Search results for: technical trading signal

Authors: Vinod Kumar Gupta, Narendrakumar M. Chaudhari, Suchismitha Iskepalli, Chitra Dutta

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Background-The community composition of the human microbiome is known to vary at distinct anatomical niches. But little is known about the nature of variations if any, at the genome/sub-genome levels of a specific microbial community across different niches. The present report aims to explore, as a case study, the variations in gene repertoire of 28 Prevotella reference draft genomes derived from different body-sites of human, as reported earlier by the Human Microbiome Consortium. Results-The analysis reveals the exclusive presence of 11798, 3673, 3348 and 934 gene families and exclusive absence of 17, 221, 115 and 645 gene families in Prevotella genomes derived from the human oral cavity, gastro-intestinal tracts (GIT), urogenital tract (UGT) and skin, respectively. The pan-genome for Prevotella remains “open”. Distribution of various functional COG categories differs appreciably among the habitat-specific genes, within Prevotella pan-genome and between the GIT-derived Bacteroides and Prevotella. The skin and GIT isolates of Prevotella are enriched in singletons involved in Signal transduction mechanisms, while the UGT and oral isolates show higher representation of the Defense mechanisms category. No niche-specific variations could be observed in the distribution of KEGG pathways. Conclusion-Prevotella may have developed distinct genetic strategies for adaptation to different anatomical habitats through selective, niche-specific acquisition and elimination of suitable gene-families. In addition, individual microorganisms tend to develop their own distinctive adaptive stratagems through large repertoires of singletons. Such in situ, habitat-driven refurbishment of the genetic makeup can impart substantial intra-lineage genome diversity within the microbes without perturbing their general taxonomic heritage.

Keywords: body niche adaptation, human microbiome, pangenome, Prevotella

Procedia PDF Downloads 251

Authors: Sahar Abbaszadeh, Sharifah Rafidah Wan Alwi, Colin Webb, Nahid Ghasemi, Ida Idayu Muhamad

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Toxic heavy metal discharges into environment due to rapid industrialization is a serious pollution problem that has drawn global attention towards their adverse impacts on both the structure of ecological systems as well as human health. Lead as toxic and bio-accumulating elements through the food chain, is regularly entering to water bodies from discharges of industries such as plating, mining activities, battery manufacture, paint manufacture, etc. The application of conventional methods to degrease and remove Pb(II) ion from wastewater is often restricted due to technical and economic constrains. Therefore, the use of various agro-wastes as low-cost bioadsorbent is found to be attractive since they are abundantly available and cheap. In this study, activated carbon of papaya peel (AC-PP) (as locally available agricultural waste) was employed to evaluate its Pb(II) uptake capacity from single-solute solutions in sets of batch mode experiments. To assess the surface characteristics of the adsorbents, the scanning electron microscope (SEM) coupled with energy disperse X-ray (EDX), and Fourier transform infrared spectroscopy (FT-IR) analysis were utilized. The removal amount of Pb(II) was determined by atomic adsorption spectrometry (AAS). The effects of pH, contact time, the initial concentration of Pb(II) and adsorbent dosage were investigated. The pH value = 5 was observed as optimum solution pH. The optimum initial concentration of Pb(II) in the solution for AC-PP was found to be 200 mg/l where the amount of Pb(II) removed was 36.42 mg/g. At the agitating time of 2 h, the adsorption processes using 100 mg dosage of AC-PP reached equilibrium. The experimental results exhibit high capability and metal affinity of modified papaya peel waste with removal efficiency of 93.22 %. The evaluation results show that the equilibrium adsorption of Pb(II) was best expressed by Freundlich isotherm model (R2 > 0.93). The experimental results confirmed that AC-PP potentially can be employed as an alternative adsorbent for Pb(II) uptake from industrial wastewater for the design of an environmentally friendly yet economical wastewater treatment process.

Keywords: activated carbon, bioadsorption, lead removal, papaya peel, wastewater treatment

Procedia PDF Downloads 287

Authors: Jiwon Lee, Yeong-Ju Go, Jong-Soo Choi

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Drones were first developed for military use and were used in World War 1. But recently drones have been used in a variety of fields. Several companies actively utilize drone technology to strengthen their services, and in agriculture, drones are used for crop monitoring and sowing. Other people use drones for hobby activities such as photography. However, as the range of use of drones expands rapidly, problems caused by drones such as improperly flying, privacy and terrorism are also increasing. As the need for monitoring and tracking of drones increases, researches are progressing accordingly. The drone detection system estimates the position of the drone using the physical phenomena that occur when the drones fly. The drone detection system measures being developed utilize many approaches, such as radar, infrared camera, and acoustic detection systems. Among the various drone detection system, the acoustic detection system is advantageous in that the microphone array system is small, inexpensive, and easy to operate than other systems. In this paper, the acoustic signal is acquired by using minimum microphone when drone is flying, and direction of drone is estimated. When estimating the Direction of Arrival(DOA), there is a method of calculating the DOA based on the Time Difference of Arrival(TDOA) and a method of calculating the DOA based on the beamforming. The TDOA technique requires less number of microphones than the beamforming technique, but is weak in noisy environments and can only estimate the DOA of a single source. The beamforming technique requires more microphones than the TDOA technique. However, it is strong against the noisy environment and it is possible to simultaneously estimate the DOA of several drones. When estimating the DOA using acoustic signals emitted from the drone, it is impossible to measure the position of the drone, and only the direction can be estimated. To overcome this problem, in this work we show how to estimate the position of drones by arranging multiple microphone arrays. The microphone array used in the experiments was four tetrahedral microphones. We simulated the performance of each DOA algorithm and demonstrated the simulation results through experiments.

Keywords: acoustic sensing, direction of arrival, drone detection, microphone array

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Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Mazyar Yosofi, Olivier Kerbrat, Pascal Mognol

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Life cycle assessment of additive manufacturing processes has evolved significantly since these past years. A lot of existing studies mainly focused on energy consumption. Nowadays, new methodologies of life cycle inventory acquisition came through the literature and help manufacturers to take into account all the input and output flows during the manufacturing step of the life cycle of products. Indeed, the environmental analysis of the phenomena that occur during the manufacturing step of additive manufacturing processes is going to be well known. Now it becomes possible to count and measure accurately all the inventory data during the manufacturing step. Optimization of the environmental performances of processes can now be considered. Environmental performance improvement can be made by varying process parameters. However, a lot of these parameters (such as manufacturing speed, the power of the energy source, quantity of support materials) affect directly the mechanical properties, surface finish and the dimensional accuracy of a functional part. This study aims to improve the environmental performance of an additive manufacturing process without deterioration of the part quality. For that purpose, the authors have developed a generic method that has been applied on multiple parts made by additive manufacturing processes. First, a complete analysis of the process parameters is made in order to identify which parameters affect only the environmental performances of the process. Then, multiple parts are manufactured by varying the identified parameters. The aim of the second step is to find the optimum value of the parameters that decrease significantly the environmental impact of the process and keep the part quality as desired. Finally, a comparison between the part made by initials parameters and changed parameters is made. In this study, the major finding claims by authors is to reduce the environmental impact of an additive manufacturing process while respecting the three quality criterion of parts, mechanical properties, dimensional accuracy and surface roughness. Now that additive manufacturing processes can be seen as mature from a technical point of view, environmental improvement of these processes can be considered while respecting the part properties. The first part of this study presents the methodology applied to multiple academic parts. Then, the validity of the methodology is demonstrated on functional parts.

Keywords: additive manufacturing, environmental impact, environmental improvement, mechanical properties

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Authors: Wanjiku Karanja

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Facebook has monopoly power in the social networking market. It has grown and entrenched its monopoly power through the capture of its users’ data value chains. However, antitrust law’s consumer welfare roots have prevented it from effectively addressing the role of data capture in Facebook’s market dominance. These regulatory blind spots are augmented in Facebook’s proposed Diem cryptocurrency project and its Novi Digital wallet. Novi, which is Diem’s digital identity component, shall enable Facebook to collect an unprecedented volume of consumer data. Consequently, Novi has seismic implications on internet identity as the network effects of Facebook’s large user base could establish it as the de facto internet identity layer. Moreover, the large tracts of data Facebook shall collect through Novi shall further entrench Facebook's market power. As such, the attendant lock-in effects of this project shall be very difficult to reverse. Urgent regulatory action is therefore required to prevent this expansion of Facebook’s data resources and monopoly power. This research thus highlights the importance of data capture to competition and market health in the social networking industry. It utilizes interviews with key experts to empirically interrogate the impact of Facebook’s data capture and control of its users’ data value chains on its market power. This inquiry is contextualized against Novi’s expansive effect on Facebook’s data value chains. It thus addresses the novel antitrust issues arising at the nexus of Facebook’s monopoly power and the privacy of its users’ data. It also explores the impact of platform design principles, specifically data portability and data portability, in mitigating Facebook’s anti-competitive practices. As such, this study finds that Facebook is a powerful monopoly that dominates the social media industry to the detriment of potential competitors. Facebook derives its power from its size, annexure of the consumer data value chain, and control of its users’ social graphs. Additionally, the platform design principles of data interoperability and data portability are not a panacea to restoring competition in the social networking market. Their success depends on the establishment of robust technical standards and regulatory frameworks.

Keywords: antitrust law, data protection law, data portability, data interoperability, digital identity, Facebook

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Authors: Mabel Usunobun Olanipekun, Henry Ogbemudia Omoregbee

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Anomalies such as water pipeline and hydraulic or petrochemical pipeline network leakages and bursts have significant implications for economic conditions and the environment. In order to ensure pipeline systems are reliable, they must be efficiently controlled. Wireless Sensor Networks (WSNs) have become a powerful network with critical infrastructure monitoring systems for water, oil and gas pipelines. The loss of water, oil and gas is inevitable and is strongly linked to financial costs and environmental problems, and its avoidance often leads to saving of economic resources. Substantial repair costs and the loss of precious natural resources are part of the financial impact of leaking pipes. Pipeline systems experts have implemented various methodologies in recent decades to identify and locate leakages in water, oil and gas supply networks. These methodologies include, among others, the use of acoustic sensors, measurements, abrupt statistical analysis etc. The issue of leak quantification is to estimate, given some observations about that network, the size and location of one or more leaks in a water pipeline network. In detecting background leakage, however, there is a greater uncertainty in using these methodologies since their output is not so reliable. In this work, we are presenting a scalable concept and simulation where a pressure-driven model (PDM) was used to determine water pipeline leakage in a system network. These pressure data were collected with the use of acoustic sensors located at various node points after a predetermined distance apart. We were able to determine with the use of correlation difference to determine the leakage point locally introduced at a predetermined point between two consecutive nodes, causing a substantial pressure difference between in a pipeline network. After de-noising the signal from the sensors at the nodes, we successfully obtained the exact point where we introduced the local leakage using the correlation difference model we developed.

Keywords: leakage detection, acoustic signals, pipeline network, correlation, wireless sensor networks (WSNs)

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Authors: Ramin Ghasemi Shayan, Morteza Janebifam

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Tumors are regularly inhomogeneous. Provincial varieties in death, metabolic action, multiplication and body part are watched. There’s expanding proof that strong tumors may contain subpopulations of cells with various genotypes and phenotypes. These unmistakable populaces of malignancy cells can connect during a serious way and may contrast in affectability to medications. Most tumors show organic heterogeneity1–3 remembering heterogeneity for genomic subtypes, varieties inside the statement of development variables and genius, and hostile to angiogenic factors4–9 and varieties inside the tumoural microenvironment. These can present as contrasts between tumors in a few people. for instance, O6-methylguanine-DNA methyltransferase, a DNA fix compound, is hushed by methylation of the quality advertiser in half of glioblastoma (GBM), adding to chemosensitivity, and improved endurance. From the outset, there includes been specific enthusiasm inside the usage of dissemination weighted imaging (DWI) and dynamic complexity upgraded MRI (DCE-MRI). DWI sharpens MRI to water dispersion inside the extravascular extracellular space (EES) and is wiped out with the size and setup of the cell populace. Additionally, DCE-MRI utilizes dynamic obtaining of pictures during and after the infusion of intravenous complexity operator. Signal changes are additionally changed to outright grouping of differentiation permitting examination utilizing pharmacokinetic models. PET scan modality gives one of a kind natural particularity, permitting dynamic or static imaging of organic atoms marked with positron emanating isotopes (for example, 15O, 18F, 11C). The strategy is explained to a colossal radiation portion, which points of confinement rehashed estimations, particularly when utilized together with PC tomography (CT). At long last, it's of incredible enthusiasm to quantify territorial hemoglobin state, which could be joined with DCE-CT vascular physiology estimation to create significant experiences for understanding tumor hypoxia.

Keywords: heterogeneity, computerized tomography scan, magnetic resonance imaging, PET

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Authors: Scott R. Butler

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Ontario, Canada’s largest province, is in the midst of an interesting experiment in mandated asset management planning for local governments. At the beginning of 2021, Ontario’s 444 municipalities were responsible for the management of 302,864 lane kilometers of roads that have a replacement cost of $97.545 billion CDN. Roadways are by far the most complex, expensive, and extensive assets that a municipality is responsible for overseeing. Since adopting Ontario Regulation 588/47: Asset Management Planning for Municipal Infrastructure in 2017, the provincial government has established prescriptions for local road authorities regarding asset category and levels of service being provided. This provincial regulation further stipulates that asset data such as extent, condition, and life cycle costing are to be captured in manner compliant with qualitative descriptions and technical metrics. The Ontario Good Roads Association undertook an exercise to aggregate the road-related data contained within the 444 asset management plans that municipalities have filed with the provincial government. This analysis concluded that collectively Ontario municipal roadways have a $34.7 billion CDN in deferred maintenance. The ill-state of repair of Ontario municipal roads has lasting implications for province’s economic competitiveness and has garnered considerable political attention. Municipal efforts to address the maintenance backlog are stymied by the extremely limited fiscal parameters municipalities must operate within in Ontario. Further exacerbating the program are provincially designed programs that are ineffective, administratively burdensome, and not necessarily aligned with local priorities or strategies. This paper addresses how municipal asset management plans – and more specifically, the data contained in these plans – can be used to design innovative policy frameworks, flexible funding programs, and new levels of service that respond to these funding challenges, as well as emerging issues such as local economic development and climate change. To fully unlock the potential that Ontario Regulation 588/17 has imposed will require a resolute commitment to data standardization and horizontal collaboration between municipalities within regions.

Keywords: transportation, municipal asset management, subnational policy design, subnational funding program design

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Authors: K. Raghu, Sree Harsha

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The interrelationship between the technology and architecture of tall buildings is investigated from the emergence of tall buildings in late 19th century to the present. In the late 19th century early designs of tall buildings recognized the effectiveness of diagonal bracing members in resisting lateral forces. Most of the structural systems deployed for early tall buildings were steel frames with diagonal bracings of various configurations such as X, K, and eccentric. Though the historical research a filtering concept is developed original and remedial technology- through which one can clearly understand inter-relationship between the technical evolution and architectural esthetic and further stylistic transition buildings. Diagonalized grid structures – “diagrids” - have emerged as one of the most innovative and adaptable approaches to structuring buildings in this millennium. Variations of the diagrid system have evolved to the point of making its use non-exclusive to the tall building. Diagrid construction is also to be found in a range of innovative mid-rise steel projects. Contemporary design practice of tall buildings is reviewed and design guidelines are provided for new design trends. Investigated in depths are the behavioral characteristics and design methodology for diagrids structures, which emerge as a new direction in the design of tall buildings with their powerful structural rationale and symbolic architectural expression. Moreover, new technologies for tall building structures and facades are developed for performance enhancement through design integration, and their architectural potentials are explored. By considering the above data the analysis and design of 40-100 storey diagrids steel buildings is carried out using E-TABS software with diagrids of various angle to be found for entire building which will be helpful to reduce the steel requirement for the structure. The present project will have to undertake wind analysis, seismic analysis for lateral loads acting on the structure due to wind loads, earthquake loads, gravity loads. All structural members are designed as per IS 800-2007 considering all load combination. Comparison of results in terms of time period, top storey displacement and inter-storey drift to be carried out. The secondary effect like temperature variations are not considered in the design assuming small variation.

Keywords: diagrid, bracings, structural, building

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Authors: Chatrabhuti Pipop, Visessri Supattra, Charinpanitkul Tawatchai

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Durian is one of the top agricultural products exported by Thailand. There is the massive market potential for the durian industry. While the global demand for Thai durians, especially the demand from China, is very high, Thailand's durian supply is far from satisfying strong demand. Poor agricultural practices result in low yields and poor quality of fruit. Most irrigation systems currently used by the farmers are fixed schedule or fixed rates that ignore actual weather conditions and crop water requirements. In addition, the technologies emerging are too difficult and complex and prices are too high for the farmers to adopt and afford. Many farmers leave the durian trees to grow naturally. With improper irrigation and nutrient management system, durians are vulnerable to a variety of issues, including stunted growth, not flowering, diseases, and death. Technical development or research for durian is much needed to support the wellbeing of the farmers and the economic development of the country. However, there are a limited number of studies or development projects for durian because durian is a perennial crop requiring a long time to obtain the results to report. This study, therefore, aims to address the problem of durian production by developing an autonomous and precision irrigation system. The system is designed and equipped with an industrial programmable controller, a weather station, and a digital flow meter. Daily water requirements are computed based on weather data such as rainfall and evapotranspiration for daily irrigation with variable flow rates. A prediction model is also designed as a part of the system to enhance the irrigation schedule. Before the system was installed in the field, a simulation model was built and tested in a laboratory setting to ensure its accuracy. Water consumption was measured daily before and after the experiment for further analysis. With this system, the crop water requirement is precisely estimated and optimized based on the data from the weather station. Durian will be irrigated at the right amount and at the right time, offering the opportunity for higher yield and higher income to the farmers.

Keywords: Durian, precision irrigation, precision agriculture, smart farm

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Authors: Elizabeth Loza-Valerdi, Victor Pardiñas-Rios, Arnulfo Pluma-Pluma, Andres Breton-Toral, Julio Cercado-Jaramillo

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The purification processes for mixtures of isomeric monosaccharides using industrial chromatographic methods poses a serious technical challenge. Mixtures of 2 or 3 monosaccharides are difficult to separate by strictly physical or chemical techniques. Differential fermentation by microbial cultures is an increasingly interesting way of selective enrichment in a particular kind of monosaccharides when a mixture of them is present in the solution, and only one has economical value. Osmotolerant yeast cultures provide an interesting source of biocatalysts for the selective catabolism of monosaccharides in media containing high concentrations of total soluble sugars. A collection of 398 yeast strains has been obtained using endemic and unique sources of fruit juices, industrial syrups, honey, and other high sugar content substrates, either natural or man made, products and by-products from Mexico. The osmotolerance of the strains was assessed by plate assay both in glucose (20-40-60%w/w). Strains were classified according to their osmotolerance in low, medium or highly tolerant to high glucose concentrations. The purified cultures were tested by their ability to growth in a solid plate media or liquid media of Yeas Nitrogen Base (YNB), added with specific monosaccharides as sole carbon source (glucose, galactose, lactose and fructose). Selected strains were subsequently tested in fermentation experiments with mixtures of two monosaccharides (galactose/glucose and glucose/fructose). Their ability to grow and selectively catabolize one monosaccharide was evaluated. Growth, fermentation activity and products of metabolism were determined by plate counts, CO2 production, turbidity and chromatographic analysis by HPLC. Selective catabolism of one monosaccharide in liquid media containing two monosaccharides was confirmed for 8 strains. Ion Exchange chromatographic processes were used in production of high fructose or galactose syrup. Laboratory scale processes for the production of fructose or galactose enriched syrups is now feasible, with important applications in food (like high fructose syrup as edulcorant) and fermentation technology (for GOS production).

Keywords: osmotolerant yeasts, selective metabolism, fructose syrup, GOS

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Authors: Izadpanh Shaghayegh, Adli Fateme

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Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by motor symptoms, including tremors, bradykinesia, rigidity, and freezing of gait (FOG), which arise from degeneration of the basal ganglia. While pharmacological treatments, particularly dopaminergic therapies, remain the primary approach for managing PD, their long-term effectiveness diminishes due to complications such as dyskinesia and motor fluctuations. Deep brain stimulation (DBS) has emerged as an alternative for symptom management but remains invasive, costly, and associated with significant risks. In light of these challenges, non-invasive brain stimulation (NIBS) techniques are gaining attention as promising alternatives for treating PD. These methods, including transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS), and microwave brain stimulation (MBS), offer advantages such as reduced risk and non-invasiveness while providing targeted modulation of brain activity. Recent innovations, such as hemispherical antenna arrays for focused stimulation and advanced signal patterns like high-frequency prime harmonics and temporal interference (TI), have further enhanced the precision and efficacy of NIBS. These techniques have shown potential in modulating neuronal excitability, improving gait, and reducing motor symptoms in PD patients, with some approaches demonstrating effectiveness in treating FOG. Despite promising results, continued research is necessary to refine these technologies, optimize treatment protocols, and evaluate their long-term impact on PD progression. This review highlights recent advances in non-invasive brain stimulation for PD and discusses their potential as adjunctive therapies for managing motor symptoms and improving quality of life in PD patients.

Keywords: Parkinson’s disease, non-invasive brain stimulation, deep brain stimulation, transcranial magnetic stimulation, transcranial direct current stimulation, freezing of gait, microwave brain stimulation, neuromodulation

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Authors: Reeta Devi, Hitender Kumar Tyagi, Dinesh Kumar

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In present scenario, cardiovascular problems are growing challenge for researchers and physiologists. As heart disease have no geographic, gender or socioeconomic specific reasons; detecting cardiac irregularities at early stage followed by quick and correct treatment is very important. Electrocardiogram is the finest tool for continuous monitoring of heart activity. Heart rate variability (HRV) is used to measure naturally occurring oscillations between consecutive cardiac cycles. Analysis of this variability is carried out using time domain, frequency domain and non-linear parameters. This paper presents HRV analysis of the online dataset for normal sinus rhythm (taken as healthy subject) and sudden cardiac death (SCD subject) using all three methods computing values for parameters like standard deviation of node to node intervals (SDNN), square root of mean of the sequences of difference between adjacent RR intervals (RMSSD), mean of R to R intervals (mean RR) in time domain, very low-frequency (VLF), low-frequency (LF), high frequency (HF) and ratio of low to high frequency (LF/HF ratio) in frequency domain and Poincare plot for non linear analysis. To differentiate HRV of healthy subject from subject died with SCD, k –nearest neighbor (k-NN) classifier has been used because of its high accuracy. Results show highly reduced values for all stated parameters for SCD subjects as compared to healthy ones. As the dataset used for SCD patients is recording of their ECG signal one hour prior to their death, it is therefore, verified with an accuracy of 95% that proposed algorithm can identify mortality risk of a patient one hour before its death. The identification of a patient’s mortality risk at such an early stage may prevent him/her meeting sudden death if in-time and right treatment is given by the doctor.

Keywords: early stage prediction, heart rate variability, linear and non-linear analysis, sudden cardiac death

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Authors: Pieter De Vries, Renate Klaassen, Maria Ioannides

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This paper is about an explorative research into the use of emerging technologies for teaching and learning in higher engineering education. The assumption is that these technologies and applications, which are not yet widely adopted, will help to improve education and as such actively work on the ability to better deal with the mismatch of skills bothering our industries. Technologies such as 3D printing, the Internet of Things, Virtual Reality, and others, are in a dynamic state of development which makes it difficult to grasp the value for education. Also, the instruments in current educational research seem not appropriate to assess the value of such technologies. This explorative research aims to foster an approach to better deal with this new complexity. The need to find out is urgent, because these technologies will be dominantly present in the near future in all aspects of life, including education. The methodology used in this research comprised an inventory of emerging technologies and tools that potentially give way to innovation and are used or about to be used in technical universities. The inventory was based on both a literature review and a review of reports and web resources like blogs and others and included a series of interviews with stakeholders in engineering education and at representative industries. In addition, a number of small experiments were executed with the aim to analyze the requirements for the use of in this case Virtual Reality and the Internet of Things to better understanding the opportunities and limitations in the day-today learning environment. The major findings indicate that it is rather difficult to decide about the value of these technologies for education due to the dynamic state of change and therefor unpredictability and the lack of a coherent policy at the institutions. Most decisions are being made by teachers on an individual basis, who in their micro-environment are not equipped to select, test and ultimately decide about the use of these technologies. Most experiences are being made in the industry knowing that the skills to handle these technologies are in high demand. The industry though is worried about the inclination and the capability of education to help bridge the skills gap related to the emergence of new technologies. Due to the complexity, the diversity, the speed of development and the decay, education is challenged to develop an approach that can make these technologies work in an integrated fashion. For education to fully profit from the opportunities, these technologies offer it is eminent to develop a pro-active strategy and a sustainable approach to frame the emerging technologies development.

Keywords: emerging technologies, internet of things, pro-active strategy, virtual reality

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Authors: Manar Makhoul, Buthainah Alsalamah, Salam Lawand, Hassan Azzam

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The major storage proteins in endosperm of 33 cultivated and wild barley genotypes (H.vulgare, H. spontaneum, H. bulbosum, H. murinum, H. marinum) were analyzed to demonstrate the variation in the hordein polypeptides encoded by multigene families in grains. The SDS-PAGE revealed 13 and 17 alleles at the Hor1 and the Hor2 loci respectively, with frequencies from 0.83 to 14 and 0.56 to 13.41% respectively, while seven alleles at the Hor3 locus with frequencies from 3.63 to 30.91% were recognized. The phylogenetic analysis indicated to relevance of the polymorphism in hordein patterns as successful tool in identifying the individual genotypes and discriminating the species according to genome type. We also reported in this research complete nucleotide sequence B-hordein genes of seven wild and cultivated barley genotypes. A 152bp upstream sequence of B-hordein promoter contained a TATA box, CATC box, AAAG motif, N-motif and E-motif. In silico analysis of B-Hordein sequences demonstrated that the coding regions were not interrupted by any intron, and included the complete ORF which varied between 882 and 906 bp, and encoded mature proteins with 293-301 residues characterized by high contents of glutamine (29%), and proline (18%). Comparison of the predicted polypeptide sequences with the published ones suggested that all S-rich prolamins genes are descended from common ancestor. The sequence started at N-terminal with a signal peptide, and then followed directly by two domains; a repetitive one based on the repetition of the repeat unit PQQPFPQQ and C-terminal domain. Also, it was found that positions of the eight cysteine residues were highly conserved in all the B-hordein sequences, but Hordeum bulbosum had additional unpaired one. The phylogenetic tree of B-hordein polypeptide separated the genotypes in distinct seven subgroups. In general, the high homology between B-hordeins and LMW glutenin subunits suggests similar bread-making influences for these B-hordeins.

Keywords: hordeum, phylogenetic tree, sequencing, storage protein

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Authors: Ifigeneia V. Mavragani, Zacharenia Nikitaki, George Kalantzis, George Iliakis, Alexandros G. Georgakilas

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Complex DNA damage consisting of a combination of DNA lesions, such as Double Strand Breaks (DSBs) and non-DSB base lesions occurring in a small volume is considered as one of the most important biological endpoints regarding ionizing radiation (IR) exposure. Strong theoretical (Monte Carlo simulations) and experimental evidence suggests an increment of the complexity of DNA damage and therefore repair resistance with increasing linear energy transfer (LET). Experimental detection of complex (clustered) DNA damage is often associated with technical deficiencies limiting its measurement, especially in cellular or tissue systems. Our groups have recently made significant improvements towards the identification of key parameters relating to the efficient detection of complex DSBs and non-DSBs in human cellular systems exposed to IR of varying quality (γ-, X-rays 0.3-1 keV/μm, α-particles 116 keV/μm and 36Ar ions 270 keV/μm). The induction and processing of DSB and non-DSB-oxidative clusters were measured using adaptations of immunofluorescence (γH2AX or 53PB1 foci staining as DSB probes and human repair enzymes OGG1 or APE1 as probes for oxidized purines and abasic sites respectively). In the current study, Relative Biological Effectiveness (RBE) values for DSB and non-DSB induction have been measured in different human normal (FEP18-11-T1) and cancerous cell lines (MCF7, HepG2, A549, MO59K/J). The experimental results are compared to simulation data obtained using a validated microdosimetric fast Monte Carlo DNA Damage Simulation code (MCDS). Moreover, this simulation approach is implemented in two realistic clinical cases, i.e. prostate cancer treatment using X-rays generated by a linear accelerator and a pediatric osteosarcoma case using a 200.6 MeV proton pencil beam. RBE values for complex DNA damage induction are calculated for the tumor areas. These results reveal a disparity between theory and experiment and underline the necessity for implementing highly precise and more efficient experimental and simulation approaches.

Keywords: complex DNA damage, DNA damage simulation, protons, radiotherapy

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Authors: Muna Al-Siyabi

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When students bring mobile devices into the classrooms, they are frequently viewed as distractions from their daily educational practices rather than developing the twenty-first century skills. Such skills may involve sorting and extracting information, solving problems and evaluating results. Mobile devices, such as smartphones and tablets, have great potential for learning. Currently, schools and universities are embracing these devices with the aim of enhancing education. In Oman, mobile technologies have been introduced in the last ten years in two private schools to keep pace with the technological advancement. The researcher set out to examine the benefits and challenges of employing mobile learning in these two schools with the aim to inform the implementation of mobile technologies in more schools in Oman. The total of 16 teachers and 237 students responded to questionnaires, and 7 teachers and three student focus groups (of 13 students) were involved in interviews to explore how mobile technologies are used in these two schools. The questionnaires indicated that 87.5% of the sample teachers considered mobile learning helpful for learning and teaching. The teachers believed that mobile learning could promote learning, help teaching, offer vast resources, motivate students and save lesson time. Moreover, interviews with the teachers showed that mobile learning could offer several benefits like immediacy, saving lesson time, supporting differentiation, opportunities to learn anywhere, showing understanding, and offering vast resources. Most of the sample were also facing technical and classroom management challenges when employing mobile technologies in their lessons. In the interviews, most teachers complained of the difficulty to control their classes when they had mobile devices, which distracted their attention and understanding. They reported that their students were distracted by games and they needed to be trained to use mobile technologies for educational purposes. Most teachers recommended that certain parameters or restrictions should be established in any mobile learning project that restrict the usage of mobile technologies to educational purposes. In addition, teachers also emphasised that students needed to be trained on the advantages and limitations of mobile technologies. Teachers were also recommending that pedagogical training for using mobile technologies should be considered when implementing mobile learning in schools. These findings reveal that although of the challenges of managing their classes, teachers believe that mobile learning has great potential for learning. These results imply that mobile learning can be effectively implemented in school in Oman if certain factors and restrictions are considered.

Keywords: effective implementation, challenges, mobile learning, opportunities

Procedia PDF Downloads 218

Authors: Ursula D. C. Resende, Fabiano S. Bicalho, Sandro T. M. Gonçalves

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The growing demand for cheap and clean energy sources have been motivated by the study and development of distinct technologies and devices able to provide different amounts of energy. In order to supply energy for small loads, the energy from the electromagnetic spectrum can be harvested. This possibility is particularly interesting because this kind of energy is constantly available in the environment and the number of radiofrequency sources is permanently increasing, due to advances in telecommunications services. A rectenna, which is a combination of an antenna and a rectifier circuit, is an equipment that can efficiently perform the electromagnetic energy harvesting. However, since the amount of electromagnetic energy available in the environment is very small, limited values of power can be harvested by the rectenna. Therefore, several technical strategies have been investigated in order to increase this amount of power. In this work, a metamaterial electromagnetic lens is used to improve the electromagnetic energy harvesting. The rectenna investigated was designed and optimized to charge a Li-Ion battery using the electromagnetic energy from an internet Wi-Fi commercial router model TL-WR841HP operating in 2.45 GHz with maximal output power equal to 18 dBm. The rectenna consists of a high directive antenna, a double voltage rectifier circuit and a metamaterial lens. The printed antenna, constituted of two rectangular radiator elements, was projected and optimized by using the Computer Simulation Software (CST) in order to obtain high directivities and values of S11 parameter below -10 dB in 2.45 GHz. The antenna was printed over a double-sided copper fiberglass substrate, FR4, with characterized relative electric permittivity εr = 4.3 and tangent of losses δ = 0.01. The rectifier circuit, which incorporates a circuit for impedance matching and uses the Schottky diode HSMS-2852, was projected and optimized by using Advanced Design Software (ADS) and built over the same FR4 substrate. The metamaterial cell is composed of two Square Split Ring Resonator (S-SRR) and a thin wire in order to operate with negative values of εr and relative magnetic permeability in 2.45 GHz. In order to evaluate the performance of the purposed rectenna two experimental charging tests were performed, one without and other with the metamaterial lens. The result obtained demonstrate that the electromagnetic lens was able to significantly increase the levels of electric current delivered to the battery, approximately 44%.

Keywords: electromagnetic energy harvesting, electromagnetic lens, metamaterial, rectenna

Procedia PDF Downloads 145

Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 77

Authors: Maryam Kamali Nezhad

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The Robert-Bourassa development (LG-2), the first to be built on the Grande Rivière, comprises two sets of eight turbines- generator units each, the East and West powerhouses. Each powerhouse has two tailrace tunnels with an average length of about 1178 m. The LG-2A powerhouse houses 6 turbine-generator units. The water is discharged through two tailrace tunnels with a length of about 1330 m. The objective of this work, at RB (LG-2), is; 1) to establish a new maximum transient level in the surge chamber, 2) to define the new maximum equipment flow rate for the future turbine-generator units, 3) to ensure safe access to various intervention locations in the surge chamber. The transient levels under normal operating conditions at the RB plant were determined in 2001 by the Hydraulics Unit of HQE using the "Chamber" software. It is a one-dimensional mass oscillation calculation software; it is used to determine the variation of the water level in the equilibrium chamber located downstream of a power plant during the load shedding of the power plant units; it can also be used in the case of an equilibrium stack upstream of a power plant. The RB (LG-2) plant study is based on the theoretical nominal geometry of the chamber and the tailrace tunnels and the flow-level relationship at the outlet of the galleries established during design. The software is used in such a way that the results have an acceptable margin of safety, especially with respect to the maximum transient level (e.g., resumption of flow at an inopportune time), to take into account the turbulent and three-dimensional aspects of the actual flow in the chamber. Note that the transient levels depend on the water levels in the river and in the steady-state equilibrium chambers. These data are established in the HQP CRP database and updated from time to time. The maximum transient levels in the RB-East and RB-West powerhouses surge chamber were revised based on the latest update (set 4) of in-river rating curves and steady-state surge chamber water levels. The results of the revision were also used to update the technical advice on the operating conditions for the aforementioned surge chamber access while considering revisions to the calculated water levels.

Keywords: generating station, surge chamber, maximum transient level, hydroelectric power station, turbine-generator, reservoir

Procedia PDF Downloads 87

Authors: Stephanie Boue, Nicolas Sierro, Julia Hoeng, Manuel C. Peitsch

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Systems biology relies on large numbers of data points and sophisticated methods to extract biologically meaningful signal and mechanistic understanding. For example, analyses of transcriptomics and proteomics data enable to gain insights into the molecular differences in tissues exposed to diverse stimuli or test items. Whereas the interpretation of endpoints specifically measuring a mechanism is relatively straightforward, the interpretation of big data is more complex and would benefit from comparing results obtained with diverse analysis methods. The sbv IMPROVER project was created to implement solutions to verify systems biology data, methods, and conclusions. Computational challenges leveraging the wisdom of the crowd allow benchmarking methods for specific tasks, such as signature extraction and/or samples classification. Four challenges have already been successfully conducted and confirmed that the aggregation of predictions often leads to better results than individual predictions and that methods perform best in specific contexts. Whenever the scientific question of interest does not have a gold standard, but may greatly benefit from the scientific community to come together and discuss their approaches and results, datathons are set up. The inaugural sbv IMPROVER datathon was held in Singapore on 23-24 September 2016. It allowed bioinformaticians and data scientists to consolidate their ideas and work on the most promising methods as teams, after having initially reflected on the problem on their own. The outcome is a set of visualization and analysis methods that will be shared with the scientific community via the Garuda platform, an open connectivity platform that provides a framework to navigate through different applications, databases and services in biology and medicine. We will present the results we obtained when analyzing data with our network-based method, and introduce a datathon that will take place in Japan to encourage the analysis of the same datasets with other methods to allow for the consolidation of conclusions.

Keywords: big data interpretation, datathon, systems toxicology, verification

Procedia PDF Downloads 279

Authors: Naveen Porika, Snigdho Majumdar, Niraj Sethi

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Water, food and energy securities are emerging as increasingly important and vital issues for India and the world. Hyderabad urban agglomeration (HUA), the capital city of Andhra Pradesh State in India, is the sixth largest city has a population of about 8.2 million. The Musi River, which is a tributary of Krishna river flows from west to east right through the heart of Hyderabad, about 80% of the water used by people is released back as sewage, which flows back into Musi every day with detrimental effects on the environment and people downstream of the city. The average daily sewage generated in Hyderabad city is 950 MLD, however, treatment capacity exists only for 541 Million Liters per Day (MLD) but only 407 MLD of sewage is treated. As a result, 543 MLD of sewage daily flows into Musi river. Hyderabad’s current estimated water demand stands at 320 Million Gallons per Day (MGD). However, its installed capacity is merely 270 MGD; by 2020 estimated demand will grow to 400 MGD. There is huge gap between current supply and demand, and this is likely to widen by 2021. Developing new fresh water sources is a challenge for Hyderabad, as the fresh water sources are few and far from the City (about 150-200 km) and requires excessive pumping. The constraints presented above make the conventional alternatives for supply augmentation unsustainable and unattractive .One such dependable and captive source of easily available water is the treated sewage. With proper treatment, water of desired quality can be recovered from the waste water (sewage) for recycle and reuse. Hyderabad Amberpet sewage treatment of capacity 339 MLD is Asia’s largest sewage treatment plant. Tertiary sewage treatment Standard basic engineering modules of 30 MLD,60 MLD, 120MLD & 180 MLD for sewage treatment plants has been developed which are utilized for developing Sewage Reclamation & Reuse model in Asia’s largest sewage treatment plant. This paper will focus on Hyderabad Water Supply & Demand, Sewage Generation & Treatment, Technical aspects of Tertiary Sewage Treatment and Utilization of developed standard modules for reclamation & reuse of treated sewage to overcome the deficit of 130 MGD as projected by 2021.

Keywords: water reclamation, reuse, Andhra Pradesh, hyderabad, musi river, sewage, demand and supply, recycle, Amberpet, 339 MLD, engineering modules, tertiary treatment

Procedia PDF Downloads 618

Authors: El Harraj Abdeslam, Raissouni Naoufal

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The detection of moving objects from a video image sequences is very important for object tracking, activity recognition, and behavior understanding in video surveillance. The most used approach for moving objects detection / tracking is background subtraction algorithms. Many approaches have been suggested for background subtraction. But, these are illumination change sensitive and the solutions proposed to bypass this problem are time consuming. In this paper, we propose a robust yet computationally efficient background subtraction approach and, mainly, focus on the ability to detect moving objects on dynamic scenes, for possible applications in complex and restricted access areas monitoring, where moving and motionless persons must be reliably detected. It consists of three main phases, establishing illumination changes in variance, background/foreground modeling and morphological analysis for noise removing. We handle illumination changes using Contrast Limited Histogram Equalization (CLAHE), which limits the intensity of each pixel to user determined maximum. Thus, it mitigates the degradation due to scene illumination changes and improves the visibility of the video signal. Initially, the background and foreground images are extracted from the video sequence. Then, the background and foreground images are separately enhanced by applying CLAHE. In order to form multi-modal backgrounds we model each channel of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture Model (GMM). Finally, we post process the resulting binary foreground mask using morphological erosion and dilation transformations to remove possible noise. For experimental test, we used a standard dataset to challenge the efficiency and accuracy of the proposed method on a diverse set of dynamic scenes.

Keywords: video surveillance, background subtraction, contrast limited histogram equalization, illumination invariance, object tracking, object detection, behavior understanding, dynamic scenes

Procedia PDF Downloads 260

Authors: Mohd Sabri Minhat, Nurul Adilla Mohd Subha

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The 1MWth PUSPATI TRIGA Reactor (RTP) in Malaysia Nuclear Agency has been operating more than 35 years. The existing core power control is using conventional controller known as Feedback Control Algorithm (FCA). It is technically challenging to keep the core power output always stable and operating within acceptable error bands for the safety demand of the RTP. Currently, the system could be considered unsatisfactory with power tracking performance, yet there is still significant room for improvement. Hence, a new design core power control is very important to improve the current performance in tracking and regulating reactor power by controlling the movement of control rods that suit the demand of highly sensitive of nuclear reactor power control. In this paper, the proposed Model Predictive Control (MPC) law was applied to control the core power. The model for core power control was based on mathematical models of the reactor core, MPC, and control rods selection algorithm. The mathematical models of the reactor core were based on point kinetics model, thermal hydraulic models, and reactivity models. The proposed MPC was presented in a transfer function model of the reactor core according to perturbations theory. The transfer function model-based predictive control (TFMPC) was developed to design the core power control with predictions based on a T-filter towards the real-time implementation of MPC on hardware. This paper introduces the sensitivity functions for TFMPC feedback loop to reduce the impact on the input actuation signal and demonstrates the behaviour of TFMPC in term of disturbance and noise rejections. The comparisons of both tracking and regulating performance between the conventional controller and TFMPC were made using MATLAB and analysed. In conclusion, the proposed TFMPC has satisfactory performance in tracking and regulating core power for controlling nuclear reactor with high reliability and safety.

Keywords: core power control, model predictive control, PUSPATI TRIGA reactor, TFMPC

Procedia PDF Downloads 245

Authors: S. Pathak, R. Lazarus

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A 25-year-old male HIV patient (CD4 cells 20/µL and HIV viral load 14200000 copies/ml) with a past medical history of duodenal ulcer, pneumocystis carinii pneumonia, oesophageal candidiasis presented with fever and a seizure to hospital. The only recent travel had been a religious pilgrimage from Singapore to Malaysia 5 days prior; during the trip he sustained skin abrasions. The patient had recently started highly active antiretroviral therapy 2 months prior. Clinical examination was unremarkable other than a temperature of 38.8°C and perianal warts. Laboratory tests showed a leukocyte count 12.5x109 cells/L, haemoglobin 9.4 g/dL, normal biochemistry and a C-reactive protein 121 mg/L. CT head and MRI head were unremarkable and cerebrospinal fluid analysis performed after a delay (due to technical difficulties) of 11 days was unremarkable. Blood cultures (three sets) taken on admission showed Gram-negative rods in the anaerobic bottles only at the end of incubation with culture result confirmed by molecular sequencing showing Helicobacter cinaedi. The patient was treated empirically with ceftriaxone for seven days and this was converted to oral co-amoxiclav for a further seven days after the blood cultures became positive. A Transthoracic echocardiogram was unremarkable. The patient made a full recovery. Helicobacter cinaedi is a gram-negative anaerobic fastidious organism affecting patients with comorbidity. Infection may manifest as cellulitius, colitis or as in this case as bloodstream infection – the latter is often attributed to faeco-oral infection. Laboratory identification requires prolonged culture. Therapeutic options may be limited by resistance to macrolides and fluoroquinolones. The likely pathogen inoculation routes in the case described include gastrointestinal translocation due to proctitis at the site of perianal warts, or breach of the skin via abrasions occurring during the pilgrimage. Such organisms are increasing in prevalence as our patient population ages and patients have multiple comorbidities including HIV. It may be necessary in patients with unexplained fever to prolong incubation of sterile sites including blood in order to identify this unusual fastidious organism.

Keywords: fastidious, Helicobacter cinaedi, HIV, immunocompromised

Procedia PDF Downloads 380

Authors: Alexander A. Tokmakov

Abstract:

Cell-free protein synthesis is widely used to synthesize recombinant proteins. It allows genome-scale expression of various polypeptides under strictly controlled uniform conditions. However, only a minor fraction of all proteins can be successfully expressed in the systems of protein synthesis that are currently used. The factors determining expression success are poorly understood. At present, the vast volume of data is accumulated in cell-free expression databases. It makes possible comprehensive bioinformatics analysis and identification of multiple features associated with successful cell-free expression. Here, we describe an approach aimed at identification of multiple physicochemical and structural properties of amino acid sequences associated with protein solubility and aggregation and highlight major correlations obtained using this approach. The developed method includes: categorical assessment of the protein expression data, calculation and prediction of multiple properties of expressed amino acid sequences, correlation of the individual properties with the expression scores, and evaluation of statistical significance of the observed correlations. Using this approach, we revealed a number of statistically significant correlations between calculated and predicted features of protein sequences and their amenability to cell-free expression. It was found that some of the features, such as protein pI, hydrophobicity, presence of signal sequences, etc., are mostly related to protein solubility, whereas the others, such as protein length, number of disulfide bonds, content of secondary structure, etc., affect mainly the expression propensity. We also demonstrated that amenability of polypeptide sequences to cell-free expression correlates with the presence of multiple sites of post-translational modifications. The correlations revealed in this study provide a plethora of important insights into protein folding and rationalization of protein production. The developed bioinformatics approach can be of practical use for predicting expression success and optimizing cell-free protein synthesis.

Keywords: bioinformatics analysis, cell-free protein synthesis, expression success, optimization, recombinant proteins

Procedia PDF Downloads 420

Authors: Vineeth G. Kuriakose, Joseph C. Chen, Ye Li

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The research follows a systematic approach to optimize the parameters for parts machined by turning and milling processes. The quality characteristic chosen is surface roughness since the surface finish plays an important role for parts that require surface contact. A tapered cylindrical surface is designed as a test specimen for the research. The material chosen for machining is aluminum alloy 6061 due to its wide variety of industrial and engineering applications. HAAS VF-2 TR computer numerical control (CNC) vertical machining center is used for milling and HAAS ST-20 CNC machine is used for turning in this research. Taguchi analysis is used to optimize the surface roughness of the machined parts. The L₉ Orthogonal Array is designed for four controllable factors with three different levels each, resulting in 18 experimental runs. Signal to Noise (S/N) Ratio is calculated for achieving the specific target value of 75 ± 15 µin. The controllable parameters chosen for turning process are feed rate, depth of cut, coolant flow and finish cut and for milling process are feed rate, spindle speed, step over and coolant flow. The uncontrollable factors are tool geometry for turning process and tool material for milling process. Hypothesis testing is conducted to study the significance of different uncontrollable factors on the surface roughnesses. The optimal parameter settings were identified from the Taguchi analysis and the process capability C_p and the process capability index C_pk were improved from 1.76 and 0.02 to 3.70 and 2.10 respectively for turning process and from 0.87 and 0.19 to 3.85 and 2.70 respectively for the milling process. The surface roughnesses were improved from 60.17 µin to 68.50 µin, reducing the defect rate from 52.39% to 0% for the turning process and from 93.18 µin to 79.49 µin, reducing the defect rate from 71.23% to 0% for the milling process. The purpose of this study is to efficiently utilize the Taguchi design analysis to improve the surface roughness.

Keywords: surface roughness, Taguchi parameter design, CNC turning, CNC milling

Procedia PDF Downloads 158

Authors: D. O. Ramadan, R. S. Dwyer-Joyce

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The measurement of the interface conditions in a cutting tool contact is essential information for performance monitoring and control. This interface provides the path for the heat flux to the cutting tool. This elevate in the cutting tool temperature leads to motivate the mechanism of tool wear, thus affect the life of the cutting tool and the productivity. This zone is representative by the tool-chip interface. Therefore, understanding and monitoring this interface is considered an important issue in machining. In this paper, an acoustic emission (AE) technique was used to find the correlation between AE parameters and the tool-chip interface. For this reason, a response surface design (RSD) has been used to analyse and optimize the machining parameters. The experiment design was based on the face centered, central composite design (CCD) in the Minitab environment. According to this design, a series of orthogonal cutting experiments for different cutting conditions were conducted on a Triumph 2500 lathe machine to study the sensitivity of the acoustic emission (AE) signal to change in tool-chip contact length. The cutting parameters investigated were the cutting speed, depth of cut, and feed and the experiments were performed for 6082-T6 aluminium tube. All the orthogonal cutting experiments were conducted unlubricated. The tool-chip contact area was investigated using a scanning electron microscope (SEM). The results obtained in this paper indicate that there is a strong dependence of the root mean square (RMS) on the cutting speed, where the RMS increases with increasing the cutting speed. A dependence on the tool-chip contact length has been also observed. However there was no effect observed of changing the cutting depth and feed on the RMS. These dependencies have been clarified in terms of the strain and temperature in the primary and secondary shear zones, also the tool-chip sticking and sliding phenomenon and the effect of these mechanical variables on dislocation activity at high strain rates. In conclusion, the acoustic emission technique has the potential to monitor in situ the tool-chip interface in turning and consequently could indicate the approaching end of life of a cutting tool.

Keywords: Acoustic emission, tool-chip interface, orthogonal cutting, monitoring

Procedia PDF Downloads 488

Authors: Hamidreza Hoshyarmanesh, Sanju Lama, Garnette R. Sutherland

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In tele-operative robotic surgery, an ideal haptic device should be equipped with an intuitive and smooth end-effector to cover the surgeon’s hand/wrist degrees of freedom (DOF) and translate the hand joint motions to the end-effector of the remote manipulator with low effort and high level of comfort. This research introduces the design and development of a microsurgery-specific end-effector, a gimbal mechanism possessing 4 passive and 1 active DOFs, equipped with a bipolar forceps and haptic feedback. The robust gimbal structure is comprised of three light-weight links/joint, pitch, yaw, and roll, each consisting of low-friction support and a 2-channel accurate optical position sensor. The third link, which provides the tool roll, was specifically designed to grip the tool prongs and accommodate a low mass geared actuator together with a miniaturized capstan-rope mechanism. The actuator is able to generate delicate torques, using a threaded cylindrical capstan, to emulate the sense of pinch/coagulation during conventional microsurgery. While the tool left prong is fixed to the rolling link, the right prong bears a miniaturized drum sector with a large diameter to expand the force scale and resolution. The drum transmits the actuator output torque to the right prong and generates haptic force feedback at the tool level. The tool is also equipped with a hall-effect sensor and magnet bar installed vis-à-vis on the inner side of the two prongs to measure the tooltip distance and provide an analogue signal to the control system. We believe that such a haptic end-effector could significantly increase the accuracy of telerobotic surgery and help avoid high forces that are known to cause bleeding/injury.

Keywords: end-effector, force generation, haptic interface, robotic surgery, surgical tool, tele-operation

Procedia PDF Downloads 123