo, Chia-Yu Yang

Abstract:

Background: Dysbiosis in the gut microbial community might be involved in the pathophysiology of attention deficit/hyperactivity disorder (ADHD). The fungal component of the gut microbiome, namely the mycobiota, is a hyperdiverse group of multicellular eukaryotes that can influence host intestinal permeability. This study therefore aimed to investigate the impact of fungal mycobiome dysbiosis and intestinal permeability on ADHD. Methods: Faecal samples were collected from 35 children with ADHD and from 35 healthy controls. Total DNA was extracted from the faecal samples, and the internal transcribed spacer (ITS) regions were sequenced using high-throughput next-generation sequencing (NGS). The fungal taxonomic classification was analysed using bioinformatics tools, and the differentially expressed fungal species between the ADHD and healthy control groups were identified. An in vitro permeability assay (Caco-2 cell layer) was used to evaluate the biological effects of fungal dysbiosis on intestinal epithelial barrier function. Results: The β-diversity (the species diversity between two communities), but not α-diversity (the species diversity within a community), reflected the differences in fungal community composition between ADHD and control groups. At the phylum level, the ADHD group displayed a significantly higher abundance of Ascomycota and significantly lower abundance of Basidiomycota than the healthy control group. At the genus level, the abundance of Candida (especially Candida albicans) was significantly increased in ADHD patients compared to the healthy controls. In addition, the in vitro cell assay revealed that C. albicans secretions significantly enhanced the permeability of Caco-2 cells. Conclusions: The current study is the first to explore altered gut mycobiome dysbiosis using the NGS platform in ADHD. The findings from this study indicated that dysbiosis of the fungal mycobiome and intestinal permeability might be associated with susceptibility to ADHD.

Keywords: ADHD, fungus, gut–brain axis, biomarker, child psychiatry

Procedia PDF Downloads 84

Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock

Abstract:

Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

Keywords: subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing

Procedia PDF Downloads 101

Authors: Dominique Arrouays, Songchao Chen, Anne C. Richer-De-Forges

Abstract:

Soils are at the crossing of many issues such as food and water security, sustainable energy, climate change mitigation and adaptation, biodiversity protection, human health and well-being. They deliver many ecosystem services that are essential to life on Earth. Therefore, there is a growing demand for soil information on a national and global scale. Unfortunately, many countries do not have detailed soil maps, and, when existing, these maps are generally based on more or less complex and often non-harmonized soil classifications. An estimate of their uncertainty is also often missing. Thus, there are not easy to understand and often not properly used by end-users. Therefore, there is an urgent need to provide end-users with spatially exhaustive grids of essential soil properties, together with an estimate of their uncertainty. One way to achieve this is digital soil mapping (DSM). The concept of DSM relies on the hypothesis that soils and their properties are not randomly distributed, but that they depend on the main soil-forming factors that are climate, organisms, relief, parent material, time (age), and position in space. All these forming factors can be approximated using several exhaustive spatial products such as climatic grids, remote sensing products or vegetation maps, digital elevation models, geological or lithological maps, spatial coordinates of soil information, etc. Thus, DSM generally relies on models calibrated with existing observed soil data (point observations or maps) and so-called “ancillary co-variates” that come from other available spatial products. Then the model is generalized on grids where soil parameters are unknown in order to predict them, and the prediction performances are validated using various methods. With the growing demand for soil information at a national and global scale and the increase of available spatial co-variates national and continental DSM initiatives are continuously increasing. This short review illustrates the main national and continental advances in Europe, the diversity of the approaches and the databases that are used, the validation techniques and the main scientific and other issues. Examples from several countries illustrate the variety of products that were delivered during the last ten years. The scientific production on this topic is continuously increasing and new models and approaches are developed at an incredible speed. Most of the digital soil mapping (DSM) products rely mainly on machine learning (ML) prediction models and/or the use or pedotransfer functions (PTF) in which calibration data come from soil analyses performed in labs or for existing conventional maps. However, some scientific issues remain to be solved and also political and legal ones related, for instance, to data sharing and to different laws in different countries. Other issues related to communication to end-users and education, especially on the use of uncertainty. Overall, the progress is very important and the willingness of institutes and countries to join their efforts is increasing. Harmonization issues are still remaining, mainly due to differences in classifications or in laboratory standards between countries. However numerous initiatives are ongoing at the EU level and also at the global level. All these progress are scientifically stimulating and also promissing to provide tools to improve and monitor soil quality in countries, EU and at the global level.

Keywords: digital soil mapping, global soil mapping, national and European initiatives, global soil mapping products, mini-review

Procedia PDF Downloads 161

Authors: Gayathri Nagarajan, L. D. Dhinesh Babu

Abstract:

Health care is one of the prominent industries that generate voluminous data thereby finding the need of machine learning techniques with big data solutions for efficient processing and prediction. Missing data, incomplete data, real time streaming data, sensitive data, privacy, heterogeneity are few of the common challenges to be addressed for efficient processing and mining of health care data. In comparison with other applications, accuracy and fast processing are of higher importance for health care applications as they are related to the human life directly. Though there are many machine learning techniques and big data solutions used for efficient processing and prediction in health care data, different techniques and different frameworks are proved to be effective for different applications largely depending on the characteristics of the datasets. In this paper, we present a framework that uses ensemble machine learning technique gradient boosted trees for data classification in health care big data. The framework is built on Spark platform which is fast in comparison with other traditional frameworks. Unlike other works that focus on a single technique, our work presents a comparison of six different machine learning techniques along with gradient boosted trees on datasets of different characteristics. Five benchmark health care datasets are considered for experimentation, and the results of different machine learning techniques are discussed in comparison with gradient boosted trees. The metric chosen for comparison is misclassification error rate and the run time of the algorithms. The goal of this paper is to i) Compare the performance of gradient boosted trees with other machine learning techniques in Spark platform specifically for health care big data and ii) Discuss the results from the experiments conducted on datasets of different characteristics thereby drawing inference and conclusion. The experimental results show that the accuracy is largely dependent on the characteristics of the datasets for other machine learning techniques whereas gradient boosting trees yields reasonably stable results in terms of accuracy without largely depending on the dataset characteristics.

Keywords: big data analytics, ensemble machine learning, gradient boosted trees, Spark platform

Procedia PDF Downloads 219

Authors: Guo Yu, Haoming Ma, Peiru Zhou

Abstract:

BACKGROUND: In addition to hyperglycemia, hypoglycemia, and glycemic variability, a decrease in the time in the targeted blood glucose range (TIR) may be associated with an increased risk of death for critically ill patients. However, the relationship between the TIR and mortality may be influenced by the presence of diabetes and glycemic variability. METHODS: A total of 998 diabetic and non-diabetic patients with severe diseases in the ICU were selected for this retrospective analysis. The TIR is defined as the percentage of time spent in the target blood glucose range of 3.9–10.0 mmol/L within 24 hours. The relationship between TIR and in-hospital in diabetic and non-diabetic patients was analyzed. The effect of glycemic variability was also analyzed. RESULTS: The binary logistic regression model showed that there was a significant association between the TIR as a continuous variable and the in-hospital death of severely ill non-diabetic patients (OR=0.991, P=0.015). As a classification variable, TIR≥70% was significantly associated with in-hospital death (OR=0.581, P=0.003). Specifically, TIR≥70% was a protective factor for the in-hospital death of severely ill non-diabetic patients. The TIR of severely ill diabetic patients was not significantly associated with in-hospital death; however, glycemic variability was significantly and independently associated with in-hospital death (OR=1.042, P=0.027). Binary logistic regression analysis of comprehensive indices showed that for non-diabetic patients, the C3 index (low TIR & high CV) was a risk factor for increased mortality (OR=1.642, P<0.001). In addition, for diabetic patients, the C3 index was an independent risk factor for death (OR=1.994, P=0.008), and the C4 index (low TIR & low CV) was independently associated with increased survival. CONCLUSIONS: The TIR of non-diabetic patients during ICU hospitalization was associated with in-hospital death even after adjusting for disease severity and glycemic variability. There was no significant association between the TIR and mortality of diabetic patients. However, for both diabetic and non-diabetic critically ill patients, the combined effect of high TIR and low CV was significantly associated with ICU mortality. Diabetic patients seem to have higher blood glucose fluctuations and can tolerate a large TIR range. Both diabetic and non-diabetic critically ill patients should maintain blood glucose levels within the target range to reduce mortality.

Keywords: severe disease, diabetes, blood glucose control, time in targeted blood glucose range, glycemic variability, mortality

Procedia PDF Downloads 197

Authors: Victoria Bila, Iryna Ventskivska, Oleksandra Zahorodnia

Abstract:

The goal of the study: To study the distribution of patients of the Kiyv Perinatal Center according to the Robson system and compare it with world data. Materials and methods: a comparison of the distribution of patients of Kiyv Perinatal center according to the Robson system for 2 periods - the first quarter of 2019 and 2020. For each group, 3 indicators were analyzed - the share of this group in the overall structure of patients of the Perinatal Center for the reporting period, the frequency of abdominal delivery in this group, as well as the contribution of this group to the total number of abdominal delivery. Obtained data were compared with those of the WHO in the guidelines for the implementation of the Robson system in 2017. Results and its discussion: The distribution of patients of the Perinatal Center into groups in the Robson classification is not much different from that recommended by the author. So, among all women, patients of group 1 dominate; this indicator does not change in dynamics. A slight increase in the share of group 2 (6.7% in 2019 and 9.3% - 2020) was due to an increase in the number of labor induction. At the same time, the number of patients of groups 1 and 2 in the Perinatal Center is greater than in the world population, which is determined by the hospitalization of primiparous women with reproductive losses in the past. The Perinatal Center is distinguished from the world population and the proportion of women of group 5 - it was 5.4%, in the world - 7.6%. The frequency of caesarean section in the Perinatal Center is within limits typical for most countries (20.5-20.8%). Moreover, the dominant groups in the structure of caesarean sections are group 5 (21-23.3%) and group 2 (21.9-22.9%), which are the reserve for reducing the number of abdominal delivery. In group 2, certain results have already been achieved in this matter - the frequency of cesarean section in 2019 here amounted to 67.8%, in the first quarter of 2020 - 51.6%. This happened due to a change in the leading method of induction of labor. Thus, the Robson system is a convenient and affordable tool for assessing the structure of caesarean sections. The analysis showed that, in general, the structure of caesarean sections in the Perinatal Center is close to world data, and the identified deviations have explanations related to the specialization of the Center.

Keywords: cesarian section, Robson system, Kyiv Perinatal Center, labor induction

Procedia PDF Downloads 106

Authors: Mohamed M. Mashaly, Ahmed M. F. El Shiwi

Abstract:

Background: Shoulder impingement syndrome is an encroachment of subacromial tissues, rotator cuff, subacromial bursa, and the long head of the biceps tendon, as a result of narrowing of the subacromial space. Activities requiring repetitive or sustained use of the arms over head often predispose the rotator cuff tendon to injury. Purpose: To compare between Combined effect therapeutic exercises and Shockwave therapy versus therapeutic exercises and phonophoresis in the treatment of shoulder impingement syndrome. Methods: Thirty patients diagnosed as shoulder impingement syndrome stage II Neer classification due to mechanical causes. Patients were randomly distributed into two equal groups. The first group consisted of 15 patients with a mean age of (45.46+8.64) received therapeutic exercises (stretching exercise of posterior shoulder capsule and strengthening exercises of shoulder muscles) and shockwave therapy (6000 shocks, 2000/session, 3 sessions, 2 weeks apart, 0.22mJ/mm^2) years. The second group consisted of 15 patients with a mean age of 46.26 (+ 8.05) received same therapeutic exercises and phonophoresis (3 times per week, each other day, for 4 consecutive weeks). Patients were evaluated pretreatment and post treatment for shoulder pain severity, shoulder functional disability, shoulder flexion, abduction and internal rotation motions. Results: Patients of both groups showed significant improvement in all the measured variables. In between groups difference the shock wave group showed a significant improvement in all measured variables than phonophoresis group. Interpretation/Conclusion: Combined effect of therapeutic exercises and shock wave were more effective than therapeutic exercises and phonophoresis on decreasing shoulder pain severity, shoulder functional disability, increasing in shoulder flexion, abduction, internal rotation in patients with shoulder impingement syndrome.

Keywords: shoulder impingement syndrome, therapeutic exercises, shockwave, phonophoresis

Procedia PDF Downloads 453

Authors: Devanshu Gupta, Kailash Chandra, Priyanka Das, Joyjit Ghosh

Abstract:

Beetles, in the insect order Coleoptera are the most species-rich group on this planet today. They represent about 40% of the total insect diversity of the world. With a considerable range of landform types including significant mountain ranges, deserts, fertile irrigational plains, and hilly forested areas, India is one of the mega-diverse countries and includes more than 0.1 million faunal species. Despite having rich biodiversity, the efforts to catalogue the beetle diversity of the extant species/taxa reported from India have been less. Therefore, in this paper, the information on the beetle fauna of India is provided based on the data available with the museum collections of Zoological Survey of India and taxa extracted from zoological records and published literature. The species were listed with their valid names, synonyms, type localities, type depositories, and their distribution in states and biogeographic zones of India. The catalogue also incorporates the bibliography on Indian Coleoptera. The exhaustive species inventory, prepared by us include distributional records from Himalaya, Trans Himalaya, Desert, Semi-Arid, Western Ghats, Deccan Peninsula, Gangetic Plains, Northeast, Islands, and Coastal areas of the country. Our study concludes that many of the species are still known from their type localities only, so there is need to revisit and resurvey those collection localities for the taxonomic evaluation of those species. There are species which exhibit single locality records, and taxa-specific biodiversity assessments are required to be undertaken to understand the distributional range of such species. The primary challenge is taxonomic identifications of the species which were described before independence, and the type materials are present in overseas museums. For such species, taxonomic revisions of the different group of beetles are required to solve the problems of identification and classification.

Keywords: checklist, taxonomy, museum collections, biogeographic zones

Procedia PDF Downloads 227

Authors: Anshu Gupta, Charu Gupta

Abstract:

Background: Punjab, a border state in India has achieved notoriety world over for its drug abuse problem. People right from school kids to elderly are hooked to drugs. This pattern of substance abuse is prevalent in both cities and villages alike. Excess of younger population in India has further aggravated the situation. It is feared that the benefits of India’s economic growth may well be negated by the rising substance abuse especially in this part of the country. It is quite evident that the pattern of substance abuse tends to change over time which is an impediment in the formulation of effective strategies to tackle this issue. Aim: Purpose of the study was to ascertain the change in the pattern of drug abuse for two consecutive years in the out patient department (OPD) population. Method: The study population comprised of all the patients reporting for deaddiction to the psychiatry outpatient department over a period of twelve months for two consecutive years. All the patients were evaluated by the International Classification of Diseases; 10 criteria for substance abuse/dependence. Results: A considerably high prevalence of substance abuse was present in the Indian population. In general, there was an increase in prevalence from first to the second year, especially among the female population. Increase in prevalence of substance abuse appeared to be more prominent among the younger age group of both the sexes. A significant increase in intravenous drug abuse was observed. Peer pressure and parental imitation were the major factors fueling substance abuse. Precipitation or fear of withdrawal symptoms was the major factor preventing abstinence. Substance abuse had a significant effect on the health and interpersonal relations of these patients. Summary/Conclusion: Drug abuse and addiction are on the rise throughout India. Changing cultural values, increasing economic stress and dwindling supportive bonds appear to be leading to initiation of substance abuse. Need of the hour is to formulate a comprehensive strategy to bring about an overall reduction in the use of drugs.

Keywords: deaddiction, peer pressure, parental imitation, substance abuse/dependance

Procedia PDF Downloads 179

Authors: Dragan Zivotic, Mirjana Ilic, Aleksandra Perovic, Predrag Gavrilovic

Abstract:

As with the provision of other services, the service quality perception is one of the key factors that the modern manager must pay attention to. Countries in which the state regulation is in transition also have specific features in providing fitness services. Identification of the dimensions in which the most significant different service quality perception between different types of fitness centers, enables managers to profile the offer according to the wishes and expectations of users. The aim of the paper was the comparison of the quality of services perception in the field of fitness in Serbia between three categories of fitness centers: the privately owned centers, the publicly owned centers, and the Public-private partnership centers. For this research 350 respondents of both genders (174 men and 176 women) were interviewed, aged between 18 and 68 years, being beneficiaries of fitness services for at least 1 year. Administered questionnaire with 100 items provided information about the 15 basic areas in which they expressed the service quality perception in the gym. The core sample was composed of 212 service users in private fitness centers, 69 service users in public fitness centers and 69 service users in the public-private partnership. Sub-samples were equal in representation of women and men, as well as by age and length of use of fitness services. The obtained results were subject of univariate analysis with the Kruskal-Wallis non-parametric analysis of variance. Significant differences between the analyzed sub-samples were not found solely in the areas of rapid response and quality outcomes. In the multivariate model, the results were processed by backward stepwise discriminant analysis that extracted 3 areas that maximize the differences between sub-samples: material and technical basis, secondary facilities and coaches. By applying the classification function 93.87% of private centers services users, 62.32% of public centers services users and 85.51% of the public-private partnership centers users of services were correctly classified (total 86.00%). These results allow optimizing the allocation of the necessary resources in profiling offers of a fitness center in order to optimally adjust it to the user’s needs and expectations.

Keywords: fitness, quality perception, management, public ownership, private ownership, public-private partnership, discriminative analysis

Procedia PDF Downloads 262

Authors: Bukunola K. Oguntade, Gareth M. Watkins

Abstract:

The synthesis and characterization of metal-organic frameworks (MOFs) is an area of coordination chemistry which has grown rapidly in recent years. Worldwide there has been growing concerns about future energy supplies, and its environmental impacts. A good number of MOFs have been tested for the adsorption of small molecules in the vapour phase. An important issue for potential applications of MOFs for gas adsorption and storage materials is the stability of their structure upon sorption. Therefore, study on the thermal stability of MOFs upon adsorption is important. The incorporation of two or more transition metals in a coordination polymer is a current challenge for designed synthesis. This work focused on the synthesis, characterization and small molecule adsorption properties of three microporous (one zinc monometal and two bimetallics) complexes involving Cu(II), Zn(II) and 1,2,4,5-benzenetetracarboxylic acid using the ambient precipitation and solvothermal method. The complexes were characterized by elemental analysis, Infrared spectroscopy, Scanning Electron microscopy, Thermogravimetry analysis and X-ray Powder diffraction. The N2-adsorption Isotherm showed the complexes to be of TYPE III in reference to IUPAC classification, with very small pores only capable for small molecule sorption. All the synthesized compounds were observed to contain water as guest. Investigations of their inclusion properties for small molecules in the vapour phase showed water and methanol as the only possible inclusion candidates with 10.25H2O in the monometal complex [Zn4(H2B4C)2.5(OH)3(H2O)]·10H2O but not reusable after a complete structural collapse. The ambient precipitation bimetallic; [(CuZnB4C(H2O)2]·5H2O, was found to be reusable and recoverable from structure collapse after adsorption of 5.75H2O. In addition, Solvo-[CuZnB4C(H2O)2.5]·2H2O obtained from solvothermal method show two cycles of rehydration with 1.75H2O and 0.75MeOH inclusion while structure remains unaltered upon dehydration and adsorption.

Keywords: adsorption, characterization, copper, metal -organic frameworks, zinc

Procedia PDF Downloads 110

Authors: Monireh Ahmadi Bani, Adel Khorramrouz, Lalenoor Morvarid, Bagheri Mahtab

Abstract:

Background:- Foot disorders are common in musculoskeletal problems. Plantar pressure distribution measurement is one the most important part of foot disorders diagnosis for quantitative analysis. However, the association of plantar pressure and foot disorders is not clear. With the growth of dataset and machine learning methods, the relationship between foot disorders and plantar pressures can be detected. Significance of the study:- The purpose of this study was to predict the probability of common foot disorders based on peak plantar pressure distribution and center of pressure during walking. Methodologies:- 2323 participants were assessed in a foot therapy clinic between 2015 and 2021. Foot disorders were diagnosed by an experienced physician and then they were asked to walk on a force plate scanner. After the data preprocessing, due to the difference in walking time and foot size, we normalized the samples based on time and foot size. Some of force plate variables were selected as input to a deep neural network (DNN), and the probability of any each foot disorder was measured. In next step, we used support vector machine (SVM) and run dataset for each foot disorder (classification of yes or no). We compared DNN and SVM for foot disorders prediction based on plantar pressure distributions and center of pressure. Findings:- The results demonstrated that the accuracy of deep learning architecture is sufficient for most clinical and research applications in the study population. In addition, the SVM approach has more accuracy for predictions, enabling applications for foot disorders diagnosis. The detection accuracy was 71% by the deep learning algorithm and 78% by the SVM algorithm. Moreover, when we worked with peak plantar pressure distribution, it was more accurate than center of pressure dataset. Conclusion:- Both algorithms- deep learning and SVM will help therapist and patients to improve the data pool and enhance foot disorders prediction with less expense and error after removing some restrictions properly.

Keywords: deep neural network, foot disorder, plantar pressure, support vector machine

Procedia PDF Downloads 318

Authors: M. Eickermann, F. Ronellenfitsch, J. Junk

Abstract:

Oilseed rape (Brassica napus L.) is one of the most important crops throughout Europe, but pressure due to pest insects and pathogens can reduce yield amount substantially. Therefore, the usage of pesticide applications is outstanding in this crop. In addition, climate change effects can interact with phenology of the host plant and their pests and can apply additional pressure on the yield. Next to the pollen beetle, Meligethes aeneus L., the seed-damaging pest insects, cabbage seed weevil (Ceutorhynchus obstrictus Marsham) and the brassica pod midge (Dasineura brassicae Winn.) are of main economic impact to the yield. While females of C. obstrictus are infesting oilseed rape by depositing single eggs into young pods, the females of D. brassicae are using this local damage in the pod for their own oviposition, while depositing batches of 20-30 eggs. Without a former infestation by the cabbage seed weevil, a significant yield reduction by the brassica pod midge can be denied. Based on long-term, multisided field experiments, a comprehensive data-set on pest migration to crops of B. napus has been built up in the last ten years. Five observational test sides, situated in different climatic regions in Luxembourg were controlled between February until the end of May twice a week. Pest migration was recorded by using yellow water pan-traps. Caught insects were identified in the laboratory according to species specific identification keys. By a combination of pest observations and corresponding meteorological observations, the set-up of models to predict the migration periods of the seed-damaging pests was possible. This approach is the basis for a computer-based decision support tool, to assist the farmer in identifying the appropriate time point of pesticide application. In addition, the derived algorithms of that decision support tool can be combined with climate change projections in order to assess the future potential threat caused by the seed-damaging pest species. Regional climate change effects for Luxembourg have been intensively studied in recent years. Significant changes to wetter winters and drier summers, as well as a prolongation of the vegetation period mainly caused by higher spring temperature, have also been reported. We used the COSMO-CLM model to perform a time slice experiment for Luxembourg with a spatial resolution of 1.3 km. Three ten year time slices were calculated: The reference time span (1991-2000), the near (2041-2050) and the far future (2091-2100). Our results projected a significant shift of pest migration to an earlier onset of the year. In addition, a prolongation of the possible migration period could be observed. Because D. brassiace is depending on the former oviposition activity by C. obstrictus to infest its host plant successfully, the future dependencies of both pest species will be assessed. Based on this approach the future risk potential of both seed-damaging pests is calculated and the status as pest species is characterized.

Keywords: CORDEX projections, decision support tool, Brassica napus, pests

Procedia PDF Downloads 351

Authors: Roshanak Afrakhteh, Abdolrasoul Salman Mahini, Mahdi Motagh, Hamidreza Kamyab

Abstract:

Urban Heat Islands (UHIs) are distinctive urban areas characterized by densely populated central cores surrounded by less densely populated peripheral lands. These areas experience elevated temperatures, primarily due to impermeable surfaces and specific land use patterns. The consequences of these temperature variations are far-reaching, impacting the environment and society negatively, leading to increased energy consumption, air pollution, and public health concerns. This paper emphasizes the need for simplified approaches to comprehend UHI temperature dynamics and explains how urban development patterns contribute to land surface temperature variation. To illustrate this relationship, the study focuses on the Guilan Plain, utilizing techniques like principal component analysis and generalized additive models. The research centered on mapping land use and land surface temperature in the low-lying area of Guilan province. Satellite data from Landsat sensors for three different time periods (2002, 2012, and 2021) were employed. Using eCognition software, a spatial unit known as a "city block" was utilized through object-based analysis. The study also applied the normalized difference vegetation index (NDVI) method to estimate land surface radiance. Predictive variables for urban land surface temperature within residential city blocks were identified categorized as intrinsic (related to the block's structure) and neighboring (related to adjacent blocks) variables. Principal Component Analysis (PCA) was used to select significant variables, and a Generalized Additive Model (GAM) approach, implemented using R's mgcv package, modeled the relationship between urban land surface temperature and predictor variables.Notable findings included variations in urban temperature across different years attributed to environmental and climatic factors. Block size, shared boundary, mother polygon area, and perimeter-to-area ratio were identified as main variables for the generalized additive regression model. This model showed non-linear relationships, with block size, shared boundary, and mother polygon area positively correlated with temperature, while the perimeter-to-area ratio displayed a negative trend. The discussion highlights the challenges of predicting urban surface temperature and the significance of block size in determining urban temperature patterns. It also underscores the importance of spatial configuration and unit structure in shaping urban temperature patterns. In conclusion, this study contributes to the growing body of research on the connection between land use patterns and urban surface temperature. Block size, along with block dispersion and aggregation, emerged as key factors influencing urban surface temperature in residential areas. The proposed methodology enhances our understanding of parameter significance in shaping urban temperature patterns across various regions, particularly in Iran.

Keywords: urban heat island, land surface temperature, LST modeling, GAM, Gilan province

Procedia PDF Downloads 48

Authors: Rakesh Tiwary, D. M. Diwakar, Sandhya Mahapatro

Abstract:

Agro-forestry offers huge opportunities for diversification of agriculture in middle Gangetic Basin of India, particularly in the state of Bihar as the region is identified with traditional & stagnant agriculture, low productivity, high population pressure, rural poverty and lack of agro- industrial development. The region is endowed with favourable agro-climatic, soil & drainage conditions; interestingly, there has been an age old tradition of agro-forestry in the state. However, due to demographic pressures, declining land holdings and other socio- economic factors, agro forestry practices have declined in recent decades. The government of Bihar has initiated a special program for expansion of agro-forestry based on modern practices with an aim to raise income level of farmers, make available raw material for wood based industries and increase green cover in the state. The Agro-forestry Schemes – Poplar & Other Species are the key components of the program being implemented by Department of Environment & Forest, Govt. of Bihar. The paper is based on fieldwork based evaluation study on experiences of implementation of the agro-forestry schemes. Understanding adoption patterns, identification of key motives for practising agro-forestry, experiences of farmers well analysing the barriers in expansion constituted the major themes of the research study. This paper is based on primary as well as secondary data. The primary data consists of beneficiary household survey, Focus Group Discussions among beneficiary communities, dialogue and multi stakeholder meetings and field visit to the sites. The secondary data information was collected and analysed from official records, policy documents and reports. Primary data was collected from about 500 beneficiary households of Muzaffarpur & Saharsa- two populous, large and agriculture dominated districts of middle Gangetic basin of North Bihar. Survey also covers 100 households of non-beneficiaries. Probability Proportionate to Size method was used to determine the number of samples to be covered in different blocks of two districts. Qualitative tools were also implemented to have better insights about key research questions. Present paper discusses socio-economic background of farmers practising agro-forestry; the adoption patterns of agro- forestry (choice of plants, methods of plantation and others); and motivation behind adoption of agro-forestry and the comparative benefits of agro-forestry (vis-a-vis traditional agriculture). Experience of beneficiary farmers with agro-forestry based on government programs & promotional campaigns (in terms of awareness, ease of access, knowhow and others) have been covered in the paper. Different aspects of survival of plants have been closely examined. Non beneficiaries but potential adopters were also interviewed to understand barriers of adoption of agro- forestry. Paper provides policy recommendations and interventions required for effective expansion of the agro- forestry and realisation of its future prospects for agricultural diversification in the region.

Keywords: agro-forestry adoption patterns, farmers’ motivations & experiences, Indian middle Gangetic plains, strategies for expansion

Procedia PDF Downloads 181

Authors: Allioua Meryem

Abstract:

Similar to much of the developing world, Algeria is currently undergoing an epidemiological transition. While mal- and under-nutrition and infectious diseases used to be the main causes of poor health, today there is a higher proportion of chronic, non-communicable diseases (NCDs), including cardiovascular disease, diabetes mellitus, cancer, etc. According to estimates for Algeria from the World Health Organization (WHO), NCDs accounted for 63% of all deaths in 2010. The objective of this study was the assessment of eating habits and anthropometric characteristics in a group of youth aged 15 to 19 years in Tlemcen. This study was conducted on a total effective of 806 youth enrolled in a descriptive cross-sectional study; the classification of nutritional status has been established by international standards IOTF, youth were defined as obese if they had a BMI ≥ 95th percentile, and youth with 85th ≤ BMI ≤ 95th percentile were defined as overweight. Wc is classified by the criteria HD, Wc with moderate risk ≥ 90th percentile and Wc with high risk ≥ 95th percentile. The dietary assessment was based on a 24-hour dietary recall assisted by food records. USDA’S nutrient database for Nutrinux® program was used to analyze dietary intake. Nutrients adequacy ratio was calculated by dividing daily individual intake to dietary recommended intake DRI for each nutrient. 9% of the population was overweight, 3% was obese, 7.5% had abdominal obesity, foods eaten in moderation are chips, cookies, chocolate 1-3 times/day and increased consumption of fried foods in the week, almost half of youth consume sugary drinks more than 3 times per week, we observe a decreased intake of energy, protein (P < 0.001, P = 0.003), SFA (P = 0.018), the NAR of phosphorus, iron, magnesium, vitamin B6, vitamin E, folate, niacin, and thiamin reflecting less consumption of fruit, vegetables, milk, and milk products. Youth surveyed have eating habits at risk of developing obesity and chronic disease.

Keywords: food intake, health, anthropometric characteristics, Algeria

Procedia PDF Downloads 517

Authors: Venuka Kuruwita Arachchige Don, Mohamed Shaheen, Chris Goodier

Abstract:

Aerated autoclaved concrete (AAC) is known for its lightweight, easy handling, high thermal insulation, and extremely porous structure. Investigation of pore behavior in AAC is crucial for characterizing the material, standardizing design and production techniques, enhancing the mechanical, durability, and thermal performance, studying the effectiveness of protective measures, and analyzing the effects of weather conditions. The significant details of pores are complicated to observe with acknowledged accuracy. The High-resolution Field Emission Scanning Electron Microscope (FESEM) image analysis is a promising technique for investigating the pore behavior and density of AAC, which is adopted in this study. Mercury intrusion porosimeter and gas pycnometer were employed to characterize porosity distribution and density parameters. The analysis considered three different densities of AAC blocks and three layers in the altitude direction within each block. A set of understandings was presented to extract and analyze the details of pore shape, pore size, pore connectivity, and pore percentages from FESEM images of AAC. Average pore behavior outcomes per unit area were presented. Comparison of porosity distribution and density parameters revealed significant variations. FESEM imaging offered unparalleled insights into porosity behavior, surpassing the capabilities of other techniques. The analysis conducted from a multi-staged approach provides porosity percentage occupied by various pore categories, total porosity, variation of pore distribution compared to AAC densities and layers, number of two-dimensional and three-dimensional pores, variation of apparent and matrix densities concerning pore behaviors, variation of pore behavior with respect to aluminum content, and relationship among shape, diameter, connectivity, and percentage in each pore classification.

Keywords: autoclaved aerated concrete, density, imaging technique, microstructure, porosity behavior

Procedia PDF Downloads 28

Authors: Mariam Vardiashvili

Abstract:

The economic value of the asset impairment process is quite large. Impairment reflects the reduction of future economic benefits or service potentials itemized in the asset. The assets owned by public sector entities bring economic benefits or are used for delivery of the free-of-charge services. Consequently, they are classified as cash-generating and non-cash-generating assets. IPSAS 21 - Impairment of non-cash-generating assets, and IPSAS 26 - Impairment of cash-generating assets, have been designed considering this specificity.  When measuring impairment of assets, it is important to select the relevant methods. For measurement of the impaired Non-Cash-Generating Assets, IPSAS 21 recommends three methods: Depreciated Replacement Cost Approach, Restoration Cost Approach, and  Service Units Approach. Impairment of Value in Use of Cash-Generating Assets (according to IPSAS 26) is measured by discounted value of the money sources to be received in future. Value in use of the cash-generating asserts (as per IPSAS 26) is measured by the discounted value of the money sources to be received in the future. The article provides classification of the assets in the public sector  as non-cash-generating assets and cash-generating assets and, deals also with the factors which should be considered when evaluating  impairment of assets. An essence of impairment of the non-financial assets and the methods of measurement thereof evaluation are formulated according to IPSAS 21 and IPSAS 26. The main emphasis is put on different methods of measurement of the value in use of the impaired Cash-Generating Assets and Non-Cash-Generation Assets and the methods of their selection. The traditional and the expected cash flow approaches for calculation of the discounted value are reviewed. The article also discusses the issues of recognition of impairment loss and its reflection in the financial reporting. The article concludes that despite a functional purpose of the impaired asset, whichever method is used for measuring the asset, presentation of realistic information regarding the value of the assets should be ensured in the financial reporting. In the theoretical development of the issue, the methods of scientific abstraction, analysis and synthesis were used. The research was carried out with a systemic approach. The research process uses international standards of accounting, theoretical researches and publications of Georgian and foreign scientists.

Keywords: cash-generating assets, non-cash-generating assets, recoverable (usable restorative) value, value of use

Procedia PDF Downloads 114