Search results for: agricultural productivity

Authors: Chandranath Chatterjee, Amina Khatun, Bhabagrahi Sahoo

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With the changing climate, precipitation events are intensified in the tropical river basins. Since these river basins are significantly influenced by the monsoonal rainfall pattern, critical impacts are observed on the agricultural practices in the downstream river reaches. This study analyses the crop damage and associated flood risk in terms of net benefit in the paddy-dominated tropical Indian delta of the Mahanadi River. The Mahanadi River basin lies in eastern part of the Indian sub-continent and is greatly affected by the southwest monsoon rainfall extending from the month of June to September. This river delta is highly flood-prone and has suffered from recurring high floods, especially after the 2000s. In this study, the lumped conceptual model, Nedbør Afstrømnings Model (NAM) from the suite of MIKE models, is used for rainfall-runoff modeling. The NAM model is laterally integrated with the MIKE11-Hydrodynamic (HD) model to route the runoffs up to the head of the delta region. To obtain the precipitation-derived future projected discharges at the head of the delta, nine Global Climate Models (GCMs), namely, BCC-CSM1.1(m), GFDL-CM3, GFDL-ESM2G, HadGEM2-AO, IPSL-CM5A-LR, IPSL-CM5A-MR, MIROC5, MIROC-ESM-CHEM and NorESM1-M, available in the Coupled Model Intercomparison Project-Phase 5 (CMIP5) archive are considered. These nine GCMs are previously found to best-capture the Indian Summer Monsoon rainfall. Based on the performance of the nine GCMs in reproducing the historical discharge pattern, three GCMs (HadGEM2-AO, IPSL-CM5A-MR and MIROC-ESM-CHEM) are selected. A higher Taylor Skill Score is considered as the GCM selection criteria. Thereafter, the 10-year return period design flood is estimated using L-moments based flood frequency analysis for the historical and three future projected periods (2010-2039, 2040-2069 and 2070-2099) under Representative Concentration Pathways (RCP) 4.5 and 8.5. A non-dimensional hydrograph analysis is performed to obtain the hydrographs for the historical/projected 10-year return period design floods. These hydrographs are forced into the calibrated and validated coupled 1D-2D hydrodynamic model, MIKE FLOOD, to simulate the flood inundation in the delta region. Historical and projected flood risk is defined based on the information about the flood inundation simulated by the MIKE FLOOD model and the inundation depth-damage-duration relationship of a normal rice variety cultivated in the river delta. In general, flood risk is expected to increase in all the future projected time periods as compared to the historical episode. Further, in comparison to the 2010s (2010-2039), an increased flood risk in the 2040s (2040-2069) is shown by all the three selected GCMs. However, the flood risk then declines in the 2070s as we move towards the end of the century (2070-2099). The methodology adopted herein for flood risk assessment is one of its kind and may be implemented in any world-river basin. The results obtained from this study can help in future flood preparedness by implementing suitable flood adaptation strategies.

Keywords: flood frequency analysis, flood risk, global climate models (GCMs), paddy cultivation

Procedia PDF Downloads 52

Authors: Cynthia E. Nwobodo, A. E. Agwu

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The study was carried out in Benue State, Nigeria. Multi-stage sampling technique was used to select 120 respondents from two agricultural zones in the State. Data was collected using interview schedule. Descriptive statistics was used in data analysis. Findings showed that youth farmers in the area had positive attitude to climate change adaptation and mitigation as shown by their response to a set of positive and negative statement including: the youth are very important stakeholders in climate change issues (M= 2.91), youths should be encouraged to be climate change conscious (2.90), everybody should be involved in planting trees not just the government (M= 2.89), I will be glad to participate in climate change seminars (M= 2.89) among others. Findings on information seeking behavior indicate that majority (80.8 %) of the respondents sought climate change information from radio at an average of 19.78 times per month, 53.3 % sought from friends and neighbours at an average of 12.55 times per month and 42.5 % sought from family members at an average of 12.55 times per month among others. It was recommended that Youth farmers should be made important stakeholders in climate change policies and programmes since they have a very positive attitude to climate change adaptation and mitigation.

Keywords: adaptation, mitigation, attitude, climate change, youth farmers

Procedia PDF Downloads 624

Authors: N. Viji, K. Siddeswaran

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Field experiment was conducted at Eastern Block farm, Department of Farm Management, Tamil Nadu Agricultural University, Coimbatore during winter season of 2011-2012 to evaluate potassium salt based glyphosate (Roundup Crop Shield 460 SL) with and without intercultural operations on seed cotton yield and weed nutrient removal in irrigated cotton. The experiment was laid out in Randomized Block Design with treatments replicated thrice. The treatments consisted of POE glyphosate (Roundup Crop Shield 460 SL) at 1350 (T1), 1800 (T2), 2250 (T3) g a.e. ha-1, 1800 g a.e. ha-1 + IC (T4), PE pendimethalin at 750 g a.i. ha-1 + IC (T5), HW at 35 and 70 DAS + IC (T6), HWW at 35 and 70 DAS + IC (T7), PWW at 35 and 70 DAS + IC (T8), HW at 25 and 45 DAS (T9) and Unweeded control (T10). Among the weed management methods, decreased nutrient removal by weeds were observed with POE glyphosate at 1800 g a.e. ha-1 + IC which was comparable with PE pendimethalin at 750 g a.i. ha-1 + IC. Higher seed cotton yield was obtained with POE glyphosate at 1800 g a.e. ha-1 at 35 and 70 DAS with + IC at 45 and 55 DAS which was comparable with PE pendimethalin at 750 g a.i. ha-1 + IC at 45 and 55 DAS. Comparing treatments without intercultural operation, intercultural operation carried out treatments performed better and recorded more seed cotton yield.

Keywords: cotton, weed, glyphosate, nutrient

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Authors: Sufian Abdo Jilo

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Veterinary services conserve and maintain animal life and improve the living conditions of human beings through improving rural livelihoods and feeding; veterinary services also address global health crises by preventing risks such as emerging pandemic diseases, antimicrobial resistance, contamination of foods, and environmental health problems at their origin. The purpose of this policy brief is to analyze the way veterinary organizations provide services and to propose an optimal organization for veterinary services in developing countries. The current situation of veterinary institutions in developing countries can't counter the challenge related to animal health and productivity. As a result, reorganization, amalgamation, merging, and consolidation of veterinary health services (veterinary clinics, slaughterhouses, quarantine, and veterinary markets) together with the construction of closer veterinary service facilities and the construction of common areas will help institutions to strengthen cooperation among different veterinarians, which is the first steps for the implementation of a One Health platform and multidisciplinary activities. The improvement and reorganization of the veterinary services institutions will also help the veterinary clinics easily obtain various medical chemicals such as blood and rumen from abattoirs, enhance the surveillance of livestock diseases, enable the community to buy healthy animals from the animal market, and help to reduce economic waste. The services can be performed by a small number of veterinarians through a model of specific areas common to all veterinary services. This model improves the skills and knowledge of veterinarians in all aspects of veterinary medicine and saves students and researchers time. Communities or customers can save time by getting all veterinary services at once. It saves the budget on purchasing medical equipment and medicines at each location and avoids expiration dates on medicines. This model is the latest solution to the global health crisis and should be implemented in the near future to combat the emergence and reemergence of new pathogenic microorganisms.

Keywords: abattoir, developing countries, reform, service, veterinary

Procedia PDF Downloads 57

Authors: L. Meksem Amara, M. Ferfar, N. Meksem, M. R. Djebar

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The wheat is the cereal the most consumed in the world. In Algeria, the production of this cereal covers only 20 in 25 % of the needs for the country, the rest being imported. To improve the efficiency and the productivity of the durum wheat, the farmers turn to the use of pesticides: weed-killers, fungicides and insecticides. However this use often entrains losses of products more at least important contaminating the environment and all the food chain. Weed-killers are substances developed to control or destroy plants considered unwanted. That they are natural or produced by the human being (molecule of synthesis), the absorption and the metabolization of weed-killers by plants cause the death of these plants. In this work, we set as goal the evaluation of the effect of a weed-killer sulfonylurea, the CossackOD with various concentrations (0, 2, 4 and 9 µg) on variety of Triticum durum: Cirta. We evaluated the plant growth by measuring the leaves and root length, compared with the witness as well as the content of proline and analyze the level of one of the antioxydative enzymes: catalase, after 14 days of treatment. Sulfonylurea is foliar and root weed-killers inhibiting the acetolactate synthase: a vegetable enzyme essential to the development of the plant. This inhibition causes the ruling of the growth then the death. The obtained results show a diminution of the average length of leaves and roots this can be explained by the fact that the ALS inhibitors are more active in the young and increasing regions of the plant, what inhibits the cellular division and talks a limitation of the foliar and root’s growth. We also recorded a highly significant increase in the proline levels and a stimulation of the catalase activity. As a response to increasing the herbicide concentrations a particular increases in antioxidative mechanisms in wheat cultivar Cirta suggest that the high sensitivity of Cirta to this sulfonylurea herbicide is related to the enhanced production and oxidative damage of reactive oxygen species.

Keywords: sulfonylurea, triticum durum, oxydative stress, toxicity

Procedia PDF Downloads 388

Authors: Elaine Wong

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This research protocol aims to explore and justify the need for nutrition and physical activity intervention to improve health outcomes among SME (Small Medium Enterprise) employees. It was found that the worksite is an ideal and convenient setting for employees to take charge of their health thru active participation in health programmes since they spent a great deal of time at their workplace. This study will examine the impact of both general or/and targeted health interventions in both SME and non-SME companies utilizing the Workplace Health Promotion (WHP) grant over a 12 months period and assessed the improvement in chronic health disease outcomes in Singapore. Random sampling of both non-SME and SME companies will be conducted to undergo health intervention and statistical packages such as Statistical Package for Social Science (SPSS) 25 will be used to examine the impact of both general and targeted interventions on employees who participate and those who do not participate in the intervention and their effects on blood glucose (BG), blood lipid, blood pressure (BP), body mass index (BMI), and body fat percentage. Using focus groups and interviews, the data results will be transcribed to investigate enablers and barriers to workplace health intervention revealed by employees and WHP coordinators that could explain the variation in the health screening results across the organisations. Dietary habits and physical activity levels of the employees participating and not participating in the intervention will be collected before and after intervention to assess any changes in their lifestyle practices. It makes economic sense to study the impact of these interventions on health screening outcomes across various organizations that are existing grant recipients to justify the sustainability of these programmes by the local government. Healthcare policy makers and employers can then tailor appropriate and relevant programmes to manage these escalating chronic health disease conditions which is integral to the competitiveness and productivity of the nation’s workforce.

Keywords: chronic diseases, health screening, nutrition and fitness intervention , workplace health

Procedia PDF Downloads 134

Authors: Sosina Adedayo O., Babyemi Olaniyi J.

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The location, population, and distribution pattern of sheep are severe challenges to agribusiness investment and policy formulation in the livestock industry. There is a significant disconnect between farmers' needs and the policy framework towards ameliorating the sheep production constraints. Information on the population, production, and distribution pattern of sheep remains very scanty. A multi-stage sampling technique was used to elicit information from 180 purposively selected respondents from the study area comprised of Oluyole, Ona-ara, Akinyele, Egbeda, Ido and Ibarapa East LGA. The Global Positioning Systems (GPS) of the farmers' location (distribution), and average sheep herd size (Total Livestock Unit, TLU) (population) were recorded, taking the longitude and latitude of the locations in question. The recorded GPS data of the study area were transferred into the ARC-GIS. The ARC-GIS software processed the data using the ARC-GIS model 10.0. Sheep production and distribution (TLU) ranged from 4.1 (Oluyole) to 25.0 (Ibarapa East), with Oluyole, Akinyele, Ona-ara and Egbeda having TLU of 5, 7, 8 and 20, respectively. The herd sizes were classified as less than 8 (smallholders), 9-25 (medium), 26-50 (large), and above 50 (commercial). The majority (45%) of farmers were smallholders. The FR CP (%) ranged from 5.81±0.26 (cassava leaf) to 24.91±0.91 (Amaranthus spinosus), NDF (%) ranged from 22.38±4.43 (Amaranthus spinosus) to 67.96 ± 2.58 (Althemanthe dedentata) while ME ranged from 7.88±0.24 (Althemanthe dedentata) to 10.68±0.18 (cassava leaf). The smallholders’ sheep farmers were the majority, evenly distributed across rural areas due to the availability of abundant feed resources (crop residues, tree crops, shrubs, natural pastures, and feed ingredients) coupled with a large expanse of land in the study area. Most feed resources available were below sheep protein requirement level, hence supplementation is necessary for productivity. Bio-informatics can provide relevant information for sheep production for policy framework and intervention strategies.

Keywords: sheep enterprise, agribusiness investment, policy, bio-informatics, ecological zone

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Authors: Panpan Xu, Qiying Zhang, Hui Qian

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Groundwater is main source of water supply in the Guanzhong Basin, China. To investigate the quality of groundwater for agricultural purposes in Jiaokou Irrigation District located in the east of the Guanzhong Basin, 141 groundwater samples were collected for analysis of major ions (K⁺, Na⁺, Mg²⁺, Ca²⁺, SO₄^2-, Cl^-, HCO₃^-, and CO₃^2-), pH, and total dissolved solids (TDS). Sodium percentage (Na%), residual sodium carbonate (RSC), magnesium hazard (MH), and potential salinity (PS) were applied for irrigation water quality assessment. In addition, multivariate statistical techniques were used to identify the underlying hydrogeochemical processes. Results show that the content of TDS mainly depends on Cl^-, Na⁺, Mg²⁺, and SO₄^2-, and the HCO₃^- content is generally high except for the eastern sand area. These are responsible for complex hydrogeochemical processes, such as dissolution of carbonate minerals (dolomite and calcite), gypsum, halite, and silicate minerals, the cation exchange, as well as evaporation and concentration. The average evaluation levels of Na%, RSC, MH, and PS for irrigation water quality are doubtful, good, unsuitable, and injurious to unsatisfactory, respectively. Therefore, it is necessary for decision makers to comprehensively consider the indicators and thus reasonably evaluate the irrigation water quality.

Keywords: irrigation water quality, multivariate statistical analysis, groundwater, hydrogeochemical process

Procedia PDF Downloads 124

Authors: Abdullah Al. Morshed, Mohammad Nahid Mia

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Introduction: Food security refers to the availability of food and a person’s access to it. It is a complex sustainable development issue, which is closely related to under-nutrition. Food security, in turn, can widely affect the living standard, and is rooted in poverty and leads to poor health, low productivity, low income, food shortage, and hunger. The study's aim was to identify the most vulnerable women who are in insecure positions. Method: 17,842 married women were selected for analysis from the Bangladesh Demographic and Health Survey 2011. Food security defined as dichotomous variables of skipped meals and eaten less food at least once in the last year. The outcome variables were cross-tabulated with women's socio-demographic characteristics and chi2 test was applied to see the significance. Logistic regression models were applied to identify the most vulnerable groups in terms of food security. Result: Only 18.5% of women said that they ever had to skip meals in the last year. 45.7% women from low socioeconomic status had skip meal for at least once whereas only 3.6% were from women with highest socioeconomic status. Women meal skipping was ranged from 1.4% to 34.2% by their educational status. 22% of women were eaten less food during the last year. The rate was higher among the poorest (51.6%), illiterate (39.9%) and household have no electricity connection (38.1) in compared with richest (4.4%), higher educated (2.0%), and household has electricity connection (14.0%). The logistic regression analysis indicated that household socioeconomic status, and women education show strong gradients to skip meals. Poorest have had higher odds (20.9) than richest and illiterate women had 7.7 higher odds than higher educated. In terms of religion, Christianity was 2.3 times more likely to skip their meals than Islam. On the other hand, a similar trend was observed in our other outcome variable eat less food. Conclusion: In this study we able to identify women with lower economics status and women with no education were mostly suffered group from starvation.

Keywords: food security, hunger, under-nutrition, women

Procedia PDF Downloads 358

Authors: Adel A. Ghobbar

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The airline industry is continuously challenging how to safely increase the service life of the aircraft with limited maintenance budgets. Operators are looking for the most qualified maintenance providers of aircraft components, offering the finest customer service. Component owner and maintenance provider is offering an Abacus agreement (Aircraft Component Leasing) to increase the efficiency and productivity of the customer service. To increase the customer service, the current focus on No Fault Found (NFF) units must change into the focus on Early Failure (EF) units. Since the effect of EF units has a significant impact on customer satisfaction, this needs to increase the reliability of EF units at minimal cost, which leads to the goal of this paper. By identifying the reliability of early failure (EF) units with regards to No Fault Found (NFF) units, in particular, the root cause analysis with an integrated cost analysis of EF units with the use of a failure mode analysis tool and a cost model, there will be a set of EF maintenance improvements. The data used for the investigation of the EF units will be obtained from the Pentagon system, an Enterprise Resource Planning (ERP) system used by Fokker Services. The Pentagon system monitors components, which needs to be repaired from Fokker aircraft owners, Abacus exchange pool, and commercial customers. The data will be selected on several criteria’s: time span, failure rate, and cost driver. When the selected data has been acquired, the failure mode and root cause analysis of EF units are initiated. The failure analysis approach tool was implemented, resulting in the proposed failure solution of EF. This will lead to specific EF maintenance improvements, which can be set-up to decrease the EF units and, as a result of this, increasing the reliability. The investigated EFs, between the time period over ten years, showed to have a significant reliability impact of 32% on the total of 23339 unscheduled failures. Since the EFs encloses almost one-third of the entire population.

Keywords: supportability, no fault found, FMEA, early failure, availability, operational reliability, predictive model

Procedia PDF Downloads 105

Authors: Hossein Asgarzadeh, Ayoub Osmani, Farrokh Asadzadeh, Mohammad Reza Mosaddeghi

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This study was conducted to evaluate the topsoil and subsoil physical quality using relative bulk density (RBD) in Urmia plain in Iran. Undisturbed samples were collected from two layers (topsoil and subsoil) of thirty agricultural soils. Categories of 0.72 ≥ RBD (low degree of compactness), 0.82 > RBD > 0.72 (moderate/optimum degree of compactness), and RBD ≥ 0.82 (high degree of compactness) were used to evaluate soil physical quality (SPQ). Two topsoils had a low degree of compactness, fourteen topsoils had an optimum degree of compactness, and the rest (i.e., fourteen topsoils) had a high degree of compactness. Only one subsoil had an optimum degree of compactness, and twenty-eight subsoils (i.e., 93%) had a high degree of compactness, indicating poor SPQ of the subsoil layer in the studied region. It seems that conventional tillage in the past decades destroyed the pore system in the majority of studied subsoils. The high degree of compactness would reduce soil aeration and increase soil penetration resistance which could restrict root and plant growth. Conversely, a low degree of soil compactness is expected to reduce the root-soil contact.

Keywords: compactness, relative bulk density, soil physical quality

Procedia PDF Downloads 95

Authors: Sinan Alsaadi, Mustafa Merdan

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Communication and access systems can be made with many methods in today’s world. These systems are such standards as Wifi, Wimax, Bluetooth, GPS and GPRS. Devices which use these standards also use system resources excessively in direct proportion to their transmission speed. However, large-scale data communication is not always needed. In such cases, a technology which will use system resources as little as possible and support smart network topologies has been needed in order to enable the transmissions of such small packet data and provide the control for this kind of devices. IEEE issued 802.15.4 standard upon this necessity and enabled the production of Zigbee protocol which takes these standards as its basis and devices which support this protocol. In our project, this communication protocol was preferred. The aim of this study is to provide the immediate data transmission of our robot from the field within the scope of the project. In addition, making the communication with the robot through Zigbee Protocol has also been aimed. While sitting on the computer, obtaining the desired data from the region where the robot is located has been taken as the basis. Arduino Uno R3 microcontroller which provides the control mechanism, 1298 shield as the motor driver.

Keywords: ZigBee, wireless network, remote monitoring, smart home, agricultural industry

Procedia PDF Downloads 259

Authors: Richard Ren

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Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 100

Authors: Sahar Fahmy Mehanna

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Wild fisheries and aquaculture offer excellent opportunities to decrease hunger and improve nutrition, relieve poverty, create economic growth and guarantee healthier use of natural resources. Employment in fisheries and aquaculture has grown continuously quicker than in the agriculture sector, providing up to 55 million jobs worldwide. Fisheries and aquaculture supplied Egypt with 2.1 million tons of fish in 2021, mostly used as food for people. Fish production in Egypt has grown dramatically in the last three decades, where fish production increased from about 346 thousand tons in 1990 to up to 2.1 million tons in 2021. In contrast to natural resources, which increased by only 30% in the period from 1990 to 2021, aquaculture production increased by 2502% during the same period. The majority of wild fisheries production in Egypt arises from coastal areas, where pollution is one of the main challenges severely affected both the productivity and quality of fish stocks. Our marine resources are at the risk of irreversible loss to habitats, ecological functions, and biodiversity because of overfishing, pollution, destructive fishing methods, climatic changes, unsustainable coastal area development and the competing demands from different industrial uses and human activities. Illegal, Unreported and Unregulated (IUU) Fishing continues to be a big challenge to achieve sustainable fisheries. Furthermore, poor governance, management and practices are a further challenge. Reducing overfishing, stimulating responsible and sustainable fisheries management, applying aquaculture new and friendly practices and conserving the marine environment health are among the government’s best opportunities to provide highly nutritious food to the increasing population in Egypt. The present presentation will discuss the fishery regulations in the Egyptian marine fisheries that taken to maintain, protect and promote the different Egyptian marine environments and to what extent these regulations were effective.

Keywords: egypt, marine fisheries, fishery regulations, fisheries management, Marine ecosystem conservation

Procedia PDF Downloads 56

Authors: Priyanka Dargode, Suhas Gore, Manju Sharma, Arvind Lali

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Anaerobic digestion has been widely used for production of methane from different biowastes. However, the complexity of microbial communities involved in the process is poorly understood. The performance of biogas production process concerning the process productivity is closely coupled to its microbial community structure and syntrophic interactions amongst the community members. The present study aims at understanding taxonomic variations occurring in any starter inoculum when acclimatised to different lignocellulosic biomass (LBM) feedstocks relating to time of digestion. The work underlines use of high throughput Next Generation Sequencing (NGS) for validating the changes in taxonomic patterns of microbial communities. Biomethane Potential (BMP) batches were set up with different pretreated and non-pretreated LBM residues using the same microbial consortium and samples were withdrawn for studying the changes in microbial community in terms of its structure and predominance with respect to changes in metabolic profile of the process. DNA of samples withdrawn at different time intervals with reference to performance changes of the digestion process, was extracted followed by its 16S rRNA amplicon sequencing analysis using Illumina Platform. Biomethane potential and substrate consumption was monitored using Gas Chromatography(GC) and reduction in COD (Chemical Oxygen Demand) respectively. Taxonomic analysis by QIIME server data revealed that microbial community structure changes with different substrates as well as at different time intervals. It was observed that biomethane potential of each substrate was relatively similar but, the time required for substrate utilization and its conversion to biomethane was different for different substrates. This could be attributed to the nature of substrate and consequently the discrepancy between the dominance of microbial communities with regards to different substrate and at different phases of anaerobic digestion process. Knowledge of microbial communities involved would allow a rational substrate specific consortium design which will help to reduce consortium adaptation period and enhance the substrate utilisation resulting in improved efficacy of biogas process.

Keywords: amplicon sequencing, biomethane potential, community predominance, taxonomic analysis

Procedia PDF Downloads 505

Authors: Monthana Weerawatanakorn, Hajime Tamaki, Yonathan Asikin, Koji Wada, Makoto Takahashi, Chi-Tang Ho, Min-Hsiung Pan

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Rice bran and sugarcane are significant sources of wax containing policosanol (PC), the cholesterol-lowering nutraceutical available in the market. The processing of rice bran oil causes the loss of PC content into various waste products. Therefore, we hypothesise that defatted rice bran (DRB) as agricultural waste product and rice bran oil (RBO) retain a varying but significant amount of PC wax. Non-centrifugal cane sugar (NCS) or cane brown sugar has been consumed worldwide and possesses various health benefits. Since PC wax is mainly in the outer layer rinds of cane, PC contents of the granulated sugar are reduced due to the peeling step. The study aimed to increase PC contents of the granular brown sugar by adding wax extracted from DRB and RBO and to investigate the toxicity of the developed products. The results showed that the total PC contents including long chain aldehyde of products were increased to the maximum level of 147.97 mg/100 g and 40.14 mg/100 g for extracted wax and rice bran oil addition, respectively. PC content of RBO was found to be 96.93 mg/100 g. DRB is promising source of policosanol (6,044.7 mg/100 g). The 28-day toxicity evaluations of the developed sugar revealed no adverse effects on the liver, spleen or kidney.

Keywords: enrichment, sugarcane, policosanol, defatted rice bran, wax

Procedia PDF Downloads 331

Authors: Beatrice Fenu, Francesco Niosi, Giovanni Bracco, Giuliana Mattiazzo

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In recent years, Europe has seen a great development of renewable energy, in a perspective of reducing polluting emissions and transitioning to cleaner forms of energy, as established by the European Green New Deal. Wind energy has come to cover almost 15% of European electricity needs andis constantly growing. In particular, far-offshore wind turbines are attractive from the point of view of exploiting high-speed winds and high wind availability. Considering offshore wind turbine siting that combines the resources analysis, the bathymetry, environmental regulations, and maritime traffic and considering the waves influence in the stability of the platform, the hydrodynamic characteristics of the platform become fundamental for the evaluation of the performances of the turbine, especially for the pitch motion. Many platform's geometries have been studied and used in the last few years. Their concept is based upon different considerations as hydrostatic stability, material, cost and mooring system. A new method to reach a high-performances substructure for different kinds of wind turbines is proposed. The system that considers substructure, mooring, and wind turbine is implemented in Orcaflex, and the simulations are performed considering several sea states and wind speeds. An external dynamic library is implemented for the turbine control system. The study shows the comparison among different substructures and the new concepts developed. In order to validate the model, CFD simulations will be performed by mean of STAR CCM+, and a comparison between rigid and elastic body for what concerns blades and tower will be carried out. A global model will be built to predict the productivity of the floating turbine according to siting, resources, substructure, and mooring. The Levelized Cost of Electricity (LCOE) of the system is estimated, giving a complete overview about the advantages of floating offshore wind turbine plants. Different case studies will be presented.

Keywords: aero-hydrodynamic model, computational fluid dynamics, floating offshore wind, siting, verification, and validation

Procedia PDF Downloads 192

Authors: Kadio Valere R. Angaman, Birahim Bouna Niang

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Land degradation is a serious problem in developing countries, including Cote d’Ivoire, which has its economy focused on agriculture. It occurs in all kinds of ecosystems over the world. However, the drivers of land degradation vary from one region to another and from one ecosystem to another. Thus, identifying these drivers is an essential prerequisite to developing and implementing appropriate policies to reverse the trend of land degradation in the country, especially in the trays ecosystem. Using the binary logistic model with primary data obtained through 780 farmers surveyed, we analyze and identify the drivers of land degradation in the trays ecosystem. The descriptive statistics show that 52% of farmers interviewed have stated facing land degradation in their farmland. This high rate shows the extent of land degradation in this ecosystem. Also, the results obtained from the binary logit regression reveal that land degradation is significantly influenced by a set of variables such as sex, education, slope, erosion, pesticide, agricultural activity, deforestation, and temperature. The drivers identified are mostly local; as a result, the government must implement some policies and strategies that facilitate and incentive the adoption of sustainable land management practices by farmers to reverse the negative trend of land degradation.

Keywords: drivers, land degradation, trays ecosystem, sustainable land management

Procedia PDF Downloads 114

Authors: Metkel Gebremedhin, Biruk Kebede, Guash Abay

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Job satisfaction largely determines the productivity and efficiency of human resources for health. There is scanty evidence on factors influencing the job satisfaction of health extension professionals (HEPs) in Addis Ababa. The objective of this study was to determine the level of and factors influencing job satisfaction among extension health workers in Addis Ababa city. This was a cross-sectional study conducted in Addis Ababa, Ethiopia. Among all public health centers found in the Addis Ababa city administration health bureau that would be included in the study, a multistage sampling technique was employed. Then we selected the study health centers randomly and urban health extension professionals from the selected health centers. In-depth interview data collection methods were carried out for a comprehensive understanding of factors affecting job satisfaction among Health extension professionals (HEPs) in Addis Ababa. HEPs working in Addis Ababa areas are the primary study population. Multivariate logistic regression with 95% CI at P ≤ 0.05 was used to assess associated factors to job satisfaction. The overall satisfaction rate was 10.7% only, while 89.3%% were dissatisfied with their jobs. The findings revealed that variables such as marital status, staff relations, community support, supervision, and rewards have a significant influence on the level of job satisfaction. For those who were not satisfied, the working environment, job description, low salary, poor leadership and training opportunities were the major causes. Other factors influencing the level of satisfaction were lack of medical equipment, lack of transport facilities, lack of training opportunities, and poor support from woreda experts. Our study documented a very low level of overall satisfaction among health extension professionals in Addis Ababa city public health centers. Considering the factors responsible for this state of affairs, urgent and concrete strategies must be developed to address the concerns of extension health professionals as they represent a sensitive domain of the health system of Addis Ababa city. Improving the overall work environment, review of job descriptions and better salaries might bring about a positive change.

Keywords: job satisfaction, extension health professionals, Addis Ababa

Procedia PDF Downloads 57

Authors: Waleed S. Alwaneen

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In many countries, cow dung is used as farm manure and for biogas production. Several bacterial strains associated with cow dung such as Campylobacter, Salmonella sp. and Escherichia coli cause serious human diseases. The objective of the present study was to investigate the use of insect larvae including fruit beetle, waxworms and tiger worms to improve the breakdown of agricultural wastes and reduce their pathogen loads. Fresh cow faeces were collected from a cattle farm and distributed into plastic boxes (100 g/box). Each box was provided with 10 larvae of fruit beetle, Waxworms and Tiger worms, respectively. There were 3 replicates in each treatment including the control. Bacteria were isolated weekly from both control and cow faeces to which larvae were added to determine the bacterial populations. Results revealed that the bacterial load was higher in the cow faeces treated with fruit beetles than in the control, while the bacterial load was lower in the cow faeces treated with waxworms and tiger worms than in the control. The activities of the fruit beetle larvae led to the cow faeces being liquefied which provided a more conducive growing media for bacteria. Therefore, higher bacterial load in the cow faeces treated with fruit beetle might be attributed to the liquefaction of cow faeces.

Keywords: fruit beetle, waxworms, tiger worms, waste conditioning, composting

Procedia PDF Downloads 233

Authors: Jayanta Kumar Ghosh, Swastik Sunil Goriwale, Himangshu Sarkar

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Groundwater is one of the most valuable natural resources that society consumes for its domestic, industrial, and agricultural water supply. Its bulk and indiscriminate consumption affects the groundwater resource. Often, it has been found that the groundwater recharge rate is much lower than its demand. Thus, to maintain water and food security, it is necessary to monitor and management of groundwater storage. However, it is challenging to estimate groundwater storage (GWS) by making use of existing hydrological models. To overcome the difficulties, machine learning (ML) models are being introduced for the evaluation of groundwater level (GWL). Thus, the objective of this research work is to develop an ML-based model for the prediction of GWL. This objective has been realized through the development of an artificial neural network (ANN) model based on hydro-gravimetry. The model has been developed using training samples from field observations spread over 8 months. The developed model has been tested for the prediction of GWL in an observation well. The root means square error (RMSE) for the test samples has been found to be 0.390 meters. Thus, it can be concluded that the hydro-gravimetric-based ANN model can be used for the prediction of GWL. However, to improve the accuracy, more hydro-gravimetric parameter/s may be considered and tested in future.

Keywords: machine learning, hydro-gravimetry, ground water level, predictive model

Procedia PDF Downloads 107

Authors: Gholba Niranjan Dilip, Anil Kumar

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Conduct of accurate reliable mapping of oil palm plantations and census of individual palm trees is a huge challenge. This study addresses this challenge and developed an optimized solution implemented deep learning techniques on remote sensing data. The oil palm is a very important tropical crop. To improve its productivity and land management, it is imperative to have accurate census over large areas. Since, manual census is costly and prone to approximations, a methodology for automated census using panchromatic images from Cartosat-2, SkySat and World View-3 satellites is demonstrated. It is selected two different study sites in Indonesia. The customized set of training data and ground-truth data are created for this study from Cartosat-2 images. The pre-trained model of Single Shot MultiBox Detector (SSD) Lite MobileNet V2 Convolutional Neural Network (CNN) from the TensorFlow Object Detection API is subjected to transfer learning on this customized dataset. The SSD model is able to generate the bounding boxes for each oil palm and also do the counting of palms with good accuracy on the panchromatic images. The detection yielded an F-Score of 83.16 % on seven different images. The detections are buffered and dissolved to generate polygons demarcating the boundaries of the oil palm plantations. This provided the area under the plantations and also gave maps of their location, thereby completing the automated census, with a fairly high accuracy (≈100%). The trained CNN was found competent enough to detect oil palm crowns from images obtained from multiple satellite sensors and of varying temporal vintage. It helped to estimate the increase in oil palm plantations from 2014 to 2021 in the study area. The study proved that high-resolution panchromatic satellite image can successfully be used to undertake census of oil palm plantations using CNNs.

Keywords: object detection, oil palm tree census, panchromatic images, single shot multibox detector

Procedia PDF Downloads 146

Authors: N. V. V. S. D. Prasad

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Field experiments were conducted at Regional Agricultural Research Station, Lam, Guntur, Andhra Pradesh, India for two seasons during 2011-13 to evaluate the efficacy of flupyradifurone SL 200 a new class of insecticide in butenolide group against leaf hoppers, aphids and whitefly in Cotton. The test insecticide flupyradifurone 200 was evaluated at three doses @ 150, 200 and 250 g ai/ha ha along with imidacloprid 200 SL @ 20g ai/ha, acetamiprid 20 SP @ 20g ai/ha, thiamethoxam 25 WG @ 25g ai/ha and monocrotophos 36 SL @ 360 g ai/ha as standards. Flupyradifurone SL 200 even at lower dose of 150g ai/ha exhibited superior efficacy against cotton leafhopper, Amrasca devastans than the neonicotinoids which are widely used for control of sucking pests in cotton. Against cotton aphids, Aphis gossypii. Flupyradifurone SL 200 @ 200 and 250 g ai/ha ha was proved to be effective and the lower dose @ 150g ai/ha performed better than some of the neonicotinoids. The effect of flupyradifurone SL 200 on cotton against whitefly, Bemisia tabaci was evident at higher doses of 200 and 250 g ai/ha and superior to all standard treatments, however, the lower dose is at par with neonicotinoids. The seed cotton yield of flupyradifurone 200 SL at all the doses tested was superior than imidacloprid 200 SL @ 20g ai/ha and acetamiprid 20 SP @ 20g ai/ha. There is no significant difference among the insecticidal treatments with regards to natural enemies. The results clearly suggest that flupyradifurone is a new tool to combat sucking pest problems in cotton and can well fit in IRM strategies in light of wide spread insecticide resistance in cotton sucking pests.

Keywords: cotton, flupyradifurone, neonicotinoids, sucking pests

Procedia PDF Downloads 168

Authors: Abdelmoniem A. Attaelmanan, Ahmed A. H. Siddig

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This study was conducted in light of continual global climate changes that projected increasing aridity, changes in soil fertility, and pollution. Plant growth and development largely depend on the combination of availing water and nutrients in the soil. Changes in the climate and atmospheric chemistry can cause serious effects on these growth factors. Plant carbon (C), nitrogen (N), and hydrogen (H) play a fundamental role in the maintenance of ecosystem structure and function. Hashab (Acacia senegal), which produces gum Arabic, supports dryland ecosystems in tropical zones by its potentiality to restore degraded soils; hence it is ecologically and economically important for the dry areas of sub-Saharan Africa. The study aims at investigating the effects of water stress (simulated drought) and poor soil type on Acacia senegal C, N, and H contents. Seven days old seedlings were assigned to the treatments in Split- plot design for four weeks. The main plot is irrigation interval (well-watered and water-stressed), and the subplot is soil types (silt and sand soils). Seedling's C%, N%, and H% were measured using CHNS-O Analyzer and applying Standard Test Method. Irrigation intervals and soil types had no effects on seedlings and leaves C%, N%, and H%, irrigation interval had affected stem C and H%, both irrigation intervals and soil types had affected root N% and interaction effect of water and soil was found on leaves and root's N%. Synthesis application of well-watered irrigation with soil that is rich in N and other nutrients would result in the greatest seedling C, N, and H content which will enhance growth and biomass accumulation and can play a crucial role in ecosystem productivity and services in the dryland regions.

Keywords: Acacia senegal, Africa, climate change, drylands, nutrients biomass, Sub-Saharan, Sudan

Procedia PDF Downloads 94

Authors: Rosaria Tizzani, Tomas Morosinotto, Fabrizio Bezzo, Eleonora Sforza

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Red microalga Porphyridium marinum CCAP 13807/10 has the potential to produce a broad range of commercially valuable chemicals such as PhycoErytrin (PE) and sulphated ExoPolySaccharides (EPS). Multiple abiotic factors influence the growth of Porphyridium sp., e.g. the wavelength of the light source and different cultivation strategies (one or two steps, batch, semi-, and continuous regime). The microalga of interest is cultivated in a two-step system. First, the culture grows photoautotrophically in a controlled bioreactor with pH-dependent CO2 injection, temperature monitoring, light intensity, and LED wavelength remote control in a semicontinuous mode. In the second step, the harvested biomass is subjected to mixotrophic conditions to enhance further growth. Preliminary tests have been performed to define the suitable media, salinity, pH, and organic carbon substrate to obtain the highest biomass productivity. Dynamic light and operational conditions (e.g. HRT) are evaluated to achieve high biomass production, high PE accumulation in the biomass, and high EPS release in the medium. Porphyridium marinum is able to chromatically adapt the photosynthetic apparatus to efficiently exploit the full light spectra composition. The effect of specific narrow LED wavelengths (white W, red R, green G, blue B) and a combination of LEDs (WR, WB, WG, BR, BG, RG) are identified to understand the phenomenon of chromatic adaptation under photoautotrophic conditions. The effect of light intensity, residence time, and light quality are investigated to define optimal operational strategies for full scale commercial applications. Production of biomass, phycobiliproteins, PE, EPS, EPS sulfate content, EPS composition, Chlorophyll-a, and pigment content are monitored to determine the effect of LED wavelength on the cultivation Porphyridium marinum in order to optimize the production of these multiple, highly valuable bioproducts of commercial interest.

Keywords: red microalgae, LED, exopolysaccharide, phycoerythrin

Procedia PDF Downloads 91

Authors: N. Lakshmipathy, Ch. S. N. Murthy, M. Aruna

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The design of lighting systems for surface mines is not an easy task because of the unique environment and work procedures encountered in the mines. The primary objective of this paper is to identify the major problems encountered in mine lighting application and to provide guidance in the solution of these problems. In the surface mining reflectance of surrounding surfaces is one of the important factors, which improve the vision, in the night hours. But due to typical working nature in the mines it is very difficult to fulfill these requirements, and also the orientation of the light at work site is a challenging task. Due to this reason machine operator and other workers in a mine need to be able to orient themselves in a difficult visual environment. The haul roads always keep on changing to tune with the mining activity. Other critical area such as dumpyards, stackyards etc. also change their phase with time, and it is difficult to illuminate such areas. Mining is a hazardous occupation, with workers exposed to adverse conditions; apart from the need for hard physical labor, there is exposure to stress and environmental pollutants like dust, noise, heat, vibration, poor illumination, radiation, etc. Visibility is restricted when operating load haul dumper and Heavy Earth Moving Machinery (HEMM) vehicles resulting in a number of serious accidents. one of the leading causes of these accidents is the inability of the equipment operator to see clearly people, objects or hazards around the machine. Results indicate blind spots are caused primarily by posts, the back of the operator's cab, and by lights and light brackets. The careful designed and implemented, lighting systems provide mine workers improved visibility and contribute to improved safety, productivity and morale. Properly designed lighting systems can improve visibility and safety during working in the opencast mines.

Keywords: contrast, efficacy, illuminance, illumination, light, luminaire, luminance, reflectance, visibility

Procedia PDF Downloads 341

Authors: Galih Imaduddin

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Knowledge has been viewed as one of the most important resources in organizations, including those that operate in the healthcare sector. On that basis, Knowledge Management (KM) is crucial for healthcare organizations to improve their productivity and ensure effective utilization of their resources. Despite the growing interests to understand how KM might work for healthcare organizations, there is only a modest amount of empirical inquiries which have specifically focused on the tools and initiatives to share knowledge. Hence, the main purpose of this paper is to investigate the way healthcare organizations, particularly public sector ones, utilize knowledge sharing tools and initiatives for the benefit of patient-care. Employing a qualitative method, 13 (thirteen) Community Health Centers (CHCs) from a high-performing district health setting in Indonesia were observed. Data collection and analysis involved a repetition of document retrievals and interviews (n=41) with multidisciplinary health professionals who work in these CHCs. A single case study was cultivated reflecting on the means that were used to share knowledge, along with the factors that inhibited the exchange of knowledge among those health professionals. The study discovers that all of the thirteen CHCs exhibited and applied knowledge sharing means which included knowledge documents, virtual communication channels (i.e. emails and chatting applications), and social learning forums such as staff meetings, morning briefings, and communities of practices. However, the intensity of utilization was different among these CHCs, in which organizational culture, leadership, professional boundaries, and employees’ technological aptitude were presumed to be the factors that inhibit knowledge sharing processes. Making a distance with the KM literature of other sectors, this study denounces the primacy of technology-based tools, suggesting that socially-based initiatives could be more reliable for sharing knowledge. This suggestion is largely due to the nature of healthcare work which is still predominantly based on the tacit form of knowledge.

Keywords: knowledge management, knowledge sharing, knowledge sharing tools and initiatives, knowledge sharing inhibitors, primary health care organizations

Procedia PDF Downloads 227

Authors: Shraddha Jadhav

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We are entering a new age in the built environment where we expect our buildings to deliver far more than just a place to work or live. It is widely believed that sustainable building design strategies create improved occupants’ comfort & satisfaction with respect to thermal comfort & indoor environmental quality. Yet this belief remains a hypothesis with little empirical support. IT buildings cater to more than 3000 users at a time. Nowadays people spend 90% of the time inside offices. These sustainable IT office buildings should provide the occupants with maximum comfort for better work productivity. Such green rated buildings fulfill all the criteria at the designing stage, but do they really work as expected at the occupancy stage. The aim of this paper is to evaluate whether green IT buildings provide the required comfort level as expected at the design stage. Building Occupants are a rich source of information for evaluating their comfort level in the building and to find out the solutions for their discomfort. This can be achieved by carrying out Post Occupancy Evaluation after the building has been occupied for more than a year or two. The technique consists of qualitative methods like questionnaire surveys & observations and quantitative methods like field measurements, photographs. Post Occupancy Evaluation was carried out in a Green (Platinum rated) IT building in Pune. 30 samples per floor were identified for the questionnaire survey. The core questions access occupant satisfaction with thermal comfort in the work area and measures adopted for making it comfortable were identified. The Mean Radiant Temperature of the same samples was taken to compare the quantitative and qualitative results. The survey was used to evaluate the occupant thermal comfort in a green office building and identify areas needing improvement. The survey has been designed in reference to ASHRAE standard 55-2010 & ISHRAE 10001:2017 IEQ and was further refined to suit the user of the building.

Keywords: green office building, building occupant, thermal comfort, POE, user satisfaction, survey

Procedia PDF Downloads 51

Authors: Amal Shehata

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Low back pain related to disc prolapse is localized in the lumbar area and it may be radiated to the lower extremities, starting from neurons near or around the spinal canal. Most of the population may be affected with disc prolapse within their lifetime and leads to lost productivity, disability and loss of function. The study purpose was to examine the effect of rehabilitative nursing program on pain intensity and functional status among patients with discectomy. Design: Aquasi experimental design was utilized. Setting: The study was carried out at neurosurgery department and out patient's clinic of Menoufia University and Teaching hospitals at Menoufia governorate, Egypt. Instrument of the study: Five Instruments were used for data collection: Structured interviewing questionnaire, Functional assessment instrument, Observational check list, Numeric rating Scale and Oswestry low back pain disability questionnaire. Results: There was an improvement in mean total knowledge score about disease process, discectomy and rehabilitation program in study group (25.32%) than control group (7.32%). There was highly statistically significant improvement in lumbar flexibility among study group (80%) than control group (30%) after rehabilitation program than before. Also there was a decrease in pain score in study group (58% no pain) than control group (28% no pain) after rehabilitation program. There was an improvement in total disability score of study group (zero %) regarding effect of pain on the activity of daily living after rehabilitation program than control group (16%). Conclusion: Application of rehabilitative nursing program for patient with discectomy had proven a positive effect in relation to knowledge score, pain reduction, activity of daily living and functional abilities. Recommendation: A continuous rehabilitative nursing program should be carried out for all patients immediately after discectomy surgery on regular basis. Also A colored illustrated booklet about rehabilitation program should be available and distributed for all patients before surgery.

Keywords: discectomy, rehabilitative nursing program, pain intensity, functional status

Procedia PDF Downloads 125

Authors: Chowdhury Dilruba Shoma

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Gender is about equal rights that both males and females having access to responsibilities and opportunities in decision making is a fundamental human right. It is also a precondition for, and a mark of, sustainable people-oriented development. In Bangladesh, women have fewer opportunities than men do to access credit from banks and financial institutions. Entrenched patriarchal attitudes, unequal inheritance rights, and male-dominated hierarchies in the financial system, plus high interest rates and a lack of security/collateral, make it harder for women to obtain bank loans. Limited access to institutional credit is a serious restraint on the productivity and income of women entrepreneurs, (and the wider economy). These gender-biased and structural barriers inhibit women’s access to fundamental economic rights. Using a liberal feminist theoretical lens, this study provides some useful insights into the relationship between gender inequality and entrepreneurship, leading to a better understanding of women’s entrepreneurship development in Bangladesh. Recently, the Bangladesh Government, the United Nations Capital Development Fund, and Bangladesh Bank opened up the Women Entrepreneur Support Fund (WESF) ‒ Credit Guarantee Scheme (CGS) pilot project to cover collateral shortfalls for women entrepreneurs in the small and medium enterprise sector. The aim is to improve gender equality and advance women’s rights in relation to receiving credit. This article examines the challenges and prospects of the WESF-CGS, and suggests that implementation of measures in WESF-CGS policymaking, coupled with a combination of legislatory and regulatory reforms that implement the fundamental tenets of liberal feminism, can lead to a comprehensive and effective credit policy to boost women’s agency and economic empowerment. This may ultimately lead to more sustainable development in Bangladesh.

Keywords: Bangladesh, credit guarantee scheme, liberal feminist theory, women entrepreneur support fund

Procedia PDF Downloads 117