Search results for: volatile memory

Authors: M. Testa, L. Peotta, S. Giusiano, B. Lazzolino, U. Manera, A. Canosa, M. Grassano, F. Palumbo, A. Bombaci, S. Cabras, F. Di Pede, L. Solero, E. Matteoni, C. Moglia, A. Calvo, A. Chio

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Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease of adulthood, which primarily affects the central nervous system and is characterized by progressive bilateral degeneration of motor neurons. The degeneration processes in ALS extend far beyond the neurons of the motor system, and affects cognition, behaviour and language. To outline the prevalence of language deficits in an ALS cohort and explore their profile along with demographic and neuropsychological data. A full neuropsychological battery and language assessment was administered to 56 ALS patients. Neuropsychological assessment included tests of executive functioning, verbal fluency, social cognition and memory. Language was assessed using tests for verbal comprehension, production and pragmatics. Patients were cognitively classified following the Revised Consensus Criteria and divided in three groups showing different levels of language deficits: group 1 - no language deficit; group 2 - one language deficit; group 3 - two or more language deficits. Chi-square for independence and non-parametric measures to compare groups were applied. Nearly half of ALS-CN patients (48%) reported one language test under the clinical cut-off, and only 13% of patents classified as ALS-CI showed no language deficits, while the rest 87% of ALS-CI reported two or more language deficits. ALS-BI and ALS-CBI cases all reported two or more language deficits. Deficits in production and in comprehension appeared more frequent in ALS-CI patients (p=0.011, p=0.003 respectively), with a higher percentage of comprehension deficits (83%). Nearly all ALS-CI reported at least one deficit in pragmatic abilities (96%) and all ALS-BI and ALS-CBI patients showed pragmatic deficits. Males showed higher percentage of pragmatic deficits (97%, p=0.007). No significant differences in language deficits have been found between bulbar and spinal onset. Months from onset and level of impairment at testing (ALS-FRS total score) were not significantly different between levels and type of language impairment. Age and education were significantly higher for cases showing no deficits in comprehension and pragmatics and in the group showing no language deficits. Comparing performances at neuropsychological tests among the three levels of language deficits, no significant differences in neuropsychological performances were found between group 1 and 2; compared to group 1, group 3 appeared to decay specifically on executive testing, verbal/visuospatial learning, and social cognition. Compared to group 2, group 3 showed worse performances specifically in tests of working memory and attention. Language deficits have found to be spread in our sample, encompassing verbal comprehension, production and pragmatics. Our study reveals that also cognitive intact patients (ALS-CN) showed at least one language deficit in 48% of cases. Pragmatic domain is the most compromised (84% of the total sample), present in nearly all ALS-CI (96%), likely due to the influence of executive impairment. Lower age and higher education seem to preserve comprehension, pragmatics and presence of language deficits. Finally, executive functions, verbal/visuospatial learning and social cognition differentiate the group with no language deficits from the group with a clinical language impairment (group 3), while attention and working memory differentiate the group with one language deficit from the clinical impaired group.

Keywords: amyotrophic lateral sclerosis, language assessment, neuropsychological assessment, language deficit

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Authors: Sandhya Parameswaran, Prajakta Dhuri

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Despite great improvements in health care, the world oral health report states that dental problems still persist, particularly among underprivileged groups in both developing and developed countries. Dental caries and periodontal diseases are identified as the most important oral health problems globally. Acidic foods and beverages can affect natural teeth, and chronic exposure often leads to the development of dental erosion, abrasion, and decay. In recent years, there has been an increased interest toward essential oils. These are secondary metabolites and possess antibacterial, antifungal and antioxidant properties. Essential oils are volatile and chemically unstable in the presence of air, light, moisture and high temperature. Hence many novel methods like a liposomal encapsulation of oils have been introduced to enhance the stability and bioavailability. This research paper focuses on two essential oils, clove and cinnamon oil. Clove oil was obtained from Syzygium aromaticum Linn using clavengers apparatus. It contains eugenol and β caryophyllene. Cinnamon oil, from the barks of Cinnamomum cassia, contains cinnamaldehyde, The objective of the current research was to develop a liposomal carrier system containing clove and cinnamon oil and study their synergistic activity against dental pathogens when formulated as a gel. Methodology: The essential oil were first tested for their antimicrobial activity against dental pathogens, Lactobacillus acidophillus (MTCC No. 10307, MRS broth) and Streptococcus Mutans (MTCC No .890, Brain Heart Infusion agar). The oils were analysed by UV spectroscopy for eugenol and cinnamaldehyde content. Standard eugenol was linear between 5ppm to 25ppm at 282nm and standard cinnamaldehde from 1ppm to 5pmm at 284nm. The concentration of eugenol in clove oil was found to be 62.65 % w/w, and that of cinnamaldehyde was found to be 5.15%s w/w. The oils were then formulated into liposomes. Liposomes were prepared by thin film hydration method using Phospholipid, Cholesterol, and other oils dissolved in a chloroform methanol (3:1) mixture. The organic solvent was evaporated in a rotary evaporator above lipid transition temperature. The film was hydrated with phosphate buffer (pH 5.5).The various batches of liposomes were characterized and compared for their size, loading rate, encapsulation efficiency and morphology. The prepared liposomes when evaluated for entrapment efficiency showed 65% entrapment for clove and 85% for cinnamon oil. They were also tested for their antimicrobial activity against dental pathogens and their synergistic activity studied. Based on the activity and the entrapment efficiency the amount of liposomes required to prepare 1gm of the gel was calculated. The gel was prepared using a simple ointment base and contained 0.56% of cinnamon and clove liposomes. A simultaneous method of analysis for eugenol and cinnamaldehyde.was then developed using HPLC. The prepared gels were then studied for their stability as per ICH guidelines. Conclusion: It was found that liposomes exhibited spherical shaped vesicles and protected the essential oil from degradation. Liposomes, therefore, constitute a suitable system for encapsulation of volatile, unstable essential oil constituents.

Keywords: cinnamon oil, clove oil, dental caries, liposomes

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Authors: Ahmad Alhawarat, Mustafa Mamat, Mohd Rivaie, Ismail Mohd

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Conjugate gradient method has been enormously used to solve large scale unconstrained optimization problems due to the number of iteration, memory, CPU time, and convergence property, in this paper we find a new class of nonlinear conjugate gradient coefficient with global convergence properties proved by exact line search. The numerical results for our new βK give a good result when it compared with well-known formulas.

Keywords: conjugate gradient method, conjugate gradient coefficient, global convergence

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Authors: Shilu Deepa Thomas, P. Jayaprakash, Dorota Łazewska, Katarzyna Kieć-Kononowicz, B. Sadek

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A large body of evidence suggests the involvement of cognitive impairment, increased levels of inflammation and oxidative stress in the pathogenesis of autism spectrum disorder (ASD). ASD commonly coexists with psychiatric conditions like anxiety and cognitive challenges, and individuals with ASD exhibit significant levels of inflammation and immune system dysregulation. Previous Studies have identified elevated levels of pro-inflammatory markers such as IL-1β, IL-6, IL-2 and TNF-α, particularly in young children with ASD. The current therapeutic options for ASD show limited effectiveness, signifying the importance of exploring an efficient drugs to address the core symptoms. The role of histamine H3 receptors (H3Rs) in memory and the prospective role of H3R antagonists in pharmacological control of neurodegenerative disorders, e.g., ASD, is well-accepted. Hence, the effects of chronic systemic administration of H3R antagonist E159 on autistic-like repetitive behaviors, social deficits, memory and anxiety parameters, as well as neuroinflammation in Black and Tan BRachyury (BTBR) mice, were evaluated using Y maze, Barnes maze, self-grooming, open field and three chamber social test. E159 (2.5, 5 and 10 mg/kg, i.p.) dose-dependently ameliorated repetitive and compulsive behaviors by reducing the increased time spent in self-grooming and improved reduced spontaneous alternation in BTBR mice. Moreover, treatment with E159 attenuated disturbed anxiety levels and social deficits in tested male BTBR mice. Furthermore, E159 attenuated oxidative stress by significantly increasing GSH, CAT, and SOD and decreasing the increased levels of MDA in the cerebellum as well as the hippocampus. In addition, E159 decreased the elevated levels of proinflammatory cytokines (tumor necrosis factor (TNF-α), interleukin-1β (IL-1β), and IL-6). The observed results show that H3R antagonists like E159 may represent a promising novel pharmacological strategy for the future treatment of ASD.

Keywords: histamine H3 receptors, antagonist E159, autism, behaviors, mice

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Authors: Yusuf Seedat

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The necessity to understand global financial markets has increased following the unfortunate spread of the recent financial crisis around the world. Financial markets are considered to be complex systems consisting of highly volatile move-ments whose indexes fluctuate without any clear pattern. Analytic methods of stock prices have been proposed in which financial markets are modeled using common network analysis tools and methods. It has been found that two key components of social network analysis are relevant to modeling financial markets, allowing us to forecast accurate predictions of stock prices within the financial market. Financial markets have a number of interacting components, leading to complex behavioral patterns. This paper describes a social network approach to analyzing financial markets as a viable approach to studying the way complex stock markets function. We also look at how social network analysis techniques and metrics are used to gauge an understanding of the evolution of financial markets as well as how community detection can be used to qualify and quantify in-fluence within a network.

Keywords: network analysis, social networks, financial markets, stocks, nodes, edges, complex networks

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Authors: Igor A. Krichtafovitch

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The evolutionary processes are not linear. Long periods of quiet and slow development turn to rather rapid emergences of new species and even phyla. During Cambrian explosion, 22 new phyla were added to the previously existed 3 phyla. Contrary to the common credence the natural selection or a survival of the fittest cannot be accounted for the dominant evolution vector which is steady and accelerated advent of more complex and more intelligent living organisms. Neither Darwinism nor alternative concepts including panspermia and intelligent design propose a satisfactory solution for these phenomena. The proposed hypothesis offers a logical and plausible explanation of the evolutionary processes in general. It is based on two postulates: a) the Biosphere is a single living organism, all parts of which are interconnected, and b) the Biosphere acts as a giant biological supercomputer, storing and processing the information in digital and analog forms. Such supercomputer surpasses all human-made computers by many orders of magnitude. Living organisms are the product of intelligent creative action of the biosphere supercomputer. The biological evolution is driven by growing amount of information stored in the living organisms and increasing complexity of the biosphere as a single organism. Main evolutionary vector is not a survival of the fittest but an accelerated growth of the computational complexity of the living organisms. The following postulates may summarize the proposed hypothesis: biological evolution as a natural life origin and development is a reality. Evolution is a coordinated and controlled process. One of evolution’s main development vectors is a growing computational complexity of the living organisms and the biosphere’s intelligence. The intelligent matter which conducts and controls global evolution is a gigantic bio-computer combining all living organisms on Earth. The information is acting like a software stored in and controlled by the biosphere. Random mutations trigger this software, as is stipulated by Darwinian Evolution Theories, and it is further stimulated by the growing demand for the Biosphere’s global memory storage and computational complexity. Greater memory volume requires a greater number and more intellectually advanced organisms for storing and handling it. More intricate organisms require the greater computational complexity of biosphere in order to keep control over the living world. This is an endless recursive endeavor with accelerated evolutionary dynamic. New species emerge when two conditions are met: a) crucial environmental changes occur and/or global memory storage volume comes to its limit and b) biosphere computational complexity reaches critical mass capable of producing more advanced creatures. The hypothesis presented here is a naturalistic concept of life creation and evolution. The hypothesis logically resolves many puzzling problems with the current state evolution theory such as speciation, as a result of GM purposeful design, evolution development vector, as a need for growing global intelligence, punctuated equilibrium, happening when two above conditions a) and b) are met, the Cambrian explosion, mass extinctions, happening when more intelligent species should replace outdated creatures.

Keywords: supercomputer, biological evolution, Darwinism, speciation

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Authors: Kherafa Abdennasser

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The application of Information and Communication Technologies (ICT) to the training area led to the creation of this new reality called E-learning. That last one is described like the marriage of multi- media (sound, image and text) and of the internet (diffusion on line, interactivity). Distance learning became an important totality for training and that last pass in particular by the setup of a distance learning platform. In our memory, we will use an open source platform named Dokeos for the management of a distance training of GPS called e-GPS. The learner is followed in all his training. In this system, trainers and learners communicate individually or in group, the administrator setup and make sure of this system maintenance.

Keywords: ICT, E-learning, learning plate-forme, Dokeos, GPS

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Authors: Melek Akay

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Turkey's agricultural commodity prices are prone to fluctuation but have gradually over time. A considerable amount of literature examines the changes in these prices by dealing with other commodities such as energy. Links between agricultural and energy markets have therefore been extensively investigated. Since red meat prices are becoming increasingly volatile in Turkey, this paper analyses the price volatility of veal, lamb and the relationship between red meat and crude oil, exchange rates by applying the generalize all period unconstraint volatility model, which generalises the GARCH (p, q) model for analysing weekly data covering a period of May 2006 to February 2017. Empirical results show that veal and lamb prices present volatility during the last decade, but particularly between 2009 and 2012. Moreover, oil prices have a significant effect on veal and lamb prices as well as their previous periods. Consequently, our research can lead policy makers to evaluate policy implementation in the appropriate way and reduce the impacts of oil prices by supporting producers.

Keywords: red meat price, volatility, crude oil, exchange rates, GARCH models, Turkey

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Authors: Periklis Brakatsoulas

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Recent empirical research shows a growing interest in investment decision-making under market anomalies that contradict the rational paradigm. Momentum is undoubtedly one of the most robust anomalies in the empirical asset pricing research and remains surprisingly lucrative ever since first documented. Although predominantly phenomena identified across equities, momentum premia are now evident across various asset classes. Yet few many attempts are made so far to provide traders a diversified portfolio of strategies across different assets and markets. Moreover, literature focuses on patterns from past returns rather than mechanisms to signal future price directions prior to momentum runs. The aim of this paper is to develop a diversified portfolio approach to price distortion signals using daily position data on stocks, credit derivatives, and bonds. An algorithm allocates assets periodically, and new investment tactics take over upon price momentum signals and across different ranking groups. We focus on momentum life cycles, trend reversals, and price acceleration signals. The main effort here concentrates on the density, time span and maturity of momentum phenomena to identify consistent patterns over time and measure the predictive power of buy-sell signals generated by these anomalies. To tackle this, we propose a two-stage modelling process. First, we generate forecasts on core macroeconomic drivers. Secondly, satellite models generate market risk forecasts using the core driver projections generated at the first stage as input. Moreover, using a combination of the ARFIMA and FIGARCH models, we examine the dependence of consecutive observations across time and portfolio assets since long memory behavior in volatilities of one market appears to trigger persistent volatility patterns across other markets. We believe that this is the first work that employs evidence of volatility transmissions among derivatives, equities, and bonds to identify momentum life cycle patterns.

Keywords: forecasting, long memory, momentum, returns

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Authors: Mayank Gupta, Siba Prasad Samal, Vasu Kakkirala

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The internet world and its priorities have changed considerably in the last decade. Browsing on smart phones has increased manifold and is set to explode much more. Users spent considerable time browsing different websites, that gives a great deal of insight into user’s preferences. Instead of plain information classifying different aspects of browsing like Bookmarks, History, and Download Manager into useful categories would improve and enhance the user’s experience. Most of the classification solutions are server side that involves maintaining server and other heavy resources. It has security constraints and maybe misses on contextual data during classification. On device, classification solves many such problems, but the challenge is to achieve accuracy on classification with resource constraints. This on device classification can be much more useful in personalization, reducing dependency on cloud connectivity and better privacy/security. This approach provides more relevant results as compared to current standalone solutions because it uses content rendered by browser which is customized by the content provider based on user’s profile. This paper proposes a Naive Bayes based lightweight classification engine targeted for a resource constraint devices. Our solution integrates with Web Browser that in turn triggers classification algorithm. Whenever a user browses a webpage, this solution extracts DOM Tree data from the browser’s rendering engine. This DOM data is a dynamic, contextual and secure data that can’t be replicated. This proposal extracts different features of the webpage that runs on an algorithm to classify into multiple categories. Naive Bayes based engine is chosen in this solution for its inherent advantages in using limited resources compared to other classification algorithms like Support Vector Machine, Neural Networks, etc. Naive Bayes classification requires small memory footprint and less computation suitable for smartphone environment. This solution has a feature to partition the model into multiple chunks that in turn will facilitate less usage of memory instead of loading a complete model. Classification of the webpages done through integrated engine is faster, more relevant and energy efficient than other standalone on device solution. This classification engine has been tested on Samsung Z3 Tizen hardware. The Engine is integrated into Tizen Browser that uses Chromium Rendering Engine. For this solution, extensive dataset is sourced from dmoztools.net and cleaned. This cleaned dataset has 227.5K webpages which are divided into 8 generic categories ('education', 'games', 'health', 'entertainment', 'news', 'shopping', 'sports', 'travel'). Our browser integrated solution has resulted in 15% less memory usage (due to partition method) and 24% less power consumption in comparison with standalone solution. This solution considered 70% of the dataset for training the data model and the rest 30% dataset for testing. An average accuracy of ~96.3% is achieved across the above mentioned 8 categories. This engine can be further extended for suggesting Dynamic tags and using the classification for differential uses cases to enhance browsing experience.

Keywords: chromium, lightweight engine, mobile computing, Naive Bayes, Tizen, web browser, webpage classification

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Authors: Joseph Roberson, Carina Kleynhans, Willie Coetzee

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The low entry barriers of the restaurant industry lead to an extremely competitive business environment. In this volatile business sector it is of the utmost importance to implement a strategy of quality differentiation. Vital aspects of a quality differentiation strategy are total quality management, benchmarking and service quality management. Ultimately, restaurant success depends on the continuous support of customers. Customers select restaurants based on their expectations of quality. If the customers' expectations are met, they perceive quality service and will re-patronize the restaurant. The restaurateur can manage perceptions of quality by influencing expectations while ensuring that those expectations are not inflated. The management of expectations can be done by communicating service quality to customers. The aim of this research paper is to describe the development of a grading process for restaurants. An assessment of the extensive body of literature on grading was conducted through content analysis. A standardized method for developing a grading system would assist in successful grading systems that could inform both customers and restaurateurs of restaurant quality.

Keywords: benchmarking, restaurants, grading, service quality, total quality management

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Authors: D. Mokatsanyane, J. Jansen Van Rensburg

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This paper analyses the influence and impact of COVID-19 on major agricultural commodity prices in South Africa. According to a World Bank report, the agricultural sector in South Africa has been unable to reduce the domestic food crisis that has been occurring over the past years, hence the increased rate of poverty, which is currently at 55.5 percent as of April 2020. Despite the significance of this sector, empirical findings concluded that the agricultural sector now accounts for 1.88 percent of South Africa's gross domestic product (GDP). Suggesting that the agricultural sector's contribution to the economy has diminished. Despite the low contribution to GDP, this primary sector continues to play an essential role in the economy. Over the past years, multiple factors have contributed to the soaring commodities prices, namely, climate shocks, biofuel demand, demand and supply shocks, the exchange rate, speculation in commodity derivative markets, trade restrictions, and economic growth. The COVID-19 outbursts have currently disturbed the supply and demand of staple crops. To address the disruption, the government has exempted the agricultural sector from closure and restrictions on movement. The spread of COVID-19 has caused turmoil all around the world, but mostly in developing countries. According to Statistic South Africa, South Africa's economy decreased by seven percent in 2020. Consequently, this has arguably made the agricultural sector the most affected sector since slumped economic growth negatively impacts food security, trade, farm livelihood, and greenhouse gas emissions. South Africa is sensitive to the fruitfulness of global food chains. Restrictions in trade, reinforced sanitary control systems, and border controls have influenced food availability and prices internationally. The main objective of this study is to evaluate the behavior of agricultural commodity prices pre-and during-COVID to determine the impact of volatility drivers on these crops. Historical secondary data of spot prices for the top five major commodities, namely white maize, yellow maize, wheat, soybeans, and sunflower seeds, are analysed from 01 January 2017 to 1 September 2021. The timeframe was chosen to capture price fluctuations between pre-COVID-19 (01 January 2017 to 23 March 2020) and during-COVID-19 (24 March 2020 to 01 September 2021). The Generalised Autoregressive Conditional Heteroscedasticity (GARCH) statistical model will be used to measure the influence of price fluctuations. The results reveal that the commodity market has been experiencing volatility at different points. Extremely high volatility is represented during the first quarter of 2020. During this period, there was high uncertainty, and grain prices were very volatile. Despite the influence of COVID-19 on agricultural prices, the demand for these commodities is still existing and decent. During COVID-19, analysis indicates that prices were low and less volatile during the pandemic. The prices and returns of these commodities were low during COVID-19 because of the government's actions to respond to the virus's spread, which collapsed the market demand for food commodities.

Keywords: commodities market, commodity prices, generalised autoregressive conditional heteroscedasticity (GARCH), Price volatility, SAFEX

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Authors: Ghizlane Barzi, Zineb Bamousse

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In an increasingly volatile global economic context characterized by recurring crises, the financial function of companies is called upon to play a strategic role not only in resource management but also in organizational resilience. The emergence of financial technologies (fintech) offers innovative tools capable of transforming this function by enhancing the efficiency of financial processes and increasing companies' ability to adapt and overcome economic shocks. However, despite the rapid rise of fintechs and their growing adoption by companies, there remain uncertainties regarding the real impact of these innovations on the financial resilience of organizations. Indeed, how do fintech-driven innovations transform the financial function, and to what extent does this transformation contribute to strengthening the financial resilience of companies in the face of contemporary crises? This research aims to explore these questions by examining the interrelationships between the financial function, fintech innovations, and corporate resilience, in order to identify optimization levers that could be adopted for better financial risk management.

Keywords: finance, financial function, fintech, resilience, innovation

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Authors: Ashleigh Beales, Anne Whitworth, Jade Cartwright

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Background: While significant benefits of lexical retrieval intervention are evident within the Primary Progressive Aphasia (PPA) and Alzheimer’s disease (AD) literature, an understanding of the mechanisms that underlie change or improvement is limited. Change mechanisms have been explored in the non-progressive post-stroke literature that may offer insight into how interventions affect change with progressive language disorders. The potential influences of cognitive factors may also play a role here, interacting with the aims of intervention. Exploring how such processes have been applied is likely to grow our understanding of how interventions have, or have not, been effective, and how and why generalisation is likely, or not, to occur. Aims: This review of the literature aimed to (1) investigate the proposed mechanisms of change which underpin lexical interventions, mapping the PPA and AD lexical retrieval literature to theoretical accounts of mechanisms that underlie change within the broader intervention literature, (2) identify whether and which nonlinguistic cognitive functions have been engaged in intervention with these populations and any proposed influence, and (3) explore evidence of linguistic generalisation, with particular reference to change mechanisms employed in interventions. Main contribution: A search of Medline, PsycINFO, and CINAHL identified 36 articles that reported data for individuals with PPA or AD following lexical retrieval intervention. A review of the mechanisms of change identified 10 studies that used stimulation, 21 studies utilised relearning, three studies drew on reorganisation, and two studies used cognitive-relay. Significant treatment gains, predominantly based on linguistic performance measures, were reported for all client groups for each of the proposed mechanisms. Reorganisation and cognitive-relay change mechanisms were only targeted in PPA. Eighteen studies incorporated nonlinguistic cognitive functions in intervention; these were limited to autobiographical memory (16 studies), episodic memory (three studies), or both (one study). Linguistic generalisation outcomes were inconsistently reported in PPA and AD studies. Conclusion: This review highlights that individuals with PPA and AD may benefit from lexical retrieval intervention, irrespective of the mechanism of change. Thorough application of a theory of intervention is required to gain a greater understanding of the change mechanisms, as well as the interplay of nonlinguistic cognitive functions.

Keywords: Alzheimer's disease, lexical retrieval, mechanisms of change, primary progressive aphasia

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Authors: Kedibone Masenya, Memory Tekere, Jasper Rees

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Sorghum is an important cereal crop in the world. In particular, it has attracted breeders due to capacity to serve as food, feed, fiber and bioenergy crop. Like any other plant, sorghum hosts a variety of microbes, which can either, have a neutral, negative and positive influence on the plant. In the current study, regions (V3/V4) of 16 S rRNA were targeted to extensively assess bacterial multitrophic interactions in the phyllosphere of sorghum. The results demonstrated that the presence of a pathogen has a significant effect on the endophytic bacterial community. Understanding these interactions is key to develop new strategies for plant protection.

Keywords: bacteria, multitrophic, sorghum, target sequencing

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Authors: M. Masar, P. Janota, J. Sedlak, M. Machovsky, I. Kuritka

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Zinc oxide (ZnO) nano crystals assembled porous architecture was prepared by thermal decomposition of zinc oxalate precursor at various temperatures ranging from 400-900°C. The effect of calcining temperature on structure and morphology was examined by scanning electron microscopy (SEM), X-ray diffractometry, thermogravimetry, and BET adsorption analysis. The porous nano crystalline ZnO morphology was developed due to the release of volatile precursor products, while the overall shape of ZnO micro crystals was retained as a legacy of the precursor. The average crystallite size increased with increasing temperature of calcination from approximately 21 nm to 79 nm, while the specific surface area decreased from 30 to 1.7 m2g-1. The photo catalytic performance of prepared ZnO powders was evaluated by degradation of methyl violet 2B, a model compound. The significantly highest photo catalytic activity was achieved with powder calcined at 500°C. This may be attributed to the sufficiently well-developed crystalline arrangement, while the specific surface area is still high enough.

Keywords: ZnO, porous structure, photodegradation, methyl violet

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Authors: Sewon Kim, Minjun Kwon, Changyeop Lee

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This study is aimed to study combustion characteristics of low NOx burner using petroleum cokes as fuel. The petroleum coke, which is produced through the oil refining process, is an attractive fuel in terms of its high heating value and low price. But petroleum coke is a challenging fuel because of its low volatile content, high sulfur and nitrogen content, which give rise to undesirable emission characteristics and low ignitability. Therefore, the research and development regarding the petroleum coke burner is needed for applying this industrial system. In this study, combustion and emission characteristics of petroleum cokes burner are experimentally investigated in an industrial steam boiler. The low NOx burner is designed to control fuel and air mixing to achieve staged combustion, which, in turn reduces both flame temperature and oxygen. Air distribution ratio of triple staged air are optimized experimentally. The result showed that NOx concentration is lowest when overfire air is used, and the burner function at a fuel rich condition. That is, the burner is operated at the equivalence ratio of 1.67 and overall equivalence ratio including overfire air is kept 0.87.

Keywords: petroleum cokes, low NOx, combustion, equivalence ratio

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Authors: Kuan Lun Pan, Moo Been Chang

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Volatile organic compounds (VOCs) are one of major air contaminants, and they can react with nitrogen oxides (NOx) in atmosphere to form ozone (O3) and peroxyacetyl nitrate (PAN) with solar irradiation, leading to environmental hazards. In addition, some VOCs are toxic at low concentration levels and cause adverse effects on human health. How to effectively reduce VOCs emission has become an important issue. Thermal catalysis is regarded as an effective way for VOCs removal because it provides oxidation route to successfully convert VOCs into carbon dioxide (CO2) and water (H2O(g)). Single perovskite-type catalysts are promising for VOC removal, and they are of good potential to replace noble metals due to good activity and high thermal stability. Single perovskites can be generally described as ABO3 or A2BO4, where A-site is often a rare earth element or an alkaline. Typically, the B-site is transition metal cation (Fe, Cu, Ni, Co, or Mn). Catalytic properties of perovskites mainly rely on nature, oxidation states and arrangement of B-site cation. Interestingly, single perovskites could be further synthesized to form double perovskite-type catalysts which can simply be represented by A2B’B”O6. Likewise, A-site stands for an alkaline metal or rare earth element, and the B′ and B′′ are transition metals. Double perovskites possess unique surface properties. In structure, three-dimensional of B-site with ordered arrangement of B’O6 and B”O6 is presented alternately, and they corner-share octahedral along three directions of the crystal lattice, while cations of A-site position between the void of octahedral. It has attracted considerable attention due to specific arrangement of alternating B-site structure. Therefore, double perovskites may have more variations than single perovskites, and this greater variation may promote catalytic performance. It is expected that activity of double perovskites is higher than that of single perovskites toward VOC removal. In this study, double perovskite-type catalyst (La2CoMnO6) is prepared and evaluated for VOC removal. Also, single perovskites including LaCoO3 and LaMnO3 are tested for the comparison purpose. Toluene (C7H8) is one of the important VOCs which are commonly applied in chemical processes. In addition to its wide application, C7H8 has high toxicity at a low concentration. Therefore, C7H8 is selected as the target compound in this study. Experimental results indicate that double perovskite (La2CoMnO6) has better activity if compared with single perovskites. Especially, C7H8 can be completely oxidized to CO2 at 300oC as La2CoMnO6 is applied. Characterization of catalysts indicates that double perovskite has unique surface properties and is of higher amounts of lattice oxygen, leading to higher activity. For durability test, La2CoMnO6 maintains high C7H8 removal efficiency of 100% at 300oC and 30,000 h-1, and it also shows good resistance to CO2 (5%) and H2O(g) (5%) of gas streams tested. For various VOCs including isopropyl alcohol (C3H8O), ethanal (C2H4O), and ethylene (C2H4) tested, as high as 100% efficiency could be achieved with double perovskite-type catalyst operated at 300℃, indicating that double perovskites are promising catalysts for VOCs removal, and possible mechanisms will be elucidated in this paper.

Keywords: volatile organic compounds, Toluene (C7H8), double perovskite-type catalyst, catalysis

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Authors: Ananya Gupta, Sangeeta Bhaskar

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Mycobacterium indicus pranii (MIP) is a saprophytic mycobacterium. It is a predecessor of M. avium complex (MAC). Whole genome analysis and growth kinetics studies have placed MIP in between pathogenic and non-pathogenic species. It shares significant antigenic repertoire with M. tuberculosis and have unique immunomodulatory properties. MIP provides better protection than BCG against pulmonary tuberculosis in animal models. Immunization with MIP by aerosol route provides significantly higher protection as compared to immunization by subcutaneous (s.c.) route. However, mechanism behind differential protection has not been studied. In this study, using mice model we have evaluated and compared the M.tb specific immune response in lung compartments (airway lumen / lung interstitium) as well as spleen following MIP immunization via nasal (i.n.) and s.c. route. MIP i.n. vaccination resulted in increased seeding of memory T cells (CD4+ and CD8+ T-cells) in the airway lumen. Frequency of CD4+ T cells expressing Th1 migratory marker (CXCR3) and activation marker (CD69) were also high in airway lumen of MIP i.n. group. Significantly high ex vivo secretion of cytokines- IFN-, IL-12, IL-17 and TNF- from cells of airway luminal spaces provides evidence of antigen-specific lung immune response, besides generating systemic immunity comparable to MIP s.c. group. Analysis of T cell response on per cell basis revealed that antigen specific T-cells of MIP i.n. group were functionally superior as higher percentage of these cells simultaneously secreted IFN-gamma, IL-2 and TNF-alpha cytokines as compared to MIP s.c. group. T-cells secreting more than one of the cytokines simultaneously are believed to have robust effector response and crucial for protection, compared with single cytokine secreting T-cells. Adoptive transfer of airway luminal T-cells from MIP i.n. group into trachea of naive B6 mice revealed that MIP induced CD8 T-cells play crucial role in providing long term protection. Thus the study demonstrates that MIP intranasal vaccination induces M.tb specific memory T-cells in the airway lumen that results in an early and robust recall response against M.tb infection.

Keywords: airway lumen, Mycobacterium indicus pranii, Th1 migratory markers, vaccination

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Authors: S. Mohamed Rabeek, Mi Kyoung Park, M. Annamalai Arasu

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This paper presents a design of a wireless read out system for tracking the frequency shift of the polymer coated piezoelectric micro electromechanical resonator due to gas absorption. The measure of this frequency shift indicates the percentage of a particular gas the sensor is exposed to. It is measured using an oscillator and an FPGA based frequency counter by employing the resonator as a frequency determining element in the oscillator. This system consists of a Gas Sensing Wireless Readout (GSWR) and an USB Wireless Transceiver (UWT). GSWR consists of an oscillator based on a trans-impedance sustaining amplifier, an FPGA based frequency readout, a sub 1GHz wireless transceiver and a micro controller. UWT can be plugged into the computer via USB port and function as a wireless module to transfer gas sensor data from GSWR to the computer through its USB port. GUI program running on the computer periodically polls for sensor data through UWT - GSWR wireless link, the response from GSWR is logged in a file for post processing as well as displayed on screen.

Keywords: gas sensor, GSWR, micromechanical system, UWT, volatile emissions

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Authors: Akiyoshi Wakatani

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This paper describes the Message Passing Interface (MPI) implementation of ADETRAN language, and its evaluation on SX-ACE supercomputers. ADETRAN language includes pdo statement that specifies the data distribution and parallel computations and pass statement that specifies the redistribution of arrays. Two methods for implementation of pass statement are discussed and the performance evaluation using Splitting-Up CG method is presented. The effectiveness of the parallelization is evaluated and the advantage of one dimensional distribution is empirically confirmed by using the results of experiments.

Keywords: iterative methods, array redistribution, translator, distributed memory

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Authors: Stefanie Jeanette Huber

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This paper explores the relevance and implications of preferences for housing services on house price fluctuations through the lens of an overlapping generation’s model. The model implies that an economy whose agents have lower preferences for housing services is characterized with lower expenditure shares on housing services and will tend to experience more frequent and more volatile housing bubbles. These model predictions are tested empirically in the companion paper Housing Booms and Busts - Convergences and Divergences across OECD countries. Between 1970 - 2013, countries who spend less on housing services as a share of total income experienced significantly more housing cycles and the associated housing boom-bust cycles were more violent. Finally, the model is used to study the impact of rental subsidies and help-to-buy schemes on rational housing bubbles. Rental subsidies are found to contribute to the control of housing bubbles, whereas help-to- buy scheme makes the economy more bubble-prone.

Keywords: housing bubbles, housing booms and busts, preference for housing services, expenditure shares for housing services, rental and purchase subsidies

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Authors: Jaechun No

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This paper focuses on I/O optimizations of N-hybrid (New-Form of hybrid), which provides a hybrid file system space constructed on SSD and HDD. Although the promising potentials of SSD, such as the absence of mechanical moving overhead and high random I/O throughput, have drawn a lot of attentions from IT enterprises, its high ratio of cost/capacity makes it less desirable to build a large-scale data storage subsystem composed of only SSDs. In this paper, we present N-hybrid that attempts to integrate the strengths of SSD and HDD, to offer a single, large hybrid file system space. Several experiments were conducted to verify the performance of N-hybrid.

Keywords: SSD, data section, I/O optimizations, hybrid system

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Authors: Thomas Vlasak, Tanja Dujlociv, Alfred Barth

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Shift work is an essential element of modern labor, ensuring ideal conditions of service for today’s economy and society. Despite the beneficial properties, its impact on the neurobehavioral performance of exposed subjects remains controversial. This meta-analysis aims to provide first summarizing the effects regarding the association between shift work exposure and different cognitive functions. A literature search was performed via the databases PubMed, PsyINFO, PsyARTICLES, MedLine, PsycNET and Scopus including eligible studies until December 2020 that compared shift workers with non-shift workers regarding neurobehavioral performance tests. A random-effects model was carried out using Hedge’s g as a meta-analytical effect size with a restricted likelihood estimator to summarize the mean differences between the exposure group and controls. The heterogeneity of effect sizes was addressed by a sensitivity analysis using funnel plots, egger’s tests, p-curve analysis, meta-regressions, and subgroup analysis. The meta-analysis included 18 studies resulting in a total sample of 18,802 participants and 37 effect sizes concerning six different neurobehavioral outcomes. The results showed significantly worse performance in shift workers compared to non-shift workers in the following cognitive functions with g (95% CI): processing speed 0.16 (0.02 - 0.30), working memory 0.28 (0.51 - 0.50), psychomotor vigilance 0.21 (0.05 - 0.37), cognitive control 0.86 (0.45 - 1.27) and visual attention 0.19 (0.11 - 0.26). Neither significant moderating effects of publication year or study quality nor significant subgroup differences regarding type of shift or type of profession were indicated for the cognitive outcomes. These are the first meta-analytical findings that associate shift work with decreased cognitive performance in processing speed, working memory, psychomotor vigilance, cognitive control, and visual attention. Further studies should focus on a more homogenous measurement of cognitive functions, a precise assessment of experience of shift work and occupation types which are underrepresented in the current literature (e.g., law enforcement). In occupations where shift work is fundamental (e.g., healthcare, industries, law enforcement), protective countermeasures should be promoted for workers.

Keywords: meta-analysis, neurobehavioral performance, occupational psychology, shift work

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Authors: H. Gorine, M. Ramadan Elmezughi

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In this paper, we investigate security issues and challenges facing researchers in wireless sensor networks and countermeasures to resolve them. The broadcast nature of wireless communication makes Wireless Sensor Networks prone to various attacks. Due to resources limitation constraint in terms of limited energy, computation power and memory, security in wireless sensor networks creates different challenges than wired network security. We will discuss several attempts at addressing the issues of security in wireless sensor networks in an attempt to encourage more research into this area.

Keywords: wireless sensor networks, network security, light weight encryption, threats

Procedia PDF Downloads 527

Authors: Fazıl Gökgöz, Fahrettin Filiz

Abstract:

Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

Procedia PDF Downloads 266

Authors: Tatsanawalai Utarasakul

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Nowadays, green office principles are very broadly initiated in many offices, organizations, as well as in universities. The concepts of green office are composed of seven prominent issues. One of them, physical implementation, is to develop a pleasant atmosphere for staff in the faculty with selected optimum plant species for the office. 50 species from NASA research and other documents were studied for the selection criteria of plants which were appropriate for specific locations in order to reduce indoor air pollutants such as formaldehyde, benzene, and trichloroethylene. For the copy and examination preparation room in which particulate matter and volatile organic compounds can be found, some plants such as peace lily, gerbera daisy, and bamboo palm should be set, which are very effective in treating trichloroethylene. For common rooms and offices where formaldehyde can be found, which is generated from many building materials, bamboo palm, mother-in-law's tongue, peace lily, striped dracaena, cornstalk plant, golden pathos, and green spider plant should be set.

Keywords: indoor plants, indoor air quality, phytoremediation, green office

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Authors: Shahram Keshavarzi

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Today, getting good service, having a good time, and leaving the company with good feelings are importanttforbothcustomers and businesses. It has been observed that when customersareexposedtopleasantsmells, their visit times increase by 26%, and theyvisittheaislesfor 3 times longer. Byusingtheeffect of scents on people, it is toensurethatcustomersshopmore, benefit from the service and be satisfied. Intoday'sresearch, visual memory can be 40% effective after a period of 4 months, whileolfactorymemory is 60% moreeffectiveevenafter 1 year. The purpose of the research is thehiddenandeffectivepower of skepticism in the behavior of consumersandtheeffectivestrategy of modern marketing. Special scentsdirectlyaffecttheincrease in sales by influencing the customer's-decision mechanism in purchasing products.

Keywords: modern marketing strategy, scent, scent marketing, consumer behavior

Procedia PDF Downloads 156

Authors: Soheil Tavakolpour

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Enhance Oil Recovery (EOR) can be considered as an undeniable action in reservoirs life period. Different kind of EOR methods are available, but suitable EOR method depends on reservoir properties, like rock and fluid properties. In this paper, we nominated fifth SPE’s Comparative Solution Projects (CSP) for testing different scenarios. We used seven EOR scenarios for this reservoir and we simulated it for 10 years after 2 years production without any injection. The first scenario is waterflooding for whole of the 10 years period. The second scenario is gas injection for ten years. The third scenario is Water-Alternation-Gas (WAG). In the next scenario, water injected for 4 years before starting WAG injection for the next 6 years. In the fifth scenario, water injected after 6 years WAG injection for 4 years. For sixth and last scenarios, all the things are similar to fourth and fifth scenarios, but gas injected instead of water. Results show that fourth scenario was the most efficient method for 10 years EOR, but it resulted very high water production. Fifth scenario was efficient too, with little water production in comparison to the fourth scenario. Gas injection was not economically attractive. In addition to high gas production, it produced less oil in comparison to other scenarios.

Keywords: WAG, SPE’s comparative solution projects, numerical simulation, EOR scenarios

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Authors: Sam Solaimani, Jack A. A. van der Veen, Mehdi Latifi

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Considering the increasingly VUCA (Volatile, Uncertain, Complex, Ambiguous) business market, innovation is the name of the game in contemporary business. Innovation is not solely created within the organization itself; its 'network environment' appears to be equally important for innovation. There are, at least, two streams of literature that emphasize the idea of using the extended organization to foster innovation capability, namely, Supply Chain Collaboration (SCC) (also rooted in the Lean philosophy) and Open Innovation (OI). Remarkably, these two concepts are still considered as being totally different in the sense that these appear in different streams of literature and applying different concepts in pursuing the same purposes. This paper explores the commonalities between the two concepts in order to conceptually further our understanding of how OI can effectively be applied in Supply Chain networks. Drawing on available literature in OI, SCC and Lean, the paper concludes with five principles that help firms to contextualize the implementation of OI to the peculiar setting of SC. Theoretically, the present paper aims at contributing to the relatively under-researched theme of Supply Chain Innovation. More in practical terms, the paper provides OI and SCC communities with a workable know-how to seize on and sustain OI initiatives.

Keywords: lean philosophy, open innovation, supply chain collaboration, supply chain management

Procedia PDF Downloads 323