Search results for: reducing power

Authors: Stefan K. Behfar

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The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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Authors: Ahlam Elkilani, Bayan Elsheikh Ali, Rasha Abu Romman, Amjed Al-mousa, Belal Sababha

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The amount of energy the world uses doubles every 20 years. Green homes play an important role in reducing the residential energy demand. This paper presents a platform that is intended to learn the behavior of home residents and build a profile about their habits and actions. The proposed resident aware home controller intervenes in the operation of home appliances in order to save energy without compromising the convenience of the residents. The presented platform can be used to simulate the actions and movements happening inside a home. The paper includes several optimization techniques that are meant to save energy in the home. In addition, several test scenarios are presented that show how the controller works. Moreover, this paper shows the computed actual savings when each of the presented techniques is implemented in a typical home. The test scenarios have validated that the techniques developed are capable of effectively saving energy at homes.

Keywords: green home, resident aware, resident profile, activity learning, machine learning

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Authors: Ahmed Al-Saadi, Ali Hassanpour, Tariq Mahmud

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The main objective of this study is to investigate ways to reduce the aerodynamic drag coefficient and to increase the stability of the full-size Sport Utility Vehicle using three-dimensional Computational Fluid Dynamics (CFD) simulation. The baseline model in the simulation was the Land Rover Discovery 4. Many aerodynamic devices and external design modifications were used in this study. These reduction aerodynamic techniques were tested individually or in combination to get the best design. All new models have the same capacity and comfort of the baseline model. Uniform freestream velocity of the air at inlet ranging from 28 m/s to 40 m/s was used. ANSYS Fluent software (version 16.0) was used to simulate all models. The drag coefficient obtained from the ANSYS Fluent for the baseline model was validated with experimental data. It is found that the use of modern aerodynamic add-on devices and modifications has a significant effect in reducing the aerodynamic drag coefficient.

Keywords: aerodynamics, RANS, sport utility vehicle, turbulent flow

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Authors: Tanveer Beg, Yasir H. Siddique, Gulshan Ara, Asfar S. Azmi, Mohammad Afzal

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Doxorubicin is a well-known DNA intercalating chemotherapy drug that is widely used for treatment of different cancers. Its clinical utility is limited due to the observed genotoxic side effects on healthy cells suggesting that newer combination and genoprotective regimens are urgently needed for the management of doxorubicin chemotherapy. Some dietary phytochemicals are well known for their protective mechanism of action and genistein from soy is recognized as an anti-oxidant with similar properties. Therefore, the present study investigates the effect of genistein against the genotoxic doses of doxorubicin by assessing chromosomal aberrations, sister chromatid exchanges, cell cycle kinetics, cell viability, apoptosis, and DNA damage markers in cultured human lymphocytes. Our results reveal that genistein treatment significantly suppresses genotoxic damage induced by doxorubicin. It is concluded that genistein has the potential to reduce the genotoxicity induced by anti-cancer drugs, thereby reducing the chances of developing secondary tumors during the therapy.

Keywords: apoptosis, DNA damage markers, doxorubicin, genistein, genotoxicity, human lymphocyte culture

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Authors: N. Amruth Raj, Suja S. Nair

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The last six decades have borne witness to a radical change in the private sectors relationship with both the state and civil society. Firms have been increasingly called upon to adopt strategies beyond the financial aspects of their operations and consider the social and environmental impact of their business activities. In this context, many companies have modified their policies and activities and engaged into Corporate Social Responsibility (CSR) especially on Rural development in India. At the firm level, CSR is implemented through various practices, which aim to enhance the company’s social and environmental performance and may cover various topics. Examples of CSR practices are abundant in Andhra Pradesh relevant literature. For instance, in India especially at Andhra Pradesh companies like Amara Raaja requires from its suppliers to prohibit child labour, Nagarjuna Cements applies a series of programs for reducing its CO2 emissions, LANCO group of Industries addresses health and safety issues in the workplace whereas GVK works limited has adopted a series of policies for addressing human rights and environmental abuse related to its operations.

Keywords: CSR, limitations, need, objectives, rural development

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Authors: Ayon Mukherjee

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Covariate-adjusted response-adaptive (CARA) designs use the available responses to skew the treatment allocation in a clinical trial in towards treatment found at an interim stage to be best for a given patient's covariate profile. Extensive research has been done on various aspects of CARA designs with the patient responses assumed to follow a parametric model. However, ranges of application for such designs are limited in real-life clinical trials where the responses infrequently fit a certain parametric form. On the other hand, robust estimates for the covariate-adjusted treatment effects are obtained from the parametric assumption. To balance these two requirements, designs are developed which are free from distributional assumptions about the survival responses, relying only on the assumption of proportional hazards for the two treatment arms. The proposed designs are developed by deriving two types of optimum allocation designs, and also by using a distribution function to link the past allocation, covariate and response histories to the present allocation. The optimal designs are based on biased coin procedures, with a bias towards the better treatment arm. These are the doubly-adaptive biased coin design (DBCD) and the efficient randomized adaptive design (ERADE). The treatment allocation proportions for these designs converge to the expected target values, which are functions of the Cox regression coefficients that are estimated sequentially. These expected target values are derived based on constrained optimization problems and are updated as information accrues with sequential arrival of patients. The design based on the link function is derived using the distribution function of a probit model whose parameters are adjusted based on the covariate profile of the incoming patient. To apply such designs, the treatment allocation probabilities are sequentially modified based on the treatment allocation history, response history, previous patients’ covariates and also the covariates of the incoming patient. Given these information, an expression is obtained for the conditional probability of a patient allocation to a treatment arm. Based on simulation studies, it is found that the ERADE is preferable to the DBCD when the main aim is to minimize the variance of the observed allocation proportion and to maximize the power of the Wald test for a treatment difference. However, the former procedure being discrete tends to be slower in converging towards the expected target allocation proportion. The link function based design achieves the highest skewness of patient allocation to the best treatment arm and thus ethically is the best design. Other comparative merits of the proposed designs have been highlighted and their preferred areas of application are discussed. It is concluded that the proposed CARA designs can be considered as suitable alternatives to the traditional balanced randomization designs in survival trials in terms of the power of the Wald test, provided that response data are available during the recruitment phase of the trial to enable adaptations to the designs. Moreover, the proposed designs enable more patients to get treated with the better treatment during the trial thus making the designs more ethically attractive to the patients. An existing clinical trial has been redesigned using these methods.

Keywords: censored response, Cox regression, efficiency, ethics, optimal allocation, power, variability

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Authors: Shehret Tilvaldyev, Jorge Flores-Garay, Alfredo Villanueva, Erwin Martinez, Lazaro Rico

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The efficiency of modern transportation is severely compromised by the prevalence of turbulent drag. The high level of turbulent skin-friction occurring, e.g., on the surface of an aircraft, automobiles or the carriage of a high-speed train, is responsible for excess fuel consumption and increased carbon emissions. The environmental, political, and economic pressure to improve fuel efficiency and reduce carbon emissions associated with transportation means that reducing turbulent skin-friction drag is a pressing engineering problem. The dynamic pressure of subsonic airflow around solid objects creates lift, but also induces drag force. This paper is presenting the results of laboratory experiments, investigating appearance and magnitude of dynamic pressure in micro scale of subsonic air flow around right cylinder and symmetrical airfoil.

Keywords: airflow, dynamic pressure, micro scale, symmetric object

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Authors: Tarcisio F. Leao, Bruno Utiyama, Jeison Fonseca, Eduardo Bock, Aron Andrade

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This work presents a blood flow estimator based in Look-Up-Table (LUT) for control of Left Ventricular Assist Device (LVAD). This device has been used as bridge to transplantation or as destination therapy to treat patients with heart failure (HF). Destination Therapy application requires a high performance LVAD; thus, a stable control is important to keep adequate interaction between heart and device. LVAD control provides an adequate cardiac output while sustaining an appropriate flow and pressure blood perfusion, also described as physiologic control. Because thrombus formation and system reliability reduction, sensors are not desirable to measure these variables (flow and pressure blood). To achieve this, control systems have been researched to estimate blood flow. LVAD used in the study is composed by blood centrifugal pump, control, and power supply. This technique used pump and actuator (motor) parameters of LVAD, such as speed and electric current. Estimator relates electromechanical torque (motor or actuator) and hydraulic power (blood pump) via LUT. An in vitro Mock Loop was used to evaluate deviations between blood flow estimated and actual. A solution with glycerin (50%) and water was used to simulate the blood viscosity with hematocrit 45%. Tests were carried out with variation hematocrit: 25%, 45% and 58% of hematocrit, or 40%, 50% and 60% of glycerin in water solution, respectively. Test with bovine blood was carried out (42% hematocrit). Mock Loop is composed: reservoir, tubes, pressure and flow sensors, and fluid (or blood), beyond LVAD. Estimator based in LUT is patented, number BR1020160068363, in Brazil. Mean deviation is 0.23 ± 0.07 L/min for mean flow estimated. Larger mean deviation was 0.5 L/min considering hematocrit variation. This estimator achieved deviation adequate for physiologic control implementation. Future works will evaluate flow estimation performance in control system of LVAD.

Keywords: blood pump, flow estimator, left ventricular assist device, look-up-table

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Authors: Wen-Hsi Lee, C.G. Kao

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In this study, Cu paste was prepared and printed with narrow line screen printing process on polycrystalline Si solar cell which has already finished the back Al printing and deposition of double anti-reflection coatings (DARCs). Then, two-step firing process was applied to sinter the front electrode and obtain the ohmic contact between front electrode and solar cell. The first step was in air atmosphere. In this process, PbO-based glass frit etched the DARCs and Ag recrystallized at the surface of Si, constructing the preliminary contact. The second step was in reducing atmosphere. In this process, CuO reduced to Cu and sintered. Besides, Ag nanoparticles recrystallized in the glass layer at interface due to the interactions between H2, Ag and PbO-based glass frit and the volatility of Pb, constructing the ohmic contact between electrode and solar cell. By experiment and analysis, reaction mechanism in each stage was surmised, and it was also proven that ohmic contact and good sheet resistance for front electrode could both be obtained by applying newly-invented paste and process.

Keywords: front electrode, solar cell, ohmic contact, screen printing, paste

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Authors: Hao-Hsiang Ku, Ching-Ho Chi

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Big data applications have become an imperative for many fields. Many researchers have been devoted into increasing correct rates and reducing time complexities. Hence, the study designs and proposes an Ontology-based backpropagation neural network classification and reasoning strategy for NoSQL big data applications, which is called ON4NoSQL. ON4NoSQL is responsible for enhancing the performances of classifications in NoSQL and SQL databases to build up mass behavior models. Mass behavior models are made by MapReduce techniques and Hadoop distributed file system based on Hadoop service platform. The reference engine of ON4NoSQL is the ontology-based backpropagation neural network classification and reasoning strategy. Simulation results indicate that ON4NoSQL can efficiently achieve to construct a high performance environment for data storing, searching, and retrieving.

Keywords: Hadoop, NoSQL, ontology, back propagation neural network, high distributed file system

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Authors: Ebrahim Farahmand, Ali Mahani

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Wireless sensor networks (WSNs) can facilitate continuous monitoring of patients and increase early detection of emergency conditions and diseases. High density WSNs helps us to accurately monitor a remote environment by intelligently combining the data from the individual nodes. Due to energy capacity limitation of sensors, enhancing the lifetime and the reliability of WSNs are important factors in designing of these networks. The clustering strategies are verified as effective and practical algorithms for reducing energy consumption in WSNs and can tackle WSNs limitations. In this paper, an Energy-efficient weight-based Clustering Protocol (EWCP) is presented. Artificial retina is selected as a case study of WSNs applied in body sensors. Cluster heads’ (CHs) selection is equipped with energy efficient parameters. Moreover, cluster members are selected based on their distance to the selected CHs. Comparing with the other benchmark protocols, the lifetime of EWCP is improved significantly.

Keywords: WSN, healthcare monitoring, weighted based clustering, lifetime

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Authors: Fuad M. Alkoot

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Different experimental technologies such as microarray sequencing have been proposed to generate high-resolution genetic data, in order to understand the complex dynamic interactions between complex diseases and the biological system components of genes and gene products. However, the generated samples have a very large dimension reaching thousands. Therefore, hindering all attempts to design a classifier system that can identify diseases based on such data. Additionally, the high overlap in the class distributions makes the task more difficult. The data we experiment with is generated for the identification of autism. It includes 142 samples, which is small compared to the large dimension of the data. The classifier systems trained on this data yield very low classification rates that are almost equivalent to a guess. We aim at reducing the data dimension and improve it for classification. Here, we experiment with applying a multistage PCA on the genetic data to reduce its dimensionality. Results show a significant improvement in the classification rates which increases the possibility of building an automated system for autism detection.

Keywords: PCA, gene expression, dimensionality reduction, classification, autism

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Authors: Bingxi Huang, Yiqing Li, Marek Morzynski, Bernd R. Noack

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We propose a Kriging-based global optimization method for active flow control with multiple actuation parameters. This method is designed to converge quickly and avoid getting trapped into local minima. We follow the model-free explorative gradient method (EGM) to alternate between explorative and exploitive steps. This facilitates a convergence similar to a gradient-based method and the parallel exploration of potentially better minima. In contrast to EGM, both kinds of steps are performed with Kriging surrogate model from the available data. The explorative step maximizes the expected improvement, i.e., favors regions of large uncertainty. The exploitive step identifies the best location of the cost function from the Kriging surrogate model for a subsequent weight-biased linear-gradient descent search method. To verify the effectiveness and robustness of the improved Kriging-based optimization method, we have examined several comparative test problems of varying dimensions with limited evaluation budgets. The results show that the proposed algorithm significantly outperforms some model-free optimization algorithms like genetic algorithm and differential evolution algorithm with a quicker convergence for a given budget. We have also performed direct numerical simulations of the fluidic pinball (N. Deng et al. 2020 J. Fluid Mech.) on three circular cylinders in equilateral-triangular arrangement immersed in an incoming flow at Re=100. The optimal cylinder rotations lead to 44.0% net drag power saving with 85.8% drag reduction and 41.8% actuation power. The optimal results for active flow control based on this configuration have achieved boat-tailing mechanism by employing Coanda forcing and wake stabilization by delaying separation and minimizing the wake region.

Keywords: direct numerical simulations, flow control, kriging, stochastic optimization, wake stabilization

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Authors: Hasan Al Bashar Abul Ulayee, AKM Saifun Nabi, MD Mesbah-Ul-Awal

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Alert system for disaster management is common now a day and can play a vital role reducing devastation and saves lives and costs. An alert in right time can save thousands of human life, help to take shelter, manage other assets including live stocks and above all, a right time alert will help to take preparation to face and early recovery of the situation. In a country like Bangladesh where populations is more than 170 million and always facing different types of natural calamities and disasters, an early right time alert is very effective and implementation of alert system is challenging. The challenge comes from the time constraint of alerting the huge number of population. The other method of existing disaster management pre alert is traditional, sequential and non-selective so efficiency is not good enough. This paper describes a way by which alert can be provided to maximum number of people within the short time bound using parallel processing as well as random selection of selective target audience.

Keywords: alert system, Bangladesh, disaster management, parallel processing, SMS

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Authors: Furqan M. Kadhum, Asmaa A. Hussein, Maysaa Ch. Hatem

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Hyaluronidase enzyme was purified from the clinical isolate Staphyloccus aureus in three purification steps, first by precipitation with 90% saturated ammonium sulfate, ion exchange chromatography on DEAE-Cellulose, and gel filtration chromatography throughout Sephacryl S-300. Specific activity of the purified enzyme was reached 930 U/mg protein with 7.4 folds of purification and 46.5% recovery. The enzyme has an average molecular weight of about 69 kDa, with an optimum pH of enzyme activity and stability at pH 7, also the optimum temperature for activity was 37oC. The enzyme was stable with full activity at a temperature ranged between 30-40 oC. Metal ions showed variable inhibitory degree with the strongest effect for Fe+3, however, the chelating and reducing agents had no or little effects. Cytotoxic studies for purified and crude hyaluronidase against cancer cell Hep G2 type at different enzyme concentrations and exposure times showed that the inhibition effect of both crude and purified enzyme increased by increasing the enzyme concentration with no change was observed at 24hr, while at 48 and 72 hrs the same inhibition rate were observed for purified enzyme and differ for the crude filtrate.

Keywords: hyaluronidase, S. aureus, metal ions, cytotoxicity

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Authors: Same Noel Ngando, Yakub Abdulfatai Olatunji

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Renewable energy micro-grids, such as those powered by solar or wind energy, are often intermittent in nature. This means that the amount of energy generated by these systems can vary depending on weather conditions or other factors, which can make it difficult to ensure a steady supply of power. To address this issue, energy storage systems have been developed to increase the reliability of renewable energy micro-grids. Battery systems have been the dominant energy storage technology for renewable energy micro-grids. Batteries can store large amounts of energy in a relatively small and compact package, making them easy to install and maintain in a micro-grid setting. Additionally, batteries can be quickly charged and discharged, allowing them to respond quickly to changes in energy demand. However, the process involved in recycling batteries is quite costly and difficult. An alternative energy storage system that is gaining popularity is hydrogen storage. Hydrogen is a versatile energy carrier that can be produced from renewable energy sources such as solar or wind. It can be stored in large quantities at low cost, making it suitable for long-distance mass storage. Unlike batteries, hydrogen does not degrade over time, so it can be stored for extended periods without the need for frequent maintenance or replacement, allowing it to be used as a backup power source when the micro-grid is not generating enough energy to meet demand. When hydrogen is needed, it can be converted back into electricity through a fuel cell. Energy consumption data is got from a particular residential area in Daegu, South Korea, and the data is processed and analyzed. From the analysis, the total energy demand is calculated, and different hybrid energy system configurations are designed using HOMER Pro (Hybrid Optimization for Multiple Energy Resources) and MATLAB software. A techno-economic and environmental comparison and life cycle assessment (LCA) of the different configurations using battery and hydrogen as storage systems are carried out. The various scenarios included PV-hydrogen-grid system, PV-hydrogen-grid-wind, PV-hydrogen-grid-biomass, PV-hydrogen-wind, PV-hydrogen-biomass, biomass-hydrogen, wind-hydrogen, PV-battery-grid-wind, PV- battery -grid-biomass, PV- battery -wind, PV- battery -biomass, and biomass- battery. From the analysis, the least cost system for the location was the PV-hydrogen-grid system, with a net present cost of about USD 9,529,161. Even though all scenarios were environmentally friendly, taking into account the recycling cost and pollution involved in battery systems, all systems with hydrogen as a storage system produced better results. In conclusion, hydrogen is becoming a very prominent energy storage solution for renewable energy micro-grids. It is easier to store compared with electric power, so it is suitable for long-distance mass storage. Hydrogen storage systems have several advantages over battery systems, including flexibility, long-term stability, and low environmental impact. The cost of hydrogen storage is still relatively high, but it is expected to decrease as more hydrogen production, and storage infrastructure is built. With the growing focus on renewable energy and the need to reduce greenhouse gas emissions, hydrogen is expected to play an increasingly important role in the energy storage landscape.

Keywords: renewable energy systems, microgrid, hydrogen production, energy storage systems

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Authors: Danielle Klassen, Reiko Yeap, Margo Schmitt-Boshnick, Scott Oddie

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The development of the 7-week Alberta Happiness Basics program was initiated in 2010 in response to the need for community mental health programming. This provincial wide program aims to increase overall happiness and reduce negative thoughts and feelings through a positive psychology intervention. While the 7-week program has proven effective, a shortened 4-week program has additionally been developed to address client needs. In this study, participants were interviewed to determine if the 4- and 7-week programs had similar success of producing lasting behavior change at 3, 6, and 9 months post-program. A health quality of life (HQOL) measure was also used to compare the two programs and examine patient outcomes. Quantitative and qualitative analysis showed significant improvements in HQOL and sustainable behavior change for both programs. Findings indicate that the shorter, patient-centered program was effective in increasing happiness and reducing negative thoughts and feelings.

Keywords: primary care, mental health, depression, short duration

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Authors: K. N. Kipreou, E. Efthmiadou, G. Kordas

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Biofouling represents one of the most crucial problems in the present maritime industries when its control still challenges the researchers all over the world. The present work is referred to the synthesis and characterization CeMo and Cu2O nanocontainers by using a wide range of techniques including scanning electron microscopy (SEM), X-ray diffraction (XRD) and thermogravimetric analysis (TGA) for marine applications. The above nanosystems will be loaded with active monomers and corrosion rendering healing ability to marine paints. The objective of this project is their ability for self-healing, self-polishing and finally for anti-corrosion activity. One of the driving forces for the exploration of CeMo, is the unique anticorrosive behavior, which will be confirmed by the electrochemistry methodology. It has be highlighted that the nanocontainers of Cu2O with the appropriate antibacterial inhibitor will improve the hydrophobicity and the morphology of the coating surfaces reducing the water friction. In summary, both novel nanoc will increase the lifetime of the paints releasing the antifouling agent in a control manner.

Keywords: marinepaints, nanocontainer, antifouling, anticorrosion, copper, electrochemistry, coating, biofouling, inhibitors, copper oxide, coating, SEM

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Authors: Yen-Po Wang, Ming-Chih Huang, Ming-Lian Chang

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A scheme integrated with deterministic–stochastic subspace system identification and the method of damage localization vector is proposed in this study for damage detection of structures based on seismic response data. A series of shaking table tests using a five-storey steel frame has been conducted in National Center for Research on Earthquake Engineering (NCREE), Taiwan. Damage condition is simulated by reducing the cross-sectional area of some of the columns at the bottom. Both single and combinations of multiple damage conditions at various locations have been considered. In the system identification analysis, either full or partial observation conditions have been taken into account. It has been shown that the damaged stories can be identified from global responses of the structure to earthquakes if sufficiently observed. In addition to detecting damage(s) with respect to the intact structure, identification of new or extended damages of the as-damaged (ill-conditioned) counterpart has also been studied. The proposed scheme proves to be effective.

Keywords: damage locating vectors, deterministic-stochastic subspace system, shaking table tests, system identification

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Authors: Ursula Das, Manavjit Singh Dhindsa, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

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Wildland fires, also known as forest fires or wildfires, are exhibiting an alarming surge in frequency in recent times, further adding to its perennial global concern. Forest fires often lead to devastating consequences ranging from loss of healthy forest foliage and wildlife to substantial economic losses and the tragic loss of human lives. Despite the existence of substantial literature on the detection of active forest fires, numerous potential research avenues in forest fire management, such as preventative measures and ancillary effects of forest fires, remain largely underexplored. This paper undertakes a systematic review of these underexplored areas in forest fire research, meticulously categorizing them into distinct phases, namely pre-fire, during-fire, and post-fire stages. The pre-fire phase encompasses the assessment of fire risk, analysis of fuel properties, and other activities aimed at preventing or reducing the risk of forest fires. The during-fire phase includes activities aimed at reducing the impact of active forest fires, such as the detection and localization of active fires, optimization of wildfire suppression methods, and prediction of the behavior of active fires. The post-fire phase involves analyzing the impact of forest fires on various aspects, such as the extent of damage in forest areas, post-fire regeneration of forests, impact on wildlife, economic losses, and health impacts from byproducts produced during burning. A comprehensive understanding of the three stages is imperative for effective forest fire management and mitigation of the impact of forest fires on both ecological systems and human well-being. Artificial intelligence and machine learning (AI/ML) methods have garnered much attention in the cyber-physical systems domain in recent times leading to their adoption in decision-making in diverse applications including disaster management. This paper explores the current state of AI/ML applications for managing the activities in the aforementioned phases of forest fire. While conventional machine learning and deep learning methods have been extensively explored for the prevention, detection, and management of forest fires, a systematic classification of these methods into distinct AI research domains is conspicuously absent. This paper gives a comprehensive overview of the state of forest fire research across more recent and prominent AI/ML disciplines, including big data, classical machine learning, computer vision, explainable AI, generative AI, natural language processing, optimization algorithms, and time series forecasting. By providing a detailed overview of the potential areas of research and identifying the diverse ways AI/ML can be employed in forest fire research, this paper aims to serve as a roadmap for future investigations in this domain.

Keywords: artificial intelligence, computer vision, deep learning, during-fire activities, forest fire management, machine learning, pre-fire activities, post-fire activities

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Authors: Hanan Alsaeid Alshenawy

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Background: Cervical dysplasia, which is potentially precancerous, has increased in young women. Detection of cervical is important for reducing morbidity and mortality in cervical cancer. This study analyzes the immunohistochemical expression of p16, HPV L1 capsid protein and Ki67 in cervical intraepithelial lesions and correlates them with lesion grade to develop a set of markers for diagnosis and detect the prognosis of cervical cancer precursors. Methods: 75 specimens were analyzed including 15 cases CIN 1, 28 CIN 2, 20 CIN 3, and 12 cervical squamous carcinoma, besides 10 normal cervical tissues. They were stained for p16, HPV L1 and Ki-67. Sensitivity, specificity, predictive values and accuracy were evaluated for each marker. Results: p16 expression increased during the progression from CIN 1 to carcinoma. HPV L1 positivity was detected in CIN 2 and decreased gradually as the CIN grade increased but disappear in carcinoma. Strong Ki-67 expression was observed with high grades CIN and carcinoma. p16, HPV L1 and Ki67 were sensitive but with variable specificity in detecting CIN lesions. Conclusions: p16, HPV L1 and Ki67 are useful set of markers in establishing the risk of high-grade CIN. They complete each other to reach accurate diagnosis and prognosis.

Keywords: p16, HPV L1, Ki67, CIN, cervical carcinoma

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Authors: Medhanie Gebremedhin Gebru, Alex Schechter

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Dimethyl ether (DME) possesses several advantages over other small organic molecules such as methanol, ethanol, and ammonia in terms of providing higher energy density, being less toxic, and having lower Nafion membrane crossover. However, the absence of an active and stable catalyst has been the bottleneck that hindered the commercialization of direct DME fuel cells. A Vulcan XC72 carbon-supported ternary metal catalyst, Pt₃Pd₃Sn₂/C is reported to have yielded the highest specific power density (90 mW mg-¹PGM) as compared to other catalysts tested fordirect DME fuel cell (DDMEFC). However, the micropores and sulfur groups present in Vulcan XC72 hinder the fuel utilization by causing Pt agglomeration and sulfur poisoning. Vulcan XC72 having a high carbon sp³ hybridization content, is also prone to corrosion. Therefore, carbon supports such as multi-walled carbon nanotube (MWCNT), black pearl 2000 (BP2000), and their cold N2 plasma-treated counterpartswere tested to further enhance the activity of the catalyst, and the outputs with these carbons were compared with the originally used support. Detailed characterization of the pristine and carbon supports was conducted. Electrochemical measurements in three-electrode cells and laboratory prototype fuel cells were conducted.Pt₃Pd₃Sn₂/BP2000 exhibited excellent performance in terms of electrochemical active surface area (ECSA), peak current density (jp), and DME oxidation charge (Qoxi). The effect of the plasma activation on the activity improvement was observed only in the case of MWCNT while having little or no effect on the other carbons. A Pt₃Pd₃Sn₂ supported on the optimized mixture of carbons containing 75% plasma-activated MWCNT and 25% BP2000 (Pt₃Pd₃Sn₂/75M25B) provided the highest reported power density of 117 mW mg-1PGM using an anode loading of1.55 mgPGMcm⁻².

Keywords: DME, DDMEFC, ternary metal catalyst, carbon support, plasma activation

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Authors: Steven D. Capener

Abstract:

The 1997 Asian financial crisis was a watershed event in Korea as it necessitated changes that begin an unravelling of many of the norms and traditions that had served to underpin society. Divorce skyrocketed; the era of lifetime employment was over; women came out the home to become, in many cases, the main breadwinners; competitive forces were exacerbated; and traditional sources of authority began to crumble. All of these changes weekend the power to structure human relations of the Confucian Three Bonds and Five Relationships (삼강오륜). Since then, this “de-confucianization” has only become more pronounced with women increasingly refusing to marry, partly in protest to what they perceive as entrenched gender inequality, married couples eschewing childbirth resulting in the lowest birthrate in the world, and diminishing inheritances eroding the traditionally strong sense of filial piety (효) of children toward parents. The result of all this can be seen in the continued weakening or outright crumbling of the hierarchies codified in the Three Bonds and Five Relationship, which have served as a social template in Korea for centuries. In his 2004 work “Oppa Came Back,” writer Kim Yong Ha depicts what he apparently sees as the “post-Confucian” family in a wickedly funny portrayal of what Korean society could look like if traditional bulwarks of prescriptive values suddenly collapse and are not replaced with tenable alternatives. In the short story, Kim subverts all the traditional hierarchies while leaving the desire to dominate these hierarchies intact. This produces the picture of a Korean family governed by the new values of money and physical power. After lying out what can be identified as major cultural changes in what could be called “traditional” society,” the article uses a close reading of Kim’s story for its implications regarding a possible new, dysfunctional version of Korean society. It seems apparent that Kim’s story is a cautionary tale of the pitfalls that lie athwart the late-modern Korean landscape. These changes have important implications in the areas of education and socio-political philosophy. The conclusion focuses on possible alternatives to this post-Confucian conundrum.

Keywords: post-confucian, three bonds and five relationships, traditional society, hierarchies

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Authors: Nikhil Kumar, Asish Bandyopadhyay

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Laser welding process is a capable technology for forming the automobile, microelectronics, marine and aerospace parts etc. In the present work, a mathematical and statistical approach is adopted to study the laser welding of AISI 304 stainless steel. A robotic control 500 W pulsed Nd:YAG laser source with 1064 nm wavelength has been used for welding purpose. Butt joints are made. The effects of welding parameters, namely; laser power, scanning speed and pulse width on the seam width and depth of penetration has been investigated using the empirical models developed by response surface methodology (RSM). Weld quality is directly correlated with the weld geometry. Twenty sets of experiments have been conducted as per central composite design (CCD) design matrix. The second order mathematical model has been developed for predicting the desired responses. The results of ANOVA indicate that the laser power has the most significant effect on responses. Microstructural analysis as well as hardness of the selected weld specimens has been carried out to understand the metallurgical and mechanical behaviour of the weld. Average micro-hardness of the weld is observed to be higher than the base metal. Higher hardness of the weld is the resultant of grain refinement and δ-ferrite formation in the weld structure. The result suggests that the lower line energy generally produce fine grain structure and improved mechanical properties than the high line energy. The combined effects of input parameters on responses have been analyzed with the help of developed 3-D response surface and contour plots. Finally, multi-objective optimization has been conducted for producing weld joint with complete penetration, minimum seam width and acceptable welding profile. Confirmatory tests have been conducted at optimum parametric conditions to validate the applied optimization technique.

Keywords: ANOVA, laser welding, modeling and optimization, response surface methodology

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Authors: Ahmad Abdul-Razzak Aboudi Al-Issa

Abstract:

Thermal is the main important aspect in any hydraulic system since it is affected on the hydraulic system performance. Therefore must be simulated the hydraulic system -that was designed- in this aspect before constructing it. In this study, an existed expert system was using to simulate the thermal aspect of a designed hydraulic system that will be used in an industrial field. The expert system which is used in this study is (Hydraulic System Calculations), and its symbol (HSC). HSC had been designed and coded in an interactive program userfriendly named (Microsoft Visual Basic 2010).

Keywords: fluid power, hydraulic system, thermal and hydrodynamic, expert system

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Authors: Young Nam Chun, Mun Sup Lim

Abstract:

Carbon dioxide and methane, the major components of biomass pyrolysis/gasification gas and biogas, top the list of substances that cause climate change, but they are also among the most important renewable energy sources in modern society. The purpose of this study is to convert carbon dioxide and methane into high-quality energy using char and commercial activated carbon obtained from biomass pyrolysis as a microwave receptor. The methane reforming process produces hydrogen and carbon. This carbon is deposited in the pores of the microwave receptor and lowers catalytic activity, thereby reducing the methane conversion rate. The deposited carbon was removed by carbon gasification due to the supply of carbon dioxide, which solved the problem of microwave receptor inactivity. In particular, the conversion rate remained stable at over 90% when the ratio of carbon dioxide to methane was 1:1. When the reforming results of carbon dioxide and methane were compared after fabricating nickel and iron catalysts using commercial activated carbon as a carrier, the conversion rate was higher in the iron catalyst than in the nickel catalyst and when no catalyst was used. 

Keywords: microwave, gas reforming, greenhouse gas, microwave receptor, catalyst

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Authors: Adamnesh A. Bogale, Dorte Thorsen

Abstract:

This paper aims to learn how children/siblings left behind due to parental migration experience care and the effects of the separation. It also aims to unpack the experiences of youth migrants in rural Ethiopia. It focuses specifically on how children and youth are affected in order to highlight in which areas intervention can enhance or inadvertently undermine the development impact of migration on young people. Based on a qualitative study in South Wollo, Ethiopia, which was undertaken in three stages in 2017-19 and involved 34 households and a number of key informants, the analysis offers insights into how migration contributes to household sustainability and, in the process, alters intergenerational relationships and dynamics. Contemporary migration in Ethiopia is complex and highly gendered. For young women, the migration corridor from Ethiopia to the Middle East is the most important, whereas young men mostly engage in local migration or travel to South Africa or Sudan. Arguing that children and youths’ experience of migration must be understood in the context of the moral, affective, and material economies, the paper distinguishes between young people’s experiences of migration as children of migrants, as siblings of a migrant, and as migrants. The material shows that children and youths demonstrate different experiences in parental migration depending on age, care arrangement, and the ability to communicate with an absent mother. Migration has a different implication for younger siblings depending on their gender. The division of work and future responsibilities post marriage combine to disadvantage female siblings while male siblings are either unaffected or reaped the benefits of investments made with remittances. Finally, migration is a mechanism to change generational power relationships. As remitters, young migrants yield better recognition in the family, though not always to the degree that they can control the use of remittances. The power to make decisions is not tied only to material resources and the household; migration facilitates social change that opens space for young women to have more influence over their own lives.

Keywords: migration, youth, Ethiopia, generations

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Authors: Farnaz Dehkhoda

Abstract:

This study was conducted to compare the effectiveness of active and receptive music-therapy on anxiety in cancer patients undergoing chemotherapy or radiotherapy. 184 young adult patients, who were diagnosed with early stage cancer and were undergoing treatment, were divided into three groups. Two groups received music therapy as a parallel treatment and the third group was control group. In active music-therapy, a music specialist helped the patients to play guitar and sing. In the receptive music-therapy, patients preferred pre-recorded music played by MP3 player. The level of anxiety was measured by the Beck Anxiety Inventory as pre-test and post-test. ANCOVA revealed that both types of music-therapy reduced anxiety level of patients and the active music-therapy intervention found to be more effective. The results suggest that music-therapy can be applied as an intervention method contemporary with cancer medical treatment, for improving quality of life in cancer patients by reducing their anxiety.

Keywords: Anxiety, Cancer, Chemotherapy, Music-therapy

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Authors: Stephanos Vassilopoulos

Abstract:

Positive psychology interventions (PPIs) targeting optimism and hope in young children are scarce. This pilot study explored the feasibility and promise of the “Feel Good - Think Positive” intervention, a brief, manualized, multicomponent group PPI for young children. The intervention aimed to enhance participants’ optimism, hope, and self-esteem while reducing their anxiety levels. Forty-one students (Mage = 9.68, SD = 1.64) participated in the intervention and provided data on optimism, hope, self-esteem, and anxiety at baseline and after the intervention was concluded. Analyses showed a significant increase in optimism and self-esteem and a significant decrease in anxiety. However, no change was observed in hope levels. The results complement previous studies of school-based PPIs and hint at the promise of designing feasible interventions that can be easily incorporated into school curriculum and produce both a promoting and a remedial effect in young children.

Keywords: positive psychology intervention, positive education, hope, children

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Authors: Sung-Won Seo, Jang-Young Choi

Abstract:

The rare earth magnets used in synchronous generators offer many advantages, including high efficiency, greatly reduced the size, and weight. The permanent magnet linear synchronous generator (PMLSG) allows for direct drive without the need for a mechanical device. Therefore, the PMLSG is well suited to translational applications, such as wave energy converters and free piston energy converters. This manuscript compares the effects of different magnetization patterns on the characteristics of double-sided PMLSGs in slotless stator structures. The Halbach array has a higher flux density in air-gap than the Vertical array, and the advantages of its performance and efficiency are widely known. To verify the advantage of Halbach array, we apply a finite element method (FEM) and analytical method. In general, a FEM and an analytical method are used in the electromagnetic analysis for determining model characteristics, and the FEM is preferable to magnetic field analysis. However, the FEM is often slow and inflexible. On the other hand, the analytical method requires little time and produces accurate analysis of the magnetic field. Therefore, the flux density in air-gap and the Back-EMF can be obtained by FEM. In addition, the results from the analytical method correspond well with the FEM results. The model of the Halbach array reveals less copper loss than the model of the Vertical array, because of the Halbach array’s high output power density. The model of the Vertical array is lower core loss than the model of Halbach array, because of the lower flux density in air-gap. Therefore, the current density in the Vertical model is higher for identical power output. The completed manuscript will include the magnetic field characteristics and structural features of both models, comparing various results, and specific comparative analysis will be presented for the determination of the best model for application in a wave energy converting system.

Keywords: wave energy converter, permanent magnet linear synchronous generator, finite element method, analytical method

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