Search results for: agriculture yield prediction

Authors: Farnaz Farhangi

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Many people in New Zealand believe that the access to water is inexhaustible, and it comes from a history of virtually unrestricted access to it. For the region like Hamilton which is one of New Zealand’s fastest growing cities, it is crucial for policy makers to know about the future water consumption and implementation of rules and regulation such as universal water metering. Hamilton residents use water freely and they do not have any idea about how much water they use. Hence, one of proposed objectives of this research is focusing on forecasting water consumption using different methods. Residential water consumption time series exhibits seasonal and trend variations. Seasonality is the pattern caused by repeating events such as weather conditions in summer and winter, public holidays, etc. The problem with this seasonal fluctuation is that, it dominates other time series components and makes difficulties in determining other variations (such as educational campaign’s effect, regulation, etc.) in time series. Apart from seasonality, a stochastic trend is also combined with seasonality and makes different effects on results of forecasting. According to the forecasting literature, preprocessing (de-trending and de-seasonalization) is essential to have more performed forecasting results, while some other researchers mention that seasonally non-adjusted data should be used. Hence, I answer the question that is pre-processing essential? A wide range of forecasting methods exists with different pros and cons. In this research, I apply double seasonal ARIMA and Artificial Neural Network (ANN), considering diverse elements such as seasonality and calendar effects (public and school holidays) and combine their results to find the best predicted values. My hypothesis is the examination the results of combined method (hybrid model) and individual methods and comparing the accuracy and robustness. In order to use ARIMA, the data should be stationary. Also, ANN has successful forecasting applications in terms of forecasting seasonal and trend time series. Using a hybrid model is a way to improve the accuracy of the methods. Due to the fact that water demand is dominated by different seasonality, in order to find their sensitivity to weather conditions or calendar effects or other seasonal patterns, I combine different methods. The advantage of this combination is reduction of errors by averaging of each individual model. It is also useful when we are not sure about the accuracy of each forecasting model and it can ease the problem of model selection. Using daily residential water consumption data from January 2000 to July 2015 in Hamilton, I indicate how prediction by different methods varies. ANN has more accurate forecasting results than other method and preprocessing is essential when we use seasonal time series. Using hybrid model reduces forecasting average errors and increases the performance.

Keywords: artificial neural network (ANN), double seasonal ARIMA, forecasting, hybrid model

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Authors: Ruchirek Ratchaburi, W. Kevin. Hicks, Christopher S. Malley, Lisa D. Emberson

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Air pollution problems in Thailand have improved over the last few decades, but in some areas, concentrations of coarse particulate matter (PM₁₀) are above health and regulatory guidelines. It is, therefore, useful to investigate how PM₁₀ varies across Thailand, what conditions cause this variation, and how could PM₁₀ concentrations be reduced. This research uses data collected by the Thailand Pollution Control Department (PCD) from 17 monitoring sites, located across 12 provinces, and obtained between 2011 and 2015 to assess PM₁₀ concentrations and the conditions that lead to different levels of pollution. This is achieved through exploration of air mass pathways using trajectory analysis, used in conjunction with the monitoring data, to understand the contribution of different months, an hour of the day and source regions to annual PM₁₀ concentrations in Thailand. A focus is placed on locations that exceed the national standard for the protection of human health. The analysis shows how this approach can be used to explore the influence of biomass burning on annual average PM₁₀ concentration and the difference in air pollution conditions between Northern and Southern Thailand. The results demonstrate the substantial contribution that open biomass burning from agriculture and forest fires in Thailand and neighboring countries make annual average PM₁₀ concentrations. The analysis of PM₁₀ measurements at monitoring sites in Northern Thailand show that in general, high concentrations tend to occur in March and that these particularly high monthly concentrations make a substantial contribution to the overall annual average concentration. In 2011, a > 75% reduction in the extent of biomass burning in Northern Thailand and in neighboring countries resulted in a substantial reduction not only in the magnitude and frequency of peak PM₁₀ concentrations but also in annual average PM₁₀ concentrations at sites across Northern Thailand. In Southern Thailand, the annual average PM₁₀ concentrations for individual years between 2011 and 2015 did not exceed the human health standard at any site. The highest peak concentrations in Southern Thailand were much lower than for Northern Thailand for all sites. The peak concentrations at sites in Southern Thailand generally occurred between June and October and were associated with air mass back trajectories that spent a substantial proportion of time over the sea, Indonesia, Malaysia, and Thailand prior to arrival at the monitoring sites. The results show that emissions reductions from biomass burning and forest fires require action on national and international scales, in both Thailand and neighboring countries, such action could contribute to ensuring compliance with Thailand air quality standards.

Keywords: annual average concentration, long-range transport, open biomass burning, particulate matter

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Authors: Linda D. F. Bambara, Marie Sawadogo

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Jatropha curcas (jatropha) is the plant that has been the most studied for biofuel production in West Africa. There exist however other plants such as Balanites aegyptiaca (balanites) that have been targeted as a potential feedstock for biofuel production. This biomass could be an alternative feedstock for the production of straight vegetable oil (SVO) at costs lower than jatropha-based SVO production costs. This study aims firstly to determine, through an MILP model, the optimal organization that minimizes the costs of the oilseeds supply of two biomass conversion units (BCU) exploiting respectively jatropha seeds and the balanitès seeds. Secondly, the study aims to carry out a comparative study of these costs obtained for each BCU. The model was then implemented on two theoretical cases studies built on the basis of the common practices in Burkina Faso and two scenarios were carried out for each case study. In Scenario 1, 3 pre-processing locations ("at the harvesting area", "at the gathering points", "at the BCU") are possible. In scenario 2, only one location ("at the BCU") is possible. For each biomass, the system studied is the upstream supply chain (harvesting, transport and pre-processing (drying, dehulling, depulping)), including cultivation (for jatropha). The model optimizes the area of land to be exploited based on the productivity of the studied plants and material losses that may occur during the harvesting and the supply of the BCU. It then defines the configuration of the logistics network allowing an optimal supply of the BCU taking into account the most common means of transport in West African rural areas. For the two scenarios, the results of the implementation showed that the total area exploited for balanites (1807 ha) is 4.7 times greater than the total area exploited for Jatropha (381 ha). In both case studies, the location of pre-processing “at the harvesting area” was always chosen for scenario1. As the balanites trees were not planted and because the first harvest of the jatropha seeds took place 4 years after planting, the cost price of the seeds at the BCU without the pre-processing costs was about 430 XOF/kg. This cost is 3 times higher than the balanites's one, which is 140 XOF/kg. After the first year of harvest, i.e. 5 years after planting, and assuming that the yield remains constant, the same cost price is about 200 XOF/kg for Jatropha. This cost is still 1.4 times greater than the balanites's one. The transport cost of the balanites seeds is about 120 XOF/kg. This cost is similar for the jatropha seeds. However, when the pre-processing is located at the BCU, i.e. for scenario2, the transport costs of the balanites seeds is 1200 XOF/kg. These costs are 6 times greater than the transport costs of jatropha which is 200 XOF/kg. These results show that the cost price of the balanites seeds at the BCU can be competitive compared to the jatropha's one if the pre-processing is located at the harvesting area.

Keywords: Balanites aegyptiaca, biomass conversion, Jatropha curcas, optimization, post-harvest operations

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Authors: Sabolč Pap, Srđana Kolaković, Jelena Radonić, Ivana Mihajlović, Dragan Adamović, Mirjana Vojinović Miloradov, Maja Turk Sekulić

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Activated carbon is one of the most used and tested adsorbents in the removal of industrial organic compounds, heavy metals, pharmaceuticals and dyes. Different types of lignocellulosic materials were used as potential precursors in the production of low cost activated carbon. There are, two different processes for the preparation and production of activated carbon: physical and chemical. Chemical activation includes impregnating the lignocellulosic raw materials with chemical agents (H3PO4, HNO3, H2SO4 and NaOH). After impregnation, the materials are carbonized and washed to eliminate the residues. The chemical activation, which was used in this study, has two important advantages when compared to the physical activation. The first advantage is the lower temperature at which the process is conducted, and the second is that the yield (mass efficiency of activation) of the chemical activation tends to be greater. Preparation of activated carbon included the following steps: apricot stones were crushed in a mill and washed with distilled water. Later, the fruit stones were impregnated with a solution of 50% H3PO4. After impregnation, the solution was filtered to remove the residual acid. Subsequently impregnated samples were air dried at room temperature. The samples were placed in a furnace and heated (10 °C/min) to the final carbonization temperature of 500 °C for 2 h without the use of nitrogen. After cooling, the adsorbent was washed with distilled water to achieve acid free conditions and its pH was monitored until the filtrate pH value exceeded 4. Chemical characterizations of the prepared activated carbon were analyzed by FTIR spectroscopy. FTIR spectra were recorded with a (Thermo Nicolet Nexus 670 FTIR) spectrometer, from 400 to 4000 cm-1 wavenumbers, identifying the functional groups on the surface of the activated carbon. The FTIR spectra of adsorbent showed a broad band at 3405.91 cm-1 due to O–H stretching vibration and a peak at 489.00 cm-1 due to O–H bending vibration. Peaks between the range of 3700 and 3200 cm−1 represent the overlapping peaks of stretching vibrations of O–H and N–H groups. The distinct absorption peaks at 2919.86 cm−1 and 2848.24 cm−1 could be assigned to -CH stretching vibrations of –CH2 and –CH3 functional groups. The adsorption peak at 1566.38 cm−1 could be characterized by primary and secondary amide bands. The sharp bond within 1164.76 – 987.86 cm−1 is attributed to the C–O groups, which confirms the lignin structure of the activated carbon. The present study has shown that the activated carbons prepared from apricot stone have a functional group on their surface, which can positively affect the adsorption characteristics with this material.

Keywords: activated carbon, FTIR, H3PO4, lignocellulosic raw materials

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Authors: Béla Kovács, Éva Bódi, Farzaneh Garousi, Szilvia Várallyay, Áron Soós, Xénia Vágó, Dávid Andrási

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In agriculture for analysis of elements in different food and food raw materials, moreover environmental samples generally flame atomic absorption spectrometers (FAAS), graphite furnace atomic absorption spectrometers (GF-AAS), inductively coupled plasma optical emission spectrometers (ICP-OES) and inductively coupled plasma mass spectrometers (ICP-MS) are routinely applied. An inductively coupled plasma mass spectrometer (ICP-MS) is capable for analysis of 70-80 elements in multielemental mode, from 1-5 cm3 volume of a sample, moreover the detection limits of elements are in µg/kg-ng/kg (ppb-ppt) concentration range. All the analytical instruments have different physical and chemical interfering effects analysing the above types of samples. The smaller the concentration of an analyte and the larger the concentration of the matrix the larger the interfering effects. Nowadays there is very important to analyse growingly smaller concentrations of elements. From the above analytical instruments generally the inductively coupled plasma mass spectrometer is capable of analysing the smallest concentration of elements. The applied ICP-MS instrument has Collision Cell Technology (CCT) also. Using CCT mode certain elements have better (smaller) detection limits with 1-3 magnitudes comparing to a normal ICP-MS analytical method. The CCT mode has better detection limits mainly for analysis of selenium, arsenic, germanium, vanadium and chromium. To elaborate an analytical method for trace elements with an inductively coupled plasma mass spectrometer the most important interfering effects (problems) were evaluated: 1) Physical interferences; 2) Spectral interferences (elemental and molecular isobaric); 3) Effect of easily ionisable elements; 4) Memory interferences. Analysing food and food raw materials, moreover environmental samples an other (new) interfering effect emerged in ICP-MS, namely the effect of various matrixes having different evaporation and nebulization effectiveness, moreover having different quantity of carbon content of food and food raw materials, moreover environmental samples. In our research work the effect of different water-soluble compounds furthermore the effect of various quantity of carbon content (as sample matrix) were examined on changes of intensity of the applied elements. So finally we could find “opportunities” to decrease or eliminate the error of the analyses of applied elements (Cr, Co, Ni, Cu, Zn, Ge, As, Se, Mo, Cd, Sn, Sb, Te, Hg, Pb, Bi). To analyse these elements in the above samples, the most appropriate inductively coupled plasma mass spectrometer is a quadrupole instrument applying a collision cell technique (CCT). The extent of interfering effect of carbon content depends on the type of compounds. The carbon content significantly affects the measured concentration (intensities) of the above elements, which can be corrected using different internal standards.

Keywords: elements, environmental and food samples, ICP-MS, interference effects

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Authors: Rajeev Ravindran, Amit K. Jaiswal

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Lignocellulose is the largest reservoir of inexpensive, renewable source of carbon. It is composed of lignin, cellulose and hemicellulose. Cellulose and hemicellulose is composed of reducing sugars glucose, xylose and several other monosaccharides which can be metabolised by microorganisms to produce several value added products such as biofuels, enzymes, aminoacids etc. Enzymatic treatment of lignocellulose leads to the release of monosaccharides such as glucose and xylose. However, factors such as the presence of lignin, crystalline cellulose, acetyl groups, pectin etc. contributes to recalcitrance restricting the effective enzymatic hydrolysis of cellulose and hemicellulose. In order to overcome these problems, pre-treatment of lignocellulose is generally carried out which essentially facilitate better degradation of lignocellulose. A range of pre-treatment strategy is commonly employed based on its mode of action viz. physical, chemical, biological and physico-chemical. However, existing pretreatment strategies result in lower sugar yield and formation of inhibitory compounds. In order to overcome these problems, we proposes a novel pre-treatment, which utilises the superior oxidising capacity of alkaline potassium permanganate assisted by ultra-sonication to break the covalent bonds in spent coffee waste to remove recalcitrant compounds such as lignin. The pre-treatment was conducted for 30 minutes using 2% (w/v) potassium permanganate at room temperature with solid to liquid ratio of 1:10. The pre-treated spent coffee waste (SCW) was subjected to enzymatic hydrolysis using enzymes cellulase and hemicellulase. Shake flask experiments were conducted with a working volume of 50mL buffer containing 1% substrate. The results showed that the novel pre-treatment strategy yielded 7 g/L of reducing sugar as compared to 3.71 g/L obtained from biomass that had undergone dilute acid hydrolysis after 24 hours. From the results obtained it is fairly certain that ultrasonication assists the oxidation of recalcitrant components in lignocellulose by potassium permanganate. Enzyme hydrolysis studies suggest that ultrasound assisted alkaline potassium permanganate pre-treatment is far superior over treatment by dilute acid. Furthermore, SEM, XRD and FTIR were carried out to analyse the effect of the new pre-treatment strategy on structure and crystallinity of pre-treated spent coffee wastes. This novel one-step pre-treatment strategy was implemented under mild conditions and exhibited high efficiency in the enzymatic hydrolysis of spent coffee waste. Further study and scale up is in progress in order to realise future industrial applications.

Keywords: spent coffee waste, alkaline potassium permanganate, ultra-sonication, physical characterisation

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Authors: Restituto I. Rodelas

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The higher education has adopted the outcomes-based education from K-12. In this approach, the teacher uses any teaching and learning strategies that enable the students to achieve the learning outcomes. The students may be required to exert more effort and figure things out on their own. Hence, outcomes-based students are assumed to be more responsible and more capable of applying the knowledge learned. Another approach that the higher education in the Philippines is starting to adopt from other countries is blended learning. This combination of classroom and fully online instruction and learning is expected to be more effective. Participating in the online sessions, however, is entirely up to the students. Thus, the effect of blended learning on the performance of students in Statistics may be mediated by outcomes-based education. If there is a significant positive mediating effect, then blended learning can be optimized by integrating outcomes-based education. In this study, the sample will consist of four blended learning Statistics classes at Jose Rizal University in the second semester of AY 2015–2016. Two of these classes will be assigned randomly to the experimental group that will be handled using outcomes-based education. The two classes in the control group will be handled using the traditional lecture approach. Prior to the discussion of the first topic, a pre-test will be administered. The same test will be given as posttest after the last topic is covered. In order to establish equality of the groups’ initial knowledge, single factor ANOVA of the pretest scores will be performed. Single factor ANOVA of the posttest-pretest score differences will also be conducted to compare the performance of the experimental and control groups. When a significant difference is obtained in any of these ANOVAs, post hoc analysis will be done using Tukey's honestly significant difference test (HSD). Mediating effect will be evaluated using correlation and regression analyses. The groups’ initial knowledge are equal when the result of pretest scores ANOVA is not significant. If the result of score differences ANOVA is significant and the post hoc test indicates that the classes in the experimental group have significantly different scores from those in the control group, then outcomes-based education has a positive effect. Let blended learning be the independent variable (IV), outcomes-based education be the mediating variable (MV), and score difference be the dependent variable (DV). There is mediating effect when the following requirements are satisfied: significant correlation of IV to DV, significant correlation of IV to MV, significant relationship of MV to DV when both IV and MV are predictors in a regression model, and the absolute value of the coefficient of IV as sole predictor is larger than that when both IV and MV are predictors. With a positive mediating effect of outcomes-base education on the effect of blended learning on student performance, it will be recommended to integrate outcomes-based education into blended learning. This will yield the best learning results.

Keywords: outcome-based teaching, blended learning, face-to-face, student-centered

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Authors: A. Shakoor, M. Arshad

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The utilization of groundwater resources in irrigation has significantly increased during the last two decades due to constrained canal water supplies. More than 70% of the farmers in the Punjab, Pakistan, depend directly or indirectly on groundwater to meet their crop water demands and hence, an unchecked paradigm shift has resulted in aquifer depletion and deterioration. Therefore, a comprehensive research was carried at central Punjab-Pakistan, regarding spatiotemporal variation in groundwater level and quality. Processing MODFLOW for window (PMWIN) and MT3D (solute transport model) models were used for existing and future prediction of groundwater level and quality till 2030. The comprehensive data set of aquifer lithology, canal network, groundwater level, groundwater salinity, evapotranspiration, groundwater abstraction, recharge etc. were used in PMWIN model development. The model was thus, successfully calibrated and validated with respect to groundwater level for the periods of 2003 to 2007 and 2008 to 2012, respectively. The coefficient of determination (R2) and model efficiency (MEF) for calibration and validation period were calculated as 0.89 and 0.98, respectively, which argued a high level of correlation between the calculated and measured data. For solute transport model (MT3D), the values of advection and dispersion parameters were used. The model used for future scenario up to 2030, by assuming that there would be no uncertain change in climate and groundwater abstraction rate would increase gradually. The model predicted results revealed that the groundwater would decline from 0.0131 to 1.68m/year during 2013 to 2030 and the maximum decline would be on the lower side of the study area, where infrastructure of canal system is very less. This lowering of groundwater level might cause an increase in the tubewell installation and pumping cost. Similarly, the predicted total dissolved solids (TDS) of the groundwater would increase from 6.88 to 69.88mg/L/year during 2013 to 2030 and the maximum increase would be on lower side. It was found that in 2030, the good quality would reduce by 21.4%, while marginal and hazardous quality water increased by 19.28 and 2%, respectively. It was found from the simulated results that the salinity of the study area had increased due to the intrusion of salts. The deterioration of groundwater quality would cause soil salinity and ultimately the reduction in crop productivity. It was concluded from the predicted results of groundwater model that the groundwater deteriorated with the depth of water table i.e. TDS increased with declining groundwater level. It is recommended that agronomic and engineering practices i.e. land leveling, rainwater harvesting, skimming well, ASR (Aquifer Storage and Recovery Wells) etc. should be integrated to meliorate management of groundwater for higher crop production in salt affected soils.

Keywords: groundwater quality, groundwater management, PMWIN, MT3D model

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Authors: Tsega Asresa, Getahun Tigistu, Melaku Bayih

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Computer vision is a subfield of artificial intelligence that allows computers and systems to extract meaning from digital images and video. It is used in a wide range of fields of study, including self-driving cars, video surveillance, medical diagnosis, manufacturing, law, agriculture, quality control, health care, facial recognition, and military applications. Aromatic medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, essential oils, decoration, cleaning, and other natural health products for therapeutic and Aromatic culinary purposes. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs but also going to export for valuable foreign currency exchange. In Ethiopia, there is a lack of technologies for the classification and identification of Aromatic medicinal plant parts and disease type cured by aromatic medicinal plants. Farmers, industry personnel, academicians, and pharmacists find it difficult to identify plant parts and disease types cured by plants before ingredient extraction in the laboratory. Manual plant identification is a time-consuming, labor-intensive, and lengthy process. To alleviate these challenges, few studies have been conducted in the area to address these issues. One way to overcome these problems is to develop a deep learning model for efficient identification of Aromatic medicinal plant parts with their corresponding disease type. The objective of the proposed study is to identify the aromatic medicinal plant parts and their disease type classification using computer vision technology. Therefore, this research initiated a model for the classification of aromatic medicinal plant parts and their disease type by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides roots, flowers, fruits, and latex. For this study, the researcher used RGB leaf images with a size of 128x128 x3. In this study, the researchers trained five cutting-edge models: convolutional neural network, Inception V3, Residual Neural Network, Mobile Network, and Visual Geometry Group. Those models were chosen after a comprehensive review of the best-performing models. The 80/20 percentage split is used to evaluate the model, and classification metrics are used to compare models. The pre-trained Inception V3 model outperforms well, with training and validation accuracy of 99.8% and 98.7%, respectively.

Keywords: aromatic medicinal plant, computer vision, convolutional neural network, deep learning, plant classification, residual neural network

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Authors: Shiwani Bhatnagar, K. K. Srivastava, Sangeeta Singh, Ameen Ullah Khan, Bundesh Kumar, Lokendra Singh Rathore

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From the instigation of the world medicinal plants are treated as part and parcel of human society to fight against diseases. Azadirachta indica (Neem) a herbal plant has been used as an Indian traditional medicine since ages and its products are acknowledged to solve agricultural, forestry and public health related problems, owing to its beneficial medicinal properties. Each part of the neem tree is known for its medicinal property. Bark & leaf extracts of neem have been used to control leprosy, respiratory disorders, constipation and also as blood purifier and a general health tonic. Neem is still regarded as ' rural community dispensary' in India or a tree for solving medical problems. Use of Neem as pesticides for the management of insect pest of agriculture crops and forestry has been seen as a shift in the use of synthetic pesticides to ecofriendly botanicals. Neem oil and seed extracts possess germicidal and anti-bacterial properties which when sprayed on the plant helps in protecting them from foliage pests. Azadirachtin, the main active ingredient found in neem tree, acts as an insect repellent and antifeedant. However the young plants are susceptible to many insect pest and foliar diseases. Recently, in the avenue plantation, planted by Arid Forest Research Institute, Jodhpur, around the premises of IIT Jodhpur, two years old neem plants were found to be severely infested with tip borer Laspeyresia koenigana (Family: Eucosmidae). The adult moth of L. koenigana lays eggs on the tender shoots and the young larvae tunnel into the shoot and feed inside. A small pinhole can be seen at the entrance point, from where the larva enters in to the stem. The severely attached apical shoots exhibit profuse gum exudation resulting in development of a callus structure. The internal feeding causes the stem to wilt and the leaves to dry up from the tips resulting in growth retardation. Alternaria Leaf spot and blight symptoms were also recorded on these neem plants. For the management of tip borer and Alternaria Leaf spot, foliar spray of monocrotophos @0.05% and Dithane M-45 @ 0.15% and powermin @ 2ml/lit were found efficient in managing the insect pest and foliar disease problem. No Further incidence of pest/diseases was noticed.

Keywords: azadirachta indica, alternaria leaf spot, laspeyresia koenigana, management

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Authors: Luis Enrique Escalante Ochoa

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This paper attempts to assess the impacts of Climate change (CC) on inequalities in the labour market. CC will have the most serious effects on some vulnerable economic sectors, such as agriculture, livestock or tourism, but also on the most vulnerable population groups. The objective of this research is to evaluate the impact of CC on the labour market and particularly on Mexican women. Influential documents such as the synthesis reports produced by the Intergovernmental Panel on Climate Change (IPCC) in 2007 and 2014 revived a global effort to counteract the effects of CC, called for an analysis of the impacts on vulnerable socio-economic groups and on economic activities, and for the development of decision-making tools to enable policy and other decisions based on the complexity of the world in relation to climate change, taking into account socio-economic attributes. We follow up this suggestion and determine the impact of CC on vulnerable populations in the Mexican labour market, taking into account two attributes (gender and level of qualification of workers). Most studies have focused on the effects of CC on the agricultural sector, as it is considered a highly vulnerable economic sector to the effects of climate variability. This research seeks to contribute to the existing literature taking into account, in addition to the agricultural sector, other sectors such as tourism, water availability, and energy that are of vital importance to the Mexican economy. Likewise, the effects of climate change will be extended to the labour market and specifically to women who in some cases have been left out. The studies are sceptical about the impact of CC on the female labour market because of the perverse effects on women's domestic work, which are too often omitted from analyses. This work will contribute to the literature by integrating domestic work, which in the case of Mexico is much higher among women than among men (80.9% vs. 19.1%), according to the 2009 time use survey. This study is relevant since it will allow us to analyse impacts of climate change not only in the labour market of the formal economy, but also in the non-market sphere. Likewise, we consider that including the gender dimension is valid for the Mexican economy as it is a country with high degrees of gender inequality in the labour market. In the OECD economic study for Mexico (2017), the low labour participation of Mexican women is highlighted. Although participation has increased substantially in recent years (from 36% in 1990 to 47% in 2017), it remains low compared to the OECD average where women participate around 70% of the labour market. According to Mexico's 2009 time use survey, domestic work represents about 13% of the total time available. Understanding the interdependence between the market and non-market spheres, and the gender division of labour within them is the necessary premise for any economic analysis aimed at promoting gender equality and inclusive growth.

Keywords: climate change, labour market, domestic work, rural sector

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Authors: Asfaw Gezae Daful, Mohsen Alimandagari, Kathleen Haigh, Somayeh Farzad, Eugene Van Rensburg, Johann F. Görgens

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The sugar industry has to 're-invent' itself to ensure long-term economic survival and opportunities for job creation and enhanced community-level impacts, given increasing pressure from fluctuating and low global sugar prices, increasing energy prices and sustainability demands. We propose biorefineries for re-vitalisation of the sugar industry using low value lignocellulosic biomass (sugarcane bagasse, leaves, and tops) annexed to existing sugar mills, producing a spectrum of high value platform chemicals along with biofuel, bioenergy, and electricity. Opportunity is presented for greener products, to mitigate climate change and overcome economic challenges. Xylose from labile hemicellulose remains largely underutilized and the conversion to value-add products a major challenge. Insight is required on pretreatment and/or extraction to optimize production of cellulosic ethanol together with lactic acid, furfural or biopolymers from sugarcane bagasse, leaves, and tops. Experimental conditions for alkaline and pressurized hot water extraction dilute acid and steam explosion pretreatment of sugarcane bagasse and harvest residues were investigated to serve as a basis for developing various process scenarios under a sugarcane biorefinery scheme. Dilute acid and steam explosion pretreatment were optimized for maximum hemicellulose recovery, combined sugar yield and solids digestibility. An optimal range of conditions for alkaline and liquid hot water extraction of hemicellulosic biopolymers, as well as conditions for acceptable enzymatic digestibility of the solid residue, after such extraction was established. Using data from the above, a series of energy efficient biorefinery scenarios are under development and modeled using Aspen Plus® software, to simulate potential factories to better understand the biorefinery processes and estimate the CAPEX and OPEX, environmental impacts, and overall viability. Rigorous and detailed sustainability assessment methodology was formulated to address all pillars of sustainability. This work is ongoing and to date, models have been developed for some of the processes which can ultimately be combined into biorefinery scenarios. This will allow systematic comparison of a series of biorefinery scenarios to assess the potential to reduce negative impacts on and maximize the benefits of social, economic, and environmental factors on a lifecycle basis.

Keywords: biomass, biorefinery, green economy, sustainability

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Authors: Hind Alshoubaki

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The world is now confronting a widespread urban phenomenon: refugee camps, which have mostly been established in ‘rushing mode,’ pointing toward affording temporary settlements for refugees that provide them with minimum levels of safety, security and protection from harsh weather conditions within a very short time period. In fact, those emergency settlements are transforming into permanent ones since time is a decisive factor in terms of construction and camps’ age. These play an essential role in transforming their temporary character into a permanent one that generates deep modifications to the city’s territorial structure, shaping a new identity and creating a contentious change in the city’s form and history. To achieve a better understanding for the transformation of refugee camps, this study is based on a mixed-methods approach: the qualitative approach explores different refugee camps and analyzes their transformation process in terms of population density and the changes to the city’s territorial structure and urban features. The quantitative approach employs a statistical regression analysis as a reliable prediction of refugees’ satisfaction within the Zaatari camp in order to predict its future transformation. Obviously, refugees’ perceptions of their current conditions will affect their satisfaction, which plays an essential role in transforming emergency settlements into permanent cities over time. The test basically discusses five main themes: the access and readiness of schools, the dispersion of clinics and shopping centers; the camp infrastructure, the construction materials, and the street networks. The statistical analysis showed that Syrian refugees were not satisfied with their current conditions inside the Zaatari refugee camp and that they had started implementing changes according to their needs, desires, and aspirations because they are conscious about the fact of their prolonged stay in this settlement. Also, the case study analyses showed that neglecting the fact that construction takes time leads settlements being created with below-minimum standards that are deteriorating and creating ‘slums,’ which lead to increased crime rates, suicide, drug use and diseases and deeply affect cities’ urban tissues. For this reason, recognizing the ‘temporary-eternal’ character of those settlements is the fundamental concept to consider refugee camps from the beginning as definite permanent cities. This is the key factor to minimize the trauma of displacement on both refugees and the hosting countries. Since providing emergency settlements within a short time period does not mean using temporary materials, having a provisional character or creating ‘makeshift cities.’

Keywords: refugee, refugee camp, temporary, Zaatari

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Authors: Szymon Rutkowski, Tomasz Korbak

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We present a reinforcement-learning-based method of training neural machine translation models without parallel corpora. The standard encoder-decoder approach to machine translation suffers from two problems we aim to address. First, it needs parallel corpora, which are scarce, especially for low-resource languages. Second, it lacks psychological plausibility of learning procedure: learning a foreign language is about learning to communicate useful information, not merely learning to transduce from one language’s 'encoding' to another. We instead pose the problem of learning to translate as learning a policy in a communication game between two agents: the translator and the classifier. The classifier is trained beforehand on a natural language inference task (determining the entailment relation between a premise and a hypothesis) in the target language. The translator produces a sequence of actions that correspond to generating translations of both the hypothesis and premise, which are then passed to the classifier. The translator is rewarded for classifier’s performance on determining entailment between sentences translated by the translator to disciple’s native language. Translator’s performance thus reflects its ability to communicate useful information to the classifier. In effect, we train a machine translation model without the need for parallel corpora altogether. While similar reinforcement learning formulations for zero-shot translation were proposed before, there is a number of improvements we introduce. While prior research aimed at grounding the translation task in the physical world by evaluating agents on an image captioning task, we found that using a linguistic task is more sample-efficient. Natural language inference (also known as recognizing textual entailment) captures semantic properties of sentence pairs that are poorly correlated with semantic similarity, thus enforcing basic understanding of the role played by compositionality. It has been shown that models trained recognizing textual entailment produce high-quality general-purpose sentence embeddings transferrable to other tasks. We use stanford natural language inference (SNLI) dataset as well as its analogous datasets for French (XNLI) and Polish (CDSCorpus). Textual entailment corpora can be obtained relatively easily for any language, which makes our approach more extensible to low-resource languages than traditional approaches based on parallel corpora. We evaluated a number of reinforcement learning algorithms (including policy gradients and actor-critic) to solve the problem of translator’s policy optimization and found that our attempts yield some promising improvements over previous approaches to reinforcement-learning based zero-shot machine translation.

Keywords: agent-based language learning, low-resource translation, natural language inference, neural machine translation, reinforcement learning

Procedia PDF Downloads 106

Authors: Majid Farsadrouh Rashti, Alireza Mohammadinejad, Amir Shafiee Kisomi

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Lead (Pb²⁺), a cation, is a prime constituent of the majority of the industrial effluents such as mining, smelting and coal combustion, Pb-based painting and Pb containing pipes in water supply systems, paper and pulp refineries, printing, paints and pigments, explosive manufacturing, storage batteries, alloy and steel industries. The maximum permissible limit of lead in the water used for drinking and domesticating purpose is 0.01 mg/L as advised by Bureau of Indian Standards, BIS. This becomes the acceptable 'safe' level of lead(II) ions in water beyond which, the water becomes unfit for human use and consumption, and is potential enough to lead health problems and epidemics leading to kidney failure, neuronal disorders, and reproductive infertility. Superabsorbent hydrogels are loosely crosslinked hydrophilic polymers that in contact with aqueous solution can easily water and swell to several times to their initial volume without dissolving in aqueous medium. Superabsorbents are kind of hydrogels capable to swell and absorb a large amount of water in their three-dimensional networks. While the shapes of hydrogels do not change extensively during swelling, because of tremendously swelling capacity of superabsorbent, their shape will broadly change.Because of their superb response to changing environmental conditions including temperature pH, and solvent composition, superabsorbents have been attracting in numerous industrial applications. For instance, water retention property and subsequently. Natural-based superabsorbent hydrogels have attracted much attention in medical pharmaceutical, baby diapers, agriculture, and horticulture because of their non-toxicity, biocompatibility, and biodegradability. Novel superabsorbent hydrogel nanocomposites were prepared by graft copolymerization of acrylamide and itaconic acid in the presence of nanoclay (laponite), using methylene bisacrylamide (MBA) and potassium persulfate, former as a crosslinking agent and the second as an initiator. The superabsorbent hydrogel nanocomposites structure was characterized by FTIR spectroscopy, SEM and TGA Spectroscopy adsorption of metal ions on poly (AAm-co-IA). The equilibrium swelling values of copolymer was determined by gravimetric method. During the adsorption of metal ions on polymer, residual metal ion concentration in the solution and the solution pH were measured. The effects of the clay content of the hydrogel on its metal ions uptake behavior were studied. The NC hydrogels may be considered as a good candidate for environmental applications to retain more water and to remove heavy metals.

Keywords: adsorption, hydrogel, nanocomposite, super adsorbent

Procedia PDF Downloads 165

Authors: Antoine Lauvray, Fabien Poulhaon, Pierre Michaud, Pierre Joyot, Emmanuel Duc

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Additive Friction Stir Manufacturing (AFSM) is a new industrial process that follows the emergence of friction-based processes. The AFSM process is a solid-state additive process using the energy produced by the friction at the interface between a rotating non-consumable tool and a substrate. Friction depends on various parameters like axial force, rotation speed or friction coefficient. The feeder material is a metallic rod that flows through a hole in the tool. Unlike in Friction Stir Welding (FSW) where abundant literature exists and addresses many aspects going from process implementation to characterization and modeling, there are still few research works focusing on AFSM. Therefore, there is still a lack of understanding of the physical phenomena taking place during the process. This research work aims at a better AFSM process understanding and implementation, thanks to numerical simulation and experimental validation performed on a prototype effector. Such an approach is considered a promising way for studying the influence of the process parameters and to finally identify a process window that seems relevant. The deposition of material through the AFSM process takes place in several phases. In chronological order these phases are the docking phase, the dwell time phase, the deposition phase, and the removal phase. The present work focuses on the dwell time phase that enables the temperature rise of the system composed of the tool, the filler material, and the substrate and due to pure friction. Analytic modeling of heat generation based on friction considers as main parameters the rotational speed and the contact pressure. Another parameter considered influential is the friction coefficient assumed to be variable due to the self-lubrication of the system with the rise in temperature or the materials in contact roughness smoothing over time. This study proposes, through numerical modeling followed by experimental validation, to question the influence of the various input parameters on the dwell time phase. Rotation speed, temperature, spindle torque, and axial force are the main monitored parameters during experimentations and serve as reference data for the calibration of the numerical model. This research shows that the geometry of the tool as well as fluctuations of the input parameters like axial force and rotational speed are very influential on the temperature reached and/or the time required to reach the targeted temperature. The main outcome is the prediction of a process window which is a key result for a more efficient process implementation.

Keywords: numerical model, additive manufacturing, friction, process

Procedia PDF Downloads 121

Authors: Tamar Grdzelishvili, Zaza Sinauridze

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Introduction: Preeclampsia is a complication of the second trimester of pregnancy, which is characterized by high morbidity and multiorgan damage. Many complex pathogenic mechanisms are now implicated to be responsible for this disease (1). Preeclampsia is one of the leading causes of maternal mortality worldwide. Statistics are enough to convince you of the seriousness of this pathology: about 100,000 women die of preeclampsia every year. It occurs in 3-14% (varies significantly depending on racial origin or ethnicity and geographical region) of pregnant women, in 75% of cases - in a mild form, and in 25% - in a severe form. During severe pre-eclampsia-eclampsia, perinatal mortality increases by 5 times and stillbirth by 9.6 times. Considering that the only way to treat the disease is to end the pregnancy, the main thing is timely diagnosis and prevention of the disease. Identification of high-risk pregnant women for PE and giving prophylaxis would reduce the incidence of preterm PE. First-trimester screening model developed by the Fetal Medicine Foundation (FMF), which uses the Bayes-theorem to combine maternal characteristics and medical history together with measurements of mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor, has been proven to be effective and have superior screening performance to that of traditional risk factor-based approach for the prediction of PE (2) Methods: Retrospective single center screening study. The study population consisted of women from the Tbilisi maternity hospital “Pineo medical ecosystem” who met the following criteria: they spoke Georgian, English, or Russian and agreed to participate in the study after discussing informed consent and answering questions. Prior to the study, the informed consent forms approved by the Institutional Review Board were obtained from the study subjects. Early assessment of preeclampsia was performed between 11-13 weeks of pregnancy. The following were evaluated: anamnesis, dopplerography of the uterine artery, mean arterial blood pressure, and biochemical parameter: Pregnancy-associated plasma protein A (PAPP-A). Individual risk assessment was performed with performed by Fast Screen 3.0 software ThermoFisher scientific. Results: A total of 513 women were recruited and through the study, 51 women were diagnosed with preeclampsia (34.5% in the pregnant women with high risk, 6.5% in the pregnant women with low risk; P<0.000 1). Conclusions: First-trimester screening combining maternal factors with uterine artery Doppler, blood pressure, and pregnancy-associated plasma protein-A is useful to predict PE in a routine care setting. More patient studies are needed for final conclusions. The research is still ongoing.

Keywords: first-trimester, preeclampsia, screening, pregnancy-associated plasma protein

Procedia PDF Downloads 51

Authors: Praskovya Britskaya, Fatima Shaizadina, Alua Omarova, Nessipkul Alysheva

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Planned preventive vaccination, which is carried out in the Republic of Kazakhstan, promoted permanent decrease in the incidence of measles and viral hepatitis B. In the structure of VHB patients prevail people of young, working age. Monitoring of infectious incidence, monitoring of coverage of immunization of the population, random serological control over the immunity enable well-timed identification of distribution of the activator, effectiveness of the taken measures and forecasting. The serological blood analysis was conducted in indicator groups of the population of Central Kazakhstan for the purpose of identification of antibody titre for vaccine preventable infections (measles, viral hepatitis B). Measles antibodies were defined by method of enzyme-linked assay (ELA) with test-systems "VektoKor" – Ig G ('Vektor-Best' JSC). Antibodies for HBs-antigen of hepatitis B virus in blood serum was identified by method of enzyme-linked assay (ELA) with VektoHBsAg test systems – antibodies ('Vektor-Best' JSC). The result of the analysis is positive, the concentration of IgG to measles virus in the studied sample is equal to 0.18 IU/ml or more. Protective level of concentration of anti-HBsAg makes 10 mIU/ml. The results of the study of postvaccinal measles immunity showed that the share of seropositive people made 87.7% of total number of surveyed. The level of postvaccinal immunity to measles in age groups differs. So, among people older than 56 the percentage of seropositive made 95.2%. Among people aged 15-25 were registered 87.0% seropositive, at the age of 36-45 – 86.6%. In age groups of 25-35 and 36-45 the share of seropositive people was approximately at the same level – 88.5% and 88.8% respectively. The share of people seronegative to a measles virus made 12.3%. The biggest share of seronegative people was found among people aged 36-45 – 13.4% and 15-25 – 13.0%. The analysis of results of the examined people for the existence of postvaccinal immunity to viral hepatitis B showed that from all surveyed only 33.5% have the protective level of concentration of anti-HBsAg of 10 mIU/ml and more. The biggest share of people protected from VHB virus is observed in the age group of 36-45 and makes 60%. In the indicator group – above 56 – seropositive people made 4.8%. The high percentage of seronegative people has been observed in all studied age groups from 40.0% to 95.2%. The group of people which is least protected from getting VHB is people above 56 (95.2%). The probability to get VHB is also high among young people aged 25-35, the percentage of seronegative people made 80%. Thus, the results of the conducted research testify to the need for carrying out serological monitoring of postvaccinal immunity for the purpose of operational assessment of the epidemiological situation, early identification of its changes and prediction of the approaching danger.

Keywords: antibodies, blood serum, immunity, immunoglobulin

Procedia PDF Downloads 228

Authors: Othman E. Othman, Amira M. Nowier, Medhat El-Denary

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Camels play an important socio-economic role within the pastoral and agricultural system in the dry and semidry zones of Asia and Africa. Camels are economically important animals in Egypt where they are dual purpose animals (meat and milk). The analysis of chemical composition of camel milk showed that the total protein contents ranged from 2.4% to 5.3% and it is divided into casein and whey proteins. The casein fraction constitutes 52% to 89% of total camel milk protein and it divided into 4 fractions namely αs1, αs2, β and κ-caseins which are encoded by four tightly genes. In spite of the important role of casein genes and the effects of their genetic polymorphisms on quantitative traits and technological properties of milk, the studies for the detection of genetic polymorphism of camel milk genes are still limited. Due to this fact, this work focused - using PCR-RFP and sequencing analysis - on the identification of genetic polymorphisms and SNPs of two casein genes in Maghrabi camel breed which is a dual purpose camel breed in Egypt. The amplified fragments at 488-bp of the camel κ-CN gene were digested with AluI endonuclease. The results showed the appearance of three different genotypes in the tested animals; CC with three digested fragments at 203-, 127- and 120-bp, TT with three digested fragments at 203-, 158- and 127-bp and CT with four digested fragments at 203-, 158-, 127- and 120-bp. The frequencies of three detected genotypes were 11.0% for CC, 48.0% for TT and 41.0% for CT genotypes. The sequencing analysis of the two different alleles declared the presence of a single nucleotide polymorphism (C→T) at position 121 in the amplified fragments which is responsible for the destruction of a restriction site (AG/CT) in allele T and resulted in the presence of two different alleles C and T in tested animals. The nucleotide sequences of κ-CN alleles C and T were submitted to GenBank with the accession numbers; KU055605 and KU055606, respectively. The primers used in this study amplified 942-bp fragments spanning from exon 4 to exon 6 of camel αS1-Casein gene. The amplified fragments were digested with two different restriction enzymes; SmlI and AluI. The results of SmlI digestion did not show any restriction site whereas the digestion with AluI endonuclease revealed the presence of two restriction sites AG^CT at positions 68^69 and 631^632 yielding the presence of three digested fragments with sizes 68-, 563- and 293-bp.The nucleotide sequences of this fragment from camel αS1-Casein gene were submitted to GenBank with the accession number KU145820. In conclusion, the genetic characterization of quantitative traits genes which are associated with the production traits like milk yield and composition is considered an important step towards the genetic improvement of livestock species through the selection of superior animals depending on the favorable alleles and genotypes; marker assisted selection (MAS).

Keywords: genetic polymorphism, SNP polymorphism, Maghrabi camels, κ-Casein gene, αS1-Casein gene

Procedia PDF Downloads 586

Authors: Heribert R. Kaijage, Samuel N. A. Codjoe, Simon H. D. Mamuya, Mangi J. Ezekiel

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There is strong evidence that climate has changed significantly affecting various sectors including public health. The recommended feasible solution is adopting development trajectories which combine both mitigation and adaptation measures for improving resilience pathways. This approach demands a consideration for complex interactions between climate and social-ecological systems. While other sectors such as agriculture and water have developed climate resilience indices, the public health sector in Tanzania is still lagging behind. The aim of this study was to find out how can we use Demographic and Health Surveys (DHS) linked with Remote Sensing (RS) technology and metrological information as tools to inform climate change resilient development and evaluation for the health sector. Methodological review was conducted whereby a number of studies were content analyzed to find appropriate indicators and indices for climate resilience household and their integration approach. These indicators were critically reviewed, listed, filtered and their sources determined. Preliminary identification and ranking of indicators were conducted using participatory approach of pairwise weighting by selected national stakeholders from meeting/conferences on human health and climate change sciences in Tanzania. DHS datasets were retrieved from Measure Evaluation project, processed and critically analyzed for possible climate change indicators. Other sources for indicators of climate change exposure were also identified. For the purpose of preliminary reporting, operationalization of selected indicators was discussed to produce methodological approach to be used in resilience comparative analysis study. It was found that household climate resilient index depends on the combination of three indices namely Household Adaptive and Mitigation Capacity (HC), Household Health Sensitivity (HHS) and Household Exposure Status (HES). It was also found that, DHS alone cannot complement resilient evaluation unless integrated with other data sources notably flooding data as a measure of vulnerability, remote sensing image of Normalized Vegetation Index (NDVI) and Metrological data (deviation from rainfall pattern). It can be concluded that if these indices retrieved from DHS data sets are computed and scientifically integrated can produce single climate resilience index and resilience maps could be generated at different spatial and time scales to enhance targeted interventions for climate resilient development and evaluations. However, further studies are need to test for the sensitivity of index in resilience comparative analysis among selected regions.

Keywords: climate change, resilience, remote sensing, demographic and health surveys

Procedia PDF Downloads 137

Authors: Neelima Rashmi Lakra

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India was among one of the highly developed economy up to 1850 due to its cottage industries. During the end of the 18th century, modern industrial enterprises began with the first cotton mill in Bombay, the jute mill near Calcutta and the coal mine in Raniganj. This was counted as the real beginning of industry in 1854 in India. Prior to this period people concentrated only to agriculture, menial service or handicraft, and the introduction of industries exposed them to the disciplines of factory which was very tedious for them. With increasing number of factories been setup adding on to mining and introduction of railway, World War Period (1914-19), Second World War Period (1939-45) and the Great Depression (1929-33) there were visible change in the nature of work for the people, which resulted in outburst of strike for various reasons in these factories. Here, with India’s independence there was emergence of public sector industries and labour legislations were introduced. Meanwhile, trade unions came to notice to the rescue of the oppressed but failed to continue till long. Soon after, with the New Economic Policy organisations came across to face challenges to perform their best, where social justice for the workmen was in question. On these backdrops, studies were found discussing the central human capabilities which could be addressed through Social Security schemes. Therefore, this study was taken up to look at the reforms and legislations mainly meant for the welfare of the labour. This paper will contribute to the large number of Indian population who are serving in public sectors in India since the introduction of industries and will complement the issue of social justice through social security measures among this huge crowd serving the nation. The objectives of the study include; to find out what labour Legislations have already been existing in India, the role of Trade Union Movement, to look at the effects of New Economic Policy on these reforms and its effects and measures taken for the workforce employed in the public sectors and finally, if these measures fulfil the social justice aspects for the larger society on whole. The methodology followed collection of data from books, journal articles, reports, company reports and manuals focusing mainly on Indian studies and the data was analysed following content analysis method. The findings showed the measures taken for Social Security, but there were also reflections of very few particular additions or amendments to these Acts and provisions with the onset of New Liberalisation Policy. Therefore, the study concluded examining the social justice aspects in the context of a developing economy and discussing the recommendations.

Keywords: public sectors, social justice, social security schemes, trade union movement

Procedia PDF Downloads 423

Authors: Redie Kidane Ghebrehawariat, Betiel Habte Hadgu, Filmon Berhane Kahsay, Rim Berhane Fisehaye, Samuel Haile Kahsay, Saron Yemane Yosief, Selemawit Mosazghi Gilazghi

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A cross-sectional study was conducted from 22 February to 9 April 2022 on small, medium, and large holder dairy farms to determine the bovine mastitis prevalence and associated risk factors in the Anseba region, Eritrea. A total of 34 dairy farms and 193 dairy cows were randomly selected. Dairy cows were physically examined for any change on the udder and milk; a California mastitis test was performed to check sub-clinical mastitis; a closed-ended semi-structured questionnaire composed of 28 variables/risk factors (21 management risk factors and 7 animal-level risk factors) was used to determine the risk factors responsible for clinical and sub-clinical mastitis in the dairy cows. The overall cow-level prevalence of mastitis was 147 (76.2%). The animal level prevalence rate of clinical and sub-clinical mastitis was found to be 22 (11.4%) and 125 (64.8%), respectively, while herd level prevalence both for clinical and subclinical mastitis was found to be 14 (41.2%) and 26 (76.5%) respectively. Based on the already set P-value, which is <0.05, a number of risk factors were found to have a significant relationship with the occurrence of clinical and sub-clinical mastitis. Generally, animal risk factors such as animal age, parity, injury on the udder or teat, and previous history of mastitis presence of injury on the udder and lactation stage were risk factors with a significant relationship with the occurrence of clinical and sub-clinical mastitis. On the other hand, management risk factors with a significant relationship to the occurrence of clinical and sub-clinical mastitis were herd size, failure to milk mastitic cow, at last, educational level, floor type, failure to use a towel, using one towel for more than one cow and failure to practice mastitis test. From a total of 772 quarters, 280 (36.3%) were found positive for sub-clinical mastitis using the California mastitis test; of these, 70 (9%) were weakly positive, 90 (11.7%) were distinct positive, and 120 (15.5%) were strongly positive. Furthermore, 13 (1.7%) quarters were blocked. Quarter level prevalence was right front 80 (41.5%), left front 64 (33.3%), right hind 69 (35.8%) and left hind 67 (34.7%). The study has shown that mastitis is a major problem for dairy farms and the findings suggested that mastitis is one of the limiting factors in increasing milk production. Subclinical mastitis was found to be a devastating problem, and it occurred in all three breeds of lactating dairy cattle. Therefore, farmers should work hard to avoid the above-mentioned risk factors to minimize the infection of their dairy cattle by mastitis and thereby increase their profit. On the other hand, the Ministry of Agriculture, through the extension unit, should work in close contact with the farmers to increase awareness of the economic importance of the disease and associated risk factors.

Keywords: mastitis, prevalence, dairy cattle, Anseba, Eritrea

Procedia PDF Downloads 99

Authors: Soad Abubakr Abdelgalil, Gaber Attia Abo-Zaid, Mohamed Mohamed Yousri Kaddah

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Background: The Environmental Protection Agency has listed eggshell waste as the 15th most significant food industry pollution hazard. The utilization of eggshell waste as a source of renewable energy has been a hot topic in recent years. Therefore, finding a sustainable solution for the recycling and valorization of eggshell waste by investigating its potential to produce acid phosphatase (ACP) and organic acids by the newly-discovered B. sonorensis was the target of the current investigation. Results: The most potent ACP-producing B. sonorensis strain ACP2 was identified as a local bacterial strain obtained from the effluent of paper and pulp industries on basis of molecular and morphological characterization. The use of consecutive statistical experimental approaches of Plackett-Burman Design (PBD), and Orthogonal Central Composite Design (OCCD), followed by pH-uncontrolled cultivation conditions in a 7 L bench-top bioreactor, revealed an innovative medium formulation that substantially improved ACP production, reaching 216 U L⁻¹ with ACP yield coefficient Yp/x of 18.2 and a specific growth rate (µ) of 0.1 h⁻¹. The metals Ag+, Sn+, and Cr+ were the most efficiently released from eggshells during the solubilization process by B. sonorensis. The uncontrolled pH culture condition is the most suited and favored setting for improving the ACP and organic acids production simultaneously. Quantitative and qualitative analyses of produced organic acids were carried out using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Lactic acid, citric acid, and hydroxybenzoic acid isomer were the most common organic acids produced throughout the cultivation process. The findings of thermogravimetric analysis (TGA), differential scan calorimeter (DSC), scanning electron microscope (SEM), energy-dispersive spectroscopy (EDS), Fourier-Transform Infrared Spectroscopy (FTIR), and X-Ray Diffraction (XRD) analysis emphasize the significant influence of organic acids and ACP activity on the solubilization of eggshells particles. Conclusions: This study emphasized robust microbial engineering approaches for the large-scale production of a newly discovered acid phosphatase accompanied by organic acids production from B. sonorensis. The biovalorization of the eggshell waste and the production of cost-effective ACP and organic acids were integrated into the current study, and this was done through the implementation of a unique and innovative medium formulation design for eggshell waste management, as well as scaling up ACP production on a bench-top scale.

Keywords: chicken eggshells waste, bioremediation, statistical experimental design, batch fermentation

Procedia PDF Downloads 344

Authors: Amit Sarkar, Jayanta K. Mahato, Tushar Bhattacharya, Amrita Kundu, P. C. Chakraborti

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With increasing the demand for safety and fuel efficiency of automobiles, automotive manufacturers are looking for light weight, high strength steel with excellent formability and corrosion resistance. Dual-phase steel is finding applications in automotive sectors, because of its high strength, good formability, and high corrosion resistance. During service automotive components suffer from environmental attack and thereby gradual degradation of the components occurs reducing the service life of the components. The objective of the present investigation is to assess the effect of deformation on corrosion behaviour of DP590 grade dual phase steel which is used in automotive industries. The material was received from TATA Steel Jamshedpur, India in the form of 1 mm thick sheet. Tensile properties of the steel at strain rate of 10-3 sec-1: 0.2 % Yield Stress is 382 MPa, Ultimate Tensile Strength is 629 MPa, Uniform Strain is 16.30% and Ductility is 29%. Rectangular strips of 100x10x1 mm were machined keeping the long axis of the strips parallel to rolling direction of the sheet. These strips were longitudinally deformed at a strain rate at 10-3 sec-1 to a different percentage of strain, e.g. 2.5, 5, 7.5,10 and 12.5%, and then slowly unloaded. Small specimens were extracted from the mid region of the unclamped portion of these deformed strips. These small specimens were metallographic polished, and corrosion behaviour has been studied by potentiodynamic polarization, electrochemical impedance spectra, and cyclic polarization and potentiostatic tests. Present results show that among three different environments, the 3.5 pct NaCl solution is most aggressive in case of DP 590 dual-phase steel. It is observed that with the increase in the amount of deformation, corrosion rate increases. With deformation, the stored energy increases and leads to enhanced corrosion rate. Cyclic polarization results revealed highly deformed specimen are more prone to pitting corrosion as compared to the condition when amount of deformation is less. It is also observed that stability of the passive layer decreases with the amount of deformation. With the increase of deformation, current density increases in a passive zone and passive zone is also decreased. From Electrochemical impedance spectroscopy study it is found that with increasing amount of deformation polarization resistance (Rp) decreases. EBSD results showed that average geometrically necessary dislocation density increases with increasing strain which in term increased galvanic corrosion as dislocation areas act as the less noble metal.

Keywords: dual phase 590 steel, prestrain, potentiodynamic polarization, cyclic polarization, electrochemical impedance spectra

Procedia PDF Downloads 406

Authors: A. M. Isakhanyan, F. N. Tkhruni, N. N. Yakimovich, Z. I. Kuvaeva, T. V. Khachatryan

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Introduction: At present, the simbiotics based on different genera and species of lactic acid bacteria (LAB) and yeasts are used. One of the basic properties of probiotics is presence of antimicrobial activity and therefore selection of LAB and yeast strains for their co-cultivation with the aim of increasing of the activity is topical. Since probiotic yeast and bacteria have different mechanisms of action, natural synergies between species, higher viability and increasing of antimicrobial activity might be expected from mixing both types of probiotics. Endemic strains of LAB Enterococcus faecium БТK-64, Lactobaccilus plantarum БТK-66, Pediococcus pentosus БТK-28, Lactobacillus rhamnosus БТK-109 and Kluyveromyces lactis БТX-412, Saccharomycopsis sp. БТX- 151 strains of yeast, with probiotic properties and hight antimicrobial activity, were selected. Strains are deposited in "Microbial Depository Center" (MDC) SPC "Armbiotechnology". Methods: LAB and yeast strains were isolated from different dairy products from rural households of Armenia. The genotyping by 16S rRNA sequencing for LAB and 26S RNA sequencing for yeast were used. Combined cultivation of LAB and yeast strains was carried out in the nutrient media on the basis of milk whey, in anaerobic conditions (without shaker, in a thermostat at 37oC, 48 hours). The complex preparations were obtained by purification of cell free culture broth (CFC) broth by the combination of ion-exchange chromatography and gel filtration methods. The spot-on-lawn method was applied for determination of antimicrobial activity and expressed in arbitrary units (AU/ml). Results. The obtained data showed that at the combined growth of bacteria and yeasts, the cultivation conditions (medium composition, time of growth, genera of LAB and yeasts) affected the display of antimicrobial activity. Purification of CFC broth allowed obtaining partially purified antimicrobial complex preparation which contains metabiotics from both bacteria and yeast. The complex preparation inhibited the growth of pathogenic and conditionally pathogenic bacteria, isolated from various internal organs from diseased animals and poultry with greater efficiency than the preparations derived individually alone from yeast and LAB strains. Discussion. Thus, our data shown perspectives of creation of a new class of antimicrobial preparations on the basis of combined cultivation of endemic strains of LAB and yeast. Obtained results suggest the prospect of use of the partially purified complex preparations instead antibiotics in the agriculture and for food safety. Acknowledgments: This work was supported by the RA MES State Committee of Science and Belarus National Foundation for Basic Research in the frames of the joint Armenian - Belarusian joint research project 13РБ-064.

Keywords: co-cultivation, antimicrobial activity, biosafety, metabiotics, lactic acid bacteria, yeast

Procedia PDF Downloads 313

Authors: M. Bahari Mehrabani, Hua-Peng Chen

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Management and maintenance of coastal defence structures during the expected life cycle have become a real challenge for decision makers and engineers. Accurate evaluation of the current condition and future performance of flood defence structures is essential for effective practical maintenance strategies on the basis of available field inspection data. Moreover, as coastal defence structures age, it becomes more challenging to implement maintenance and management plans to avoid structural failure. Therefore, condition inspection data are essential for assessing damage and forecasting deterioration of ageing flood defence structures in order to keep the structures in an acceptable condition. The inspection data for flood defence structures are often collected using discrete visual condition rating schemes. In order to evaluate future condition of the structure, a probabilistic deterioration model needs to be utilised. However, existing deterioration models may not provide a reliable prediction of performance deterioration for a long period due to uncertainties. To tackle the limitation, a time-dependent condition-based model associated with a transition probability needs to be developed on the basis of condition grade scheme for flood defences. This paper presents a probabilistic method for predicting future performance deterioration of coastal flood defence structures based on condition grading inspection data and deterioration curves estimated by expert judgement. In condition-based deterioration modelling, the main task is to estimate transition probability matrices. The deterioration process of the structure related to the transition states is modelled according to Markov chain process, and a reliability-based approach is used to estimate the probability of structural failure. Visual inspection data according to the United Kingdom Condition Assessment Manual are used to obtain the initial condition grade curve of the coastal flood defences. The initial curves then modified in order to develop transition probabilities through non-linear regression based optimisation algorithms. The Monte Carlo simulations are then used to evaluate the future performance of the structure on the basis of the estimated transition probabilities. Finally, a case study is given to demonstrate the applicability of the proposed method under no-maintenance and medium-maintenance scenarios. Results show that the proposed method can provide an effective predictive model for various situations in terms of available condition grading data. The proposed model also provides useful information on time-dependent probability of failure in coastal flood defences.

Keywords: condition grading, flood defense, performance assessment, stochastic deterioration modelling

Procedia PDF Downloads 211

Authors: Weikang Gong, Chunhua Li

Abstract:

Dynamics plays an essential role in function exertion of proteins. Elastic network model (ENM), a harmonic potential-based and cost-effective computational method, is a valuable and efficient tool for characterizing the intrinsic dynamical properties encoded in biomacromolecule structures and has been widely used to detect the large-amplitude collective motions of proteins. Gaussian network model (GNM) and anisotropic network model (ANM) are the two often-used ENM models. In recent years, many ENM variants have been proposed. Here, we propose a small but effective modification (denoted as modified mENM) to the multiscale ENM (mENM) where fitting weights of Kirchhoff/Hessian matrixes with the least square method (LSM) is modified since it neglects the details of pairwise interactions. Then we perform its comparisons with the original mENM, traditional ENM, and parameter-free ENM (pfENM) on reproducing dynamical properties for the six representative proteins whose molecular dynamics (MD) trajectories are available in http://mmb.pcb.ub.es/MoDEL/. In the results, for B-factor prediction, mENM achieves the best performance among the four ENM models. Additionally, it is noted that with the weights of the multiscale Kirchhoff/Hessian matrixes modified, interestingly, the modified mGNM/mANM still has a much better performance than the corresponding traditional ENM and pfENM models. As to dynamical cross-correlation map (DCCM) calculation, taking the data obtained from MD trajectories as the standard, mENM performs the worst while the results produced by the modified mENM and pfENM models are close to those from MD trajectories with the latter a little better than the former. Generally, ANMs perform better than the corresponding GNMs except for the mENM. Thus, pfANM and the modified mANM, especially the former, have an excellent performance in dynamical cross-correlation calculation. Compared with GNMs (except for mGNM), the corresponding ANMs can capture quite a number of positive correlations for the residue pairs nearly largest distances apart, which is maybe due to the anisotropy consideration in ANMs. Furtherly, encouragingly the modified mANM displays the best performance in capturing the functional motional modes, followed by pfANM and traditional ANM models, while mANM fails in all the cases. This suggests that the consideration of long-range interactions is critical for ANM models to produce protein functional motions. Based on the analyses, the modified mENM is a promising method in capturing multiple dynamical characteristics encoded in protein structures. This work is helpful for strengthening the understanding of the elastic network model and provides a valuable guide for researchers to utilize the model to explore protein dynamics.

Keywords: elastic network model, ENM, multiscale ENM, molecular dynamics, parameter-free ENM, protein structure

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Authors: Zhihua Cao, Hongfei Zhao, Zhongneng Wu

Abstract:

The development of polar-based agroforestry was necessary due to the influence of the timber market environment in China, which can promote the coordinated development of forestry and agriculture, and gain remarkable ecological, economic and social benefits. The main agroforestry models of the main poplar planting area in Huaibei plain and along the Yangtze River plain were carried out. 11 typical management models of poplar were selected to sum up: pure poplar forest, poplar-rape-soybean, poplar-wheat-soybean, poplar-rape-cotton, poplar-wheat, poplar-chicken, poplar-duck, poplar-sheep, poplar-Agaricus blazei, poplar-oil peony, poplar-fish, represented by M0-M10, respectively. 12 indexes related with economic, ecological and social benefits (annual average cost, net income, ratio of output to investment, payback period of investment, land utilization ratio, utilization ratio of light energy, improvement and system stability of ecological and production environment, product richness, labor capacity, cultural quality of labor force, sustainability) were screened out to carry on the comprehensive evaluation and analysis to 11 kinds of typical agroforestry models based on analytic hierarchy process (AHP). The results showed that the economic benefit of each agroforestry model was in the order of: M8 > M6 > M9 > M7 > M5 > M10 > M4 > M1 > M2 > M3 > M0. The economic benefit of poplar-A. blazei model was the highest (332, 800 RMB / hm²), followed by poplar-duck and poplar-oil peony model (109, 820RMB /hm², 5, 7226 RMB /hm²). The order of comprehensive benefit was: M8 > M4 > M9 > M6 > M1 > M2 > M3 > M7 > M5 > M10 > M0. The economic benefit and comprehensive benefit of each agroforestry model were higher than that of pure poplar forest. The comprehensive benefit of poplar-A. blazei model was the highest, and that of poplar-wheat model ranked second, while its economic benefit was not high. Next were poplar-oil peony and poplar-duck models. It was suggested that the model of poplar-wheat should be adopted in the plain along the Yangtze River, and the whole cycle mode of poplar-grain, popalr-A. blazei, or poplar-oil peony should be adopted in Huaibei plain, northern Anhui. Furthermore, wheat, rape, and soybean are the main crops before the stand was closed; the agroforestry model of edible fungus or Chinese herbal medicine can be carried out when the stand was closed in order to maximize the comprehensive benefit. The purpose of this paper is to provide a reference for forest farmers in the selection of poplar agroforestry model in the future and to provide the basic data for the sustainable and efficient study of poplar agroforestry in Anhui province, eastern China.

Keywords: agroforestry, analytic hierarchy process (AHP), comprehensive benefit, model, poplar

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Authors: Benjamin Castillo, Luis Pastenes, Fernando Cerdova

Abstract:

The contamination of food by microbial agents is a common problem in the industry, especially regarding the elaboration of animal source products. Incorrect manipulation of the machinery or on the raw materials can cause a decrease in production or an epidemiological outbreak due to intoxication. In order to improve food product quality, different methods have been used to reduce or, at least, to slow down the growth of the pathogens, especially deteriorated, infectious or toxigenic bacteria. These methods are usually carried out under low temperatures and short processing time (abiotic agents), along with the application of antibacterial substances, such as bacteriocins (biotic agents). This, in a controlled and efficient way that fulfills the purpose of bacterial control without damaging the final product. Therefore, the objective of the present study is to design a secondary mathematical model that allows the prediction of both the biotic and abiotic factor impact associated with animal source food processing. In order to accomplish this objective, the authors propose a three-dimensional differential equation model, whose components are: bacterial growth, release, production and artificial incorporation of bacteriocins and changes in pH levels of the medium. These three dimensions are constantly being influenced by the temperature of the medium. Secondly, this model adapts to an idealized situation of cross-contamination animal source food processing, with the study agents being both the animal product and the contact surface. Thirdly, the stochastic simulations and the parametric sensibility analysis are compared with referential data. The main results obtained from the analysis and simulations of the mathematical model were to discover that, although bacterial growth can be stopped in lower temperatures, even lower ones are needed to eradicate it. However, this can be not only expensive, but counterproductive as well in terms of the quality of the raw materials and, on the other hand, higher temperatures accelerate bacterial growth. In other aspects, the use and efficiency of bacteriocins are an effective alternative in the short and medium terms. Moreover, an indicator of bacterial growth is a low-level pH, since lots of deteriorating bacteria are lactic acids. Lastly, the processing times are a secondary agent of concern when the rest of the aforementioned agents are under control. Our main conclusion is that when acclimating a mathematical model within the context of the industrial process, it can generate new tools that predict bacterial contamination, the impact of bacterial inhibition, and processing method times. In addition, the mathematical modeling proposed logistic input of broad application, which can be replicated on non-meat food products, other pathogens or even on contamination by crossed contact of allergen foods.

Keywords: bacteriocins, cross-contamination, mathematical model, temperature

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Authors: Linlong Mu, Maosong Huang

Abstract:

Considering excavations in urban areas, the soil deformation induced by the excavations usually causes damage to the surrounding structures. Displacement control becomes a critical indicator of foundation design in order to protect the surrounding structures. Evaluation, the damage potential of the surrounding structures induced by the excavations, usually depends on the finite element method (FEM) because of the complexity of the excavation and the variety of the surrounding structures. Besides, evaluation the influence of the excavation on surrounding structures is a three-dimensional problem. And it is now well recognized that small strain behaviour of the soil influences the responses of the excavation significantly. Three-dimensional FEM considering small strain behaviour of the soil is a very complex method, which is hard for engineers to use. Thus, it is important to obtain a simplified method for engineers to predict the influence of the excavations on the surrounding structures. Based on large-scale finite element calculation with small-strain based soil model coupling with inverse analysis, an empirical method is proposed to calculate the three-dimensional soil movement induced by braced excavation. The empirical method is able to capture the small-strain behaviour of the soil. And it is suitable to be used in layered soil. Then the free-field soil movement is applied to the pile to calculate the responses of the pile in both vertical and horizontal directions. The asymmetric solutions for problems in layered elastic half-space are employed to solve the interactions between soil points. Both vertical and horizontal pile responses are solved through finite difference method based on elastic theory. Interactions among the nodes along a single pile, pile-pile interactions, pile-soil-pile interaction action and soil-soil interactions are counted to improve the calculation accuracy of the method. For passive piles, the shadow effects are also calculated in the method. Finally, the restrictions of the raft on the piles and the soils are summarized as: (1) the summations of the internal forces between the elements of the raft and the elements of the foundation, including piles and soil surface elements, is equal to 0; (2) the deformations of pile heads or of the soil surface elements are the same as the deformations of the corresponding elements of the raft. Validations are carried out by comparing the results from the proposed method with the results from the model tests, FEM and other existing literatures. From the comparisons, it can be seen that the results from the proposed method fit with the results from other methods very well. The method proposed herein is suitable to predict the responses of the pile-raft foundation induced by braced excavation in layered soil in both vertical and horizontal directions when the deformation is small. However, more data is needed to verify the method before it can be used in practice.

Keywords: excavation, pile-raft foundation, passive piles, deformation control, soil movement

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