Search results for: plant growth models

Authors: Sadhvi Gupta, Charulatha S.

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Since the dawn of the early 1950s humans have launched numerous vehicles in space. Be it from rockets to rovers humans have done tremendous growth in the technology sector. While there is mostly upside for it for humans the only major downside which cannot be ignored now is the amount of junk produced in space due to it i.e. space debris. All this space junk amounts from objects we launch from earth which so remains in orbit until it re-enters the atmosphere. Space debris can be of various sizes mainly the big ones are of the dead satellites floating in space and small ones can consist of various things like paint flecks, screwdrivers, bolts etc. Tracking of small space debris whose size is less than 10 cm is impossible and can have vast implications. As the amount of space debris increases in space the chances of it hitting a functional satellite also increases. And it is extremely costly to repair or recover the satellite once hit by a revolving space debris. So the proposed solution is, Actively removing space debris while keeping space sustainability in mind. For this solution a total of 8 modules will be launched in LEO and in GEO and these models will be placed in their desired orbits through Hohmann transfer and for that calculating ΔV values is crucial. After which the modules will be placed in their designated positions in STK software and thorough analysis is conducted.

Keywords: space debris, Hohmann transfer, STK, delta-V

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Authors: Adetunji Abiola Olaoye

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The study examined the students’ self-concepts and mathematics achievement viz-a-viz the existing three theoretical models: Humanist self-concept (M1), Contemporary self-concept (M2) and Skills development self-concept (M3). As a qualitative research study, it comprised of one research question, which was transformed into hypothesis viz-a-viz the existing theoretical models. Sample to the study comprised of twelve public secondary schools from which twenty-five mathematics teachers, twelve counselling officers and one thousand students of Upper Basic II were selected based on intact class as school administrations and system did not allow for randomization. Two instruments namely 10 items ‘Achievement test in Mathematics’ (r1=0.81) and 10 items Student’s self-concept questionnaire (r2=0.75) were adapted, validated and used for the study. Data were analysed through descriptive, one way ANOVA, t-test and correlation statistics at 5% level of significance. Finding revealed mean and standard deviation of pre-achievement test scores of (51.322, 16.10), (54.461, 17.85) and (56.451, 18.22) for the Humanist Self-Concept, Contemporary Self-Concept and Skill Development Self-Concept respectively. Apart from that study showed that there was significant different in the academic performance of students along the existing models (F-cal>F-value, df = (2,997); P<0.05). Furthermore, study revealed students’ achievement in mathematics and self-concept questionnaire with the mean and standard deviation of (57.4, 11.35) and (81.6, 16.49) respectively. Result confirmed an affirmative relationship with the Contemporary Self-Concept model that expressed an individual subject and specific self-concept as the primary determinants of higher academic achievement in the subject as there is a statistical correlation between students’ self-concept and mathematics achievement viz-a-viz the existing three theoretical models of Contemporary (M2) with -Z_cal<-Z_val, df=998: P<0.05*. The implication of the study was discussed with recommendations and suggestion for further studies proffered.

Keywords: contemporary, humanists, self-concepts, skill development

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Authors: Jianhua Wang

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To obtain key information quickly from long texts on small screens of mobile devices, sight-interpreters need to establish optimized summarization model for fast information retrieval. Four summarization models based on previous studies were studied including title+key words (TKW), title+topic sentences (TTS), key words+topic sentences (KWTS) and title+key words+topic sentences (TKWTS). Psychological experiments were conducted on the four models for three different genres of interpreting texts to establish the optimized summarization model for sight-interpreters. This empirical study shows that the optimized summarization model for sight-interpreters to quickly grasp the key information of the texts they interpret is title+key words (TKW) for cultural texts, title+key words+topic sentences (TKWTS) for economic texts and topic sentences+key words (TSKW) for political texts.

Keywords: different genres, mobile screens, optimized summarization models, sight-interpreters

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Authors: Alia Ragheb

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Philodendron species were reported in traditional medicine for the treatment of several diseases. From the 70% methanol extract of the aerial parts of Philodendron bipinnatifidum Schott ex Endl, nine flavonoid compounds were isolated and identified for the first time; saponarin, genkwanin 8-C-(2′′-O-β-glucopyranosyl)-β-glucopyranoside, apigenin 6-C-(2′′-O-β-glucopyranosyl)-β-glucopyranoside, schaftoside, swertisin, swertiajaponin, isoswertisin, isorhamnetin 3-O-(2′′-acetyl)-β-glucopyranoside and apigenin. Characterization of the plant was achieved using chromatographic, physical, chemical, spectroscopic, and spectrometric techniques. The 70% methanol aerial parts extract and the methanol fraction of the plant were in vivo screened for their acute anti-inflammatory, antipyretic and analgesic effects where significant effects were exhibited compared to that of reference drugs. From the reported literature, these biological activities could be attributed to its phenolic constituent. The 70% methanol aerial parts and successive extracts, as well as some pure isolated flavonoid compounds, were in vitro investigated for their antioxidant, antimicrobial and cytotoxic activities.

Keywords: antioxidant, araceae, cytotoxicity, flavonoids

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Authors: Ogbe E. E., Ossia. C. V., Saturday. E. G., Ezekwe M. C.

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The disparity in power output between a simple and a modified gas turbine plant is noticeable when the gas turbine functions under local environmental conditions that deviate from the standard ISO specifications. Extensive research and literature have demonstrated a well-known direct correlation between ambient temperature and the power output of a gas turbine plant. In this study, the Omotosho gas turbine plant was modified into three different configurations. The reason for the modification is to improve its performance and reduce the fuel consumption and emission rate. Aspen Hysys software was used to simulate both the simple (Omotosho) and the three modified gas turbine plants. The input parameters considered include ambient temperature, air mass flow rate, fuel mass flow rate, water mass flow rate, turbine inlet temperature, compressor efficiency, and turbine efficiency, while the output parameters considered are thermal efficiency, specific fuel consumption, heat rate, emission rate, compressor power, turbine power and power output. The three modified gas turbine power plants incorporate an inlet air cooling system and a heat recovery steam generator. The variations between the modifications are due to additional components or enhancements alongside the inlet air cooling system and heat recovery steam generator incorporated; the first modification has an additional turbine, the second modification has an additional combustion chamber, and the third modification has an additional turbine and combustion chamber. This paper clearly shows ambient temperature effects on both the simple and three modified gas turbine plants. for every 10-degree kelvin increase in ambient temperature, there is an approximate reduction of 3977 kW, 4795 kW, 4681 kW, and 4793 kW of the power output for the simple gas turbine, first, second, and third modifications, respectively. Also, for every 10-degree kelvin increase in temperature, there is a thermal efficiency decrease of 1.22%, 1.45%, 1.43%, and 1.44% for the simple gas turbine, first, second, and third modifications respectively. Low ambient temperature will help save fuel; looking at the high price of fuel presently in Nigeria for every 10 degrees kelvin increase in temperature, there is a specific fuel consumption increase of 0.0074 kg/kWh, 0.0051 kg/kWh, 0.0061 kg/kWh, and 0.0057 kg/kWh for the simple gas turbine, first, second, and third modifications respectively. These findings will aid in accurately evaluating local power generating plants, particularly in hotter regions, for installing gas turbine inlet air cooling (GTIAC) systems.

Keywords: Aspen HYSYS software, Brayton Cycle, modified gas turbine, power plant, simple gas turbine, thermal efficiency.

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Authors: Osatuyi Kehinde Micheal

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There is much research that has contributed to an improved understanding of the future of food security, especially during the COVID-19 pandemic. A pathway was developed by using a local community kitchen in Muizenberg in western cape province, cape town, south Africa, a case study to map out the future of food security in times of crisis. This kitchen aims to provide nutritious, affordable, plant-based meals to our community. It is also a place of diverse learning, sharing, empowering the volunteers, and growth to support the local economy and future resilience by sustaining our community kitchen for the community. This document contains an overview of the story of the community kitchen on how we create self-sustainability as a new pathway development to sustain the community and reduce Zero hunger in the regional food system. This paper describes the key elements of how we respond to covid-19 pandemic by sharing food parcels and creating 13 soup kitchens across the community to tackle the immediate response to covid-19 pandemic and agricultural systems by growing home food gardening in different homes, also having a consciousness Dry goods store to reduce Zero waste and a local currency as an innovation to reduce food crisis. Insights gained from our article and outreach and their value in how we create adaptation, transformation, and sustainability as a new development pathway to solve any future problem crisis in the food security system in our society.

Keywords: sustainability, food security, community development, adapatation, transformation

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Authors: Amreth Chandrasehar

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Machine Learning (ML) Models are developed and run in production to solve various use cases that help organizations to be more efficient and help drive the business. But this comes at a massive development cost and lost business opportunities. According to the Gartner report, 85% of data science projects fail, and one of the factors impacting this is not paying attention to Model Observability. Model Observability helps the developers and operators to pinpoint the model performance issues data drift and help identify root cause of issues. This paper focuses on providing insights into incorporating model observability in model development and operationalizing it in production.

Keywords: model observability, monitoring, drift detection, ML observability platform

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Authors: Sandeep J. Kumar

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Urbanisation is considered as the primary driver of land use and land cover change that has direct link to population and economic growth. In India, as well as in other developing countries, cities are urbanizing at an alarming rate. This unprecedented and uncontrolled urbanisation can result in urban sprawl. Due to a number of factors, urban sprawl is recognised to be a result of poor planning, inadequate policies, and poor governance. Urban sprawl may be seen as posing a threat to the development of sustainable cities. Hence, it is very essential to manage this. Planning for predicted future growth is critical to avoid the negative effects of urban growth at the local and regional levels. Thiruvananthapuram being the capital city of Kerala is a city of economic success, challenges, and opportunities. Urbanization trends in the city have paved way for Urban Sprawl. This thesis aims to formulate a framework to combat the emerging urban sprawl in the city of Thiruvananthapuram. For that, the first step was to quantify trends of urban growth in Thiruvananthapuram city using Geographical Information System(GIS) and remote sensing techniques. The technique and results obtained in the study are extremely valuable in analysing the land use changes. Secondly, these change in the trends were analysed through some of the critical factors that helped the study to understand the underlying issues of the existing city structure that has resulted in urban sprawl. Anticipating development trends can modify the current order. This can be productively resolved using regional and municipal planning and management strategies. Hence efficient strategies to curb the sprawl in Thiruvananthapuram city have been formulated in this study that can be considered as recommendations for future planning.

Keywords: urbanisation, urban sprawl, geographical information system(GIS), thiruvananthapuram

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Authors: Kenichi Yamahara, Makiko Ohshima, Shunsuke Ohnishi, Hidetoshi Tsuda, Akihiko Taguchi, Toshihiro Soma, Hiroyasu Ogawa, Jun Yoshimatsu, Tomoaki Ikeda

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We have previously reported the therapeutic potential of rat fetal membrane(FM)-derived mesenchymal stem cells (MSCs) using various rat models including hindlimb ischemia, autoimmune myocarditis, glomerulonephritis, renal ischemia-reperfusion injury, and myocardial infarction. In this study, 1) we isolated and characterized MSCs from human amnion and chorion; 2) we examined their differences in the expression profile of growth factors and cytokines; and 3) we investigated the therapeutic potential and difference of these MSCs using murine hindlimb ischemia and acute graft-versus-host disease (GVHD) models. Isolated MSCs from both amnion and chorion layers of FM showed similar morphological appearance, multipotency, and cell-surface antigen expression. Conditioned media obtained from amnion- and chorion-derived MSCs inhibited cell death caused by serum starvation or hypoxia in endothelial cells and cardiomyocytes. Amnion and chorion MSCs secreted significant amounts of angiogenic factors including HGF, IGF-1, VEGF, and bFGF, although differences in the cellular expression profile of these soluble factors were observed. Transplantation of human amnion or chorion MSCs significantly increased blood flow and capillary density in a murine hindlimb ischemia model. In addition, compared to human chorion MSCs, human amnion MSCs markedly reduced T-lymphocyte proliferation with the enhanced secretion of PGE2, and improved the pathological situation of a mouse model of GVHD disease. Our results highlight that human amnionand chorion-derived MSCs, which showed differences in their soluble factor secretion and angiogenic/immuno-suppressive function, could be ideal cell sources for regenerative medicine.

Keywords: amnion, chorion, fetal membrane, mesenchymal stem cells

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Authors: Altaf H. Khan, Frank Stenger, Mohammed A. Hussein, Reaz A. Chaudhuri, Sameera Asif

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This paper discusses a novel approach to approximate quadrature integrals that arise in the estimation of likelihood parameters for the generalized linear mixed models (GLMM) as well as Bayesian methodology also requires computation of multidimensional integrals with respect to the posterior distributions in which computation are not only tedious and cumbersome rather in some situations impossible to find solutions because of singularities, irregular domains, etc. An attempt has been made in this work to apply Sinc function based quadrature rules to approximate intractable integrals, as there are several advantages of using Sinc based methods, for example: order of convergence is exponential, works very well in the neighborhood of singularities, in general quite stable and provide high accurate and double precisions estimates. The Sinc function based approach seems to be utilized first time in statistical domain to our knowledge, and it's viability and future scopes have been discussed to apply in the estimation of parameters for GLMM models as well as some other statistical areas.

Keywords: generalized linear mixed model, likelihood parameters, qudarature, Sinc function

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Authors: Collen T. Masilo, Brane Semolic, Pieter Steyn

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The Internet Protocol Television (IPTV) and Hybrid Fibre-Coaxial (HFC) Broadband industrial sector landscape are rapidly changing and organisations within the industry need to stay competitive by exploring new business models so that they can be able to offer new services and products to customers. The business challenge in this industrial sector is meeting or exceeding high customer expectations across multiple content delivery modes. The increasing challenges in the IPTV and HFC broadband industrial sector encourage service providers to form strategic partnerships with key suppliers, marketing partners, advertisers, and technology partners. The need to form enterprise collaborative networks poses a challenge for any organisation in this sector, in selecting the right strategic partners who will ensure that the organisation’s services and products are marketed in new markets. Partners who will ensure that customers are efficiently supported by meeting and exceeding their expectations. Lastly, selecting cooperation partners who will represent the organisation in a positive manner, and contribute to improving the performance of the organisation. Companies in the IPTV and HFC broadband industrial sector tend to form informal partnerships with suppliers, vendors, system integrators and technology partners. Generally, partnerships are formed without thorough analysis of the real reason a company is forming collaborations, without proper evaluations of prospective partners using specific selection criteria, and with ineffective performance monitoring of partners to ensure that a firm gains real long term benefits from its partners and gains competitive advantage. Similar tendencies are illustrated in the research case study and are based on Skyline Communications, a global leader in end-to-end, multi-vendor network management and operational support systems (OSS) solutions. The organisation’s flagship product is the DataMiner network management platform used by many operators across multiple industries and can be referred to as a smart system that intelligently manages complex technology ecosystems for its customers in the IPTV and HFC broadband industry. The approach of the research is to develop the most efficient business model that can be deployed to improve a strategic partnership programme in order to significantly improve the performance and growth of organisations participating in a collaborative network in the IPTV and HFC broadband industrial sector. This involves proposing and implementing a new strategic partnership model and its main features within the industry which should bring about significant benefits for all involved companies to achieve value add and an optimal growth strategy. The proposed business model has been developed based on the research of existing relationships, value chains and business requirements in this industrial sector and validated in 'Skyline Communications'. The outputs of the business model have been demonstrated and evaluated in the research business case study the IPTV and HFC broadband service provider 'Skyline Communications'.

Keywords: growth, partnership, selection criteria, value chain

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Authors: Pravinchandra Patel

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Sustainable agriculture in sandy loam soil generally faces large constraints due to low water holding and nutrient retention capacity, and accelerated mineralization of soil organic matter. There is need to increase soil organic carbon in the soil for higher crop productivity and soil sustainability. Recently biochar is considered as sixth element and work as a catalyst for increasing crop yield, soil fertility, soil sustainability and mitigation of climate change. Biochar was generated at the Sansoli Farm of Anand Agricultural University, Gujarat, India by pyrolysis at temperatures (250-400°C) in absence of oxygen using slow chemical process (using two kilns) from corn stover (Zea mays, L), cluster bean stover (Cyamopsis tetragonoloba) and Prosopis julifera wood. There were 16 treatments; 4 organic sources (3 biochar; corn stover biochar (MS), cluster bean stover (CB) & Prosopis julifera wood (PJ) and one farmyard manure-FYM) with two rate of application (5 & 10 metric tons/ha), so there were eight treatments of organic sources. Eight organic sources was applied with the recommended dose of fertilizers (RDF) (80-40-0 kg/ha N-P-K) while remaining eight organic sources were kept without RDF. Application of corn stover biochar @ 10 metric tons/ha along with RDF (RDF+MS) increased dry matter (DM) yield, crude protein (CP) yield, chlorophyll content and plant height (at 30 and 60 days after sowing) than CB and PJ biochar and FYM. Nutrient uptake of P, K, Ca, Mg, S and Cu were significantly increased with the application of RDF + corn stover @ 10 metric tons/ha while uptake of N and Mn were significantly increased in RDF + corn stover @ 5 metric tons/ha. It was found that soil application of corn stover biochar @ 10 metric tons/ha along with the recommended dose of chemical fertilizers (RDF+MS ) exhibited the highest impact in obtaining significantly higher dry matter and crude protein yields and larger removal of nutrients from the soil and it also beneficial for built up nutrients in soil. It also showed significantly higher organic carbon content and cation exchange capacity in sandy loam soil. The lower dose of corn stover biochar @ 5 metric tons/ha (RDF+ MS) was also remained the second highest for increasing dry matter and crude protein yields of forage corn crop which ultimately resulted in larger removals of nutrients from the soil. This study highlights the importance of mixing of biochar along with recommended dose of fertilizers on its synergistic effect on sandy loam soil nutrient retention, organic carbon content and water holding capacity hence, the amendment value of biochar in sandy loam soil.

Keywords: biochar, corn yield, plant nutrient, fertility status

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Authors: Pedro M. Abreu, Bruno R. Mendes

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The management of pharmacotherapy and the process of dispensing medicines is becoming critical in clinical pharmacy due to the increase of incidence and prevalence of chronic diseases, the complexity and customization of therapeutic regimens, the introduction of innovative and more expensive medicines, the unbalanced relation between expenditure and revenue as well as due to the lack of rationalization associated with medication use. For these reasons, co-payments emerged in Europe in the 70s and have been applied over the past few years in healthcare. Co-payments lead to a rationing and rationalization of user’s access under healthcare services and products, and simultaneously, to a qualification and improvement of the services and products for the end-user. This analysis, under hospital practices particularly and co-payment strategies in general, was carried out on all the European regions and identified four reference countries, that apply repeatedly this tool and with different approaches. The structure, content and adaptation of European co-payments were analyzed through 7 qualitative attributes and 19 performance indicators, and the results expressed in a scorecard, allowing to conclude that the German models (total score of 68,2% and 63,6% in both elected co-payments) can collect more compliance and effectiveness, the English models (total score of 50%) can be more accessible, and the French models (total score of 50%) can be more adequate to the socio-economic and legal framework. Other European models did not show the same quality and/or performance, so were not taken as a standard in the future design of co-payments strategies. In this sense, we can see in the co-payments a strategy not only to moderate the consumption of healthcare products and services, but especially to improve them, as well as a strategy to increment the value that the end-user assigns to these services and products, such as medicines.

Keywords: clinical pharmacy, co-payments, healthcare, medicines

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Authors: Uduak Umoh, Imo Eyoh, Emmauel Nyoho

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This paper compares fuzzy-machine learning algorithms such as Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) for the predicting cases of fire outbreak. The paper uses the fire outbreak dataset with three features (Temperature, Smoke, and Flame). The data is pre-processed using Interval Type-2 Fuzzy Logic (IT2FL) algorithm. Min-Max Normalization and Principal Component Analysis (PCA) are used to predict feature labels in the dataset, normalize the dataset, and select relevant features respectively. The output of the pre-processing is a dataset with two principal components (PC1 and PC2). The pre-processed dataset is then used in the training of the aforementioned machine learning models. K-fold (with K=10) cross-validation method is used to evaluate the performance of the models using the matrices – ROC (Receiver Operating Curve), Specificity, and Sensitivity. The model is also tested with 20% of the dataset. The validation result shows KNN is the better model for fire outbreak detection with an ROC value of 0.99878, followed by SVM with an ROC value of 0.99753.

Keywords: Machine Learning Algorithms , Interval Type-2 Fuzzy Logic, Fire Outbreak, Support Vector Machine, K-Nearest Neighbour, Principal Component Analysis

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Authors: Ezekiel Ejiofor Nnadi

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Nigeria construction industry is known for its active construction activities. This has earmarked the industry to be the key to economic growth of the nation. It has largest employer of labour and gives sustenance to other industries like manufacturing industry. While this is a sign of growth and prosperity; the waste generated by the industry has always been a problem and a serious concern. It results in wastage of economic gain and has resultant health effect on the populace apart from injury being sustained on sites. This work provides a platform to learn more about construction waste, its management strategy and how to reduce waste production in Nigeria construction industry. Construction sites, waste management authority and public health institutions in Lagos as the centre of most construction activities in Nigeria were selected, and a set of questionnaire was administered to using the systematic sampling technique. Descriptive statistics and relative importance index (RII) technique were employed for the analysis of the data gathered. The findings of the analysis show that excessive wastes reduce contractors’ profit margin and also that some construction wastes contain hazardous and toxic elements such as lead, asbestos or radioactive materials which required proper handling and effective disposal. The conclusion was drawn that the check on waste on construction sites starts with the designers to the contractors who execute on site.

Keywords: construction cost, construction industry, economic growth, materials wastes

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Authors: Gizem Buldum, Alexander Bismarck, Athanasios Mantalaris

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Cellulose is the most abundant biopolymer on earth and it is currently being utilised in a multitude of industrial applications. Over the last 30 years, attention has been paid to the bacterial cellulose (BC), since BC exhibits unique physical, chemical and mechanical properties when compared to plant-based cellulose, including high purity and biocompatibility. Although Acetobacter xylinum is the most efficient producer of BC, it’s long doubling time results in insufficient yields of the cellulose production. This limits widespread and continued use of BC. In this study, E. coli BL21 (DE3) or E. coli HMS cells are selected as host organisms for the expression of bacterial cellulose synthase operon (bcs) of A.xylinum. The expression system is created based on pET-Duet1 and pCDF plasmid vectors, which carry bcs operon. The results showed that all bcs genes were successfully transferred and expressed in E.coli strains. The expressions of bcs proteins were shown by SDS and Native page analyses. The functionality of the bcs operon was proved by congo red binding assay. The effect of culturing temperature and the inducer concentration (IPTG) on cell growth and plasmid stability were monitored. The percentage of plasmid harboring cells induced with 0.025 mM IPTG was obtained as 85% at 22˚C in the end of 10-hr culturing period. It was confirmed that the high output cellulose production machinery of A.xylinum can be transferred into other organisms.

Keywords: bacterial cellulose, biopolymer, recombinant expression system, production

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Authors: R. A. Eman Elsheikh, Bart Schultz, Abraham Mehari Haile, Hussein S. Adam

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A field experiment was conducted at Gezira research station farm during the winter season in the third week of November 2012, in WadMedani, Sudan (Lat 14.23 W, Long 33.39 E and altitude 405 m above sea level, in deep cracking alkaline heavy clay Vertisols). The objective of this study was to determine the effect of three different irrigation for 10 days (W1), 15 days (W2) and 20 days (W3) and for two rows of 30 cm (S1) and 40 cm (S2), respectively. The experimental design was split plot with three replicates. The sunflower test variety was Hysun 33 cultivar. The seasonal water applied during the study was 6898, 6647, 5256, 5435, 5214, 5416 m3/ha for W1S1, W1S2, W2S1, W2S2, W3S1 and W3S2 respectively. The seed yield obtained for the above treatment in that sequence was 4208, 5542, 5167, 4579, 2931, 2936 kg/ha. The corresponding computed water productivity was 0.61, 0.82, 0.87, 0.95, 0.54, 0.56 kg/m3. The study clearly indicated that the highest seed yield was obtained when the crop was sown at 40 cm row spacing and was irrigated every 10 days (W1S2), followed by W2S1.

Keywords: water productivity, water deficit, sunflower, plant spacing

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Authors: Shahrokh Ranjbar-Bahadori, Nima Farhadifar, Leila Mohammadyar

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Plant preparations from thyme and garlic have been shown to be effective acaricides against the poultry red mite, Dermanyssus gallinae. In a layer house with a history of D. gallinae problem, mites were detected in the monitoring traps for the first time and number of them was counted. Then, some rows of layer house was sprayed twice using a concentration of 0.21 mg/cm2 thyme essential oil and 0.07 mg/cm2 garlic juice and a similar row was used as an untreated control group. Red mite traps made of cardboard were used to assess the mite density during days 1 and 7 after treatment and always removed after 24 h. the collected mites were counted and the efficacy against all mite stages (larvae, nymphs and adults) was calculated. Results showed that on day 1 and 7 after the administration of garlic extract efficacy rate was 92.05% and 74.62%, respectively. Moreover, efficacy rate on day 1 and 7 was 89.4% and 95.37% when treatment was done with thyme essential oil. It is concluded that using garlic juice to control of D. gallinae is more effective on short time. But thyme essential oil has a long time effect in compare to garlic preparation.

Keywords: Dermanyssus gallinae, essential oil, garlic, thyme, efficacy

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Authors: Iman Farasat, Howard M. Salis

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Engineered genetic circuits reprogram cellular behavior to act as living computers with applications in detecting cancer, creating self-controlling artificial tissues, and dynamically regulating metabolic pathways. Phenemenological models are often used to simulate and design genetic circuit behavior towards a desired behavior. While such models assume that each circuit component’s function is modular and independent, even small changes in a circuit (e.g. a new promoter, a change in transcription factor expression level, or even a new media) can have significant effects on the circuit’s function. Here, we use statistical thermodynamics to account for the several factors that control transcriptional regulation in bacteria, and experimentally demonstrate the model’s accuracy across 825 measurements in several genetic contexts and hosts. We then employ our first principles model to design, experimentally construct, and characterize a family of signal amplifying genetic circuits (genetic OpAmps) that expand the dynamic range of cell sensors. To develop these models, we needed a new approach to measuring the in vivo binding free energies of transcription factors (TFs), a key ingredient of statistical thermodynamic models of gene regulation. We developed a new high-throughput assay to measure RNA polymerase and TF binding free energies, requiring the construction and characterization of only a few constructs and data analysis (Figure 1A). We experimentally verified the assay on 6 TetR-homolog repressors and a CRISPR/dCas9 guide RNA. We found that our binding free energy measurements quantitatively explains why changing TF expression levels alters circuit function. Altogether, by combining these measurements with our biophysical model of translation (the RBS Calculator) as well as other measurements (Figure 1B), our model can account for changes in TF binding sites, TF expression levels, circuit copy number, host genome size, and host growth rate (Figure 1C). Model predictions correctly accounted for how these 8 factors control a promoter’s transcription rate (Figure 1D). Using the model, we developed a design framework for engineering multi-promoter genetic circuits that greatly reduces the number of degrees of freedom (8 factors per promoter) to a single dimensionless unit. We propose the Ptashne (Pt) number to encapsulate the 8 co-dependent factors that control transcriptional regulation into a single number. Therefore, a single number controls a promoter’s output rather than these 8 co-dependent factors, and designing a genetic circuit with N promoters requires specification of only N Pt numbers. We demonstrate how to design genetic circuits in Pt number space by constructing and characterizing 15 2-repressor OpAmp circuits that act as signal amplifiers when within an optimal Pt region. We experimentally show that OpAmp circuits using different TFs and TF expression levels will only amplify the dynamic range of input signals when their corresponding Pt numbers are within the optimal region. Thus, the use of the Pt number greatly simplifies the genetic circuit design, particularly important as circuits employ more TFs to perform increasingly complex functions.

Keywords: transcription factor, synthetic biology, genetic circuit, biophysical model, binding energy measurement

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Authors: S. Nurdiana, A. S. Nor Haziqah, M. K. Nur Ezwa Khairunnisa, S. Nurul Izzati, Y. Siti Amna M. J. Norashirene, I. Nur Hilwani

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Azadirachta excelsa or locally known as sentang are frequently used as a traditional medicine by diabetes patients in Malaysia. However, less attention has been given to their toxicity effect. Thus, the study is an attempt to examine the protective effect of A. excelsa on the pancreas and to determine possible toxicity mediated by the extract. Diabetes was induced experimentally in rats by high-fat-diet for 16 weeks followed by intraperitoneal injection of streptozotocin at dosage of 35 mg/kg of body weight. Declination of the fasting blood glucose level was observed after continuous administration of A. excelsa for 14 days twice daily. This is due to the refining structure of the pancreas. However, surprisingly, the plant extract reduced the leukocytes, erythrocytes, hemoglobin, MCHC and lymphocytes. In addition, the rat treated with the plant extract exhibited increment in AST and eosinocytes level. Overall, the finding shows that A. excelsa possesses antidiabetic activity by improving the structure of pancreatic islet of Langerhans but involved in ameliorating of hematology and biochemical parameters.

Keywords: Azadirachta excelsa, diabetes, pancreas, hemato-biochemical parameters

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Authors: Mohammed Nasser Al-Suqri

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Former information-seeking models are proposed more than two decades ago. These already existed models were given prior to the evolution of digital information era and Artificial Intelligence (AI) technologies. Lack of current information seeking models within Library and Information Studies resulted in fewer advancements for teaching students about information-seeking behaviors, design of library tools and services. In order to better facilitate the aforementioned concerns, this study aims to propose state-of-the-art model while focusing on the information seeking behavior of library users in the Sultanate of Oman. This study aims for the development, designing and contextualizing the real-time user-centric information seeking model capable of enhancing information needs and information usage along with incorporating critical insights for the digital library practices. Another aim is to establish far-sighted and state-of-the-art frame of reference covering Artificial Intelligence (AI) while synthesizing digital resources and information for optimizing information-seeking behavior. The proposed study is empirically designed based on a mix-method process flow, technical surveys, in-depth interviews, focus groups evaluations and stakeholder investigations. The study data pool is consist of users and specialist LIS staff at 4 public libraries and 26 academic libraries in Oman. The designed research model is expected to facilitate LIS by assisting multi-dimensional insights with AI integration for redefining the information-seeking process, and developing a technology rich model.

Keywords: artificial intelligence, information seeking, information behavior, information seeking models, libraries, Sultanate of Oman

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Authors: H. Hruschka

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This paper presents the first comparison of the performance of the restricted Boltzmann machine and the deep belief net on binary market basket data relative to binary factor analysis and the two best-known topic models, namely Dirichlet allocation and the correlated topic model. This comparison shows that the restricted Boltzmann machine and the deep belief net are superior to both binary factor analysis and topic models. Managerial implications that differ between the investigated models are treated as well. The restricted Boltzmann machine is defined as joint Boltzmann distribution of hidden variables and observed variables (purchases). It comprises one layer of observed variables and one layer of hidden variables. Note that variables of the same layer are not connected. The comparison also includes deep belief nets with three layers. The first layer is a restricted Boltzmann machine based on category purchases. Hidden variables of the first layer are used as input variables by the second-layer restricted Boltzmann machine which then generates second-layer hidden variables. Finally, in the third layer hidden variables are related to purchases. A public data set is analyzed which contains one month of real-world point-of-sale transactions in a typical local grocery outlet. It consists of 9,835 market baskets referring to 169 product categories. This data set is randomly split into two halves. One half is used for estimation, the other serves as holdout data. Each model is evaluated by the log likelihood for the holdout data. Performance of the topic models is disappointing as the holdout log likelihood of the correlated topic model – which is better than Dirichlet allocation - is lower by more than 25,000 compared to the best binary factor analysis model. On the other hand, binary factor analysis on its own is clearly surpassed by both the restricted Boltzmann machine and the deep belief net whose holdout log likelihoods are higher by more than 23,000. Overall, the deep belief net performs best. We also interpret hidden variables discovered by binary factor analysis, the restricted Boltzmann machine and the deep belief net. Hidden variables characterized by the product categories to which they are related differ strongly between these three models. To derive managerial implications we assess the effect of promoting each category on total basket size, i.e., the number of purchased product categories, due to each category's interdependence with all the other categories. The investigated models lead to very different implications as they disagree about which categories are associated with higher basket size increases due to a promotion. Of course, recommendations based on better performing models should be preferred. The impressive performance advantages of the restricted Boltzmann machine and the deep belief net suggest continuing research by appropriate extensions. To include predictors, especially marketing variables such as price, seems to be an obvious next step. It might also be feasible to take a more detailed perspective by considering purchases of brands instead of purchases of product categories.

Keywords: binary factor analysis, deep belief net, market basket analysis, restricted Boltzmann machine, topic models

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Authors: Messis A., Adjebli A., Ayeche R., Talbi M., Tighilet K., Louardiane M.

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Cancers are the second cause of death worldwide. Prevalence and incidence of cancers is getting increased by aging and population growth. This study aims to predict and modeling the evolution of breast, Colorectal, Lung, Bladder and Prostate cancers over the period of 2014-2019. In this study, data were analyzed using time series analysis with double exponential smoothing method to forecast the future pattern. To describe and fit the appropriate models, Minitab statistical software version 17 was used. Between 2014 and 2019, the overall trend in the raw number of new cancer cases registered has been increasing over time; the change in observations over time has been increasing. Our forecast model is validated since we have good prediction for the period 2020 and data not available for 2021 and 2022. Time series analysis showed that the double exponential smoothing is an efficient tool to model the future data on the raw number of new cancer cases.

Keywords: cancer, time series, prediction, double exponential smoothing

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Authors: Huijuan Liu, Fukun Li, Hao Yuan

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The bolted spherical node is a common type of joint in space steel structures. The bolt-sphere joint portion almost always controls the bearing capacity of the bolted spherical node. The investigation of the bearing performance and progressive failure in service often requires high-fidelity numerical models. This paper focuses on the constitutive models of bolt steel and sphere steel used in China’s space structure construction. The elastoplastic model is determined by a standard tensile test and calibrated Voce saturated hardening rule. The ductile damage is found dominant based on the fractography analysis. Then Rice-Tracey ductile fracture rule is selected and the model parameters are calibrated based on tensile tests of notched specimens. These calibrated material models can benefit research or engineering work in similar fields.

Keywords: bolt-sphere joint, steel, constitutive model, ductile damage, model calibration

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Authors: Yogesh Bacchaw, Ashish Dabade

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Nowadays oral health is raising concern in society. Acid producing microorganisms changes the oral pH and creates a favorable environment for microbial growth. This growth not only promotes dental decay but also bad breath. Generally Recognized As Safe (GRAS) listed component was incorporated in chewing gum as an antimicrobial agent. The chewing gum produced exhibited up to 9 hours of antimicrobial activity against oral microflora. The toxicity of GRAS component per RACC value of chewing gum was negligible as compared to actual toxicity level of GRAS component. The antibacterial efficiency of chewing gum was tested by using total plate count (TPC) and colony forming unit (CFU). Nine hours were required to microflora to reach TPC/CFU of before chewing gum consumption. This chewing gum not only provides mouth freshening activity but also helps in lowering dental decay, bad breath, and enamel whitening.

Keywords: colony forming unit (CFU), chewing gum, generally recognized as safe (GRAS), microbial growth, microorganisms, oral health, RACC, total plate count (TPC), antimicrobial agent, enamel whitening, oral pH

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Authors: Avinoam Rabinovich

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CO₂ geological storage is a proven technology for reducing anthropogenic carbon emissions, which is paramount for achieving the ambitious net zero emissions goal. Core flooding experiments are an important step in any CO₂ storage project, allowing us to gain information on the flow of CO₂ and brine in the porous rock extracted from the reservoir. This information is important for understanding basic mechanisms related to CO₂ geological storage as well as for reservoir modeling, which is an integral part of a field project. In this work, a different method for constructing accurate models of CO₂-brine core flooding will be presented. Results for synthetic cases and real experiments will be shown and compared with numerical models to exhibit their predictive capabilities. Furthermore, the various mechanisms which impact the CO₂ distribution and trapping in the rock samples will be discussed, and examples from models and experiments will be provided. The new method entails solving an inverse problem to obtain a three-dimensional permeability distribution which, along with the relative permeability and capillary pressure functions, constitutes a model of the flow experiments. The model is more accurate when data from a number of experiments are combined to solve the inverse problem. This model can then be used to test various other injection flow rates and fluid fractions which have not been tested in experiments. The models can also be used to bridge the gap between small-scale capillary heterogeneity effects (sub-core and core scale) and large-scale (reservoir scale) effects, known as the upscaling problem.

Keywords: CO₂ geological storage, residual trapping, capillary heterogeneity, core flooding, CO₂-brine flow

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Authors: Dino Carpentras, Alejandro Dinkelberg, Michael Quayle

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Opinion dynamics models use an agent-based modeling approach to model people’s opinions. Model's properties are usually explored by testing the two 'degrees of freedom': the interaction rule and the network topology. The latter defines the connection, and thus the possible interaction, among agents. The interaction rule, instead, determines how agents select each other and update their own opinion. Here we show the existence of the third degree of freedom. This can be used for turning one model into each other or to change the model’s output up to 100% of its initial value. Opinion dynamics models represent the evolution of real-world opinions parsimoniously. Thus, it is fundamental to know how real-world opinion (e.g., supporting a candidate) could be turned into a number. Specifically, we want to know if, by choosing a different opinion-to-number transformation, the model’s dynamics would be preserved. This transformation is typically not addressed in opinion dynamics literature. However, it has already been studied in psychometrics, a branch of psychology. In this field, real-world opinions are converted into numbers using abstract objects called 'scales.' These scales can be converted one into the other, in the same way as we convert meters to feet. Thus, in our work, we analyze how this scale transformation may affect opinion dynamics models. We perform our analysis both using mathematical modeling and validating it via agent-based simulations. To distinguish between scale transformation and measurement error, we first analyze the case of perfect scales (i.e., no error or noise). Here we show that a scale transformation may change the model’s dynamics up to a qualitative level. Meaning that a researcher may reach a totally different conclusion, even using the same dataset just by slightly changing the way data are pre-processed. Indeed, we quantify that this effect may alter the model’s output by 100%. By using two models from the standard literature, we show that a scale transformation can transform one model into the other. This transformation is exact, and it holds for every result. Lastly, we also test the case of using real-world data (i.e., finite precision). We perform this test using a 7-points Likert scale, showing how even a small scale change may result in different predictions or a number of opinion clusters. Because of this, we think that scale transformation should be considered as a third-degree of freedom for opinion dynamics. Indeed, its properties have a strong impact both on theoretical models and for their application to real-world data.

Keywords: degrees of freedom, empirical validation, opinion scale, opinion dynamics

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Authors: Rostika Flora, Muhammad Zulkarnain, Syokumawena

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Background: Aerobic physical exercises are recommended to keep body fit and healthy although physical exercises themselves can increase body metabolism and oxygen and can lead into tissue hypoxia. Oxygen pressure can serve as Vascular Endhothelial Growth Factor (VEGF) regulator. Hypoxia increases gene expression of VEGF through ascendant regulation of HIF-1. VEGF is involved in regulating angiogenesis process. Aerobic physical exercises can increase the concentration of VEGF in brain and enables angiogenesis process. We have investigated the influence of aerobic physical exercise to the VGEF concentration of wistar rat’s brain. Methods: This was experimental study using post test only control group design. Independent t-test was used as statistical test. The samples were twenty four wistar rat (Rattus Norvegicus) which were divided into four groups: group P1 (control group), group P2 (treatment group with once-a-week exercise), group P3 (treatment group with three time-a-week exercise), and group P4 (treatment group with seven time-a-week exercise). Group P2, P3, and P4 were treated with treadmil with speed of 20 m/minute for 30 minutes. The concentration of VEGF was determined by ELISA. Results: There was a significant increase of VEGF in treatment group compared with control one (<0.05). The maximum increase was found in group P2 (129.02±64.49) and the minimum increase was in group P4 (96.98±11.20). Conclusion: The frequency of aerobic physical exercises influenced the concentration of Vascular Endhothelial Growth Factor (VEGF) of brain tissue of Rattus Norvegicus.

Keywords: brain tissue, hypoxia, physical exercises, vascular endhothelial growth factor

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Authors: David Lall, Vikram Vishal, P. G. Ranjith

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Numerical modeling of gas production from hydrate-bearing reservoirs requires the solution of various thermal, hydrological, chemical, and mechanical phenomena in a coupled manner. Among the various reservoir properties that influence gas production estimates, the distribution of permeability across the domain is one of the most crucial parameters since it determines both heat transfer and mass transfer. The aspect of permeability in hydrate-bearing reservoirs is particularly complex compared to conventional reservoirs since it depends on the saturation of gas hydrates and hence, is dynamic during production. The dependence of permeability on hydrate saturation is mathematically represented using permeability-reduction models, which are specific to the expected morphology of hydrate accumulations (such as grain-coating or pore-filling hydrates). In this study, we demonstrate the impact of various permeability-reduction models, and consequently, different morphologies of hydrate deposits on the estimates of gas production using depressurization at the reservoir scale. We observe significant differences in produced water volumes and cumulative mass of produced gas between the models, thereby highlighting the uncertainty in production behavior arising from the ambiguity in the prevalent gas hydrate morphology.

Keywords: gas hydrate morphology, multi-scale modeling, THMC, fluid flow in porous media

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Authors: Samuel Ahamefula

Abstract:

Turbulent motion is a highly nonlinear and complex phenomenon, and its modelling is still very challenging. In this study, we developed a hybrid computational approach to accurately simulate fluid turbulence phenomenon. The focus is coupling and transitioning between Direct Numerical Simulation (DNS) and Large Eddy Simulating Wall Models (LES-WM) regions. In the framework, high-order fidelity fluid dynamical methods are utilized to simulate the unsteady compressible Navier-Stokes equations in the Eulerian format on the unstructured moving grids. The coupling and transitioning of DNS and LES-WM are conducted through the linearly staggered Dirichlet-Neumann coupling scheme. The high-fidelity framework is verified and validated based on namely, DNS ability for capture full range of turbulent scales, giving accurate results and LES-WM efficiency in simulating near-wall turbulent boundary layer by using wall models.

Keywords: computational methods, turbulence modelling, turbulence entropy, navier-stokes equations

Procedia PDF Downloads 96