Search results for: carbon stock

Authors: Aristeidis Samitas, Evangelos Vasileiou

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The aim of this study is to examine the month and the trading month effect under changing financial trends. We choose the Greek stock market to implement our assumption because there are clear and long term periods of financial growth and recession. Daily financial data from Athens Exchange General Index for the period 2002-2012 are considered. The paper employs several linear and non-linear models, although the TGARCH asymmetry model best fits in this sample and for this reason we mainly present the TGARCH results. Empirical results show that changing economic and financial conditions influences the calendar effects. Especially, the trading month effect totally changes in each fortnight according to the financial trend. On the other hand, in Greece the January effect exists during the growth periods, although it does not exist when the financial trend changes. The findings are helpful to anybody who invest and deals with the Greek stock market. Moreover, they may pave the way for an alternative calendar anomalies research approach, so it may be useful to investors who take into account these anomalies when they draw their investment strategy.

Keywords: month effect, trading month effect, economic cycles, crisis

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Authors: Vahidullah Tac, Ercan Gurses

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There have been numerous attempts at modelling carbon nanotube – polymer composites micromechanically in recent years, albeit to limited success. One of the major setbacks of the models used in the scientific community is the lack of regard to the different phases present in a nanocomposite. We employ a multi-phase micromechanical model that allows functionally grading certain phases to determine the mechanical properties of nanocomposites. The model has four distinct phases; the nanotube, the interface between the nanotube and polymer, the interphase, and the bulk matrix. Among the four phases, the interphase is functionally graded such that its moduli gradually decrease from some predetermined values to those of the bulk polymer. We find that the interface plays little role in stiffening/softening of the polymer per se , but instead, it is responsible for load transfer between the polymer and the carbon nanotube. Our results indicate that the carbon nanotube, as well as the interphase, have significant roles in stiffening the composite. The results are then compared to experimental findings and the interphase is tuned accordingly.

Keywords: carbon nanotube, composite, interphase, micromechanical modeling

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Authors: Chao Hu, Xinwen Liao, Qing-Hua Qin, Gang Wang

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The hierarchical carbon nanotube (CNT)/carbon fiber (CF)/high density polyethylene (HDPE) was fabricated via compound extrusion and injection molding, in which to author’s best knowledge CNT was employed as a nano-coatings on the surface of CF for the first time by spray coating technique. The CNT coatings relative to CF was set at 1 wt% and the CF content relative to the composites varied from 0 to 25 wt% to study the influence of CNT coatings and CF contents on the mechanical, thermal and morphological performance of this hierarchical composites. The results showed that with the rise of CF contents, the mechanical properties, including the tensile properties, flexural properties, and hardness of CNT/CF/HDPE composites, were effectively improved. Furthermore, the CNT-coated composites showed overall higher mechanical performance than the uncoated counterparts. It can be ascribed to the enhancement of interfacial bonding between the CF and HDPE via the incorporation of CNT, which was demonstrated by the scanning electron microscopy observation. Meanwhile, the differential scanning calorimetry data indicated that by the introduction of CNT and CF, the crystallization temperature and crystallinity of HDPE were affected while the melting temperature did not have an obvious alteration.

Keywords: carbon fibers, carbon nanotubes, extrusion, high density polyethylene

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Authors: Guillaume Craveur

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This study shows the opportunity to use numerical tools dedicated to Fire Safety Engineering for the Rolling Stock. Indeed, some lawful requirements can now be demonstrated by using numerical tools. The first part of this study presents the use of modelling evacuation tool to satisfy the criteria of evacuation time for the rolling stock. The buildingEXODUS software is used to model and simulate the evacuation of rolling stock. Firstly, in order to demonstrate the reliability of this tool to calculate the complete evacuation time, a comparative study was achieved between a real test and simulations done with buildingEXODUS. Multiple simulations are performed to capture the stochastic variations in egress times. Then, a new study is done to calculate the complete evacuation time of a train with the same geometry but with a different interior architecture. The second part of this study shows some applications of Computational Fluid Dynamics. This work presents the approach of a multi scales validation of numerical simulations of standardized tests with Fire Dynamics Simulations software developed by the National Institute of Standards and Technology (NIST). This work highlights in first the cone calorimeter test, described in the standard ISO 5660, in order to characterize the fire reaction of materials. The aim of this process is to readjust measurement results from the cone calorimeter test in order to create a data set usable at the seat scale. In the second step, the modelisation concerns the fire seat test described in the standard EN 45545-2. The data set obtained thanks to the validation of the cone calorimeter test was set up in the fire seat test. To conclude with the third step, after controlled the data obtained for the seat from the cone calorimeter test, a larger scale simulation with a real part of train is achieved.

Keywords: fire safety engineering, numerical tools, rolling stock, multi-scales validation

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Authors: Azeez O. Idris, Benjamin O. Orimolade, Potlako J. Mafa, Alex T. Kuvarega, Usisipho Feleni, Bhekie B. Mamba

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We report a simple and cheaper method for the electrochemical detection of Se(IV) using carbon nanodots (CNDTs) prepared from oat. The carbon nanodots were synthesised by green and facile approach and characterised using scanning electron microscopy, high-resolution transmission electron microscopy, Fourier transform infrared spectroscopy, X-ray diffraction, and Raman spectroscopy. The CNDT was used to fabricate an electrochemical sensor for the quantification of Se(IV) in water. The modification of glassy carbon electrode (GCE) with carbon nanodots led to an increase in the electroactive surface area of the electrode, which enhances the redox current peak of [Fe(CN)₆]₃₋/₄‒ in comparison to the bare GCE. Using the square wave voltammetry, the detection limit and quantification limit of 0.05 and 0.167 ppb were obtained under the optimised parameters using deposition potential of -200 mV, 0.1 M HNO₃ electrolyte, electrodeposition time of 60 s, and pH 1. The results further revealed that the GCE-CNDT was not susceptible to many interfering cations except Cu(II) and Pb(II), and Fe(II). The sensor fabrication involves a one-step electrode modification and was used to detect Se(IV) in a real water sample, and the result obtained is in agreement with the inductively coupled plasma technique. Overall, the electrode offers a cheap, fast, and sensitive way of detecting selenium in environmental matrices.

Keywords: carbon nanodots, square wave voltammetry, nanomaterials, selenium, sensor

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Authors: Hamid Rostami Jaz, Kamran Ameri Siahooei

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Up to now different methods have been used to forecast the index returns and the index rate. Artificial intelligence and artificial neural networks have been one of the methods of index returns forecasting. This study attempts to carry out a comparative study on the performance of different Radial Base Neural Network and Feed-Forward Perceptron Neural Network to forecast investment returns on the index. To achieve this goal, the return on investment in Tehran Stock Exchange index is evaluated and the performance of Radial Base Neural Network and Feed-Forward Perceptron Neural Network are compared. Neural networks performance test is applied based on the least square error in two approaches of in-sample and out-of-sample. The research results show the superiority of the radial base neural network in the in-sample approach and the superiority of perceptron neural network in the out-of-sample approach.

Keywords: exchange index, forecasting, perceptron neural network, Tehran stock exchange

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Authors: Ousmane Sarr

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The Senegalese coasts have high productivity of fishery resources due to the frequency of intense up-welling system that occurs along its coast, caused by the maritime trade winds making its waters nutrients rich. Fishing plays a primordial role in Senegal's socioeconomic plans and food security. However, a global diagnosis of the Senegalese maritime fishing sector has highlighted the challenges this sector encounters. Among these concerns, some significant stocks, a priority target for artisanal fishing, need further assessment. If no efforts are made in this direction, most stock will be overexploited or even in decline. It is in this context that this research was initiated. This investigation aimed to apply a multi-modal approach (LBB, Catch-only-based CMSY model and its most recent version (CMSY++); JABBA, and JABBA-Select) to assess the stock of Atlantic bonito, Sarda sarda (Bloch, 1793) in the Senegalese Exclusive Economic Zone (SEEZ). Available catch, effort, and size data from Atlantic bonito over 15 years (2004-2018) were used to calculate the nominal and standardized CPUE, size-frequency distribution, and length at retentions (50 % and 95 % selectivity) of the species. These relevant results were employed as input parameters for stock assessment models mentioned above to define the stock status of this species in this region of the Atlantic Ocean. The LBB model indicated an Atlantic bonito healthy stock status with B/BMSY values ranging from 1.3 to 1.6 and B/B0 values varying from 0.47 to 0.61 of the main scenarios performed (BON_AFG_CL, BON_GN_Length, and BON_PS_Length). The results estimated by LBB are consistent with those obtained by CMSY. The CMSY model results demonstrate that the SEEZ Atlantic bonito stock is in a sound condition in the final year of the main scenarios analyzed (BON, BON-bt, BON-GN-bt, and BON-PS-bt) with sustainable relative stock biomass (B2018/BMSY = 1.13 to 1.3) and fishing pressure levels (F2018/FMSY= 0.52 to 1.43). The B/BMSY and F/FMSY results for the JABBA model ranged between 2.01 to 2.14 and 0.47 to 0.33, respectively. In contrast, The estimated B/BMSY and F/FMSY for JABBA-Select ranged from 1.91 to 1.92 and 0.52 to 0.54. The Kobe plots results of the base case scenarios ranged from 75% to 89% probability in the green area, indicating sustainable fishing pressure and an Atlantic bonito healthy stock size capable of producing high yields close to the MSY. Based on the stock assessment results, this study highlighted scientific advice for temporary management measures. This study suggests an improvement of the selectivity parameters of longlines and purse seines and a temporary prohibition of the use of sleeping nets in the fishery for the Atlantic bonito stock in the SEEZ based on the results of the length-base models. Although these actions are temporary, they can be essential to reduce or avoid intense pressure on the Atlantic bonito stock in the SEEZ. However, it is necessary to establish harvest control rules to provide coherent and solid scientific information that leads to appropriate decision-making for rational and sustainable exploitation of Atlantic bonito in the SEEZ and the Eastern Atlantic Ocean.

Keywords: multi-model approach, stock assessment, atlantic bonito, healthy stock, sustainable, SEEZ, temporary management measures

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Authors: Mai M. Khalaf, Hany M. Abd El-Lateef

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A new good application for the sol gel method is to improve the corrosion inhibition properties of carbon steel by the dip coating method of Nano TiO2 films and its modification with Poly Ethylene Glycol (PEG). The prepared coating samples were investigated by different techniques, X-ray diffraction, Scanning Electron Microscopy (SEM), transmission electron microscopy and Energy Dispersive X-ray Spectroscopy (EDAX). The corrosion inhibition performance of the blank carbon steel and prepared coatings samples were evaluated in 0.5 M H2SO4 by using Electrochemical Impedance Spectroscopy (EIS) and potentiodynamic polarization measurements. The results showed that corrosion resistance of carbon steel increases with increasing the number of coated layers of both nano–TiO2 films and its modification of PEG. SEM-EDAX analyses confirmed that the percentage atomic content of iron for the carbon steel in 0.5 M H2SO4 is 83% and after the deposition of the steel in nano TiO2 sol and that with PEG are 94.3% and 93.7% respectively.

Keywords: dip-coatings, corrosion protection, sol gel, TiO2 films, PEG

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Authors: S. Yessengabulov, A. Uyzbayeva

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Residential buildings fund of Kazakhstan was built in the Soviet time about 35-60 years ago without considering energy efficiency measures. Currently, most of these buildings are in a rundown condition and fail to meet the minimum of hygienic, sanitary and comfortable living requirements. The paper aims to examine the reports of recent building energy survey activities in the country and provide a possible solution for retrofitting existing housing stock built before 1989 which could be applicable for building envelope in cold climate. Methodology also includes two-dimensional modeling of possible practical solutions and further recommendations.

Keywords: energy audit, energy efficient buildings in Kazakhstan, retrofit, two-dimensional conduction heat transfer analysis

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Authors: Tsegaye Adane Birhan

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Recently, rapid industrialization has led to the excessive release of heavy metals such as Cr (VI) into the environment. Exposure to chromium (VI) can cause kidney and liver damage, depressed immune systems, and a variety of cancers. Therefore, treatment of Cr (VI) containing wastewater is mandatory. This study aims to optimize the removal of Cr (VI) from an aqueous solution using locally available Teff husk-activated carbon adsorbent. The laboratory-based study was conducted on the optimization of Cr (VI) removal efficiency of Teff husk-activated carbon from aqueous solution. A central composite design was used to examine the effect of the interaction of process parameters and to optimize the process using Design Expert version 7.0 software. The optimized removal efficiency of Teff husk activated carbon (95.597%) was achieved at 1.92 pH, 87.83mg/L initial concentration, 20.22g/L adsorbent dose and 2.07Hrs contact time. The adsorption of Cr (VI) on Teff husk-activated carbon was found to be best fitted with pseudo-second-order kinetics and Langmuir isotherm model of the adsorption. Teff husk-activated carbon can be used as an efficient adsorbent for the removal of chromium (VI) from contaminated water. Column adsorption needs to be studied in the future.

Keywords: batch adsorption, chromium (VI), teff husk activated carbon, response surface methodology, tannery wastewater

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Authors: Salim Ahmed

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The aim of this study was to recover a natural residue in the form of activated carbon prepared from Moroccan "argan pits and date pits" plant waste. After preparing the raw material for manufacture, the carbon was carbonised at 300°C and chemically activated with phosphoric acid of purity 85. The various characterisation results (moisture and ash content, specific surface area, pore volume, etc.) showed that the carbons obtained are comparable to those manufactured industrially and could therefore be tested, for example, in water treatment processes and especially for the depollution of effluents used in the agri-food and textile industries.

Keywords: activated carbon, water treatment, adsorption, argan

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Authors: Peng Hao Wang, Ronald Sterkenburg, Garam Kim, Yuwei He

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As composite materials continue to gain popularity in the aerospace industry; large airframe sections made out of composite materials are becoming the standard for aerospace manufacturers. However, the heavy utilization of these composite materials also increases the importance of the recycling of these composite materials. A team of Purdue University School of Aviation and Transportation Technology (SATT) faculty and students have partnered to investigate the characteristics of 3D printed recycled carbon fiber. A prototype of a 3D printed recycled carbon fiber part was provided by an industry partner and different sections of the prototype were used to create specimens. A furnace was utilized in order to remove the polymer from the specimens and the specimen’s fiber content and fiber length was calculated from the remaining fibers. A differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA) test was also conducted on the 3D printed recycled carbon fiber prototype in order to determine the prototype’s degree of cure at different locations. The data collected from this study provided valuable information in the process improvement and understanding of 3D printed recycled carbon fiber.

Keywords: 3D printed, carbon fiber, fiber content, recycling

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Authors: Jafar Khan Kasi, Ajab Khan Kasi, Muzamil Bokhari

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Carbon nanotube is one of the most attractive materials for the potential applications of nanotechnology due to its excellent mechanical, thermal, electrical and optical properties. In this paper we report a supercapacitor made of nickel foil electrodes, coated with multiwall carbon nanotubes (MWCNTs) thin film using electrophoretic deposition (EPD) method. Chemical vapor deposition method was used for the growth of MWCNTs and ethanol was used as a hydrocarbon source. High graphitic multiwall carbon nanotube was found at 750 C analyzing by Raman spectroscopy. We observed the electrochemical performance of supercapacitor by cyclic voltammetry. The electrodes of supercapacitor fabricated from MWCNTs exhibit considerably small equivalent series resistance (ESR), and a high specific power density. Electrophoretic deposition is an easy method in fabricating MWCNT electrodes for high performance supercapacitor.

Keywords: carbon nanotube, chemical vapor deposition, catalyst, charge, cyclic voltammetry

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Authors: Taylan Kabbani, Ekrem Duman

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The design of adaptive systems that take advantage of financial markets while reducing the risk can bring more stagnant wealth into the global market. However, most efforts made to generate successful deals in trading financial assets rely on Supervised Learning (SL), which suffered from various limitations. Deep Reinforcement Learning (DRL) offers to solve these drawbacks of SL approaches by combining the financial assets price "prediction" step and the "allocation" step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. In this paper, a continuous action space approach is adopted to give the trading agent the ability to gradually adjust the portfolio's positions with each time step (dynamically re-allocate investments), resulting in better agent-environment interaction and faster convergence of the learning process. In addition, the approach supports the managing of a portfolio with several assets instead of a single one. This work represents a novel DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem, or what is referred to as The Agent Environment as Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. More specifically, we design an environment that simulates the real-world trading process by augmenting the state representation with ten different technical indicators and sentiment analysis of news articles for each stock. We then solve the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which can learn policies in high-dimensional and continuous action spaces like those typically found in the stock market environment. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of deep reinforcement learning in financial markets over other types of machine learning such as supervised learning and proves its credibility and advantages of strategic decision-making.

Keywords: the stock market, deep reinforcement learning, MDP, twin delayed deep deterministic policy gradient, sentiment analysis, technical indicators, autonomous agent

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Authors: Stephen Rathinaraj Benjamin, Flavio Colmati Junior, Maria Izabel Florindo Guedes, Rosa Amalia Fireman Dutra

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A new enzymatic electrochemical biosensor based on multiwall carbon nanotubes and cerium oxide nanoparticles for the detection of rutin has been developed. The cerium oxide nanoparticles /HRP/ multiwall carbon nanotubes/ carbon paste electrode (HRP/ CeO2/MWCNTs/CPE) was prepared by ensuing addition of MWCNTs and HRP on the CPE, followed by the mixing with cerium oxide nanoparticles. Surface physical characteristics of the modified electrode and the electrochemical properties of the composite were investigated by scanning electron microscopy (SEM), transmission electron microscopy (TEM), cylic voltammetry (CV), differential pulse voltammetry (DPV) and square wave voltammetry (SWV). The HRP/ CeO2/MWCNTs/CPE showed good selectivity, stability and reproducibility, which was further applied to detect rutin tablet and capsule samples with satisfactory results.

Keywords: cerium dioxide nanoparticles, horseradish peroxidase, multiwall carbon nanotubes, rutin

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Authors: Mohamed H. Gabr, Kiyoshi Uzawa

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The current study aims to investigate the effect of fillers with different geometries and sizes on the interfacial shear properties of PA6 composites with de-sized carbon fiber. The fillers which have been investigated are namely; nano-layer silicates (nanoclay), sub-micro aluminum titanium (ALTi) particles, and multiwall carbon nanotube (MWCNT). By means of X-ray photoelectron spectroscopy (XPS), epoxide group which defined as a sizing agent, has been removed. Sizing removal can reduce the acid parameter of carbon fibers surface promoting bonding strength at the fiber/matrix interface which is a desirable property for the carbon fiber composites. Microdroplet test showed that the interfacial shear strength (IFSS) has been enhanced with the addition of 10wt% ALTi by about 23% comparing with neat PA6. However, with including other types of fillers into PA6, the results did not show enhancement of IFSS.

Keywords: sub-micro particles, nano-composites, interfacial shear strength, polyamide 6

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Authors: Giulia Dal Maso

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Within the contemporary financial capitalist configuration, the interplay of Chinese statecraft and financialization has shaped a new ‘ecology of financial expertise.’ This indicates the emergence of a new financial technocratic governance; that is increasingly changing the Chinese economy, reducing the state’s administrative and fiscal functions and increasing state assets in accordance with a new shareholder logic. In this shift, the creation of the stock market by the state was conceived not only as a new redistributor of wealth but as a ‘clearing house’ for social discontent resulting from work casualization, wage repression and a lack of social welfare. Since its inception in the wake of Deng Xiaoping’s reforms, the Chinese state has used the stock market as a means of securing social legitimation by providing a prearranged space where the disaggregated and vulnerable subjects left behind by the dismantlement of the collective work units of the Maoist period (danwei) can congregate. However, fieldwork which included both participant observation as well as interviews with investors in brokerage rooms in Shanghai (where one of only two mainland Chinese stock exchanges is situated) reveals that both new formal and informal financial experts—namely the haigui (Chinese returnees with a financial degree abroad) and sanhu (individual Chinese scattered players), are equally dissatisfied with their investing activities. They express discontent with the state, which they hold responsible for the summer 2015 financial crisis and for the financial turmoil that jeopardizes China’s financial and political project. What the investors want is a state that will guarantee the continuation of the current gupiaore ‘stock fever’. This paper holds that, by embracing financialization, the state is undermining the contract at the base of its legitimacy.

Keywords: Chinese state, Deng Xiaoping, financial capitalism, individual investors

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Authors: Mostafa Ghasemi, Andrew Urquhart

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In this study, fluorescent carbon dots (CDs) were synthesized in a green way using a one-step hydrothermal method. Carbon dots are carbon-based nanomaterials with a size of less than 10 nm, unique structure, and excellent properties such as low toxicity, good biocompatibility, tunable fluorescence, excellent photostability, and easy functionalization. These properties make them a good candidate to use in different fields such as biological sensing, photocatalysis, photodynamic, and drug delivery. Fourier transformed infrared (FTIR) spectra approved OH/NH groups on the surface of the as-synthesized CDs, and UV-vis spectra showed excellent fluorescence quenching effect of Fe (III) ion on the as-synthesized CDs with high selectivity detection compared with other metal ions. The probe showed a linear response concentration range (0–2.0 mM) to Fe (III) ion, and the limit of detection was calculated to be about 0.50 μM. In addition, CDs also showed good sensitivity to the pH value in the range from 2 to 14, indicating great potential as a pH sensor.

Keywords: carbon dots, fluorescence, pH sensing, metal ions sensor

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Authors: A. Rana, M. Badri, D. Lopez Behar, O. Yee, H. Al Bqaei

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The building sector is one of the largest emitters of greenhouse gases. However, as operation energy demands of this sector decrease with more effective energy policies and strategies, there is an urgent need to parallel focus on the growing proportion of embodied carbons. In this regard, benchmarks on embodied carbon of buildings can provide a point of reference to compare and improve the environmental performance of buildings for the stakeholders. Therefore, embodied carbon benchmarks can serve as a useful tool to address climate change challenges. This research utilizes the method to provide a knowledge roadmap of embodied carbon benchmarks development and implementation trends. Two main databases, Web of Science and Engineering Village, are considered for the study. The mapping was conducted with the help of VosViewer tool to provide information regarding: the critical research areas; most cited authors and publications; and countries with the highest publications. It is revealed that the role of benchmarks in energy policies is an emerging trend. In addition, the research highlighted that in policies, embodied carbon benchmarks are gaining importance at the material, whole building, and building portfolio levels. This research reveals direction for improvement and future research and of relevance to building industry professionals, policymakers, and researchers.

Keywords: buildings embodied carbon benchmark, methods, policy

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Authors: Ankur Sachan

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Carbon dioxide being the most anthropogenic greenhouse gas,it needs to be isolated from entering into atmosphere. Carbon capture and storage is process that captures CO2 emitted from various sources, separates it from other gases and stores it in a safe place preferably in underground geological formations for large period of time. It is then purified and monitored so that can be made to reuse. Monoethanolamine, zeolitic imidazolate framework, microalgae, membranes etc are utilized to capture CO2. Post-combustion, pre-combustion and oxyfuel combustion along with chemical looping combustion are technologies for scrubbing CO2. The properties of CO2 being easily miscible and readily dissolving in oil with impurities makes it capable for numerous applications such as in producing oil by enhanced oil recovery (EOR), Bio CCS Algal Synthesis etc. CO2-EOR operation is capable to produce million barrels of oil and extend the field's lifetime as in case of Weyburn Oil Field in Canada. The physical storage of CO2 is technically the most feasible direction provided that the associated safety and sustainability issues can be met and new materials for CCUS process at low cost are urgently found so that so that fossil based systems with carbon capture are cost competitive.

Keywords: carbon capture, CCUS, sustainability, oil

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Authors: Byomakesh Debata, Jitendra Mahakud

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The recent financial crisis has been characterized by massive monetary policy interventions by the Central bank, and it has amplified the importance of liquidity for the stability of the stock market. This paper empirically elucidates the actual impact of monetary policy interventions on stock market liquidity covering all National Stock Exchange (NSE) Stocks, which have been traded continuously from 2002 to 2015. The present study employs a multivariate VAR model along with VAR-granger causality test, impulse response functions, block exogeneity test, and variance decomposition to analyze the direction as well as the magnitude of the relationship between monetary policy and market liquidity. Our analysis posits a unidirectional relationship between monetary policy (call money rate, base money growth rate) and aggregate market liquidity (traded value, turnover ratio, Amihud illiquidity ratio, turnover price impact, high-low spread). The impulse response function analysis clearly depicts the influence of monetary policy on stock liquidity for every unit innovation in monetary policy variables. Our results suggest that an expansionary monetary policy increases aggregate stock market liquidity and the reverse is documented during the tightening of monetary policy. To ascertain whether our findings are consistent across all periods, we divided the period of study as pre-crisis (2002 to 2007) and post-crisis period (2007-2015) and ran the same set of models. Interestingly, all liquidity variables are highly significant in the post-crisis period. However, the pre-crisis period has witnessed a moderate predictability of monetary policy. To check the robustness of our results we ran the same set of VAR models with different monetary policy variables and found the similar results. Unlike previous studies, we found most of the liquidity variables are significant throughout the sample period. This reveals the predictability of monetary policy on aggregate market liquidity. This study contributes to the existing body of literature by documenting a strong predictability of monetary policy on stock liquidity in an emerging economy with an order driven market making system like India. Most of the previous studies have been carried out in developing economies with quote driven or hybrid market making system and their results are ambiguous across different periods. From an eclectic sense, this study may be considered as a baseline study to further find out the macroeconomic determinants of liquidity of stocks at individual as well as aggregate level.

Keywords: market liquidity, monetary policy, order driven market, VAR, vector autoregressive model

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Authors: C. A. Roberts, S. L. Mascaro, J. R. Gerrish, J. L. Horner

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Management-intensive Grazing (MiG) is a practice that rotates livestock through paddocks in a way that best matches the nutrient requirements of the animal to the yield and quality of the pasture. In the USA, MiG has been taught to livestock producers throughout the state of Missouri in 2- and 3-day workshops called “Missouri Grazing Schools.” The economic impact of these schools was quantified using IMPLAN software. The model included hectares of adoption, animal performance, carrying capacity, and input costs. To date, MiG, as taught in the Missouri Grazing Schools, has been implemented on more than 70,000 hectares in Missouri. The economic impact of these schools is presently $125 million USD per year added to the state economy. This magnitude of impact is the result not only of widespread adoption but also because of increased livestock carrying capacity; in Missouri, a capacity increase of 25 to 30% has been well documented. Additional impacts have been MiG improving forage quality and reducing the cost of feed and fertilizer. The environmental impact of MiG in the state of Missouri is currently being estimated. Environmental impact takes into account the reduction in the application of commercial fertilizers; in MiG systems, nitrogen is supplied by N fixation from legumes, and much of the P and K is recycled naturally by well-distributed manure. The environmental impact also estimates carbon sequestration and methane production; MiG can increase carbon sequestration and reduce methane production in comparison to default grazing practices and feedlot operations in the USA.

Keywords: agricultural education, forage quality, management-intensive grazing, nutrient cycling, stock density, sustainable agriculture

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Authors: Zouhaier Nasr, Mohamed Nouri

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The increase in greenhouse gases since the pre-industrial period is a real threat to disrupting the balance of marine and terrestrial ecosystems. Along with the oceans, forest soils are considered to be the planet's second-largest carbon sink. North African forests have been subject to alarming degradation for several decades. The objective of this investigation is to determine and quantify the effect of thinning practiced in pine forests in northern Tunisia on the storage of organic carbon in the trees and in the soil. The plot planted in 1989 underwent thinning in 2005 on to plots; the density is therefore 1600 trees/ha in control and 400 trees/ha in thinning. Direct dendrometric measurements (diameter, height, branches, stem) were taken. In the soil part, six profiles of 1m / 1m / 1m were used for soil and root samples and biomass and organic matter measurements. The measurements obtained were statistically processed by appropriate software. The results clearly indicate that thinning improves tree growth, so the diameter increased from 24.3 cm to 30.1 cm. Carbon storage in the trunks was 35% more and 25% for the whole tree. At ground level, the thinned plot shows a slight increase in soil organic matter and quantity of carbon per tree, exceeding the control by 10 to 25%.

Keywords: forest, soil, carbon, climate change, Tunisia

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Authors: Vish Putcha, Chandrasekhar Putcha, Siva Hari

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In the current digital era of free trading and pandemic-driven remote work culture, markets worldwide gained momentum for retail investors to trade from anywhere easily. The number of retail traders rose to 24% of the market from 15% at the pre-pandemic level. Most of them are young retail traders with high-risk tolerance compared to the previous generation of retail traders. This trend boosted the growth of subscription-based market predictors and market data vendors. Young traders are betting on these predictors, assuming one of them is correct. However, 90% of retail traders are on the losing end. This paper presents multiple indicators and attempts to derive behavioral patterns from the underlying stocks. The two major indicators that traders and investors follow are technical and fundamental. The famous investor, Warren Buffett, adheres to the “Value Investing” method that is based on a stock’s fundamental Analysis. In this paper, we present multiple indicators from various methods to understand the behavior patterns of stocks. For this research, we picked five stocks with a market capitalization of more than $200M, listed on the exchange for more than 20 years, and from different industry sectors. To study the behavioral pattern over time for these five stocks, a total of 8 indicators are chosen from fundamental, technical, and financial indicators, such as Price to Earning (P/E), Price to Book Value (P/B), Debt to Equity (D/E), Beta, Volatility, Relative Strength Index (RSI), Moving Averages and Dividend yields, followed by detailed mathematical Analysis. This is an interdisciplinary paper between various disciplines of Engineering, Accounting, and Finance. The research takes a new approach to identify clear indicators affecting stocks. Statistical Analysis of the data will be performed in terms of the probabilistic distribution, then follow and then determine the probability of the stock price going over a specific target value. The Chi-square test will be used to determine the validity of the assumed distribution. Preliminary results indicate that this approach is working well. When the complete results are presented in the final paper, they will be beneficial to the community.

Keywords: stock pattern, stock market analysis, stock predictions, trading, investing, fundamental analysis, technical analysis, quantitative trading, financial analysis, behavioral analysis

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Authors: Yosra Mefteh Rekik, Younes Boujelbene

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We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the intelligence investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.

Keywords: artificial intelligence methods, artificial stock market, behavioral modeling, multi-agent based simulation

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Authors: Pakhapoom Sarapat, James M. Hill, Duangkamon Baowan

Abstract:

Carbon nanotori provide several properties such as high tensile strength and heat resistance. They are promised to be ideal structures for encapsulation, and their encapsulation ability can be determined by the interaction energy between the carbon nanotori and the encapsulated nanostructures. Such interaction energy is evaluated using Lennard-Jones potential and continuum approximation. Here, four problems relating to toroidal molecules are determined in order to find the most stable configuration. Firstly, the interaction energy between a carbon nanotorus and an atom is examined. The second problem relates to the energy of a fullerene encapsulated inside a carbon nanotorus. Next, the interaction energy between two symmetrically situated and parallel nanotori is considered. Finally, the classical mechanics is applied to model the interaction energy between the toroidal structure of cyclodextrin and the spherical DNA molecules. These mathematical models might be exploited to study a number of promising devices for future developments in bio and nanotechnology.

Keywords: carbon nanotori, continuum approximation, interaction energy, Lennard-Jones potential, nanotechnology

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Authors: Emmanuel Jr. Ballad, Herman Mendoza

Abstract:

The recovery of fine activated carbon with adsorbed gold in the cyanidation tailings of a small-scale gold plant was investigated due to the high amount of gold present. In the study, collectors that were used are kerosene and diesel. Emulsification of the oils was done to improve its collecting property, thus also the recovery. It was found out that the best hydrophile lypophile balance (HLB) of emulsified diesel and kerosene oil is 13 and 12 respectively. The amount of surfactants (SPAN 20 and TWEEN 20) for the best stability of the emulsified oils was found to be 10% in both kerosene and diesel. Optical microscopy showed that the oil dispersion in the water forms spherical droplets like features. The higher the stability, the smaller the droplets and their number were increasing. The smaller droplets indicate better dispersion of oil in the water. Consequently, it will have a greater chance of oil and activated carbon particle interaction during flotation. Due to the interaction of dispersed oil phase with carbon, the hydrophobicity of the carbon will be improved and will be attached to the bubble. Thus, flotation recovery will be increased. Results showed that the recovery of the fine activated carbon using emulsified diesel or kerosene is three times more effective than using pure diesel or kerosene.

Keywords: emulsified oils, flotation, hydrophile lyophile balance, non-ionic surfactants

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Authors: Antonella D'Alessandro, Filippo Ubertini, Annibale Luigi Materazzi

Abstract:

The progress of nanotechnology resulted in the development of new instruments in the field of civil engineering. In particular, the introduction of carbon nanofillers into construction materials can enhance their mechanical and electrical properties. In construction, concrete is among the most used materials. Due to the characteristics of its components and its structure, concrete is suitable for modification, at the nanometer level too. Moreover, to guarantee structural safety, it is desirable to achieve a widespread monitoring of structures. The ideal thing would be to realize structures able to identify their behavior modifications, states of incipient damage or conditions of possible risk for people. This paper presents a research work about novel cementitious composites with conductive carbon nanoinclusions able of monitoring their state of deformation, with particular attention to concrete. The self-sensing ability is achieved through the correlation between the variation of stress or strain and that of electrical resistance. Carbon nanofillers appear particularly suitable for such applications. Nanomodified concretes with different carbon nanofillers has been tested. The samples have been subjected to cyclic and dynamic loads. The experimental campaign shows the potentialities of this new type of sensors made of nanomodified concrete for diffuse Structural Health Monitoring.

Keywords: carbon nanofillers, cementitious nanocomposites, smart sensors, structural health monitoring.

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Authors: Vara Prasad Vemu

Abstract:

The aim of the present work is to investigate the mechanical properties and water absorption capacity of carbon and basalt fibers mixed with matrix epoxy. At present, there is demand for nature friendly products. Basalt reinforced composites developed recently, and these mineral amorphous fibres are a valid alternative to carbon fibres for their lower cost and to glass fibres for their strength. The present paper describes briefly on basalt and carbon fibres (uni-directional) which are used as reinforcement materials for composites. The matrix epoxy (LY 556-HY 951) is taken into account to assess its influence on the evaluated parameters. In order to use reinforced composites for structural applications, it is necessary to perform a mechanical characterization. With this aim experiments like tensile strength, flexural strength, hardness and water absorption are performed. Later the mechanical properties obtained from experiments are compared with ANSYS software results.

Keywords: carbon fibre, basalt fibre, uni-directional, reinforcement, mechanical tests, water absorption test, ANSYS

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Authors: Talal Alsulaiman, Khaldoun Khashanah

Abstract:

In this paper, we provided a literature survey on the artificial stock problem (ASM). The paper began by exploring the complexity of the stock market and the needs for ASM. ASM aims to investigate the link between individual behaviors (micro level) and financial market dynamics (macro level). The variety of patterns at the macro level is a function of the AFM complexity. The financial market system is a complex system where the relationship between the micro and macro level cannot be captured analytically. Computational approaches, such as simulation, are expected to comprehend this connection. Agent-based simulation is a simulation technique commonly used to build AFMs. The paper proceeds by discussing the components of the ASM. We consider the roles of behavioral finance (BF) alongside the traditionally risk-averse assumption in the construction of agent's attributes. Also, the influence of social networks in the developing of agents’ interactions is addressed. Network topologies such as a small world, distance-based, and scale-free networks may be utilized to outline economic collaborations. In addition, the primary methods for developing agents learning and adaptive abilities have been summarized. These incorporated approach such as Genetic Algorithm, Genetic Programming, Artificial neural network and Reinforcement Learning. In addition, the most common statistical properties (the stylized facts) of stock that are used for calibration and validation of ASM are discussed. Besides, we have reviewed the major related previous studies and categorize the utilized approaches as a part of these studies. Finally, research directions and potential research questions are argued. The research directions of ASM may focus on the macro level by analyzing the market dynamic or on the micro level by investigating the wealth distributions of the agents.

Keywords: artificial stock markets, market dynamics, bounded rationality, agent based simulation, learning, interaction, social networks

Procedia PDF Downloads 354