Search results for: estimate value

Authors: Ahmad Saadiq, Neeraj Sahu

Abstract:

Sediment, which comprises of solid particles of mineral and organic material are transported by water. In river systems, the amount of sediment transported is controlled by both the transport capacity of the flow and the supply of sediment. The transport of sediment in rivers is important with respect to pollution, channel navigability, reservoir ageing, hydroelectric equipment longevity, fish habitat, river aesthetics and scientific interests. The sediment load transported in a river is a very complex hydrological phenomenon. Hence, sediment transport has attracted the attention of engineers from various aspects, and different methods have been used for its estimation. So, several experimental equations have been submitted by experts. Though the results of these methods have considerable differences with each other and with experimental observations, because the sediment measures have some limits, these equations can be used in estimating sediment load. In this present study, two black box models namely, an SRC (Sediment Rating Curve) and ANN (Artificial Neural Network) are used in the simulation of the suspended sediment load. The study is carried out for Seonath subbasin. Seonath is the biggest tributary of Mahanadi river, and it carries a vast amount of sediment. The data is collected for Jondhra hydrological observation station from India-WRIS (Water Resources Information System) and IMD (Indian Meteorological Department). These data include the discharge, sediment concentration and rainfall for 10 years. In this study, sediment load is estimated from the input parameters (discharge, rainfall, and past sediment) in various combination of simulations. A sediment rating curve used the water discharge to estimate the sediment concentration. This estimated sediment concentration is converted to sediment load. Likewise, for the application of these data in ANN, they are normalised first and then fed in various combinations to yield the sediment load. RMSE (root mean square error) and R² (coefficient of determination) between the observed load and the estimated load are used as evaluating criteria. For an ideal model, RMSE is zero and R² is 1. However, as the models used in this study are black box models, they don’t carry the exact representation of the factors which causes sedimentation. Hence, a model which gives the lowest RMSE and highest R² is the best model in this study. The lowest values of RMSE (based on normalised data) for sediment rating curve, feed forward back propagation, cascade forward back propagation and neural network fitting are 0.043425, 0.00679781, 0.0050089 and 0.0043727 respectively. The corresponding values of R² are 0.8258, 0.9941, 0.9968 and 0.9976. This implies that a neural network fitting model is superior to the other models used in this study. However, a drawback of neural network fitting is that it produces few negative estimates, which is not at all tolerable in the field of estimation of sediment load, and hence this model can’t be crowned as the best model among others, based on this study. A cascade forward back propagation produces results much closer to a neural network model and hence this model is the best model based on the present study.

Keywords: artificial neural network, Root mean squared error, sediment, sediment rating curve

Procedia PDF Downloads 299

Authors: Silvia Grassi, Stefano Schiavon, Ernestina Casiraghi, Cristina Alamprese

Abstract:

Dry-cured ham is an uncooked meat product particularly appreciated for its peculiar sensory traits among which lipid component plays a key role in defining quality and, consequently, consumers’ acceptability. Usually, fat content and distribution are chemically determined by expensive, time-consuming, and destructive analyses. Moreover, different sensory techniques are applied to assess product conformity to desired standards. In this context, visual systems are getting a foothold in the meat market envisioning more reliable and time-saving assessment of food quality traits. The present work aims at developing a simple but systematic and objective visual methodology to assess the fat amount of dry-cured ham slices, in terms of total, intermuscular and intramuscular fractions. To the aim, 160 slices from 80 PDO dry-cured hams were evaluated by digital image analysis and Soxhlet extraction. RGB images were captured by a flatbed scanner, converted in grey-scale images, and segmented based on intensity histograms as well as on a multi-stage algorithm aimed at edge enhancement. The latter was performed applying the Canny algorithm, which consists of image noise reduction, calculation of the intensity gradient for each image, spurious response removal, actual thresholding on corrected images, and confirmation of strong edge boundaries. The approach allowed for the automatic calculation of total, intermuscular and intramuscular fat fractions as percentages of the total slice area. Linear regression models were run to estimate the relationships between the image analysis results and the chemical data, thus allowing for the prediction of the total, intermuscular and intramuscular fat content by the dry-cured ham images. The goodness of fit of the obtained models was confirmed in terms of coefficient of determination (R²), hypothesis testing and pattern of residuals. Good regression models have been found being 0.73, 0.82, and 0.73 the R2 values for the total fat, the sum of intermuscular and intramuscular fat and the intermuscular fraction, respectively. In conclusion, the edge enhancement visual procedure brought to a good fat segmentation making the simple visual approach for the quantification of the different fat fractions in dry-cured ham slices sufficiently simple, accurate and precise. The presented image analysis approach steers towards the development of instruments that can overcome destructive, tedious and time-consuming chemical determinations. As future perspectives, the results of the proposed image analysis methodology will be compared with those of sensory tests in order to develop a fast grading method of dry-cured hams based on fat distribution. Therefore, the system will be able not only to predict the actual fat content but it will also reflect the visual appearance of samples as perceived by consumers.

Keywords: dry-cured ham, edge detection algorithm, fat content, image analysis

Procedia PDF Downloads 151

Authors: Shanza Akram, Sameen Toor, Heba Harb Abu Alkass, Zainab Abdulsalam Altaha, Sara Taha Abdulla, Saleem Imran

Abstract:

Acute pulmonary embolism (PE) is a common disease and can be fatal. The clinical presentation is variable and nonspecific, making accurate diagnosis difficult. Testing patients with suspected acute PE has increased dramatically. However, the overuse of some tests, particularly CT and D-dimer measurement, may not improve care while potentially leading to patient harm and unnecessary expense. CTPA is the investigation of choice for PE. Its easy availability, accuracy and ability to provide alternative diagnosis has lowered the threshold for performing it, resulting in its overuse. Guidelines have recommended the use of clinical pretest probability tools such as ‘Wells score’ to assess risk of suspected PE. Unfortunately, implementation of guidelines in clinical practice is inconsistent. This has led to low risk patients being subjected to unnecessary imaging, exposure to radiation and possible contrast related complications. Aim: To study the diagnostic yield of CT PA, clinical pretest probability of patients according to wells score and to determine whether or not there was an overuse of CTPA in our service. Methods: CT scans done on patients with suspected P.E in our hospital from 1st January 2014 to 31st December 2014 were retrospectively reviewed. Medical records were reviewed to study demographics, clinical presentation, final diagnosis, and to establish if Wells score and D-Dimer were used correctly in predicting the probability of PE and the need for subsequent CTPA. Results: 100 patients (51male) underwent CT PA in the time period. Mean age was 57 years (24-91 years). Majority of patients presented with shortness of breath (52%). Other presenting symptoms included chest pain 34%, palpitations 6%, collapse 5% and haemoptysis 5%. D Dimer test was done in 69%. Overall Wells score was low (<2) in 28 %, moderate (>2 - < 6) in 47% and high (> 6) in 15% of patients. Wells score was documented in medical notes of only 20% patients. PE was confirmed in 12% (8 male) patients. 4 had bilateral PE’s. In high-risk group (Wells > 6) (n=15), there were 5 diagnosed PEs. In moderate risk group (Wells >2 - < 6) (n=47), there were 6 and in low risk group (Wells <2) (n=28), one case of PE was confirmed. CT scans negative for PE showed pleural effusion in 30, Consolidation in 20, atelactasis in 15 and pulmonary nodule in 4 patients. 31 scans were completely normal. Conclusion: Yield of CT for pulmonary embolism was low in our cohort at 12%. A significant number of our patients who underwent CT PA had low Wells score. This suggests that CT PA is over utilized in our institution. Wells score was poorly documented in medical notes. CT-PA was able to detect alternative pulmonary abnormalities explaining the patient's clinical presentation. CT-PA requires concomitant pretest clinical probability assessment to be an effective diagnostic tool for confirming or excluding PE. . Clinicians should use validated clinical prediction rules to estimate pretest probability in patients in whom acute PE is being considered. Combining Wells scores with clinical and laboratory assessment may reduce the need for CTPA.

Keywords: CT PA, D dimer, pulmonary embolism, wells score

Procedia PDF Downloads 195

Authors: Junaid Hamid Bhat

Abstract:

Background: Musculoskeletal disorders are one of the main causes of occupational illness. Mechanisms and the factors like repetitive work, physical effort and posture, endangering the risk of musculoskeletal disorders would now appear to have been properly identified. Teacher’s exposure to work-related musculoskeletal disorders appears to be insufficiently described in the literature. Little research has investigated the prevalence and risk factors of musculoskeletal disorders in teaching profession. Very few studies are available in this regard and there are no studies evident in India. Purpose: To determine the prevalence of musculoskeletal disorders and to identify and measure the association of such risk factors responsible for developing musculoskeletal disorders among school teachers. Methodology: An observational cross sectional study was carried out. 500 school teachers from primary, middle, high and secondary schools were selected, based on eligibility criteria. A signed consent was obtained and a self-administered, validated questionnaire was used. Descriptive statistics was used to compute the statistical mean and standard deviation, frequency and percentage to estimate the prevalence of musculoskeletal disorders among school teachers. The data analysis was done by using SPSS version 16.0. Results: Results indicated higher pain prevalence (99.6%) among school teachers during the past 12 months. Neck pain (66.1%), low back pain (61.8%) and knee pain (32.0%) were the most prevalent musculoskeletal complaints of the subjects. Prevalence of shoulder pain was also found to be high among school teachers (25.9%). 52.0% subjects reported pain as disabling in nature, causing sleep disturbance (44.8%) and pain was found to be associated with work (87.5%). A significant association was found between musculoskeletal disorders and sick leaves/absenteeism. Conclusion: Work-related musculoskeletal disorders particularly neck pain, low back pain, and knee pain, is highly prevalent and risk factors are responsible for the development of same in school teachers. There is little awareness of musculoskeletal disorders among school teachers, due to work load and prolonged/static postures. Further research should concentrate on specific risk factors like repetitive movements, psychological stress, and ergonomic factors and should be carried out all over the country and the school teachers should be studied carefully over a period of time. Also, an ergonomic investigation is needed to decrease the work-related musculoskeletal disorder problems. Implication: Recall bias and self-reporting can be considered as limitations. Also, cause and effect inferences cannot be ascertained. Based on these results, it is important to disseminate general recommendations for prevention of work-related musculoskeletal disorders with regards to the suitability of furniture, equipment and work tools, environmental conditions, work organization and rest time to school teachers. School teachers in the early stage of their careers should try to adapt the ergonomically favorable position whilst performing their work for a safe and healthy life later. Employers should be educated on practical aspects of prevention to reduce musculoskeletal disorders, since changes in workplace and work organization and physical/recreational activities are required.

Keywords: work related musculoskeletal disorders, school teachers, risk factors funding, medical and health sciences

Procedia PDF Downloads 245

Authors: T. Al-Alawi, N. Shorbaji, E. Rashaidi, M.Alidrisi

Abstract:

Purpose/Objective(s): The main purpose of this study is to analyze the planning of SBRT treatments for localized prostate cancer with 6FFF and 10FFF energies to see if there is a dosimetric difference between the two energies and how we can increase the plan efficiency and reduce its complexity. Also, to introduce a planning method in our department to treat prostate cancer by utilizing high energy photons without increasing patient toxicity and fulfilled all dosimetric constraints for OAR (an organ at risk). Then toevaluate the target 95% coverage PTV95, V5%, V2%, V1%, low dose volume for OAR (V1Gy, V2Gy, V5Gy), monitor unit (beam-on time), and estimate the values of homogeneity index HI, conformity index CI a Gradient index GI for each treatment plan.Materials/Methods: Two treatment plans were generated for15 patients with localized prostate cancer retrospectively using the CT planning image acquired for radiotherapy purposes. Each plan contains two/three complete arcs with two/three different collimator angle sets. The maximum dose rate available is 1400MU/min for the energy 6FFF and 2400MU/min for 10FFF. So in case, we need to avoid changing the gantry speed during the rotation, we tend to use the third arc in the plan with 6FFF to accommodate the high dose per fraction. The clinical target volume (CTV) consists of the entire prostate for organ-confined disease. The planning target volume (PTV) involves a margin of 5 mm. A 3-mm margin is favored posteriorly. Organs at risk identified and contoured include the rectum, bladder, penile bulb, femoral heads, and small bowel. The prescription dose is to deliver 35Gyin five fractions to the PTV and apply constraints for organ at risk (OAR) derived from those reported in references. Results: In terms of CI=0.99, HI=0.7, and GI= 4.1, it was observed that they are all thesame for both energies 6FFF and 10FFF with no differences, but the total delivered MUs are much less for the 10FFF plans (2907 for 6FFF vs.2468 for 10FFF) and the total delivery time is 124Sc for 6FFF vs. 61Sc for 10FFF beams. There were no dosimetric differences between 6FFF and 10FFF in terms of PTV coverage and mean doses; the mean doses for the bladder, rectum, femoral heads, penile bulb, and small bowel were collected, and they were in favor of the 10FFF. Also, we got lower V1Gy, V2Gy, and V5Gy doses for all OAR with 10FFF plans. Integral dosesID in (Gy. L) were recorded for all OAR, and they were lower with the 10FFF plans. Conclusion: High energy 10FFF has lower treatment time and lower delivered MUs; also, 10FFF showed lower integral and meant doses to organs at risk. In this study, we suggest usinga 10FFF beam for SBRTprostate treatment, which has the advantage of lowering the treatment time and that lead to lessplan complexity with respect to 6FFF beams.

Keywords: FFF beam, SBRT prostate, VMAT, prostate cancer

Procedia PDF Downloads 57

Authors: Naod Mekonnen Anega

Abstract:

The very objective of this paper was to empirically identify technology tailored determinants to the adoption and adoption intensity (extent of use) of agricultural water management technologies in Meda Welabu Woreda, Oromia regional state, Ethiopia. Meda Welabu Woreda which is one of the administrative Woredas of the Oromia regional state was selected purposively as this Woreda is one of the Woredas in the region where small scale irrigation practices and the use of agricultural water management technologies can be found among smallholders. Using the existence water management practices (use of water management technologies) and land use pattern as a criterion Genale Mekchira Kebele is selected to undergo the study. A total of 200 smallholders were selected from the Kebele using the technique developed by Krejeie and Morgan. The study employed the Logit and Tobit models to estimate and identify the economic, social, geographical, household, institutional, psychological, technological factors that determine adoption and adoption intensity of water management technologies. The study revealed that while 55 of the sampled households are adopters of agricultural water management technology the rest 140 were non adopters of the technologies. Among the adopters included in the sample 97% are using river diversion technology (traditional) with traditional canal while the rest 7% percent are using pond with treadle pump technology. The Logit estimation reveled that while adoption of river diversion is positively and significantly affected by membership to local institutions, active labor force, income, access to credit and land ownership, adoption of treadle pump technology is positively and significantly affected by family size, education level, access to credit, extension contact, income, access to market, and slope. The Logit estimation also revealed that whereas, group action requirement, distance to farm, and size of active labor force negative and significantly influenced adoption of river diversion, age and perception has negatively and significantly influenced adoption decision of treadle pump technology. On the other hand, the Tobit estimation reveled that while adoption intensity (extent of use) of agricultural water management is positively and significantly affected by education, credit, and extension contact, access to credit, access to market and income. This study revealed that technology tailored study on adoption of Agricultural water management technologies (AWMTs) should be considered to indentify and scale up best agricultural water management practices. In fact, in countries like Ethiopia, where there is difference in social, economic, cultural, environmental and agro ecological conditions even within the same Kebele technology tailored study that fit the condition of each Kebele would help to identify and scale up best practices in agricultural water management.

Keywords: water management technology, adoption, adoption intensity, smallholders, technology tailored approach

Procedia PDF Downloads 413

Authors: Haya Salah, Srinivas Sharan

Abstract:

Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.

Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time

Procedia PDF Downloads 90

Authors: Shamsulhaq Amin

Abstract:

Unbound granular materials (UGMs) are pivotal in ensuring long-term quality, especially in the layers under the surface of flexible pavements and other constructions. This study seeks to better understand the behavior of the UGMs by looking at popular models for predicting lasting deformation under various levels of stresses and load cycles. These models focus on variables such as the number of load cycles, stress levels, and features specific to materials and were evaluated on the basis of their ability to accurately predict outcomes. The study showed that these factors play a crucial role in how well the models work. Therefore, the research highlights the need to look at a wide range of stress situations to more accurately predict how much the UGMs bend or shift. The research looked at important factors, like how permanent deformation relates to the number of times a load is applied, how quickly this phenomenon happens, and the shakedown effect, in two different types of UGMs: granite and limestone. A detailed study was done over 100,000 load cycles, which provided deep insights into how these materials behave. In this study, a number of factors, such as the level of stress applied, the number of load cycles, the density of the material, and the moisture present were seen as the main factors affecting permanent deformation. It is vital to fully understand these elements for better designing pavements that last long and handle wear and tear. A series of laboratory tests were performed to evaluate the mechanical properties of materials and acquire model parameters. The testing included gradation tests, CBR tests, and Repeated load triaxial tests. The repeated load triaxial tests were crucial for studying the significant components that affect deformation. This test involved applying various stress levels to estimate model parameters. In addition, certain model parameters were established by regression analysis, and optimization was conducted to improve outcomes. Afterward, the material parameters that were acquired were used to construct graphs for each model. The graphs were subsequently compared to the outcomes obtained from the repeated load triaxial testing. Additionally, the models were evaluated to determine if they demonstrated the two inherent deformation behaviors of materials when subjected to repetitive load: the initial phase, post-compaction, and the second phase volumetric changes. In this study, using log-log graphs was key to making the complex data easier to understand. This method made the analysis clearer and helped make the findings easier to interpret, adding both precision and depth to the research. This research provides important insight into picking the right models for predicting how these materials will act under expected stress and load conditions. Moreover, it offers crucial information regarding the effect of load cycle and permanent deformation as well as the shakedown effect on granite and limestone UGMs.

Keywords: permanent deformation, unbound granular materials, load cycles, stress level

Procedia PDF Downloads 12

Authors: Monkiz Khasreen

Abstract:

In the context of the global trend towards reducing new buildings carbon footprint, the design team is required to make early decisions that have a major influence on embodied and operational carbon. Sustainability strategies should be clear during early stages of building design process, as changes made later can be extremely costly. Life-Cycle Assessment (LCA) could be used as the vehicle to carry other tools and processes towards achieving the requested improvement. Although LCA is the ‘golden standard’ to evaluate buildings from 'cradle to grave', lack of details available on the concept design makes LCA very difficult, if not impossible, to be used as an estimation tool at early stages. Issues related to transparency and accessibility of information in the building industry are affecting the credibility of LCA studies. A verified database derived from LCA case studies is required to be accessible to researchers, design professionals, and decision makers in order to offer guidance on specific areas of significant impact. This database could be the build-up of data from multiple sources within a pool of research held in this context. One of the most important factors that affects the reliability of such data is the temporal factor as building materials, components, and systems are rapidly changing with the advancement of technology making production more efficient and less environmentally harmful. Recent LCA studies on different building functions, types, and structures are always needed to update databases derived from research and to form case bases for comparison studies. There is also a need to make these studies transparent and accessible to designers. The work in this paper sets out to address this need. This paper also presents life-cycle case study of a new-build educational building in England. The building utilised very current construction methods and technologies and is rated as BREEAM excellent. Carbon emissions of different life-cycle stages and different building materials and components were modelled. Scenario and sensitivity analyses were used to estimate the future of new educational buildings in England. The study attempts to form an indicator during the early design stages of similar buildings. Carbon dioxide emissions of this case study building, when normalised according to floor area, lie towards the lower end of the range of worldwide data reported in the literature. Sensitivity analysis shows that life cycle assessment results are highly sensitive to future assumptions made at the design stage, such as future changes in electricity generation structure over time, refurbishment processes and recycling. The analyses also prove that large savings in carbon dioxide emissions can result from very small changes at the design stage.

Keywords: architecture, building, carbon dioxide, construction, educational buildings, England, environmental impact, life-cycle assessment

Procedia PDF Downloads 94

Authors: Fatemeh Behbahani, Mehdi Behbahani

Abstract:

The new materials have exposed the technological advancement that has been used to facilitate the presentation of buildings to effectively suppress vibration. Recently researchers have increased their advantages, including decreased power requirements, mechanical simplicity, and a high power capability, because of the regulated Fluids and their applications. The fluids used in magneto-rheological dampers also improved their mechanical characteristics. The damper force caused by the current excitement adjustment was applied within the damper to the electromagnet. A supreme model is needed to be able to accurately estimate damping force according to the superior present hysteresis damper behavior to use the advantage of this remarkable method. Due to the supreme coverage of the nonlinear field of the hysteresis loop among the parametric model, the Spencer model has been commonly used for MR damper to describe hysteresis behavior. Despite this, there are still essential differences in the simulation and experimental outcomes. A novelty model according to the Spencer model is being used here to simulate the damper's nonlinear hysteretic behavior by taking the excitations of frequency, current, and amplitude as displacement and velocity as input variables. This suggested model has a greater benefit than the historically uncertain parameters of the Spencer model, where it can be re-evaluated if a new grouping of excitation parameters is preferred. Experimental experiments in the damping force measuring machine were carried out for validation of the simulations using MATLAB software, as shown in the previous paper which will be mentioned in the content. This paper aims to explain the optimal value of the parameters for the proposed model using a biological-inspired algorithm called Particle Swarm Optimization. The working principles of the classical Particle Swarm Optimisation (PSO) algorithm for a better understanding of the basic framework of a PSO algorithm will be discussed and also, learn to demonstrate the functionality of a PSO algorithm in MATLAB. A PSO algorithm's design is similar to that of bird flocking and starts with a randomly generated population group. They have fitness values to determine the population. They update the population check for optimal parameters with random strategies and update the simulation resets as well. However, not all algorithms guarantee F. B. with the Department of artificial intelligence and robotics (CAIRO), Malaysia-Japan International Institute of Technology (MJIIT), UTM, 54100, Kuala Lumpur, Malaysia (corresponding author, phone: +60-1136463246; e-mail: [email protected]). success. In displacement, velocity, and time curves, a great deal was found between the prediction and experimental works with an appropriate error as a result of the confirmation that the model can correctly measure the hysteresis damping force and the error has decreased relative to the Spencer model.

Keywords: modeling and simulation, semi-active control, MR damper RD-8040-1, particle swarm optimization, magnetorheological fluid, based spencer model

Procedia PDF Downloads 15

Authors: S. N. C. M. Dias, Niels Schuetze, Franz Lennartz

Abstract:

The current focus in irrigated agriculture will move from maximizing crop production per unit area towards maximizing the crop production per unit amount of water (water productivity) used. At the same time, inadequate water supply or deficit irrigation will be the only solution to cope with water scarcity in the near future. Soil matric potential based irrigation plays an important role in such deficit irrigated agriculture to grow any crop including rice. Rice as the staple food for more than half of the world population, grows mainly under flooded conditions. It requires more water compared to other upland cereals. A major amount of this water is used in the land preparation and is lost at field level due to evaporation, deep percolation, and seepage. A field experimental study was conducted in the experimental premises of rice research and development institute of Sri Lanka in Kurunegala district to estimate the water productivity of rice under deficit irrigation. This paper presents the feasibility of improving current irrigation management in rice cultivation under water scarce conditions. The experiment was laid out in a randomized complete block design with four different irrigation treatments with three replicates. Irrigation treatments were based on soil matric potential threshold values. Treatment W0 was maintained between 60-80mbars. W1 was maintained between 80-100mbars. Other two dry treatments W2 and W3 were maintained at 100-120 mbar and 120 -140 mbar respectively. The sprinkler system was used to irrigate each plot individually upon reaching the maximum threshold value in respective treatment. Treatments were imposed two weeks after seed establishment and continued until two weeks before physiological maturity. Fertilizer applications, weed management, and other management practices were carried out per the local recommendations. Weekly plant growth measurements, daily climate parameters, soil parameters, soil tension values, and water content were measured throughout the growing period. Highest plant growth and grain yield (5.61t/ha) were observed in treatment W2 followed by W0, W1, and W3 in comparison to the reference yield (5.23t/ha) of flooded rice grown in the study area. Water productivity was highest in W3. Concerning the irrigation water savings, grain yield, and water productivity together, W2 showed the better performance. Rice grown under unsaturated conditions (W2) shows better performance compared to the continuously saturated conditions(W0). In conclusion, soil matric potential based irrigation is a promising practice in irrigation management in rice. Higher irrigation water savings can be achieved in this method. This strategy can be applied to a wide range of locations under different climates and soils. In future studies, higher soil matric potential values can be applied to evaluate the maximum possible values for rice to get higher water savings at minimum yield losses.

Keywords: irrigation, matric potential, rice, water scarcity

Procedia PDF Downloads 176

Authors: Amjad Ali Khan, Muhammad Ishaq Saqi, Kashif Ali

Abstract:

The focus of hydrocarbon exploration in Pakistan has been primarily on conventional hydrocarbon resources. Directorate General Petroleum Concessions (DGPC) has taken the lead on the assessment of indigenous unconventional oil and gas resources, which has resulted in a ‘Shale Oil/Gas Resource Assessment Study’ conducted with the help of USAID. This was critically required in the energy-starved Pakistan, where the gap between indigenous oil & gas production and demand continues to widen for a long time. Exploration & exploitation of indigenous unconventional resources of Pakistan have become vital to meet our energy demand and reduction of oil and gas import bill of the country. This study has attempted to bridge a critical gap in geological information about the potential of shale gas & oil in Pakistan in the four formations, i.e., Sembar, Lower Goru, Ranikot and Ghazij in the Middle and Lower Indus Basins, which were selected for the study as for resource assessment for shale gas & oil. The primary objective of the study was to estimate and establish shale oil/gas resource assessment of the study area by carrying out extensive geological analysis of exploration, appraisal and development wells drilled in the Middle and Lower Indus Basins, along with identification of fairway(s) and sweet spots in the study area. The Study covers the Lower parts of the Middle Indus basins located in Sindh, southern Punjab & eastern parts of the Baluchistan provinces, with a total sedimentary area of 271,795 km2. Initially, 1611 wells were reviewed, including 1324 wells drilled through different shale formations. Based on the availability of required technical data, a detailed petrophysical analysis of 124 wells (21 Confidential & 103 in the public domain) has been conducted for the shale gas/oil potential of the above-referred formations. The core & cuttings samples of 32 wells and 33 geochemical reports of prospective Shale Formations were available, which were analyzed to calibrate the results of petrophysical analysis with petrographic/ laboratory analyses to increase the credibility of the Shale Gas Resource assessment. This study has identified the most prospective intervals, mainly in Sembar and Lower Goru Formations, for shale gas/oil exploration in the Middle and Lower Indus Basins of Pakistan. The study recommends seven (07) sweet spots for undertaking pilot projects, which will enable to evaluate of the actual production capability and production sustainability of shale oil/gas reservoirs of Pakistan for formulating future strategies to explore and exploit shale/oil resources of Pakistan including fiscal incentives required for developing shale oil/gas resources of Pakistan. Some E&P Companies are being persuaded to make a consortium for undertaking pilot projects that have shown their willingness to participate in the pilot project at appropriate times. The location for undertaking the pilot project has been finalized as a result of a series of technical sessions by geoscientists of the potential consortium members after the review and evaluation of available studies.

Keywords: conventional resources, petrographic analysis, petrophysical analysis, unconventional resources, shale gas & oil, sweet spots

Procedia PDF Downloads 14

Authors: Shreya Saxena

Abstract:

Background: Choledocholithiasis is a common complication of gallstone disease. Risk scoring systems exist to guide the need for further imaging or endoscopy in managing choledocholithiasis. We completed an audit to review the American Society for Gastrointestinal Endoscopy (ASGE) scoring system for prediction and management of choledocholithiasis against the current practice at a tertiary hospital to assess its utility in resource optimisation. We have now conducted a cost focused sub-analysis on patients categorized high-risk for choledocholithiasis according to the guidelines to determine any associated cost benefits. Method: Data collection from our prior audit was used to retrospectively identify thirteen patients considered high-risk for choledocholithiasis. Their ongoing management was mapped against the guidelines. Individual costs for the key investigations were obtained from our hospital financial data. Total cost for the different management pathways identified in clinical practice were calculated and compared against predicted costs associated with recommendations in the guidelines. We excluded the cost of laparoscopic cholecystectomy and considered a set figure for per day hospital admission related expenses. Results: Based on our previous audit data, we identified a77% positive predictive value for the ASGE risk stratification tool to determine patients at high-risk of choledocholithiasis. 47% (6/13) had an magnetic resonance cholangiopancreatography (MRCP) prior to endoscopic retrograde cholangiopancreatography (ERCP), whilst 53% (7/13) went straight for ERCP. The average length of stay in the hospital was 7 days, with an additional day and cost of £328.00 (£117 for ERCP) for patients awaiting an MRCP prior to ERCP. Per day hospital admission was valued at £838.69. When calculating total cost, we assumed all patients had admission bloods and ultrasound done as the gold standard. In doing an MRCP prior to ERCP, there was a 130% increase in cost incurred (£580.04 vs £252.04) per patient. When also considering hospital admission and the average length of stay, it was an additional £1166.69 per patient. We then calculated the exact costs incurred by the department, over a three-month period, for all patients, for key investigations or procedures done in the management of choledocholithiasis. This was compared to an estimate cost derived from the recommended pathways in the ASGE guidelines. Overall, 81% (£2048.45) saving was associated with following the guidelines compared to clinical practice. Conclusion: MRCP is the most expensive test associated with the diagnosis and management of choledocholithiasis. The ASGE guidelines recommend endoscopy without an MRCP in patients stratified as high-risk for choledocholithiasis. Our audit that focused on assessing the utility of the ASGE risk scoring system showed it to be relatively reliable for identifying high-risk patients. Our cost analysis has shown significant cost savings per patient and when considering the average length of stay associated with direct endoscopy rather than an additional MRCP. Part of this is also because of an increased average length of stay associated with waiting for an MRCP. The above data supports the ASGE guidelines for the management of high-risk for choledocholithiasis patients from a cost perspective. The only caveat is our small data set that may impact the validity of our average length of hospital stay figures and hence total cost calculations.

Keywords: cost-analysis, choledocholithiasis, risk stratification tool, general surgery

Procedia PDF Downloads 75

Authors: Nowrozy Jahan, Sharifah Syed Hassan, Daniel Reidpath

Abstract:

In recent decades, Malaysia has become a dengue hyper-endemic country with the co-circulation of the four-dengue virus (DENV) serotypes. The number of symptomatic dengue cases is maintaining an increasing trend since 1995 and sharply increased in 2014. The four DENV serotypes have been co-circulating since 2000, and this pattern of cyclical dominance of sub-types contributed to the development of frequent major dengue epidemics in Malaysia. Since 2012, different Malaysian state was dominated by different serotypes. The study aims to estimate the burden of asymptomatic dengue in a healthy adult population which may act as a potential source of further symptomatic dengue infection. It also aims to identify the predominant DENV serotypes which are circulating at the community level. A longitudinal prospective community-based study was conducted in the Segamat district of Johor State, southern part of Malaysia where the number of reported dengue cases has steadily increased over the last three years (2013-2015). More specifically, the study was conducted in and around of Kampung Abdullah of Sungai Segamat sub-district which was identified as a hot spot area over the period of 2013-2015. This community-based study has been conducted by Southeast Asia Community Observatory (SEACO), an ISO-certified research platform in collaboration of the Ministry of Health Malaysia and Monash University Malaysia. It was conducted from May 2015 to May 2016. In this study, 277 apparently looking healthy respondents joined who were followed up as a cohort for four times during the one-year study period. Blood was collected to detect the serological marker of dengue at each round of follow-up. Among 277, 184 respondents (66%) joined all four rounds. Half of the study respondents were at the age-group of 45-64 years, slightly more than half of the respondents (59%) were female, and the most (69%) of them were Malay; only 35% lived in urban areas. During the baseline, the study found a very high prevalence of exposure to dengue virus; 89% of the study respondents had serological evidence of previous asymptomatic dengue infection; the majority of them did not know about it as they did not develop any symptom of dengue fever; only 13% knew as they developed symptoms. At the end of the one-year study period, 19% of respondents developed recent secondary dengue infection which was also identified by the serological marker as they did not develop any symptom (asymptomatic cases). The asymptomatic dengue incidence was higher during the rainy season compared to the dry season. All four dengue serotypes were identified in the serum of the infected respondents; among them, DENV-2 was the most prominent. Further genetic analysis is going on to identify the association of HLA-B*46 and HLA-DRB1*08 with dengue resistance. This study provides evidence for the policymakers to be aware of asymptomatic dengue infection, to develop a useful tool for raising awareness about asymptomatic dengue infection among the general population, to monitor the community participation to strengthen the individual and community level dengue prevention and control measures when neither there is vaccine nor particular treatment for dengue.

Keywords: asymptomatic, dengue, health adults, prospective study

Procedia PDF Downloads 105

Authors: Peter Palasti, Eva Kerepeczki

Abstract:

Extensive fish farming is one of the most traditional forms of aquaculture in Europe, usually practiced in large pond systems with earthen beds, where the growth of fish is based on natural feed and supplementary foraging. These farms have semi-natural environmental conditions, sustaining diverse wildlife communities that have complex effects on fish production and also provide a livelihood for many wetland related taxa. Based on their characteristics, these communities could be sources of various ecosystem services (ESs), that could also enhance the value and enable the multifunctional use of these artificially constructed and maintained production zones. To identify and estimate the whole range of wildlife’s contribution we have conducted an integrated assessment in an extensively managed pond system in Biharugra, Hungary, where we studied 14 previously revealed ESs: fish and reed production, water storage, water and air quality regulation, CO2 absorption, groundwater recharge, aesthetics, recreational activities, inspiration, education, scientific research, presence of semi-natural habitats and useful/protected species. ESs were collected through structured interviews with the local experts of all major stakeholder groups, where we have also gathered information about the known forms, levels (none, low, high) and orientations (positive, negative) of the contributions of the wildlife community. After that, a quantitative analysis was carried out: we calculated the total mean value of the services being used between 2014-16, then we estimated the value and percentage of contributions. For the quantification, we mainly used biophysical indicators with the available data and empirical knowledge of the local experts. During the interviews, 12 of the previously listed services (85%) were mentioned to be related to wildlife community, consisting of 5 fully (e.g., recreation, reed production) and seven partially dependent ESs (e.g., inspiration, CO2 absorption) from our list. The orientation of the contributions was said to be positive almost every time; however, in the case of fish production, the feeding habit of some wild species (Phalacrocorax carbo, Lutra lutra) caused significant losses in fish stocks in the study period. During the biophysical assessment, we calculated the total mean value of the services and quantified the aid of wildlife community at the following services: fish and reed production, recreation, CO2 absorption, and the presence of semi-natural habitats and wild species. The combined results of our interviews and biophysical evaluations showed that the presence of wildlife community not just greatly increased the productivity of the fish farms in Biharugra (with ~53% of natural yield generated by planktonic and benthic communities) but also enhanced the multifunctionality of the system through expanding the quality and number of its services. With these abilities, extensively managed fishponds could play an important role in the future as refugia for wetland related services and species threatened by the effects of global warming.

Keywords: ecosystem services, fishpond systems, integrated assessment, wildlife community

Procedia PDF Downloads 91

Authors: Elissandro Voigt Beier, Cristiano Poleto

Abstract:

The main objective of the research is to assess the loss through the quantification of material culture (archaeological fragments) in rural areas, sites explored economically by machining on seasonal crops, and also permanent, in a hydrographic subsystem Camaquã River in the state of Rio Grande do Sul, Brazil. The study area consists of different micro basins and differs in area, ranging between 1,000 m² and 10,000 m², respectively the largest and the smallest, all with a large number of occurrences and outcrop locations of archaeological material and high density in intense farm environment. In the first stage of the research aimed to identify the dispersion of points of archaeological material through field survey through plot points by the Global Positioning System (GPS), within each river basin, was made use of concise bibliography on the topic in the region, helping theoretically in understanding the old landscaping with preferences of occupation for reasons of ancient historical people through the settlements relating to the practice observed in the field. The mapping was followed by the cartographic development in the region through the development of cartographic products of the land elevation, consequently were created cartographic products were to contribute to the understanding of the distribution of the absolute materials; the definition and scope of the material dispersed; and as a result of human activities the development of revolving letter by mechanization of in situ material, it was also necessary for the preparation of materials found density maps, linking natural environments conducive to ancient historical occupation with the current human occupation. The third stage of the project it is for the systematic collection of archaeological material without alteration or interference in the subsurface of the indigenous settlements, thus, the material was prepared and treated in the laboratory to remove soil excesses, cleaning through previous communication methodology, measurement and quantification. Approximately 15,000 were identified archaeological fragments belonging to different periods of ancient history of the region, all collected outside of its environmental and historical context and it also has quite changed and modified. The material was identified and cataloged considering features such as object weight, size, type of material (lithic, ceramic, bone, Historical porcelain and their true association with the ancient history) and it was disregarded its principles as individual lithology of the object and functionality same. As observed preliminary results, we can point out the change of materials by heavy mechanization and consequent soil disturbance processes, and these processes generate loading of archaeological materials. Therefore, as a next step will be sought, an estimate of potential losses through a mathematical model. It is expected by this process, to reach a reliable model of high accuracy which can be applied to an archeological site of lower density without encountering a significant error.

Keywords: degradation of heritage, quantification in archaeology, watershed, use and occupation of land

Procedia PDF Downloads 244

Authors: Ayesha Mushtaq

Abstract:

Asthma is a pulmonary disease in which blockade of the airway takes place due to inflammation as a response to certain allergens. Breathing troubles, cough, and dyspnea are one of the few symptoms. Several studies have indicated a significant effect on asthma due to changes in dietary routines. Certain food items, such as oily foods and other materials, are known to cause an increase in the symptoms of asthma. Low dietary intake of fruits and vegetables may be important in relation to asthma prevalence. The objective of this study is to assess and compare the nutritional status of asthmatic and non-asthmatic patients. The significance of this study lies in the factor that it will help nutritionists to arrange a feasible dietary routine for asthmatic patients. This research was conducted at the Pulmonology Department of the Pakistan Institute of Medical Science Islamabad. About thirty hundred thirty-four million people are affected by asthma worldwide. Pakistan is on the verge of being an uplifted urban population and asthma cases are increasingly high these days. Several studies suggest an increase in the Asthmatic patient population due to improper diet. This is a cross-sectional study aimed at assessing the nutritious standing of Asthmatic and non-asthmatic patients. This research took place at the Pakistan Institute of Medical Sciences (PIMS), Islamabad, Pakistan. The research included asthmatic and non-asthmatic patients coming to the pulmonology department clinic at the Pakistan Institute of Medical Sciences (PIMS). These patients were aged between 20-60 years. A questionnaire was developed for these patients to estimate their dietary plans in these patients. The methodology included four sections. The first section was the Socio-Demographic profile, which included age, gender, monthly income and occupation. The next section was anthropometric measurements which included the weight, height and body mass index (BMI) of an individual. The next section, section three, was about the biochemical attributes, such as for biochemical profiling, pulmonary function testing (PFT) was performed. In the next section, Dietary habits were assessed by a food frequency questionnaire (FFQ) through food habits and consumption pattern was assessed. The next section life style data, in which the person's level of physical activity, sleep and smoking habits were assessed. The next section was statistical analysis. All the data obtained from the study were statistically analyzed and assessed. Most of the asthma Patients were females, with weight more than normal or even obese. Body Mass Index (BMI) was higher in asthma Patients than those in non-Asthmatic ones. When the nutritional Values were assessed, we came to know that these patients were low on certain nutrients and their diet included more junk and oily food than healthy vegetables and fruits. Beverages intake was also included in the same assessment. It is evident from this study that nutritional status has a contributory effect on asthma. So, patients on the verge of developing asthma or those who have developed asthma should focus on their diet, maintain good eating habits and take healthy diets, including fruits and vegetables rather than oily foods. Proper sleep may also contribute to the control of asthma.

Keywords: BMI, nutrition, PAL, diet

Procedia PDF Downloads 50

Authors: Ch. Sridevi, S. P. Shailender Kumar, B. Gurudayal, A. Chalapathi Rao, K. Koteswara Rao, P. Srinivasulu

Abstract:

System reliability and system availability evaluation plays a crucial role in ensuring the seamless operation of complex satellite data reception system with consistent performance for longer periods. This paper presents a novel approach for the same using a case study on one of the antenna systems at satellite data reception ground station in India. The methodology involves analyzing system's components, their failure rates, system's architecture, generation of logical reliability block diagram model and estimating the reliability of the system using the component level mean time between failures considering exponential distribution to derive a baseline estimate of the system's reliability. The model is then validated with collected system level field failure data from the operational satellite data reception systems that includes failure occurred, failure time, criticality of the failure and repair times by using statistical techniques like median rank, regression and Weibull analysis to extract meaningful insights regarding failure patterns and practical reliability of the system and to assess the accuracy of the developed reliability model. The study mainly focused on identification of critical units within the system, which are prone to failures and have a significant impact on overall performance and brought out a reliability model of the identified critical unit. This model takes into account the interdependencies among system components and their impact on overall system reliability and provides valuable insights into the performance of the system to understand the Improvement or degradation of the system over a period of time and will be the vital input to arrive at the optimized design for future development. It also provides a plug and play framework to understand the effect on performance of the system in case of any up gradations or new designs of the unit. It helps in effective planning and formulating contingency plans to address potential system failures, ensuring the continuity of operations. Furthermore, to instill confidence in system users, the duration for which the system can operate continuously with the desired level of 3 sigma reliability was estimated that turned out to be a vital input to maintenance plan. System availability and station availability was also assessed by considering scenarios of clash and non-clash to determine the overall system performance and potential bottlenecks. Overall, this paper establishes a comprehensive methodology for reliability and availability analysis of complex satellite data reception systems. The results derived from this approach facilitate effective planning contingency measures, and provide users with confidence in system performance and enables decision-makers to make informed choices about system maintenance, upgrades and replacements. It also aids in identifying critical units and assessing system availability in various scenarios and helps in minimizing downtime and optimizing resource allocation.

Keywords: exponential distribution, reliability modeling, reliability block diagram, satellite data reception system, system availability, weibull analysis

Procedia PDF Downloads 53

Authors: Amirah Azzeri, Fatiha H. Shabaruddin, Scott A. McDonald, Rosmawati Mohamed, Maznah Dahlui

Abstract:

Objective: A scaled-up treatment cascade with direct-acting antiviral (DAA) therapy is necessary to achieve global WHO targets for hepatitis C virus (HCV) elimination in Malaysia. Recently, limited access to Sofosbuvir/Daclatasvir (SOF/DAC) is available through compulsory licensing, with future access to Sofosbuvir/Velpatasvir (SOF/VEL) expected through voluntary licensing due to recent agreements. SOF/VEL has superior clinical outcomes, particularly for cirrhotic stages, but has higher drug acquisition costs compared to SOF/DAC. It has been proposed that a stratified treatment cascade might be the most cost-efficient approach for Malaysia whereby all HCV patients are treated with SOF/DAC except for patients with cirrhosis who are treated with SOF/VEL. This study aimed to conduct a five-year budget impact analysis from the provider perspective of the proposed stratified treatment cascade for HCV treatment in Malaysia. Method: A disease progression model that was developed based on model-predicted HCV epidemiology data in Malaysia was used for the analysis, where all HCV patients in scenario A were treated with SOF/DAC for all disease stages while in scenario B, SOF/DAC was used only for non-cirrhotic patients and SOF/VEL was used for the cirrhotic patients. The model projections estimated the annual numbers of patients in care and the numbers of patients to be initiated on DAA treatment nationally. Healthcare costs associated with DAA therapy and disease stage monitoring was included to estimate the downstream cost implications. For scenario B, the estimated treatment uptake of SOF/VEL for cirrhotic patients were 25%, 50%, 75%, 100% and 100% for 2018, 2019, 2020, 2021 and 2022 respectively. Healthcare costs were estimated based on standard clinical pathways for DAA treatment described in recent guidelines. All costs were reported in US dollars (conversion rate US$1=RM4.09, the price year 2018). Scenario analysis was conducted for 5% and 10% reduction of SOF/VEL acquisition cost anticipated from the competitive market pricing of generic DAA in Malaysia. Results: The stratified treatment cascade with SOF/VEL in Scenario B was found to be cost-saving compared to Scenario A. A substantial portion of the cost reduction was due to the costs associated with DAA therapy which resulted in USD 40 thousand (year 1) to USD 443 thousand (year 5) savings annually, with cumulative savings of USD 1.1 million after 5 years. Cost reductions for disease stage monitoring were seen in year three onwards which resulted in cumulative savings of USD 1.1 thousand. Scenario analysis estimated cumulative savings of USD 1.24 to USD 1.35 million when the acquisition cost of SOF/VEL was reduced. Conclusion: A stratified treatment cascade with SOF/VEL was expected to be cost-saving and can results in a budget impact reduction in overall healthcare expenditure in Malaysia compared to treatment with SOF/DAC. The better clinical efficacy with SOF/VEL is expected to halt patients’ HCV disease progression and may reduce downstream costs of treating advanced disease stages. The findings of this analysis may be useful to inform healthcare policies for HCV treatment in Malaysia.

Keywords: Malaysia, direct acting antiviral, compulsory licensing, voluntary licensing

Procedia PDF Downloads 141

Authors: Massimo Ferrari, Maria Sole Pagliari

Abstract:

Pollution is a classic example of economic externality: agents who produce it do not face direct costs from emissions. Therefore, there are no direct economic incentives for reducing pollution. One way to address this market failure would be directly taxing emissions. However, because emissions are global, governments might as well find it optimal to wait let foreign countries to tax emissions so that they can enjoy the benefits of lower pollution without facing its direct costs. In this paper, we first document the empirical relation between pollution and economic output with static and dynamic regression methods. We show that there is a negative relation between aggregate output and the stock of pollution (measured as the stock of CO₂ emissions). This relationship is also highly non-linear, increasing at an exponential rate. In the second part of the paper, we develop and estimate a two-country, two-sector model for the US and the euro area. With this model, we aim at analyzing how the public sector should respond to higher emissions and what are the direct costs that these policies might have. In the model, there are two types of firms, brown firms (which produce a polluting technology) and green firms. Brown firms also produce an externality, CO₂ emissions, which has detrimental effects on aggregate output. As brown firms do not face direct costs from polluting, they do not have incentives to reduce emissions. Notably, emissions in our model are global: the stock of CO₂ in the economy affects all countries, independently from where it is produced. This simplified economy captures the main trade-off between emissions and production, generating a classic market failure. According to our results, the current level of emission reduces output by between 0.4 and 0.75%. Notably, these estimates lay in the upper bound of the distribution of those delivered by studies in the early 2000s. To address market failure, governments should step in introducing taxes on emissions. With the tax, brown firms pay a cost for polluting hence facing the incentive to move to green technologies. Governments, however, might also adopt a beggar-thy-neighbour strategy. Reducing emissions is costly, as moves production away from the 'optimal' production mix of brown and green technology. Because emissions are global, a government could just wait for the other country to tackle climate change, ripping the benefits without facing any costs. We study how this strategic game unfolds and show three important results: first, cooperation is first-best optimal from a global prospective; second, countries face incentives to deviate from the cooperating equilibria; third, tariffs on imported brown goods (the only retaliation policy in case of deviation from the cooperation equilibrium) are ineffective because the exchange rate would move to compensate. We finally study monetary policy under when costs for climate change rise and show that the monetary authority should react stronger to deviations of inflation from its target.

Keywords: climate change, general equilibrium, optimal taxation, monetary policy

Procedia PDF Downloads 131

Authors: L. Bidyalakshmi, R. Ananthan, T. Longvah

Abstract:

Antioxidants are substances that can prevent or delay oxidative damage of lipids, proteins and nucleic acids by reactive oxygen species. These help in lowering incidence of degenerative diseases such as cancer, arthritis, atherosclerosis, heart disease, inflammation, brain dysfunction and acceleration of the ageing process. The north eastern part of India falls among the global hotspots of biodiversity. Over the years, the local communities in the region have developed ingenious uses of many wild plants within their environment as food sources. Many of these less familiar foods form an integral part of the diet of these communities, and some are traditionally valued for its therapeutic effects. So the study was carried to estimate the antioxidant activity of some of these indigenous foods. Twenty-eight indigenous plant foods were studied for their antioxidant activity. Antioxidant activities were determined by using DPPH (2, 2-diphenyl-1-picrylhydrazyl) assay, FRAP (Ferric Reducing Antioxidant Power) assay and SOSA (Super Oxide Scavenging Assay). Out of the twenty-eight plant foods, there were thirteen leafy vegetables, four fruits, five roots and tubers, four spices and two mushrooms. Water extract and methanol extract of the samples were used for the analysis. The leafy vegetable samples exhibited antioxidant capacity with IC50 ranging from 8-1414 mg/ml for lipid extract and 34-37878 mg/ml for aqueous extract in DPPH assay. Total FRAP value ranging from 58-1005 mmol FeSO4 Eq/100g of the sample, which is comparatively higher than the antioxidant capacity of some commonly consumed leafy vegetables. In SOSA, water extract of leafy vegetables show a range of 0.05-193.68 µmol ascorbic acid equivalent/g of the samples. While the methanol extract of the samples show 0.20-21.94 µmol Trolox equivalent/g of the samples. Polygonum barbatum, Wendlandia glabrata and Polygonum posumbu have higher antioxidant activity among the leafy vegetables analysed. Among the fruits, Rhus hookerii showed the highest antioxidant activities in both FRAP and SOSA methods while Spondias magnifera exhibited higher antioxidant activity in DPPH method. Alocasia cucullata exhibited higher antioxidant activity in DPPH and FRAP assays while Alpinia galanga showed higher antioxidant activity in SOSA assay when compared to the other samples of roots and tubers. Elsholtzia communis showed high antioxidant activity in all the three parameters among the spices. For the mushrooms, Pleurotus ostreatus exhibited higher antioxidant activity than Auricularia delicate in DPPH and SOSA. The samples analysed exhibited antioxidant activity at varying levels and some exhibited higher antioxidant activity than the commonly consumed foods. So consumption of these less familiar foods may play a role in preventing human disease in which free radicals are involved. Further studies on these food samples on phytonutrients and its contribution to the antioxidant activities are required.

Keywords: antioxidant activity, DPPH, FRAP, SOSA

Procedia PDF Downloads 255

Authors: Ionut Vintu, Stefan Laible, Ruth Schulz

Abstract:

Agricultural robotics has been developing steadily over recent years, with the goal of reducing and even eliminating pesticides used in crops and to increase productivity by taking over human labor. The majority of crops are arranged in rows. The first step towards autonomous robots, capable of driving in fields and performing crop-handling tasks, is for robots to robustly detect the rows of plants. Recent work done towards autonomous driving between plant rows offers big robotic platforms equipped with various expensive sensors as a solution to this problem. These platforms need to be driven over the rows of plants. This approach lacks flexibility and scalability when it comes to the height of plants or distance between rows. This paper proposes instead an algorithm that makes use of cheaper sensors and has a higher variability. The main application is in tree nurseries. Here, plant height can range from a few centimeters to a few meters. Moreover, trees are often removed, leading to gaps within the plant rows. The core idea is to combine row detection algorithms with graph-based localization methods as they are used in SLAM. Nodes in the graph represent the estimated pose of the robot, and the edges embed constraints between these poses or between the robot and certain landmarks. This setup aims to improve individual plant detection and deal with exception handling, like row gaps, which are falsely detected as an end of rows. Four methods were developed for detecting row structures in the fields, all using a point cloud acquired with a 3D LiDAR as an input. Comparing the field coverage and number of damaged plants, the method that uses a local map around the robot proved to perform the best, with 68% covered rows and 25% damaged plants. This method is further used and combined with a graph-based localization algorithm, which uses the local map features to estimate the robot’s position inside the greater field. Testing the upgraded algorithm in a variety of simulated fields shows that the additional information obtained from localization provides a boost in performance over methods that rely purely on perception to navigate. The final algorithm achieved a row coverage of 80% and an accuracy of 27% damaged plants. Future work would focus on achieving a perfect score of 100% covered rows and 0% damaged plants. The main challenges that the algorithm needs to overcome are fields where the height of the plants is too small for the plants to be detected and fields where it is hard to distinguish between individual plants when they are overlapping. The method was also tested on a real robot in a small field with artificial plants. The tests were performed using a small robot platform equipped with wheel encoders, an IMU and an FX10 3D LiDAR. Over ten runs, the system achieved 100% coverage and 0% damaged plants. The framework built within the scope of this work can be further used to integrate data from additional sensors, with the goal of achieving even better results.

Keywords: 3D LiDAR, agricultural robots, graph-based localization, row detection

Procedia PDF Downloads 105

Authors: Rose Branch-Allen, John Jayachandran

Abstract:

Background and purpose: Canada is a pluralistic, multicultural society with an ethno-cultural composition that has been shaped over time by immigrants and their descendants. Although Canada welcomes these immigrants, many will endure hardship and assimilation difficulties. Despite these life hurdles, surveys consistently disclose high life satisfaction for all Canadians. Most research studies on Life Satisfaction/ Subjective Wellbeing (SWB) have focused on one main determinant and a variety of social demographic variables to delineate the determinants of life satisfaction. However, very few research studies examine life satisfaction from a holistic approach. In addition, we need to understand the causal pathways leading to life satisfaction, and develop theories that explain why certain variables differentially influence the different components of SWB. The aim this study was to utilize a holistic approach to construct a causal model and identify major determinants of life satisfaction. Data and measures: This study utilized data from the General Social Survey, with a sample size of 19, 597. The exogenous concepts included age, gender, marital status, household size, socioeconomic status, ethnicity, location, immigration status, religiosity, and neighborhood. The intervening concepts included health, social contact, leisure, enjoyment, work-family balance, quality time, domestic labor, and sense of belonging. The endogenous concept life satisfaction was measured by multiple indicators (Cronbach’s alpha = .83). Analysis: Several multiple regression models were run sequentially to estimate path coefficients for the causal model. Results: Overall, above average satisfaction with life was reported for respondents with specific socio-economic, demographic and lifestyle characteristics. With regard to exogenous factors, respondents who were female, younger, married, from high socioeconomic status background, born in Canada, very religious, and demonstrated high level of neighborhood interaction had greater satisfaction with life. Similarly, intervening concepts suggested respondents had greater life satisfaction if they had better health, more social contact, less time on passive leisure activities and more time on active leisure activities, more time with family and friends, more enjoyment with volunteer activities, less time on domestic labor and a greater sense of belonging to the community. Conclusions and Implications: Our results suggest that a holistic approach is necessary for establishing determinants of life satisfaction, and that life satisfaction is not merely comprised of positive or negative affect rather understanding the causal process of life satisfaction. Even though, most of our findings are consistent with previous studies, a significant number of causal connections contradict some of the findings in literature today. We have provided possible explanation for these anomalies researchers encounter in studying life satisfaction and policy implications.

Keywords: causal model, holistic approach, life satisfaction, socio-demographic variables, subjective well-being

Procedia PDF Downloads 332

Authors: Supriya Majumder, Pabitra Banik

Abstract:

Fates of Arsenic (As) on the soil-plant environment belong to the critical emerging issue, which in turn to appraises the threatening implications of a human health risk — assessing the dynamics of As in soil solid components are likely to impose its potential availability towards plant uptake. In the present context, we introduced an improved Sequential Extraction Procedure (SEP) questioning to identify solid-phase speciation of As in paddy soil under variable soil environmental conditions during two consecutive seasons of rice cultivation practices. We coupled gradients of water management practices with the addition of fertilizer amendments to assess the changes in a partition of As through a field experimental study during monsoon and post-monsoon season using two rice cultivars. Water management regimes were varied based on the methods of cultivation of rice by Conventional (waterlogged) vis-a-vis System of Rice Intensification-SRI (saturated). Fertilizer amendment through the nutrient treatment of absolute control, NPK-RD, NPK-RD + Calcium silicate, NPK-RD + Ferrous sulfate, Farmyard manure (FYM), FYM + Calcium silicate, FYM + Ferrous sulfate, Vermicompost (VC), VC + Calcium silicate, VC + Ferrous sulfate were selected to construct the study. After harvest, soil samples were sequentially extracted to estimate partition of As among the different fractions such as: exchangeable (F1), specifically sorbed (F2), As bound to amorphous Fe oxides (F3), crystalline Fe oxides (F4), organic matter (F5) and residual phase (F6). Results showed that the major proportions of As were found in F3, F4 and F6, whereas F1 exhibited the lowest proportion of total soil As. Among the nutrient treatment mediated changes on As fractions, the application of organic manure and ferrous sulfate were significantly found to restrict the release of As from exchangeable phase. Meanwhile, conventional practice produced much higher release of As from F1 as compared to SRI, which may substantially increase the environmental risk. In contrast, SRI practice was found to retain a significantly higher proportion of As in F2, F3, and F4 phase resulting restricted mobilization of As. This was critically reflected towards rice grain As bioavailability where the reduction in grain As concentration of 33% and 55% in SRI concerning conventional treatment (p <0.05) during monsoon and post-monsoon season respectively. Also, prediction assay for rice grain As bioavailability based on the linear regression model was performed. Results demonstrated that rice grain As concentration was positively correlated with As concentration in F1 and negatively correlated with F2, F3, and F4 with a satisfactory level of variation being explained (p <0.001). Finally, we conclude that F1, F2, F3 and F4 are the major soil. As fractions critically may govern the potential availability of As in soil and suggest that rice cultivation with the SRI treatment is particularly at less risk of As availability in soil. Such exhaustive information may be useful for adopting certain management practices for rice grown in contaminated soil concerning to the environmental issues in particular.

Keywords: arsenic, fractionation, paddy soil, potential availability

Procedia PDF Downloads 102

Authors: F. Infante, W. Kaal, S. Perfetto, S. Herold

Abstract:

In the last decade the demand of wireless sensors and low-power electric devices for condition monitoring in mechanical structures has been strongly increased. Networks of wireless sensors can potentially be applied in a huge variety of applications. Due to the reduction of both size and power consumption of the electric components and the increasing complexity of mechanical systems, the interest of creating dense nodes sensor networks has become very salient. Nevertheless, with the development of large sensor networks with numerous nodes, the critical problem of powering them is drawing more and more attention. Batteries are not a valid alternative for consideration regarding lifetime, size and effort in replacing them. Between possible alternative solutions for durable power sources useable in mechanical components, vibrations represent a suitable source for the amount of power required to feed a wireless sensor network. For this purpose, energy harvesting from structural vibrations has received much attention in the past few years. Suitable vibrations can be found in numerous mechanical environments including automotive moving structures, household applications, but also civil engineering structures like buildings and bridges. Similarly, a dynamic vibration absorber (DVA) is one of the most used devices to mitigate unwanted vibration of structures. This device is used to transfer the primary structural vibration to the auxiliary system. Thus, the related energy is effectively localized in the secondary less sensitive structure. Then, the additional benefit of harvesting part of the energy can be obtained by implementing dedicated components. This paper describes the design process of an energy harvesting tuned vibration absorber (EHTVA) for rotating systems using piezoelectric elements. The energy of the vibration is converted into electricity rather than dissipated. The device proposed is indeed designed to mitigate torsional vibrations as with a conventional rotational TVA, while harvesting energy as a power source for immediate use or storage. The resultant rotational multi degree of freedom (MDOF) system is initially reduced in an equivalent single degree of freedom (SDOF) system. The Den Hartog’s theory is used for evaluating the optimal mechanical parameters of the initial DVA for the SDOF systems defined. The performance of the TVA is operationally assessed and the vibration reduction at the original resonance frequency is measured. Then, the design is modified for the integration of active piezoelectric patches without detuning the TVA. In order to estimate the real power generated, a complex storage circuit is implemented. A DC-DC step-down converter is connected to the device through a rectifier to return a fixed output voltage. Introducing a big capacitor, the energy stored is measured at different frequencies. Finally, the electromechanical prototype is tested and validated achieving simultaneously reduction and harvesting functions.

Keywords: energy harvesting, piezoelectricity, torsional vibration, vibration absorber

Procedia PDF Downloads 118

Authors: Andrea Ghermandi

Abstract:

Natural treatment systems such as constructed wetlands and waste stabilization ponds are increasingly used to treat water and wastewater from a variety of sources, including stormwater and polluted surface water. The provision of ancillary benefits in the form of cultural ecosystem services makes these systems unique among water and wastewater treatment technologies and greatly contributes to determine their potential role in promoting sustainable water management practices. A quantitative analysis of these benefits, however, has been lacking in the literature. Here, a critical assessment of the recreational and educational benefits in natural treatment systems is provided, which combines observed public use from a survey of managers and operators with estimated public use as obtained using geotagged photos from social media as a proxy for visitation rates. Geographic Information Systems (GIS) are used to characterize the spatial boundaries of 273 natural treatment systems worldwide. Such boundaries are used as input for the Application Program Interfaces (APIs) of two popular photo-sharing websites (Flickr and Panoramio) in order to derive the number of photo-user-days, i.e., the number of yearly visits by individual photo users in each site. The adequateness and predictive power of four univariate calibration models using the crowdsourced data as a proxy for visitation are evaluated. A high correlation is found between photo-user-days and observed annual visitors (Pearson's r = 0.811; p-value < 0.001; N = 62). Standardized Major Axis (SMA) regression is found to outperform Ordinary Least Squares regression and count data models in terms of predictive power insofar as standard verification statistics – such as the root mean square error of prediction (RMSEP), the mean absolute error of prediction (MAEP), the reduction of error (RE), and the coefficient of efficiency (CE) – are concerned. The SMA regression model is used to estimate the intensity of public use in all 273 natural treatment systems. System type, influent water quality, and area are found to statistically affect public use, consistently with a priori expectations. Publicly available information regarding the home location of the sampled visitors is derived from their social media profiles and used to infer the distance they are willing to travel to visit the natural treatment systems in the database. Such information is analyzed using the travel cost method to derive monetary estimates of the recreational benefits of the investigated natural treatment systems. Overall, the findings confirm the opportunities arising from an integrated design and management of natural treatment systems, which combines the objectives of water quality enhancement and provision of cultural ecosystem services through public use in a multi-functional approach and compatibly with the need to protect public health.

Keywords: constructed wetlands, cultural ecosystem services, ecological engineering, waste stabilization ponds

Procedia PDF Downloads 157

Authors: Elena Collino, Dario A. Ronzio, Goffredo Decimi, Maurizio Riva

Abstract:

The rapid increase of renewable energy in Italy is led by wind and solar installations. The 2017 Italian energy strategy foresees a further development of these sustainable technologies, especially solar. This fact has resulted in new opportunities, challenges, and different problems to deal with. The growth of renewables allows to meet the European requirements regarding energy and environmental policy, but these types of sources are difficult to manage because they are intermittent and non-programmable. Operationally, these characteristics can lead to instability on the voltage profile and increasing uncertainty on energy reserve scheduling. The increasing renewable production must be considered with more and more attention especially by the Transmission System Operator (TSO). The TSO, in fact, every day provides orders on energy dispatch, once the market outcome has been determined, on extended areas, defined mainly on the basis of power transmission limitations. In Italy, six market zone are defined: Northern-Italy, Central-Northern Italy, Central-Southern Italy, Southern Italy, Sardinia, and Sicily. An accurate hourly renewable power forecasting for the day-ahead on these extended areas brings an improvement both in terms of dispatching and reserve management. In this study, an operational forecasting tool of the hourly solar output for the six Italian market zones is presented, and the performance is analysed. The implementation is carried out by means of a numerical weather prediction model, coupled with a statistical post-processing in order to derive the power forecast on the basis of the meteorological projection. The weather forecast is obtained from the limited area model RAMS on the Italian territory, initialized with IFS-ECMWF boundary conditions. The post-processing calculates the solar power production with the Analog Ensemble technique (AN). This statistical approach forecasts the production using a probability distribution of the measured production registered in the past when the weather scenario looked very similar to the forecasted one. The similarity is evaluated for the components of the solar radiation: global (GHI), diffuse (DIF) and direct normal (DNI) irradiation, together with the corresponding azimuth and zenith solar angles. These are, in fact, the main factors that affect the solar production. Considering that the AN performance is strictly related to the length and quality of the historical data a training period of more than one year has been used. The training set is made by historical Numerical Weather Prediction (NWP) forecasts at 12 UTC for the GHI, DIF and DNI variables over the Italian territory together with corresponding hourly measured production for each of the six zones. The AN technique makes it possible to estimate the aggregate solar production in the area, without information about the technologic characteristics of the all solar parks present in each area. Besides, this information is often only partially available. Every day, the hourly solar power forecast for the six Italian market zones is made publicly available through a website.

Keywords: analog ensemble, electricity market, PV forecast, solar energy

Procedia PDF Downloads 127

Authors: S. Sabatino, V. Calderaro, V. Galdi, G. Graber, L. Ippolito

Abstract:

Climate change is a rapidly growing global threat caused mainly by increased emissions of carbon dioxide (CO₂) into the atmosphere. These emissions come from multiple sources, including industry, power generation, and the transport sector. The need to tackle climate change and reduce CO₂ emissions is indisputable. A crucial solution to achieving decarbonization in the transport sector is the adoption of electric vehicles (EVs). These vehicles use lithium (Li-Ion) batteries as an energy source, making them extremely efficient and with low direct emissions. However, Li-Ion batteries are not without problems, including the risk of overheating and performance degradation. To ensure its safety and longevity, it is essential to use a battery management system (BMS). The BMS constantly monitors battery status, adjusts temperature and cell balance, ensuring optimal performance and preventing dangerous situations. From the monitoring carried out, it is also able to optimally manage the battery to increase its life. Among the parameters monitored by the BMS, the main ones are State of Charge (SoC), State of Health (SoH), and State of Power (SoP). The evaluation of these parameters can be carried out in two ways: offline, using benchtop batteries tested in the laboratory, or online, using batteries installed in moving vehicles. Online estimation is the preferred approach, as it relies on capturing real-time data from batteries while operating in real-life situations, such as in everyday EV use. Actual battery usage conditions are highly variable. Moving vehicles are exposed to a wide range of factors, including temperature variations, different driving styles, and complex charge/discharge cycles. This variability is difficult to replicate in a controlled laboratory environment and can greatly affect performance and battery life. Online estimation captures this variety of conditions, providing a more accurate assessment of battery behavior in real-world situations. In this article, a hybrid approach based on a neural network and a statistical method for real-time estimation of SoC, SoH, and SoP parameters of interest is proposed. These parameters are estimated from the analysis of a one-day driving profile of an electric vehicle, assumed to be divided into the following four phases: (i) Partial discharge (SoC 100% - SoC 50%), (ii) Partial discharge (SoC 50% - SoC 80%), (iii) Deep Discharge (SoC 80% - SoC 30%) (iv) Full charge (SoC 30% - SoC 100%). The neural network predicts the values of ohmic resistance and incremental capacity, while the statistical method is used to estimate the parameters of interest. This reduces the complexity of the model and improves its prediction accuracy. The effectiveness of the proposed model is evaluated by analyzing its performance in terms of square mean error (RMSE) and percentage error (MAPE) and comparing it with the reference method found in the literature.

Keywords: electric vehicle, Li-Ion battery, BMS, state-of-charge, state-of-health, state-of-power, artificial neural networks

Procedia PDF Downloads 40

Authors: Damian Graham, Ashleigh H. Hall, Damani R. Sulph, Michael A. James, Shawn B. Vassell

Abstract:

This paper assesses the design and feasibility of a Materials Recovery Facility (MRF) in Jamaica as a possible green industry approach to the nation’s economic and solid waste management problems. Jamaica is a developing nation that is vulnerable to climate change that can affect its blue economy and tourism on which it is heavily reliant. Jamaica’s National Solid Waste Management Authority (NSWMA) collects only a fraction of all the solid waste produced annually which is then transported to dumpsites. The remainder is either burnt by the population or disposed of illegally. These practices negatively impact the environment, threaten the sustainability of economic growth from blue economy and tourism and its waste management system is predominantly a cost centre. The implementation of an MRF could boost the manufacturing sector, contribute to economic growth, and be a catalyst in creating a green industry with multiple downstream value chains with supply chain linkages. Globally, there is a trend to reuse and recycle that created an international market for recycled solid waste. MRFs enable the efficient sorting of solid waste into desired recoverable materials thus providing a gateway for entrance to the international trading of recycled waste. Research into the current state and effort to improve waste management in Jamaica in contrast with the similar and more advanced territories are outlined. The study explores the concept of green industrialization and its applicability to vulnerable small state economies like Jamaica. The study highlights the possible contributions and benefits derived from MRFs as a seeding factory that can anchor the reverse and forward logistics of other green industries as part of a logistic-cantered economy. Further, the study showcases an engineering economic analysis that assesses the viability of the implementation of an MRF in Jamaica. This research outlines the potential cost of constructing and operating an MRF and provides a realistic cash flow estimate to establish a baseline for profitability. The approach considers quantitative and qualitative data, assumptions, and modelling using industrial engineering tools and techniques that are outlined. Techniques of facility planning, system analysis and operations research with a focus on linear programming techniques are expressed. Approaches to overcome some implementation challenges including policy, technology and public education are detailed. The results of this study present a reasonable judgment of the prospects of incorporating an MRF to improve Jamaica’s solid waste management and contribute to socioeconomic and environmental benefits and an alternate pathway for economic sustainability.

Keywords: engineering-economic analysis, facility design, green industry, MRF, manufacturing, plant layout, solid-waste management, sustainability, waste disposal

Procedia PDF Downloads 192

Authors: Casta Guillaume, Robert Jagers, Deborah Rivas-Drake

Abstract:

Civically engaged youth are critical to maintaining and/or improving the functioning of local, national and global communities and their institutions. The present study investigated how school climate and academic beliefs (academic self-efficacy and school belonging) may inform emergent civic behaviors (emergent citizenship) among self-identified middle school youth of color (African American, Multiracial or Mixed, Latino, Asian American or Pacific Islander, Native American, and other). Study aims: 1) Understand whether and how school climate is associated with civic engagement behaviors, directly and indirectly, by fostering a positive sense of connection to the school and/or engendering feelings of self-efficacy in the academic domain. Accordingly, we examined 2) The association of youths’ sense of school connection and academic self-efficacy with their personally responsible and participatory civic behaviors in school and community contexts—both concurrently and longitudinally. Data from two subsamples of a larger study of social/emotional development among middle school students were used for longitudinal and cross sectional analysis. The cross-sectional sample included 324 6th-8th grade students, of which 43% identified as African American, 20% identified as Multiracial or Mixed, 18% identified as Latino, 12% identified as Asian American or Pacific Islander, 6% identified as Other, and 1% identified as Native American. The age of the sample ranged from 11 – 15 (M = 12.33, SD = .97). For the longitudinal test of our mediation model, we drew on data from the 6th and 7th grade cohorts only (n =232); the ethnic and racial diversity of this longitudinal subsample was virtually identical to that of the cross-sectional sample. For both the cross-sectional and longitudinal analyses, full information maximum likelihood was used to deal with missing data. Fit indices were inspected to determine if they met the recommended thresholds of RMSEA below .05 and CFI and TLI values of at least .90. To determine if particular mediation pathways were significant, the bias-corrected bootstrap confidence intervals for each indirect pathway were inspected. Fit indices for the latent variable mediation model using the cross-sectional data suggest that the hypothesized model fit the observed data well (CFI = .93; TLI =. 92; RMSEA = .05, 90% CI = [.04, .06]). In the model, students’ perceptions of school climate were significantly and positively associated with greater feelings of school connectedness, which were in turn significantly and positively associated with civic engagement. In addition, school climate was significantly and positively associated with greater academic self-efficacy, but academic self-efficacy was not significantly associated with civic engagement. Tests of mediation indicated there was one significant indirect pathway between school climate and civic engagement behavior. There was an indirect association between school climate and civic engagement via its association with sense of school connectedness, indirect association estimate = .17 [95% CI: .08, .32]. The aforementioned indirect association via school connectedness accounted for 50% (.17/.34) of the total effect. Partial support was found for the prediction that students’ perceptions of a positive school climate are linked to civic engagement in part through their role in students’ sense of connection to school.

Keywords: civic engagement, early adolescence, school climate, school belonging, developmental niche

Procedia PDF Downloads 343