Search results for: agricultural plant extract
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6651

Search results for: agricultural plant extract

3321 Monitoring and Improving Performance of Soil Aquifer Treatment System and Infiltration Basins Performance: North Gaza Emergency Sewage Treatment Plant as Case Study

Authors: Sadi Ali, Yaser Kishawi

Abstract:

As part of Palestine, Gaza Strip (365 km2 and 1.8 million habitants) is considered a semi-arid zone relies solely on the Coastal Aquifer. The coastal aquifer is only source of water with only 5-10% suitable for human use. This barely cover the domestic and agricultural needs of Gaza Strip. Palestinian Water Authority Strategy is to find non-conventional water resource from treated wastewater to irrigate 1500 hectares and serves over 100,000 inhabitants. A new WWTP project is to replace the old-overloaded Biet Lahia WWTP. The project consists of three parts; phase A (pressure line & 9 infiltration basins - IBs), phase B (a new WWTP) and phase C (Recovery and Reuse Scheme – RRS – to capture the spreading plume). Currently, phase A is functioning since Apr 2009. Since Apr 2009, a monitoring plan is conducted to monitor the infiltration rate (I.R.) of the 9 basins. Nearly 23 million m3 of partially treated wastewater were infiltrated up to Jun 2014. It is important to maintain an acceptable rate to allow the basins to handle the coming quantities (currently 10,000 m3 are pumped an infiltrated daily). The methodology applied was to review and analysis the collected data including the I.R.s, the WW quality and the drying-wetting schedule of the basins. One of the main findings is the relation between the Total Suspended Solids (TSS) at BLWWTP and the I.R. at the basins. Since April 2009, the basins scored an average I.R. of about 2.5 m/day. Since then the records showed a decreasing pattern of the average rate until it reached the lower value of 0.42 m/day in Jun 2013. This was accompanied with an increase of TSS (mg/L) concentration at the source reaching above 200 mg/L. The reducing of TSS concentration directly improved the I.R. (by cleaning the WW source ponds at Biet Lahia WWTP site). This was reflected in an improvement in I.R. in last 6 months from 0.42 m/day to 0.66 m/day then to nearly 1.0 m/day as the average of the last 3 months of 2013. The wetting-drying scheme of the basins was observed (3 days wetting and 7 days drying) besides the rainfall rates. Despite the difficulty to apply this scheme accurately a control of flow to each basin was applied to improve the I.R. The drying-wetting system affected the I.R. of individual basins, thus affected the overall system rate which was recorded and assessed. Also the ploughing activities at the infiltration basins as well were recommended at certain times to retain a certain infiltration level. This breaks the confined clogging layer which prevents the infiltration. It is recommended to maintain proper quality of WW infiltrated to ensure an acceptable performance of IBs. The continual maintenance of settling ponds at BLWWTP, continual ploughing of basins and applying soil treatment techniques at the IBs will improve the I.R.s. When the new WWTP functions a high standard effluent quality (TSS 20mg, BOD 20 mg/l and TN 15 mg/l) will be infiltrated, thus will enhance I.R.s of IBs due to lower organic load.

Keywords: SAT, wastewater quality, soil remediation, North Gaza

Procedia PDF Downloads 232
3320 Variation of Litter Chemistry under Intensified Drought: Consequences on Flammability

Authors: E. Ormeno, C. Gutigny, J. Ruffault, J. Madrigal, M. Guijarro, C. Lecareux, C. Ballini

Abstract:

Mediterranean plant species feature numerous metabolic and morpho-physiological responses crucial to survive under both, typical Mediterranean drought conditions and future aggravated drought expected by climate change. Whether these adaptive responses will, in turn, increase the ecosystem perturbation in terms of fire hazard, is an issue that needs to be addressed. The aim of this study was to test whether recurrent and aggravated drought in the Mediterranean area favors the accumulation of waxes in leaf litter, with an eventual increase of litter flammability. The study was conducted in 2017 in a garrigue in Southern France dominated by Quercus coccifera, where two drought treatments were used: a treatment with recurrent aggravated drought consisting of ten rain exclusion structures which withdraw part of the annual precipitation since January 2012, and a natural drought treatment where Q. coccifera stands are free of such structures and thus grow under natural precipitation. Waxes were extracted with organic solvent and analyzed by GC-MS and litter flammability was assessed through measurements of the ignition delay, flame residence time and flame intensity (flame height) using an epiradiator as well as the heat of combustion using an oxygen bomb calorimeter. Results show that after 5 years of rain restriction, wax content in the cuticle of leaf litter increases significantly compared to shrubs growing under natural precipitation, in accordance with the theoretical knowledge which expects increases of cuticle waxes in green leaves in order to limit water evapotranspiration. Wax concentrations were also linearly and positively correlated to litter flammability, a correlation that lies on the high flammability own to the long-chain alkanes (C25-C31) found in leaf litter waxes. This innovative investigation shows that climate change is likely to favor ecosystem fire hazard through accumulation of highly flammable waxes in litter. It also adds valuable information about the types of metabolites that are associated with increasing litter flammability, since so far, within the leaf metabolic profile, only terpene-like compounds had been related to plant flammability.

Keywords: cuticular waxes, drought, flammability, litter

Procedia PDF Downloads 166
3319 Regulation of the Regeneration of Epidermal Langerhans Cells by Stress Hormone

Authors: Junichi Hosoi

Abstract:

Epidermal Langerhans cells reside in upper layer of epidermis and play a role in immune surveillance. The finding of the close association of nerve endings to Langerhans cells triggered the research on systemic regulation of Langerhans cells. They disappear from epidermis after exposure to environmental and internal stimuli and reappear about a week later. Myeloid progenitor cells are assumed to be one of the sources of Langerhans cells. We examined the effects of cortisol on the reappearance of Langerhans cells in vitro. Cord-blood derived CD34-positive cells were cultured in the medium supplemented with stem cell factor/Flt3 ligand/granulocyte macrophage-colony stimulating factor/tumor necrosis factor alpha/bone morphologic protein 7/transforming growth factor beta in the presence or absence of cortisol. Cells were analyzed by flow cytometry for CD1a (cluster differentiation 1a), a marker of Langerhans cells and dermal dendritic cells, and CD39 (cluster differentiation factor 39), extracellular adenosine triphosphatase. Both CD1a-positive cells and CD39-positive cells were decreased by treatment with cortisol (suppression by 35% and 22% compared to no stress hormone, respectively). Differentiated Langerhans cells are attracted to epidermis by chemokines that are secreted from keratinocytes. Epidermal keratinocytes were cultured in the presence or absence of cortisol and analyzed for the expression of CCL2 (C-C motif chemokine ligand 2) and CCL20 (C-C motif chemokine ligand 20), which are typical attractants of Langerhans cells, by quantitative reverse transcriptase polymerase chain reaction. The expression of both chemokines, CCL2 and CCL20, were suppressed by treatment with cortisol (suppression by 38% and 48% compared to no stress hormone, respectively). We examined the possible regulation of the suppression by cortisol with plant extracts. The extracts of Ganoderma lucidum and Iris protected the suppression of the differentiation to CD39-positive cells and also the suppression of the gene expression of LC-chemoattractants. These results suggest that cortisol, which is either systemic or locally produced, blocks the supply of epidermal Langerhans cells at 2 steps, differentiation from the precursor and attraction to epidermis. The suppression is possibly blocked by some plant extracts.

Keywords: Langerhans cell, stress, CD39, chemokine

Procedia PDF Downloads 177
3318 Identification of Dynamic Friction Model for High-Precision Motion Control

Authors: Martin Goubej, Tomas Popule, Alois Krejci

Abstract:

This paper deals with experimental identification of mechanical systems with nonlinear friction characteristics. Dynamic LuGre friction model is adopted and a systematic approach to parameter identification of both linear and nonlinear subsystems is given. The identification procedure consists of three subsequent experiments which deal with the individual parts of plant dynamics. The proposed method is experimentally verified on an industrial-grade robotic manipulator. Model fidelity is compared with the results achieved with a static friction model.

Keywords: mechanical friction, LuGre model, friction identification, motion control

Procedia PDF Downloads 407
3317 Analysis of the Significance of Multimedia Channels Using Sparse PCA and Regularized SVD

Authors: Kourosh Modarresi

Abstract:

The abundance of media channels and devices has given users a variety of options to extract, discover, and explore information in the digital world. Since, often, there is a long and complicated path that a typical user may venture before taking any (significant) action (such as purchasing goods and services), it is critical to know how each node (media channel) in the path of user has contributed to the final action. In this work, the significance of each media channel is computed using statistical analysis and machine learning techniques. More specifically, “Regularized Singular Value Decomposition”, and “Sparse Principal Component” has been used to compute the significance of each channel toward the final action. The results of this work are a considerable improvement compared to the present approaches.

Keywords: multimedia attribution, sparse principal component, regularization, singular value decomposition, feature significance, machine learning, linear systems, variable shrinkage

Procedia PDF Downloads 306
3316 Crude Palm Oil Antioxidant Extraction and the Antioxidation Activity

Authors: Supriyono Supriyono, Sumardiyono Sumardiyono, Peni Pujiastuti, Dian Indriana Hapsari

Abstract:

Crude palm oil (CPO) is a vegetable oil that came from a palm tree bunch. The productivity of the oil is 12 ton/hectare/year. Thus palm oil tree was known as highest vegetable oil yield. It was grown across Equatorial County, especially in Malaysia and Indonesia. The greenish-red color on CPO was come from carotenoid. Carotenoid is one of the antioxidants that could be extracted. Carotenoid could be used as functional food and other purposes. Another antioxidant that also found in CPO is tocopherol. The aim of the research work is to find antioxidant activity on CPO comparing to the synthetic antioxidant that available in a market. In this research work, antioxidant was extracted by a mixture of acetone and n.hexane, while the activity of the antioxidant extract was determined by DPPH method. Antioxidant activity of the extracted compound about 46% compared to pure tocopherol. While the solvent mixture compose by 90% acetone and 10% n. hexane meet the best on the antioxidant activity.

Keywords: antioxidant, beta carotene, crude palm oil, DPPH, tocopherol

Procedia PDF Downloads 202
3315 Robust Features for Impulsive Noisy Speech Recognition Using Relative Spectral Analysis

Authors: Hajer Rahali, Zied Hajaiej, Noureddine Ellouze

Abstract:

The goal of speech parameterization is to extract the relevant information about what is being spoken from the audio signal. In speech recognition systems Mel-Frequency Cepstral Coefficients (MFCC) and Relative Spectral Mel-Frequency Cepstral Coefficients (RASTA-MFCC) are the two main techniques used. It will be shown in this paper that it presents some modifications to the original MFCC method. In our work the effectiveness of proposed changes to MFCC called Modified Function Cepstral Coefficients (MODFCC) were tested and compared against the original MFCC and RASTA-MFCC features. The prosodic features such as jitter and shimmer are added to baseline spectral features. The above-mentioned techniques were tested with impulsive signals under various noisy conditions within AURORA databases.

Keywords: auditory filter, impulsive noise, MFCC, prosodic features, RASTA filter

Procedia PDF Downloads 420
3314 Bio-Hub Ecosystems: Profitability through Circularity for Sustainable Forestry, Energy, Agriculture and Aquaculture

Authors: Kimberly Samaha

Abstract:

The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding biomass as a feedstock for power plants. Yet the lack of an economically-viable business model for bioenergy facilities has resulted in the continuation of idled and decommissioned plants. This study analyzed data and submittals to the Born Global Maine Innovation Challenge. The Innovation Challenge was a global innovation challenge to identify process innovations that could address a ‘whole-tree’ approach of maximizing the products, byproducts, energy value and process slip-streams into a circular zero-waste design. Participating companies were at various stages of developing bioproducts and included biofuels, lignin-based products, carbon capture platforms and biochar used as both a filtration medium and as a soil amendment product. This case study shows the QCA (Qualitative Comparative Analysis) methodology of the prequalification process and the resulting techno-economic model that was developed for the maximizing profitability of the Bio-Hub Ecosystem through continuous expansion of system waste streams into valuable process inputs for co-hosts. A full site plan for the integration of co-hosts (biorefinery, land-based shrimp and salmon aquaculture farms, a tomato green-house and a hops farm) at an operating forestry-based biomass to energy plant in West Enfield, Maine USA. This model and process for evaluating the profitability not only proposes models for integration of forestry, aquaculture and agriculture in cradle-to-cradle linkages of what have typically been linear systems, but the proposal also allows for the early measurement of the circularity and impact of resource use and investment risk mitigation, for these systems. In this particular study, profitability is assessed at two levels CAPEX (Capital Expenditures) and in OPEX (Operating Expenditures). Given that these projects start with repurposing facilities where the industrial level infrastructure is already built, permitted and interconnected to the grid, the addition of co-hosts first realizes a dramatic reduction in permitting, development times and costs. In addition, using the biomass energy plant’s waste streams such as heat, hot water, CO₂ and fly ash as valuable inputs to their operations and a significant decrease in the OPEX costs, increasing overall profitability to each of the co-hosts bottom line. This case study utilizes a proprietary techno-economic model to demonstrate how utilizing waste streams of a biomass energy plant and/or biorefinery, results in significant reduction in OPEX for both the biomass plants and the agriculture and aquaculture co-hosts. Economically viable Bio-Hubs with favorable environmental and community impacts may prove critical in garnering local and federal government support for pilot programs and more wide-scale adoption, especially for those living in severely economically depressed rural areas where aging industrial sites have been shuttered and local economies devastated.

Keywords: bio-economy, biomass energy, financing, zero-waste

Procedia PDF Downloads 127
3313 Superordinated Control for Increasing Feed-in Capacity and Improving Power Quality in Low Voltage Distribution Grids

Authors: Markus Meyer, Bastian Maucher, Rolf Witzmann

Abstract:

The ever increasing amount of distributed generation in low voltage distribution grids (mainly PV and micro-CHP) can lead to reverse load flows from low to medium/high voltage levels at times of high feed-in. Reverse load flow leads to rising voltages that may even exceed the limits specified in the grid codes. Furthermore, the share of electrical loads connected to low voltage distribution grids via switched power supplies continuously increases. In combination with inverter-based feed-in, this results in high harmonic levels reducing overall power quality. Especially high levels of third-order harmonic currents can lead to neutral conductor overload, which is even more critical if lines with reduced neutral conductor section areas are used. This paper illustrates a possible concept for smart grids in order to increase the feed-in capacity, improve power quality and to ensure safe operation of low voltage distribution grids at all times. The key feature of the concept is a hierarchically structured control strategy that is run on a superordinated controller, which is connected to several distributed grid analyzers and inverters via broad band powerline (BPL). The strategy is devised to ensure both quick response time as well as the technically and economically reasonable use of the available inverters in the grid (PV-inverters, batteries, stepless line voltage regulators). These inverters are provided with standard features for voltage control, e.g. voltage dependent reactive power control. In addition they can receive reactive power set points transmitted by the superordinated controller. To further improve power quality, the inverters are capable of active harmonic filtering, as well as voltage balancing, whereas the latter is primarily done by the stepless line voltage regulators. By additionally connecting the superordinated controller to the control center of the grid operator, supervisory control and data acquisition capabilities for the low voltage distribution grid are enabled, which allows easy monitoring and manual input. Such a low voltage distribution grid can also be used as a virtual power plant.

Keywords: distributed generation, distribution grid, power quality, smart grid, virtual power plant, voltage control

Procedia PDF Downloads 264
3312 The Effects of Drought and Nitrogen on Soybean (Glycine max (L.) Merrill) Physiology and Yield

Authors: Oqba Basal, András Szabó

Abstract:

Legume crops are able to fix atmospheric nitrogen by the symbiotic relation with specific bacteria, which allows the use of the mineral nitrogen-fertilizer to be reduced, or even excluded, resulting in more profit for the farmers and less pollution for the environment. Soybean (Glycine max (L.) Merrill) is one of the most important legumes with its high content of both protein and oil. However, it is recommended to combine the two nitrogen sources under stress conditions in order to overcome its negative effects. Drought stress is one of the most important abiotic stresses that increasingly limits soybean yields. A precise rate of mineral nitrogen under drought conditions is not confirmed, as it depends on many factors; soybean yield-potential and soil-nitrogen content to name a few. An experiment was conducted during 2017 growing season in Debrecen, Hungary to investigate the effects of nitrogen source on the physiology and the yield of the soybean cultivar 'Boglár'. Three N-fertilizer rates including no N-fertilizer (0 N), 35 kg ha-1 of N-fertilizer (35 N) and 105 kg ha-1 of N-fertilizer (105 N) were applied under three different irrigation regimes; severe drought stress (SD), moderate drought stress (MD) and control with no drought stress (ND). Half of the seeds in each treatment were pre-inoculated with Bradyrhizobium japonicum inoculant. The overall results showed significant differences associated with fertilization and irrigation, but not with inoculation. Increasing N rate was mostly accompanied with increased chlorophyll content and leaf area index, whereas it positively affected the plant height only when the drought was waived off. Plant height was the lowest under severe drought, regardless of inoculation and N-fertilizer application and rate. Inoculation increased the yield when there was no drought, and a low rate of N-fertilizer increased the yield furthermore; however, the high rate of N-fertilizer decreased the yield to a level even less than the inoculated control. On the other hand, the yield of non-inoculated plants increased as the N-fertilizer rate increased. Under drought conditions, adding N-fertilizer increased the yield of the non-inoculated plants compared to their inoculated counterparts; moreover, the high rate of N-fertilizer resulted in the best yield. Regardless of inoculation, the mean yield of the three fertilization rates was better when the water amount increased. It was concluded that applying N-fertilizer to provide the nitrogen needed by soybean plants, with the absence of N2-fixation process, is very important. Moreover, adding relatively high rate of N-fertilizer is very important under severe drought stress to alleviate the drought negative effects. Further research to recommend the best N-fertilizer rate to inoculated soybean under drought stress conditions should be executed.

Keywords: drought stress, inoculation, N-fertilizer, soybean physiology, yield

Procedia PDF Downloads 148
3311 In-situ Phytoremediation Of Polluted Soils By Micropollutants From Artisanal Gold Mining Processes In Burkina Faso

Authors: Yamma Rose, Kone Martine, Yonli Arsène, Wanko Ngnien Adrien

Abstract:

Artisanal gold mining has seen a resurgence in recent years in Burkina Faso with its corollary of soil and water pollution. Indeed, in addition to visible impacts, it generates discharges rich in trace metal elements and acids. This pollution has significant environmental consequences, making these lands unusable while the population depends on the natural environment for its survival. The goal of this study is to assess the decontamination potential of Chrysopogon zizanioides on two artisanal gold processing sites in Burkina Faso. The cyanidation sites of Nebia (1Ha) and Nimbrogo (2Ha) located respectively in the Central West and Central South regions were selected. The soils were characterized to determine the initial pollution levels before the implementation of phytoremediation. After development of the site, parallel trenches equidistant 6 m apart, 30 cm deep, 40 cm wide and opposite to the water flow direction were dug and filled with earth amended with manure. The Chrysopogon zizanioides plants were transplanted 5 cm equidistant into the trenches. The mere fact that Chrysopogon zizanioides grew in the polluted soil is an indication that this plant tolerates and resists the toxicity of trace elements present on the site. The characterization shows sites very polluted with free cyanide 900 times higher than the national standard, the level of Hg in the soil is 5 times more than the limit value, iron and Zn are respectively 1000 times and 200 more than the tolerated environmental value. At time T1 (6 months) and T2 (12 months) of culture, Chrysopogon zizanioides showed less development on the Nimbrogo site than that of the Nebia site. Plant shoots and associated soil samples were collected and analyzed for total As, Hg, Fe and Zn concentration. The trace element content of the soil, the bioaccumulation factor and the hyper accumulation thresholds were also determined to assess the remediation potential. The concentration of As and Hg in the soil was below international risk thresholds, while that of Fe and Zn was well above these thresholds. The CN removal efficiency at the Nebia site is respectively 29.90% and 68.62% compared to 6.6% and 60.8% at Nimbrogo at time T1 and T2.

Keywords: chrysopogon zizanioides, in-situ phytoremediation, polluted soils, micropollutants

Procedia PDF Downloads 70
3310 An Ensemble-based Method for Vehicle Color Recognition

Authors: Saeedeh Barzegar Khalilsaraei, Manoocheher Kelarestaghi, Farshad Eshghi

Abstract:

The vehicle color, as a prominent and stable feature, helps to identify a vehicle more accurately. As a result, vehicle color recognition is of great importance in intelligent transportation systems. Unlike conventional methods which use only a single Convolutional Neural Network (CNN) for feature extraction or classification, in this paper, four CNNs, with different architectures well-performing in different classes, are trained to extract various features from the input image. To take advantage of the distinct capability of each network, the multiple outputs are combined using a stack generalization algorithm as an ensemble technique. As a result, the final model performs better than each CNN individually in vehicle color identification. The evaluation results in terms of overall average accuracy and accuracy variance show the proposed method’s outperformance compared to the state-of-the-art rivals.

Keywords: Vehicle Color Recognition, Ensemble Algorithm, Stack Generalization, Convolutional Neural Network

Procedia PDF Downloads 75
3309 Monitoring and Improving Performance of Soil Aquifer Treatment System and Infiltration Basins of North Gaza Emergency Sewage Treatment Plant as Case Study

Authors: Sadi Ali, Yaser Kishawi

Abstract:

As part of Palestine, Gaza Strip (365 km2 and 1.8 million habitants) is considered a semi-arid zone relies solely on the Coastal Aquifer. The coastal aquifer is only source of water with only 5-10% suitable for human use. This barely covers the domestic and agricultural needs of Gaza Strip. Palestinian Water Authority Strategy is to find non-conventional water resource from treated wastewater to irrigate 1500 hectares and serves over 100,000 inhabitants. A new WWTP project is to replace the old-overloaded Biet Lahia WWTP. The project consists of three parts; phase A (pressure line & 9 infiltration basins - IBs), phase B (a new WWTP) and phase C (Recovery and Reuse Scheme – RRS – to capture the spreading plume). Currently, phase A is functioning since Apr 2009. Since Apr 2009, a monitoring plan is conducted to monitor the infiltration rate (I.R.) of the 9 basins. Nearly 23 million m3 of partially treated wastewater were infiltrated up to Jun 2014. It is important to maintain an acceptable rate to allow the basins to handle the coming quantities (currently 10,000 m3 are pumped an infiltrated daily). The methodology applied was to review and analysis the collected data including the I.R.s, the WW quality and the drying-wetting schedule of the basins. One of the main findings is the relation between the Total Suspended Solids (TSS) at BLWWTP and the I.R. at the basins. Since April 2009, the basins scored an average I.R. of about 2.5 m/day. Since then the records showed a decreasing pattern of the average rate until it reached the lower value of 0.42 m/day in Jun 2013. This was accompanied with an increase of TSS (mg/L) concentration at the source reaching above 200 mg/L. The reducing of TSS concentration directly improved the I.R. (by cleaning the WW source ponds at Biet Lahia WWTP site). This was reflected in an improvement in I.R. in last 6 months from 0.42 m/day to 0.66 m/day then to nearly 1.0 m/day as the average of the last 3 months of 2013. The wetting-drying scheme of the basins was observed (3 days wetting and 7 days drying) besides the rainfall rates. Despite the difficulty to apply this scheme accurately a control of flow to each basin was applied to improve the I.R. The drying-wetting system affected the I.R. of individual basins, thus affected the overall system rate which was recorded and assessed. Also the ploughing activities at the infiltration basins as well were recommended at certain times to retain a certain infiltration level. This breaks the confined clogging layer which prevents the infiltration. It is recommended to maintain proper quality of WW infiltrated to ensure an acceptable performance of IBs. The continual maintenance of settling ponds at BLWWTP, continual ploughing of basins and applying soil treatment techniques at the IBs will improve the I.R.s. When the new WWTP functions a high standard effluent quality (TSS 20mg, BOD 20 mg/l, and TN 15 mg/l) will be infiltrated, thus will enhance I.R.s of IBs due to lower organic load.

Keywords: soil aquifer treatment, recovery and reuse scheme, infiltration basins, North Gaza

Procedia PDF Downloads 239
3308 Anticancer Activity of Gnidia glauca Extracts in Human Breast Cancer Cells

Authors: Vandana Gawande, Chandani Satija

Abstract:

Gnidia glauca is a semi-woody herb of thymelaeaceae family traditionally used as fish poison in India. It is also found in Sri lanka and Africa. In the present study, potential anticancer effect of n-hexane and ethanolic extracts of Gnidia glauca in human breast cancer cells was investigated. Human breast cancer cells (MCF-7) were cultured as monolayers in RPMI 1640 medium. The cells were cultured for 48 hours to allow growth and achieve about 80% confluence in 96-well culture plates. The cells were treated with various concentrations of Gnidia glauca (0.1-100 mg/mL) for 72 hours. Percentage of viable cells after treatment was assessed using a sulforhodamine B colorimetric assay. Both n-hexane and ethanolic extract showed significant cytotoxic activity on MCF-7 cancer cells. This study supports the notion of using Gnidia glauca as a novel anticancer agent for breast cancer.

Keywords: 96 well plate, anticancer activity, Gnidia glauca, MCF-7

Procedia PDF Downloads 283
3307 Timing and Noise Data Mining Algorithm and Software Tool in Very Large Scale Integration (VLSI) Design

Authors: Qing K. Zhu

Abstract:

Very Large Scale Integration (VLSI) design becomes very complex due to the continuous integration of millions of gates in one chip based on Moore’s law. Designers have encountered numerous report files during design iterations using timing and noise analysis tools. This paper presented our work using data mining techniques combined with HTML tables to extract and represent critical timing/noise data. When we apply this data-mining tool in real applications, the running speed is important. The software employs table look-up techniques in the programming for the reasonable running speed based on performance testing results. We added several advanced features for the application in one industry chip design.

Keywords: VLSI design, data mining, big data, HTML forms, web, VLSI, EDA, timing, noise

Procedia PDF Downloads 250
3306 Aromatic and Medicinal Plants in Morocco: Diversity and Socio-Economic Role

Authors: Mohammed Sghir Taleb

Abstract:

Morocco is characterized by a great richness and diversity in aromatic and medicinal plants and it has an ancestral knowledge in the use of plants for medicinal and cosmetic purposes. In effect, the poverty of riparian, specially, mountain populations have greatly contributed to the development of traditional pharmacopoeia in Morocco. The analysis of the bibliographic data showed that a large number of plants in Morocco are exploited for aromatic and medicinal purposes and several of them are commercialized internationally. However, these potentialities of aromatic and medicinal plants are currently subjected to climate change and strong human pressures: Collecting fruits, agriculture development, harvesting plants, urbanization, overgrazing...

Keywords: aromatic, medicinal, plant, Morocco

Procedia PDF Downloads 296
3305 Classification Rule Discovery by Using Parallel Ant Colony Optimization

Authors: Waseem Shahzad, Ayesha Tahir Khan, Hamid Hussain Awan

Abstract:

Ant-Miner algorithm that lies under ACO algorithms is used to extract knowledge from data in the form of rules. A variant of Ant-Miner algorithm named as cAnt-MinerPB is used to generate list of rules using pittsburgh approach in order to maintain the rule interaction among the rules that are generated. In this paper, we propose a parallel Ant MinerPB in which Ant colony optimization algorithm runs parallel. In this technique, a data set is divided vertically (i-e attributes) into different subsets. These subsets are created based on the correlation among attributes using Mutual Information (MI). It generates rules in a parallel manner and then merged to form a final list of rules. The results have shown that the proposed technique achieved higher accuracy when compared with original cAnt-MinerPB and also the execution time has also reduced.

Keywords: ant colony optimization, parallel Ant-MinerPB, vertical partitioning, classification rule discovery

Procedia PDF Downloads 285
3304 Level Set and Morphological Operation Techniques in Application of Dental Image Segmentation

Authors: Abdolvahab Ehsani Rad, Mohd Shafry Mohd Rahim, Alireza Norouzi

Abstract:

Medical image analysis is one of the great effects of computer image processing. There are several processes to analysis the medical images which the segmentation process is one of the challenging and most important step. In this paper the segmentation method proposed in order to segment the dental radiograph images. Thresholding method has been applied to simplify the images and to morphologically open binary image technique performed to eliminate the unnecessary regions on images. Furthermore, horizontal and vertical integral projection techniques used to extract the each individual tooth from radiograph images. Segmentation process has been done by applying the level set method on each extracted images. Nevertheless, the experiments results by 90% accuracy demonstrate that proposed method achieves high accuracy and promising result.

Keywords: integral production, level set method, morphological operation, segmentation

Procedia PDF Downloads 311
3303 Profiling the Volatile Metabolome in Pear Leaves with Different Resistance to the Pear Psylla Cacopsylla bidens (Sulc) and Characterization of Phenolic Acid Decarboxylase

Authors: Mwafaq Ibdah, Mossab, Yahyaa, Dor Rachmany, Yoram Gerchman, Doron Holland, Liora Shaltiel-Harpaz

Abstract:

Pear Psylla is the most important pest of pear in all pear-growing regions, in Asian, European, and the USA. Pear psylla damages pears in several ways: high-density populations of these insects can cause premature leaf and fruit drop, diminish plant growth, and reduce fruit size. In addition, their honeydew promotes sooty mold on leaves and russeting on fruit. Pear psyllas are also considered vectors of pear pathogens such as Candidatus Phytoplasma pyri causing pear decline that can lead to loss of crop and tree vigor, and sometimes loss of trees. Psylla control is a major obstacle to efficient integrated pest management. Recently we have identified two naturally resistance pear accessions (Py.760-261 and Py.701-202) in the Newe Ya’ar live collection. GC-MS volatile metabolic profiling identified several volatile compounds common in these accessions but lacking, or much less common, in a sensitive accession, the commercial Spadona variety. Among these volatiles were styrene and its derivatives. When the resistant accessions were used as inter-stock, the volatile compounds appear in commercial Spadona scion leaves, and it showed reduced susceptibility to pear psylla. Laboratory experiments and applications of some of these volatile compounds were very effective against psylla eggs, nymphs, and adults. The genes and enzymes involved in the specific reactions that lead to the biosynthesis of styrene in plant are unknown. We have identified a phenolic acid decarboxylase that catalyzes the formation of p-hydroxystyrene, which occurs as a styrene analog in resistant pear genotypes. The His-tagged and affinity chromatography purified E. coli-expressed pear PyPAD1 protein could decarboxylate p-coumaric acid and ferulic acid to p-hydroxystyrene and 3-methoxy-4-hydroxystyrene. In addition, PyPAD1 had the highest activity toward p-coumaric acid. Expression analysis of the PyPAD gene revealed that its expressed as expected, i.e., high when styrene levels and psylla resistance were high.

Keywords: pear Psylla, volatile, GC-MS, resistance

Procedia PDF Downloads 138
3302 Modelling and Control of Milk Fermentation Process in Biochemical Reactor

Authors: Jožef Ritonja

Abstract:

The biochemical industry is one of the most important modern industries. Biochemical reactors are crucial devices of the biochemical industry. The essential bioprocess carried out in bioreactors is the fermentation process. A thorough insight into the fermentation process and the knowledge how to control it are essential for effective use of bioreactors to produce high quality and quantitatively enough products. The development of the control system starts with the determination of a mathematical model that describes the steady state and dynamic properties of the controlled plant satisfactorily, and is suitable for the development of the control system. The paper analyses the fermentation process in bioreactors thoroughly, using existing mathematical models. Most existing mathematical models do not allow the design of a control system for controlling the fermentation process in batch bioreactors. Due to this, a mathematical model was developed and presented that allows the development of a control system for batch bioreactors. Based on the developed mathematical model, a control system was designed to ensure optimal response of the biochemical quantities in the fermentation process. Due to the time-varying and non-linear nature of the controlled plant, the conventional control system with a proportional-integral-differential controller with constant parameters does not provide the desired transient response. The improved adaptive control system was proposed to improve the dynamics of the fermentation. The use of the adaptive control is suggested because the parameters’ variations of the fermentation process are very slow. The developed control system was tested to produce dairy products in the laboratory bioreactor. A carbon dioxide concentration was chosen as the controlled variable. The carbon dioxide concentration correlates well with the other, for the quality of the fermentation process in significant quantities. The level of the carbon dioxide concentration gives important information about the fermentation process. The obtained results showed that the designed control system provides minimum error between reference and actual values of carbon dioxide concentration during a transient response and in a steady state. The recommended control system makes reference signal tracking much more efficient than the currently used conventional control systems which are based on linear control theory. The proposed control system represents a very effective solution for the improvement of the milk fermentation process.

Keywords: biochemical reactor, fermentation process, modelling, adaptive control

Procedia PDF Downloads 125
3301 The Use of Microorganisms in the Bioleaching of Soils Polluted with Heavy Metals

Authors: I. M. Sur, A. M. Chirila-Babau, T. Gabor, V. Micle

Abstract:

This paper shows researches in order to extract Cr, Cu and Ni from the polluted soils. Research is based on preliminary studies regarding the usage of Thiobacillus ferrooxidans bacterium (9K medium) for bioleaching of soil polluted with heavy metal (Cu, Cr and Ni). The microorganisms (Thiobacillus ferooxidans) selected directly from polluted soil samples were used in this experimental work. Soil samples used in the experimental research were taken from an area polluted with heavy metals from Romania. The soil samples are subjected to the cleaning process using the 9K medium solution (20 mL and 40 mL, respectively), stirred 200 rpm for 20 hours at a controlled temperature (30 ˚C). During the experiment (0, 2, 4, 8 and 20 h), liquid samples have been extracted and analyzed using the Atomic Absorption Spectrophotometer AA-6800 (AAS) in order to determine the Cr, Cu and Ni concentration. Experiments led to the conclusion that these soils can be depolluted by bioleaching, being a biological treatment method involving the use of microorganisms to favor the extraction of Cr, Cu and Ni from polluted soils.

Keywords: bioleaching, extraction, microorganisms, soil, polluted, Thiobacillus ferooxidans

Procedia PDF Downloads 153
3300 Fuzzy Time Series- Markov Chain Method for Corn and Soybean Price Forecasting in North Carolina Markets

Authors: Selin Guney, Andres Riquelme

Abstract:

Among the main purposes of optimal and efficient forecasts of agricultural commodity prices is to guide the firms to advance the economic decision making process such as planning business operations and marketing decisions. Governments are also the beneficiaries and suppliers of agricultural price forecasts. They use this information to establish a proper agricultural policy, and hence, the forecasts affect social welfare and systematic errors in forecasts could lead to a misallocation of scarce resources. Various empirical approaches have been applied to forecast commodity prices that have used different methodologies. Most commonly-used approaches to forecast commodity sectors depend on classical time series models that assume values of the response variables are precise which is quite often not true in reality. Recently, this literature has mostly evolved to a consideration of fuzzy time series models that provide more flexibility in terms of the classical time series models assumptions such as stationarity, and large sample size requirement. Besides, fuzzy modeling approach allows decision making with estimated values under incomplete information or uncertainty. A number of fuzzy time series models have been developed and implemented over the last decades; however, most of them are not appropriate for forecasting repeated and nonconsecutive transitions in the data. The modeling scheme used in this paper eliminates this problem by introducing Markov modeling approach that takes into account both the repeated and nonconsecutive transitions. Also, the determination of length of interval is crucial in terms of the accuracy of forecasts. The problem of determining the length of interval arbitrarily is overcome and a methodology to determine the proper length of interval based on the distribution or mean of the first differences of series to improve forecast accuracy is proposed. The specific purpose of this paper is to propose and investigate the potential of a new forecasting model that integrates methodologies for determining the proper length of interval based on the distribution or mean of the first differences of series and Fuzzy Time Series- Markov Chain model. Moreover, the accuracy of the forecasting performance of proposed integrated model is compared to different univariate time series models and the superiority of proposed method over competing methods in respect of modelling and forecasting on the basis of forecast evaluation criteria is demonstrated. The application is to daily corn and soybean prices observed at three commercially important North Carolina markets; Candor, Cofield and Roaring River for corn and Fayetteville, Cofield and Greenville City for soybeans respectively. One main conclusion from this paper is that using fuzzy logic improves the forecast performance and accuracy; the effectiveness and potential benefits of the proposed model is confirmed with small selection criteria value such MAPE. The paper concludes with a discussion of the implications of integrating fuzzy logic and nonarbitrary determination of length of interval for the reliability and accuracy of price forecasts. The empirical results represent a significant contribution to our understanding of the applicability of fuzzy modeling in commodity price forecasts.

Keywords: commodity, forecast, fuzzy, Markov

Procedia PDF Downloads 215
3299 Investigation of Wind Farm Interaction with Ethiopian Electric Power’s Grid: A Case Study at Ashegoda Wind Farm

Authors: Fikremariam Beyene, Getachew Bekele

Abstract:

Ethiopia is currently on the move with various projects to raise the amount of power generated in the country. The progress observed in recent years indicates this fact clearly and indisputably. The rural electrification program, the modernization of the power transmission system, the development of wind farm is some of the main accomplishments worth mentioning. As it is well known, currently, wind power is globally embraced as one of the most important sources of energy mainly for its environmentally friendly characteristics, and also that once it is installed, it is a source available free of charge. However, integration of wind power plant with an existing network has many challenges that need to be given serious attention. In Ethiopia, a number of wind farms are either installed or are under construction. A series of wind farm is planned to be installed in the near future. Ashegoda Wind farm (13.2°, 39.6°), which is the subject of this study, is the first large scale wind farm under construction with the capacity of 120 MW. The first phase of 120 MW (30 MW) has been completed and is expected to be connected to the grid soon. This paper is concerned with the investigation of the wind farm interaction with the national grid under transient operating condition. The main concern is the fault ride through (FRT) capability of the system when the grid voltage drops to exceedingly low values because of short circuit fault and also the active and reactive power behavior of wind turbines after the fault is cleared. On the wind turbine side, a detailed dynamic modelling of variable speed wind turbine of a 1 MW capacity running with a squirrel cage induction generator and full-scale power electronics converters is done and analyzed using simulation software DIgSILENT PowerFactory. On the Ethiopian electric power corporation side, after having collected sufficient data for the analysis, the grid network is modeled. In the model, a fault ride-through (FRT) capability of the plant is studied by applying 3-phase short circuit on the grid terminal near the wind farm. The results show that the Ashegoda wind farm can ride from voltage deep within a short time and the active and reactive power performance of the wind farm is also promising.

Keywords: squirrel cage induction generator, active and reactive power, DIgSILENT PowerFactory, fault ride-through capability, 3-phase short circuit

Procedia PDF Downloads 163
3298 Generation of Photo-Mosaic Images through Block Matching and Color Adjustment

Authors: Hae-Yeoun Lee

Abstract:

Mosaic refers to a technique that makes image by gathering lots of small materials in various colours. This paper presents an automatic algorithm that makes the photomosaic image using photos. The algorithm is composed of four steps: Partition and feature extraction, block matching, redundancy removal and colour adjustment. The input image is partitioned in the small block to extract feature. Each block is matched to find similar photo in database by comparing similarity with Euclidean difference between blocks. The intensity of the block is adjusted to enhance the similarity of image by replacing the value of light and darkness with that of relevant block. Further, the quality of image is improved by minimizing the redundancy of tiles in the adjacent blocks. Experimental results support that the proposed algorithm is excellent in quantitative analysis and qualitative analysis.

Keywords: photomosaic, Euclidean distance, block matching, intensity adjustment

Procedia PDF Downloads 275
3297 Sustainable Crop Production: Greenhouse Gas Management in Farm Value Chain

Authors: Aswathaman Vijayan, Manish Jha, Ullas Theertha

Abstract:

Climate change and Global warming have become an issue for both developed and developing countries and perhaps the biggest threat to the environment. We at ITC Limited believe that a company’s performance must be measured by its Triple Bottom Line contribution to building economic, social and environmental capital. This Triple Bottom Line strategy focuses on - Embedding sustainability in business practices, Investing in social development and Adopting a low carbon growth path with a cleaner environment approach. The Agri Business Division - ILTD operates in the tobacco crop growing regions of Andhra Pradesh and Karnataka province of India. The Agri value chain of the company comprises of two distinct phases: First phase is Agricultural operations undertaken by ITC trained farmers and the second phase is Industrial operations which include marketing and processing of the agricultural produce. This research work covers the Greenhouse Gas (GHG) management strategy of ITC in the Agricultural operations undertaken by the farmers. The agriculture sector adds considerably to global GHG emissions through the use of carbon-based energies, use of fertilizers and other farming operations such as ploughing. In order to minimize the impact of farming operations on the environment, ITC has a taken a big leap in implementing system and process in reducing the GHG impact in farm value chain by partnering with the farming community. The company has undertaken a unique three-pronged approach for GHG management at the farm value chain: 1) GHG inventory at farm value chain: Different sources of GHG emission in the farm value chain were identified and quantified for the baseline year, as per the IPCC guidelines for greenhouse gas inventories. The major sources of emission identified are - emission due to nitrogenous fertilizer application during seedling production and main-field; emission due to diesel usage for farm machinery; emission due to fuel consumption and due to burning of crop residues. 2) Identification and implementation of technologies to reduce GHG emission: Various methodologies and technologies were identified for each GHG emission source and implemented at farm level. The identified methodologies are – reducing the consumption of chemical fertilizer usage at the farm through site-specific nutrient recommendation; Usage of sharp shovel for land preparation to reduce diesel consumption; implementation of energy conservation technologies to reduce fuel requirement and avoiding burning of crop residue by incorporation in the main field. These identified methodologies were implemented at farm level, and the GHG emission was quantified to understand the reduction in GHG emission. 3) Social and farm forestry for CO2 sequestration: In addition, the company encouraged social and farm forestry in the waste lands to convert it into green cover. The plantations are carried out with fast growing trees viz., Eucalyptus, Casuarina, and Subabul at the rate of 10,000 Ha of land per year. The above approach minimized considerable amount of GHG emission at the farm value chain benefiting farmers, community, and environment at a whole. In addition, the CO₂ stock created by social and farm forestry program has made the farm value chain to become environment-friendly.

Keywords: CO₂ sequestration, farm value chain, greenhouse gas, ITC limited

Procedia PDF Downloads 289
3296 Assessment of DNA Sequence Encoding Techniques for Machine Learning Algorithms Using a Universal Bacterial Marker

Authors: Diego Santibañez Oyarce, Fernanda Bravo Cornejo, Camilo Cerda Sarabia, Belén Díaz Díaz, Esteban Gómez Terán, Hugo Osses Prado, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

Abstract:

The advent of high-throughput sequencing technologies has revolutionized genomics, generating vast amounts of genetic data that challenge traditional bioinformatics methods. Machine learning addresses these challenges by leveraging computational power to identify patterns and extract information from large datasets. However, biological sequence data, being symbolic and non-numeric, must be converted into numerical formats for machine learning algorithms to process effectively. So far, some encoding methods, such as one-hot encoding or k-mers, have been explored. This work proposes additional approaches for encoding DNA sequences in order to compare them with existing techniques and determine if they can provide improvements or if current methods offer superior results. Data from the 16S rRNA gene, a universal marker, was used to analyze eight bacterial groups that are significant in the pulmonary environment and have clinical implications. The bacterial genes included in this analysis are Prevotella, Abiotrophia, Acidovorax, Streptococcus, Neisseria, Veillonella, Mycobacterium, and Megasphaera. These data were downloaded from the NCBI database in Genbank file format, followed by a syntactic analysis to selectively extract relevant information from each file. For data encoding, a sequence normalization process was carried out as the first step. From approximately 22,000 initial data points, a subset was generated for testing purposes. Specifically, 55 sequences from each bacterial group met the length criteria, resulting in an initial sample of approximately 440 sequences. The sequences were encoded using different methods, including one-hot encoding, k-mers, Fourier transform, and Wavelet transform. Various machine learning algorithms, such as support vector machines, random forests, and neural networks, were trained to evaluate these encoding methods. The performance of these models was assessed using multiple metrics, including the confusion matrix, ROC curve, and F1 Score, providing a comprehensive evaluation of their classification capabilities. The results show that accuracies between encoding methods vary by up to approximately 15%, with the Fourier transform obtaining the best results for the evaluated machine learning algorithms. These findings, supported by the detailed analysis using the confusion matrix, ROC curve, and F1 Score, provide valuable insights into the effectiveness of different encoding methods and machine learning algorithms for genomic data analysis, potentially improving the accuracy and efficiency of bacterial classification and related genomic studies.

Keywords: DNA encoding, machine learning, Fourier transform, Fourier transformation

Procedia PDF Downloads 12
3295 Green Procedure for Energy and Emission Balancing of Alternative Scenario Improvements for Cogeneration System: A Case of Hardwood Lumber Manufacturing Process

Authors: Aldona Kluczek

Abstract:

Energy efficient process have become a pressing research field in manufacturing. The arguments for having an effective industrial energy efficiency processes are interacted with factors: economic and environmental impact, and energy security. Improvements in energy efficiency are most often achieved by implementation of more efficient technology or manufacturing process. Current processes of electricity production represents the biggest consumption of energy and the greatest amount of emissions to the environment. The goal of this study is to improve the potential energy-savings and reduce greenhouse emissions related to improvement scenarios for the treatment of hardwood lumber produced by an industrial plant operating in the U.S. through the application of green balancing procedure, in order to find the preferable efficient technology. The green procedure for energy is based on analysis of energy efficiency data. Three alternative scenarios of the cogeneration systems plant (CHP) construction are considered: generation of fresh steam, the purchase of a new boiler with the operating pressure 300 pounds per square inch gauge (PSIG), an installation of a new boiler with a 600 PSIG pressure. In this paper, the application of a bottom-down modelling for energy flow to devise a streamlined Energy and Emission Flow Analyze method for the technology of producing electricity is illustrated. It will identify efficiency or technology of a given process to be reached, through the effective use of energy, or energy management. Results have shown that the third scenario seem to be the efficient alternative scenario considered from the environmental and economic concerns for treating hardwood lumber. The energy conservation evaluation options could save an estimated 6,215.78 MMBtu/yr in each year, which represents 9.5% of the total annual energy usage. The total annual potential cost savings from all recommendations is $143,523/yr, which represents 30.1% of the total annual energy costs. Estimation have presented that energy cost savings are possible up to 43% (US$ 143,337.85), representing 18.6% of the total annual energy costs.

Keywords: alternative scenario improvements, cogeneration system, energy and emission flow analyze, energy balancing, green procedure, hardwood lumber manufacturing process

Procedia PDF Downloads 201
3294 Liver Tumor Detection by Classification through FD Enhancement of CT Image

Authors: N. Ghatwary, A. Ahmed, H. Jalab

Abstract:

In this paper, an approach for the liver tumor detection in computed tomography (CT) images is represented. The detection process is based on classifying the features of target liver cell to either tumor or non-tumor. Fractional differential (FD) is applied for enhancement of Liver CT images, with the aim of enhancing texture and edge features. Later on, a fusion method is applied to merge between the various enhanced images and produce a variety of feature improvement, which will increase the accuracy of classification. Each image is divided into NxN non-overlapping blocks, to extract the desired features. Support vector machines (SVM) classifier is trained later on a supplied dataset different from the tested one. Finally, the block cells are identified whether they are classified as tumor or not. Our approach is validated on a group of patients’ CT liver tumor datasets. The experiment results demonstrated the efficiency of detection in the proposed technique.

Keywords: fractional differential (FD), computed tomography (CT), fusion, aplha, texture features.

Procedia PDF Downloads 354
3293 Jet-Stream Airsail: Study of the Shape and the Behavior of the Connecting Cable

Authors: Christopher Frank, Yoshiki Miyairi

Abstract:

A jet-stream airsail concept takes advantage of aerology in order to fly without propulsion. Weather phenomena, especially jet streams, are relatively permanent high winds blowing from west to east, located at average altitudes and latitudes in both hemispheres. To continuously extract energy from the jet-stream, the system is composed of a propelled plane and a wind turbine interconnected by a cable. This work presents the aerodynamic characteristics and the behavior of the cable that links the two subsystems and transmits energy from the turbine to the aircraft. Two ways of solving this problem are explored: numerically and analytically. After obtaining the optimal shape of the cross-section of the cable, its behavior is analyzed as a 2D problem solved numerically and analytically. Finally, a 3D extension could be considered by adding lateral forces. The results of this work can be further used in the design process of the overall system: aircraft-turbine.

Keywords: jet-stream, cable, tether, aerodynamics, aircraft, airsail, wind

Procedia PDF Downloads 360
3292 Comparative Study of the Earth Land Surface Temperature Signatures over Ota, South-West Nigeria

Authors: Moses E. Emetere, M. L. Akinyemi

Abstract:

Agricultural activities in the South–West Nigeria are mitigated by the global increase in temperature. The unpredictive surface temperature of the area had increased health challenges amongst other social influence. The satellite data of surface temperatures were compared with the ground station Davis weather station. The differential heating of the lower atmosphere were represented mathematically. A numerical predictive model was propounded to forecast future surface temperature.

Keywords: numerical predictive model, surface temperature, satellite date, ground data

Procedia PDF Downloads 464