Search results for: short columns

Authors: Mohammad Hossein Karimi Darvanjooghi, Sara Magdouli, Satinder Kaur Brar

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It has been reported that the microorganism’s attachment to the surfaces of ore samples is a key factor that influences the biooxidation in pretreatment for recovery of gold in sulfide-bearing ores. In this research, the implementation of D-(+)-Sucrose on the biooxidation of ore samples were studied in a semi-pilot experiment. The experiments were carried out in five separate jacketed columns (1 m height and 6 cm diameter) at a constant temperature of 37.5 ̊C and saturated humidity. The airflow rate and recycling solution flow rate were studied in the research and the optimum operating condition were reported. The ore sample (0.49 ppm gold grade) was obtained from the Hammond Reef mine site containing 15 wt.% of pyrite which included 98% of gold according to the results of micrograph images. The experiments were continued up to 100 days while air flow rates were chosen to be 0.5, 1, 1.5, 2, and 3 lit/min and the recycling solution (Containing 9K media and 0.4 wt.% D-(+)-Sucrose) flow rates were kept 5, 8, 15 ml/hr. The results indicated that the addition of D-(+)-Sucrose increased the bacterial activity due to the overproduction of extracellular polymeric substance (EPS) up to 95% and for the condition that the recycling solution and air flow rate were chosen to be 8 ml/hr and 2 lit/min, respectively, the maximum pyrite dissolution of 76% was obtained after 60 days. The results indicated that for the air flow rates of 0.5, 1, 1.5, 2, and 3 lit/min the ratio of daily pyrite dissolution per daily solution lost were found to be 0.025, 0.033, 0.031, 0.043, and 0.009 %-pyrite dissolution/ml-lost. The implementation of this microorganisms and the addition of D-(+)-Sucrose will enhance the efficiency of gold recovery through faster biooxidation process and leads to decrease in the time and energy of operation toward desired target; however, still other parameters including particle size distribution, agglomeration, aeration design, chemistry of recycling solution need to be controlled and monitored for reaching the optimum condition.

Keywords: column tests, biooxidation, gold recovery, Ferroplasma acidophilum, optimization

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Authors: Abdulkarim Yusuf

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Motivation: A crucial but difficult goal for governments and policymakers in Nigeria in recent years has been the sustainability of economic growth. This goal must be accomplished by regulating or lowering greenhouse gas emissions, which calls for switching to a low- or zero-carbon production system. The lack of in-depth empirical studies on the environmental impact of socioeconomic variables on Nigeria and a number of unresolved issues from earlier research is what led to the current study. Objective: This study fills an important empirical gap by investigating the existence of an Environmental Kuznets Curve hypothesis and the long and short-run dynamic impact of socioeconomic variables on ecological sustainability in Nigeria. Data and method: Annual time series data covering the period 1980 to 2020 and the Autoregressive Distributed Lag technique in the presence of structural breaks were adopted for this study. Results: The empirical findings support the existence of the environmental Kuznets curve hypothesis for Nigeria in the long and short run. Energy consumption and total import exacerbate environmental deterioration in the long and short run, whereas total export improves environmental quality in the long and short run. Financial development, which contributed to a conspicuous decrease in the level of environmental destruction in the long run, escalated it in the short run. In contrast, urbanization caused a significant increase in environmental damage in the long run but motivated a decrease in biodiversity loss in the short run. Implications: The government, policymakers, and all energy stakeholders should take additional measures to ensure the implementation and diversification of energy sources to accommodate more renewable energy sources that emit less carbon in order to promote efficiency in Nigeria's production processes and lower carbon emissions. In order to promote the production and trade of environmentally friendly goods, they should also revise and strengthen environmental policies. With affordable, dependable, and sustainable energy use for higher productivity and inclusive growth, Nigeria will be able to achieve its long-term development goals of good health and wellbeing.

Keywords: economic growth, energy consumption, environmental degradation, environmental Kuznets curve, urbanization, Nigeria

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Authors: Abderrazek Ben Maatoug, Ibrahim Fatnassi, Wassim Ben Ayed

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In this paper we investigate the issue of market risk quantification for Middle East and North Africa (MENA) Islamic market equity. We use Value-at-Risk (VaR) as a measure of potential risk in Islamic stock market, for long and short position, based on Riskmetrics model and the conditional parametric ARCH class model volatility with normal, student and skewed student distribution. The sample consist of daily data for the 2006-2014 of 11 Islamic stock markets indices. We conduct Kupiec and Engle and Manganelli tests to evaluate the performance for each model. The main finding of our empirical results show that (i) the superior performance of VaR models based on the Student and skewed Student distribution, for the significance level of α=1% , for all Islamic stock market indices, and for both long and short trading positions (ii) Risk Metrics model, and VaR model based on conditional volatility with normal distribution provides the best accurate VaR estimations for both long and short trading positions for a significance level of α=5%.

Keywords: value-at-risk, risk management, islamic finance, GARCH models

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Authors: Jinhoa Lee

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The relationships between environmental quality, energy use and economic output have created growing attention over the past decades among researchers and policy makers. Focusing on the empirical aspects of the role of carbon dioxide (CO2) emissions and energy use in affecting the economic output, this paper is an effort to fulfill the gap in a comprehensive case study at a country level using modern econometric techniques. To achieve the goal, this country-specific study examines the short-run and long-run relationships among energy consumption (using disaggregated energy sources: crude oil, coal, natural gas, and electricity), CO2 emissions and gross domestic product (GDP) for Turkey using time series analysis from the year 1980-2010. To investigate the relationships between the variables, this paper employs the Augmented Dickey-Fuller (ADF) test for stationarity, Johansen’s maximum likelihood method for cointegration and a Vector Error Correction Model (VECM) for both short- and long-run causality among the research variables for the sample. The long-run equilibrium in the VECM suggests no effects of the CO2 emissions and energy use on the GDP in Turkey. There exists a short-run bidirectional relationship between the electricity and natural gas consumption, and also there is a negative unidirectional causality running from the GDP to electricity use. Overall, the results partly support arguments that there are relationships between energy use and economic output; however, the effects may differ due to the source of energy such as in the case of Turkey for the period of 1980-2010. However, there is no significant relationship between the CO2 emissions and the GDP and between the CO2 emissions and the energy use both in the short term and long term.

Keywords: CO2 emissions, energy consumption, GDP, Turkey, time series analysis

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Authors: O. Delage, H. Bencherif, T. Portafaix, A. Bourdier

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The main purpose of time series analysis is to learn about the dynamics behind some time ordered measurement data. Two approaches are used in the literature to get a better knowledge of the dynamics contained in observation data sequences. The first of these approaches concerns time series decomposition, which is an important analysis step allowing patterns and behaviors to be extracted as components providing insight into the mechanisms producing the time series. As in many cases, time series are short, noisy, and non-stationary. To provide components which are physically meaningful, methods such as Empirical Mode Decomposition (EMD), Empirical Wavelet Transform (EWT) or, more recently, Empirical Adaptive Wavelet Decomposition (EAWD) have been proposed. The second approach is to reconstruct the dynamics underlying the time series as a trajectory in state space by mapping a time series into a set of Rᵐ lag vectors by using the method of delays (MOD). Takens has proved that the trajectory obtained with the MOD technic is equivalent to the trajectory representing the dynamics behind the original time series. This work introduces the singular spectrum decomposition (SSD), which is a new adaptive method for decomposing non-linear and non-stationary time series in narrow-banded components. This method takes its origin from singular spectrum analysis (SSA), a nonparametric spectral estimation method used for the analysis and prediction of time series. As the first step of SSD is to constitute a trajectory matrix by embedding a one-dimensional time series into a set of lagged vectors, SSD can also be seen as a reconstruction method like MOD. We will first give a brief overview of the existing decomposition methods (EMD-EWT-EAWD). The SSD method will then be described in detail and applied to experimental time series of observations resulting from total columns of ozone measurements. The results obtained will be compared with those provided by the previously mentioned decomposition methods. We will also compare the reconstruction qualities of the observed dynamics obtained from the SSD and MOD methods.

Keywords: time series analysis, adaptive time series decomposition, wavelet, phase space reconstruction, singular spectrum analysis

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Authors: Yazdani Saeed, Rafiei Hamed, Nekoofar Farahnaz

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Governments Policies play a major role in national and international Markets. Pistachio is one of the most important non-oil export commodity of Iran. Therefore, in this study the relation between the producer support policies and the export of Pistachio was examined. An econometric model (VAR) was applied to test the study hypothesis. According to the estimated coefficient in VAR model, lag of producer support index has a significant and negative effect on variation of Pistachio’s export in short term. In other word, in short term, export advantage index is dependent on the amount of producers support in previous period.

Keywords: producer support, export advantage, pistachio, Iran

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Authors: R. Ramesh, K. K. Shivaraman

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The main aim of this paper is to handle the energy requirement in an efficient manner by merging the advanced digital communication and control technologies for smart grid applications. In order to reduce user home load during peak load hours, utility applies several incentives such as real-time pricing, time of use, demand response for residential customer through smart meter. However, this method provides inconvenience in the sense that user needs to respond manually to prices that vary in real time. To overcome these inconvenience, this paper proposes a convolutional neural network (CNN) with k-means clustering machine learning model which have ability to forecast energy requirement in short term, i.e., hour of the day or day of the week. By integrating our proposed technique with home energy management based on Bluetooth low energy provides predicted value to user for scheduling appliance in advanced. This paper describes detail about CNN configuration and k-means clustering algorithm for short-term energy forecasting.

Keywords: convolutional neural network, fuzzy logic, k-means clustering approach, smart home energy management

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Authors: Mehdi Radmehr, Amir Hamed Mashhadzadeh, Mehdi Jafari

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Traditional HVDC systems are tough to DC short circuits as they are current regulated with a large reactance connected in series with cables. Multi-terminal DC wind farm topologies are attracting increasing research attempt. With AC/DC converters on the generator side, this topology can be developed into a multi-terminal DC network for wind power collection, which is especially suitable for large-scale offshore wind farms. For wind farms, the topology uses high-voltage direct-current transmission based on voltage-source converters (VSC-HVDC). Therefore, they do not suffer from over currents due to DC cable faults and there is no over current to react to. In this study, the multi-terminal DC wind farm topology is introduced. Then, possible internal DC faults are analyzed according to type and characteristic. Fault over current expressions are given in detail. Under this characteristic analysis, fault detection and detailed protection methods are proposed. Theoretical analysis and PSCAD/EMTDC simulations are provided.

Keywords: DC short circuits, multi-terminal DC wind farm topologies, HVDC transmission based on VSC, fault analysis

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Authors: Byl Farney Cunha Junior

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In this work the dynamic three-dimensional analysis of a 47-story building located in Goiania city when subjected to wind loads generated using both the Wind Brazilian code, NBR6123 (ABNT, 1988) and the Synthetic-Wind method is realized. To model the frames three different methodologies are used: the shear building model and both bi and three-dimensional finite element models. To start the analysis, a plane frame is initially studied to validate the shear building model and, in order to compare the results of natural frequencies and displacements at the top of the structure the same plane frame was modeled using the finite element method through the SAP2000 V10 software. The same steps were applied to an idealized 20-story spacial frame that helps in the presentation of the stiffness correction process applied to columns. Based on these models the two methods used to generate the Wind loads are presented: a discrete model proposed in the Wind Brazilian code, NBR6123 (ABNT, 1988) and the Synthetic-Wind method. The method uses the Davenport spectrum which is divided into a variety of frequencies to generate the temporal series of loads. Finally, the 47- story building was analyzed using both the three-dimensional finite element method through the SAP2000 V10 software and the shear building model. The models were loaded with Wind load generated by the Wind code NBR6123 (ABNT, 1988) and by the Synthetic-Wind method considering different wind directions. The displacements and internal forces in columns and beams were compared and a comparative study considering a situation of a full elevated reservoir is realized. As can be observed the displacements obtained by the SAP2000 V10 model are greater when loaded with NBR6123 (ABNT, 1988) wind load related to the permanent phase of the structure’s response.

Keywords: finite element method, synthetic wind, tall buildings, shear building

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Authors: Serge Provost, Yishan Zang

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Following a review of various approaches that are utilized for classifying the tail behavior of a distribution, an easily implementable methodology that relies on an arctangent transformation is presented. The classification criterion is actually based on the difference between two specific quantiles of the transformed distribution. The resulting categories enable one to classify distributional tails as distinctly short, short, nearly medium, medium, extended medium and somewhat long, providing that at least two moments exist. Distributions possessing a single moment are said to be long tailed while those failing to have any finite moments are classified as having an extremely long tail. Several illustrative examples will be presented.

Keywords: arctangent transformation, tail classification, heavy-tailed distributions, distributional moments

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Authors: Taimoor Hussain Alvi, Syed Toqueer Akhter

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The focus of this research is to identify Pak-India bilateral trade spillover effects upon Pakistan’s Growth rate. Cross-country spillover growth Effects have been linked with openness and access to markets. In this research, we intend to see the short run and long run effects of Pak-India Bilateral Trade Openness upon economic growth in Pakistan. Trade Openness has been measured as the sum of bilateral exports and imports between the two countries. Increased emphasis on the condition and environment of financial markets is laid in light of globalization and trade liberalization. This research paper makes use of the Univariate Autoregressive Distributed Lagged Model to analyze the effects of bilateral trade variables upon the growth pattern of Pakistan in the short run and long run. Key findings of the study empirically support the notion that increased bilateral trade will be beneficial for Pakistan in the short run because of cost advantage and knowledge spillover in terms of increased technical and managerial ability from multinational firms. However, contrary to extensive literature, increased bilateral trade measures will affect Pakistan’s growth rate negatively in the long run because of the industrial size differential and increased integration of Indian economy with the world.

Keywords: bilateral trade openness, spillover, comparative advantage, univariate

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Authors: Mahmut Yildirim

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This paper proposed the bidirectional long short-term memory (Bi-LSTM) network-aided deep learning (DL)-based signal detection for Orthogonal frequency division multiplexing with all index modulation (OFDM-AIM), namely Bi-DeepAIM. OFDM-AIM is developed to increase the spectral efficiency of OFDM with index modulation (OFDM-IM), a promising multi-carrier technique for communication systems beyond 5G. In this paper, due to its strong classification ability, Bi-LSTM is considered an alternative to the maximum likelihood (ML) algorithm, which is used for signal detection in the classical OFDM-AIM scheme. The performance of the Bi-DeepAIM is compared with LSTM network-aided DL-based OFDM-AIM (DeepAIM) and classic OFDM-AIM that uses (ML)-based signal detection via BER performance and computational time criteria. Simulation results show that Bi-DeepAIM obtains better bit error rate (BER) performance than DeepAIM and lower computation time in signal detection than ML-AIM.

Keywords: bidirectional long short-term memory, deep learning, maximum likelihood, OFDM with all index modulation, signal detection

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Authors: C. Senabre, S. Valero, M. Lopez, E. Velasco, M. Sanchez

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This paper focuses on an application of linear mixed models to short-term load forecasting. The challenge of this research is to improve a currently working model at the Spanish Transport System Operator, programmed by us, and based on linear autoregressive techniques and neural networks. The forecasting system currently forecasts each of the regions within the Spanish grid separately, even though the behavior of the load in each region is affected by the same factors in a similar way. A load forecasting system has been verified in this work by using the real data from a utility. In this research it has been used an integration of several regions into a linear mixed model as starting point to obtain the information from other regions. Firstly, the systems to learn general behaviors present in all regions, and secondly, it is identified individual deviation in each regions. The technique can be especially useful when modeling the effect of special days with scarce information from the past. The three most relevant regions of the system have been used to test the model, focusing on special day and improving the performance of both currently working models used as benchmark. A range of comparisons with different forecasting models has been conducted. The forecasting results demonstrate the superiority of the proposed methodology.

Keywords: short-term load forecasting, mixed effects models, neural networks, mixed effects models

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Authors: M. Zielina, W. Dabrowski, E. Radziszewska-Zielina

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Several different cements have been tested to evaluate their potential to leach calcium, chromium and aluminum ions in soft water environment. The research allows comparing some different cements in order to the potential risk of water contamination. This can be done only in the same environment. To reach the results in reasonable short time intervals and to make heavy metals measurements with high accuracy, demineralized water was used. In this case the conditions of experiments are far away from the water supply practice, but short time experiments and measurably high concentrations of elements in the water solution are an important advantage. Moreover leaching mechanisms can be recognized, our experiments reported here refer to this kind of cements evaluation.

Keywords: concrete corrosion, hydrogen sulfide, odors, reinforced concrete sewers, sewerage

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Authors: Lynmar M. Didal, Ramises G. Manzano Jr., Jacque Bon-Isaac C. Aboy

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This study analyzes the performance of global minimum variance and naive portfolios across different economic periods, using monthly stock returns from the Philippine Stock Exchange Index (PSEI), S&P 500, and Dow Jones Industrial Average (DOW). The performance is evaluated through the Sharpe ratio, Sortino ratio, Jensen’s Alpha, Treynor ratio, and Information ratio. Additionally, the study investigates the impact of short selling on portfolio performance. Six-time periods are defined for analysis, encompassing events such as the global financial crisis and the COVID-19 pandemic. Findings indicate that the Naive portfolio generally outperforms the GMV portfolio in the S&P 500, signifying higher returns with increased volatility. Conversely, in the PSEI and DOW, the GMV portfolio shows more efficient risk-adjusted returns. Short selling significantly impacts the GMV portfolio during mid-GFC and mid-COVID periods. The study offers insights for investors, suggesting the Naive portfolio for higher risk tolerance and the GMV portfolio as a conservative alternative.

Keywords: portfolio performance, global minimum variance, naïve portfolio, risk-adjusted metrics, short-selling

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Authors: Nadia Sghaier

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In this paper, we aim to identify the determinants of the life and non-life insurance premiums of different lines for the case of the Tunisian insurance market over a recent period from 1997 to 2019. The empirical analysis is conducted using the linear cointegration techniques in the panel data framework, which allow both long and short-run relationships. The obtained results show evidence of long-run relationship between premiums, losses, and financial variables (stock market indices and interest rate). Furthermore, we find that the short-run effect of explanatory variables differs across lines. This finding has important implications for insurance tarification and regulation.

Keywords: insurance premiums, lines, Tunisian insurance market, cointegration approach in panel data

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Authors: Buti Suryabrahmam, V. A. Raghunathan

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We study the effect of short chain alcohols on mechanical properties of saturated lipid bilayers in the fluid phase. The Bending rigidity of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) membrane was measured at 28 °C by employing Vesicle Fluctuation Analysis technique. The concentration and chain length (n) of alcohol in the buffer solution were varied from 0 to 1.5 M and from 2 to 8 respectively. We observed a non-linear reduction in the bending rigidity from ~17×10⁻²⁰ J to ~10×10⁻²⁰ J, for all chain lengths of alcohols used in our experiment. We observed approximately three orders of the concentration difference between ethanol and octanol, to show the similar reduction in the bending values. We attribute this phenomenon to thinning of the bilayer due to the adsorption of alcohols at the bilayer-water interface.

Keywords: alcohols, bending rigidity, DMPC, lipid bilayers

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Authors: Nikhil Kumar, Aparna Singh

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Microstructural development when annealed at different temperatures in a high aluminum and manganese light weight steel has been examined. The FCC matrix of the manganese (Mn)-rich and nickel (Ni)-rich areas in the studied Fe-Mn-Al-Ni-C-light weight steel have been found to contain anti phase domains. In the Mn-rich region short order range of domains manifested by the diffuse scattering in the electron diffraction patterns was observed. Domains in the Ni-rich region were found to be arranged periodically validated through lattice imaging. The nature of these domains can be tuned with annealing temperature resulting in profound influence in the mechanical properties.

Keywords: Anti-phase domain boundaries, BCC, FCC, Light Weight Steel

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Authors: N. Massoum, B. Bouazza

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In this paper, we have developed a numerical simulation model to describe the electrical properties of GaInP MESFET with submicron gate (Lg = 0.5 µm). This model takes into account the three-dimensional (3D) distribution of the load in the short channel and the law effect of mobility as a function of electric field. Simulation software based on a stochastic method such as Monte Carlo has been established. The results are discussed and compared with those of the experiment. The result suggests experimentally that, in a very small gate length in our devices (smaller than 40 nm), short-channel tunneling explains the degradation of transistor performance, which was previously enhanced by velocity overshoot.

Keywords: Monte Carlo simulation, transient electron transport, MESFET device, simulation software

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Authors: Gregory W. Smith, Paul J. Riccomini

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The goal of this empirical inquiry is to explore the effect of noise reducing headphones on the short-term memory recall of college students. Immediately following the presentation (via PowerPoint) of 12 unrelated and randomly selected one- and two-syllable words, students were asked to recall as many words as possible. Using a linear model with conditions marked with binary indicators, we examined the frequency and accuracy of words that were recalled. The findings indicate that for some students, a reduction of noise has a significant positive impact on their ability to recall information. As classrooms become more aurally distracting due to the implementation of cooperative learning activities, these findings highlight the need for a quiet learning environment for some learners.

Keywords: auditory distraction, education, instruction, noise, working memory

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Authors: Nona Mirzamohammadi, Bahram Nasernejad

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This work mainly focuses on studying the mechanism governing the adsorption of tetraethylammonium bromide, a short-chain quaternary ammonium salt, on the surface of natural zeolite and to characterize modified and raw zeolites in order to study the removal of nitrate anions from water. Natural clinoptilolite, as the most common zeolite, was chosen and modified in an ultrasonication process using tetraethylammonium bromide, subsequent to being contacted with NaCl solutions. FT-IR studies indicated a peak attributed to the stretching vibrations of the –CH₂ group in the molecule of tetraethylammonium bromide in the spectrum of the modified sample. Moreover, the SEM images showed some obvious changes in the surface morphology and crystallinity of clinoptilolite after being modified. Batch adsorption experiments show that the modified zeolite is capable of removing nitrate anions, and the predominant removal mechanism is suggested to be a combination of electrostatic attraction and ion exchange since the results from the zeta potential analysis showed a decrease in the net negative charge of clinoptilolite after modification, while bromide ions were detected in the modified sample in the µXRF analysis.

Keywords: adsorption, clinoptilolite, short-chain quaternary ammonium salt, tetraethylammoniumbromide, ultrasonication

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Authors: Kwa-Sur Tam, Byung O. Kang

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By using different ranges of daily sky clearness index defined in this paper, any day can be classified as a clear sky day, a partly cloudy day or a cloudy day. This paper demonstrates how short-term forecasting of solar irradiation can be improved by taking into consideration the type of day so defined. The source of day type dependency has been identified. Forecasting methods that take into consideration of day type have been developed and their efficacy have been established. While all methods that implement some form of adjustment to the cloud cover forecast provided by the U.S. National Weather Service provide accuracy improvement, methods that incorporate day type dependency provides even further improvement in forecast accuracy.

Keywords: day types, forecast methods, National Weather Service, sky cover, solar energy

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Authors: S. Sharan Sundar, Nithish B. Moudhgalya, Nidhi Bhandari, Vineeth Vijayaraghavan

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Automatic Short Answer Grading is one of the prime applications of artificial intelligence in education. Several approaches involving the utilization of selective handcrafted features, graphical matching techniques, concept identification and mapping, complex deep frameworks, sentence embeddings, etc. have been explored over the years. However, keeping in mind the real-world application of the task, these solutions present a slight overhead in terms of computations and resources in achieving high performances. In this work, a simple and effective solution making use of elemental features based on statistical, linguistic properties, and word-based similarity measures in conjunction with tree-based classifiers and regressors is proposed. The results for classification tasks show improvements ranging from 1%-30%, while the regression task shows a stark improvement of 35%. The authors attribute these improvements to the addition of multiple similarity scores to provide ensemble of scoring criteria to the models. The authors also believe the work could reinstate that classical natural language processing techniques and simple machine learning models can be used to achieve high results for short answer grading.

Keywords: artificial intelligence, intelligent systems, natural language processing, text mining

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Authors: Muhammad Mazhar, Yong Zhu, Likang Qin

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Foods contain endogenous components known as dietary fibers, which are classified into soluble and insoluble forms. Dietary fibers are resistant to gut digestive enzymes, modulating anaerobic intestinal microbiota (AIM) and fabricating short-chain fatty acids (SCFAs). Acetate, butyrate, and propionate dominate in the gut, and different pathways, including Wood-Ljungdahl and acrylate pathways, generate these SCFAs. In pancreatic dysfunction, the release of insulin/glucagon is impaired, which leads to hyperglycemia. SCFAs enhance insulin sensitivity or secretion, beta-cell functions, leptin release, mitochondrial functions, and intestinal gluconeogenesis in human organs, which positively affect type 2 diabetes (T2D). Research models presented that SCFAs either enhance the release of peptide YY (PYY) and glucagon-like peptide-1 (GLP-1) from L-cells (entero-endocrine) or promote the release of leptin hormone satiation in adipose tissues through G-protein receptors, i.e., GPR-41/GPR-43. Dietary fibers are the components of foods that influence AIM and produce SCFAs, which may be offering beneficial effects on T2D. This review addresses the effectiveness of SCFAs in modulating gut AIM in the fermentation of dietary fiber and their worth against T2D.

Keywords: dietary fibers, intestinal microbiota, short-chain fatty acids, fermentation, type 2 diabetes

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Authors: Ogbonna Olelewe

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This quality improvement project seeks to address the background and significance of promoting antidepressant (AD) medication adherence to reduce depression symptoms in patients diagnosed with major depression. This project aims to substantiate using daily encrypted short message service (SMS) text reminders to take prescribed antidepressant medications with the goal of increasing medication adherence to reduce depression scores in patients diagnosed with major depression, thereby preventing relapses and increasing remission rates. Depression symptoms were measured using the Patient Health Questionnaire-9 (PHQ-9) scale. The PHQ-9 provides a total score of depression symptoms from mild to severe, ranging from 0 to 27. A -pretest/post-test design was used, with a convenience sample size of 35 adult patients aged 18 years old to 45 years old, diagnosed with MDD, and prescribed at least one antidepressant for one year or more. Pre- and post-test PHQ-9 scores were conducted to compare depression scores before and after the four-week intervention period. The results indicated improved post-intervention PHQ-9 scores, improved AD medication adherence, and a significant reduction in depression symptoms.

Keywords: major depressive disorder, antidepressants, short message services, text reminders, Medication adherence/non-adherence, Patient Health Questionnaire 9

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Authors: D. S. Mohale, A.V. Chandewar

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Study was undertaken to investigate the effect of imipramine on various biochemical parameters and oxidative stress markers in short and long term depression on rats. Rats were subjected for short (21 days) and long term (84 days) social isolation for and checked for depression on force swim test and tail suspension method. Various markers of oxidative stress like lipid peroxidation (LPO), reduced glutathione (GSH), Supersoxide dismutase (SOD), catalase (CAT) and biochemical parameters like Serum glutamate oxaloacetate transaminase (SGOT), Serum glutamate pyruate transaminase (SGPT), and blood glucose were determined in depressed, control, imipramine and Vitamin E treated group. The rats displayed an increase in depression on force swim test and tail suspension method relative to control. There was significant increase in the level of LPO and decrease in the levels of GSH, SOD and CAT after short and long term depression. Increased oxidative stress in depression which may leads to alteration of biochemical parameters. Treatment with imipramine an tricyclic antidepressant significantly decreases in level of LPO, SGOT, SGPT and increase in the levels of GSH, SOD and CAT in long term depression.

Keywords: depression, oxidative stress, lipid peroxidation, reduced glutathione

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Authors: Zbigniew Olczykowski

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The paper presents the impact of work on the electric arc furnace power grid. The arc furnace operating will be modeled at different power conditions of steelworks. The paper will describe how to determine the increase in voltage fluctuations caused by working in parallel arc furnaces. The analysis of indicators characterizing the quality of electricity recorded during several cycles of measurement made at the same time at three points grid, with different power and different short-circuit rated voltage, will be carried out. The measurements analysis presented in this paper were conducted in the mains of one of the Polish steel. The indicators characterizing the quality of electricity was recorded during several cycles of measurement while making measurements at three points of different power network short-circuit power and various voltage ratings. Measurements of power quality indices included the one-week measurement cycles in accordance with the EN-50160. Data analysis will include the results obtained during the simultaneous measurement of three-point grid. This will determine the actual propagation of interference generated by the device. Based on the model studies and measurements of quality indices of electricity we will establish the effect of a specific arc on the mains. The short-circuit power network’s minimum value will also be estimated, this is necessary to limit the voltage fluctuations generated by arc furnaces.

Keywords: arc furnaces, long-term flicker, measurement and modeling of power quality, voltage fluctuations

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Authors: Xiang-Yao Zheng, Jen-Cheng Wang, Joe-Air Jiang

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Improving the line ampacity while using existing power grids is an important issue that electricity dispatchers are now facing. Using the information provided by the dynamic thermal rating (DTR) of transmission lines, an overhead power grid can operate safely. However, dispatchers usually lack real-time DTR information. Thus, this study proposes a long-short-term memory (LSTM)-based method, which is one of the neural network models. The LSTM-based method predicts the DTR of lines using the weather data provided by Central Weather Bureau (CWB) of Taiwan. The possible thermal bottlenecks at different locations along the line and the margin of line ampacity can be real-time determined by the proposed LSTM-based prediction method. A case study that targets the 345 kV power grid of TaiPower in Taiwan is utilized to examine the performance of the proposed method. The simulation results show that the proposed method is useful to provide the information for the smart grid application in the future.

Keywords: electricity dispatch, line ampacity prediction, dynamic thermal rating, long-short-term memory neural network, smart grid

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Authors: Yanmin Zhao, Siu Ming Yiu

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To claim the ownership for an executable program is a non-trivial task. An emerging direction is to add a watermark to the program such that the watermarked program preserves the original program’s functionality and removing the watermark would heavily destroy the functionality of the watermarked program. In this paper, the first watermarking signature scheme with the watermark and the constraint function hidden in the symmetric key setting is constructed. The scheme uses well-known techniques of lattice trapdoors and a lattice evaluation. The watermarking signature scheme is unforgeable under the Short Integer Solution (SIS) assumption and satisfies other security requirements such as the unremovability security property.

Keywords: short integer solution (SIS) problem, symmetric-key setting, watermarking schemes, watermarked signatures

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Authors: Edison E. Haro, Akindele G. Odeshi, Jerzy A. Szpunar

Abstract:

Hybrid bio-composites are developed for use in protective armor through positive hybridization offered by reinforcement of high-density polyethylene (HDPE) with Kevlar short fibers and palm wood micro-fillers. The manufacturing process involved a combination of extrusion and compression molding techniques. The mechanical behavior of Kevlar fiber reinforced HDPE with and without palm wood filler additions are compared. The effect of the weight fraction of the added palm wood micro-fillers is also determined. The Young modulus was found to increase as the weight fraction of organic micro-particles increased. However, the flexural strength decreased with increasing weight fraction of added micro-fillers. The interfacial interactions between the components were investigated using scanning electron microscopy. The influence of the size, random alignment and distribution of the natural micro-particles was evaluated. Ballistic impact and dynamic shock loading tests were performed to determine the optimum proportion of Kevlar short fibers and organic micro-fillers needed to improve impact strength of the HDPE. These results indicate a positive hybridization by deposition of organic micro-fillers on the surface of short Kevlar fibers used in reinforcing the thermoplastic matrix leading to enhancement of the mechanical strength and dynamic impact behavior of these materials. Therefore, these hybrid bio-composites can be promising materials for different applications against high velocity impacts.

Keywords: hybrid bio-composites, organic nano-fillers, dynamic shocking loading, ballistic impacts, energy absorption

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