Search results for: tumor growth model
Commenced in January 2007
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Edition: International
Paper Count: 21873

Search results for: tumor growth model

21513 Governance and Economic Growth: Evidence for Ten Asian Countries

Authors: Chiung-Ju Huang

Abstract:

This study utilizes a frequency domain approach over the period of 1996 to 2013 to examine the causal relationship between governance and economic growth in ten Asian countries, which have different levels of democracy; classified as “Free”, “Partly Free”, and “Not Free” countries. The empirical results show that there is no Granger causality running from governance to economic growth in “Not Free” countries and “Partly Free” countries with the exception of Singapore. As for “Free” countries such as South Korea and Taiwan, there is a one-way causality running from governance to economic growth. The findings of this study indicate that policy makers in South Korea, Taiwan, and Singapore could use governance index to improve their predictions of the future economic growth.

Keywords: economic growth, frequency domain, governance, granger causality

Procedia PDF Downloads 334
21512 Effects of Temperature and the Use of Bacteriocins on Cross-Contamination from Animal Source Food Processing: A Mathematical Model

Authors: Benjamin Castillo, Luis Pastenes, Fernando Cerdova

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

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

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21511 Model Evaluation of Nanosecond, High-Intensity Electric Pulses Induced Cellular Apoptosis

Authors: Jiahui Song, Ravindra Joshi

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High-intensity, nanosecond, pulsed electric fields have been shown to be useful non-thermal tools capable of producing a variety of specific cellular responses. While reversible and temporary changes are often desired based on electromanipulation, irreversible effects can also be important objectives. These include elimination of tumor cells and bacterial decontamination. A simple model-based rate-equation treatment of the various cellular biochemical processes was used to qualitatively predict the pulse number-dependent caspase activation and cell survival trends. The model incorporated the caspase-8 associated extrinsic pathway, the delay inherent in its activation, cytochrome c release, and the internal feedback mechanism between caspase-3 and Bid. Results were roughly in keeping with the experimental cell-survival data. A pulse-number threshold was predicted followed by a near-exponential fall-off. The intrinsic pathway was shown to be much weaker as compared to the extrinsic mechanism for electric pulse induced cell apoptosis. Also, delays of about an hour are predicted for detectable molecular concentration increases following electrical pulsing.

Keywords: apoptosis, cell survival, model, pathway

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21510 Optimization of Feeder Bus Routes at Urban Rail Transit Stations Based on Link Growth Probability

Authors: Yu Song, Yuefei Jin

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Urban public transportation can be integrated when there is an efficient connection between urban rail lines, however, there are currently no effective or quick solutions being investigated for this connection. This paper analyzes the space-time distribution and travel demand of passenger connection travel based on taxi track data and data from the road network, excavates potential bus connection stations based on potential connection demand data, and introduces the link growth probability model in the complex network to solve the basic connection bus lines in order to ascertain the direction of the bus lines that are the most connected given the demand characteristics. Then, a tree view exhaustive approach based on constraints is suggested based on graph theory, which can hasten the convergence of findings while doing chain calculations. This study uses WEI QU NAN Station, the Xi'an Metro Line 2 terminal station in Shaanxi Province, as an illustration, to evaluate the model's and the solution method's efficacy. According to the findings, 153 prospective stations have been dug up in total, the feeder bus network for the entire line has been laid out, and the best route adjustment strategy has been found.

Keywords: feeder bus, route optimization, link growth probability, the graph theory

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21509 Dexamethasone Treatment Deregulates Proteoglycans Expression in Normal Brain Tissue

Authors: A. Y. Tsidulko, T. M. Pankova, E. V. Grigorieva

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High-grade gliomas are the most frequent and most aggressive brain tumors which are characterized by active invasion of tumor cells into the surrounding brain tissue, where the extracellular matrix (ECM) plays a crucial role. Disruption of ECM can be involved in anticancer drugs effectiveness, side-effects and also in tumor relapses. The anti-inflammatory agent dexamethasone is a common drug used during high-grade glioma treatment for alleviating cerebral edema. Although dexamethasone is widely used in the clinic, its effects on normal brain tissue ECM remain poorly investigated. It is known that proteoglycans (PGs) are a major component of the extracellular matrix in the central nervous system. In our work, we studied the effects of dexamethasone on the ECM proteoglycans (syndecan-1, glypican-1, perlecan, versican, brevican, NG2, decorin, biglican, lumican) using RT-PCR in the experimental animal model. It was shown that proteoglycans in rat brain have age-specific expression patterns. In early post-natal rat brain (8 days old rat pups) overall PGs expression was quite high and mainly expressed PGs were biglycan, decorin, and syndecan-1. The overall transcriptional activity of PGs in adult rat brain is 1.5-fold decreased compared to post-natal brain. The expression pattern was changed as well with biglycan, decorin, syndecan-1, glypican-1 and brevican becoming almost equally expressed. PGs expression patterns create a specific tissue microenvironment that differs in developing and adult brain. Dexamethasone regimen close to the one used in the clinic during high-grade glioma treatment significantly affects proteoglycans expression. It was shown that overall PGs transcription activity is 1.5-2-folds increased after dexamethasone treatment. The most up-regulated PGs were biglycan, decorin, and lumican. The PGs expression pattern in adult brain changed after treatment becoming quite close to the expression pattern in developing brain. It is known that microenvironment in developing tissues promotes cells proliferation while in adult tissues proliferation is usually suppressed. The changes occurring in the adult brain after dexamethasone treatment may lead to re-activation of cell proliferation due to signals from changed microenvironment. Taken together obtained data show that dexamethasone treatment significantly affects the normal brain ECM, creating the appropriate microenvironment for tumor cells proliferation and thus can reduce the effectiveness of anticancer treatment and promote tumor relapses. This work has been supported by a Russian Science Foundation (RSF Grant 16-15-10243)

Keywords: dexamthasone, extracellular matrix, glioma, proteoglycan

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21508 Kinetic Modelling of Fermented Probiotic Beverage from Enzymatically Extracted Annona Muricata Fruit

Authors: Calister Wingang Makebe, Wilson Ambindei Agwanande, Emmanuel Jong Nso, P. Nisha

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Traditional liquid-state fermentation processes of Annona muricata L. juice can result in fluctuating product quality and quantity due to difficulties in control and scale up. This work describes a laboratory-scale batch fermentation process to produce a probiotic Annona muricata L. enzymatically extracted juice, which was modeled using the Doehlert design with independent extraction factors being incubation time, temperature, and enzyme concentration. It aimed at a better understanding of the traditional process as an initial step for future optimization. Annona muricata L. juice was fermented with L. acidophilus (NCDC 291) (LA), L. casei (NCDC 17) (LC), and a blend of LA and LC (LCA) for 72 h at 37 °C. Experimental data were fitted into mathematical models (Monod, Logistic and Luedeking and Piret models) using MATLAB software, to describe biomass growth, sugar utilization, and organic acid production. The optimal fermentation time was obtained based on cell viability, which was 24 h for LC and 36 h for LA and LCA. The model was particularly effective in estimating biomass growth, reducing sugar consumption, and lactic acid production. The values of the determination coefficient, R2, were 0.9946, 0.9913 and 0.9946, while the residual sum of square error, SSE, was 0.2876, 0.1738 and 0.1589 for LC, LA and LCA, respectively. The growth kinetic parameters included the maximum specific growth rate, µm, which was 0.2876 h-1, 0.1738 h-1 and 0.1589 h-1 as well as the substrate saturation, Ks, with 9.0680 g/L, 9.9337 g/L and 9.0709 g/L respectively for LC, LA and LCA. For the stoichiometric parameters, the yield of biomass based on utilized substrate (YXS) was 50.7932, 3.3940 and 61.0202, and the yield of product based on utilized substrate (YPS) was 2.4524, 0.2307 and 0.7415 for LC, LA, and LCA, respectively. In addition, the maintenance energy parameter (ms) was 0.0128, 0.0001 and 0.0004 with respect to LC, LA and LCA. With the kinetic model proposed by Luedeking and Piret for lactic acid production rate, the growth associated, and non-growth associated coefficients were determined as 1.0028 and 0.0109, respectively. The model was demonstrated for batch growth of LA, LC, and LCA in Annona muricata L. juice. The present investigation validates the potential of Annona muricata L. based medium for heightened economical production of a probiotic medium.

Keywords: L. acidophilus, L. casei, fermentation, modelling, kinetics

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21507 Development of Polymer Nano-Particles as in vivo Imaging Agents for Photo-Acoustic Imaging

Authors: Hiroyuki Aoki

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Molecular imaging has attracted much attention to visualize a tumor site in a living body on the basis of biological functions. A fluorescence in vivo imaging technique has been widely employed as a useful modality for small animals in pre-clinical researches. However, it is difficult to observe a site deep inside a body because of a short penetration depth of light. A photo-acoustic effect is a generation of a sound wave following light absorption. Because the sound wave is less susceptible to the absorption of tissues, an in vivo imaging method based on the photoacoustic effect can observe deep inside a living body. The current study developed an in vivo imaging agent for a photoacoustic imaging method. Nano-particles of poly(lactic acid) including indocyanine dye were developed as bio-compatible imaging agent with strong light absorption. A tumor site inside a mouse body was successfully observed in a photo-acoustic image. A photo-acoustic imaging with polymer nano-particle agent would be a powerful method to visualize a tumor.

Keywords: nano-particle, photo-acoustic effect, polymer, dye, in vivo imaging

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21506 Comprehensive Analysis of RNA m5C Regulator ALYREF as a Suppressive Factor of Anti-tumor Immune and a Potential Tumor Prognostic Marker in Pan-Cancer

Authors: Yujie Yuan, Yiyang Fan, Hong Fan

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Objective: The RNA methylation recognition protein Aly/REF export factor (ALYREF) is considered one type of “reader” protein acting as a recognition protein of m5C, has been reported involved in several biological progresses including cancer initiation and progression. 5-methylcytosine (m5C) is a conserved and prevalent RNA modification in all species, as accumulating evidence suggests its role in the promotion of tumorigenesis. It has been claimed that ALYREF mediates nuclear export of mRNA with m5C modification and regulates biological effects of cancer cells. However, the systematical regulatory pathways of ALYREF in cancer tissues have not been clarified, yet. Methods: The expression level of ALYREF in pan-cancer and their normal tissues was compared through the data acquired from The Cancer Genome Atlas (TCGA). The University of Alabama at Birmingham Cancer data analysis Portal UALCAN was used to analyze the relationship between ALYREF and clinical pathological features. The relationship between the expression level of ALYREF and prognosis of pan-cancer, and the correlation genes of ALYREF were figured out by using Gene Expression Correlation Analysis database GEPIA. Immune related genes were obtained from TISIDB (an integrated repository portal for tumor-immune system interactions). Immune-related research was conducted by using Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) and TIMER. Results: Based on the data acquired from TCGA, ALYREF has an obviously higher-level expression in various types of cancers compared with relevant normal tissues excluding thyroid carcinoma and kidney chromophobe. The immunohistochemical images on The Human Protein Atlas showed that ALYREF can be detected in cytoplasm, membrane, but mainly located in nuclear. In addition, a higher expression level of ALYREF in tumor tissue generates a poor prognosis in majority of cancers. According to the above results, cancers with a higher expression level of ALYREF compared with normal tissues and a significant correlation between ALYREF and prognosis were selected for further analysis. By using TISIDB, we found that portion of ALYREF co-expression genes (such as BIRC5, H2AFZ, CCDC137, TK1, and PPM1G) with high Pearson correlation coefficient (PCC) were involved in anti-tumor immunity or affect resistance or sensitivity to T cell-mediated killing. Furthermore, based on the results acquired from GEPIA, there was significant correlation between ALYREF and PD-L1. It was exposed that there is a negative correlation between the expression level of ALYREF and ESTIMATE score. Conclusion: The present study indicated that ALYREF plays a vital and universal role in cancer initiation and progression of pan-cancer through regulating mitotic progression, DNA synthesis and metabolic process, and RNA processing. The correlation between ALYREF and PD-L1 implied ALYREF may affect the therapeutic effect of immunotherapy of tumor. More evidence revealed that ALYREF may play an important role in tumor immunomodulation. The correlation between ALYREF and immune cell infiltration level indicated that ALYREF can be a potential therapeutic target. Exploring the regulatory mechanism of ALYREF in tumor tissues may expose the reason for poor efficacy of immunotherapy and offer more directions of tumor treatment.

Keywords: ALYREF, pan-cancer, immunotherapy, PD-L1

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21505 Investigating a Deterrence Function for Work Trips for Perth Metropolitan Area

Authors: Ali Raouli, Amin Chegenizadeh, Hamid Nikraz

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The Perth metropolitan area and its surrounding regions have been expanding rapidly in recent decades and it is expected that this growth will continue in the years to come. With this rapid growth and the resulting increase in population, consideration should be given to strategic planning and modelling for the future expansion of Perth. The accurate estimation of projected traffic volumes has always been a major concern for the transport modelers and planners. Development of a reliable strategic transport model depends significantly on the inputs data into the model and the calibrated parameters of the model to reflect the existing situation. Trip distribution is the second step in four-step modelling (FSM) which is complex due to its behavioral nature. Gravity model is the most common method for trip distribution. The spatial separation between the Origin and Destination (OD) zones will be reflected in gravity model by applying deterrence functions which provide an opportunity to include people’s behavior in choosing their destinations based on distance, time and cost of their journeys. Deterrence functions play an important role for distribution of the trips within a study area and would simulate the trip distances and therefore should be calibrated for any particular strategic transport model to correctly reflect the trip behavior within the modelling area. This paper aims to review the most common deterrence functions and propose a calibrated deterrence function for work trips within the Perth Metropolitan Area based on the information obtained from the latest available Household data and Perth and Region Travel Survey (PARTS) data. As part of this study, a four-step transport model using EMME software has been developed for Perth Metropolitan Area to assist with the analysis and findings.

Keywords: deterrence function, four-step modelling, origin destination, transport model

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21504 Development and Investigation of Efficient Substrate Feeding and Dissolved Oxygen Control Algorithms for Scale-Up of Recombinant E. coli Cultivation Process

Authors: Vytautas Galvanauskas, Rimvydas Simutis, Donatas Levisauskas, Vykantas Grincas, Renaldas Urniezius

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The paper deals with model-based development and implementation of efficient control strategies for recombinant protein synthesis in fed-batch E.coli cultivation processes. Based on experimental data, a kinetic dynamic model for cultivation process was developed. This model was used to determine substrate feeding strategies during the cultivation. The proposed feeding strategy consists of two phases – biomass growth phase and recombinant protein production phase. In the first process phase, substrate-limited process is recommended when the specific growth rate of biomass is about 90-95% of its maximum value. This ensures reduction of glucose concentration in the medium, improves process repeatability, reduces the development of secondary metabolites and other unwanted by-products. The substrate limitation can be enhanced to satisfy restriction on maximum oxygen transfer rate in the bioreactor and to guarantee necessary dissolved carbon dioxide concentration in culture media. In the recombinant protein production phase, the level of substrate limitation and specific growth rate are selected within the range to enable optimal target protein synthesis rate. To account for complex process dynamics, to efficiently exploit the oxygen transfer capability of the bioreactor, and to maintain the required dissolved oxygen concentration, adaptive control algorithms for dissolved oxygen control have been proposed. The developed model-based control strategies are useful in scale-up of cultivation processes and accelerate implementation of innovative biotechnological processes for industrial applications.

Keywords: adaptive algorithms, model-based control, recombinant E. coli, scale-up of bioprocesses

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21503 Determinants of Economic Growth in Pakistan: A Structural Vector Auto Regression Approach

Authors: Muhammad Ajmair

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This empirical study followed structural vector auto regression (SVAR) approach proposed by the so-called AB-model of Amisano and Giannini (1997) to check the impact of relevant macroeconomic determinants on economic growth in Pakistan. Before that auto regressive distributive lag (ARDL) bound testing technique and time varying parametric approach along with general to specific approach was employed to find out relevant significant determinants of economic growth. To our best knowledge, no author made such a study that employed auto regressive distributive lag (ARDL) bound testing and time varying parametric approach with general to specific approach in empirical literature, but current study will bridge this gap. Annual data was taken from World Development Indicators (2014) during period 1976-2014. The widely-used Schwarz information criterion and Akaike information criterion were considered for the lag length in each estimated equation. Main findings of the study are that remittances received, gross national expenditures and inflation are found to be the best relevant positive and significant determinants of economic growth. Based on these empirical findings, we conclude that government should focus on overall economic growth augmenting factors while formulating any policy relevant to the concerned sector.

Keywords: economic growth, gross national expenditures, inflation, remittances

Procedia PDF Downloads 172
21502 A Multi-Release Software Reliability Growth Models Incorporating Imperfect Debugging and Change-Point under the Simulated Testing Environment and Software Release Time

Authors: Sujit Kumar Pradhan, Anil Kumar, Vijay Kumar

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The testing process of the software during the software development time is a crucial step as it makes the software more efficient and dependable. To estimate software’s reliability through the mean value function, many software reliability growth models (SRGMs) were developed under the assumption that operating and testing environments are the same. Practically, it is not true because when the software works in a natural field environment, the reliability of the software differs. This article discussed an SRGM comprising change-point and imperfect debugging in a simulated testing environment. Later on, we extended it in a multi-release direction. Initially, the software was released to the market with few features. According to the market’s demand, the software company upgraded the current version by adding new features as time passed. Therefore, we have proposed a generalized multi-release SRGM where change-point and imperfect debugging concepts have been addressed in a simulated testing environment. The failure-increasing rate concept has been adopted to determine the change point for each software release. Based on nine goodness-of-fit criteria, the proposed model is validated on two real datasets. The results demonstrate that the proposed model fits the datasets better. We have also discussed the optimal release time of the software through a cost model by assuming that the testing and debugging costs are time-dependent.

Keywords: software reliability growth models, non-homogeneous Poisson process, multi-release software, mean value function, change-point, environmental factors

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21501 Creating Growth and Reducing Inequality in Developing Countries

Authors: Rob Waddle

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We study an economy with weak justice and security systems and with weak public policy and regulation or little capacity to implement them, and with high barriers to profitable sectors. We look at growth and development opportunities based on the derived demand. We show that there is hope for such an economy to grow up and to generate a win-win situation for all stakeholders if the derived demand is supplied. We then investigate conditions that could stimulate the derived demand supply. We show that little knowledge of public, private and international expenditures in the economy and academic tools are enough to trigger the derived demand supply. Our model can serve as guidance to donor and NGO working in developing countries, and show to media the best way to help is to share information about existing and accessible opportunities. It can also provide direction to vocational schools and universities that could focus more on providing tools to seize existing opportunities.

Keywords: growth, development, monopoly, oligopoly, inequality

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21500 Corruption, Institutional Quality and Economic Growth in Nigeria

Authors: Ogunlana Olarewaju Fatai, Kelani Fatai Adeshina

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The interplay of corruption and institutional quality determines how effective and efficient an economy progresses. An efficient institutional quality is a key requirement for economic stability. Institutional quality in most cases has been used interchangeably with Governance and these have given room for proxies that legitimized Governance as measures for institutional quality. A poorly-tailored institutional quality has a penalizing effect on corruption and economic growth, while defective institutional quality breeds corruption. Corruption is a hydra-headed phenomenon as it manifests in different forms. The most celebrated definition of corruption is given as “the use or abuse of public office for private benefits or gains”. It also denotes an arrangement between two mutual parties in the determination and allocation of state resources for pecuniary benefits to circumvent state efficiency. This study employed Barro (1990) type augmented model to analyze the nexus among corruption, institutional quality and economic growth in Nigeria using annual time series data, which spanned the period 1996-2019. Within the analytical framework of Johansen Cointegration technique, Error Correction Mechanism (ECM) and Granger Causality tests, findings revealed a long-run relationship between economic growth, corruption and selected measures of institutional quality. The long run results suggested that all the measures of institutional quality except voice & accountability and regulatory quality are positively disposed to economic growth. Moreover, the short-run estimation indicated a reconciliation of the divergent views on corruption which pointed at “sand the wheel” and “grease the wheel” of growth. In addition, regulatory quality and the rule of law indicated a negative influence on economic growth in Nigeria. Government effectiveness and voice & accountability, however, indicated a positive influence on economic growth. The Granger causality test results suggested a one-way causality between GDP and Corruption and also between corruption and institutional quality. Policy implications from this study pointed at checking corruption and streamlining institutional quality framework for better and sustained economic development.

Keywords: institutional quality, corruption, economic growth, public policy

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21499 Bayesian Estimation of Hierarchical Models for Genotypic Differentiation of Arabidopsis thaliana

Authors: Gautier Viaud, Paul-Henry Cournède

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Plant growth models have been used extensively for the prediction of the phenotypic performance of plants. However, they remain most often calibrated for a given genotype and therefore do not take into account genotype by environment interactions. One way of achieving such an objective is to consider Bayesian hierarchical models. Three levels can be identified in such models: The first level describes how a given growth model describes the phenotype of the plant as a function of individual parameters, the second level describes how these individual parameters are distributed within a plant population, the third level corresponds to the attribution of priors on population parameters. Thanks to the Bayesian framework, choosing appropriate priors for the population parameters permits to derive analytical expressions for the full conditional distributions of these population parameters. As plant growth models are of a nonlinear nature, individual parameters cannot be sampled explicitly, and a Metropolis step must be performed. This allows for the use of a hybrid Gibbs--Metropolis sampler. A generic approach was devised for the implementation of both general state space models and estimation algorithms within a programming platform. It was designed using the Julia language, which combines an elegant syntax, metaprogramming capabilities and exhibits high efficiency. Results were obtained for Arabidopsis thaliana on both simulated and real data. An organ-scale Greenlab model for the latter is thus presented, where the surface areas of each individual leaf can be simulated. It is assumed that the error made on the measurement of leaf areas is proportional to the leaf area itself; multiplicative normal noises for the observations are therefore used. Real data were obtained via image analysis of zenithal images of Arabidopsis thaliana over a period of 21 days using a two-step segmentation and tracking algorithm which notably takes advantage of the Arabidopsis thaliana phyllotaxy. Since the model formulation is rather flexible, there is no need that the data for a single individual be available at all times, nor that the times at which data is available be the same for all the different individuals. This allows to discard data from image analysis when it is not considered reliable enough, thereby providing low-biased data in large quantity for leaf areas. The proposed model precisely reproduces the dynamics of Arabidopsis thaliana’s growth while accounting for the variability between genotypes. In addition to the estimation of the population parameters, the level of variability is an interesting indicator of the genotypic stability of model parameters. A promising perspective is to test whether some of the latter should be considered as fixed effects.

Keywords: bayesian, genotypic differentiation, hierarchical models, plant growth models

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21498 Monetary Policy and Economic Growth in West African Business Cycles: Markov Switching Approach

Authors: Omolade Adeleke, Jonathan Olusegun Famoroti

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This study empirically examined the monetary policy and economic growth in the classical cycles in 8 member countries of the West African Economic and Monetary Union (WAEMU), using the Markov switching model for the Two-phase Regime, covering the period 1980Q1 to 2020Q4. Our estimates suggest that these countries demonstrate to have similar business cycles, and the economies stay more in an expansion regime than a recession regime. The result further shows that the union has an average duration period of 3.1 and 15.9 quarters for contraction and expansion periods, respectively. The business cycle duration, on average, suggests 19 quarters, varying from country to country. Therefore, the formulation of policies that can enhance aggregate demand by member countries in the union is an antidote for recession and is necessary to drive the economy into equilibrium. Also, a low-interest rate and reduced inflation rate would ginger long-run economic growth.

Keywords: monetary policy, business cycle, economic growth, Markov switching

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21497 The Sustainable Blue Economy Innovation and Growth: Data Based on China for 2006-2015 Years

Authors: Mingbao Chen

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The blue economy is a new comprehensive marine economy integrated with resources, industries, and regions, and is an upgraded version of the marine economy. The blue economy attaches great importance to the coordinated development of the ecological environment and the economy, which is an emerging economic form advocated by all countries in the world. This paper constructs the model including four variables:natural capital, economic capital, intellectual capital, cultural capital. Theoretically, this paper deduces the function mechanism of variables on economic growth, and empirically calculates the driving force and influence of the blue economy on the national economy by using data of China's 2006-2015 year. The results show that natural capital and economic capital remain the main factors of blue growth in the blue economy. And with the development of economic society and technological progress, the role of intellectual capital and cultural capital is bigger and bigger. Therefore, promoting the development of marine science and technology and culture is the focus of the future blue economic development.

Keywords: blue growth, natural capital, intellectual capital, cultural capital

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21496 A Rapid Prototyping Tool for Suspended Biofilm Growth Media

Authors: Erifyli Tsagkari, Stephanie Connelly, Zhaowei Liu, Andrew McBride, William Sloan

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Biofilms play an essential role in treating water in biofiltration systems. The biofilm morphology and function are inextricably linked to the hydrodynamics of flow through a filter, and yet engineers rarely explicitly engineer this interaction. We develop a system that links computer simulation and 3-D printing to optimize and rapidly prototype filter media to optimize biofilm function with the hypothesis that biofilm function is intimately linked to the flow passing through the filter. A computational model that numerically solves the incompressible time-dependent Navier Stokes equations coupled to a model for biofilm growth and function is developed. The model is imbedded in an optimization algorithm that allows the model domain to adapt until criteria on biofilm functioning are met. This is applied to optimize the shape of filter media in a simple flow channel to promote biofilm formation. The computer code links directly to a 3-D printer, and this allows us to prototype the design rapidly. Its validity is tested in flow visualization experiments and by microscopy. As proof of concept, the code was constrained to explore a small range of potential filter media, where the medium acts as an obstacle in the flow that sheds a von Karman vortex street that was found to enhance the deposition of bacteria on surfaces downstream. The flow visualization and microscopy in the 3-D printed realization of the flow channel validated the predictions of the model and hence its potential as a design tool. Overall, it is shown that the combination of our computational model and the 3-D printing can be effectively used as a design tool to prototype filter media to optimize biofilm formation.

Keywords: biofilm, biofilter, computational model, von karman vortices, 3-D printing.

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21495 Analysis of the Impacts of Capital Goods' Import and Human Capital on the Economic Growth of the Sub Sahahra Africa: A Panel-ARDL Approach

Authors: Adeleke Omolade

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The study investigated the impacts of capital goods' import and human capital on the economic growth of the Sub Sahahra Africa (SSA). 30 countries were used in the Panel- ARDL analysis where economic growth is the dependent variables and capital goods' import, human capital, primary export, investment exchange rate, among others were used as the independent variables. The result from the panel analysis indicates that capital goods' import will significantly and positively influence economic growth but human capital fails to have significant positive impact on economic growth of the SSA. Earlier the trend analysis and the correlation results have shown that there is a weak association between capital goods' import and human capital in the SSA. The results offer an expository analysis that reveals that the quality of the human capital is very germane to the effective utilization of capital goods' import for the purpose of growth in a primary goods' export dominated region like the SSA.

Keywords: capital goods import, economic growth, human capital, Sub-Sahara Africa

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21494 Effect of Enterprise Digital Transformation on Enterprise Growth: Theoretical Logic and Chinese Experience

Authors: Bin Li

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In the era of the digital economy, digital transformation has gradually become a strategic choice for enterprise development, but there is a relative lack of systematic research from the perspective of enterprise growth. Based on the sample of Chinese A-share listed companies from 2011 to 2021, this paper constructs A digital transformation index system and an enterprise growth composite index to empirically test the impact of enterprise digital transformation on enterprise growth and its mechanism. The results show that digital transformation can significantly promote corporate growth. The mechanism analysis finds that reducing operating costs, optimizing human capital structure, promoting R&D output and improving digital innovation capability play an important intermediary role in the process of digital transformation promoting corporate growth. At the same time, the level of external digital infrastructure and the strength of organizational resilience play a positive moderating role in the process of corporate digital transformation promoting corporate growth. In addition, while further analyzing the heterogeneity of enterprises, this paper further deepens the analysis of the driving factors and digital technology support of digital transformation, as well as the three dimensions of enterprise growth, thus deepening the research depth of enterprise digital transformation.

Keywords: digital transformation, enterprise growth, digital technology, digital infrastructure, organization resilience, digital innovation

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21493 Tracheal Stenting to Relieve Respiratory Distress in Patient with Advanced Esophageal Malignancy and Its Anaesthetic Management

Authors: Aarti Agarwal, Ajmal Khan

Abstract:

Background and Objective: Breathing difficulty is most distressing symptom for the patient and their caregivers providing palliative care to individuals with advanced malignancy. It needs to be tackled effectively and sometimes preemptively to provide relief from respiratory obstruction. Interventional procedures like tracheal stenting are becoming increasingly popular as a part of palliation for respiratory symptoms. We present a case of esophageal tumor earlier stented by Gastroenterologist to maintain esophageal patency, but the tumor outgrew to produce tracheal infiltration and thereby causing airway obstruction. Method and Result: 62-year-old man presented with unresectable Carcinoma oesophagus with inability to swallow. A metallic stent was placed by the gastroenterologist, to maintain esophageal patency and enable patient to swallow. Two months later, the patient returned to hospital in emergency with respiratory distress. CT neck and thorax revealed tumor infiltration through posterior tracheal wall. Lower extent of the tumor was till 1 cm above the carina. Airway stenting with Tracheo bronchial stent with Y configuration was planned under general anaesthesia with airway blocks. Superior Laryngeal Nerve Block, Glossopharyngeal block and Trans tracheal infiltration of local anaesthetics were performed. The patient was sedated with Fentanyl, Midazolam and propofol infusion but was breathing spontaneously. Once the rigid bronchoscope was placed inside trachea, breathing was supported with oxygen and sevoflurane. Initially, the trachea was cleared of tumor by coring. After creating space, tracheal stent was positioned and deployed. After stent placement patient was awakened, suctioned and nebulized. His respiratory stridor relieved instantaneously and was shifted to recovery. Conclusion: Airway blocks help in decreasing the incidence and severity of coughing during airway instrumentation thereby help in proper stent placement. They also reduce the requirement of general anaesthetics and hasten the post stenting recovery. Airway stent provided immediate relief to patient from symptoms of respiratory difficulty. Decision for early tracheal stenting may be taken for a select group of patients with high propensity for local spread, thereby avoiding respiratory complications and providing better quality of life in patients with inoperable malignancy.

Keywords: tracheal stent, respiratory difficulty, esophageal tumor, anaesthetic management

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21492 Construction of Ovarian Cancer-on-Chip Model by 3D Bioprinting and Microfluidic Techniques

Authors: Zakaria Baka, Halima Alem

Abstract:

Cancer is a major worldwide health problem that has caused around ten million deaths in 2020. In addition, efforts to develop new anti-cancer drugs still face a high failure rate. This is partly due to the lack of preclinical models that recapitulate in-vivo drug responses. Indeed conventional cell culture approach (known as 2D cell culture) is far from reproducing the complex, dynamic and three-dimensional environment of tumors. To set up more in-vivo-like cancer models, 3D bioprinting seems to be a promising technology due to its ability to achieve 3D scaffolds containing different cell types with controlled distribution and precise architecture. Moreover, the introduction of microfluidic technology makes it possible to simulate in-vivo dynamic conditions through the so-called “cancer-on-chip” platforms. Whereas several cancer types have been modeled through the cancer-on-chip approach, such as lung cancer and breast cancer, only a few works describing ovarian cancer models have been described. The aim of this work is to combine 3D bioprinting and microfluidic technics with setting up a 3D dynamic model of ovarian cancer. In the first phase, alginate-gelatin hydrogel containing SKOV3 cells was used to achieve tumor-like structures through an extrusion-based bioprinter. The desired form of the tumor-like mass was first designed on 3D CAD software. The hydrogel composition was then optimized for ensuring good and reproducible printability. Cell viability in the bioprinted structures was assessed using Live/Dead assay and WST1 assay. In the second phase, these bioprinted structures will be included in a microfluidic device that allows simultaneous testing of different drug concentrations. This microfluidic dispositive was first designed through computational fluid dynamics (CFD) simulations for fixing its precise dimensions. It was then be manufactured through a molding method based on a 3D printed template. To confirm the results of CFD simulations, doxorubicin (DOX) solutions were perfused through the dispositive and DOX concentration in each culture chamber was determined. Once completely characterized, this model will be used to assess the efficacy of anti-cancer nanoparticles developed in the Jean Lamour institute.

Keywords: 3D bioprinting, ovarian cancer, cancer-on-chip models, microfluidic techniques

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21491 Modeling of the Fermentation Process of Enzymatically Extracted Annona muricata L. Juice

Authors: Calister Wingang Makebe, Wilson Agwanande Ambindei, Zangue Steve Carly Desobgo, Abraham Billu, Emmanuel Jong Nso, P. Nisha

Abstract:

Traditional liquid-state fermentation processes of Annona muricata L. juice can result in fluctuating product quality and quantity due to difficulties in control and scale up. This work describes a laboratory-scale batch fermentation process to produce a probiotic Annona muricata L. enzymatically extracted juice, which was modeled using the Doehlert design with independent extraction factors being incubation time, temperature, and enzyme concentration. It aimed at a better understanding of the traditional process as an initial step for future optimization. Annona muricata L. juice was fermented with L. acidophilus (NCDC 291) (LA), L. casei (NCDC 17) (LC), and a blend of LA and LC (LCA) for 72 h at 37 °C. Experimental data were fitted into mathematical models (Monod, Logistic and Luedeking and Piret models) using MATLAB software, to describe biomass growth, sugar utilization, and organic acid production. The optimal fermentation time was obtained based on cell viability, which was 24 h for LC and 36 h for LA and LCA. The model was particularly effective in estimating biomass growth, reducing sugar consumption, and lactic acid production. The values of the determination coefficient, R2, were 0.9946, 0.9913 and 0.9946, while the residual sum of square error, SSE, was 0.2876, 0.1738 and 0.1589 for LC, LA and LCA, respectively. The growth kinetic parameters included the maximum specific growth rate, µm, which was 0.2876 h-1, 0.1738 h-1 and 0.1589 h-1, as well as the substrate saturation, Ks, with 9.0680 g/L, 9.9337 g/L and 9.0709 g/L respectively for LC, LA and LCA. For the stoichiometric parameters, the yield of biomass based on utilized substrate (YXS) was 50.7932, 3.3940 and 61.0202, and the yield of product based on utilized substrate (YPS) was 2.4524, 0.2307 and 0.7415 for LC, LA, and LCA, respectively. In addition, the maintenance energy parameter (ms) was 0.0128, 0.0001 and 0.0004 with respect to LC, LA and LCA. With the kinetic model proposed by Luedeking and Piret for lactic acid production rate, the growth associated and non-growth associated coefficients were determined as 1.0028 and 0.0109, respectively. The model was demonstrated for batch growth of LA, LC, and LCA in Annona muricata L. juice. The present investigation validates the potential of Annona muricata L. based medium for heightened economical production of a probiotic medium.

Keywords: L. acidophilus, L. casei, fermentation, modelling, kinetics

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21490 Site-Specific Delivery of Hybrid Upconversion Nanoparticles for Photo-Activated Multimodal Therapies of Glioblastoma

Authors: Yuan-Chung Tsai, Masao Kamimura, Kohei Soga, Hsin-Cheng Chiu

Abstract:

In order to enhance the photodynamic/photothermal therapeutic efficacy on glioblastoma, the functionized upconversion nanoparticles with the capability of converting the deep tissue penetrating near-infrared light into visible wavelength for activating photochemical reaction were developed. The drug-loaded nanoparticles (NPs) were obtained from the self-assembly of oleic acid-coated upconversion nanoparticles along with maleimide-conjugated poly(ethylene glycol)-cholesterol (Mal-PEG-Chol), as the NP stabilizer, and hydrophobic photosensitizers, IR-780 (for photothermal therapy, PTT) and mTHPC (for photodynamic therapy, PDT), in aqueous phase. Both the IR-780 and mTHPC were loaded into the hydrophobic domains within NPs via hydrophobic association. The peptide targeting ligand, angiopep-2, was further conjugated with the maleimide groups at the end of PEG adducts on the NP surfaces, enabling the affinity coupling with the low-density lipoprotein receptor-related protein-1 of tumor endothelial cells and malignant astrocytes. The drug-loaded NPs with the size of ca 80 nm in diameter exhibit a good colloidal stability in physiological conditions. The in vitro data demonstrate the successful targeting delivery of drug-loaded NPs toward the ALTS1C1 cells (murine astrocytoma cells) and the pronounced cytotoxicity elicited by combinational effect of PDT and PTT. The in vivo results show the promising brain orthotopic tumor targeting of drug-loaded NPs and sound efficacy for brain tumor dual-modality treatment. This work shows great potential for improving photodynamic/photothermal therapeutic efficacy of brain cancer.

Keywords: drug delivery, orthotopic brain tumor, photodynamic/photothermal therapies, upconversion nanoparticles

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21489 Software Assessment Using Ant Colony Optimization Algorithm

Authors: Saad M. Darwish

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Recently, software quality issues have come to be seen as important subject as we see an enormous growth of agencies involved in software industries. However,these agencies cannot guarantee the quality of their products, thus leaving users in uncertainties. Software certification is the extension of quality by means that quality needs to be measured prior to certification granting process. This research participates in solving the problem of software assessment by proposing a model for assessment and certification of software product that uses a fuzzy inference engine to integrate both of process–driven and application-driven quality assurance strategies. The key idea of the on hand model is to improve the compactness and the interpretability of the model’s fuzzy rules via employing an ant colony optimization algorithm (ACO), which tries to find good rules description by dint of compound rules initially expressed with traditional single rules. The model has been tested by case study and the results have demonstrated feasibility and practicability of the model in a real environment.

Keywords: optimization technique, quality assurance, software certification model, software assessment

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21488 The Extent of Land Use Externalities in the Fringe of Jakarta Metropolitan: An Application of Spatial Panel Dynamic Land Value Model

Authors: Rahma Fitriani, Eni Sumarminingsih, Suci Astutik

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In a fast growing region, conversion of agricultural lands which are surrounded by some new development sites will occur sooner than expected. This phenomenon has been experienced by many regions in Indonesia, especially the fringe of Jakarta (BoDeTaBek). Being Indonesia’s capital city, rapid conversion of land in this area is an unavoidable process. The land conversion expands spatially into the fringe regions, which were initially dominated by agricultural land or conservation sites. Without proper control or growth management, this activity will invite greater costs than benefits. The current land use is the use which maximizes its value. In order to maintain land for agricultural activity or conservation, some efforts are needed to keep the land value of this activity as high as possible. In this case, the knowledge regarding the functional relationship between land value and its driving forces is necessary. In a fast growing region, development externalities are the assumed dominant driving force. Land value is the product of the past decision of its use leading to its value. It is also affected by the local characteristics and the observed surrounded land use (externalities) from the previous period. The effect of each factor on land value has dynamic and spatial virtues; an empirical spatial dynamic land value model will be more useful to capture them. The model will be useful to test and to estimate the extent of land use externalities on land value in the short run as well as in the long run. It serves as a basis to formulate an effective urban growth management’s policy. This study will apply the model to the case of land value in the fringe of Jakarta Metropolitan. The model will be used further to predict the effect of externalities on land value, in the form of prediction map. For the case of Jakarta’s fringe, there is some evidence about the significance of neighborhood urban activity – negative externalities, the previous land value and local accessibility on land value. The effects are accumulated dynamically over years, but they will fully affect the land value after six years.

Keywords: growth management, land use externalities, land value, spatial panel dynamic

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21487 Role of Finance in Firm Innovation and Growth: Evidence from African Countries

Authors: Gebrehiwot H., Giorgis Bahita

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Firms in Africa experience less financial market in comparison to other emerging and developed countries, thus lagging behind the rest of the world in terms of innovation and growth. Though there are different factors to be considered, underdeveloped financial systems take the lion's share in hindering firm innovation and growth in Africa. Insufficient capacity to innovate is one of the problems facing African businesses. Moreover, a critical challenge faced by firms in Africa is access to finance and the inability of financially constrained firms to grow. Only little is known about how different sources of finance affect firm innovation and growth in Africa, specifically the formal and informal finance effect on firm innovation and growth. This study's aim is to address this gap by using formal and informal finance for working capital and fixed capital and its role in firm innovation and firm growth using firm-level data from the World Bank enterprise survey 2006-2019 with a total of 5661 sample firms from 14 countries based on available data on the selected variables. Additionally, this study examines factors for accessing credit from a formal financial institution. The logit model is used to examine the effect of finance on a firm’s innovation and factors to access formal finance, while the Ordinary List Square (OLS) regression mode is used to investigate the effect of finance on firm growth. 2SLS instrumental variables are used to address the possible endogeneity problem in firm growth and finance-innovation relationships. A result from the logistic regression indicates that both formal and informal finance used for working capital and investment in fixed capital was found to have a significant positive association with product and process innovation. In the case of finance and growth, finding show that positive association of both formal and informal financing to working capital and new investment in fixed capital though the informal has positive relations to firm growth as measured by sale growth but no significant association as measured by employment growth. Formal finance shows more magnitude of effect on innovation and growth when firms use formal finance to finance investment in fixed capital, while informal finance show less compared to formal finance and this confirms previous studies as informal is mainly used for working capital in underdeveloped economies like Africa. The factors that determine credit access: Age, firm size, managerial experience, exporting, gender, and foreign ownership are found to have significant determinant factors in accessing credit from formal and informal sources among the selected sample countries.

Keywords: formal finance, informal finance, innovation, growth

Procedia PDF Downloads 50
21486 Overexpression of CAS8 Enhances Necroptosis and Metastasis in Iranian Sporadic Colorectal Cancer

Authors: Sayed Ali Garossi, Azar Heidarizadi, Shahla Mohammad Ganji

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Context: Colorectal cancer is the second type of cancer-related mortality globally. Expression of cas8 (caspase 8) is closely connected to growth and metastasis of colorectal cancer.Cas8/Rip1 plays a vital role in the apoptosis pathway and resistance to chemotherapy. The aim of the present study is to investigate the pattern of gene expression in colorectal cancer and compare the differences using Real-Time PCR to find a potential biomarker candidate for colorectal cancer. Methodology: This study conducted real-time PCR to evaluate gene expression of Cas8 in colorectal cancer patients. The gene-specific primer sequences exon–exon junction was designed by OLIGO7 software for the expression of the gene under investigation. Forty-six patient samples without any chemotherapy were selected, including tumoral tissue and adjacent normal tissue samples. The age of the patients was 50 and the size of the tumors was 5.5 cm. The categories were before and after age 50. Findings: Here, we found that Caspase 8 was overexpressed in CRC tissues compared to corresponding adjacent colon tissues (Cas8: 5.2 vs. 1 ratio); high expression of Cas8 was associated with poor overall survival and independent risk factors for the prognosis of CRC patients. Conclusion: In conclusion, our study pioneered the reporting of high Casp8 expression as a predictor of poor prognosis and chemical resistance in CRC patients.Cas8 overexpression suppressed Cas 8 / Rip1-dependent apoptosis and activated the proliferation of tumor cells by activating necroptosis. The necroptosis pathway has also emerged as a new approach to anti-tumor in cancer treatment.

Keywords: Cas8, necroptosis, apoptosis, Real-Time PCR

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21485 Predicting of Hydrate Deposition in Loading and Offloading Flowlines of Marine CNG Systems

Authors: Esam I. Jassim

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The main aim of this paper is to demonstrate the prediction of the model capability of predicting the nucleation process, the growth rate, and the deposition potential of second phase particles in gas flowlines. The primary objective of the research is to predict the risk hazards involved in the marine transportation of compressed natural gas. However, the proposed model can be equally used for other applications including production and transportation of natural gas in any high-pressure flow-line. The proposed model employs the following three main components to approach the problem: computational fluid dynamics (CFD) technique is used to configure the flow field; the nucleation model is developed and incorporated in the simulation to predict the incipient hydrate particles size and growth rate; and the deposition of the gas/particle flow is proposed using the concept of the particle deposition velocity. These components are integrated in a comprehended model to locate the hydrate deposition in natural gas flowlines. The present research is prepared to foresee the deposition location of solid particles that could occur in a real application in Compressed Natural Gas loading and offloading. A pipeline with 120 m length and different sizes carried a natural gas is taken in the study. The location of particle deposition formed as a result of restriction is determined based on the procedure mentioned earlier and the effect of water content and downstream pressure is studied. The critical flow speed that prevents such particle to accumulate in the certain pipe length is also addressed.

Keywords: hydrate deposition, compressed natural gas, marine transportation, oceanography

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21484 Analysis of Population and Growth Rate Methanotof Bateria as Reducers Methane Gases Emission in Rice Field

Authors: Maimuna Nontji

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The life cycle of rice plant has three phases of growth; they are the vegetative, reproductive and maturation phase. They greatly affect the life of dynamics metanotrof bacterial as reducer methane emissions in the rice field, both of population and on the rate of growth. The aim of this study was to analyze the population and growth rate of methanotrof isolates which has been isolated in previous studies. Isolates were taken at all the life cycle of rice plant. Population of analysis was conducted by standard plate count method and growth rate was analysed by logarithmic calculation. The results showed that each isolate varied in population and growth rate. The highest population was obtained in the isolates Gowa Methanotrof Reproductive (GMR 8) about 7.06 x 10 11 cfu / ml on 3 days of incubation and the lowest population was obtained in the Gowa Methanotrof Maturation (GMP 5) about 0.27 x 10 11 cfu / ml on 7 day of incubation. Some isolate were demonstrated in long growth rate about 5 days of incubation and another are 3 days.

Keywords: emission, methanotrof, methane, population

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