Search results for: lipid productivity
355 Image Processing-Based Maize Disease Detection Using Mobile Application
Authors: Nathenal Thomas
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In the food chain and in many other agricultural products, corn, also known as maize, which goes by the scientific name Zea mays subsp, is a widely produced agricultural product. Corn has the highest adaptability. It comes in many different types, is employed in many different industrial processes, and is more adaptable to different agro-climatic situations. In Ethiopia, maize is among the most widely grown crop. Small-scale corn farming may be a household's only source of food in developing nations like Ethiopia. The aforementioned data demonstrates that the country's requirement for this crop is excessively high, and conversely, the crop's productivity is very low for a variety of reasons. The most damaging disease that greatly contributes to this imbalance between the crop's supply and demand is the corn disease. The failure to diagnose diseases in maize plant until they are too late is one of the most important factors influencing crop output in Ethiopia. This study will aid in the early detection of such diseases and support farmers during the cultivation process, directly affecting the amount of maize produced. The diseases in maize plants, such as northern leaf blight and cercospora leaf spot, have distinct symptoms that are visible. This study aims to detect the most frequent and degrading maize diseases using the most efficiently used subset of machine learning technology, deep learning so, called Image Processing. Deep learning uses networks that can be trained from unlabeled data without supervision (unsupervised). It is a feature that simulates the exercises the human brain goes through when digesting data. Its applications include speech recognition, language translation, object classification, and decision-making. Convolutional Neural Network (CNN) for Image Processing, also known as convent, is a deep learning class that is widely used for image classification, image detection, face recognition, and other problems. it will also use this algorithm as the state-of-the-art for my research to detect maize diseases by photographing maize leaves using a mobile phone.Keywords: CNN, zea mays subsp, leaf blight, cercospora leaf spot
Procedia PDF Downloads 69354 Evaluation of Wheat Varieties on Water Use Efficiency under Staggering Sowing times and Variable Irrigation Regimes under Timely and Late Sown Conditions
Authors: Vaibhav Baliyan, Shweta Mehrotra, S. S. Parihar
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The agricultural productivity is challenged by climate change and depletion in natural resources, including water and land, which significantly affects the crop yield. Wheat is a thermo-sensitive crop and is prone to heat stress. High temperature decreases crop duration, yield attributes, and, subsequently, grain yield and biomass production. Terminal heat stress affects grain filling duration, grain yield, and yield attributes, thus causing a reduction in wheat yield. A field experiment was conducted at Indian Agricultural Research Institute, New Delhi, for two consecutive rabi seasons (2017-18 and 2018-19) on six varieties of wheat (early sown - HD 2967, HD 3086, HD 2894 and late sown - WR 544, HD 3059, HD 3117 ) with three moisture regimes (100%, 80%, and 60% ETc, and no irrigation) and six sowing dates in three replications to investigate the effect of different moisture regimes and sowing dates on growth, yield and water use efficiency of wheat for development of best management practices for mitigation of terminal heat stress. HD3086 and HD3059 gave higher grain yield than others under early sown and late sown conditions, respectively. Maximum soil moisture extraction was recorded from 0-30 cm soil depth across the sowing dates, irrigation regimes, and varieties. Delayed sowing resulted in reducing crop growth period and forced maturity, in turn, led to significant deterioration in all the yield attributing characters and, there by, reduction in yield, suggesting that terminal heat stress had greater impact on yield. Early sowing and irrigation at 80% ETc resulted in improved growth and yield attributes and water use efficiency in both the seasons and helped to some extent in reducing the risk of terminal heat stress of wheat grown on sandy loam soils of semi-arid regions of India.Keywords: sowing, irrigation, yield, heat stress
Procedia PDF Downloads 83353 Fermentation of Pretreated Herbaceous Cellulosic Wastes to Ethanol by Anaerobic Cellulolytic and Saccharolytic Thermophilic Clostridia
Authors: Lali Kutateladze, Tamar Urushadze, Tamar Dudauri, Besarion Metreveli, Nino Zakariashvili, Izolda Khokhashvili, Maya Jobava
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Lignocellulosic waste streams from agriculture, paper and wood industry are renewable, plentiful and low-cost raw materials that can be used for large-scale production of liquid and gaseous biofuels. As opposed to prevailing multi-stage biotechnological processes developed for bioconversion of cellulosic substrates to ethanol where high-cost cellulase preparations are used, Consolidated Bioprocessing (CBP) offers to accomplish cellulose and xylan hydrolysis followed by fermentation of both C6 and C5 sugars to ethanol in a single-stage process. Syntrophic microbial consortium comprising of anaerobic, thermophilic, cellulolytic, and saccharolytic bacteria in the genus Clostridia with improved ethanol productivity and high tolerance to fermentation end-products had been proposed for achieving CBP. 65 new strains of anaerobic thermophilic cellulolytic and saccharolytic Clostridia were isolated from different wetlands and hot springs in Georgia. Using new isolates, fermentation of mechanically pretreated wheat straw and corn stalks was done under oxygen-free nitrogen environment in thermophilic conditions (T=550C) and pH 7.1. Process duration was 120 hours. Liquid and gaseous products of fermentation were analyzed on a daily basis using Perkin-Elmer gas chromatographs with flame ionization and thermal detectors. Residual cellulose, xylan, xylose, and glucose were determined using standard methods. Cellulolytic and saccharolytic bacteria strains degraded mechanically pretreated herbaceous cellulosic wastes and fermented glucose and xylose to ethanol, acetic acid and gaseous products like hydrogen and CO2. Specifically, maximum yield of ethanol was reached at 96 h of fermentation and varied between 2.9 – 3.2 g/ 10 g of substrate. The content of acetic acid didn’t exceed 0.35 g/l. Other volatile fatty acids were detected in trace quantities.Keywords: anaerobic bacteria, cellulosic wastes, Clostridia sp, ethanol
Procedia PDF Downloads 285352 Effect of Nanoparticles on Wheat Seed Germination and Seedling Growth
Authors: Pankaj Singh Rawat, Rajeew Kumar, Pradeep Ram, Priyanka Pandey
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Wheat is an important cereal crop for food security. Boosting the wheat production and productivity is the major challenge across the nation. Good quality of seed is required for maintaining optimum plant stand which ultimately increases grain yield. Ensuring a good germination is one of the key steps to ensure proper plant stand and moisture assurance during seed germination may help to speed up the germination. The tiny size of nanoparticles may help in entry of water into seed without disturbing their internal structure. Considering above, a laboratory experiment was conducted during 2012-13 at G.B. Pant University of Agriculture and Technology, Pantnagar, India. The completely randomized design was used for statistical analysis. The experiment was conducted in two phases. In the first phase, the appropriate concentration of nanoparticles for seed treatment was screened. In second phase seed soaking hours of nanoparticles for better seed germination were standardized. Wheat variety UP2526 was taken as test crop. Four nanoparticles (TiO2, ZnO, nickel and chitosan) were taken for study. The crop germination studies were done in petri dishes and standard package and practices were used to raise the seedlings. The germination studies were done by following standard procedure. In first phase of the experiment, seeds were treated with 50 and 300 ppm of nanoparticles and control was also maintained for comparison. In the second phase of experiment, seeds were soaked for 4 hours, 6 hours and 8 hours with 50 ppm nanoparticles of TiO2, ZnO, nickel and chitosan along with control treatment to identify the soaking time for better seed germination. Experiment revealed that the application of nanoparticles help to enhance seed germination. The study revealed that seed treatment with nanoparticles at 50 ppm concentration increases root length, shoot length, seedling length, shoot dry weight, seedling dry weight, seedling vigour index I and seedling vigour index II as compared to seed soaking at 300 ppm concentration. This experiment showed that seed soaking up to 4 hr was better as compared to 6 and 8 hrs. Seed soaking with nanoparticles specially TiO2, ZnO, and chitosan proved to enhance germination and seedling growth indices of wheat crop.Keywords: nanoparticles, seed germination, seed soaking, wheat
Procedia PDF Downloads 221351 Environmental Performance Measurement for Network-Level Pavement Management
Authors: Jessica Achebe, Susan Tighe
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The recent Canadian infrastructure report card reveals the unhealthy state of municipal infrastructure intensified challenged faced by municipalities to maintain adequate infrastructure performance thresholds and meet user’s required service levels. For a road agency, huge funding gap issue is inflated by growing concerns of the environmental repercussion of road construction, operation and maintenance activities. As the reduction of material consumption and greenhouse gas emission when maintain and rehabilitating road networks can achieve added benefits including improved life cycle performance of pavements, reduced climate change impacts and human health effect due to less air pollution, improved productivity due to optimal allocation of resources and reduced road user cost. Incorporating environmental sustainability measure into pavement management is solution widely cited and studied. However measuring the environmental performance of road network is still a far-fetched practice in road network management, more so an ostensive agency-wide environmental sustainability or sustainable maintenance specifications is missing. To address this challenge, this present research focuses on the environmental sustainability performance of network-level pavement management. The ultimate goal is to develop a framework to incorporate environmental sustainability in pavement management systems for network-level maintenance programming. In order to achieve this goal, this study reviewed previous studies that employed environmental performance measures, as well as the suitability of environmental performance indicators for the evaluation of the sustainability of network-level pavement maintenance strategies. Through an industry practice survey, this paper provides a brief forward regarding the pavement manager motivations and barriers to making more sustainable decisions, and data needed to support the network-level environmental sustainability. The trends in network-level sustainable pavement management are also presented, existing gaps are highlighted, and ideas are proposed for sustainable network-level pavement management.Keywords: pavement management, sustainability, network-level evaluation, environment measures
Procedia PDF Downloads 208350 Developing a Green Information Technology Model in Australian Higher-Educational Institutions
Authors: Mahnaz Jafari, Parisa Izadpanahi, Francesco Mancini, Muhammad Qureshi
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The advancement in Information Technology (IT) has been an intrinsic element in the developments of the 21st century bringing benefits such as increased economic productivity. However, its widespread application has also been associated with inadvertent negative impacts on society and the environment necessitating selective interventions to mitigate these impacts. This study responded to this need by developing a Green IT Rating Tool (GIRT) for higher education institutions (HEI) in Australia to evaluate the sustainability of IT-related practices from an environmental, social, and economic perspective. Each dimension must be considered equally to achieve sustainability. The development of the GIRT was informed by the views of interviewed IT professionals whose opinions formed the basis of a framework listing Green IT initiatives in order of their importance as perceived by the interviewed professionals. This framework formed the base of the GIRT, which identified Green IT initiatives (such as videoconferencing as a substitute for long-distance travel) and the associated weighting of each practice. The proposed sustainable Green IT model could be integrated into existing IT systems, leading to significant reductions in carbon emissions and e-waste and improvements in energy efficiency. The development of the GIRT and the findings of this study have the potential to inspire other organizations to adopt sustainable IT practices, positively impact the environment, and be used as a reference by IT professionals and decision-makers to evaluate IT-related sustainability practices. The GIRT could also serve as a benchmark for HEIs to compare their performance with other institutions and to track their progress over time. Additionally, the study's results suggest that virtual and cloud-based technologies could reduce e-waste and energy consumption in the higher education sector. Overall, this study highlights the importance of incorporating Green IT practices into the IT systems of HEI to contribute to a more sustainable future.Keywords: green information technology, international higher-educational institution, sustainable solutions, environmentally friendly IT systems
Procedia PDF Downloads 72349 The Successful in Construction Project via Effectiveness of Project Team
Authors: Zarabizan Zakaria, Hayati Zainal
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The construction industry is one of the most important sectors that contribute to the nation’s economy and catalyze towards the growth of other industries. However, some construction projects have not been completed on its stipulated time and duration, scope and budget due to several factors. This problem arises due to the weaknesses of human factors, especially from ineffective leadership quality practiced by project managers and contractors in managing project teams. Therefore, a construction project should impose the element of Project Team. The project team is formed in the implementation of the project which includes the project brief, project scope, customer requirements and provided designs. Many organizations in the construction sector use teams to meet today's global competition and customer expectations, however, team effectiveness evaluation is required. In insuring the construction team is successful and effectiveness, the construction department must encourage, measure, set up, and evaluate or review the effectiveness of project team that was formed. In order to produce a better outcome for a high-end project, an effective and efficient project team is required which also help in increasing overall productivity. The purpose of this study is to determine the role of team effectiveness in the construction project team based on the overall construction project performance. It examines several different factors which related to team effectiveness. It also examines the relationship between team effectiveness factor and project performance aspect. Team Effect Review and Project Performance Review are developed to be used for data collection. Data collected were analyzed using several statistical tests. Results obtained from data analysis are validated using semi-structured interviews. Besides that, a comprehensive survey were developed to assess the way construction project teams in order to maintain its effectiveness throughout the project phase. In order to determine a project successful it has been found that Project Team Leadership is the most important factor. In addition, the definition of team effectiveness in the construction project team is developed based on the perspective of project clients and project team members. The results of this study are expected to provide an idea on the factors that are needed to be focused on improving the team's effectiveness towards project performance aspects. At the same time, the definition of team effectiveness from team members and owner views has been developed in order to provide a better understanding of the word team's effectiveness in construction projects.Keywords: project team, leadership, construction project, project successful
Procedia PDF Downloads 168348 Machine Learning in Agriculture: A Brief Review
Authors: Aishi Kundu, Elhan Raza
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"Necessity is the mother of invention" - Rapid increase in the global human population has directed the agricultural domain toward machine learning. The basic need of human beings is considered to be food which can be satisfied through farming. Farming is one of the major revenue generators for the Indian economy. Agriculture is not only considered a source of employment but also fulfils humans’ basic needs. So, agriculture is considered to be the source of employment and a pillar of the economy in developing countries like India. This paper provides a brief review of the progress made in implementing Machine Learning in the agricultural sector. Accurate predictions are necessary at the right time to boost production and to aid the timely and systematic distribution of agricultural commodities to make their availability in the market faster and more effective. This paper includes a thorough analysis of various machine learning algorithms applied in different aspects of agriculture (crop management, soil management, water management, yield tracking, livestock management, etc.).Due to climate changes, crop production is affected. Machine learning can analyse the changing patterns and come up with a suitable approach to minimize loss and maximize yield. Machine Learning algorithms/ models (regression, support vector machines, bayesian models, artificial neural networks, decision trees, etc.) are used in smart agriculture to analyze and predict specific outcomes which can be vital in increasing the productivity of the Agricultural Food Industry. It is to demonstrate vividly agricultural works under machine learning to sensor data. Machine Learning is the ongoing technology benefitting farmers to improve gains in agriculture and minimize losses. This paper discusses how the irrigation and farming management systems evolve in real-time efficiently. Artificial Intelligence (AI) enabled programs to emerge with rich apprehension for the support of farmers with an immense examination of data.Keywords: machine Learning, artificial intelligence, crop management, precision farming, smart farming, pre-harvesting, harvesting, post-harvesting
Procedia PDF Downloads 99347 Edge Enhancement Visual Methodology for Fat Amount and Distribution Assessment in Dry-Cured Ham Slices
Authors: Silvia Grassi, Stefano Schiavon, Ernestina Casiraghi, Cristina Alamprese
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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 171346 Health Economics in the Cost-Benefit Analysis of Transport Schemes
Authors: Henry Kelly, Helena Shaw
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This paper will seek how innovative methods from Health Economics and, to a lesser extent, wellbeing analysis can be applied in the Cost-Benefit Analysis (CBA) of transport infrastructure and policy interventions. The context for this will focus on the framework articulated by the UK Treasury (finance department) and the English Department for Transport. Both have well-established methods for undertaking CBA, but there is increased policy interest, particularly at a regional level of exploring broader strategic goals beyond those traditionally associated with transport user benefits, productivity gains, and labour market access. Links to different CBA approaches internationally, such as New Zealand, France, and Wales will be referenced. By exploring a complementary method of accessing the impacts of policies through the quantification of health impacts is a fruitful line to explore. In a previous piece of work, 14 impact pathways were identified, mapping the relationship between transport and health. These are wide-ranging, from improved employment prospects, the stress of unreliable journey times, and air quality to isolation and loneliness. Importantly, we will consider these different measures of health from an intersectional point of view to ensure that the basis that remains in the health industry does not get translated across to this work. The objective is to explore how a CBA based on these pathways may, through quantifying forecast impacts in terms of Quality-Adjusted Life Years may, produce different findings than a standard approach. Of particular interest is how a health-based approach may have different distributional impacts on socio-economic groups and may favour distinct types of interventions. Consideration will be given to the degree this approach may double-count impacts or if it is possible to identify additional benefits to the established CBA approach. The investigation will explore a range of schemes, from a high-speed rail link, highway improvements, rural mobility hubs, and coach services to cycle lanes. The conclusions should aid the progression of methods concerning the assessment of publicly funded infrastructure projects.Keywords: cost-benefit analysis, health, QALYs transport
Procedia PDF Downloads 74345 Elucidating the Defensive Role of Silicon-Induced Biochemical Responses in Wheat Exposed to Drought and Diuraphis noxia Infestation
Authors: Lintle Mohase, Ninikoe Lebusa, Mpho Stephen Mafa
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Wheat is an economically important cereal crop. However, the changing climatic conditions that intensify drought in production areas, and additional pest infestation, such as the Russian wheat aphid (RWA, Diuraphis noxia), severely hamper its production. Drought and pest management require an additional water supply through irrigation and applying inorganic nutrients (including silicon) as alternative strategies to mitigate the stress effects. Therefore, other approaches are needed to enhance wheat productivity during drought stress and aphid abundance. Two wheat cultivars were raised under greenhouse conditions, exposed to drought stress, and treated with silicon before infestation with the South African RWA biotype 2 (RWASA2). The morphological evaluations showed that severe drought or a combination of drought and infestation significantly reduced the plant height of wheat cultivars. Silicon treatment did not alleviate the growth reduction. The biochemical responses were measured using spectrophotometric assays with specific substrates. An evaluation of the enzyme activities associated with oxidative stress and defence responses indicated that drought stress increased NADPH oxidase activity, while silicon treatment significantly reduced it in drought-stressed and infested plants. At 48 and 72 hours sampling periods, a combination of silicon, drought and infestation treatment significantly increased peroxidase activity compared to drought and infestation treatment. The treatment also increased β-1,3-glucanase activity 72 hours after infestation. In addition, silicon and drought treatment increased glucose but reduced sucrose accumulation. Furthermore, silicon, drought, and infestation treatment combinations reduced the sucrose content. Finally, silicon significantly increased the trehalose content under severe drought and infestation, evident at 48 and 72-hour sampling periods. Our findings shed light on silicon’s ability to induce protective biochemical responses during drought and aphid infestation.Keywords: drought, enzyme activity, silicon, soluble sugars, Russian wheat aphid, wheat
Procedia PDF Downloads 71344 Bioinformatic Prediction of Hub Genes by Analysis of Signaling Pathways, Transcriptional Regulatory Networks and DNA Methylation Pattern in Colon Cancer
Authors: Ankan Roy, Niharika, Samir Kumar Patra
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Anomalous nexus of complex topological assemblies and spatiotemporal epigenetic choreography at chromosomal territory may forms the most sophisticated regulatory layer of gene expression in cancer. Colon cancer is one of the leading malignant neoplasms of the lower gastrointestinal tract worldwide. There is still a paucity of information about the complex molecular mechanisms of colonic cancerogenesis. Bioinformatics prediction and analysis helps to identify essential genes and significant pathways for monitoring and conquering this deadly disease. The present study investigates and explores potential hub genes as biomarkers and effective therapeutic targets for colon cancer treatment. Colon cancer patient sample containing gene expression profile datasets, such as GSE44076, GSE20916, and GSE37364 were downloaded from Gene Expression Omnibus (GEO) database and thoroughly screened using the GEO2R tool and Funrich software to find out common 2 differentially expressed genes (DEGs). Other approaches, including Gene Ontology (GO) and KEGG pathway analysis, Protein-Protein Interaction (PPI) network construction and hub gene investigation, Overall Survival (OS) analysis, gene correlation analysis, methylation pattern analysis, and hub gene-Transcription factors regulatory network construction, were performed and validated using various bioinformatics tool. Initially, we identified 166 DEGs, including 68 up-regulated and 98 down-regulated genes. Up-regulated genes are mainly associated with the Cytokine-cytokine receptor interaction, IL17 signaling pathway, ECM-receptor interaction, Focal adhesion and PI3K-Akt pathway. Downregulated genes are enriched in metabolic pathways, retinol metabolism, Steroid hormone biosynthesis, and bile secretion. From the protein-protein interaction network, thirty hub genes with high connectivity are selected using the MCODE and cytoHubba plugin. Survival analysis, expression validation, correlation analysis, and methylation pattern analysis were further verified using TCGA data. Finally, we predicted COL1A1, COL1A2, COL4A1, SPP1, SPARC, and THBS2 as potential master regulators in colonic cancerogenesis. Moreover, our experimental data highlights that disruption of lipid raft and RAS/MAPK signaling cascade affects this gene hub at mRNA level. We identified COL1A1, COL1A2, COL4A1, SPP1, SPARC, and THBS2 as determinant hub genes in colon cancer progression. They can be considered as biomarkers for diagnosis and promising therapeutic targets in colon cancer treatment. Additionally, our experimental data advertise that signaling pathway act as connecting link between membrane hub and gene hub.Keywords: hub genes, colon cancer, DNA methylation, epigenetic engineering, bioinformatic predictions
Procedia PDF Downloads 124343 The Evaluation of the Effect of a Weed-Killer Sulfonylurea on Durum Wheat (Triticum durum Desf)
Authors: Meksem Amara Leila, Ferfar Meriem, Meksem Nabila, Djebar Mohammed Reda
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The wheat is the cereal the most consumed in the world. In Algeria, the production of this cereal covers only 20 in 25 % of the needs for the country, the rest being imported. To improve the efficiency and the productivity of the durum wheat, the farmers turn to the use of pesticides: weed-killers, fungicides and insecticides. However this use often entrains losses of products more at least important contaminating the environment and all the food chain. Weed-killers are substances developed to control or destroy plants considered unwanted. That they are natural or produced by the human being (molecule of synthesis), the absorption and the metabolization of weed-killers by plants cause the death of these plants.In this work, we set as goal the evaluation of the effect of a weed-killer sulfonylurea, the CossackOD with various concentrations (0, 2, 4 and 9 µg) on variety of Triticum durum: Cirta. We evaluated the plant growth by measuring the leaves and root length, compared with the witness as well as the content of proline and analyze the level of one of the antioxydative enzymes: catalse, after 14 days of treatment. Sulfonylurea is foliar and root weed-killers inhibiting the acetolactate synthase: a vegetable enzyme essential to the development of the plant. This inhibition causes the ruling of the growth then the death. The obtained results show a diminution of the average length of leaves and roots this can be explained by the fact that the ALS inhibitors are more active in the young and increasing regions of the plant, what inhibits the cellular division and talks a limitation of the foliar and root’s growth. We also recorded a highly significant increase in the proline levels and a stimulation of the catalase activity. As a response to increasing the herbicide concentrations a particular increases in antioxidative mechanisms in wheat cultivar Cirta suggest that the high sensitivity of Cirta to this sulfonylurea herbicide is related to the enhanced production and oxidative damage of reactive oxygen species.Keywords: sulfonylurea, Triticum durum, oxydative stress, Toxicity
Procedia PDF Downloads 420342 Impact of Pharmacist-Led Care on Glycaemic Control in Patients with Type 2 Diabetes: A Randomised-Controlled Trial
Authors: Emmanuel A. David, Rebecca O. Soremekun, Roseline I. Aderemi-Williams
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Background: The complexities involved in the management of diabetes mellitus require a multi-dimensional, multi-professional collaborative and continuous care by health care providers and a substantial self-care by the patients in order to achieve desired treatment outcomes. The effect of pharmacists’ care in the management of diabetes in resource-endowed nations is well documented in literature, but randomised-controlled assessment of the impact of pharmacist-led care among patients with diabetes in resource-limited settings like Nigeria and sub-Saharan Africa countries is scarce. Objective: To evaluate the impact of Pharmacist-led care on glycaemic control in patients with uncontrolled type 2 diabetes, using a randomised-controlled study design Methods: This study employed a prospective randomised controlled design, to assess the impact of pharmacist-led care on glycaemic control of 108 poorly controlled type 2 diabetic patients. A total of 200 clinically diagnosed type 2 diabetes patients were purposively selected using fasting blood glucose ≥ 7mmol/L and tested for long term glucose control using Glycated haemoglobin measure. One hundred and eight (108) patients with ≥ 7% Glycated haemoglobin were recruited for the study and assigned unique identification numbers. They were further randomly allocated to intervention and usual care groups using computer generated random numbers, with each group containing 54 subjects. Patients in the intervention group received pharmacist-structured intervention, including education, periodic phone calls, adherence counselling, referral and 6 months follow-up, while patients in usual care group only kept clinic appointments with their physicians. Data collected at baseline and six months included socio-demographic characteristics, fasting blood glucose, Glycated haemoglobin, blood pressure, lipid profile. With an intention to treat analysis, Mann-Whitney U test was used to compared median change from baseline in the primary outcome (Glycated haemoglobin) and secondary outcomes measure, effect size was computed and proportion of patients that reached target laboratory parameter were compared in both arms. Results: All enrolled participants (108) completed the study, 54 in each study. Mean age was 51±11.75 and majority were female (68.5%). Intervention patients had significant reduction in Glycated haemoglobin (-0.75%; P<0.001; η2 = 0.144), with greater proportion attaining target laboratory parameter after 6 months of care compared to usual care group (Glycated haemoglobin: 42.6% vs 20.8%; P=0.02). Furthermore, patients who received pharmacist-led care were about 3 times more likely to have better glucose control (AOR 2.718, 95%CI: 1.143-6.461) compared to usual care group. Conclusion: Pharmacist-led care significantly improved glucose control in patients with uncontrolled type 2 diabetes mellitus and should be integrated in the routine management of diabetes patients, especially in resource-limited settings.Keywords: glycaemic control , pharmacist-led care, randomised-controlled trial , type 2 diabetes mellitus
Procedia PDF Downloads 115341 Accessibility of Institutional Credit and Its Impact on Agricultural Output: A Case Study
Authors: Showkat Ahmad Bhat, M. S. Bhatt
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The study evaluates the ex-post impact of institutional credit on agricultural output. It first examines the key factors that influence the accessibility of institutional credit by farm households. For quantitative analysis both program participant and non-participant respondents were drawn and cross-sectional survey data were collected from 412 households in Pulwama District of Jammu & Kashmir (India). Propensity Score Matching Method was employed to analyze the impact of the institutional credit on agricultural output. Results show that institutional credit has a positive and significant impact on the agricultural output measured in terms of farm income and crop productivity. To estimate the accessibility of credit, an examination of both demand side and supply side factors were carried out. The demand for credit was measured with respect to respondents who applied for credit. Supply side credit allocation measured in terms of the proportion of ‘credit amount’ farmers obtained. Logit and Two-limit Tobit Regression Models were used to investigate the determinants that influence the accessibility of formal credit for Demand for and supply of credit respectively. The estimated results suggested that the demand for credit is positively and significantly affected by the factors such as: age of the household head, formal education, membership, cash crop grown, farm size and saving account. All the variables were found significantly increasing the household’s likelihood to demand for and supply of credit from banks. However, the impact of these factors varies considerably across the credit markets. Factors which were found negatively and significantly influencing the accessibility of credit were: ‘square of the age’, household assets and rate of interest. The credit constraints analysis suggested that square of the age; household assets and rate of interest were the three most important factors that increased the probability of being constrained. The study finally discusses these results in detail and draws some recommendations.Keywords: institutional credit, agriculture, propensity score matching logit model, Tobit model
Procedia PDF Downloads 304340 Real Energy Performance Study of Large-Scale Solar Water Heater by Using Remote Monitoring
Authors: F. Sahnoune, M. Belhamel, M. Zelmat
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Solar thermal systems available today provide reliability, efficiency and significant environmental benefits. In housing, they can satisfy the hot water demand and reduce energy bills by 60 % or more. Additionally, collective systems or large scale solar thermal systems are increasingly used in different conditions for hot water applications and space heating in hotels and multi-family homes, hospitals, nursing homes and sport halls as well as in commercial and industrial building. However, in situ real performance data for collective solar water heating systems has not been extensively outlined. This paper focuses on the study of real energy performances of a collective solar water heating system using the remote monitoring technique in Algerian climatic conditions. This is to ensure proper operation of the system at any time, determine the system performance and to check to what extent solar performance guarantee can be achieved. The measurements are performed on an active indirect heating system of 12 m2 flat plate collector’s surface installed in Algiers and equipped with a various sensors. The sensors transmit measurements to a local station which controls the pumps, valves, electrical auxiliaries, etc. The simulation of the installation was developed using the software SOLO 2000. The system provides a yearly solar yield of 6277.5 KWh for an estimated annual need of 7896 kWh; the yearly average solar cover rate amounted to 79.5%. The productivity is in the order of 523.13 kWh / m²/year. Simulation results are compared to measured results and to guaranteed solar performances. The remote monitoring shows that 90% of the expected solar results can be easy guaranteed on a long period. Furthermore, the installed remote monitoring unit was able to detect some dysfunctions. It follows that remote monitoring is an important tool in energy management of some building equipment.Keywords: large-scale solar water heater, real energy performance, remote monitoring, solar performance guarantee, tool to promote solar water heater
Procedia PDF Downloads 232339 A 4-Month Low-carb Nutrition Intervention Study Aimed to Demonstrate the Significance of Addressing Insulin Resistance in 2 Subjects with Type-2 Diabetes for Better Management
Authors: Shashikant Iyengar, Jasmeet Kaur, Anup Singh, Arun Kumar, Ira Sahay
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Insulin resistance (IR) is a condition that occurs when cells in the body become less responsive to insulin, leading to higher levels of both insulin and glucose in the blood. This condition is linked to metabolic syndromes, including diabetes. It is crucial to address IR promptly after diagnosis to prevent long-term complications associated with high insulin and high blood glucose. This four-month case study highlights the importance of treating the underlying condition to manage diabetes effectively. Insulin is essential for regulating blood sugar levels by facilitating the uptake of glucose into cells for energy or storage. In IR individuals, cells are less efficient at taking up glucose from the blood resulting in elevated blood glucose levels. As a result of IR, beta cells produce more insulin to make up for the body's inability to use insulin effectively. This leads to high insulin levels, a condition known as hyperinsulinemia, which further impairs glucose metabolism and can contribute to various chronic diseases. In addition to regulating blood glucose, insulin has anti-catabolic effects, preventing the breakdown of molecules in the body, such as inhibiting glycogen breakdown in the liver, inhibiting gluconeogenesis, and inhibiting lipolysis. If a person is insulin-sensitive or metabolically healthy, an optimal level of insulin prevents fat cells from releasing fat and promotes the storage of glucose and fat in the body. Thus optimal insulin levels are crucial for maintaining energy balance and plays a key role in metabolic processes. During the four-month study, researchers looked at the impact of a low-carb dietary (LCD) intervention on two male individuals (A & B) who had Type-2 diabetes. Althoughvneither of these individuals were obese, they were both slightly overweight and had abdominal fat deposits. Before the trial began, important markers such as fasting blood glucose (FBG), triglycerides (TG), high-density lipoprotein (HDL) cholesterol, and Hba1c were measured. These markers are essential in defining metabolic health, their individual values and variability are integral in deciphering metabolic health. The ratio of TG to HDL is used as a surrogate marker for IR. This ratio has a high correlation with the prevalence of metabolic syndrome and with IR itself. It is a convenient measure because it can be calculated from a standard lipid profile and does not require more complex tests. In this four-month trial, an improvement in insulin sensitivity was observed through the ratio of TG/HDL, which, in turn, improves fasting blood glucose levels and HbA1c. For subject A, HbA1c dropped from 13 to 6.28, and for subject B, it dropped from 9.4 to 5.7. During the trial, neither of the subjects were taking any diabetic medications. The significant improvements in their health markers, such as better glucose control, along with an increase in energy levels, demonstrate that incorporating LCD interventions can effectively manage diabetes.Keywords: metabolic disorder, insulin resistance, type-2 diabetes, low-carb nutrition
Procedia PDF Downloads 32338 Sustainable Agriculture Practices Using Bacterial-mediated Alleviation of Salinity Stress in Crop Plants
Authors: Mohamed Trigui, Fatma Masmoudi, Imen Zouari
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Massive utilizations of chemical fertilizer and chemical pesticides in agriculture sector to improve the farming productivity have created increasing environmental damages. Then, agriculture must become sustainable, focusing on production systems that respect the environment and help to reduce climate change. Isolation and microbial identification of new bacterial strains from naturally saline habitats and compost extracts could be a prominent way in pest management and crop production under saline conditions. In this study, potential mechanisms involved in plant growth promotion and suppressive activity against fungal diseases of a compost extract produced from poultry manure/olive husk compost and halotolerant and halophilic bacterial strains under saline stress were investigated. On the basis of the antimicrobial tests, different strains isolated from Sfax solar saltern (Tunisia) and from compost extracts were selected and tested for their plant growth promoting traits, such as siderophores production, nitrogen fixation, phosphate solubilization and the production of extracellular hydrolytic enzymes (protease and lipase) under in-vitro conditions. Among 450 isolated bacterial strains, 16 isolates showed potent antifungal activity against the tested plant pathogenic fungi. Their identification based on 16S rRNA gene sequence revealed they belonged to different species. Some of these strains were also characterized for their plant growth promoting capacities. Obtained results showed the ability of four strains belonging to Bacillus genesis to ameliorate germination rate and root elongation compared to the untreated positive controls. Combinatorial capacity of halotolerant bacteria with antimicrobial activity and plant growth promoting traits could be promising sources of interesting bioactive substances under saline stress.Keywords: abiotic stress, biofertilizer, biotic stress, compost extract, halobacteria, plant growth promoting (PGP), soil fertility
Procedia PDF Downloads 85337 Assessing the Impact of Climate Change on Pulses Production in Khyber Pakhtunkhwa, Pakistan
Authors: Khuram Nawaz Sadozai, Rizwan Ahmad, Munawar Raza Kazmi, Awais Habib
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Climate change and crop production are intrinsically associated with each other. Therefore, this research study is designed to assess the impact of climate change on pulses production in Southern districts of Khyber Pakhtunkhwa (KP) Province of Pakistan. Two pulses (i.e. chickpea and mung bean) were selected for this research study with respect to climate change. Climatic variables such as temperature, humidity and precipitation along with pulses production and area under cultivation of pulses were encompassed as the major variables of this study. Secondary data of climatic variables and crop variables for the period of thirty four years (1986-2020) were obtained from Pakistan Metrological Department and Agriculture Statistics of KP respectively. Panel data set of chickpea and mung bean crops was estimated separately. The analysis validate that both data sets were a balanced panel data. The Hausman specification test was run separately for both the panel data sets whose findings had suggested the fixed effect model can be deemed as an appropriate model for chickpea panel data, however random effect model was appropriate for estimation of the panel data of mung bean. Major findings confirm that maximum temperature is statistically significant for the chickpea yield. This implies if maximum temperature increases by 1 0C, it can enhance the chickpea yield by 0.0463 units. However, the impact of precipitation was reported insignificant. Furthermore, the humidity was statistically significant and has a positive association with chickpea yield. In case of mung bean the minimum temperature was significantly contributing in the yield of mung bean. This study concludes that temperature and humidity can significantly contribute to enhance the pulses yield. It is recommended that capacity building of pulses growers may be made to adapt the climate change strategies. Moreover, government may ensure the availability of climate change resistant varieties of pulses to encourage the pulses cultivation.Keywords: climate change, pulses productivity, agriculture, Pakistan
Procedia PDF Downloads 40336 Direct Fed Microbes: A Better Approach to Maximize Utilization of Roughages in Tropical Ruminants
Authors: Muhammad Adeel Arshad, Shaukat Ali Bhatti, Faiz-ul Hassan
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Manipulating microbial ecosystem in the rumen is considered as an important strategy to optimize production efficiency in ruminants. In the past, antibiotics and synthetic chemical compounds have been used for the manipulation of rumen fermentation. However, since the non-therapeutic use of antibiotics has been banned, efforts are being focused to search out safe alternative products. In tropics, crop residues and forage grazing are major dietary sources for ruminants. Poor digestibility and utilization of these feedstuffs by animals is a limiting factor to exploit the full potential of ruminants in this area. Hence, there is a need to enhance the utilization of these available feeding resources. One of the potential strategies in this regard is the use of direct-fed microbes. Bacteria and fungi are mostly used as direct-fed microbes to improve animal health and productivity. Commonly used bacterial species include lactic acid-producing and utilizing bacteria (Lactobacillus, Streptococcus, Enterococcus, Bifidobacterium, and Bacillus) and fungal species of yeast are Saccharomyces and Aspergillus. Direct-fed microbes modulate microbial balance in the gastrointestinal tract through the competitive exclusion of pathogenic species and favoring beneficial microbes. Improvement in weight gain and feed efficiency has been observed as a result of feeding direct-fed bacteria. The use of fungi as a direct-fed microbe may prevent excessive production of lactate and harmful oxygen in the rumen leading to better feed digestibility. However, the mechanistic mode of action for bacterial or fungal direct-fed microbes has not been established yet. Various reports have confirmed an increase in dry matter intake, milk yield, and milk contents in response to the administration of direct-fed microbes. However, the application of a direct-fed microbe has shown variable responses mainly attributed to dosages and strains of microbes. Nonetheless, it is concluded that the inclusion of direct-fed microbes may mediate the rumen ecosystem to manage lactic acid production and utilization in both clinical and sub-acute rumen acidosis.Keywords: microbes, roughages, rumen, feed efficiency, production, fermentation
Procedia PDF Downloads 129335 Evaluation of the Effect of Lactose Derived Monosaccharide on Galactooligosaccharides Production by β-Galactosidase
Authors: Yenny Paola Morales Cortés, Fabián Rico Rodríguez, Juan Carlos Serrato Bermúdez, Carlos Arturo Martínez Riascos
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Numerous benefits of galactooligosaccharides (GOS) as prebiotics have motivated the study of enzymatic processes for their production. These processes have special complexities due to several factors that make difficult high productivity, such as enzyme type, reaction medium pH, substrate concentrations and presence of inhibitors, among others. In the present work the production of galactooligosaccharides (with different degrees of polymerization: two, three and four) from lactose was studied. The study considers the formulation of a mathematical model that predicts the production of GOS from lactose using the enzyme β-galactosidase. The effect of pH in the reaction was studied. For that, phosphate buffer was used and with this was evaluated three pH values (6.0.6.5 and 7.0). Thus it was observed that at pH 6.0 the enzymatic activity insignificant. On the other hand, at pH 7.0 the enzymatic activity was approximately 27 times greater than at 6.5. The last result differs from previously reported results. Therefore, pH 7.0 was chosen as working pH. Additionally, the enzyme concentration was analyzed, which allowed observing that the effect of the concentration depends on the pH and the concentration was set for the following studies in 0.272 mM. Afterwards, experiments were performed varying the lactose concentration to evaluate its effects on the process and to generate the data for the adjustment of the mathematical model parameters. The mathematical model considers the reactions of lactose hydrolysis and transgalactosylation for the production of disaccharides and trisaccharides, with their inverse reactions. The production of tetrasaccharides was negligible and, because of that, it was not included in the model. The reaction was monitored by HPLC and for the quantitative analysis of the experimental data the Matlab programming language was used, including solvers for differential equations systems integration (ode15s) and nonlinear problems optimization (fminunc). The results confirm that the transgalactosylation and hydrolysis reactions are reversible, additionally inhibition by glucose and galactose is observed on the production of GOS. In relation to the production process of galactooligosaccharides, the results show that it is necessary to have high initial concentrations of lactose considering that favors the transgalactosylation reaction, while low concentrations favor hydrolysis reactions.Keywords: β-galactosidase, galactooligosaccharides, inhibition, lactose, Matlab, modeling
Procedia PDF Downloads 347334 In Vitro Assessment of True Digestibility and Rumen Parameters of Forage-Based Sheep Diet, Supplemented with Dietary Fossil Shell Flour
Authors: Olusegun O. Ikusika, Conference T. Mpendulo
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The abundance of fossil shell flour (FSF) globally has increased interest in its use as a natural feed additive in livestock diets. Therefore, identifying its optimum inclusion levels in livestock production is essential for animal productivity. This study investigated the effects of various fossil shell flour (FSF) inclusion levels on in vitro digestibility, relative feed values, and rumen parameters of Dohne-Merino wethers. Twenty-four fistulated wethers with an average body weight of 20 ± 1•5 kg in a complete randomized design of four treatments having six wethers per treatment were used. They were fed a basal diet without fossil shell flour (control, 0%) or with the addition of 2% FSF (T2), 4% FSF(T3), and 6% FSF (T4) of diet DM for 35 days, excluding 14 days adaptation period. The results showed that increasing FSF levels had no effect on ruminal T0C or pH, but Ammonia-N increased (P<0.01) with increasing FSF. The total molar concentrations of volatile fatty acids (VFA) decreased (P<0.05) with increasing levels of FSF. Acetic: propionic ratio decreased except at the 4 % inclusion level. IVTDDM, IVTDNDF and IVTDADF decreased up till 4% FSF inclusion but tended to increase (P = 0.06) at 6% inclusion. Relative feed values of the diets tended to increase (P=0.07) by adding fossil shell flour. In conclusion, adding FSF to the diets of Dohne-Merino wether up to 6% FSF inclusion rates did not improve IVTDDM (In vitro true digestibility dry matter), IVTDNDF (In vitro true digestibility neutral detergent fiber), and IVTDADF (In vitro true digestibility acid detergent fiber). However, a small increment of rumen nitrogen with no adverse effects on the rumen parameters was observed. The relative feed value (RFV) moved the feed from good to premium when supplemented. Therefore, FSF supplementation could improve feed value and maintain a normal range of rumen parameters for the effective functionality of the rumen.Keywords: fossil shell flour, rumen parameters, in vitro digestibility, feed quality, dohne-merino sheep
Procedia PDF Downloads 96333 Career Guidance System Using Machine Learning
Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan
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Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should properly evaluate their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, Neural Networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable to offer an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills
Procedia PDF Downloads 76332 Identification of Hub Genes in the Development of Atherosclerosis
Authors: Jie Lin, Yiwen Pan, Li Zhang, Zhangyong Xia
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Atherosclerosis is a chronic inflammatory disease characterized by the accumulation of lipids, immune cells, and extracellular matrix in the arterial walls. This pathological process can lead to the formation of plaques that can obstruct blood flow and trigger various cardiovascular diseases such as heart attack and stroke. The underlying molecular mechanisms still remain unclear, although many studies revealed the dysfunction of endothelial cells, recruitment and activation of monocytes and macrophages, and the production of pro-inflammatory cytokines and chemokines in atherosclerosis. This study aimed to identify hub genes involved in the progression of atherosclerosis and to analyze their biological function in silico, thereby enhancing our understanding of the disease’s molecular mechanisms. Through the analysis of microarray data, we examined the gene expression in media and neo-intima from plaques, as well as distant macroscopically intact tissue, across a cohort of 32 hypertensive patients. Initially, 112 differentially expressed genes (DEGs) were identified. Subsequent immune infiltration analysis indicated a predominant presence of 27 immune cell types in the atherosclerosis group, particularly noting an increase in monocytes and macrophages. In the Weighted gene co-expression network analysis (WGCNA), 10 modules with a minimum of 30 genes were defined as key modules, with blue, dark, Oliver green and sky-blue modules being the most significant. These modules corresponded respectively to monocyte, activated B cell, and activated CD4 T cell gene patterns, revealing a strong morphological-genetic correlation. From these three gene patterns (modules morphology), a total of 2509 key genes (Gene Significance >0.2, module membership>0.8) were extracted. Six hub genes (CD36, DPP4, HMOX1, PLA2G7, PLN2, and ACADL) were then identified by intersecting 2509 key genes, 102 DEGs with lipid-related genes from the Genecard database. The bio-functional analysis of six hub genes was estimated by a robust classifier with an area under the curve (AUC) of 0.873 in the ROC plot, indicating excellent efficacy in differentiating between the disease and control group. Moreover, PCA visualization demonstrated clear separation between the groups based on these six hub genes, suggesting their potential utility as classification features in predictive models. Protein-protein interaction (PPI) analysis highlighted DPP4 as the most interconnected gene. Within the constructed key gene-drug network, 462 drugs were predicted, with ursodeoxycholic acid (UDCA) being identified as a potential therapeutic agent for modulating DPP4 expression. In summary, our study identified critical hub genes implicated in the progression of atherosclerosis through comprehensive bioinformatic analyses. These findings not only advance our understanding of the disease but also pave the way for applying similar analytical frameworks and predictive models to other diseases, thereby broadening the potential for clinical applications and therapeutic discoveries.Keywords: atherosclerosis, hub genes, drug prediction, bioinformatics
Procedia PDF Downloads 58331 Career Guidance System Using Machine Learning
Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan
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Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should evaluate properly their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, neural networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable of offering an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills
Procedia PDF Downloads 64330 Projected Uncertainties in Herbaceous Production Result from Unpredictable Rainfall Pattern and Livestock Grazing in a Humid Tropical Savanna Ecosystem
Authors: Daniel Osieko Okach, Joseph Otieno Ondier, Gerhard Rambold, John Tenhunen, Bernd Huwe, Dennis Otieno
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Increased human activities such as grazing, logging, and agriculture alongside unpredictable rainfall patterns have been detrimental to the ecosystem service delivery, therefore compromising its productivity potential. This study aimed at simulating the impact of drought (50%) and enhanced rainfall (150%) on the future herbaceous CO2 uptake, biomass production and soil C:N dynamics in a humid savanna ecosystem influenced by livestock grazing. Rainfall pattern was predicted using manipulation experiments set up to reduce (50%) and increase (150%) ambient (100%) rainfall amounts in grazed and non-grazed plots. The impact of manipulated rainfall regime on herbaceous CO2 fluxes, biomass production and soil C:N dynamics was measured against volumetric soil water content (VWC) logged every 30 minutes using the 5TE (Decagon Devices Inc., Washington, USA) soil moisture sensors installed (at 20 cm soil depth) in every plots. Herbaceous biomass was estimated using destructive method augmented by standardized photographic imaging. CO2 fluxes were measured using the ecosystem chamber method and the gas analysed using LI-820 gas analyzer (USA). C:N ratio was calculated from the soil carbon and Nitrogen contents (analyzed using EA2400CHNS/O and EA2410 N elemental analyzers respectively) of different plots under study. The patterning of VWC was directly influenced by the rainfall amount with lower VWC observed in the grazed compared to the non-grazed plots. Rainfall variability, grazing and their interaction significantly affected changes in VWC (p < 0.05) and subsequently total biomass and CO2 fluxes. VWC had a strong influence on CO2 fluxes under 50% rainfall reduction in the grazed (r2 = 0.91; p < 0.05) and ambient rainfall in the ungrazed (r2 = 0.77; p < 0.05). The dependence of biomass on VWC across plots was enhanced under grazed (r2 = 0.78 - 0.87; p < 0.05) condition as compared to ungrazed (r2 = 0.44 - 0.85; p < 0.05). The C:N ratio was however not correlated to VWC across plots. This study provides insight on how the predicted trends in humid savanna will respond to changes influenced by rainfall variability and livestock grazing and consequently the sustainable management of such ecosystems.Keywords: CO2 fluxes, rainfall manipulation, soil properties, sustainability
Procedia PDF Downloads 127329 Literature Review on the Barriers to Access Credit for Small Agricultural Producers and Policies to Mitigate Them in Developing Countries
Authors: Margarita Gáfaro, Karelys Guzmán, Paola Poveda
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This paper establishes the theoretical aspects that explain the barriers to accessing credit for small agricultural producers in developing countries and identifies successful policy experiences to mitigate them. We will test two hypotheses. The first one is that information asymmetries, high transaction costs and high-risk exposure limit the supply of credit to small agricultural producers in developing countries. The second hypothesis is that low levels of financial education and productivity and high uncertainty about the returns of agricultural activity limit the demand for credit. To test these hypotheses, a review of the theoretical and empirical literature on access to rural credit in developing countries will be carried out. The first part of this review focuses on theoretical models that incorporate information asymmetries in the credit market and analyzes the interaction between these asymmetries and the characteristics of the agricultural sector in developing countries. Some of the characteristics we will focus on are the absence of collateral, the underdevelopment of the judicial systems and insurance markets, and the high dependence on climatic factors of production technologies. The second part of this review focuses on the determinants of credit demand by small agricultural producers, including the profitability of productive projects, security conditions, risk aversion or loss, financial education, and cognitive biases, among others. There are policies that focus on resolving these supply and demand constraints and managing to improve credit access. Therefore, another objective of this paper is to present a review of effective policies that have promoted access to credit for smallholders in the world. For this, information available in policy documents will be collected. This information will be complemented by interviews with officials in charge of the design and execution of these policies in a subset of selected countries. The information collected will be analyzed in light of the conceptual framework proposed in the first two parts of this section. The barriers to access to credit that each policy attempts to resolve and the factors that could explain its effectiveness will be identified.Keywords: agricultural economics, credit access, smallholder, developing countries
Procedia PDF Downloads 60328 Gender-based Violence and Associated Factors among Private College Female Students in Harar City, Ethiopia, Jan 2023
Authors: Taju Abdela Mohammed
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Introduction: There has been a rise in awareness of violence against young women and girls, particularly when it occurs in educational environments. Gender-based violence in schools is a significant barrier. Therefore, it would be a threat to the achievement of the sustainable development goals, strive for gender equality in all our programs, right from the planning stages, to make sure we are as equitable as possible. Research on the causes, attitudes, and perceptions of gender-based violence was scant. Furthermore, there aren't many studies done on female students attending private colleges. Thus, the purpose of this study is to evaluate the frequency of gender-based violence and related variables among female students attending private colleges in Harar City, Ethiopia. Methodology: A facility-based mixed method concurrent triangulation study design was conducted among 500 randomly selected Private college female students in Harar City. Self-administered questionnaire and an in-depth interview were used to collect the data. The collected data were cleaned and analyzed using a statistical package for social science. Descriptive statistics were conducted and the results were reported using frequency, and percentile. Bivariate logistic regression was performed to identify associated factors. Adjusted odds ratios with 95% confidence intervals and p values < 0.05 were used to explain statistically significant associations. Thematic analysis was used to manually translate, transcribe, and analyze qualitative data. Result: The study showed the prevalence of gender-based violence was 338 (67.6%) (CI 0.432–0.721) Private college female students in Harar city Administration. Age less than 20 years and 20–24 years, [AOR = 0.21, 95% CI (0.03–0.81)] and [AOR = 0.12, 95% CI (0.03–0.51)], tight family control, [AOR = 5.12, 95% CI (1.43–6.9)], Witnessed father abuse mother at childhood; [AOR = 4.04, 95% CI (1.36–12.1)], had drunkenness female or boyfriend; [AOR = 2.12, 95% CI (1.60–14.05)] had significant association with gender-based violence. Conclusion: Our study shows the prevalence of gender-based violence among Private college female students is significant. This is due to the fact that gender-based violence, such as school dropout, unintended pregnancy, abortion, STDs, and psychological disorders, is abandoning young girls' lives and lowering their productivity.Keywords: female students, gender-violence, harar, Ethiopia
Procedia PDF Downloads 59327 Online Bakery Management System Proposal
Authors: Alexander Musyoki, Collins Odour
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Over the past few years, the bakery industry in Kenya has experienced significant growth largely in part to the increased adoption of technology and automation in their processes; more specifically due to the adoption of bakery management systems to help in running bakeries. While they have been largely responsible for the improved productivity and efficiency in bakeries, most of them are now outdated and pose more challenges than benefits. The proposed online bakery management system mentioned in this paper aims to address this by allowing bakery owners to track inventory, budget, job progress, and data analytics on each job and in doing so, promote the Sustainable Development Goals 3 and 12, which aim to ensure healthy lives and promote sustainable economic growth as the proposed benefits of these features include scalability, easy accessibility, reduced acquisition costs, better reliability, and improved functionality that will allow bakeries to become more competitive, reduce waste and track inventory more efficiently. To better understand the challenges, a comprehensive study has been performed to assess these traditional systems and try to understand if an online bakery management system can prove to be advantageous to bakery owners. The study conducted gathered feedback from bakery owners and employees in Nairobi County, Kenya using an online survey with a response rate of about 86% from the target population. The responses cited complex and hard to use bakery management systems (59.7%), lack of portability from one device to the other (58.1%) and high acquisition costs (51.6%) as the top challenges of traditional bakery management systems. On the other hand, some of the top benefits that most of the respondents would realize from the online bakery management system was better reliability (58.1%) and reduced acquisition costs (58.1%). Overall, the findings suggest that an online bakery management system has a lot of advantages over traditional systems and is likely to be well-received in the market. In conclusion, the proposed online bakery management system has the potential to improve the efficiency and competitiveness of small-sized bakeries in Nairobi County. Further research is recommended to expand the sample size and diversity of respondents and to conduct more in-depth analyses of the data collected.Keywords: ICT, technology and automation, bakery management systems, food innovation
Procedia PDF Downloads 71326 Alternative Approach to the Machine Vision System Operating for Solving Industrial Control Issue
Authors: M. S. Nikitenko, S. A. Kizilov, D. Y. Khudonogov
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The paper considers an approach to a machine vision operating system combined with using a grid of light markers. This approach is used to solve several scientific and technical problems, such as measuring the capability of an apron feeder delivering coal from a lining return port to a conveyor in the technology of mining high coal releasing to a conveyor and prototyping an autonomous vehicle obstacle detection system. Primary verification of a method of calculating bulk material volume using three-dimensional modeling and validation in laboratory conditions with relative errors calculation were carried out. A method of calculating the capability of an apron feeder based on a machine vision system and a simplifying technology of a three-dimensional modelled examined measuring area with machine vision was offered. The proposed method allows measuring the volume of rock mass moved by an apron feeder using machine vision. This approach solves the volume control issue of coal produced by a feeder while working off high coal by lava complexes with release to a conveyor with accuracy applied for practical application. The developed mathematical apparatus for measuring feeder productivity in kg/s uses only basic mathematical functions such as addition, subtraction, multiplication, and division. Thus, this fact simplifies software development, and this fact expands the variety of microcontrollers and microcomputers suitable for performing tasks of calculating feeder capability. A feature of an obstacle detection issue is to correct distortions of the laser grid, which simplifies their detection. The paper presents algorithms for video camera image processing and autonomous vehicle model control based on obstacle detection machine vision systems. A sample fragment of obstacle detection at the moment of distortion with the laser grid is demonstrated.Keywords: machine vision, machine vision operating system, light markers, measuring capability, obstacle detection system, autonomous transport
Procedia PDF Downloads 105