Search results for: fuzzy genetic network programming

Authors: Desmond Chinedu Oparaku, Emmanuel Uwazie Anyanwu, Oyemike Victor Benson, Ogbonna Isaac-Nnadimele

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The purpose of this paper is to provide a theoretical discourse that highlights the challenges associated with management of indigenous knowledge with reference to developing countries. Literature review and brainstorming were used to collect relevant data and draw inferences. The findings indicate that non-existence of indigenous knowledge management policy (IKMP), low level of partnership drive among library and information services providers, non-uniformity of format and content of indigenous knowledge, inadequate funding, and lack of access to ICTs, lack of indigenous people with indigenous expertise and hoarding of knowledge as challenges to indigenous knowledge management. The study is based on literature review and information gathered through brain storming with professional colleagues the geographic scope as developing countries. The study has birth several implication based on the findings made. Professionally, it has necessitated the need for formulating a viable indigenous knowledge management policy (IKMP), creating of collaborative network through partnership, and integration of ICTs to indigenous knowledge management practices by libraries in developing countries etc. The originality of this paper is revealed in its capability as serving as an eye opener to librarians on the need for preserving and managing indigenous knowledge in developing countries. It further unlocks the possibilities of exploring empirical based researches to substantiate the theoretical issues raised in this paper. The findings may be used by library managers to improve indigenous knowledge management (IKM).

Keywords: developing countries, ICTs, indigenous knowledge, knowledge management

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Authors: Johnnie Hay

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New Zealand is well known for its natural beauty, diversity of people but also for its strong focus on mental health through the provision of a vast network of psycho-social support services. South African-trained psychologists often make New Zealand their new home when emigrating - as it is relatively simple to slot into the well-established mental health system. South Africa is bigger in size, population, GDP and probably people diversity than New Zealand but struggles to provide adequate educational and psychological support services to schools. This is mainly due to budgetary pressures brought about by the imperative to first ensure that the approximately 13 million learners all have a teacher in front of their classes and at an average ratio of not more than 40 learners per class. In this paper, perspectives on educational and psychological support in New Zealand and South African schools will be shared. Through basic qualitative research encompassing semi-structured interviews with two South African educational psychologists who returned from New Zealand, supplemented by document analysis, the New Zealand situation will be scrutinized. South African perspectives will be obtained through a number of semi-structured interviews and questionnaires administered by education support services specialists working in district-based support teams in three provinces of the country. This research is in process, but preliminary findings indicate large disparities between the two countries' emphasis, funding, post provisioning and structure regarding educational and psychological support services.

Keywords: educational psychological support services, support for learners experiencing special needs, education support services, diverse learner population

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Authors: Serhat Tüzün, Tufan Demirel

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Decision Support Systems (DSS) have been investigated by researchers and technologists for more than 35 years. This paper analyses the developments in the architecture and software of these systems, provides a systematic analysis for different Web-based DSS approaches and Intelligent Decision-making Technologies (IDT), with the suggestion for future studies. Decision Support Systems literature begins with building model-oriented DSS in the late 1960s, theory developments in the 1970s, and the implementation of financial planning systems and Group DSS in the early and mid-80s. Then it documents the origins of Executive Information Systems, online analytic processing (OLAP) and Business Intelligence. The implementation of Web-based DSS occurred in the mid-1990s. With the beginning of the new millennia, intelligence is the main focus on DSS studies. Web-based technologies are having a major impact on design, development and implementation processes for all types of DSS. Web technologies are being utilized for the development of DSS tools by leading developers of decision support technologies. Major companies are encouraging its customers to port their DSS applications, such as data mining, customer relationship management (CRM) and OLAP systems, to a web-based environment. Similarly, real-time data fed from manufacturing plants are now helping floor managers make decisions regarding production adjustment to ensure that high-quality products are produced and delivered. Web-based DSS are being employed by organizations as decision aids for employees as well as customers. A common usage of Web-based DSS has been to assist customers configure product and service according to their needs. These systems allow individual customers to design their own products by choosing from a menu of attributes, components, prices and delivery options. The Intelligent Decision-making Technologies (IDT) domain is a fast growing area of research that integrates various aspects of computer science and information systems. This includes intelligent systems, intelligent technology, intelligent agents, artificial intelligence, fuzzy logic, neural networks, machine learning, knowledge discovery, computational intelligence, data science, big data analytics, inference engines, recommender systems or engines, and a variety of related disciplines. Innovative applications that emerge using IDT often have a significant impact on decision-making processes in government, industry, business, and academia in general. This is particularly pronounced in finance, accounting, healthcare, computer networks, real-time safety monitoring and crisis response systems. Similarly, IDT is commonly used in military decision-making systems, security, marketing, stock market prediction, and robotics. Even though lots of research studies have been conducted on Decision Support Systems, a systematic analysis on the subject is still missing. Because of this necessity, this paper has been prepared to search recent articles about the DSS. The literature has been deeply reviewed and by classifying previous studies according to their preferences, taxonomy for DSS has been prepared. With the aid of the taxonomic review and the recent developments over the subject, this study aims to analyze the future trends in decision support systems.

Keywords: decision support systems, intelligent decision-making, systematic analysis, taxonomic review

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Authors: Sushish Baral, Pratibha Joshi, Yaman Maharjan

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Glaucoma is a chronic eye condition that causes vision loss that is irreversible. Early detection and treatment are critical to prevent vision loss because it can be asymptomatic. For the identification of glaucoma, multiple deep learning algorithms are used. Transformer-based architectures, which use the self-attention mechanism to encode long-range dependencies and acquire extremely expressive representations, have recently become popular. Convolutional architectures, on the other hand, lack knowledge of long-range dependencies in the image due to their intrinsic inductive biases. The aforementioned statements inspire this thesis to look at transformer-based solutions and investigate the viability of adopting transformer-based network designs for glaucoma detection. Using retinal fundus images of the optic nerve head to develop a viable algorithm to assess the severity of glaucoma necessitates a large number of well-curated images. Initially, data is generated by augmenting ocular pictures. After that, the ocular images are pre-processed to make them ready for further processing. The system is trained using pre-processed images, and it classifies the input images as normal or glaucoma based on the features retrieved during training. The Vision Transformer (ViT) architecture is well suited to this situation, as it allows the self-attention mechanism to utilise structural modeling. Extensive experiments are run on the common dataset, and the results are thoroughly validated and visualized.

Keywords: glaucoma, vision transformer, convolutional architectures, retinal fundus images, self-attention, deep learning

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Authors: Mostafa Mohammadpour, Christoph Kapeller, Christy Li, Josef Scharinger, Christoph Guger

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Interictal spikes provide valuable information on electrocorticography (ECoG), which aids in surgical planning for patients who suffer from refractory epilepsy. However, the shape and temporal dynamics of these spikes remain unclear. The purpose of this work was to analyze the shape of interictal spikes and measure their distance to the seizure onset zone (SOZ) to use in epilepsy surgery. Thirteen patients' data from the iEEG portal were retrospectively studied. For analysis, half an hour of ECoG data was used from each patient, with the data being truncated before the onset of a seizure. Spikes were first detected and grouped in a sequence, then clustered into interictal epileptiform discharges (IEDs) and non-IED groups using two-step clustering. The distance of the spikes from IED and non-IED groups to SOZ was quantified and compared using the Wilcoxon rank-sum test. Spikes in the IED group tended to be in SOZ or close to it, while spikes in the non-IED group were in distance of SOZ or non-SOZ area. At the group level, the distribution for sharp wave, positive baseline shift, slow wave, and slow wave to sharp wave ratio was significantly different for IED and non-IED groups. The distance of the IED cluster was 10.00mm and significantly closer to the SOZ than the 17.65mm for non-IEDs. These findings provide insights into the shape and spatiotemporal dynamics of spikes that could influence the network mechanisms underlying refractory epilepsy.

Keywords: spike propagation, spike pattern, clustering, SOZ

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Authors: V. Ayishwarya Bharathi, S. M. Hasker, J. Indhu, M. Mohamed Azarudeen, G. Gowthami, R. Vinoth Rajan, N. Vijayarangan

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Identification of water quality conditions in a river system based on limited observations is an essential task for meeting the goals of environmental management. The traditional method of water quality testing is to collect samples manually and then send to laboratory for analysis. However, it has been unable to meet the demands of water quality monitoring today. So a set of automatic measurement and reporting system of water quality has been developed. In this project specifies Water quality parameters collected by multi-parameter water quality probe are transmitted to data processing and monitoring center through GPRS wireless communication network of mobile. The multi parameter sensor is directly placed above the water level. The monitoring center consists of GPRS and micro-controller which monitor the data. The collected data can be monitor at any instant of time. In the pollution control board they will monitor the water quality sensor data in computer using Visual Basic Software. The system collects, transmits and processes water quality parameters automatically, so production efficiency and economy benefit are improved greatly. GPRS technology can achieve well within the complex environment of poor water quality non-monitored, and more specifically applicable to the collection point, data transmission automatically generate the field of water analysis equipment data transmission and monitoring.

Keywords: multiparameter sensor, GPRS, visual basic software, RS232

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Authors: Akinbo Razak Yinka, Adesanya Kehinde Kazeem, Oladokun Oluwagbenga Peter

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Time series data are sequences of observations collected over a period of time. Such data can be used to predict health outcomes, such as disease progression, mortality, hospitalization, etc. The Statistical approach is based on mathematical models that capture the patterns and trends of the data, such as autocorrelation, seasonality, and noise, while Neural methods are based on artificial neural networks, which are computational models that mimic the structure and function of biological neurons. This paper compared both parametric and non-parametric time series models of patients treated for malaria in Maternal and Child Health Centres in Lagos State, Nigeria. The forecast methods considered linear regression, Integrated Moving Average, ARIMA and SARIMA Modeling for the parametric approach, while Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) Network were used for the non-parametric model. The performance of each method is evaluated using the Mean Absolute Error (MAE), R-squared (R2) and Root Mean Square Error (RMSE) as criteria to determine the accuracy of each model. The study revealed that the best performance in terms of error was found in MLP, followed by the LSTM and ARIMA models. In addition, the Bootstrap Aggregating technique was used to make robust forecasts when there are uncertainties in the data.

Keywords: ARIMA, bootstrap aggregation, MLP, LSTM, SARIMA, time-series analysis

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Authors: Jara Kaye S. Villanueva, M. Rosario Concepcion O. Ang

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For the past few years, Philippines has depended most of its energy source on oil, coal, and fossil fuel. According to the Department of Energy (DOE), the dominance of coal in the energy mix will continue until the year 2020. The expanding energy needs in the country have led to increasing efforts to promote and develop renewable energy. This research is a part of the government initiative in preparation for renewable energy development and expansion in the country. The Philippine Renewable Energy Resource Mapping from Light Detection and Ranging (LiDAR) Surveys is a three-year government project which aims to assess and quantify the renewable energy potential of the country and to put them into usable maps. This study focuses on the site suitability analysis of the four renewable energy sources – biomass (coconut, corn, rice, and sugarcane), hydro, solar, and wind energy. The site assessment is a key component in determining and assessing the most suitable locations for the construction of renewable energy power plants. This method maximizes the use of both the technical methods in resource assessment, as well as taking into account the environmental, social, and accessibility aspect in identifying potential sites by utilizing and integrating two different methods: the Multi-Criteria Decision Analysis (MCDA) method and Geographic Information System (GIS) tools. For the MCDA, Analytical Hierarchy Processing (AHP) is employed to determine the parameters needed for the suitability analysis. To structure these site suitability parameters, various experts from different fields were consulted – scientists, policy makers, environmentalists, and industrialists. The need to have a well-represented group of people to consult with is relevant to avoid bias in the output parameter of hierarchy levels and weight matrices. AHP pairwise matrix computation is utilized to derive weights per level out of the expert’s gathered feedback. Whereas from the threshold values derived from related literature, international studies, and government laws, the output values were then consulted with energy specialists from the DOE. Geospatial analysis using GIS tools translate this decision support outputs into visual maps. Particularly, this study uses Euclidean distance to compute for the distance values of each parameter, Fuzzy Membership algorithm which normalizes the output from the Euclidean Distance, and the Weighted Overlay tool for the aggregation of the layers. Using the Natural Breaks algorithm, the suitability ratings of each of the map are classified into 5 discrete categories of suitability index: (1) not suitable (2) least suitable, (3) suitable, (4) moderately suitable, and (5) highly suitable. In this method, the classes are grouped based on the best groups similar values wherein each subdivision are set from the rest based on the big difference in boundary values. Results show that in the entire Philippine area of responsibility, biomass has the highest suitability rating with rice as the most suitable at 75.76% suitability percentage, whereas wind has the least suitability percentage with score 10.28%. Solar and Hydro fall in the middle of the two, with suitability values 28.77% and 21.27%.

Keywords: site suitability, biomass energy, hydro energy, solar energy, wind energy, GIS

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Authors: Roy Hanney

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This research study aims to develop an evidential basis to inform strategic development of the film industry in the Solent (south central) region of the UK. The density of the creative industries around the region is driving the growth of jobs. Yet, film production in particular, appears to struggle with field configuration, lacks ecological cohesion, and suffers from underdeveloped ecosystems when compared to other areas bordering the region. Though thriving, a lack of coordinated leadership results in the continued reproduction of an ill-configured, constricted and socio-economically filtered workforce. One that struggles to seize strategic opportunities arising as a consequence of the ongoing investment in UK film production around the west of London. Taking a participatory approach, the study seeks to avoid the universalism of place marketing and focus on the situatedness of the region and its specific cultural, social, and economic contexts. The staging of a series of high profile networking events provided a much needed field configuring activity and enabled the capture of voices of those currently working in the sector. It will also provided the opportunity for an exploratory network mapping of the regional creative industries as a value exchange ecosystem. It is understood that a focus on production is not in itself a solution to the challenges faced in the region. There is a need to address issues of access as a counterbalance to skewed representation among the creative workforces thus the study also aims to report on opportunities for embedding diversity and inclusion in any strategic solutions.

Keywords: creative, industries, ecosystem, ecology

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Authors: Feng Zisu

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Community is the basic unit of the city, community pedestrian space is also an important part of the urban public space, and its quality improvement is also closely related to the residents' happiness and sense of belonging. Domestic and international research perspectives on community pedestrian space have gradually changed to inclusive design for the whole population, paying more attention to the equitable accessibility of urban space and the multiple composite enhancement of spatial connotation. In order to realize the inclusive and sustainable development of pedestrian space in old communities, this article selects Cao Yang New Village in Shanghai as a practice case, and based on the connotation of inclusiveness, the four dimensions of space, traffic, function and emotion are selected as the layers of inclusive connotation of pedestrian space in old communities. This article identifies the objective social needs, dynamic activity characteristics and subjective feelings of multiple subjects, and reconstructs the structural hierarchy of “spatial perception - behavioral characteristics - subjective feelings” of walking. It also proposes a governance strategy of “reconfiguring the pedestrian network, optimizing street quality, integrating ecological space and reshaping the community scene” from the aspects of quality of physical environment and quality of behavioral perception, aiming to provide new ideas for promoting the inclusive and sustainable development of pedestrian space in old communities.

Keywords: inclusivity, old community, pedestrian space, spatial quality, sustainable renovation

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Authors: Julia Gontar, Natalia Buderatskaya, Igor Ilyin, Olga Parnitskaya, Sergey Lavrynenko, Eduard Kapustin, Ekaterina Ilyina, Yana Lakhno

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Introduction: It is well known that oocytes obtained from older reproductive women have accumulated mitochondrial DNA mutations, which negatively affects the morphology of a developing embryo and may lead to the birth of a child with mitochondrial disease. Special techniques have been developed to allow a donor oocyte cytoplasmic transfer with the parents’ biological nuclear DNA retention. At the same time, it is important to understand whether the procedure affects the future embryonic chromosome sets as the nuclear DNA is the transfer subject in this new complex procedure. Material and Methods: From July 2015 to July 2016, the investigation was carried out in the Medical Centre IGR. 34 donor oocytes (group A) were used for the manipulation with the aim of donating cytoplasm: 21 oocytes were used for zygotes pronuclear transfer and oocytes 13 – for the spindle transfer. The mean age of the oocyte donors was 28.4±2.9 years. The procedure was performed using Nikon Ti Eclipse inverted microscope equipped with the micromanipulators Narishige system (Japan), Saturn 3 laser console (UK), Oosight imaging systems (USA). For the preimplantation genetic screening (PGS) blastocyst biopsy was performed, trophectoderm samples were diagnosed using fluorescent in situ hybridization on chromosomes 9, 13, 15, 16, 17, 18, 21, 22, X, Y. For comparison of morphological characteristics and euploidy, was chosen a group of embryos (group B) with the amount of 121 blastocysts obtained from 213 oocytes, which were gotten from the donor programs of assisted reproductive technologies (ART). Group B was not subjected to donor oocyte cytoplasmic transfer procedure and studied on the above mentioned chromosomes. Statistical analysis was carried out using the criteria t, x^2 at a significance levels p<0.05, p<0.01, p<0.001. Results: After the donor cytoplasm transfer process the amount of the third day developing embryos was 27 (79.4%). In this stage, the group B consisted of 189 (88.7%) developing embryos, and there was no statistically significant difference (SSD) between the two groups (p>0.05). After a comparative analysis of the morphological characteristics of the embryos on the fifth day, we also found no SSD among the studied groups (p>0.05): from 34 oocytes exposed to manipulation, 14 (41.2%) blastocysts was obtained, while the group B blastocyst yield was 56.8% (n=121) from 213 oocytes. The following results were obtained after PGS performing: in group A euploidy in studied chromosomes were 28.6%(n=4) blastocysts, whereas in group B this rate was 40.5%(n=49), 28.6%(n=4) and 21.5%(n=26) of mosaic embryos and 42.8%(n=6) and 38.0%(n=46) aneuploid blastocysts respectively were identified. None of these specified parameters had an SSD (p>0.05). But attention was drawn by the blastocysts in group A with identified mosaicism, which was chaotic without any cell having euploid chromosomal set, in contrast to the mosaic embryos in group B where identified chaotic mosaicism was only 2.5%(n=3). Conclusions: According to the obtained results, there is no direct procedural effect on the chromosome in embryos obtained following donor oocyte cytoplasmic transfer. Thus, the technology introduction will enhance the infertility treating effectiveness as well as avoiding having a child with mitochondrial disease.

Keywords: donor oocyte cytoplasmic transfer, embryos’ chromosome set, oocyte spindle transfer, pronuclear transfer

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Authors: Badr M. Thamer

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The use of hydrogels as adsorbents for pollutants removal from wastewater is limited due to their high swelling properties and the difficulty in recovering them after the adsorption process. To overcome these problems, a new hydrogel nanocomposite based on chitosan-g-polyacrylic acid/oxidized electrospun carbon nanofibers (CT-g-PAA/O-ECNFs) was prepared by in-situ grafting polymerization process. The prepared hydrogel nanocomposite was used as a novel effective and highly reusable adsorbent for the removal of methylene blue (MB) from polluted water with low cost. The morphology and the structure of CT-g-PAA/O-ECNFs were investigated by numerous techniques. The effect of incorporating O-ECNFs on the swelling capability of the prepared hydrogel was explored in distillated water and MB solution at normal pH. The effect of parameters including the ratio of O-ECNFs, contact time, pH, initial concentration, and temperature on the adsorption process were explored. The adsorption isotherm and kinetic were studied by numerous non-linear models. The obtained results confirmed that the incorporation of O-ECNFs into the hydrogel network improved its ability towards MB dye removal with decreasing their swelling capacity. The adsorption process depends on the pH value of the dye solution. Additionally, the adsorption and kinetic results were fitted using the Freundlich isotherm model and pseudo second order model (PSO), respectively. Moreover, the new adsorbents can be recycled for at least five cycles keeping its adsorption capacity and can be easily recovered without loss in its initial weight.

Keywords: carbon nanofibers, hydrogels, nanocomposites, water treatment

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Authors: Ran Etgar, Yuval Cohen, Erel Avineri

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One of the major challenges of transportation in medium sized inner-cities (such as Tel-Aviv) is the last-mile solution. Personal rapid transit (PRT) seems like an applicable candidate for this, as it combines the benefits of personal (car) travel with the operational benefits of transit. However, the investment required for large area PRT grid is significant and there is a need to economically justify such investment by correctly evaluating the grid capacity. PRT main elements are small automated vehicles (sometimes referred to as podcars) operating on a network of specially built guideways. The research is looking at a specific concept of elevated PRT system. Literature review has revealed the drawbacks PRT modelling and simulation approaches, mainly due to the lack of consideration of technical and operational features of the system (such as headways, acceleration, safety issues); the detailed design of infrastructure (guideways, stations, and docks); the stochastic and sessional characteristics of demand; and safety regulations – all of them have a strong effect on the system performance. A highly detailed model of the system, developed in this research, is applying a discrete event simulation combined with an agent-based approach, to represent the system elements and the podecars movement logic. Applying a case study approach, the simulation model is used to study the capacity of the system, the expected throughput of the system, the utilization, and the level of service (journey time, waiting time, etc.).

Keywords: capacity, productivity measurement, PRT, simulation, transportation

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Authors: Betim Bahtiri, B. Arash, R. Rolfes

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Epoxy-based materials are frequently exposed to high-humidity environments in many engineering applications. As a result, their material properties would be degraded by water absorption. A full characterization of the material properties under hygrothermal conditions requires time- and cost-consuming experimental tests. To gain insights into the physics of diffusion mechanisms, atomistic simulations have been shown to be effective tools. Concerning the diffusion of water in polymers, spatial trajectories of water molecules are obtained from molecular dynamics (MD) simulations allowing the interpretation of diffusion pathways at the nanoscale in a polymer network. Conventional MD simulations of water diffusion in amorphous polymers lead to discrepancies at low temperatures due to the short timescales of the simulations. In the proposed model, this issue is solved by using a combined scheme of autonomous basin climbing (ABC) with kinetic Monte Carlo and reactive MD simulations to investigate the diffusivity of water molecules in epoxy resins across a wide range of temperatures. It is shown that the proposed simulation framework estimates kinetic properties of water diffusion in epoxy resins that are consistent with experimental observations and provide a predictive tool for investigating the diffusion of small molecules in other amorphous polymers.

Keywords: epoxy resins, water diffusion, autonomous basin climbing, kinetic Monte Carlo, reactive molecular dynamics

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Authors: Ime R. Udotong, Justina I. R. Udotong, Ofonime U. M. John

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Mobil Producing Nigeria Unlimited (MPNU), a subsidiary of ExxonMobil and the highest crude oil & condensate producer in Nigeria has its operational base and an oil terminal, the Qua Iboe terminal (QIT) located at Ibeno, Nigeria. Other oil companies like Network Exploration and Production Nigeria Ltd, Frontier Oil Ltd; Shell Petroleum Development Company Ltd; Elf Petroleum Nigeria Ltd and Nigerian Agip Energy, a subsidiary of the Italian ENI E&P operate onshore, on the continental shelf and in deep offshore of the Atlantic Ocean, respectively with the coastal waters of Ibeno, Nigeria as the nearest shoreline. This study was designed to delineate the oil-polluted sites in Ibeno, Nigeria using microbiological and physico-chemical characterization of soils, sediments and ground and surface water samples from the study area. Results obtained revealed that there have been significant recent hydrocarbon inputs into this environment as observed from the high counts of hydrocarbonoclastic microorganisms in excess of 1% at all the stations sampled. Moreover, high concentrations of THC, BTEX and heavy metals contents in all the samples analyzed corroborate the high recent crude oil input into the study area. The results also showed that the pollution of the different environmental media sampled were of varying degrees, following the trend: Ground water > surface water > sediments > soils.

Keywords: microbiological characterization, oil-polluted sites, physico-chemical analyses, total hydrocarbon content

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Authors: Martin Elstner

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Processing of information by means of handling chemicals is a ubiquitous phenomenon in nature. Technical implementations of chemical information processing lack of low integration densities compared to electronic devices. Stimuli responsive hydrogels are promising candidates for materials with information processing capabilities. These hydrogels are sensitive toward chemical stimuli like metal ions or amino acids. The binding of an analyte molecule induces conformational changes inside the polymer network and subsequently the water content and volume of the hydrogel varies. This volume change can control material flows, and concurrently information flows, in microfluidic devices. The combination of this technology with powerful chemical logic gates yields in a platform for highly integrated chemical circuits. The manufacturing process of such devices is very challenging and rapid prototyping is a key technology used in the study. 3D printing allows generating three-dimensional defined structures of high complexity in a single and fast process step. This thermoplastic master is molded into PDMS and the master is removed by dissolution in an organic solvent. A variety of hydrogel materials is prepared by dispenser printing of pre-polymer solutions. By a variation of functional groups or cross-linking units, the functionality of the hole circuit can be programmed. Finally, applications in the field of bio-molecular analytics were demonstrated with an autonomously operating microfluidic chip.

Keywords: bioanalytics, hydrogels, information processing, microvalve

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Authors: Yeliz Karaca, Carlo Cattani

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This study focuses on the local Holder exponent as a measure of the function regularity for time series related to finance data. In this study, the attributes of the finance dataset belonging to 13 countries (India, China, Japan, Sweden, France, Germany, Italy, Australia, Mexico, United Kingdom, Argentina, Brazil, USA) located in 5 different continents (Asia, Europe, Australia, North America and South America) have been examined.These countries are the ones mostly affected by the attributes with regard to financial development, covering a period from 2012 to 2017. Our study is concerned with the most important attributes that have impact on the development of finance for the countries identified. Our method is comprised of the following stages: (a) among the multi fractal methods and Brownian motion Holder regularity functions (polynomial, exponential), significant and self-similar attributes have been identified (b) The significant and self-similar attributes have been applied to the Artificial Neuronal Network (ANN) algorithms (Feed Forward Back Propagation (FFBP) and Cascade Forward Back Propagation (CFBP)) (c) the outcomes of classification accuracy have been compared concerning the attributes that have impact on the attributes which affect the countries’ financial development. This study has enabled to reveal, through the application of ANN algorithms, how the most significant attributes are identified within the relevant dataset via the Holder functions (polynomial and exponential function).

Keywords: artificial neural networks, finance data, Holder regularity, multifractals

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Authors: Vivek Rangarajan, Kim G. Klarke

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With overpopulation threatening the world’s ability to feed itself, food production and protection has become a major issue, especially in developing countries. Almost one-third of the food produced for human consumption, around 1.3 billion tonnes, is either wasted or lost annually. Postharvest decay in particular constitutes a major cause of crop loss with about 20% of fruits and vegetables produced lost during postharvest storage, mainly due to fungal disease. Some of the major phytopathogenic fungi affecting postharvest fruit crops in South Africa include Aspergillus, Botrytis, Penicillium, Alternaria and Sclerotinia spp. To date control of fungal phytopathogens has primarily been dependent on synthetic chemical fungicides, but these chemicals pose a significant threat to the environment, mainly due to their xenobiotic properties and tendency to generate resistance in the phytopathogens. Here, an environmentally benign alternative approach to control postharvest fungal phytopathogens in perishable fruit crops has been presented, namely the application of a bio-fungicide in the form of lipopeptide molecules. Lipopeptides are biosurfactants produced by Bacillus spp. which have been established as green, nontoxic and biodegradable molecules with antimicrobial properties. However, since the Bacillus are capable of producing a large number of lipopeptide homologues with differing efficacies against distinct target organisms, the lipopeptide production conditions and strategy are critical to produce the maximum lipopeptide concentration with homologue ratios to specification for optimum bio-fungicide efficacy. Process conditions, and their impact on Bacillus lipopeptide production, were evaluated in fully instrumented laboratory scale bioreactors under well-regulated controlled and defined environments. Factors such as the oxygen availability and trace element and nitrate concentrations had profound influences on lipopeptide yield, productivity and selectivity. Lipopeptide yield and homologue selectivity were enhanced in cultures where the oxygen in the sparge gas was increased from 21 to 30 mole%. The addition of trace elements, particularly Fe2+, increased the total concentration of lipopeptides and a nitrate concentration equivalent to 8 g/L ammonium nitrate resulted in optimum lipopeptide yield and homologue selectivity. Efficacy studies of the culture supernatant containing the crude lipopeptide mixture were conducted using phytopathogens isolated from fruit in the field, identified using genetic sequencing. The supernatant exhibited antifungal activity against all the test-isolates, namely Lewia, Botrytis, Penicillium, Alternaria and Sclerotinia spp., even in this crude form. Thus the lipopeptide product efficacy has been confirmed to control the main diseases, even in the basic crude form. Future studies will be directed towards purification of the lipopeptide product and enhancement of efficacy.

Keywords: antifungal efficacy, biocontrol, lipopeptide production, perishable crops

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Authors: Xinyue Ma, Dishen Zhang, Yijun Liu, Yutian Jiang, Huiyan Yu, Chufeng Gu

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Conformity is defined as one in a social group changing his or her behavior to match the others’ behavior in the group. It is used to find that people show a higher level of online conformity behavior than offline. However, as anonymity can decrease the level of online conformity behavior, the difference between online and offline conformity behavior among Chinese college students still needs to be tested. In this study, college students (N = 60) have been randomly assigned into three groups: control group, offline experimental group, and online experimental group. Through comparing the results of offline experimental group and online experimental group with the Mann-Whitney U test, this study verified the results of Asch’s experiment, and found out that people show a lower level of online conformity behavior than offline, which contradicted the previous finding found in China. These results can be used to explain why some people make a lot of vicious remarks and radical ideas on the Internet but perform normally in their real life: the anonymity of the network makes the online group pressure less than offline, so people are less likely to conform to social norms and public opinions on the Internet. What is more, these results support the importance and relevance of online voting, because fewer online group pressures make it easier for people to expose their true ideas, thus gathering more comprehensive and truthful views and opinions.

Keywords: anonymity, Asch’s group conformity, Chinese college students, online conformity

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Authors: Minhas Alam, Muhammad Hidayat Rasool, Mohsin Khurshid, Bilal Aslam

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The genus Acinetobacter has emerged as a significant concern in hospital-acquired infections, particularly due to the versatility of Acinetobacter baumannii in causing nosocomial infections. The organism's remarkable metabolic adaptability allows it to thrive in various environments, including the environment, animals, and humans. However, the extent of antimicrobial resistance in Acinetobacter species from veterinary settings, especially in developing countries like Pakistan, remains unclear. This study aimed to isolate and characterize Acinetobacter spp. from veterinary settings in Punjab, Pakistan. A total of 2,230 specimens were collected, including 1,960 samples from veterinary settings (nasal and rectal swabs from dairy and beef cattle), 200 from the environment, and 70 from human clinical settings. Isolates were identified using routine microbiological procedures and confirmed by polymerase chain reaction (PCR). Antimicrobial susceptibility was determined by the disc diffusion method, and minimum inhibitory concentration (MIC) was measured by the micro broth dilution method. Molecular techniques, such as PCR and DNA sequencing, were used to screen for antimicrobial-resistant determinants. Genetic diversity was assessed using standard techniques. The results showed that the overall prevalence of A. baumannii in cattle was 6.63% (65/980). However, among cattle, a higher prevalence of A. baumannii was observed in dairy cattle, 7.38% (54/731), followed by beef cattle, 4.41% (11/249). Out of 65 A. baumannii isolates, the carbapenem resistance was found in 18 strains, i.e. 27.7%. The prevalence of A. baumannii in nasopharyngeal swabs was higher, i.e., 87.7% (57/65), as compared to rectal swabs, 12.3% (8/65). Class D β-lactamases genes blaOXA-23 and blaOXA-51 were present in all the CRAB from cattle. Among carbapenem-resistant isolates, 94.4% (17/18) were positive for class B β-lactamases gene blaIMP, whereas the blaNDM-1 gene was detected in only one isolate of A. baumannii. Among 70 clinical isolates of A. baumannii, 58/70 (82.9%) were positive for the blaOXA-23-like gene, and 87.1% (61/70) were CRAB isolates. Among all clinical isolates of A. baumannii, blaOXA-51-like gene was present. Hence, the co-existence of blaOXA-23 and blaOXA-51 was found in 82.85% of clinical isolates. From the environmental settings, a total of 18 A. baumannii isolates were recovered; among these, 38.88% (7/18) strains showed carbapenem resistance. All environmental isolates of A. baumannii harbored class D β-lactamases genes, i.e., blaOXA-51 and blaOXA-23 were detected in 38.9% (7/18) isolates. Hence, the co-existence of blaOXA-23 and blaOXA-51 was found in 38.88% of isolates. From environmental settings, 18 A. baumannii isolates were recovered, with 38.88% showing carbapenem resistance. All environmental isolates harbored blaOXA-51 and blaOXA-23 genes, with co-existence in 38.88% of isolates. MLST results showed ten different sequence types (ST) in clinical isolates, with ST 589 being the most common in carbapenem-resistant isolates. In veterinary isolates, ST2 was most common in CRAB isolates from cattle. Immediate control measures are needed to prevent the transmission of CRAB isolates among animals, the environment, and humans. Further studies are warranted to understand the mechanisms of antibiotic resistance spread and implement effective disease control programs.

Keywords: Acinetobacter baumannii, carbapenemases, drug resistance, MSLT

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Authors: P.P. Rupasinghe, A.H. Farid

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The Aleutian mink disease virus (AMDV, Carnivore amdoparvovirus 1) causes persistent infection, plasmacytosis, and formation and deposition of immune complexes in various organs in adult mink, leading to glomerulonephritis, arteritis and sometimes death. The disease has no cure nor an effective vaccine, and identification and culling of mink positive for anti-AMDV antibodies have not been successful in controlling the infection in many countries. The failure to eradicate the virus from infected farms may be caused by keeping false-negative individuals on the farm, virus transmission from wild animals, or neighboring farms. The identification of sources of infection, which can be performed by comparing viral sequences, is important in the success of viral eradication programs. High mutation rates could cause inaccuracies when viral sequences are used to trace back an infection to its origin. There is no published information on the mutation rate of AMDV either in vivo or in vitro. The in vivo estimation is the most accurate method, but it is difficult to perform because of the inherent technical complexities, namely infecting live animals, the unknown numbers of viral generations (i.e., infection cycles), the removal of deleterious mutations over time and genetic drift. The objective of this study was to determine the mutation rate of AMDV on which no information was available. A homogenate was prepared from the spleen of one naturally infected American mink (Neovison vison) from Nova Scotia, Canada (parental template). The near full-length genome of this isolate (91.6%, 4,143 bp) was bidirectionally sequenced. A group of black mink was inoculated with this homogenate (descendant mink). Spleen sampled were collected from 10 descendant mink after 16 weeks post-inoculation (wpi) and from anther 10 mink after 176 wpi, and their near-full length genomes were bi-directionally sequenced. Sequences of these mink were compared with each other and with the sequence of the parental template. The number of nucleotide substitutions at 176 wpi was 3.1 times greater than that at 16 wpi (113 vs 36) whereas the estimates of mutation rate at 176 wpi was 3.1 times lower than that at 176 wpi (2.85×10-3 vs 9.13×10-4 substitutions/ site/ year), showing a decreasing trend in the mutation rate per unit of time. Although there is no report on in vivo estimate of the mutation rate of DNA viruses in animals using the same method which was used in the current study, these estimates are at the higher range of reported values for DNA viruses determined by various techniques. These high estimates are logical based on the wide range of diversity and pathogenicity of AMDV isolates. The results suggest that increases in the number of nucleotide substitutions over time and subsequent divergence make it difficult to accurately trace back AMDV isolates to their origin when several years elapsed between the two samplings.

Keywords: Aleutian mink disease virus, American mink, mutation rate, nucleotide substitution

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Authors: Nebila Lichiheb, LaToya Myles, William Pendergrass, Bruce Hicks, Dawson Cagle

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Atmospheric transport of hazardous materials in urban areas is increasingly under investigation due to the potential impact on human health and the environment. In response to health and safety concerns, several dispersion models have been developed to analyze and predict the dispersion of hazardous contaminants. The models of interest usually rely on meteorological information obtained from the meteorological models of NOAA’s National Weather Service (NWS). However, due to the complexity of the urban environment, NWS forecasts provide an inadequate basis for dispersion computation in urban areas. A dense meteorological network in Washington, DC, called DCNet, has been operated by NOAA since 2003 to support the development of urban monitoring methodologies and provide the driving meteorological observations for atmospheric transport and dispersion models. This study focuses on the comparison of wind observations from the DCNet station on the U.S. Department of Commerce Herbert C. Hoover Building against the North American Mesoscale (NAM) model outputs for the period 2017-2019. The goal is to develop a simple methodology for modifying NAM outputs so that the dispersion requirements of the city and its urban area can be satisfied. This methodology will allow us to quantify the prediction errors of the NAM model and propose adjustments of key variables controlling dispersion model calculation.

Keywords: meteorological data, Washington D.C., DCNet data, NAM model

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Authors: Hwang Ho Kim, Do Gyun Kim, Jin Young Choi, Sang Chul Park

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Since tire production process is very complicated, company-wide management of it is very difficult, necessitating considerable amounts of capital and labors. Thus, productivity should be enhanced and maintained competitive by developing and applying effective production plans. Among major processes for tire manufacturing, consisting of mixing component preparation, building and curing, the mixing process is an essential and important step because the main component of tire, called compound, is formed at this step. Compound as a rubber synthesis with various characteristics plays its own role required for a tire as a finished product. Meanwhile, scheduling tire mixing process is similar to flexible job shop scheduling problem (FJSSP) because various kinds of compounds have their unique orders of operations, and a set of alternative machines can be used to process each operation. In addition, setup time required for different operations may differ due to alteration of additives. In other words, each operation of mixing processes requires different setup time depending on the previous one, and this kind of feature, called sequence dependent setup time (SDST), is a very important issue in traditional scheduling problems such as flexible job shop scheduling problems. However, despite of its importance, there exist few research works dealing with the tire mixing process. Thus, in this paper, we consider the scheduling problem for tire mixing process and suggest an efficient particle swarm optimization (PSO) algorithm to minimize the makespan for completing all the required jobs belonging to the process. Specifically, we design a particle encoding scheme for the considered scheduling problem, including a processing sequence for compounds and machine allocation information for each job operation, and a method for generating a tire mixing schedule from a given particle. At each iteration, the coordination and velocity of particles are updated, and the current solution is compared with new solution. This procedure is repeated until a stopping condition is satisfied. The performance of the proposed algorithm is validated through a numerical experiment by using some small-sized problem instances expressing the tire mixing process. Furthermore, we compare the solution of the proposed algorithm with it obtained by solving a mixed integer linear programming (MILP) model developed in previous research work. As for performance measure, we define an error rate which can evaluate the difference between two solutions. As a result, we show that PSO algorithm proposed in this paper outperforms MILP model with respect to the effectiveness and efficiency. As the direction for future work, we plan to consider scheduling problems in other processes such as building, curing. We can also extend our current work by considering other performance measures such as weighted makespan or processing times affected by aging or learning effects.

Keywords: compound, error rate, flexible job shop scheduling problem, makespan, particle encoding scheme, particle swarm optimization, sequence dependent setup time, tire mixing process

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Authors: Ayten Ekin Meşe, Selahattin Şentürk, Melike Duvanoğlu

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Petroleum refineries are a highly complex process industry with continuous production and high operating costs. Physical separation of crude oil starts with the crude oil distillation unit, continues with various conversion and purification units, and passes through many stages until obtaining the final product. To meet the desired product specification, process parameters are strictly followed. To be able to ensure the quality of distillates, routine analyses are performed in quality control laboratories based on appropriate international standards such as American Society for Testing and Materials (ASTM) standard methods and European Standard (EN) methods. The cut point of distillates in the crude distillation unit is very crucial for the efficiency of the upcoming processes. In order to maximize the process efficiency, the determination of the quality of distillates should be as fast as possible, reliable, and cost-effective. In this sense, an alternative study was carried out on the crude oil distillation unit that serves the entire refinery process. In this work, studies were conducted with three different crude oil distillates which are Light Straight Run Naphtha (LSRN), Heavy Straight Run Naphtha (HSRN), and Kerosene. These products are named after separation by the number of carbons it contains. LSRN consists of five to six carbon-containing hydrocarbons, HSRN consist of six to ten, and kerosene consists of sixteen to twenty-two carbon-containing hydrocarbons. Physical properties of three different crude distillation unit products (LSRN, HSRN, and Kerosene) were determined using Near-Infrared Spectroscopy with multivariate calibration. The absorbance spectra of the petroleum samples were obtained in the range from 10000 cm⁻¹ to 4000 cm⁻¹, employing a quartz transmittance flow through cell with a 2 mm light path and a resolution of 2 cm⁻¹. A total of 400 samples were collected for each petroleum sample for almost four years. Several different crude oil grades were processed during sample collection times. Extended Multiplicative Signal Correction (EMSC) and Savitzky-Golay (SG) preprocessing techniques were applied to FT-NIR spectra of samples to eliminate baseline shifts and suppress unwanted variation. Two different multivariate calibration approaches (Partial Least Squares Regression, PLS and Genetic Inverse Least Squares, GILS) and an ensemble model were applied to preprocessed FT-NIR spectra. Predictive performance of each multivariate calibration technique and preprocessing techniques were compared, and the best models were chosen according to the reproducibility of ASTM reference methods. This work demonstrates the developed models can be used for routine analysis instead of conventional analytical methods with over 90% accuracy.

Keywords: crude distillation unit, multivariate calibration, near infrared spectroscopy, data preprocessing, refinery

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Authors: Jeanne Leblond, Warren Viricel, Amira Mbarek

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Although several products have reached the market, gene therapeutics are still in their first stages and require optimization. It is possible to improve their lacking efficiency by the use of carefully engineered vectors, able to carry the genetic material through each of the biological barriers they need to cross. In particular, getting inside the cell is a major challenge, because these hydrophilic nucleic acids have to cross the lipid-rich plasmatic and/or endosomal membrane, before being degraded into lysosomes. It takes less than one hour for newly endocytosed liposomes to reach highly acidic lysosomes, meaning that the degradation of the carried gene occurs rapidly, thus limiting the transfection efficiency. We propose to use a new pH-sensitive lipid able to change its conformation upon protonation at endosomal pH values, leading to the disruption of the lipidic bilayer and thus to the fast release of the nucleic acids into the cytosol. It is expected that this new pH-sensitive mechanism promote endosomal escape of the gene, thereby its transfection efficiency. The main challenge of this work was to design a preparation presenting fast-responding lipidic bilayer destabilization properties at endosomal pH 5 while remaining stable at blood pH value and during storage. A series of pH-sensitive lipids able to perform a conformational switch upon acidification were designed and synthesized. Liposomes containing these switchable lipids, as well as co-lipids were prepared and characterized. The liposomes were stable at 4°C and pH 7.4 for several months. Incubation with siRNA led to the full entrapment of nucleic acids as soon as the positive/negative charge ratio was superior to 2. The best liposomal formulation demonstrated a silencing efficiency up to 10% on HeLa cells, very similar to a commercial agent, with a lowest toxicity than the commercial agent. Using flow cytometry and microscopy assays, we demonstrated that drop of pH was required for the transfection efficiency, since bafilomycin blocked the transfection efficiency. Additional evidence was brought by the synthesis of a negative control lipid, which was unable to switch its conformation, and consequently exhibited no transfection ability. Mechanistic studies revealed that the uptake was mediated through endocytosis, by clathrin and caveolae pathways, as reported for previous lipid nanoparticle systems. This potent system was used for the treatment of hypercholesterolemia. The switchable lipids were able to knockdown PCSK9 expression on human hepatocytes (Huh-7). Its efficiency is currently evaluated on in vivo mice model of PCSK9 KO mice. In summary, we designed and optimized a new cationic pH-sensitive lipid for gene delivery. Its transfection efficiency is similar to the best available commercial agent, without the usually associated toxicity. The promising results lead to its use for the treatment of hypercholesterolemia on a mice model. Anticancer applications and pulmonary chronic disease are also currently investigated.

Keywords: liposomes, siRNA, pH-sensitive, molecular switch

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Authors: Naveed Ahmad Fazili

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More than 20 human diseases involve the fibrillation of a specific protein/peptide which forms pathological deposits at various sites. Hereditary lysozyme amyloidosis is a systemic disorder which mostly affects liver, spleen and kidney. This conformational disorder is featured by lysozyme fibril formation. In vivo lysozyme fibrillation was simulated under in vitro conditions using a strong denaturant GdHCl at 3M concentration. Sharp decline in the ANS fluorescence intensity compared to the partially unfolded states, almost 20 fold increase in ThT fluorescence intensity, increase in absorbance at 450 nm suggesting turbidity, negative ellipticity peak in the far-UVCD at 217 nm, red shift of 50 nm compared to the native state in congo red assay and appearance of a network of long rope like fibrils in TEM analysis suggested HEWL fibrillation. Anti-fibrillation potency of baicalein against the preformed fibrils of HEWL was investigated following ThT assay in which there was a dose dependent decrease in ThT fluorescence intensity compared to the fibrillar state of HEWL with the maximum effect observed at 150 μM baicalein concentration, loss of negative ellipticity peak in the far-UVCD region, dip in the Rayleigh scattering intensity and absorbance at 350 nm and 450 nm respectively together with a reduction in the density of fibrillar structure in TEM imaging. Thus, it could be suggested that baicalein could prove to be a positive therapeutics for hereditary human lysozyme amyloidosis.

Keywords: amyloid fibrils, baicalein, congo red, negative ellipticity, therapeutics

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Authors: Nicole Merkle, Stefan Zander

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Ambient Assisted Living (AAL) describes a technological and methodological stack of (e.g. formal model-theoretic semantics, rule-based reasoning and machine learning), different aspects regarding the behavior, activities and characteristics of humans. Hence, a semantic representation of the user environment and its relevant elements are required in order to allow assistive agents to recognize situations and deduce appropriate actions. Furthermore, the user and his/her characteristics (e.g. physical, cognitive, preferences) need to be represented with a high degree of expressiveness in order to allow software agents a precise evaluation of the users’ context models. The correct interpretation of these context models highly depends on temporal, spatial circumstances as well as individual user preferences. In most AAL approaches, model representations of real world situations represent the current state of a universe of discourse at a given point in time by neglecting transitions between a set of states. However, the AAL domain currently lacks sufficient approaches that contemplate on the dynamic adaptions of context-related representations. Semantic representations of relevant real-world excerpts (e.g. user activities) help cognitive, rule-based agents to reason and make decisions in order to help users in appropriate tasks and situations. Furthermore, rules and reasoning on semantic models are not sufficient for handling uncertainty and fuzzy situations. A certain situation can require different (re-)actions in order to achieve the best results with respect to the user and his/her needs. But what is the best result? To answer this question, we need to consider that every smart agent requires to achieve an objective, but this objective is mostly defined by domain experts who can also fail in their estimation of what is desired by the user and what not. Hence, a smart agent has to be able to learn from context history data and estimate or predict what is most likely in certain contexts. Furthermore, different agents with contrary objectives can cause collisions as their actions influence the user’s context and constituting conditions in unintended or uncontrolled ways. We present an approach for dynamically updating a semantic model with respect to the current user context that allows flexibility of the software agents and enhances their conformance in order to improve the user experience. The presented approach adapts rules by learning sensor evidence and user actions using probabilistic reasoning approaches, based on given expert knowledge. The semantic domain model consists basically of device-, service- and user profile representations. In this paper, we present how this semantic domain model can be used in order to compute the probability of matching rules and actions. We apply this probability estimation to compare the current domain model representation with the computed one in order to adapt the formal semantic representation. Our approach aims at minimizing the likelihood of unintended interferences in order to eliminate conflicts and unpredictable side-effects by updating pre-defined expert knowledge according to the most probable context representation. This enables agents to adapt to dynamic changes in the environment which enhances the provision of adequate assistance and affects positively the user satisfaction.

Keywords: ambient intelligence, machine learning, semantic web, software agents

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Authors: Saeed Karimi, Ali Behbahaninia

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In this study, the design and optimization of combined cooling, heating, and power system (CCHP) for a sustainable building are dealt with. Sustainable buildings are environmentally responsible and help us to save energy also reducing waste, pollution and environmental degradation. CCHP systems are widely used to save energy sources. In these systems, electricity, cooling, and heating are generating using just one primary energy source. The selection of the size of components based on the maximum demand of users will lead to an increase in the total cost of energy and equipment for the building complex. For this purpose, a system was designed in which the prime mover (gas turbine), heat recovery boiler, and absorption chiller are lower than the needed maximum. The difference in months with peak consumption is supplied with the help of electrical absorption chiller and auxiliary boiler (and the national electricity network). In this study, the optimum capacities of each of the equipment are determined based on Thermo economic method, in a way that the annual capital cost and energy consumption will be the lowest. The design was done for a gas turbine prime mover, and finally, the optimum designs were investigated using exergy analysis and were compared with a traditional energy supply system.

Keywords: sustainable building, CCHP, energy optimization, gas turbine, exergy, thermo-economic

Procedia PDF Downloads 75

Authors: Weerawan Marangkun

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This study is a survey intended to investigate cost, revenue and factors affecting changes in revenue and to provide guidelines for improving factors affecting changes in revenue from tourist walking street activities in Songkhla City Municipality. Instruments used in this study were structured interviews, using Yaman table (1973) where the random sampling error was+ 10%. The sample consisting of 83 entrepreneurs were drawn from a total population of 272. The purposive sampling method was used. Data were collected during the 6-month period from December 2011 until May 2012. The findings indicate that the cost paid by an entrepreneur in connection with his/her services for tourists is mainly for travel, which stands at about 290 Baht per day. Each entrepreneur earns about 3,850 Baht per day, which means about 400,000 Baht per year. The combined total revenue from walking street tourist activities is about 108.8 million Baht per year. Such activities add economic value to tourist facilities due to expenditures by tourists and provide the entrepreneurs with considerable income. Factors affecting changes in revenue from tourist walking street activities are: the increase in the number of entrepreneurs; the holding of trade fairs, events or interesting shows in the vicinity; and weather conditions (e.g. abundant rainfall, which can contribute to a decrease in the number of tourists). Suggested measures to improve factors affecting changes in the income are: addition or creation of new activities; regulation of operations of the stalls and parking area; and generation of greater publicity through the social network.

Keywords: cost, revenue, tourist, walking street

Procedia PDF Downloads 346

Authors: Alexander Rodríguez-Hernández, Arnulfo Rojas-Perez, Liz Diaz-Vazquez

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The rise in consumerism over the past century has resulted in the creation of higher amounts of plasticizers, personal care products and other chemical substances, which enter and accumulate in water systems. Other sources of pollutants in Neotropical regions experience large inputs of nutrients with these pollutants resulting in eutrophication of water which consume large quantities of oxygen, resulting in high fish mortality. This dilemma has created a need for the development of targeted detection in complex matrices and remediation of emerging contaminants. We have synthesized carbon nanoparticles from macro algae (Ulva fasciata) by oxidizing the graphitic carbon network under extreme acidic conditions. The resulting material was characterized by STEM, yielding a spherical 12 nm average diameter nanoparticles, which can be fixed into a polysaccharide aerogel synthesized from the same macro algae. Spectrophotometer analyses show a pH dependent fluorescent behavior varying from 450-620 nm in aqueous media. Heavily oxidized edges provide for easy functionalization with enzymes for a more targeted analysis and remediation technique. Given the optical properties of the carbon base nanoparticles and the numerous possibilities of functionalization, we have developed a selective and robust targeted bio-detection and bioremediation technique for the treatment of emerging contaminants in complex matrices like estuarine embayment.

Keywords: aerogels, carbon nanoparticles, fluorescent, targeted analysis

Procedia PDF Downloads 228