Search results for: neural regeneration

Authors: Fernando Vega, Esmeralda Portillo, Sara Camino, Benito Navarrete, Elena Montavez

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The European Union aims at strongly reducing their CO₂ emissions from energy and industrial sector by 2030. The energy sector contributes with more than two-thirds of the CO₂ emission share derived from anthropogenic activities. Although efforts are mainly focused on the use of renewables by energy production sector, carbon capture and storage (CCS) remains as a frontline option to reduce CO₂ emissions from industrial process, particularly from fossil-fuel power plants and cement production. Among the most feasible and near-to-market CCS technologies, namely post-combustion and oxy-combustion, partial oxy-combustion is a novel concept that can potentially reduce the overall energy requirements of the CO₂ capture process. This technology consists in the use of higher oxygen content in the oxidizer that should increase the CO₂ concentration of the flue gas once the fuel is burnt. The CO₂ is then separated from the flue gas downstream by means of a conventional CO₂ chemical absorption process. The production of a higher CO₂ concentrated flue gas should enhance the CO₂ absorption into the solvent, leading to further reductions of the CO₂ separation performance in terms of solvent flow-rate, equipment size, and energy penalty related to the solvent regeneration. This work evaluates a portfolio of CCS technologies applied to fossil-fuel power plants. For this purpose, an economic evaluation methodology was developed in detail to determine the main economical parameters for CO₂ emission removal such as the levelized cost of electricity (LCOE) and the CO₂ captured and avoided costs. ASPEN Plus™ software was used to simulate the main units of power plant and solve the energy and mass balance. Capital and investment costs were determined from the purchased cost of equipment, also engineering costs and project and process contingencies. The annual capital cost and operating and maintenance costs were later obtained. A complete energy balance was performed to determine the net power produced in each case. The baseline case consists of a supercritical 500 MWe coal-fired power plant using anthracite as a fuel without any CO₂ capture system. Four cases were proposed: conventional post-combustion capture, oxy-combustion and partial oxy-combustion using two levels of oxygen-enriched air (40%v/v and 75%v/v). CO₂ chemical absorption process using monoethanolamine (MEA) was used as a CO₂ separation process whereas the O₂ requirement was achieved using a conventional air separation unit (ASU) based on Linde's cryogenic process. Results showed a reduction of 15% of the total investment cost of the CO₂ separation process when partial oxy-combustion was used. Oxygen-enriched air production also reduced almost half the investment costs required for ASU in comparison with oxy-combustion cases. Partial oxy-combustion has a significant impact on the performance of both CO₂ separation and O₂ production technologies, and it can lead to further energy reductions using new developments on both CO₂ and O₂ separation processes.

Keywords: carbon capture, cost methodology, economic evaluation, partial oxy-combustion

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Authors: George Mahalu

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The Chua diode has been configured over time in various ways, using electronic structures like as operational amplifiers (OAs) or devices with gas or semiconductors. When discussing the use of semiconductor devices, tunnel diodes (Esaki diodes) are most often considered, and more recently, transistorized configurations such as lambda diodes. The paper-work proposed here uses in the modeling a lambda diode type configuration consisting of two Junction Field Effect Transistors (JFET). The original scheme is created in the MULTISIM electronic simulation environment and is analyzed in order to identify the conditions for the appearance of evolutionary unpredictability specific to nonlinear dynamic systems with chaos-induced behavior. The chaotic deterministic oscillator is one autonomous type, a fact that places it in the class of Chua’s type oscillators, the only significant and most important difference being the presence of a nonlinear device like the one mentioned structure above. The chaotic behavior is identified both by means of strange attractor-type trajectories and visible during the simulation and by highlighting the hypersensitivity of the system to small variations of one of the input parameters. The results obtained through simulation and the conclusions drawn are useful in the further research of ways to implement such constructive electronic solutions in theoretical and practical applications related to modern small signal amplification structures, to systems for encoding and decoding messages through various modern ways of communication, as well as new structures that can be imagined both in modern neural networks and in those for the physical implementation of some requirements imposed by current research with the aim of obtaining practically usable solutions in quantum computing and quantum computers.

Keywords: chaos, lambda diode, strange attractor, nonlinear system

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Authors: Fatin Khalida Abdul Khadir, Husna Takaijudin

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Bioretention system is one of the alternatives to approach the conventional stormwater management, low impact development (LID) strategy for best management practices (BMPs). Incorporating both filtration and infiltration, initial research on bioretention systems has shown that this practice extensively decreases runoff volumes and peak flows. The LID-BMP treatment train is one of the latest LID-BMPs for stormwater treatments in urbanized watersheds. The treatment train is developed to overcome the drawbacks that arise from conventional LID-BMPs and aims to enhance the performance of the existing practices. In addition, it is also used to improve treatments in both water quality and water quantity controls as well as maintaining the natural hydrology of an area despite the current massive developments. The objective of this paper is to review the effectiveness of the conventional LID-BMPS on hydrologic and hydraulic performances through column studies in different configurations. The previous studies on the applications of LID-BMP treatment train that were developed to overcome the drawbacks of conventional LID-BMPs are reviewed and use as the guidelines for implementing this system in Universiti Teknologi Petronas (UTP) and elsewhere. The reviews on the analysis conducted for hydrologic and hydraulic performances using the artificial neural network (ANN) model are done in order to be utilized in this study. In this study, the role of the LID-BMP treatment train is tested by arranging bioretention cells in series in order to be implemented for controlling floods that occurred currently and in the future when the construction of the new buildings in UTP completed. A summary of the research findings on the performances of the system is provided which includes the proposed modifications on the designs.

Keywords: bioretention system, LID-BMP treatment train, hydrological and hydraulic performance, ANN analysis

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Authors: Sanjeev K. Singh, Maloy B. Mandal, Revand R.

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The physiology of baroreceptors and chemoreceptors present in large blood vessels of the heart is well known in regulation of cardiorespiratory functions. Since large blood vessels and peripheral blood vessels are of same mesodermal origin, therefore, involvement of the latter in regulation of cardiorespiratory system is expected. Role of perivascular nerves in mediating cardiorespiratory alterations produced after intra-arterial injection of a nociceptive agent (bradykinin) was examined in urethane anesthetized male rats. Respiratory frequency, blood pressure, and heart rate were recorded for 30 min after the retrograde injection of bradykinin/saline in the femoral artery. In addition, paw edema was determined and water content was expressed as percentage of wet weight. Injection of bradykinin produced immediate tachypnoeic, hypotensive and bradycardiac responses of shorter latency (5-8 s) favoring the neural mechanisms involved in it. Injection of equi-volume of saline did not produce any responses and served as time matched control. Paw edema was observed in the ipsilateral hind limb. Pretreatment with diclofenac sodium significantly attenuated the bradykinin-induced responses and also blocked the paw edema. Ipsilateral femoral and sciatic nerve sectioning attenuated bradykinin-induced responses significantly indicating the origin of responses from the local vascular bed. Administration of bradykinin in the segment of an artery produced reflex cardiorespiratory changes by stimulating the perivascular nociceptors involving prostaglandins. This is a novel study exhibiting the role of peripheral blood vessels in regulation of cardiorespiratory system.

Keywords: vasosensory reflex, cardiorespiratory changes, nociceptive agent, bradykinin, VR1 receptors

Procedia PDF Downloads 137

Authors: V. Schmidt, L. Janovák, N. Wiegand, B. Patczai, K. Turzó

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Large bone defects are not able to heal spontaneously. Bioactive glasses seem to be appropriate (bio)materials for bone reconstruction. Bioactive glasses are osteoconductive and osteoinductive, therefore, play a useful role in bony regeneration and repair. Because of their not optimal mechanical properties (e.g., brittleness, low bending strength, and fracture toughness), their applications are limited. Bioactive glass can be used as a coating material applied on metal surfaces. In this way -when using them as implants- the excellent mechanical properties of metals and the biocompatibility and bioactivity of glasses will be utilized. Furthermore, ion release effects of bioactive glasses regarding osteogenic and angiogenic responses have been shown. Silicate bioactive glasses (45S5 Bioglass) induce the release and exchange of soluble Si, Ca, P, and Na ions on the material surface. This will lead to special cellular responses inducing bone formation, which is favorable in the biointegration of the orthopedic prosthesis. The incorporation of other additional elements in the silicate network such as fluorine, magnesium, iron, silver, potassium, or zinc has been shown, as the local delivery of these ions is able to enhance specific cell functions. Although hip and knee prostheses present a high success rate, bacterial infections -mainly implant associated- are serious and frequent complications. Infection can also develop after implantation of hip prostheses, the elimination of which means more surgeries for the patient and additional costs for the clinic. Prosthesis-related infection is a severe complication of orthopedic surgery, which often causes prolonged illness, pain, and functional loss. While international efforts are made to reduce the risk of these infections, orthopedic surgical infections (SSIs) continue to occur in high numbers. It is currently estimated that up to 2.5% of primary hip and knee surgeries and up to 20% of revision arthroplasties are complicated by periprosthetic joint infection (PJIs). According to some authors, these numbers are underestimated, and they are also increasing. Staphylococcus aureus is the leading cause of both SSIs and PJIs, and the prevalence of methicillin-resistant S. aureus (MRSA) is on the rise, particularly in the United States. These deep infections lead to implant removal and consequently increase morbidity and mortality. The study targets this clinical problem using our experience so far with the Ag-doped polymer coatings on Titanium implants. Non-modified or modified (e.g., doped with antibacterial agents, like Ag) bioactive glasses could play a role in the prevention of infections or the therapy of infected tissues. Bioactive glasses have excellent biocompatibility, proved by in vitro cell culture studies of human osteoblast-like MG-63 cells. Ag-doped bioactive glass-scaffold has a good antibacterial ability against Escherichia coli and other bacteria. It may be concluded that these scaffolds have great potential in the prevention and therapy of implant-associated bone infection.

Keywords: antibacterial agents, bioactive glass, hip and knee prosthesis, medical implants

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Authors: Jacob Green, Cecilia Cabrera, Maximilian Jakobs, Andrea Dimitracopoulos, Mark van der Wilk, Ryan Greenhalgh

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Predicting drug properties is key in drug discovery to enable de-risking of assets before expensive clinical trials and to find highly active compounds faster. Interest from the machine learning community has led to the release of a variety of benchmark datasets and proposed methods. However, it remains unclear for practitioners which method or approach is most suitable, as different papers benchmark on different datasets and methods, leading to varying conclusions that are not easily compared. Our large-scale empirical study links together numerous earlier works on different datasets and methods, thus offering a comprehensive overview of the existing property classes, datasets, and their interactions with different methods. We emphasise the importance of uncertainty quantification and the time and, therefore, cost of applying these methods in the drug development decision-making cycle. To the best of the author's knowledge, it has been observed that the optimal approach varies depending on the dataset and that engineered features with classical machine learning methods often outperform deep learning. Specifically, QSAR datasets are typically best analysed with classical methods such as Gaussian Processes, while ADMET datasets are sometimes better described by Trees or deep learning methods such as Graph Neural Networks or language models. Our work highlights that practitioners do not yet have a straightforward, black-box procedure to rely on and sets a precedent for creating practitioner-relevant benchmarks. Deep learning approaches must be proven on these benchmarks to become the practical method of choice in drug property prediction.

Keywords: activity (QSAR), ADMET, classical methods, drug property prediction, empirical study, machine learning

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Authors: Marita Pigłowska, Beata Kurc, Maciej Galiński

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The application of carbon materials in the branches of the electrochemical industry shows an increasing tendency each year due to the many interesting properties they possess. These are, among others, a well-developed specific surface, porosity, high sorption capacity, good adsorption properties, low bulk density, electrical conductivity and chemical resistance. All these properties allow for their effective use, among others in supercapacitors, which can store electric charges of the order of 100 F due to carbon electrodes constituting the capacitor plates. Coals (including expanded graphite, carbon black, graphite carbon fibers, activated carbon) are commonly used in electrochemical methods of removing oil derivatives from water after tanker disasters, e.g. phenols and their derivatives by their electrochemical anodic oxidation. Phenol can occupy practically the entire surface of carbon material and leave the water clean of hydrophobic impurities. Regeneration of such electrodes is also not complicated, it is carried out by electrochemical methods consisting in unblocking the pores and reducing resistances, and thus their reactivation for subsequent adsorption processes. Graphite is commonly used as an anode material in lithium-ion cells, while due to the limited capacity it offers (372 mAh g-1), new solutions are sought that meet both capacitive, efficiency and economic criteria. Increasingly, biodegradable materials, green materials, biomass, waste (including agricultural waste) are used in order to reuse them and reduce greenhouse effects and, above all, to meet the biodegradability criterion necessary for the production of lithium-ion cells as chemical power sources. The most common of these materials are cellulose, starch, wheat, rice, and corn waste, e.g. from agricultural, paper and pharmaceutical production. Such products are subjected to appropriate treatments depending on the desired application (including chemical, thermal, electrochemical). Starch is a biodegradable polysaccharide that consists of polymeric units such as amylose and amylopectin that build an ordered (linear) and amorphous (branched) structure of the polymer. Carbon is also used as a catalyst. Elemental carbon has become available in many nano-structured forms representing the hybridization combinations found in the primary carbon allotropes, and the materials can be enriched with a large number of surface functional groups. There are many examples of catalytic applications of coal in the literature, but the development of this field has been hampered by the lack of a conceptual approach combining structure and function and a lack of understanding of material synthesis. In the context of catalytic applications, the integrity of carbon environmental management properties and parameters such as metal conductivity range and bond sequence management should be characterized. Such data, along with surface and textured information, can form the basis for the provision of network support services.

Keywords: carbon materials, catalysis, BET, capacitors, lithium ion cell

Procedia PDF Downloads 159

Authors: O. S. Ebrahim, K. O. Shawky, M. O. S. Ebrahim, P. K. Jain

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Induction Motor (IM) driving pump is the main consumer of electricity in a typical fluid transportation system (FTS). It was illustrated that changing the connection of the stator windings from delta to star at no load could achieve noticeable active and reactive energy savings. This paper proposes a supervisory hysteresis liquid-level control with three-state energy saving mode (ESM) for IM in FTS including storage tank. The IM pump drive comprises modified star/delta switch and hydromantic coupler. Three-state ESM is defined, along with the normal running, and named analog to computer ESMs as follows: Sleeping mode in which the motor runs at no load with delta stator connection, hibernate mode in which the motor runs at no load with a star connection, and motor shutdown is the third energy saver mode. A logic flow-chart is synthesized to select the motor state at no-load for best energetic cost reduction, considering the motor thermal capacity used. An artificial neural network (ANN) state estimator, based on the recurrent architecture, is constructed and learned in order to provide fault-tolerant capability for the supervisory controller. Sequential test of Wald is used for sensor fault detection. Theoretical analysis, preliminary experimental testing and, computer simulations are performed to show the effectiveness of the proposed control in terms of reliability, power quality and energy/coenergy cost reduction with the suggestion of power factor correction.

Keywords: ANN, ESM, IM, star/delta switch, supervisory control, FT, reliability, power quality

Procedia PDF Downloads 177

Authors: Yiorgos Hadjichristou

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The paper will focus on the strategic development deriving from the evolution of the traditional courtyard spatial organization towards a new, contemporary sustainable way of living. New sustainable approaches that engulf the social issues, the notion of place, the understanding of weather architecture blended together with the bioclimatic behaviour will be seen through a series of experimental case studies in the island of Cyprus, inspired and originated from its traditional wisdom, ranging from small scale of living to urban interventions. Weather and nature will be seen as co-architectural authors with architects as intelligently claimed by Jonathan Hill in his Weather Architecture discourse. Furthermore, following Pallasmaa’s understanding, the building will be seen not as an end itself and the elements of an architectural experience as having a verb form rather than being nouns. This will further enhance the notion of merging the subject-human and the object-building as discussed by Julio Bermudez. This eventually will enable to generate the discussion of the understanding of the building constructed according to the specifics of place and inhabitants, shaped by its physical and human topography as referred by Adam Sharr in relation to Heidegger’s thinking. The specificities of the divided island and the dealing with sites that are in vicinity with the diving Green Line will further trigger explorations dealing with the regeneration issues and the social sustainability offering unprecedented opportunities for innovative sustainable ways of living. The above premises will lead us to develop innovative strategies for a profound, both technical and social sustainability, which fruitfully yields to innovative living built environments, responding to the ever changing environmental and social needs. As a starting point, a case study in Kaimakli in Nicosia a refurbishment with an extension of a traditional house, already engulfs all the traditional/ vernacular wisdom of the bioclimatic architecture. It aims at capturing not only its direct and quite obvious bioclimatic features, but rather to evolve them by adjusting the whole house in a contemporary living environment. In order to succeed this, evolutions of traditional architectural elements and spatial conditions are integrated in a way that does not only respond to some certain weather conditions, but they integrate and blend the weather within the built environment. A series of innovations aiming at maximum flexibility is proposed. The house can finally be transformed into a winter enclosure, while for the most part of the year it turns into a ‘camping’ living environment. Parallel to experimental interventions in existing traditional units, we will proceed examining the implementation of the same developed methodology in designing living units and complexes. Malleable courtyard organizations that attempt to blend the traditional wisdom with the contemporary needs for living, the weather and nature with the built environment will be seen tested in both horizontal and vertical developments. A new social identity of people, directly involved and interacting with the weather and climatic conditions will be seen as the result of balancing the social with the technological sustainability, the immaterial and the material aspects of the built environment.

Keywords: building as a verb, contemporary living, traditional bioclimatic wisdom, weather architecture

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Authors: Irene M. Arora

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Hypothesis: Attention Deficit Hyperactivity Disorder is the result of an underdeveloped prefrontal cortex which is the primary cause for the signs and symptoms seen as defining features of ADHD. Methods: Through ‘PubMed’, ‘Wiley’ and ‘Google Scholar’ studies published between 2011-2018 were evaluated, determining if a dysfunctional prefrontal cortex caused the characteristic symptoms associated with ADHD. The search terms "prefrontal cortex", "Attention-Deficit/Hyperactivity Disorder", "cognitive control", "frontostriatal tract" among others, were used to maximize the assortment of relevant studies. Excluded papers were systematic reviews, meta-analyses and publications published before 2010 to ensure clinical relevance. Results: Nine publications were analyzed in this review, all of which were non-randomized matched control studies. Three studies found a decrease in the functional integrity of the frontostriatal tract fibers in conjunction with four studies finding impaired frontal cortex stimulation. Prefrontal dysfunction, specifically medial and orbitofrontal areas, displayed abnormal functionality of reward processing in ADHD patients when compared to their normal counterparts. A total of 807 subjects were studied in this review, yielding that a little over half (54%) presented with remission of symptoms in adulthood. Conclusion: While the prefrontal cortex shows the highest consistency of impaired activity and thinner volumes in patients with ADHD, this is a heterogenous disorder implicating its pathophysiology to the dysfunction of other neural structures as well. However, remission of ADHD symptomatology in adulthood was found to be attributable to increased prefrontal functional connectivity and integration, suggesting a key role for the prefrontal cortex in the development of ADHD.

Keywords: prefrontal cortex, ADHD, inattentive, impulsivity, reward processing

Procedia PDF Downloads 111

Authors: Marc Solé, Francesc Giné, Magda Valls, Nina Bijedic

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What people say on social media has turned into a rich source of information to understand social behavior. Specifically, the growing use of Twitter social media for political communication has arisen high opportunities to know the opinion of large numbers of politically active individuals in real time and predict the global political tendencies of a specific country. It has led to an increasing body of research on this topic. The majority of these studies have been focused on polarized political contexts characterized by only two alternatives. Unlike them, this paper tackles the challenge of forecasting Spanish political trends, characterized by multiple political parties, by means of analyzing the Twitters Users political tendency. According to this, a new strategy, named Tweets Analysis Strategy (TAS), is proposed. This is based on analyzing the users tweets by means of discovering its sentiment (positive, negative or neutral) and classifying them according to the political party they support. From this individual political tendency, the global political prediction for each political party is calculated. In order to do this, two different strategies for analyzing the sentiment analysis are proposed: one is based on Positive and Negative words Matching (PNM) and the second one is based on a Neural Networks Strategy (NNS). The complete TAS strategy has been performed in a Big-Data environment. The experimental results presented in this paper reveal that NNS strategy performs much better than PNM strategy to analyze the tweet sentiment. In addition, this research analyzes the viability of the TAS strategy to obtain the global trend in a political context make up by multiple parties with an error lower than 23%.

Keywords: political tendency, prediction, sentiment analysis, Twitter

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Authors: Hamdi Beji, Toufik Kanit, Tanguy Messager

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This study aims to construct a predictive model proficient in foreseeing the linear elastic and thermal characteristics of composite materials, drawing on a multitude of influencing parameters. These parameters encompass the shape of inclusions (circular, elliptical, square, triangle), their spatial coordinates within the matrix, orientation, volume fraction (ranging from 0.05 to 0.4), and variations in contrast (spanning from 10 to 200). A variety of machine learning techniques are deployed, including decision trees, random forests, support vector machines, k-nearest neighbors, and an artificial neural network (ANN), to facilitate this predictive model. Moreover, this research goes beyond the predictive aspect by delving into an inverse analysis using genetic algorithms. The intent is to unveil the intrinsic characteristics of composite materials by evaluating their thermomechanical responses. The foundation of this research lies in the establishment of a comprehensive database that accounts for the array of input parameters mentioned earlier. This database, enriched with this diversity of input variables, serves as a bedrock for the creation of machine learning and genetic algorithm-based models. These models are meticulously trained to not only predict but also elucidate the mechanical and thermal conduct of composite materials. Remarkably, the coupling of machine learning and genetic algorithms has proven highly effective, yielding predictions with remarkable accuracy, boasting scores ranging between 0.97 and 0.99. This achievement marks a significant breakthrough, demonstrating the potential of this innovative approach in the field of materials engineering.

Keywords: machine learning, composite materials, genetic algorithms, mechanical and thermal proprieties

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Authors: Nidhal Azawi

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Colonoscopy procedure is widely used in the world to detect an abnormality. Early diagnosis can help to heal many patients. Because of the unavoidable artifacts that exist in colon images, doctors cannot detect a colon surface precisely. The purpose of this work is to improve the visual quality of colonoscopy videos to provide better information for physicians by removing some artifacts. This work complements a series of work consisting of three previously published papers. In this paper, Optic flow is used for motion compensation, and then consecutive images are aligned/registered to integrate some information to create a new image that has or reveals more information than the original one. Colon images have been classified into informative and noninformative images by using a deep neural network. Then, two different strategies were used to treat informative and noninformative images. Informative images were treated by using Lucas Kanade (LK) with an adaptive temporal mean/median filter, whereas noninformative images are treated by using Lucas Kanade with a derivative of Gaussian (LKDOG) with adaptive temporal median images. A comparison result showed that this work achieved better results than that results in the state- of- the- art strategies for the same degraded colon images data set, which consists of 1000 images. The new proposed algorithm reduced the error alignment by about a factor of 0.3 with a 100% successfully image alignment ratio. In conclusion, this algorithm achieved better results than the state-of-the-art approaches in case of enhancing the informative images as shown in the results section; also, it succeeded to convert the non-informative images that have very few details/no details because of the blurriness/out of focus or because of the specular highlight dominate significant amount of an image to informative images.

Keywords: optic flow, colonoscopy, artifacts, spatial temporal filter

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Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

Procedia PDF Downloads 133

Authors: Dileep G., Akash Singh, Dalchand Ahirwar, Arkadeep Ghosh, Ashutosh Purohit, Gaurav Guleria, Kshatriya Om Prashant, Pushkar Patel, Saksham Kumar, Vanshaj Nathani, Vikas Dangi, Shubhajit Roy Chowdhury, Varun Dutt

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Transcranial direct current stimulation (tDCS) has shown promise as a novel approach to enhance cognitive performance and provide therapeutic benefits for various brain disorders. However, the exact underlying brain mechanisms are not fully understood. We conducted a study to examine the brain's functional changes when subjected to simultaneous tDCS and music (Indian classical raga). During the study, participants in the experimental group underwent a 20-minute session of tDCS at two mA while listening to music (raga) for a duration of seven days. In contrast, the control group received a sham stimulation for two minutes at two mA over the same seven-day period. The objective was to examine whether repetitive tDCS could lead to the formation of additional functional connections between the medial prefrontal cortex (the stimulated area) and the auditory cortex in comparison to a sham stimulation group. In this study, 26 participants (5 female) underwent pre- and post-intervention scans, where changes were compared after one week of either tDCS or sham stimulation in conjunction with music. The study revealed significant effects of tDCS on functional connectivity between the stimulated area and the auditory cortex. The combination of tDCS applied over the mPFC and music resulted in newly formed connections. Based on our findings, it can be inferred that applying anodal tDCS over the mPFC enhances functional connectivity between the stimulated area and the auditory cortex when compared to the effects observed with sham stimulation.

Keywords: fNIRS, tDCS, neuroplasticity, music

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Authors: William Cheng, Rini Sekartini

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Background: Sleep is essential for children because it provides enhancement for the neural system activities that give physiologic effects for the body to support growth and development. One of the modifiable factors that relates with sleep is nutrition, which includes nutritional status, iron intake, and magnesium intake. Nutritional status represents the balance between nutritional intake and expenditure, while iron and magnesium are micronutrients that are related to sleep regulation. The aim of this study is to identify prevalence of sleep disturbance among Indonesian children and to evaluate its relation with aspect to nutrition. Methods : A cross-sectional study involving children aged 5 to 7-years-old in an urban primary health care between 2012 and 2013 was carried out. Related data includes anthropometric status, iron intake, and magnesium intake. Iron and magnesium intake was obtained by 24-hours food recall procedure. Sleep Disturbance Scale for Children (SDSC) was used as the diagnostic tool for sleep disturbance, with score under 39 indicating presence of problem. Results: Out of 128 school-aged children included in this study, 28 (23,1%) of them were found to have sleep disturbance. The majority of children had good nutritional status, with only 15,7% that were severely underweight or underweight, and 12,4% that were identified as stunted. On the contrary, 99 children (81,8%) were identified to have inadequate magnesium intake and 56 children (46,3%) with inadequate iron intake. Our analysis showed there was no significant relation between all of the nutritional status indicators and sleep disturbance (p>0,05%). Moreover, inadequate iron and magnesium intake also failed to prove significant relation with sleep disturbance in this population. Conclusion: Almost fourth of school-aged children in Indonesia were found to have sleep disturbance and further study are needed to overcome this problem. According to our finding, there is no correlation between nutritional status, iron intake, magnesium intake, and sleep disturbance.

Keywords: iron intake, magnesium intake, nutritional status, school-aged children, sleep disturbance

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Authors: Keundong Lee, Dongha Yoo, Youngbin Tchoe, Gyu-Chul Yi

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Light emitting diode (LED) array is an ideal optical stimulation tool for optogenetics, which controls inhibition and excitation of specific neurons with light-sensitive ion channels or pumps. Although a fiber-optic cable with an external light source, either a laser or LED mechanically connected to the end of the fiber-optic cable has widely been used for illumination on neural tissue, a new approach to use micro LEDs (µLEDs) has recently been demonstrated. The LEDs can be placed directly either on the cortical surface or within the deep brain using a penetrating depth probe. Accordingly, this method would not need a permanent opening in the skull if the LEDs are integrated with miniature electrical power source and wireless communication. In addition, multiple color generation from single µLED cell would enable to excite and/or inhibit neurons in localized regions. Here, we demonstrate flexible and color tunable µLEDs for the optogenetic device applications. The flexible and color tunable LEDs was fabricated using multifaceted gallium nitride (GaN) nanorod arrays with GaN nanorods grown on InxGa1−xN/GaN single quantum well structures (SQW) anisotropically formed on the nanorod tips and sidewalls. For various electroluminescence (EL) colors, current injection paths were controlled through a continuous p-GaN layer depending on the applied bias voltage. The electric current was injected through different thickness and composition, thus changing the color of light from red to blue that the LED emits. We believe that the flexible and color tunable µLEDs enable us to control activities of the neuron by emitting various colors from the single µLED cell.

Keywords: light emitting diode, optogenetics, graphene, flexible optoelectronics

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Authors: Natalia Lukasik, Ewa Wagner-Wysiecka

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Development of selective, fast-responsive, and economical sensors for diverse ions detection and determination is one of the most extensively studied areas due to its importance in the field of clinical, environmental and industrial analysis. Among chemical sensors, vast popularity has gained ionophore-based optical sensors, where the generated analytical signal is a consequence of the molecular recognition of ion by the ionophore. Change of color occurring during host-guest interactions allows for quantitative analysis and for 'naked-eye' detection without the need of using sophisticated equipment. An example of application of such sensors is colorimetric detection of iron(III) cations. Iron as one of the most significant trace elements plays roles in many biochemical processes. For these reasons, the development of reliable, fast, and selective methods of iron ions determination is highly demanded. Taking all mentioned above into account a chromogenic amide derivative of 3,4-dihydroxybenzoic acid was synthesized, and its ability to iron(III) recognition was tested. To the best of authors knowledge (according to chemical abstracts) the obtained ligand has not been described in the literature so far. The catechol moiety was introduced to the ligand structure in order to mimic the action of naturally occurring siderophores-iron(III)-selective receptors. The ligand–ion interactions were studied using spectroscopic methods: UV-Vis spectrophotometry and infrared spectroscopy. The spectrophotometric measurements revealed that the amide exhibits affinity to iron(III) in dimethyl sulfoxide and fully aqueous solution, what is manifested by the change of color from yellow to green. Incorporation of the tested amide into a polymeric matrix (cellulose triacetate) ensured effective recognition of iron(III) at pH 3 with the detection limit 1.58×10⁻⁵ M. For the obtained sensor material parameters like linear response range, response time, selectivity, and possibility of regeneration were determined. In order to evaluate the effect of the size of the sensing material on iron(III) detection nanospheres (in the form of nanoemulsion) containing the tested amide were also prepared. According to DLS (dynamic light scattering) measurements, the size of the nanospheres is 308.02 ± 0.67 nm. Work parameters of the nanospheres were determined and compared with cellulose triacetate-based material. Additionally, for fast, qualitative experiments the test strips were prepared by adsorption of the amide solution on a glass microfiber material. Visual limit of detection of iron(III) at pH 3 by the test strips was estimated at the level 10⁻⁴ M. In conclusion, reported here amide derived from 3,4- dihydroxybenzoic acid proved to be an effective candidate for optical sensing of iron(III) in fully aqueous solutions. N. L. kindly acknowledges financial support from National Science Centre Poland the grant no. 2017/01/X/ST4/01680. Authors thank for financial support from Gdansk University of Technology grant no. 032406.

Keywords: ion-selective optode, iron(III) recognition, nanospheres, optical sensor

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Authors: Dmitriy Yu. Korulkin, Raissa A. Muzychkina

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The last decade the growth of severe and disseminated forms of inflammatory diseases is observed in Kazakhstan, in particular, septic shock, which progresses on 3-15% of patients with infectious complications of postnatal period. In terms of the rate of occurrence septic shock takes third place after hemorrhagic and cardiovascular shock, in terms of lethality it takes first place. The structure of obstetric sepsis has significantly changed. Currently the first place is taken by postabortive sepsis (40%) that is connected with usage of imperfect methods of artificial termination of pregnancy in late periods (intraamnial injection of sodium chloride, glucose). The second place is taken by postnatal sepsis (32%); the last place is taken by septic complications of caesarean section (28%). In this connection, search for and assessment of effectiveness of new medicines for treatment of postoperative infectious complications, having biostimulating effect and speeding up regeneration processes, is very promising and topical. Essential oil was obtained by the method hydrodistillation air-dry aerial part of Sedum L. plants using Clevenger apparatus. Pilot batch of plant medicinal product based on Sedum essential oils was produced by Chimpharm JSC, Santo Member of Polpharma Group (Kazakhstan). During clinical test of the plant medicinal product based on Sedum L. essential oils 37 female patients at the age from 35 to 57 with clinical signs of complicated postoperative processes and 12 new mothers with clinical signs of inflammatory process on sutures on anterior abdominal wall after caesarean section and partial disruption of surgical suture line on perineum were examined. Medicine usage methods - surgical wound treatment 2 times a day, treatment with other medicines of local action was not performed. Before and after treatment general clinical test, determination of immune status, bacterioscopic test of wound fluid was performed to all women, medical history data was taken into account, wound cleansing and healing time, full granulations, side effects and complications, satisfaction with the used medicine was assessed. On female patients with inflammatory infiltration and partial disruption of surgical suture line anesthetic wound healing effect of plant medicinal product based on Sedum L. essential oils was observed as early as on the second day after beginning of using it, wound cleansing took place, as a rule, within the first row days. Hyperemia in the area of suture line also was not observed for 2-3-d day of usage of medicine, good constant course was observed. The absence of clinical effect on this group of patients was not registered. The represented data give evidence of that clinical effect was accompanied with normalization of changed laboratory findings. No allergic responses or side effects were observed during usage of the plant medicinal products based on Sedum L. essential oils.

Keywords: antiinflammatory, bioactive substances, essential oils, isolation, sedum L., wound healing

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Authors: Reva Sharan Thakur, Mrinalini Tiwari, Jyoti das

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Cerebral malaria-associated over expression of pro-inflammatory cytokines and chemokines ultimately results in the up-regulation of adhesion molecules in the brain endothelium leading to sequestration of mature parasitized RBCs in the brain. The high-parasitic load subsequently results in increased mortality or development of neurological symptoms within a week of infection. Studies in the human and experimental cerebral malaria have implicated the breakdown of the integrity of blood-brain barrier during the lethal course of infection, cerebral dysfunction, and fatal organ pathologies that result in multi-organ failure. In the present study, using Plasmodium berghei Anka as a mouse model and in vitro conditions, we have investigated the effect of MSCs to attenuate cerebral malaria pathogenesis by diminishing the effect of inflammation altered organ morphology, reduced parasitemia, and increased survival of the mice. MSCs are also validated for their role in preventing BBB dysfunction and reducing malarial toxins. It was observed that administration of MSCs significantly reduced parasitemia and increased survival in Pb A infected mice. It was further demonstrated that MSCs play a significant role in reversing neurological complexities associated with cerebral malaria. Infusion of MSCs in infected mice decreased hemozoin deposition; oedema, and haemorrhagic lesions in vascular organs. MSCs administration also preserved the integrity of the blood-brain barrier and reduced neural inflammation. Taken together, our results demonstrate the potential of MSCs as an emerging anti-malarial candidate.

Keywords: cerebral malaria, mesenchymal stem cells, erythropoesis, cell death

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Authors: Naniek Widayati Priyomarsono

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Introduction: In beginning of Karaton formation, namely, era of Javanese kingdom town had the power region outside castle town (called as Mancanegara), settlement of karaton can function as “the space-between” and “space-defense”, besides it was one of components from governmental structure and karaton power at that time (internal servant/abdi dalem and sentana dalem). Upon the Independence of Indonesia in 1945 “Kingdom-City” converted its political status into part of democratic town managed by statutes based on the classification. The latter affects local culture hierarchy alteration due to the physical development and events. Dynamics of social economy activities in Kampung Karaton surrounded by buildings of Complex of Karaton Kasunanan ini, have impact on the urban system disturbed into the región. Also cultural region image fades away with the weak visual access from existant cultural artefacts. That development lacks of giving appreciation to the established region image providing identity of Karaton Kasunanan particularly and identity of Surakarta city in general. Method used is strategy of grounded theory research (research providing strong base of a theory). Research is focused on actors active and passive relevantly getting involved in change process of Karaton settlement. Data accumulated is “Investigation Focus” oriented on actors affecting that change either internal or external. Investigation results are coupled with field observation data, documentation, literature study, thus it takes accurate findings. Findings: Karaton village has potential products as attraction, possessing human resource support, strong motivation from society still living in that settlement, possessing facilities and means supports, tourism event-supporting facilities, cultural art institution, available fields or development area. Data analyzed: To get the expected result it takes restoration in social cultural development direction, and economy, with ways of: Doing social cultural development strategy, economy, and politics. To-do steps are program socialization of Karaton village as Tourism Village, economical development of local society, regeneration pattern, filtering, and selection of tourism development, integrated planning system development, development with persuasive approach, regulation, market mechanism, social cultural event sector development, political development for region activity sector. Summary: In case the restoration is done by getting society involved as subject of that settlement (active participation in the field), managed and packed interestingly and naturally with tourism-supporting facilities development, village of Karaton Kasunanan Surakarta is ready to receive visit of domestic and foreign tourists.

Keywords: karaton village, finding, restoration, economy, Indonesia

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Authors: Zouhair Haddi, Stephane Delliaux, Jean-Francois Pons, Ismail Kechaf, Jean-Claude De Haro, Mustapha Ouladsine

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Atrial fibrillation (AF) has been considered as the most common cardiac arrhythmia, and a major public health burden associated with significant morbidity and mortality. Nowadays, telemedical approaches targeting cardiac outpatients situate AF among the most challenged medical issues. The automatic, early, and fast AF detection is still a major concern for the healthcare professional. Several algorithms based on univariate analysis have been developed to detect atrial fibrillation. However, the published results do not show satisfactory classification accuracy. This work was aimed at resolving this shortcoming by proposing multivariate data analysis methods for automatic AF detection. Four publicly-accessible sets of clinical data (AF Termination Challenge Database, MIT-BIH AF, Normal Sinus Rhythm RR Interval Database, and MIT-BIH Normal Sinus Rhythm Databases) were used for assessment. All time series were segmented in 1 min RR intervals window and then four specific features were calculated. Two pattern recognition methods, i.e., Principal Component Analysis (PCA) and Learning Vector Quantization (LVQ) neural network were used to develop classification models. PCA, as a feature reduction method, was employed to find important features to discriminate between AF and Normal Sinus Rhythm. Despite its very simple structure, the results show that the LVQ model performs better on the analyzed databases than do existing algorithms, with high sensitivity and specificity (99.19% and 99.39%, respectively). The proposed AF detection holds several interesting properties, and can be implemented with just a few arithmetical operations which make it a suitable choice for telecare applications.

Keywords: atrial fibrillation, multivariate data analysis, automatic detection, telemedicine

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Authors: A. M. Bumbea, A. Musetescu, P. Ciurea, A. Bighea

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Objectives: The authors present a Parsonage Turner syndrome, a rare disease characterized by onset in apparently healthy person with shoulder and/or arm pain, sensory deficit, motor deficit. The causes are not established, could be determinate by vaccination, postoperative, immunologic disease, post traumatic etc. Methods: The authors present a woman case, 32 years old, (in 2006), no medical history, with arm pain and no other symptom. The onset was sudden with pain at very high level quantified as 10 to a 0 to 10 scale, with no response to classical analgesic and corticoids. The only drugs which can reduce the intensity of pain were oxycodone hydrochloride, 60 mg daily and pregabalinum150 mg daily. After two weeks the intensity of pain was reduced to 5. The patient started a rehabilitation program. After 6 weeks the patient associated sensory and motor deficit. We performed electromyography for upper limb that showed incomplete denervation with reduced neural transmission speed. The patient receives neurotrophic drugs and painkillers for a long period and physical and kinetic therapy. After 6 months the pain was reduced to level 2 and the patient maintained only 150 mg pregabalinum for another 6 months. Then, the evaluation showed no pain but general amiotrophy in upper limb. Results: At the evaluation in 2009, the patient developed a rheumatoid syndrome with tender and swelling joints, but no positive inflammation test, no antibodies or rheumatoid factor. After two years, in 2011 the patient develops an increase of antinuclear antibodies. This context certifies the diagnosis of lupus and the patient receives the specific therapy. Conclusions: This case is not a typical case of onset of lupus with PTS, but the onset of PTS could include the onset of an immune disease.

Keywords: lupus, arm pain, patient, swelling

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Authors: Tahmidul Islam

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Propensity Score Matching (PSM) technique has been widely used for estimating causal effect of treatment in observational studies. One major step of implementing PSM is estimating the propensity score (PS). Logistic regression model with additive linear terms of covariates is most used technique in many studies. Logistics regression model is also used with cubic splines for retaining flexibility in the model. However, choosing the functional form of the logistic regression model has been a question since the effectiveness of PSM depends on how accurately the PS been estimated. In many situations, the linearity assumption of linear logistic regression may not hold and non-linear relation between the logit and the covariates may be appropriate. One can estimate PS using machine learning techniques such as random forest, neural network etc for more accuracy in non-linear situation. In this study, an attempt has been made to compare the efficacy of Generalized Additive Model (GAM) in various linear and non-linear settings and compare its performance with usual logistic regression. GAM is a non-parametric technique where functional form of the covariates can be unspecified and a flexible regression model can be fitted. In this study various simple and complex models have been considered for treatment under several situations (small/large sample, low/high number of treatment units) and examined which method leads to more covariate balance in the matched dataset. It is found that logistic regression model is impressively robust against inclusion quadratic and interaction terms and reduces mean difference in treatment and control set equally efficiently as GAM does. GAM provided no significantly better covariate balance than logistic regression in both simple and complex models. The analysis also suggests that larger proportion of controls than treatment units leads to better balance for both of the methods.

Keywords: accuracy, covariate balances, generalized additive model, logistic regression, non-linearity, propensity score matching

Procedia PDF Downloads 359

Authors: Zatovska T. V., Nesterova N. V., Baranova G. V., Zagorodnya S. D.

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In recent years, biosensor technologies based on the phenomenon of surface plasmon resonance (SPR) are becoming increasingly used in biology and medicine. Their application facilitates exploration in real time progress of binding of biomolecules and identification of agents that specifically interact with biologically active substances immobilized on the biosensor surface (biochips). Special attention is paid to the use of Biosensor analysis in determining the antibody-antigen interaction in the diagnostics of diseases caused by viruses and bacteria. According to WHO, the diseases that are caused by the herpes simplex virus (HSV), take second place (15.8%) after influenza as a cause of death from viral infections. Current diagnostics of HSV infection include PCR and ELISA assays. The latter allows determination the degree of immune response to viral infection and respective stages of its progress. In this regard, the searches for new and available diagnostic methods are very important. This work was aimed to develop Biosensor chip for detection of specific antibodies to HSV-1 in the human blood serum. The proteins of HSV1 (strain US) were used as antigens. The viral particles were accumulated in cell culture MDBK and purified by differential centrifugation in cesium chloride density gradient. Analysis of the HSV1 proteins was performed by polyacrylamide gel electrophoresis and ELISA. The protein concentration was measured using De Novix DS-11 spectrophotometer. The device for detection of antigen-antibody interactions was an optoelectronic two-channel spectrometer ‘Plasmon-6’, using the SPR phenomenon in the Krechman optical configuration. It was developed at the Lashkarev Institute of Semiconductor Physics of NASU. The used carrier was a glass plate covered with 45 nm gold film. Screening of human blood serums was performed using the test system ‘HSV-1 IgG ELISA’ (GenWay, USA). Development of Biosensor chip included optimization of conditions of viral antigen sorption and analysis steps. For immobilization of viral proteins 0.2% solution of Dextran 17, 200 (Sigma, USA) was used. Sorption of antigen took place at 4-8°C within 18-24 hours. After washing of chip, three times with citrate buffer (pH 5,0) 1% solution of BSA was applied to block the sites not occupied by viral antigen. It was found direct dependence between the amount of immobilized HSV1 antigen and SPR response. Using obtained biochips, panels of 25 positive and 10 negative for the content of antibodies to HSV-1 human sera were analyzed. The average value of SPR response was 185 a.s. for negative sera and from 312 to. 1264 a.s. for positive sera. It was shown that SPR data were agreed with ELISA results in 96% of samples proving the great potential of SPR in such researches. It was investigated the possibility of biochip regeneration and it was shown that application of 10 mM NaOH solution leads to rupture of intermolecular bonds. This allows reuse the chip several times. Thus, in this study biosensor chip for detection of specific antibodies to HSV1 was successfully developed expanding a range of diagnostic methods for this pathogen.

Keywords: biochip, herpes virus, SPR

Procedia PDF Downloads 413

Authors: Dario Barsi, Marina Ubaldi, Pietro Zunino, Robert Fink

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A design and optimization procedure is proposed and developed to provide the geometry of a high efficiency compact hydraulic propeller turbine for low head. For the preliminary design of the machine, classic design criteria, based on the use of statistical correlations for the definition of the fundamental geometric parameters and the blade shapes are used. These relationships are based on the fundamental design parameters (i.e., specific speed, flow coefficient, work coefficient) in order to provide a simple yet reliable procedure. Particular attention is paid, since from the initial steps, on the correct conformation of the meridional channel and on the correct arrangement of the blade rows. The preliminary geometry thus obtained is used as a starting point for the hydrodynamic optimization procedure, carried out using a CFD calculation software coupled with a genetic algorithm that generates and updates a large database of turbine geometries. The optimization process is performed using a commercial approach that solves the turbulent Navier Stokes equations (RANS) by exploiting the axial-symmetric geometry of the machine. The geometries generated within the database are therefore calculated in order to determine the corresponding overall performance. In order to speed up the optimization calculation, an artificial neural network (ANN) based on the use of an objective function is employed. The procedure was applied for the specific case of a propeller turbine with an innovative design of a modular type, specific for applications characterized by very low heads. The procedure is tested in order to verify its validity and the ability to automatically obtain the targeted net head and the maximum for the total to total internal efficiency.

Keywords: renewable energy conversion, hydraulic turbines, low head hydraulic energy, optimization design

Procedia PDF Downloads 144

Authors: Wang Hong, Liu Chang Kui, Zhao Bing Jing, Hu Min

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Objection We observed the repairment effection of canine mandibular defect with meshy Ti6Al4V scaffold fabricated by electron beam melting (EBM) combined with bone marrow mesenchymal stem cells (BMMSCs) encapsulated in chitosan hydrogel. Method Meshy titanium scaffolds were prepared by EBM of commercial Ti6Al4V power. The length of scaffolds was 24 mm, the width was 5 mm and height was 8mm. The pore size and porosity were evaluated by scanning electron microscopy (SEM). Chitosan /Bio-Oss hydrogel was prepared by chitosan, β- sodium glycerophosphate and Bio-Oss power. BMMSCs were harvested from canine iliac crests. BMMSCs were seeded in titanium scaffolds and encapsulated in Chitosan /Bio-Oss hydrogel. The validity of BMMSCs was evaluated by cell count kit-8 (CCK-8). The osteogenic differentiation ability was evaluated by alkaline phosphatase (ALP) activity and gene expression of OC, OPN and CoⅠ. Combination were performed by injecting BMMSCs/ Chitosan /Bio-Oss hydrogel into the meshy Ti6Al4V scaffolds and solidified. 24 mm long box-shaped bone defects were made at the mid-portion of mandible of adult beagles. The defects were randomly filled with BMMSCs/ Chitosan/Bio-Oss + titanium, Chitosan /Bio-Oss+titanium, titanium alone. Autogenous iliac crests graft as control group in 3 beagles. Radionuclide bone imaging was used to monitor the new bone tissue at 2, 4, 8 and 12 weeks after surgery. CT examination was made on the surgery day and 4 weeks, 12 weeks and 24 weeks after surgery. The animals were sacrificed in 4, 12 and 24 weeks after surgery. The bone formation were evaluated by histology and micro-CT. Results: The pores of the scaffolds was interconnected, the pore size was about 1 mm, the average porosity was about 76%. The pore size of the hydrogel was 50-200μm and the average porosity was approximately 90%. The hydrogel were solidified under the condition of 37℃in 10 minutes. The validity and the osteogenic differentiation ability of BMSCs were not affected by titanium scaffolds and hydrogel. Radionuclide bone imaging shown an increasing tendency of the revascularization and bone regeneration was observed in all the groups at 2, 4, 8 weeks after operation, and there were no changes at 12weeks.The tendency was more obvious in the BMMSCs/ Chitosan/Bio-Oss +titanium group and autogenous group. CT, Micro-CT and histology shown that new bone formed increasingly with the time extend. There were more new bone regenerated in BMMSCs/ Chitosan /Bio-Oss + titanium group and autogenous group than the other two groups. At 24 weeks, the autogenous group was achieved bone union. The BMSCs/ Chitosan /Bio-Oss group was seen extensive new bone formed around the scaffolds and more new bone inside of the central pores of scaffolds than Chitosan /Bio-Oss + titanium group and titanium group. The difference was significantly. Conclusion: The titanium scaffolds fabricated by EBM had controlled porous structure, good bone conduction and biocompatibility. Chitosan /Bio-Oss hydrogel had injectable plasticity, thermosensitive property and good biocompatibility. The meshy Ti6Al4V scaffold produced by EBM combined BMSCs encapsulated in chitosan hydrogel had good capacity on mandibular bone defect repair.

Keywords: mandibular reconstruction, tissue engineering, electron beam melting, titanium alloy

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Authors: Louise Moles, Steve Riley, Sarah D. Lichenstein, Marzieh Babaeianjelodar, Robert Kohler, Annie Cheng, Corey Horien Abigail Greene, Wenjing Luo, Jonathan Ahern, Bohan Xu, Yize Zhao, Chun Chieh Fan, R. Todd Constable, Sarah W. Yip

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Background: Risks for depression are myriad and include both genetic and brain-based factors. However, relationships between these systems are poorly understood, limiting understanding of disease etiology, particularly at the developmental level. Methods: We use a data-driven machine learning approach connectome-based predictive modeling (CPM) to identify functional connectivity signatures associated with polygenic risk scores for depression (DEP-PRS) among youth from the Adolescent Brain and Cognitive Development (ABCD) study across diverse brain states, i.e., during resting state, during affective working memory, during response inhibition, during reward processing. Results: Using 10-fold cross-validation with 100 iterations and permutation testing, CPM identified connectivity signatures of DEP-PRS across all examined brain states (rho’s=0.20-0.27, p’s<.001). Across brain states, DEP-PRS was positively predicted by increased connectivity between frontoparietal and salience networks, increased motor-sensory network connectivity, decreased salience to subcortical connectivity, and decreased subcortical to motor-sensory connectivity. Subsampling analyses demonstrated that model accuracies were robust across random subsamples of N’s=1,000, N’s=500, and N’s=250 but became unstable at N’s=100. Conclusions: These data, for the first time, identify neural networks of polygenic depression risk in a large sample of youth before the onset of significant clinical impairment. Identified networks may be considered potential treatment targets or vulnerability markers for depression risk.

Keywords: genetics, functional connectivity, pre-adolescents, depression

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Authors: Heba M. Saad Eldien, Ola Abdel-Tawab Hussein, Ahmed Yassein Nassar

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Background: Indomethacin is a non-steroidal anti inflammatory drug. Indomethacin induces an injury to gastrointestinal mucosa in experimental animals and humans and their use is associated with a significant risk of hemorrhage, erosions and perforation of both gastric and intestinal ulcers. The anti-inflammatory action of copper complexes is an important activity of their anti-ulcer effect achieved by their intermediary role as a transport form of copper that allow activation of the several copper-dependent enzymes. Therefore, several copper complexes were synthesized and investigated as promising alternative anti-ulcer therapy. Aim of the work: The purpose of this study was to evaluate a copper chelating complex consisting of egg albumin and copper as one of the copper peptides that can be used as anti-inflammatory agent and effective in ameliorates the hazards of the indomethacin on the histological structure of the fundus of the stomach that could be added to raise the efficacy of the currently used simple and cheap gastric anti-inflammatory drug mucogel. Material &methods: This study was carried out on 40 adult male albino rats,divided equally into 4 groups;Group I(control group) received distilled water,Group II(indomethacin treated group) received (25 mg/kg body weight, oral intubation) once, Group III (mucogel treated group)2 mL/rat once daily, oral incubation, Group IV(copper complex group) 1 mL /rat of 30 gm of copper albumin complex was mixed uniformly with mucogel to 100 mL. Treatment has been started six hour after Induction of Ulcers and continued till the 3rd day. The animals sacrificed and was processed for light, transmission electron microscopy(TEM) and immunostaining for inducible nitric oxide synthase(iNOS). Results: Fundic mucosa of group II, showed exfoliation of epithelial cells lining the gland, discontinuity of surface epithelial cells (ulcer formation), vacuolation and detachment of cells, eosinophilic infiltration and congestion of blood vessels in the lamina propria and submucosa. There was thickening and disarrangement of mucosa, weak positive reaction for PAS and marked increase in the collagen fibers lamina propria and the submucosa of the fundus. TEM revealed degeneration of cheif and parietal cells.Marked increase positive reactive of iNOS in all cells of the fundic gland. Group III showed reconstruction of gastric gland with cystic dilatation and vacuolation, moderate decrease of collagen fibers, reduced the intensity of iNOS while in Group IV healthy mucosa with normal surface lining epithelium and fundic glands, strong positive reaction for PAS, marked decrease of collagen fibers and positive reaction for iNOS. TEM revealed regeneration of cheif and parietal cells. Conclusion: Co treatment of copper-albumin complex seems to be useful for gastric ulcer treatment and ameliorates most of hazards of indomethacin.

Keywords: copper complex, gastric ulcer, indomethacin, rat

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Authors: Chen Jun-Hong, He Pu, Tao Wen-Quan

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Proton exchange membrane fuel cell (PEMFC) is the most promising future energy source owing to its low operating temperature, high energy efficiency, high power density, and environmental friendliness. In this paper, a comprehensive PEMFC system control-oriented model is developed in the Matlab/Simulink environment, which includes the hydrogen supply subsystem, air supply subsystem, and thermal management subsystem. Besides, Improved Artificial Bee Colony (IABC) is used in the parameter identification of PEMFC semi-empirical equations, making the maximum relative error between simulation data and the experimental data less than 0.4%. Operation temperature is essential for PEMFC, both high and low temperatures are disadvantageous. In the thermal management subsystem, water pump and fan are both controlled with the PID controller to maintain the appreciate operation temperature of PEMFC for the requirements of safe and efficient operation. To improve the control effect further, fuzzy control is introduced to optimize the PID controller of the pump, and the Radial Basis Function (RBF) neural network is introduced to optimize the PID controller of the fan. The results demonstrate that Fuzzy-PID and RBF-PID can achieve a better control effect with 22.66% decrease in Integral Absolute Error Criterion (IAE) of T_st (Temperature of PEMFC) and 77.56% decrease in IAE of T_in (Temperature of inlet cooling water) compared with traditional PID. In the end, a novel thermal management structure is proposed, which uses the cooling air passing through the main radiator to continue cooling the secondary radiator. In this thermal management structure, the parasitic power dissipation can be reduced by 69.94%, and the control effect can be improved with a 52.88% decrease in IAE of T_in under the same controller.

Keywords: PEMFC system, parameter identification, temperature control, Fuzzy-PID, RBF-PID, parasitic power

Procedia PDF Downloads 72