Search results for: growth dynamics
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9043

Search results for: growth dynamics

8743 Inverse Dynamics of the Mould Base of Blow Molding Machines

Authors: Vigen Arakelian

Abstract:

This paper deals with the study of devices for displacement of the mould base of blow-molding machines. The displacement of the mould in the studied case is carried out by a linear actuator, which ensures the descent of the mould base and by extension springs, which return the letter in the initial position. The aim of this paper is to study the inverse dynamics of the device for displacement of the mould base of blow-molding machines and to determine its optimum parameters for higher rate of production. In the other words, it is necessary to solve the inverse dynamic problem to find the equation of motion linking applied forces with displacements. This makes it possible to determine the stiffness coefficient of the spring to turn the mold base back to the initial position for a given time. The obtained results are illustrated by a numerical example. It is shown that applying a spring with stiffness returns the mould base of the blow molding machine into the initial position in 0.1 sec.

Keywords: design, mechanisms, dynamics, blow-molding machines

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8742 AI Predictive Modeling of Excited State Dynamics in OPV Materials

Authors: Pranav Gunhal., Krish Jhurani

Abstract:

This study tackles the significant computational challenge of predicting excited state dynamics in organic photovoltaic (OPV) materials—a pivotal factor in the performance of solar energy solutions. Time-dependent density functional theory (TDDFT), though effective, is computationally prohibitive for larger and more complex molecules. As a solution, the research explores the application of transformer neural networks, a type of artificial intelligence (AI) model known for its superior performance in natural language processing, to predict excited state dynamics in OPV materials. The methodology involves a two-fold process. First, the transformer model is trained on an extensive dataset comprising over 10,000 TDDFT calculations of excited state dynamics from a diverse set of OPV materials. Each training example includes a molecular structure and the corresponding TDDFT-calculated excited state lifetimes and key electronic transitions. Second, the trained model is tested on a separate set of molecules, and its predictions are rigorously compared to independent TDDFT calculations. The results indicate a remarkable degree of predictive accuracy. Specifically, for a test set of 1,000 OPV materials, the transformer model predicted excited state lifetimes with a mean absolute error of 0.15 picoseconds, a negligible deviation from TDDFT-calculated values. The model also correctly identified key electronic transitions contributing to the excited state dynamics in 92% of the test cases, signifying a substantial concordance with the results obtained via conventional quantum chemistry calculations. The practical integration of the transformer model with existing quantum chemistry software was also realized, demonstrating its potential as a powerful tool in the arsenal of materials scientists and chemists. The implementation of this AI model is estimated to reduce the computational cost of predicting excited state dynamics by two orders of magnitude compared to conventional TDDFT calculations. The successful utilization of transformer neural networks to accurately predict excited state dynamics provides an efficient computational pathway for the accelerated discovery and design of new OPV materials, potentially catalyzing advancements in the realm of sustainable energy solutions.

Keywords: transformer neural networks, organic photovoltaic materials, excited state dynamics, time-dependent density functional theory, predictive modeling

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8741 Investigation and Analysis of Vortex-Induced Vibrations in Sliding Gate Valves Using Computational Fluid Dynamics

Authors: Kianoosh Ahadi, Mustafa Ergil

Abstract:

In this study, the event of vibrations caused by vortexes and the distribution of induced hydrodynamic forces due to vortexes on the sliding gate valves has been investigated. For this reason, a sliding valve with the help of computational fluid dynamics (CFD) software was simulated in two-dimensional )2D(, where the flow and turbulence equations were solved for three different valve openings (full, half, and 16.7 %) models. The variety of vortexes formed within the vicinity of the valve structure was investigated based on time where the trend of fluctuations and their occurrence regions have been detected. From the gathered solution dataset of the numerical simulations, the pressure coefficient (CP), the lift force coefficient (CL), the drag force coefficient (CD), and the momentum coefficient due to hydrodynamic forces (CM) were examined, and relevant figures were generated were from these results, the vortex-induced vibrations were analyzed.

Keywords: induced vibrations, computational fluid dynamics, sliding gate valves, vortexes

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8740 The Appropriate Patent System to Promote Economic Growth in Afghanistan

Authors: Mohammad Reza Fooladi

Abstract:

The patent system which fits with industrial and economic situation in the country, by strengthening research and development, technology transfer and increasing foreign investment can provide economic and industrial growth of the countries. However, the extent and manner of support should be commensurate with the country's conditions and comply with significant rules to have a positive effect on research and development, technology transfer and the amount of foreign investment. The present article tries to while reviewing the state of effectiveness of the patent system on economic growth, to illustrate the characteristics of the patent system fits Afghanistan and according to this matter provide the necessary recommendations about the improvement of laws and regulations related to the patent in Afghanistan.

Keywords: patent, economic growth, technology transfer, Afghanistan

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8739 A Transfer Function Representation of Thermo-Acoustic Dynamics for Combustors

Authors: Myunggon Yoon, Jung-Ho Moon

Abstract:

In this paper, we present a transfer function representation of a general one-dimensional combustor. The input of the transfer function is a heat rate perturbation of a burner and the output is a flow velocity perturbation at the burner. This paper considers a general combustor model composed of multiple cans with different cross sectional areas, along with a non-zero flow rate.

Keywords: combustor, dynamics, thermoacoustics, transfer function

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8738 The Influence of Substrate and Temperature on the Growth of Phytophthora palmivora of Cocoa Black Pod Disease

Authors: Suhaida Salleh, Tee Yei Kheng

Abstract:

Black pod is the most commonly destructive disease of cacao (Theobroma cacao) which cause major losses to global production of cocoa beans. The genus of Phytophthora is the important pathogen of this disease worldwide. The species of P. megakarya causes black pod disease in West Africa, whereas P. capsici and P. citrophthora cause the incident in Central and South America. In Malaysia, this disease is caused by P. palmivora which infect all stages of pod development including flower cushion, cherelle, immature and mature pods. This pathogen destroys up to 10% of trees yearly through stem cankers and causes 20 to 30% pod damages through black pod rot. Since P. palmivora has a high impact on cocoa yield, it is crucial to identify some of the abiotic factors that can constrain their growth. In an effort to evaluate the effect of different substrates and temperatures to the growth of P. palmivora, a laboratory study was done under a different range of temperatures. Different substrate for the growth of P. palmivora were used which are corn meal agar (CMA) media and detached pod of cocoa. An agar plug of seven days old of P. palmivora growth was transferred on both substrates and incubated at 24, 27, 30, 33 and 36ᵒC, respectively. The diameter of lesion on pod and the cultural growth of pathogen was recorded for 7 consecutive days. The optimum incubation temperature of P. palmivora on both substrates is at 27ᵒC. However, the growth tends to be inhibited as the temperature increases. No lesion developed on pod surface incubated at 36ᵒC and only a small lesion observed at 33ᵒC. The sporulation with the formation of white mycelial growth on pod surface was only visible at optimum temperature, 27ᵒC. On CMA, the pathogen grew over the entire range of temperatures tested. The study is, therefore, concluded that P. palmivora grow the best at temperature of 27ᵒC on both substrates and their growth begin to inhibit when the temperature rises to more than 27ᵒC. The growth pattern of this pathogen is similar on both pod surface and cultural media.

Keywords: cocoa, Phytophthora palmivora, substrate, temperature

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8737 Release Response of Black Spruce and White Spruce Following Overstory Lodgepole Pine Mortality Due to Mountain Pine Beetle Attack

Authors: F. O. Oboite, P. G. Comeau

Abstract:

Advance regeneration is present in many lodgepole pine stands in Alberta. When the overstory pine canopy is killed by Mountain Pine Beetle (MPB) the growth of this advance is likely to increase. Understanding the growth response of these understory tree species is needed to improve mid-term timber supply projections and management decisions. To quantify the growth (diameter, height, height/diameter ratio) responses of black spruce and white spruce to lodgepole pine mortality, sample trees of black and white spruce advance regeneration were selected from 7 lodgepole pine dominated stands (5 attacked; 2 control) in the Foothills Region of western Alberta. Measurements were collected 7-8 years after MPB attack across a wide range of spruce height and stand densities. Analysis was done using mixed model linear regression. Result indicates that there was an increase in both diameter and height growth after MPB attack; however, this increase in growth was delayed for about four years. Both spruce species had similar height response and their height/diameter ratio decreased after release, partly as a result of increased understory light associated with loss of needles in the pine canopy. In addition, the diameter and height growth responses of both spruce species were strongly related to density, prerelease growth and initial size.

Keywords: mountain pine beetle, forest regeneration, lodgepole pine, growth response

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8736 Lattice Dynamics of (ND4Br)x(KBr)1-x Mixed Crystals

Authors: Alpana Tiwari, N. K. Gaur

Abstract:

We have incorporated the translational rotational (TR) coupling effects in the framework of three body force shell model (TSM) to develop an extended TSM (ETSM). The dynamical matrix of ETSM has been applied to compute the phonon frequencies of orientationally disordered mixed crystal (ND4Br)x(KBr)1-x in (q00), (qq0) and (qqq) symmetry directions for compositions 0.10≤x≤0.50 at T=300K.These frequencies are plotted as a function of wave vector k. An unusual acoustic mode softening is found along symmetry directions (q00) and (qq0) as a result of translation-rotation coupling.

Keywords: orientational glass, phonons, TR-coupling, lattice dynamics

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8735 Energy Consumption, Population and Economic Development Dynamics in Nigeria: An Empirical Evidence

Authors: Evelyn Nwamaka Ogbeide-Osaretin, Bright Orhewere

Abstract:

This study examined the role of the population in the linkage between energy consumption and economic development in Nigeria. Time series data on energy consumption, population, and economic development were used for the period 1995 to 2020. The Autoregressive Distributed Lag -Error Correction Model (ARDL-ECM) was engaged. Economic development had a negative substantial impact on energy consumption in the long run. Population growth had a positive significant effect on energy consumption. Government expenditure was also found to impact the level of energy consumption, while energy consumption is not a function of oil price in Nigeria.

Keywords: dynamic analysis, energy consumption, population, economic development, Nigeria

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8734 The Importance of Absorptive Capacities in the Foreign Direct Investment-Growth Nexus: Evidence from Sub-Saharan Africa

Authors: Edmund Kwablah, Anthony Amoah

Abstract:

The merits associated with Foreign Direct Investment (FDI) inflows to host countries in Sub-Saharan Africa cannot be overemphasized. Against this background, countries have sought to design and implement strategic policies geared towards enhacing FDI and promoting economic growth. In this study, we used the Fully Modified Ordinary Least Squares technique and a panel data for Sub-Saharan African (SSA) countries spanning from 1998 to 2016. We hypothesize that FDI’s effect on economic growth is contingent on some absorptive capacities (e.g., financial market development and economic freedom) of the host country. We used financial market data that accounts for market fragility as a measure of financial market development and economic freedom data which uses the overall score of all the freedom indicators as a measure of economic freedom. Our results suggest that FDI has a statistically positive effect on economic growth when we account for host country’s absorptive capacities. However, a negative relationship will ensue if these absorptive capacities are not accounted for. We recommend that a developing continent like SSA should focus on identifying and building the relevant absorptive capacities that can translate the effect of FDI into a positive growth. This is because an economy with sound absorptive capacities reduces business risk and spur economic growth.

Keywords: FDI, absorptive capacity, economic growth, FMOLS, Fully Modified Ordinary Least Squares, SSA

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8733 Examining the Relational Approach Elements in City Development Strategy of Qazvin 2031

Authors: Majid Etaati, Hamid Majedi

Abstract:

Relational planning approach proposed by Patsy Healey goes beyond the physical proximity and emphasizes social proximity. This approach stresses the importance of nodes and flows between nodes. Current plans in European cities have incrementally incorporated this approach, but urban plans in Iran have still stayed very detailed and rigid. In response to the weak evaluation results of the comprehensive planning approach in Qazvin, the local authorities applied the City Development Strategy (CDS) to cope with new urban challenges. The paper begins with an explanation of relational planning and suggests that Healey gives urban planners about spatial strategies and then it surveys relational factors in CDS of Qazvin. This study analyzes the extent which CDS of Qazvin have highlighted nodes, flows, and dynamics. In the end, the study concludes that there is a relational understanding of urban dynamics in the plan, but it is weak.

Keywords: relational, dynamics, city development strategy, urban planning, Qazvin

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8732 Oncogenic Role of MicroRNA-346 in Human Non-Small Cell Lung Cancer by Regulation of XPC/ERK/Snail/E-Cadherin Pathway

Authors: Cheng-Cao Sun, Shu-Jun Li, De-Jia Li

Abstract:

Determinants of growth and metastasis in cancer remain of great interest to define. MicroRNAs (miRNAs) have frequently emerged as tumor metastatic regulator by acting on multiple signaling pathways. Here, we report the definition of miR-346 as an oncogenic microRNA that facilitates non-small cell lung cancer (NSCLC) cell growth and metastasis. XPC, an important DNA damage recognition factor in nucleotide excision repair was defined as a target for down-regulation by miR-346, functioning through direct interaction with the 3'-UTR of XPC mRNA. Blocking miR-346 by an antagomiR was sufficient to inhibit NSCLC cell growth and metastasis, an effect that could be phenol-copied by RNAi-mediated silencing of XPC. In vivo studies established that miR-346 overexpression was sufficient to promote tumor growth by A549 cells in xenografts mice, relative to control cells. Overall, our results defined miR-346 as an oncogenic miRNA in NSCLC, the levels of which contributed to tumor growth and invasive aggressiveness.

Keywords: microRNA-346, miR-346, XPC, non-small cell lung cancer, oncogenesis

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8731 Building an Opinion Dynamics Model from Experimental Data

Authors: Dino Carpentras, Paul J. Maher, Caoimhe O'Reilly, Michael Quayle

Abstract:

Opinion dynamics is a sub-field of agent-based modeling that focuses on people’s opinions and their evolutions over time. Despite the rapid increase in the number of publications in this field, it is still not clear how to apply these models to real-world scenarios. Indeed, there is no agreement on how people update their opinion while interacting. Furthermore, it is not clear if different topics will show the same dynamics (e.g., more polarized topics may behave differently). These problems are mostly due to the lack of experimental validation of the models. Some previous studies started bridging this gap in the literature by directly measuring people’s opinions before and after the interaction. However, these experiments force people to express their opinion as a number instead of using natural language (and then, eventually, encoding it as numbers). This is not the way people normally interact, and it may strongly alter the measured dynamics. Another limitation of these studies is that they usually average all the topics together, without checking if different topics may show different dynamics. In our work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions in natural language (“agree” or “disagree”). We also measured the certainty of their answer, expressed as a number between 1 and 10. However, this value was not shown to other participants to keep the interaction based on natural language. We then showed the opinion (and not the certainty) of another participant and, after a distraction task, we repeated the measurement. To make the data compatible with opinion dynamics models, we multiplied opinion and certainty to obtain a new parameter (here called “continuous opinion”) ranging from -10 to +10 (using agree=1 and disagree=-1). We firstly checked the 5 topics individually, finding that all of them behaved in a similar way despite having different initial opinions distributions. This suggested that the same model could be applied for different unpolarized topics. We also observed that people tend to maintain similar levels of certainty, even when they changed their opinion. This is a strong violation of what is suggested from common models, where people starting at, for example, +8, will first move towards 0 instead of directly jumping to -8. We also observed social influence, meaning that people exposed with “agree” were more likely to move to higher levels of continuous opinion, while people exposed with “disagree” were more likely to move to lower levels. However, we also observed that the effect of influence was smaller than the effect of random fluctuations. Also, this configuration is different from standard models, where noise, when present, is usually much smaller than the effect of social influence. Starting from this, we built an opinion dynamics model that explains more than 80% of data variance. This model was also able to show the natural conversion of polarization from unpolarized states. This experimental approach offers a new way to build models grounded on experimental data. Furthermore, the model offers new insight into the fundamental terms of opinion dynamics models.

Keywords: experimental validation, micro-dynamics rule, opinion dynamics, update rule

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8730 Stock Market Development and the Growth of Nigerian Economy

Authors: Godwin Chigozie Okpara, Eugene Iheanacho

Abstract:

This paper examined the dynamic behavior of stock market development and the growth of Nigerian economy. The variables; market capitalization ratio, turnover ratio and liquidity proxies by the ratio of market capitalization to gross domestic product were sourced and computed from the Nigerian stock exchange fact books and the CBN statistical bulletin of the Central Bank of Nigeria. The variables were tested and found stationary and cointregrated using the augumented Dickey Fuller unit root test and the Johnson cointegration test respectively. The dynamic behavior of the stock market development model was verified using the error correction model. The result shows that about 0.4l percent of the short run deviation is corrected every year and also reveals that market capitalization ratio and market liquidity are positive and significant function of economic growth. In other words market capitalization ratio and liquidity positively and significantly impact economic growth. Market development variables such as turnover ratio and market restriction can exert positive but insignificant impact on the growth of the economy suggesting that securities transaction relative to the size of the securities market are not high enough to significantly engender economic growth in Nigeria. In the light of this, the researchers recommend that the regulatory body as well as the government, should provide a conducive environment capable of encouraging the growth and development of the stock market. This if well articulated will enhance the market turnover and the growth of the economy.

Keywords: market capitalization ratio, turnover ratio, liquidity, unit root test, cointegration

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8729 Regional Dynamics of Innovation and Entrepreneurship in the Optics and Photonics Industry

Authors: Mustafa İlhan Akbaş, Özlem Garibay, Ivan Garibay

Abstract:

The economic entities in innovation ecosystems form various industry clusters, in which they compete and cooperate to survive and grow. Within a successful and stable industry cluster, the entities acquire different roles that complement each other in the system. The universities and research centers have been accepted to have a critical role in these systems for the creation and development of innovations. However, the real effect of research institutions on regional economic growth is difficult to assess. In this paper, we present our approach for the identification of the impact of research activities on the regional entrepreneurship for a specific high-tech industry: optics and photonics. The optics and photonics has been defined as an enabling industry, which combines the high-tech photonics technology with the developing optics industry. The recent literature suggests that the growth of optics and photonics firms depends on three important factors: the embedded regional specializations in the labor market, the research and development infrastructure, and a dynamic small firm network capable of absorbing new technologies, products and processes. Therefore, the role of each factor and the dynamics among them must be understood to identify the requirements of the entrepreneurship activities in optics and photonics industry. There are three main contributions of our approach. The recent studies show that the innovation in optics and photonics industry is mostly located around metropolitan areas. There are also studies mentioning the importance of research center locations and universities in the regional development of optics and photonics industry. These studies are mostly limited with the number of patents received within a short period of time or some limited survey results. Therefore the first contribution of our approach is conducting a comprehensive analysis for the state and recent history of the photonics and optics research in the US. For this purpose, both the research centers specialized in optics and photonics and the related research groups in various departments of institutions (e.g. Electrical Engineering, Materials Science) are identified and a geographical study of their locations is presented. The second contribution of the paper is the analysis of regional entrepreneurship activities in optics and photonics in recent years. We use the membership data of the International Society for Optics and Photonics (SPIE) and the regional photonics clusters to identify the optics and photonics companies in the US. Then the profiles and activities of these companies are gathered by extracting and integrating the related data from the National Establishment Time Series (NETS) database, ES-202 database and the data sets from the regional photonics clusters. The number of start-ups, their employee numbers and sales are some examples of the extracted data for the industry. Our third contribution is the utilization of collected data to investigate the impact of research institutions on the regional optics and photonics industry growth and entrepreneurship. In this analysis, the regional and periodical conditions of the overall market are taken into consideration while discovering and quantifying the statistical correlations.

Keywords: entrepreneurship, industrial clusters, optics, photonics, emerging industries, research centers

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8728 Biaxial Buckling of Single Layer Graphene Sheet Based on Nonlocal Plate Model and Molecular Dynamics Simulation

Authors: R. Pilafkan, M. Kaffash Irzarahimi, S. F. Asbaghian Namin

Abstract:

The biaxial buckling behavior of single-layered graphene sheets (SLGSs) is studied in the present work. To consider the size-effects in the analysis, Eringen’s nonlocal elasticity equations are incorporated into classical plate theory (CLPT). A Generalized Differential Quadrature Method (GDQM) approach is utilized and numerical solutions for the critical buckling loads are obtained. Then, molecular dynamics (MD) simulations are performed for a series of zigzag SLGSs with different side-lengths and with various boundary conditions, the results of which are matched with those obtained by the nonlocal plate model to numerical the appropriate values of nonlocal parameter relevant to each type of boundary conditions.

Keywords: biaxial buckling, single-layered graphene sheets, nonlocal elasticity, molecular dynamics simulation, classical plate theory

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8727 The Effect of Degraded Shock Absorbers on the Safety-Critical Stationary and Non-Stationary Lateral Dynamics of Passenger Cars

Authors: Tobias Schramm, Günther Prokop

Abstract:

The average age of passenger cars is rising steadily around the world. Older vehicles are more sensitive to the degradation of chassis components. A higher age and a higher mileage of passenger cars correlate with an increased failure rate of vehicle shock absorbers. The most common degradation mechanism of vehicle shock absorbers is the loss of oil and gas. It is not yet fully understood how the loss of oil and gas in twin-tube shock absorbers affects the lateral dynamics of passenger cars. The aim of this work is to estimate the effect of degraded twin-tube shock absorbers of passenger cars on their safety-critical lateral dynamics. A characteristic curve-based five-mass full vehicle model and a semi-physical phenomenological shock absorber model were set up, parameterized and validated. The shock absorber model is able to reproduce the damping characteristics of vehicle twin-tube shock absorbers with oil and gas loss for various excitations. The full vehicle model was used to simulate stationary cornering and steering wheel angle step maneuvers on road classes A to D. The simulations were carried out in a realistic parameter space in order to demonstrate the influence of various vehicle characteristics on the effect of degraded shock absorbers. As a result, it was shown that degraded shock absorbers have a negative effect on the understeer gradient of vehicles. For stationary lateral dynamics, degraded shock absorbers for high road excitations reduce the maximum lateral accelerations. Degraded rear axle shock absorbers can change the understeer gradient of a vehicle in the direction of oversteer. Degraded shock absorbers also lead to increased rolling angles. Furthermore, degraded shock absorbers have a major impact on driving stability during steering wheel angle steps. Degraded rear axle shock absorbers, in particular, can lead to unstable handling. Especially the tire stiffness, the unsprung mass and the stabilizer stiffness influence the effect of degraded shock absorbers on the lateral dynamics of passenger cars.

Keywords: driving dynamics, numerical simulation, road safety, shock absorber degradation, stationary and nonstationary lateral dynamics.

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8726 Assessment of the Effect of Cu and Zn on the Growth of Two Chlorophytic Microalgae

Authors: Medina O. Kadiri, John E. Gabriel

Abstract:

Heavy metals are metallic elements with a relatively high density, at least five times greater compared to water. The sources of heavy metal pollution in the environment include industrial, medical, agricultural, pharmaceutical, domestic effluents, and atmospheric sources, mining, foundries, smelting, and any heavy metal-based operation. Although some heavy metals in trace quantities are required for biological metabolism, their higher concentrations elicit toxicities. Others are distinctly toxic and are of no biological functions. Microalgae are the primary producers of aquatic ecosystems and, therefore, the foundation of the aquatic food chain. A study investigating the effects of copper and zinc on the two chlorophytes-Chlorella vulgaris and Dictyosphaerium pulchellum was done in the laboratory, under different concentrations of 0mg/l, 2mg/l, 4mg/l, 6mg/l, 8mg/l, 10mg/l, and 20mg/l. The growth of the test microalgae was determined every two days for 14 days. The results showed that the effects of the test heavy metals were concentration-dependent. From the two microalgae species tested, Chlorella vulgaris showed appreciable growth up to 8mg/l concentration of zinc. Dictyoshphaerium pulchellum had only minimal growth at different copper concentrations except for 2mg/l, which seemed to have relatively higher growth. The growth of the control was remarkably higher than in other concentrations. Generally, the growth of both test algae was consistently inhibited by heavy metals. Comparatively, copper generally inhibited the growth of both algae than zinc. Chlorella vulgaris can be used for bioremediation of high concentrations of zinc. The potential of many microalgae in heavy metal bioremediation can be explored.

Keywords: heavy metals, green algae, microalgae, pollution

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8725 Adding a Degree of Freedom to Opinion Dynamics Models

Authors: Dino Carpentras, Alejandro Dinkelberg, Michael Quayle

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Within agent-based modeling, opinion dynamics is the field that focuses on modeling people's opinions. In this prolific field, most of the literature is dedicated to the exploration of the two 'degrees of freedom' and how they impact the model’s properties (e.g., the average final opinion, the number of final clusters, etc.). These degrees of freedom are (1) the interaction rule, which determines how agents update their own opinion, and (2) the network topology, which defines the possible interaction among agents. In this work, we show that the third degree of freedom exists. This can be used to change a model's output up to 100% of its initial value or to transform two models (both from the literature) into each other. Since opinion dynamics models are representations of the real world, it is fundamental to understand how people’s opinions can be measured. Even for abstract models (i.e., not intended for the fitting of real-world data), it is important to understand if the way of numerically representing opinions is unique; and, if this is not the case, how the model dynamics would change by using different representations. The process of measuring opinions is non-trivial as it requires transforming real-world opinion (e.g., supporting most of the liberal ideals) to a number. Such a process is usually not discussed in opinion dynamics literature, but it has been intensively studied in a subfield of psychology called psychometrics. In psychometrics, opinion scales can be converted into each other, similarly to how meters can be converted to feet. Indeed, psychometrics routinely uses both linear and non-linear transformations of opinion scales. Here, we analyze how this transformation affects opinion dynamics models. We analyze this effect by using mathematical modeling and then validating our analysis with agent-based simulations. Firstly, we study the case of perfect scales. In this way, we show that scale transformations affect the model’s dynamics up to a qualitative level. This means that if two researchers use the same opinion dynamics model and even the same dataset, they could make totally different predictions just because they followed different renormalization processes. A similar situation appears if two different scales are used to measure opinions even on the same population. This effect may be as strong as providing an uncertainty of 100% on the simulation’s output (i.e., all results are possible). Still, by using perfect scales, we show that scales transformations can be used to perfectly transform one model to another. We test this using two models from the standard literature. Finally, we test the effect of scale transformation in the case of finite precision using a 7-points Likert scale. In this way, we show how a relatively small-scale transformation introduces both changes at the qualitative level (i.e., the most shared opinion at the end of the simulation) and in the number of opinion clusters. Thus, scale transformation appears to be a third degree of freedom of opinion dynamics models. This result deeply impacts both theoretical research on models' properties and on the application of models on real-world data.

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

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8724 Growth and Biochemical Composition of Tetraselmis sp. and Chlorella sp. under Varied Growth Conditions

Authors: M. Alsull

Abstract:

In this study, Tetraselmis sp. and Chlorella sp. isolated from Penang National Park coastal waters, Malaysia, and cultivated under combined various laboratory conditions (temperature, light and nitrogen limitation and starvation). Growth rate, dry weight, chlorophyll a content, total lipids content and total carbohydrates content were estimated at mid-exponential growth phase. Tetraselmis sp. and Chlorella sp. showed remarkably decrease in growth rate, chlorophyll a content and dry weight when maintained under nitrogen limitation and starvation conditions, as well as when grown under 12:12 h light, dark regime conditions. Chlorella sp. showed ability to counter the fluctuation in temperature with no significant effects on the measured parameters; in contrast, Tetraselmis sp. showed a decrease in growth rate, chlorophyll a content and dry weight when grown under 15±1˚C temperature. Cultures maintained under nitrogen full concentration, and 24 h light regime showed decrease in total lipids content, compared with 12:12 h light, dark cycle regime, in the two tested species.

Keywords: microalgae, biochemical composition, temperature, light, nitrogen limitation

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8723 A Crop Growth Subroutine for Watershed Resources Management (WRM) Model

Authors: Kingsley Nnaemeka Ogbu, Constantine Mbajiorgu

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Vegetation has a marked effect on runoff and has become an important component in hydrologic model. The watershed Resources Management (WRM) model, a process-based, continuous, distributed parameter simulation model developed for hydrologic and soil erosion studies at the watershed scale lack a crop growth component. As such, this model assumes a constant parameter values for vegetation and hydraulic parameters throughout the duration of hydrologic simulation. Our approach is to develop a crop growth algorithm based on the original plant growth model used in the Environmental Policy Integrated Climate Model (EPIC) model. This paper describes the development of a single crop growth model which has the capability of simulating all crops using unique parameter values for each crop. Simulated crop growth processes will reflect the vegetative seasonality of the natural watershed system. An existing model was employed for evaluating vegetative resistance by hydraulic and vegetative parameters incorporated into the WRM model. The improved WRM model will have the ability to evaluate the seasonal variation of the vegetative roughness coefficient with depth of flow and further enhance the hydrologic model’s capability for accurate hydrologic studies

Keywords: crop yield, roughness coefficient, PAR, WRM model

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8722 Fracture and Fatigue Crack Growth Analysis and Modeling

Authors: Volkmar Nolting

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Fatigue crack growth prediction has become an important topic in both engineering and non-destructive evaluation. Crack propagation is influenced by the mechanical properties of the material and is conveniently modelled by the Paris-Erdogan equation. The critical crack size and the total number of load cycles are calculated. From a Larson-Miller plot the maximum operational temperature can for a given stress level be determined so that failure does not occur within a given time interval t. The study is used to determine a reasonable inspection cycle and thus enhances operational safety and reduces costs.

Keywords: fracturemechanics, crack growth prediction, lifetime of a component, structural health monitoring

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8721 Effect of Fiscal Policy on Growth in India

Authors: Parma Chakravartti

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The impact of government spending and taxation on economic growth has remained a central issue of fiscal policy analysis. There is a wide range of opinions over the strength of fiscal policy’s effect on macroeconomic variables. It can be argued that the impact of fiscal policy depends on the structure and economic condition of the economy. This study makes an attempt to examine the effect of fiscal policy shocks on growth in India using the structural vector autoregressive model (SVAR), considering data from 1950 to 2019. The study finds that government spending is an important instrument of growth in India, where the share of revenue expenditure to capital expenditure plays a key role. The optimum composition of total expenditure is important for growth and it is not necessarily true that capital expenditure multiplier is more than revenue expenditure multiplier. The study also finds that the impact of public economic activities on private economic activities for both consumption expenditure and gross capital formation of government crowds in private consumption expenditure and private gross capital formation, respectively, thus indicating that government expenditure complements private expenditure in India.

Keywords: government spending, fiscal policy, multiplier, growth

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8720 Foreign Direct Investment on Economic Growth by Industries in Central and Eastern European Countries

Authors: Shorena Pharjiani

Abstract:

The Present empirical paper investigates the relationship between FDI and economic growth by 10 selected industries in 10 Central and Eastern European countries from the period 1995 to 2012. Different estimation approaches were used to explore the connection between FDI and economic growth, for example OLS, RE, FE with and without time dummies. Obtained empirical results leads to some main consequences: First, the Central and East European countries (CEEC) attracted foreign direct investment, which raised the productivity of industries they entered in. It should be concluded that the linkage between FDI and output growth by industries is positive and significant enough to suggest that foreign firm’s participation enhanced the productivity of the industries they occupied. There had been an endogeneity problem in the regression and fixed effects estimation approach was used which partially corrected the regression analysis in order to make the results less biased. Second, it should be stressed that the results show that time has an important role in making FDI operational for enhancing output growth by industries via total factor productivity. Third, R&D positively affected economic growth and at the same time, it should take some time for research and development to influence economic growth. Fourth, the general trends masked crucial differences at the country level: over the last 20 years, the analysis of the tables and figures at the country level show that the main recipients of FDI of the 11 Central and Eastern European countries were Hungary, Poland and the Czech Republic. The main reason was that these countries had more open door policies for attracting the FDI. Fifth, according to the graphical analysis, while Hungary had the highest FDI inflow in this region, it was not reflected in the GDP growth as much as in other Central and Eastern European countries.

Keywords: central and East European countries (CEEC), economic growth, FDI, panel data

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8719 A Neural Network Approach to Understanding Turbulent Jet Formations

Authors: Nurul Bin Ibrahim

Abstract:

Advancements in neural networks have offered valuable insights into Fluid Dynamics, notably in addressing turbulence-related challenges. In this research, we introduce multiple applications of models of neural networks, namely Feed-Forward and Recurrent Neural Networks, to explore the relationship between jet formations and stratified turbulence within stochastically excited Boussinesq systems. Using machine learning tools like TensorFlow and PyTorch, the study has created models that effectively mimic and show the underlying features of the complex patterns of jet formation and stratified turbulence. These models do more than just help us understand these patterns; they also offer a faster way to solve problems in stochastic systems, improving upon traditional numerical techniques to solve stochastic differential equations such as the Euler-Maruyama method. In addition, the research includes a thorough comparison with the Statistical State Dynamics (SSD) approach, which is a well-established method for studying chaotic systems. This comparison helps evaluate how well neural networks can help us understand the complex relationship between jet formations and stratified turbulence. The results of this study underscore the potential of neural networks in computational physics and fluid dynamics, opening up new possibilities for more efficient and accurate simulations in these fields.

Keywords: neural networks, machine learning, computational fluid dynamics, stochastic systems, simulation, stratified turbulence

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8718 Genetic Analysis of Growth Traits in White Boni Sheep under the Central Highlands Region of Yemen

Authors: Abed Al-Bial, S. Alazazie, A. Shami

Abstract:

The data were collected from 1992 to 2009 of White Boni sheep maintained at the Regional Research Station in the Central Highlands of Yemen. Data were analyzed to study the growth related traits and their genetic control. The least square means for body weights were 2.26±0.67, 11.14±0.46 and 19.21±1.25 kg for birth weight (BW), weaning weight (WW), six-month weight (WM6), respectively. The pre- and post-weaning average daily weight gains (ADG1 and ADG2) were 106.04±4.98g and 46.21±8.36 g/ day. Significant differences associated with the year of lambing were observed in body weight and weight gain at different stages of growth. Males were heavier and had a higher weight gain than females at almost all stages of growth and differences tended to increase with age. Single-born lambs had a distinct advantage over those born in twin births at all stages of growth. The lambs in the dam’s second to fourth parities were generally of heavier weight and higher daily weight gain than those in other parities. The heritabilities of all body weights, weight gains at different stages of growth were moderate (0.11-0.43). The phenotypic and genetic correlation among the different body weights were positive and high. The genetic correlations of the pre- and post-weaning average daily gains with body weights were hight to moderate, except BW with ADG2.

Keywords: breed, genetics, growth traits, heritability, sheep

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8717 Growth Performance and Critical Supersaturation of Heterogeneous Condensation for High Concentration of Insoluble Sub-Micron Particles

Authors: Jie Yin, Jun Zhang

Abstract:

Measuring the growth performance and critical supersaturation of particle group have a high reference value for constructing a supersaturated water vapor environment that can improve the removal efficiency of the high-concentration particle group. The critical supersaturation and the variation of the growth performance with supersaturation for high-concentration particles were measured by a flow cloud chamber. Findings suggest that the influence of particle concentration on the growth performance will reduce with the increase of supersaturation. Reducing residence time and increasing particle concentration have similar effects on the growth performance of the high-concentration particle group. Increasing particle concentration and shortening residence time will increase the critical supersaturation of the particle group. The critical supersaturation required to activate a high-concentration particle group is lower than that of the single-particle when the minimum particle size in the particle group is the same as that of a single particle.

Keywords: sub-micron particles, heterogeneous condensation, critical supersaturation, nucleation

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8716 Competition, Stability, and Economic Growth: A Causality Approach

Authors: Mahvish Anwaar

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Research Question: In this paper, we explore the causal relationship between banking competition, banking stability, and economic growth. Research Findings: The unbalanced panel data starting from 2000 to 2018 is collected to analyze the causality among banking competition, banking stability, and economic growth. The main focus of the study is to check the direction of causality among selected variables. The results of the study support the demand following, supply leading, feedback, and neutrality hypothesis conditional to different measures of banking competition, banking stability, and economic growth. Theoretical Implication: Jayakumar, Pradhan, Dash, Maradana, and Gaurav (2018) proposed a theoretical model of the causal relationship between banking competition, banking stability, and economic growth by using different indicators. So, we empirically test the proposed indicators in our study. This study makes a contribution to the literature by showing the defined relationship between developing and developed countries. Policy Implications: The study covers various policy implications regarding investors to analyze how to properly manage their finances, and government agencies will take help from the present study to find the best and most suitable policies by examining how the economy can grow concerning its finances.

Keywords: competition, stability, economic growth, vector auto-regression, granger causality

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8715 Surface Sensing of Atomic Behavior of Polymer Nanofilms via Molecular Dynamics Simulation

Authors: Ling Dai

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Surface-sensing devices such as atomic force microscope have been widely used to characterize the surface structure and properties of nanoscale polymer films. However, using molecular dynamics simulations, we show that there is intrinsic and unavoidable inelastic deformation at polymer surfaces induced by the sensing tip. For linear chain polymers like perfluoropolyether, such tip-induced deformation derives from the differences in the atomic interactions which are atomic specie-based Van der Waals interactions, and resulting in atomic shuffling and causing inelastic alternation in both molecular structures and mechanical properties at the regions of the polymer surface. For those aromatic chain polymers like epoxy, the intrinsic deformation is depicted as the intra-chain rotation of aromatic rings and kinking of linear atomic connections. The present work highlights the need to reinterpret the data obtained from surface-sensing tests by considering this intrinsic inelastic deformation occurring at polymer surfaces.

Keywords: polymer, surface, nano, molecular dynamics

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8714 Decoupling PM₂.₅ Emissions and Economic Growth in China over 1998-2016: A Regional Investment Perspective

Authors: Xi Zhang, Yong Geng

Abstract:

It is crucial to decouple economic growth from environmental pollution in China. This study aims to evaluate the decoupling degree between PM₂.₅ emissions and economic growth in China from a regional investment perspective. Using the panel data of 30 Chinese provinces for the period of 1998-2016, this study combines decomposition analysis with decoupling analysis to identify the roles of conventional factors and three novel investment factors in the mitigation and decoupling of PM₂.₅ emissions in China and its four sub-regions. The results show that China’s PM₂.₅ emissions were weakly decoupled to economic growth during the period of 1998-2016, as well as in China’s four sub-regions. At the national level, investment scale played the dominant role while investment structure had a marginal effect. In contrast, emission intensity was the largest driver in promoting the decoupling effect, followed by investment efficiency and energy intensity. The investment scale effect in the western region far exceeded those in other three sub-regions. At the provincial level, the investment structure of Inner Mongolia and investment scales of Xinjiang and Inner Mongolia had the greatest impacts on PM₂.₅ emission growth. Finally, several policy recommendations are raised for China to mitigate its PM₂.₅ emissions.

Keywords: decoupling, economic growth, investment, PM₂.₅ emissions

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