Search results for: tree species selection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5936

Search results for: tree species selection

866 Assessment of Attractency of Bactrocera Zonata and Bactrocera dorsalis (Diptera:Tephritidae) to Different Biolure Phagostimulant-Mixtures

Authors: Muhammad Dildar Gogi, Muhammad Jalal Arif, Muhammad Junaid Nisar, Mubashir Iqbal, Waleed Afzal Naveed, Muhammad Ahsan Khan, Ahmad Nawaz, Muhammad Sufian, Muhammad Arshad, Amna Jalal

Abstract:

Fruit flies of Bactrocera genus cause heavy losses in fruits and vegetables globally and insecticide-application for their control creates issues of ecological backlash, environmental pollution, and food safety. There is need to explore alternatives and food-baits application is considered safe for the environment and effective for fruit fly management. Present experiment was carried out to assess the attractancy of five phagostimulant-Mixtures (PHS-Mix) prepared by mixing banana-squash, mulberry, protein-hydrolysate and molasses with some phagostimulant-lure sources including beef extract, fish extract, yeast, starch, rose oil, casein and cedar oil in five different ratios i.e., PHS-Mix-1 (1 part of all ingredients), PHS-Mix-2 (1 part of banana with 0.75 parts of all other ingredients), PHS-Mix-3 (1 part of banana with 0.5 parts of all other ingredients), PHS-Mix-4 (1 part of banana with 0.25 parts of all other ingredients) and PHS-Mix-5 (1 part of banana with 0.125 parts of all other ingredients). These were evaluated in comparison with a standard (GF-120). PHS-Mix-4 demonstrated 40.5±1.3-46.2±1.6% AI for satiated flies (class-II i.e., moderately attractive) and 59.5±2.0-68.6±3.0% AI for starved flies (class-III i.e., highly attractive) for both B. dorsalis and B. zonata in olfactometric study while the same exhibited 51.2±0.53% AI (class-III i.e., highly attractive) for B. zonata and 45.4±0.89% AI (class-II i.e., moderately attractive) for B. dorsalis in field study. PHS-Mix-1 proved non-attractive (class-I) and moderately attractive (class-II) phagostimulant in olfactometer and field studies, respectively. PHS-Mix-2 exhibited moderate attractiveness for starved lots in olfactometer and field-lot in field studies. PHS-Mix-5 proved non-attractive to starved and satiated lots of B. zonata and B. dorsalis females in olfactometer and field studies. Overall PHS-Mix-4 proved better phagostimulant-mixture followed by PHS-Mix-3 which was categorized as class-II (moderately attractive) phagostimulant for starved and satiated lots of female flies of both species in olfactometer and field studies; hence these can be exploited for fruit fly management.

Keywords: attractive index, field conditions, olfactometer, Tephritid flies

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865 A Descriptive Study of the Mineral Content of Conserved Forage Fed to Horses in the United Kingdom, Ireland, and France

Authors: Louise Jones, Rafael De Andrade Moral, John C. Stephens

Abstract:

Background: Minerals are an essential component of correct nutrition. Conserved hay/haylage is an important component of many horse's diets. Variations in the mineral content of conserved forage should be considered when assessing dietary intake. Objectives: This study describes the levels and differences in 15 commonly analysed minerals in conserved forage fed to horses in the United Kingdom (UK), Ireland (IRL), and France (FRA). Methods: Hay (FRA n=92, IRL n=168, UK n=152) and haylage samples (UK n=287, IRL n=49) were collected during 2017-2020. Mineral analysis was undertaken using inductively coupled plasma-mass spectrometry (ICP-MS). Statistical analysis was performed using beta regression, Gaussian, or gamma models, depending on the nature of the response variable. Results: There are significant differences in the mineral content of the UK, IRL, and FRA conserved forage samples. FRA hay samples had a significantly higher (p < 0.05) levels of Sulphur (0.16 ± 0.0051 %), Calcium (0.56 ± 0.0342%), Magnesium (0.16 ± 0.0069 mg/ kg DM), Iron (194 ± 23.0 mg/kg DM), Cobalt (0.21 ± 0.0244 mg/kg DM) and Copper (4.94 ± 0.196 mg/kg DM) content compared to hay from the other two countries. UK hay samples had significantly less (p < 0.05) Selenium (0.07 ± 0.0084 mg/kg DM), whilst IRL hay samples were significantly (p < 0.05) higher in Chloride (0.9 ± 0.026mg/kg DM) compared to hay from the other two countries. IRL haylage samples were significantly (p < 0.05) higher in Phosphorus (0.26 ± 0.0102 %), Sulphur (0.17 ± 0.0052 %), Chloride (1.01 ± 0.0519 %), Calcium (0.54 ± 0.0257 %), Selenium (0.17 ± 0.0322 mg/kg DM) and Molybdenum (1.47 ± 0.137 mg/kg DM) compared to haylage from the UK. Main Limitations: Forage samples were obtained from professional yards and may not be reflective of forages fed by most horse owners. Information regarding soil type, species of grass, fertiliser treatment, harvest, or storage conditions were not included in this study. Conclusions: At a DM intake of 2% body weight, conserved forage as sampled in this study will be insufficient to meet Zinc, Iodine, and Copper NRC maintenance requirements, and Se intake will also be insufficient for horses fed the UK conserved forage. Many horses receive hay/haylage as the main component of their diet; this study highlights the need to consider forage analysis when making dietary recommendations.

Keywords: conserved forage, hay, haylage, minerals

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864 Experimental Investigation of the Impact of Biosurfactants on Residual-Oil Recovery

Authors: S. V. Ukwungwu, A. J. Abbas, G. G. Nasr

Abstract:

The increasing high price of natural gas and oil with attendant increase in energy demand on world markets in recent years has stimulated interest in recovering residual oil saturation across the globe. In order to meet the energy security, efforts have been made in developing new technologies of enhancing the recovery of oil and gas, utilizing techniques like CO2 flooding, water injection, hydraulic fracturing, surfactant flooding etc. Surfactant flooding however optimizes production but poses risk to the environment due to their toxic nature. Amongst proven records that have utilized other type of bacterial in producing biosurfactants for enhancing oil recovery, this research uses a technique to combine biosurfactants that will achieve a scale of EOR through lowering interfacial tension/contact angle. In this study, three biosurfactants were produced from three Bacillus species from freeze dried cultures using sucrose 3 % (w/v) as their carbon source. Two of these produced biosurfactants were screened with the TEMCO Pendant Drop Image Analysis for reduction in IFT and contact angle. Interfacial tension was greatly reduced from 56.95 mN.m-1 to 1.41 mN.m-1 when biosurfactants in cell-free culture (Bacillus licheniformis) were used compared to 4. 83mN.m-1 cell-free culture of Bacillus subtilis. As a result, cell-free culture of (Bacillus licheniformis) changes the wettability of the biosurfactant treatment for contact angle measurement to more water-wet as the angle decreased from 130.75o to 65.17o. The influence of microbial treatment on crushed rock samples was also observed by qualitative wettability experiments. Treated samples with biosurfactants remained in the aqueous phase, indicating a water-wet system. These results could prove that biosurfactants can effectively change the chemistry of the wetting conditions against diverse surfaces, providing a desirable condition for efficient oil transport in this way serving as a mechanism for EOR. The environmental friendly effect of biosurfactants applications for industrial purposes play important advantages over chemically synthesized surfactants, with various possible structures, low toxicity, eco-friendly and biodegradability.

Keywords: bacillus, biosurfactant, enhanced oil recovery, residual oil, wettability

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863 Modeling Biomass and Biodiversity across Environmental and Management Gradients in Temperate Grasslands with Deep Learning and Sentinel-1 and -2

Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

Abstract:

Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

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862 Predicting Success and Failure in Drug Development Using Text Analysis

Authors: Zhi Hao Chow, Cian Mulligan, Jack Walsh, Antonio Garzon Vico, Dimitar Krastev

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Drug development is resource-intensive, time-consuming, and increasingly expensive with each developmental stage. The success rates of drug development are also relatively low, and the resources committed are wasted with each failed candidate. As such, a reliable method of predicting the success of drug development is in demand. The hypothesis was that some examples of failed drug candidates are pushed through developmental pipelines based on false confidence and may possess common linguistic features identifiable through sentiment analysis. Here, the concept of using text analysis to discover such features in research publications and investor reports as predictors of success was explored. R studios were used to perform text mining and lexicon-based sentiment analysis to identify affective phrases and determine their frequency in each document, then using SPSS to determine the relationship between our defined variables and the accuracy of predicting outcomes. A total of 161 publications were collected and categorised into 4 groups: (i) Cancer treatment, (ii) Neurodegenerative disease treatment, (iii) Vaccines, and (iv) Others (containing all other drugs that do not fit into the 3 categories). Text analysis was then performed on each document using 2 separate datasets (BING and AFINN) in R within the category of drugs to determine the frequency of positive or negative phrases in each document. A relative positivity and negativity value were then calculated by dividing the frequency of phrases with the word count of each document. Regression analysis was then performed with SPSS statistical software on each dataset (values from using BING or AFINN dataset during text analysis) using a random selection of 61 documents to construct a model. The remaining documents were then used to determine the predictive power of the models. Model constructed from BING predicts the outcome of drug performance in clinical trials with an overall percentage of 65.3%. AFINN model had a lower accuracy at predicting outcomes compared to the BING model at 62.5% but was not effective at predicting the failure of drugs in clinical trials. Overall, the study did not show significant efficacy of the model at predicting outcomes of drugs in development. Many improvements may need to be made to later iterations of the model to sufficiently increase the accuracy.

Keywords: data analysis, drug development, sentiment analysis, text-mining

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861 The Effect of Acute Toxicity and Thyroid Hormone Treatments on Hormonal Changes during Embryogenesis of Acipenser persicus

Authors: Samaneh Nazeri, Bagher Mojazi Amiri, Hamid Farahmand

Abstract:

Production of high quality fish eggs with reasonable hatching rate makes a success in aquaculture industries. It is influenced by the environmental stimulators and inhibitors. Diazinon is a widely-used pesticide in Golestan province (Southern Caspian Sea, North of Iran) which is washed to the aquatic environment (3 mg/L in the river). It is little known about the effect of this pesticide on the embryogenesis of sturgeon fish, the valuable species of the Caspian Sea. Hormonal content of the egg is an important factor to guaranty the successful passes of embryonic stages. In this study, the fate of Persian sturgeon embryo to 24, 48, 72, and 96-hours exposure of diazinon (LC50 dose) was tested. Also, the effect of thyroid hormones (T3 and T4) on these embryos was tested concurrently or separately with diazinon LC 50 dose. Fertilized eggs are exposed to T3 (low dose: 1 ng/ml, high dose: 10 ng/ml), T4 (low dose: 1 ng/ml, high dose: 10 ng/ml). Six eggs were randomly selected from each treatment (with three replicates) in five developmental stages (two cell- division, neural, heart present, heart beaten, and hatched larvae). The possibility of changing T3, T4, and cortisol contents of the embryos were determined in all treated groups and in every mentioned embryonic stage. The hatching rate in treated groups was assayed at the end of the embryogenesis to clarify the effect of thyroid hormones and diazinon. The results indicated significant differences in thyroid hormone contents, but no significant differences were recognized in cortisol levels at various early life stages of embryos. There was also significant difference in thyroid hormones in (T3, T4) + diazinon treated embryos (P˂0.05), while no significant difference between control and treatments in cortisol levels was observed. The highest hatching rate was recorded in HT3 treatment, while the lowest hatching rate was recorded for diazinon LC50 treatment. The result confirmed that Persian sturgeon embryo is less sensitive to diazinon compared to teleost embryos, and thyroid hormones may increase hatching rate even in the presence of diazinon.

Keywords: Persian sturgeon, diazinon, thyroid hormones, cortisol, embryo

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860 A Study on the Measurement of Spatial Mismatch and the Influencing Factors of “Job-Housing” in Affordable Housing from the Perspective of Commuting

Authors: Daijun Chen

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Affordable housing is subsidized by the government to meet the housing demand of low and middle-income urban residents in the process of urbanization and to alleviate the housing inequality caused by market-based housing reforms. It is a recognized fact that the living conditions of the insured have been improved while constructing the subsidized housing. However, the choice of affordable housing is mostly in the suburbs, where the surrounding urban functions and infrastructure are incomplete, resulting in the spatial mismatch of "jobs-housing" in affordable housing. The main reason for this problem is that the residents of affordable housing are more sensitive to the spatial location of their residence, but their selectivity and controllability to the housing location are relatively weak, which leads to higher commuting costs. Their real cost of living has not been effectively reduced. In this regard, 92 subsidized housing communities in Nanjing, China, are selected as the research sample in this paper. The residents of the affordable housing and their commuting Spatio-temporal behavior characteristics are identified based on the LBS (location-based service) data. Based on the spatial mismatch theory, spatial mismatch indicators such as commuting distance and commuting time are established to measure the spatial mismatch degree of subsidized housing in different districts of Nanjing. Furthermore, the geographically weighted regression model is used to analyze the influencing factors of the spatial mismatch of affordable housing in terms of the provision of employment opportunities, traffic accessibility and supporting service facilities by using spatial, functional and other multi-source Spatio-temporal big data. The results show that the spatial mismatch of affordable housing in Nanjing generally presents a "concentric circle" pattern of decreasing from the central urban area to the periphery. The factors affecting the spatial mismatch of affordable housing in different spatial zones are different. The main reasons are the number of enterprises within 1 km of the affordable housing district and the shortest distance to the subway station. And the low spatial mismatch is due to the diversity of services and facilities. Based on this, a spatial optimization strategy for different levels of spatial mismatch in subsidized housing is proposed. And feasible suggestions for the later site selection of subsidized housing are also provided. It hopes to avoid or mitigate the impact of "spatial mismatch," promote the "spatial adaptation" of "jobs-housing," and truly improve the overall welfare level of affordable housing residents.

Keywords: affordable housing, spatial mismatch, commuting characteristics, spatial adaptation, welfare benefits

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859 Development of a Turbulent Boundary Layer Wall-pressure Fluctuations Power Spectrum Model Using a Stepwise Regression Algorithm

Authors: Zachary Huffman, Joana Rocha

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Wall-pressure fluctuations induced by the turbulent boundary layer (TBL) developed over aircraft are a significant source of aircraft cabin noise. Since the power spectral density (PSD) of these pressure fluctuations is directly correlated with the amount of sound radiated into the cabin, the development of accurate empirical models that predict the PSD has been an important ongoing research topic. The sound emitted can be represented from the pressure fluctuations term in the Reynoldsaveraged Navier-Stokes equations (RANS). Therefore, early TBL empirical models (including those from Lowson, Robertson, Chase, and Howe) were primarily derived by simplifying and solving the RANS for pressure fluctuation and adding appropriate scales. Most subsequent models (including Goody, Efimtsov, Laganelli, Smol’yakov, and Rackl and Weston models) were derived by making modifications to these early models or by physical principles. Overall, these models have had varying levels of accuracy, but, in general, they are most accurate under the specific Reynolds and Mach numbers they were developed for, while being less accurate under other flow conditions. Despite this, recent research into the possibility of using alternative methods for deriving the models has been rather limited. More recent studies have demonstrated that an artificial neural network model was more accurate than traditional models and could be applied more generally, but the accuracy of other machine learning techniques has not been explored. In the current study, an original model is derived using a stepwise regression algorithm in the statistical programming language R, and TBL wall-pressure fluctuations PSD data gathered at the Carleton University wind tunnel. The theoretical advantage of a stepwise regression approach is that it will automatically filter out redundant or uncorrelated input variables (through the process of feature selection), and it is computationally faster than machine learning. The main disadvantage is the potential risk of overfitting. The accuracy of the developed model is assessed by comparing it to independently sourced datasets.

Keywords: aircraft noise, machine learning, power spectral density models, regression models, turbulent boundary layer wall-pressure fluctuations

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858 Time and Energy Saving Kitchen Layout

Authors: Poonam Magu, Kumud Khanna, Premavathy Seetharaman

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The two important resources of any worker performing any type of work at any workplace are time and energy. These are important inputs of the worker and need to be utilised in the best possible manner. The kitchen is an important workplace where the homemaker performs many essential activities. Its layout should be so designed that optimum use of her resources can be achieved.Ideally, the shape of the kitchen, as determined by the physical space enclosed by the four walls, can be square, rectangular or irregular. But it is the shape of the arrangement of counter that one normally refers to while talking of the layout of the kitchen. The arrangement can be along a single wall, along two opposite walls, L shape, U shape or even island. A study was conducted in 50 kitchens belonging to middle income group families. These were DDA built kitchens located in North, South, East and West Delhi.The study was conducted in three phases. In the first phase, 510 non working homemakers were interviewed. The data related to personal characteristics of the homemakers was collected. Additional information was also collected regarding the kitchens-the size, shape , etc. The homemakers were also questioned about various aspects related to meal preparation-people performing the task, number of items cooked, areas used for meal preparation , etc. In the second phase, a suitable technique was designed for conducting time and motion study in the kitchen while the meal was being prepared. This technique was called Path Process Chart. The final phase was carried out in 50 kitchens. The criterion for selection was that all items for a meal should be cooked at the same time. All the meals were cooked by the homemakers in their own kitchens. The meal preparation was studied using the Path Process Chart technique. The data collected was analysed and conclusions drawn. It was found that of all the shapes, it was the kitchen with L shape arrangement in which, on an average a homemaker spent minimum time on meal preparation and also travelled the minimum distance. Thus, the average distance travelled in a L shaped layout was 131.1 mts as compared to 181.2 mts in an U shaped layout. Similarly, 48 minutes was the average time spent on meal preparation in L shaped layout as compared to 53 minutes in U shaped layout. Thus, the L shaped layout was more time and energy saving layout as compared to U shaped.

Keywords: kitchen layout, meal preparation, path process chart technique, workplace

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857 Prevalence of Seropositivity for Cytomegalovirus in Patients with Hereditary Bleeding Diseases in West Azerbaijan of Iran

Authors: Zakieh Rostamzadeh, Zahra Shirmohammadi

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Human cytomegalovirus is a species of the cytomegalovirus family of viruses, which in turn is a member of the viral family known as herpesviridae or herpesviruses. Although they may be found throughout the body, HCMV infections are frequently associated with the salivary glands. HCMV infection is typically unnoticed in healthy people, but can be life-threatening for the immunocompromised such as HIV-infected persons, organ transplant recipients, or newborn infants. After infection, HCMV has an ability to remain latent within the body over long periods. Cytomegalovirus (CMV) causes infection in immunocompromised, hemophilia patients and those who received blood transfusion frequently. This study aimed at determining the prevalence of cytomegalovirus (CMV) antibodies in hemophilia patients. Materials and Methods: A retrospective observational study was carried out in Urmia, North West of Iran. The study population comprised a sample of 50 hemophilic patients born after 1985 and have received blood factors in West Azerbaijan. The exclusion criteria include: drug abusing, high risk sexual contacts, vertical transmission of mother to fetus and suspicious needling. All samples were evaluated with the method of ELISA, with a certain kind of kit and by a certain laboratory. Results: Fifty hemophiliacs from 250 patients registered with Urmia Hemophilia Society were enrolled in the study including 43 (86%) male, and 7 (14%) female. The mean age of patients was 10.3 years, range 3 to 25 years. None of patients had risk factors mentioned above. Among our studied population, 34(68%) had hemophilia A, 1 (2%) hemophilia B, 8 (16%) VWF, 3(6%) factor VII deficiency, 1 (2%) factor V deficiency, 1 (2%) factor X deficiency, 1 (2%). Sera of 50 Hemodialysis patients were investigated for CMV-specific immunoglobulin G (IgG) and IgM. % 91.89 patients were anti-CMV IgG positive and %40.54 was seropositive for anti-CMV IgM. 37.8% patient had serological evidence of reactivation and 2.7% of patients had the primary infection. Discussion: There was no relationship between the antibody titer and: drug abusing, high risk sexual contacts, vertical transmission of mother to fetus and suspicious needling.

Keywords: bioinformatics, biomedicine, cytomegalovirus, immunocompromise

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856 Using Two-Mode Network to Access the Connections of Film Festivals

Authors: Qiankun Zhong

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In a global cultural context, film festival awards become authorities to define the aesthetic value of films. To study which genres and producing countries are valued by different film festivals and how those evaluations interact with each other, this research explored the interactions between the film festivals through their selection of movies and the factors that lead to the tendency of film festivals to nominate the same movies. To do this, the author employed a two-mode network on the movies that won the highest awards at five international film festivals with the highest attendance in the past ten years (the Venice Film Festival, the Cannes Film Festival, the Toronto International Film Festival, Sundance Film Festival, and the Berlin International Film Festival) and the film festivals that nominated those movies. The title, genre, producing country and language of 50 movies, and the range (regional, national or international) and organizing country or area of 129 film festivals were collected. These created networks connected by nominating the same films and awarding the same movies. The author then assessed the density and centrality of these networks to answer the question: What are the film festivals that tend to have more shared values with other festivals? Based on the Eigenvector centrality of the two-mode network, Palm Springs, Robert Festival, Toronto, Chicago, and San Sebastian are the festivals that tend to nominate commonly appreciated movies. In contrast, Black Movie Film Festival has the unique value of generally not sharing nominations with other film festivals. A homophily test was applied to access the clustering effects of film and film festivals. The result showed that movie genres (E-I index=0.55) and geographic location (E-I index=0.35) are possible indicators of film festival clustering. A blockmodel was also created to examine the structural roles of the film festivals and their meaning in real-world context. By analyzing the same blocks with film festival attributes, it was identified that film festivals either organized in the same area, with the same history, or with the same attitude on independent films would occupy the same structural roles in the network. Through the interpretation of the blocks, language was identified as an indicator that contributes to the role position of a film festival. Comparing the result of blockmodeling in the different periods, it is seen that international film festivals contrast with the Hollywood industry’s dominant value. The structural role dynamics provide evidence for a multi-value film festival network.

Keywords: film festivals, film studies, media industry studies, network analysis

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855 The Impact of Artificial Intelligence on Digital Factory

Authors: Mona Awad Wanis Gad

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The method of factory making plans has changed loads, in particular, whilst it's miles approximately making plans the factory building itself. Factory making plans have the venture of designing merchandise, plants, tactics, organization, regions, and the construction of a factory. Ordinary restructuring is turning into greater essential for you to preserve the competitiveness of a manufacturing unit. Regulations in new regions, shorter lifestyle cycles of product and manufacturing era, in addition to a VUCA global (Volatility, Uncertainty, Complexity and Ambiguity) cause extra common restructuring measures inside a factory. A digital factory model is the planning foundation for rebuilding measures and turns into a critical device. Furthermore, digital building fashions are increasingly being utilized in factories to help facility management and manufacturing processes. First, exclusive styles of digital manufacturing unit fashions are investigated, and their residences and usabilities to be used instances are analyzed. Within the scope of research are point cloud fashions, building statistics fashions, photogrammetry fashions, and those enriched with sensor information are tested. It investigated which digital fashions permit a simple integration of sensor facts and in which the variations are. In the end, viable application areas of virtual manufacturing unit models are determined by a survey, and the respective digital manufacturing facility fashions are assigned to the application areas. Ultimately, an application case from upkeep is selected and implemented with the assistance of the best virtual factory version. It is shown how a completely digitalized preservation process can be supported by a digital manufacturing facility version by offering facts. Among different functions, the virtual manufacturing facility version is used for indoor navigation, facts provision, and display of sensor statistics. In summary, the paper suggests a structuring of virtual factory fashions that concentrates on the geometric representation of a manufacturing facility building and its technical facilities. A practical application case is proven and implemented. For that reason, the systematic selection of virtual manufacturing facility models with the corresponding utility cases is evaluated.

Keywords: augmented reality, digital factory model, factory planning, restructuring digital factory model, photogrammetry, factory planning, restructuring building information modeling, digital factory model, factory planning, maintenance

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854 Exploring Exposed Political Economy in Disaster Risk Reduction Efforts in Bangladesh

Authors: Shafiqul Islam, Cordia Chu

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Bangladesh is one of the most vulnerable countries to climate related disasters such as flood and cyclone. Exploring from the semi-structured in-depth interviews of 38 stakeholders and literature review, this study examined the public spending distribution process in DRR. This paper demonstrates how the processes of political economy-enclosure, exclusion, encroachment, and entrenchment hinder the Disaster Risk Reduction (DRR) efforts of Department of Disaster Management (DDM) such as distribution of flood centres, cyclone centres and 40 days employment generation programs. Enclosure refers to when DRR projects allocated to less vulnerable areas or expand the roles of influencing actors into the public sphere. Exclusion refers to when DRR projects limit affected people’s access to resources or marginalize particular stakeholders in decision-making activities. Encroachment refers to when allocation of DRR projects and selection of location and issues degrade the environmental affect or contribute to other forms of disaster risk. Entrenchment refers to when DRR projects aggravate the disempowerment of common people worsen the concentrations of wealth and income inequality within a community. In line with United Nations (UN) Sustainable Development Goals (SDGs), Hyogo and Sendai Frameworks, in the case of Bangladesh, DRR policies implemented under the country’s national five-year plan, disaster-related acts and rules. These policies and practices have somehow enabled influential-elites to mobilize and distribute resources through bureaucracies. Exclusionary forms of fund distribution of DRR exist at both the national and local scales. DRR related allocations have encroached through the low land areas development project without consulting local needs. Most severely, DRR related unequal allocations have entrenched social class trapping the backward communities vulnerable to climate related disasters. Planners and practitioners of DRR need to take necessary steps to eliminate the potential risks from the processes of enclosure, exclusion, encroachment, and entrenchment happens in project fund allocations.

Keywords: Bangladesh, disaster risk reduction, fund distribution, political economy

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853 Evaluation of Methods for Simultaneous Extraction and Purification of Fungal and Bacterial DNA from Vaginal Swabs

Authors: Vanessa De Carvalho, Chad MacPherson, Julien Tremblay, Julie Champagne, Stephanie-Anne Girard

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Background: The interactions between bacteria and fungi in the human vaginal microbiome are fundamental to the concept of health and disease. The means by which the microbiota and mycobiota interact is still poorly understood and further studies are necessary to properly characterize this complex ecosystem. The aim of this study was to select a DNA extraction method capable of recovering high qualities of fungal and bacterial DNA from a single vaginal swab. Methods: 11 female volunteers ( ≥ 20 to < 55 years old) self-collected vaginal swabs in triplicates. Three commercial extraction kits: Masterpure Yeast Purification kit (Epicenter), PureLink™ Microbiome DNA Purification kit (Invitrogen), and Quick-DNA™ Fecal/Soil Microbe Miniprep kit (Zymo) were evaluated on the ability to recover fungal and bacterial DNA simultaneously. The extraction kits were compared on the basis of recovery, yield, purity, and the community richness of bacterial (16S rRNA - V3-V4 region) and fungal (ITS1) microbiota composition by Illumina MiSeq amplicon sequencing. Results: Recovery of bacterial DNA was achieved with all three kits while fungal DNA was only consistently recovered with Masterpure Yeast Purification kit (yield and purity). Overall, all kits displayed similar microbiota profiles for the top 20 OTUs; however, Quick-DNA™ Fecal/Soil Microbe Miniprep kit (Zymo) showed more species richness than the other two kits. Conclusion: In the present study, Masterpure Yeast purification kit proved to be a good candidate for purification of high quality fungal and bacterial DNA simultaneously. These findings have potential benefits that could be applied in future vaginal microbiome research. Whilst the use of a single extraction method would lessen the burden of multiple swab sampling, decrease laboratory workload and off-set costs associated with multiple DNA extractions, thoughtful consideration must be taken when selecting an extraction kit depending on the desired downstream application.

Keywords: bacterial vaginosis, DNA extraction, microbiota, mycobiota, vagina, vulvovaginal candidiasis, women’s health

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852 Acoustic Emission Monitoring of Surface Roughness in Ultra High Precision Grinding of Borosilicate-Crown Glass

Authors: Goodness Onwuka, Khaled Abou-El-Hossein

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The increase in the demand for precision optics, coupled with the absence of much research output in the ultra high precision grinding of precision optics as compared to the ultrahigh precision diamond turning of optical metals has fostered the need for more research in the ultra high precision grinding of an optical lens. Furthermore, the increase in the stringent demands for nanometric surface finishes through lapping, polishing and grinding processes necessary for the use of borosilicate-crown glass in the automotive and optics industries has created the demand to effectively monitor the surface roughness during the production process. Acoustic emission phenomenon has been proven as useful monitoring technique in several manufacturing processes ranging from monitoring of bearing production to tool wear estimation. This paper introduces a rare and unique approach with the application of acoustic emission technique to monitor the surface roughness of borosilicate-crown glass during an ultra high precision grinding process. This research was carried out on a 4-axes Nanoform 250 ultrahigh precision lathe machine using an ultra high precision grinding spindle to machine the flat surface of the borosilicate-crown glass with the tip of the grinding wheel. A careful selection of parameters and design of experiment was implemented using Box-Behnken method to vary the wheel speed, feed rate and depth of cut at three levels with a 3-center point design. Furthermore, the average surface roughness was measured using Taylor Hobson PGI Dimension XL optical profilometer, and an acoustic emission data acquisition device from National Instruments was utilized to acquire the signals while the data acquisition codes were designed with National Instrument LabVIEW software for acquisition at a sampling rate of 2 million samples per second. The results show that the raw and root mean square amplitude values of the acoustic signals increased with a corresponding increase in the measured average surface roughness values for the different parameter combinations. Therefore, this research concludes that acoustic emission monitoring technique is a potential technique for monitoring the surface roughness in the ultra high precision grinding of borosilicate-crown glass.

Keywords: acoustic emission, borosilicate-crown glass, surface roughness, ultra high precision grinding

Procedia PDF Downloads 285
851 Sea of Light: A Game 'Based Approach for Evidence-Centered Assessment of Collaborative Problem Solving

Authors: Svenja Pieritz, Jakab Pilaszanovich

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Collaborative Problem Solving (CPS) is recognized as being one of the most important skills of the 21st century with having a potential impact on education, job selection, and collaborative systems design. Therefore, CPS has been adopted in several standardized tests, including the Programme for International Student Assessment (PISA) in 2015. A significant challenge of evaluating CPS is the underlying interplay of cognitive and social skills, which requires a more holistic assessment. However, the majority of the existing tests are using a questionnaire-based assessment, which oversimplifies this interplay and undermines ecological validity. Two major difficulties were identified: Firstly, the creation of a controllable, real-time environment allowing natural behaviors and communication between at least two people. Secondly, the development of an appropriate method to collect and synthesize both cognitive and social metrics of collaboration. This paper proposes a more holistic and automated approach to the assessment of CPS. To address these two difficulties, a multiplayer problem-solving game called Sea of Light was developed: An environment allowing students to deploy a variety of measurable collaborative strategies. This controlled environment enables researchers to monitor behavior through the analysis of game actions and chat. The according solution for the statistical model is a combined approach of Natural Language Processing (NLP) and Bayesian network analysis. Social exchanges via the in-game chat are analyzed through NLP and fed into the Bayesian network along with other game actions. This Bayesian network synthesizes evidence to track and update different subdimensions of CPS. Major findings focus on the correlations between the evidences collected through in- game actions, the participants’ chat features and the CPS self- evaluation metrics. These results give an indication of which game mechanics can best describe CPS evaluation. Overall, Sea of Light gives test administrators control over different problem-solving scenarios and difficulties while keeping the student engaged. It enables a more complete assessment based on complex, socio-cognitive information on actions and communication. This tool permits further investigations of the effects of group constellations and personality in collaborative problem-solving.

Keywords: bayesian network, collaborative problem solving, game-based assessment, natural language processing

Procedia PDF Downloads 122
850 Implementation of Efficiency and Energy Conservation Concept in Office Building as an Effort to Achieve Green Office Building Case Studies Office Building in Jakarta

Authors: Jarwa Prasetya Sih Handoko

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The issue of energy crisis for big cities in Indonesia are issues raised in line with the development of the city is rapidly increasing. Various attempts were made by the government in overcoming problems of energy needs in Indonesia. In addition to the efforts of the government required the efforts made by the public to solve this problem. The concept of green building in the design of the building with efforts to use energy efficiently can be one of the efforts that can be applied to solve this problem. Jakarta is capital and the one of the major cities in Indonesia with high economic growth. This leads to increased demand for office space for the people. So that the construction of office buildings in big cities like Jakarta very numerous. Office building is one of the buildings that require large energy consumption. As a building that could potentially require huge amounts of energy, the design should consider the use of energy to help provide solutions to problems of energy crisis in Indonesia. The concept of energy efficient is one of the concepts addressed in an effort to use energy in buildings to save energy needs of the building operations. Therefore, it is necessary to have a study that explores the application of the concept of energy efficiency and conservation in office buildings in Jakarta. In this study using two (2) buildings case study that Sequis Center Building and Sampoerna Strategic Square. Both are office buildings in Jakarta have earned the Green Building Certificate of Green Building Council Indonesia (GBCI). The study used literature review methods to address issues raised earlier. Whether it's related to a literature review on the study of office buildings and green building. With this paper is expected to be obtained on the application of the concept of energy efficiency and conservation in office buildings that have earned recognition as a green building by GBCI. The result could be a reference to the architect in designing the next office buildings, especially related to the concept of energy use in buildings. From this study, it can be concluded that the concept of energy efficiency and conservation in the design of office buildings can be applied to its orientation, the openings, the use shade in buildings, vegetation and building material selection and efficient use of water. So that it can reduce energy requirements needed to meet the needs of the building user activity. So the concept of energy efficiency and conservation in office buildings can be one of the efforts to realize the Green Office Building. Recommendations from this study is that the design of office buildings should be able to apply the concept of energy utilization in the design office. This is to meet the energy needs of the office buildings in an effort to realize the Green Building.

Keywords: energy crisis, energy efficiency, energy conservation, green building, office building

Procedia PDF Downloads 291
849 Effect of Spirulina Supplementation on Growth Performance and Body Conformation of Two Omani Goat Breeds

Authors: Fahad Al Yahyaey, Ihab Shaat, Russell Bush

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This study was conducted at the Livestock Research Centre, Ministry of Agriculture and Fisheries, Oman, on two local goat breeds (Jabbali and Sahrawi) due to their importance to Omani livestock production and food security. The Jabbali is characterized by increased growth rates and a higher twinning rate, while the Sahrawi has increased milk production. The aim of the study was to investigate the effect of Spirulina supplementation on live weight (BWT), average daily gain (ADG), and body conformation measurements; chest girth (CG), wither height (WH), body length (BL), and body condition score (BCS). Thirty-six males (approximately nine-months-old and 16.44 ± 0.33 kg average of initial body weight) were used across an eleven-week study from November–February 2019-2020. Each breed was divided into three groups (n = 6/group) and fed one of three rations: (1) concentrate mixture (Control) with crude protein 14% and energy 11.97% MJ/kg DM; (2) the same concentrate feed with the addition of 2 gm /capita daily Spirulina platensis (Treatment 1) and (3) the same concentrate feed with the addition of 4 gm /capita daily Spirulina platensis (Treatment 2). Analysis of weekly data collections for all traits indicated a significant effect of feeding Spirulina on all the studied traits except WH and BL. Analysis of variance for fixed effects in this study (damage and kid birth type i.e., single, twin or triple) were not significant for all studied traits. However, the breed effect was highly significant (P < 0.001) on BWT, ADG, BCS, and CG traits. On the other hand, when the analysis was done for the treatment effect within breeds for ADG, the Sahrawi breed had a significant effect (P < 0.05) at 56.52, 85.51, and 85.50 g/day for control, treatment 1 and treatment 2, respectively. This is a 51% difference between the control and treatment 1 (2 gm /capita). Whereas for the Jabbali breed, the treatment effect was not significant for ADG (P =0.55), and the actual ADG was 104.59, 118.84, and 114.25 g/day for control, treatment 1, and treatment 2, respectively, providing a 14% difference between the control group and the treated group (4 gm /capita). These findings indicate using Spirulina supplementation in Omani goat diets is recommended at 2 gm per capita as there was no benefit in feeding at 4 gm per capita for either breed. Farmers feeding Spirulina supplementation to kids after weaning at six-months could increase their herd performance and growth rate and facilitate buck selection at an earlier age.

Keywords: body conformation, goats, live weight, spirulina

Procedia PDF Downloads 103
848 Autophagy Defects That Modify Human Immune Cell Metabolism and Promote Aging-Associated Inflammation

Authors: Grace McCambridge, Alanna Keady, Madhur Agrawal, Dequina Nicholas Alvarado, Barbara Nikolajczyk, Leena Panneerseelan-Bharath

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Age is a non-modifiable risk factor for the inflammation that underlies pathologies such as type 2 diabetes mellitus (T2DM). Inflammation, as indicated by circulating cytokines, rises in aging, but mechanisms that promote this ‘inflammaging’ remain poorly defined. Furthermore, downstream consequences of inflammaging, including the development of an inflammatory profile that predicts comorbidities like T2DM, remain speculative. We tested the possibility that natural aging-associated changes in autophagy, a process that is compromised in both aging and T2DM, regulates inflammatory profiles in older subjects. Our data showed that circulating CD4⁺ T cells from older compared to younger subjects have (i) defects in autophagy; (ii) higher mitochondria accumulation; (iii) a failure to metabolically shift from oxidative phosphorylation to anaerobic glycolysis upon αCD3/CD28 activation; (iv) more reactive oxygen species (ROS) accumulation; and (v) a cytokine profile that recapitulates the Th17 profile that predicts T2DM. ROS scavenging in cells from older subjects restored mitochondrial mass and membrane potential (indicators of improved autophagy) and reduced Th17 cytokines to amounts made by T cells from younger subjects. Knock-down of the autophagy protein Atg3 in T cells from younger subjects increased mitochondrial accumulation and Th17 cytokines. To begin translating these findings to clinical practice, we showed that physiological concentrations of the diabetes drug metformin (100 µM) added in vitro enhanced autophagy, prevented mitochondria and ROS accumulation, increased anaerobic glycolysis, and decreased Th17 cytokines in activated CD4⁺ T cells from older subjects. Metformin therefore improves autophagy and multiple downstream pro-inflammatory mechanisms CD4⁺ T cells from older subjects. We conclude that autophagy improvement ameliorates the development of a T2DM-predictive Th17 profile in aging, and thus holds promise for delay or prevention of aging-associated metabolic decline.

Keywords: autophagy, mitochondrial turnover, ROS, glycolysis

Procedia PDF Downloads 154
847 Microwave-Assisted Alginate Extraction from Portuguese Saccorhiza polyschides – Influence of Acid Pretreatment

Authors: Mário Silva, Filipa Gomes, Filipa Oliveira, Simone Morais, Cristina Delerue-Matos

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Brown seaweeds are abundant in Portuguese coastline and represent an almost unexploited marine economic resource. One of the most common species, easily available for harvesting in the northwest coast, is Saccorhiza polyschides grows in the lowest shore and costal rocky reefs. It is almost exclusively used by local farmers as natural fertilizer, but contains a substantial amount of valuable compounds, particularly alginates, natural biopolymers of high interest for many industrial applications. Alginates are natural polysaccharides present in cell walls of brown seaweed, highly biocompatible, with particular properties that make them of high interest for the food, biotechnology, cosmetics and pharmaceutical industries. Conventional extraction processes are based on thermal treatment. They are lengthy and consume high amounts of energy and solvents. In recent years, microwave-assisted extraction (MAE) has shown enormous potential to overcome major drawbacks that outcome from conventional plant material extraction (thermal and/or solvent based) techniques, being also successfully applied to the extraction of agar, fucoidans and alginates. In the present study, acid pretreatment of brown seaweed Saccorhiza polyschides for subsequent microwave-assisted extraction (MAE) of alginate was optimized. Seaweeds were collected in Northwest Portuguese coastal waters of the Atlantic Ocean between May and August, 2014. Experimental design was used to assess the effect of temperature and acid pretreatment time in alginate extraction. Response surface methodology allowed the determination of the optimum MAE conditions: 40 mL of HCl 0.1 M per g of dried seaweed with constant stirring at 20ºC during 14h. Optimal acid pretreatment conditions have enhanced significantly MAE of alginates from Saccorhiza polyschides, thus contributing for the development of a viable, more environmental friendly alternative to conventional processes.

Keywords: acid pretreatment, alginate, brown seaweed, microwave-assisted extraction, response surface methodology

Procedia PDF Downloads 365
846 Extremophilic Amylases of Mycelial Fungi Strains Isolated in South Caucasus for Starch Processing

Authors: T. Urushadze, R. Khvedelidze, L. Kutateladze, M. Jobava, T. Burduli, T. Alexidze

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There is an increasing interest in reliable, wasteless, ecologically friendly technologies. About 40% of enzymes produced all over the world are used for production of syrups with high concentration of glucose-fructose. One of such technologies complies obtaining fermentable sugar glucose from raw materials containing starch by means of amylases. In modern alcohol-producing factories this process is running in two steps, involving two enzymes of different origin: bacterial α-amylase and fungal glucoamylase, as generally fungal amylases are less thermostable as compared to bacterial amylases. Selection of stable and operable at 700С and higher temperatures enzyme preparation with both α- and glucoamylase activities will allow conducting this process in one step. S. Durmishidze Institute of Biochemistry and Biotechnology owns unique collection of mycelial fungi, isolated from different ecological niches of Caucasus. As a result of screening our collection 39 strains poducing amylases were revealed. Most of them belong to the genus Aspergillus. Optimum temperatures of action of selected amylases from three producers were estableshed to be within the range 67-80°C. A. niger B-6 showed higher α-amylase activity at 67°C, and glucoamylase activity at 62°C, A. niger 6-12 showed higher α-amylase activity at 72°C, and glucoamylase activity at 65°C, Aspergillus niger p8-3 showed higher activities at 82°C and 70°C, for α-amylase and glucoamylase activities, respectively. Exhaustive hydrolysis process of starch solutions of different concentrations (3, 5, 15, and 30 %) with cultural liquid and technical preparation of Aspergillus niger p8-3 enzyme was studied. In case of low concentrations exhaustive hydrolysis of starch lasts 40–60 minutes, in case of high concentrations hydrolysis takes longer time. 98, 6% yield of glucose can be reached at incubation during 12 hours with enzyme cultural liquid and 8 hours incubation with technical preparation of the enzyme at gradual increase of temperature from 50°C to 82°C during the first 20 minutes and further decrease of temperature to 70°C. Temperature setting for high yield of glucose and high hydrolysis (pasteurizing), optimal for activity of these strains is the prerequisite to be able to carry out hydrolysis of starch to glucose in one step, and consequently, using one strain, what will be economically justified.

Keywords: amylase, glucose hydrolisis, stability, starch

Procedia PDF Downloads 341
845 Comprehensive Machine Learning-Based Glucose Sensing from Near-Infrared Spectra

Authors: Bitewulign Mekonnen

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Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

Procedia PDF Downloads 80
844 Model Organic Ranikin Cycle Power Plant for Waste Heat Recovery in Olkaria-I Geothermal Power Plant

Authors: Haile Araya Nigusse, Hiram M. Ndiritu, Robert Kiplimo

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Energy consumption is an indispensable component for the continued development of the human population. The global energy demand increases with development and population rise. The increase in energy demand, high cost of fossil fuels and the link between energy utilization and environmental impacts have resulted in the need for a sustainable approach to the utilization of the low grade energy resources. The Organic Rankine Cycle (ORC) power plant is an advantageous technology that can be applied in generation of power from low temperature brine of geothermal reservoirs. The power plant utilizes a low boiling organic working fluid such as a refrigerant or a hydrocarbon. Researches indicated that the performance of ORC power plant is highly dependent upon factors such as proper organic working fluid selection, types of heat exchangers (condenser and evaporator) and turbine used. Despite a high pressure drop, shell-tube heat exchangers have satisfactory performance for ORC power plants. This study involved the design, fabrication and performance assessment of the components of a model Organic Rankine Cycle power plant to utilize the low grade geothermal brine. Two shell and tube heat exchangers (evaporator and condenser) and a single stage impulse turbine have been designed, fabricated and the performance assessment of each component has been conducted. Pentane was used as a working fluid and hot water simulating the geothermal brine. The results of the experiment indicated that the increase in mass flow rate of hot water by 0.08 kg/s caused a rise in overall heat transfer coefficient of the evaporator by 17.33% and the heat transferred was increased by 6.74%. In the condenser, the increase of cooling water flow rate from 0.15 kg/s to 0.35 kg/s increased the overall heat transfer coefficient by 1.21% and heat transferred was increased by 4.26%. The shaft speed varied from 1585 to 4590 rpm as inlet pressure was varied from 0.5 to 5.0 bar and power generated was varying from 4.34 to 14.46W. The results of the experiments indicated that the performance of each component of the model Organic Rankine Cycle power plant operating at low temperature heat resources was satisfactory.

Keywords: brine, heat exchanger, ORC, turbine

Procedia PDF Downloads 638
843 Bio-Hub Ecosystems: Investment Risk Analysis Using Monte Carlo Techno-Economic Analysis

Authors: Kimberly Samaha

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In order to attract new types of investors into the emerging Bio-Economy, new methodologies to analyze investment risk are needed. The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding the use of biomass as a feedstock for power plants. This study looked at repurposing existing biomass-energy plants into Circular Zero-Waste Bio-Hub Ecosystems. A Bio-Hub model that first targets a ‘whole-tree’ approach and then looks at the circular economics of co-hosting diverse industries (wood processing, aquaculture, agriculture) in the vicinity of the Biomass Power Plants facilities. This study modeled the economics and risk strategies of cradle-to-cradle linkages to incorporate the value-chain effects on capital/operational expenditures and investment risk reductions using a proprietary techno-economic model that incorporates investment risk scenarios utilizing the Monte Carlo methodology. The study calculated the sequential increases in profitability for each additional co-host on an operating forestry-based biomass energy plant in West Enfield, Maine. Phase I starts with the base-line of forestry biomass to electricity only and was built up in stages to include co-hosts of a greenhouse and a land-based shrimp farm. Phase I incorporates CO2 and heat waste streams from the operating power plant in an analysis of lowering and stabilizing the operating costs of the agriculture and aquaculture co-hosts. Phase II analysis incorporated a jet-fuel biorefinery and its secondary slip-stream of biochar which would be developed into two additional bio-products: 1) A soil amendment compost for agriculture and 2) A biochar effluent filter for the aquaculture. The second part of the study applied the Monte Carlo risk methodology to illustrate how co-location derisks investment in an integrated Bio-Hub versus individual investments in stand-alone projects of energy, agriculture or aquaculture. The analyzed scenarios compared reductions in both Capital and Operating Expenditures, which stabilizes profits and reduces the investment risk associated with projects in energy, agriculture, and aquaculture. The major findings of this techno-economic modeling using the Monte Carlo technique resulted in the masterplan for the first Bio-Hub to be built in West Enfield, Maine. In 2018, the site was designated as an economic opportunity zone as part of a Federal Program, which allows for Capital Gains tax benefits for investments on the site. Bioenergy facilities are currently at a critical juncture where they have an opportunity to be repurposed into efficient, profitable and socially responsible investments, or be idled and scrapped. The Bio-hub Ecosystems techno-economic analysis model is a critical model to expedite new standards for investments in circular zero-waste projects. Profitable projects will expedite adoption and advance the critical transition from the current ‘take-make-dispose’ paradigm inherent in the energy, forestry and food industries to a more sustainable Bio-Economy paradigm that supports local and rural communities.

Keywords: bio-economy, investment risk, circular design, economic modelling

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842 Sustainable Development Goals 2030: A Case of Malaysian Priorities from the Perspectives of Undergraduate Students

Authors: Zurina Mahadi, Hukil Sino

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United Nations resolved 2030 Sustainable Development Goals (SDGs) in 2015 to complete what Millennium Development Goals did not achieve. Accommodating 17 goals and 169 targets, Sustainable Development Goals are designated to be achieved over the next 15 years. A survey was conducted in July 2019 among the undergraduate students of a public university in Selangor, Malaysia, to learn their selection over Sustainable Development Goals, which they think is the most critical in the Malaysian scenario. This study adopted a qualitative approach, and data is gathered from a single instruction questionnaire administered to a purposive sample of participants. 13 goals were selected by the participants which are Goal 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, 16 and 17 while none has selected Goal 7, 9, 14 and 15 which are ‘Affordable and Clean Energy’; ‘Industry, Innovation and Infrastructure’; ‘Life Below Water’ and ‘Life On Land’ respectively. The selected goals are then ranked according to the number of participants who chose that particular goal. Goal 8 is found to be at the highest position of the ranking while Goal 5, 6, 10, and 13 accommodating the lowest position. Goal 8, which is ‘Decent Work and Economic Growth’ is chosen by 13 participants as the most critical goal in Malaysia while Goal 5,6 10, and 13, which are ‘Gender Equality’; ‘Clean Water and Sanitation’; ‘Reduced Inequalities’ and ‘Climate Action’ respectively, are chosen by only one participant each. Issues highlighted by the participants are themed into 10 themes, which are job availability, cost of living, well-being, corruption, education, environment, gender, development planning, consumption, and partnership. The theme of the cost of living has the highest number of issues, followed by the theme of job availability and the environment. The theme of gender has the least number of issues, followed by the theme of corruption and development planning. In principle, these findings, therefore, conclude that from a public university students’ point of view, the most critical sustainable development goal is decent work and economic growth while the most concerning issue is the cost of living. The implications of these findings are students’ knowledge towards the current issues of development, and their views of future sustainable development are considerably high. This study, therefore, suggests their views be inculcated into local, sustainable development frameworks to increase the inclusiveness of the young generation as they are the future SDGs stakeholders.

Keywords: cost of living, inclusiveness, job availability, sustainable development goals

Procedia PDF Downloads 133
841 Effect of Sodium Aluminate on Compressive Strength of Geopolymer at Elevated Temperatures

Authors: Ji Hoi Heo, Jun Seong Park, Hyo Kim

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Geopolymer is an inorganic material synthesized by alkali activation of source materials rich in soluble SiO2 and Al2O3. Many researches have studied the effect of aluminum species on the synthesis of geopolymer. However, it is still unclear about the influence of Al additives on the properties of geopolymer. The current study identified the role of the Al additive on the thermal performance of fly ash based geopolymer and observing the microstructure development of the composite. NaOH pellets were dissolved in water for 14 M (14 moles/L) sodium hydroxide solution which was used as an alkali activator. The weight ratio of alkali activator to fly ash was 0.40. Sodium aluminate powder was employed as an Al additive and added in amounts of 0.5 wt.% to 2 wt.% by the weight of fly ash. The mixture of alkali activator and fly ash was cured in a 75°C dry oven for 24 hours. Then, the hardened geopolymer samples were exposed to 300°C, 600°C and 900°C for 2 hours, respectively. The initial compressive strength after oven curing increased with increasing sodium aluminate content. It was also observed in SEM results that more amounts of geopolymer composite were synthesized as sodium aluminate was added. The compressive strength increased with increasing heating temperature from 300°C to 600°C regardless of sodium aluminate addition. It was consistent with the ATR-FTIR results that the peak position related to asymmetric stretching vibrations of Si-O-T (T: Si or Al) shifted to higher wavenumber as the heating temperature increased, indicating the further geopolymer reaction. In addition, geopolymer sample with higher content of sodium aluminate showed better compressive strength. It was also reflected on the IR results by more shift of the peak position assigned to Si-O-T toward the higher wavenumber. However, the compressive strength decreased after being exposed to 900°C in all samples. The degree of reduction in compressive strength was decreased with increasing sodium aluminate content. The deterioration in compressive strength was most severe in the geopolymer sample without sodium aluminate additive, while the samples with sodium aluminate addition showed better thermal durability at 900°C. This is related to the phase transformation with the occurrence of nepheline phase at 900°C, which was most predominant in the sample without sodium aluminate. In this work, it was concluded that sodium aluminate could be a good additive in the geopolymer synthesis by showing the improved compressive strength at elevated temperatures.

Keywords: compressive strength, fly ash based geopolymer, microstructure development, Na-aluminate

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840 Microbial Effects of Iron Elution from Hematite into Seawater Mediated via Dissolved Organic Matter

Authors: Apichaya Aneksampant, Xuefei Tu, Masami Fukushima, Mitsuo Yamamoto

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The restoration of seaweed beds recovery has been developed using a fertilization technique for supplying dissolved iron to barren coastal areas. The fertilizer is composed of iron oxides as a source of iron and compost as humic substance (HS) source, which can serve as chelator of iron to stabilize the dissolved species under oxic seawater condition. However, elution mechanisms of iron from iron oxide surfaces have not sufficiently elucidated. In particular, roles of microbial activities in the elution of iron from the fertilizer are not sufficiently understood. In the present study, a fertilizer (iron oxide/compost = 1/1, v/v) was incubated in a water tank at Mashike coast, Hokkaido Japan. Microorganisms in the 6-month fertilizer were isolated and identified as Exiguobacterium oxidotolerans sp. (T-2-2). The identified bacteria were inoculated to perform iron elution test in a postgate B medium, prepared in artificial seawater. Hematite was used as a model iron oxide and anthraquinone-2,7-disolfonate (AQDS) as a model for HSs. The elution test performed in presence and absence of bacteria inoculation. ICP-AES was used to analyze total iron and a colorimetric technique using ferrozine employed for the determination of ferrous ion. During the incubation period, sample contained hematite and T-2-2 in both presence and absence of AQDS continuously showed the iron elution and reached at the highest concentration after 9 days of incubation and then slightly decrease to stabilize within 20 days. Comparison to the sample without T-2-2, trace amount of iron was observed, suggesting that iron elution to seawater can be attributed to bacterial activities. The levels of total organic carbon (TOC) in the culture solution with hematite decreased. This may be to the adsorption of organic compound, AQDS, to hematite surfaces. The decrease in UV-vis absorption of AQDS in the culture solution also support the results of TOC that AQDS was adsorbed to hematite surfaces. AQDS can enhance the iron elution, while the adsorption of organic matter suppresses the iron elution from hematite.

Keywords: anthraquinone-2, 7-disolfonate, barren ground, E.oxidotolerans sp., hematite, humic substances, iron elution

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839 Effect of Roasting Temperature on the Proximate, Mineral and Antinutrient Content of Pigeon Pea (Cajanus cajan) Ready-to-Eat Snack

Authors: Olaide Ruth Aderibigbe, Oluwatoyin Oluwole

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Pigeon pea is one of the minor leguminous plants; though underutilised, it is used traditionally by farmers to alleviate hunger and malnutrition. Pigeon pea is cultivated in Nigeria by subsistence farmers. It is rich in protein and minerals, however, its utilisation as food is only common among the poor and rural populace who cannot afford expensive sources of protein. One of the factors contributing to its limited use is the high antinutrient content which makes it indigestible, especially when eaten by children. The development of value-added products that can reduce the antinutrient content and make the nutrients more bioavailable will increase the utilisation of the crop and contribute to reduction of malnutrition. This research, therefore, determined the effects of different roasting temperatures (130 0C, 140 0C, and 150 0C) on the proximate, mineral and antinutrient component of a pigeon pea snack. The brown variety of pigeon pea seeds were purchased from a local market- Otto in Lagos, Nigeria. The seeds were cleaned, washed, and soaked in 50 ml of water containing sugar and salt (4:1) for 15 minutes, and thereafter the seeds were roasted at 130 0C, 140 0C, and 150 0C in an electric oven for 10 minutes. Proximate, minerals, phytate, tannin and alkaloid content analyses were carried out in triplicates following standard procedures. The results of the three replicates were polled and expressed as mean±standard deviation; a one-way analysis of variance (ANOVA) and the Least Significance Difference (LSD) were carried out. The roasting temperatures significantly (P<0.05) affected the protein, ash, fibre and carbohydrate content of the snack. Ready-to-eat snack prepared by roasting at 150 0C significantly had the highest protein (23.42±0.47%) compared the ones roasted at 130 0C and 140 0C (18.38±1.25% and 20.63±0.45%, respectively). The same trend was observed for the ash content (3.91±0.11 for 150 0C, 2.36±0.15 for 140 0C and 2.26±0.25 for 130 0C), while the fibre and carbohydrate contents were highest at roasting temperature of 130 0C. Iron, zinc, and calcium were not significantly (P<0.5) affected by the different roasting temperatures. Antinutrients decreased with increasing temperature. Phytate levels recorded were 0.02±0.00, 0.06±0.00, and 0.07±0.00 mg/g; tannin levels were 0.50±0.00, 0.57±0.00, and 0.68±0.00 mg/g, while alkaloids levels were 0.51±0.01, 0.78±0.01, and 0.82±0.01 mg/g for 150 0C, 140 0C, and 130 0C, respectively. These results show that roasting at high temperature (150 0C) can be utilised as a processing technique for increasing protein and decreasing antinutrient content of pigeon pea.

Keywords: antinutrients, pigeon pea, protein, roasting, underutilised species

Procedia PDF Downloads 128
838 The Effects of Cultural Distance and Institutions on Foreign Direct Investment Choices: Evidence from Turkey and China

Authors: Nihal Kartaltepe Behram, Göksel Ataman, Dila Okçu

Abstract:

With the development of foreign direct investments, the social, cultural, political and economic interactions between countries and institutions have become visible and they have become determining factors for the strategic structuring and market goals. In this context the purpose of this study is to investigate the effects of cultural distance and institutions on foreign direct investment choices in terms of location and investment model. For international establishments, the concept of culture, as well as the concept of cultural distance, is taken specifically into consideration, especially in the selection of methods for entering the market. In the researches and empirical studies conducted, a direct relationship between cultural distance and foreign direct investments is set and institutions and effective variable factors are examined at the level of defining the investment types. When the detailed calculation strategies and empirical researches and studies are taken into consideration, the most common methods for determining the direct investment model, considering the cultural distances, are full-ownership enterprises and joint ventures. Also, when all of the factors affecting the investments are taken into consideration, it was seen that the effect of institutions such as Government Intervention, Intellectual Property Rights, Corruption and Contract Enforcements is very important. Furthermore agglomeration is more intense and effective on the investment, compared to other factors. China has been selected as the target country, due to its effectiveness in world economy and its contributions to developing countries, which has commercial relationships with. Qualitative research methods are used for this study conducted, to measure the effects of determinative variable factors in the hypotheses of study, on the direct foreign investors and to evaluate the findings. In this study in-depth interview is used as a data collection method and the data analysis is made through descriptive analysis. Foreign Direct Investments are so reactive to institutions and cultural distance is identified by all interviews and analysis. On the other hand, agglomeration is the most strong determiner factor on foreign direct investors in Chinese Market. The reason of this factors, which comprise the sectorial aggregate, are not the strongest factors as agglomeration that the most important finding. We expect that this study became a beneficial guideline for developed and developing countries and local and national institutions’ strategic plans.

Keywords: China, cultural distance, Foreign Direct Investments, institutions

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837 High Blood Pressure and Type 2 Diabetes Mellitus: A Study on Lay Understandings and Uses of Pharmaceuticals and Medicinal Plants for Treatment in Matzikama Municipal Region, Western Cape, South Africa

Authors: Diana Gibson

Abstract:

Aim: The first aim of the study was to ascertain the percentage of people who had been diagnosed with High Blood Pressure and/ or Type2 Diabetes Mellitus in Matzikama municipal district, Western Cape, South Africa. These two conditions are reportedly very high in this particular province, even though few statistics are available. A second aim was to gain insight into the understanding of these two conditions among sufferers. A third aim was to determine their allopathic use as well as indigenous medicinal plants to manage these conditions. A fourth aim was to understand how users of medicinal plants attend to their materiality and relationality as a continuum between humans and plants. The final aim was to ascertain the conservation status of medicinal plants utilised. Methods: One thousand one hundred and eighty-four (1184) respondents were interviewed. Semi-structured surveys were utilised to gather data on the percentage of people who had been medically diagnosed with High Blood Pressure and/or Type 2 Diabetes Mellitus. Local healers and knowledgeable old people were subsequently selected through a non-probability snowball sampling method. They were helped with plant collection. The plants were botanically identified. Results: The study found that people who have been diagnosed with High Blood Pressure or Type 2 Diabetes Mellitus drew on and continuously moved between biomedical and local understandings of these conditions. While they followed biomedical treatment regimens as far as possible they also drew on alternative ways of managing it through the use of medicinal plants. The most commonly used plant species overall were Lessertia frutescens, Tulbaghia violacea, Artemisia afra and Leonotus leonurus. For the users, medicinal plants were not mere material entities, they were actants in social networks where knowledge was produced through particular practices in specific places. None of the identified plants are currently threatened. Significance: Sufferers had a good understanding of the symptoms of and biomedical treatment regime for both conditions, but in everyday life they adhered to their local understandings and medicinal plants for treatment. The majority used reportedly used prescribed medication as well as plant alternatives.

Keywords: diabetes, high blood pressure, medicine, plants

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