Search results for: optical burst switching networks
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4793

Search results for: optical burst switching networks

383 The Use of Artificial Intelligence in Diagnosis of Mastitis in Cows

Authors: Djeddi Khaled, Houssou Hind, Miloudi Abdellatif, Rabah Siham

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In the field of veterinary medicine, there is a growing application of artificial intelligence (AI) for diagnosing bovine mastitis, a prevalent inflammatory disease in dairy cattle. AI technologies, such as automated milking systems, have streamlined the assessment of key metrics crucial for managing cow health during milking and identifying prevalent diseases, including mastitis. These automated milking systems empower farmers to implement automatic mastitis detection by analyzing indicators like milk yield, electrical conductivity, fat, protein, lactose, blood content in the milk, and milk flow rate. Furthermore, reports highlight the integration of somatic cell count (SCC), thermal infrared thermography, and diverse systems utilizing statistical models and machine learning techniques, including artificial neural networks, to enhance the overall efficiency and accuracy of mastitis detection. According to a review of 15 publications, machine learning technology can predict the risk and detect mastitis in cattle with an accuracy ranging from 87.62% to 98.10% and sensitivity and specificity ranging from 84.62% to 99.4% and 81.25% to 98.8%, respectively. Additionally, machine learning algorithms and microarray meta-analysis are utilized to identify mastitis genes in dairy cattle, providing insights into the underlying functional modules of mastitis disease. Moreover, AI applications can assist in developing predictive models that anticipate the likelihood of mastitis outbreaks based on factors such as environmental conditions, herd management practices, and animal health history. This proactive approach supports farmers in implementing preventive measures and optimizing herd health. By harnessing the power of artificial intelligence, the diagnosis of bovine mastitis can be significantly improved, enabling more effective management strategies and ultimately enhancing the health and productivity of dairy cattle. The integration of artificial intelligence presents valuable opportunities for the precise and early detection of mastitis, providing substantial benefits to the dairy industry.

Keywords: artificial insemination, automatic milking system, cattle, machine learning, mastitis

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382 Non-Steroidal Microtubule Disrupting Analogues Induce Programmed Cell Death in Breast and Lung Cancer Cell Lines

Authors: Marcel Verwey, Anna M. Joubert, Elsie M. Nolte, Wolfgang Dohle, Barry V. L. Potter, Anne E. Theron

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A tetrahydroisoquinolinone (THIQ) core can be used to mimic the A,B-ring of colchicine site-binding microtubule disruptors such as 2-methoxyestradiol in the design of anti-cancer agents. Steroidomimeric microtubule disruptors were synthesized by introducing C'2 and C'3 of the steroidal A-ring to C'6 and C'7 of the THIQ core and by introducing a decorated hydrogen bond acceptor motif projecting from the steroidal D-ring to N'2. For this in vitro study, four non-steroidal THIQ-based analogues were investigated and comparative studies were done between the non-sulphamoylated compound STX 3450 and the sulphamoylated compounds STX 2895, STX 3329 and STX 3451. The objective of this study was to investigate the modes of cell death induced by these four THIQ-based analogues in A549 lung carcinoma epithelial cells and metastatic breast adenocarcinoma MDA-MB-231 cells. Cytotoxicity studies to determine the half maximal growth inhibitory concentrations were done using spectrophotometric quantification via crystal violet staining and lactate dehydrogenase (LDH) assays. Microtubule integrity and morphologic changes of exposed cells were investigated using polarization-optical transmitted light differential interference contrast microscopy, transmission electron microscopy and confocal microscopy. Flow cytometric quantification was used to determine apoptosis induction and the effect that THIQ-based analogues have on cell cycle progression. Signal transduction pathways were elucidated by quantification of the mitochondrial membrane integrity, cytochrome c release and caspase 3, -6 and -8 activation. Induction of autophagic cell death by the THIQ-based analogues was investigated by morphological assessment of fluorescent monodansylcadaverine (MDC) staining of acidic vacuoles and by quantifying aggresome formation via flow cytometry. Results revealed that these non-steroidal microtubule disrupting analogues inhibited 50% of cell growth at nanomolar concentrations. Immunofluorescence microscopy indicated microtubule depolarization and the resultant mitotic arrest was further confirmed through cell cycle analysis. Apoptosis induction via the intrinsic pathway was observed due to depolarization of the mitochondrial membrane, induction of cytochrome c release as well as, caspase 3 activation. Potential involvement of programmed cell death type II was observed due to the presence of acidic vacuoles and aggresome formation. Necrotic cell death did not contribute significantly, indicated by stable LDH levels. This in vitro study revealed the induction of the intrinsic apoptotic pathway as well as possible involvement of autophagy after exposure to these THIQ-based analogues in both MDA-MB-231- and A549 cells. Further investigation of this series of anticancer drugs still needs to be conducted to elucidate the temporal, mechanistic and functional crosstalk mechanisms between the two observed programmed cell deaths pathways.

Keywords: apoptosis, autophagy, cancer, microtubule disruptor

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381 The Sustainable Development for Coastal Tourist Building

Authors: D. Avila

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The tourism industry is a phenomenon that has become a growing presence in international socio-economic dynamics, which in most cases exceeds the control parameters in the various environmental regulations and sustainability of existing resources. Because of this, the effects on the natural environment at the regional and national levels represent a challenge, for which a number of strategies are necessary to minimize the environmental impact generated by the occupation of the territory. The hotel tourist building and sustainable development in the coastal zone, have an important impact on the environment and on the physical and psychological health of the inhabitants. Environmental quality associated with the comfort of humans to the sustainable development of natural resources; applied to the hotel architecture this concept involves the incorporation of new demands on all of the constructive process of a building, changing customs of developers and users. The methodology developed provides an initial analysis to determine and rank the different tourist buildings, with the above it will be feasible to establish methods of study and environmental impact assessment. Finally, it is necessary to establish an overview regarding the best way to implement tourism development on the coast, containing guidelines to improve and protect the natural environment. This paper analyzes the parameters and strategies to reduce environmental impacts derived from deployments tourism on the coast, through a series of recommendations towards sustainability, in the context of the Bahia de Banderas, Puerto Vallarta, Jalisco. The environmental impact caused by the implementation of tourism development, perceived in a coastal environment, forcing a series of processes, ranging from the identification of impacts, prediction and evaluation of them. For this purpose are described below, different techniques and valuation procedures: Identification of impacts. Methods for the identification of damage caused to the environment pursue general purpose to obtain a group of negative indicators that are subsequently used in the study of environmental impact. There are several systematic methods to identify the impacts caused by human activities. In the present work, develops a procedure based and adapted from the Ministry of works public urban reference in studies of environmental impacts, the representative methods are: list of contrast, arrays, and networks, method of transparencies and superposition of maps.

Keywords: environmental impact, physical health, sustainability, tourist building

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380 Enhancing Signal Reception in a Mobile Radio Network Using Adaptive Beamforming Antenna Arrays Technology

Authors: Ugwu O. C., Mamah R. O., Awudu W. S.

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This work is aimed at enhancing signal reception on a mobile radio network and minimizing outage probability in a mobile radio network using adaptive beamforming antenna arrays. In this research work, an empirical real-time drive measurement was done in a cellular network of Globalcom Nigeria Limited located at Ikeja, the headquarters of Lagos State, Nigeria, with reference base station number KJA 004. The empirical measurement includes Received Signal Strength and Bit Error Rate which were recorded for exact prediction of the signal strength of the network as at the time of carrying out this research work. The Received Signal Strength and Bit Error Rate were measured with a spectrum monitoring Van with the help of a Ray Tracer at an interval of 100 meters up to 700 meters from the transmitting base station. The distance and angular location measurements from the reference network were done with the help Global Positioning System (GPS). The other equipment used were transmitting equipment measurements software (Temsoftware), Laptops and log files, which showed received signal strength with distance from the base station. Results obtained were about 11% from the real-time experiment, which showed that mobile radio networks are prone to signal failure and can be minimized using an Adaptive Beamforming Antenna Array in terms of a significant reduction in Bit Error Rate, which implies improved performance of the mobile radio network. In addition, this work did not only include experiments done through empirical measurement but also enhanced mathematical models that were developed and implemented as a reference model for accurate prediction. The proposed signal models were based on the analysis of continuous time and discrete space, and some other assumptions. These developed (proposed) enhanced models were validated using MATLAB (version 7.6.3.35) program and compared with the conventional antenna for accuracy. These outage models were used to manage the blocked call experience in the mobile radio network. 20% improvement was obtained when the adaptive beamforming antenna arrays were implemented on the wireless mobile radio network.

Keywords: beamforming algorithm, adaptive beamforming, simulink, reception

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379 Controlled Nano Texturing in Silicon Wafer for Excellent Optical and Photovoltaic Properties

Authors: Deb Kumar Shah, M. Shaheer Akhtar, Ha Ryeon Lee, O-Bong Yang, Chong Yeal Kim

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The crystalline silicon (Si) solar cells are highly renowned photovoltaic technology and well-established as the commercial solar technology. Most of the solar panels are globally installed with the crystalline Si solar modules. At the present scenario, the major photovoltaic (PV) market is shared by c-Si solar cells, but the cost of c-Si panels are still very high as compared with the other PV technology. In order to reduce the cost of Si solar panels, few necessary steps such as low-cost Si manufacturing, cheap antireflection coating materials, inexpensive solar panel manufacturing are to be considered. It is known that the antireflection (AR) layer in c-Si solar cell is an important component to reduce Fresnel reflection for improving the overall conversion efficiency. Generally, Si wafer exhibits the 30% reflection because it normally poses the two major intrinsic drawbacks such as; the spectral mismatch loss and the high Fresnel reflection loss due to the high contrast of refractive indices between air and silicon wafer. In recent years, researchers and scientists are highly devoted to a lot of researches in the field of searching effective and low-cost AR materials. Silicon nitride (SiNx) is well-known AR materials in commercial c-Si solar cells due to its good deposition and interaction with passivated Si surfaces. However, the deposition of SiNx AR is usually performed by expensive plasma enhanced chemical vapor deposition (PECVD) process which could have several demerits like difficult handling and damaging the Si substrate by plasma when secondary electrons collide with the wafer surface for AR coating. It is very important to explore new, low cost and effective AR deposition process to cut the manufacturing cost of c-Si solar cells. One can also be realized that a nano-texturing process like the growth of nanowires, nanorods, nanopyramids, nanopillars, etc. on Si wafer can provide a low reflection on the surface of Si wafer based solar cells. The above nanostructures might be enhanced the antireflection property which provides the larger surface area and effective light trapping. In this work, we report on the development of crystalline Si solar cells without using the AR layer. The Silicon wafer was modified by growing nanowires like Si nanostructures using the wet controlled etching method and directly used for the fabrication of Si solar cell without AR. The nanostructures over Si wafer were optimized in terms of sizes, lengths, and densities by changing the etching conditions. Well-defined and aligned wires like structures were achieved when the etching time is 20 to 30 min. The prepared Si nanostructured displayed the minimum reflectance ~1.64% at 850 nm with the average reflectance of ~2.25% in the wavelength range from 400-1000 nm. The nanostructured Si wafer based solar cells achieved the comparable power conversion efficiency in comparison with c-Si solar cells with SiNx AR layer. From this study, it is confirmed that the reported method (controlled wet etching) is an easy, facile method for preparation of nanostructured like wires on Si wafer with low reflectance in the whole visible region, which has greater prospects in developing c-Si solar cells without AR layer at low cost.

Keywords: chemical etching, conversion efficiency, silicon nanostructures, silicon solar cells, surface modification

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378 Accessible Mobile Augmented Reality App for Art Social Learning Based on Technology Acceptance Model

Authors: Covadonga Rodrigo, Felipe Alvarez Arrieta, Ana Garcia Serrano

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Mobile augmented reality technologies have become very popular in the last years in the educational field. Researchers have studied how these technologies improve the engagement of the student and better understanding of the process of learning. But few studies have been made regarding the accessibility of these new technologies applied to digital humanities. The goal of our research is to develop an accessible mobile application with embedded augmented reality main characters of the art work and gamification events accompanied by multi-sensorial activities. The mobile app conducts a learning itinerary around the artistic work, driving the user experience in and out the museum. The learning design follows the inquiry-based methodology and social learning conducted through interaction with social networks. As for the software application, it’s being user-centered designed, following the universal design for learning (UDL) principles to assure the best level of accessibility for all. The mobile augmented reality application starts recognizing a marker from a masterpiece of a museum using the camera of the mobile device. The augmented reality information (history, author, 3D images, audio, quizzes) is shown through virtual main characters that come out from the art work. To comply with the UDL principles, we use a version of the technology acceptance model (TAM) to study the easiness of use and perception of usefulness, extended by the authors with specific indicators for measuring accessibility issues. Following a rapid prototype method for development, the first app has been recently produced, fulfilling the EN 301549 standard and W3C accessibility guidelines for mobile development. A TAM-based web questionnaire with 214 participants with different kinds of disabilities was previously conducted to gather information and feedback on user preferences from the artistic work on the Museo del Prado, the level of acceptance of technology innovations and the easiness of use of mobile elements. Preliminary results show that people with disabilities felt very comfortable while using mobile apps and internet connection. The augmented reality elements seem to offer an added value highly engaging and motivating for the students.

Keywords: H.5.1 (multimedia information systems), artificial, augmented and virtual realities, evaluation/methodology

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377 A Method To Assess Collaboration Using Perception of Risk from the Architectural Engineering Construction Industry

Authors: Sujesh F. Sujan, Steve W. Jones, Arto Kiviniemi

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The use of Building Information Modelling (BIM) in the Architectural-Engineering-Construction (AEC) industry is a form of systemic innovation. Unlike incremental innovation, (such as the technological development of CAD from hand based drawings to 2D electronically printed drawings) any form of systemic innovation in Project-Based Inter-Organisational Networks requires complete collaboration and results in numerous benefits if adopted and utilised properly. Proper use of BIM involves people collaborating with the use of interoperable BIM compliant tools. The AEC industry globally has been known for its adversarial and fragmented nature where firms take advantage of one another to increase their own profitability. Due to the industry’s nature, getting people to collaborate by unifying their goals is critical to successful BIM adoption. However, this form of innovation is often being forced artificially in the old ways of working which do not suit collaboration. This may be one of the reasons for its low global use even though the technology was developed more than 20 years ago. Therefore, there is a need to develop a metric/method to support and allow industry players to gain confidence in their investment into BIM software and workflow methods. This paper departs from defining systemic risk as a risk that affects all the project participants at a given stage of a project and defines categories of systemic risks. The need to generalise is to allow method applicability to any industry where the category will be the same, but the example of the risk will depend on the industry the study is done in. The method proposed seeks to use individual perception of an example of systemic risk as a key parameter. The significance of this study lies in relating the variance of individual perception of systemic risk to how much the team is collaborating. The method bases its notions on the claim that a more unified range of individual perceptions would mean a higher probability that the team is collaborating better. Since contracts and procurement devise how a project team operates, the method could also break the methodological barrier of highly subjective findings that case studies inflict, which has limited the possibility of generalising between global industries. Since human nature applies in all industries, the authors’ intuition is that perception can be a valuable parameter to study collaboration which is essential especially in projects that utilise systemic innovation such as BIM.

Keywords: building information modelling, perception of risk, systemic innovation, team collaboration

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376 Task Based Functional Connectivity within Reward Network in Food Image Viewing Paradigm Using Functional MRI

Authors: Preetham Shankapal, Jill King, Kori Murray, Corby Martin, Paula Giselman, Jason Hicks, Owen Carmicheal

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Activation of reward and satiety networks in the brain while processing palatable food cues, as well as functional connectivity during rest has been studied using functional Magnetic Resonance Imaging of the brain in various obesity phenotypes. However, functional connectivity within the reward and satiety network during food cue processing is understudied. 14 obese individuals underwent two fMRI scans during viewing of Macronutrient Picture System images. Each scan included two blocks of images of High Sugar/High Fat (HSHF), High Carbohydrate/High Fat (HCHF), Low Sugar/Low Fat (LSLF) and also non-food images. Seed voxels within seven food reward relevant ROIs: Insula, putamen and cingulate, precentral, parahippocampal, medial frontal and superior temporal gyri were isolated based on a prior meta-analysis. Beta series correlation for task-related functional connectivity between these seed voxels and the rest of the brain was computed. Voxel-level differences in functional connectivity were calculated between: first and the second scan; individuals who saw novel (N=7) vs. Repeated (N=7) images in the second scan; and between the HC/HF, HSHF blocks vs LSLF and non-food blocks. Computations and analysis showed that during food image viewing, reward network ROIs showed significant functional connectivity with each other and with other regions responsible for attentional and motor control, including inferior parietal lobe and precentral gyrus. These functional connectivity values were heightened among individuals who viewed novel HS/HF images in the second scan. In the second scan session, functional connectivity was reduced within the reward network but increased within attention, memory and recognition regions, suggesting habituation to reward properties and increased recollection of previously viewed images. In conclusion it can be inferred that Functional Connectivity within reward network and between reward and other brain regions, varies by important experimental conditions during food photography viewing, including habituation to shown foods.

Keywords: fMRI, functional connectivity, task-based, beta series correlation

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375 Sensor Network Structural Integration for Shape Reconstruction of Morphing Trailing Edge

Authors: M. Ciminello, I. Dimino, S. Ameduri, A. Concilio

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Improving aircraft's efficiency is one of the key elements of Aeronautics. Modern aircraft possess many advanced functions, such as good transportation capability, high Mach number, high flight altitude, and increasing rate of climb. However, no aircraft has a possibility to reach all of this optimized performance in a single airframe configuration. The aircraft aerodynamic efficiency varies considerably depending on the specific mission and on environmental conditions within which the aircraft must operate. Structures that morph their shape in response to their surroundings may at first seem like the stuff of science fiction, but take a look at nature and lots of examples of plants and animals that adapt to their environment would arise. In order to ensure both the controllable and the static robustness of such complex structural systems, a monitoring network is aimed at verifying the effectiveness of the given control commands together with the elastic response. In order to achieve this kind of information, the use of FBG sensors network is, in this project, proposed. The sensor network is able to measure morphing structures shape which may show large, global displacements due to non-standard architectures and materials adopted. Chord -wise variations may allow setting and chasing the best layout as a function of the particular and transforming reference state, always targeting best aerodynamic performance. The reason why an optical sensor solution has been selected is that while keeping a few of the contraindication of the classical systems (like cabling, continuous deployment, and so on), fibre optic sensors may lead to a dramatic reduction of the wires mass and weight thanks to an extreme multiplexing capability. Furthermore, the use of the ‘light’ as ‘information carrier’, permits dealing with nimbler, non-shielded wires, and avoids any kind of interference with the on-board instrumentation. The FBG-based transducers, herein presented, aim at monitoring the actual shape of adaptive trailing edge. Compared to conventional systems, these transducers allow more fail-safe measurements, by taking advantage of a supporting structure, hosting FBG, whose properties may be tailored depending on the architectural requirements and structural constraints, acting as strain modulator. The direct strain may, in fact, be difficult because of the large deformations occurring in morphing elements. A modulation transducer is then necessary to keep the measured strain inside the allowed range. In this application, chord-wise transducer device is a cantilevered beam sliding trough the spars and copying the camber line of the ATE ribs. FBG sensors array position are dimensioned and integrated along the path. A theoretical model describing the system behavior is implemented. To validate the design, experiments are then carried out with the purpose of estimating the functions between rib rotation and measured strain.

Keywords: fiber optic sensor, morphing structures, strain sensor, shape reconstruction

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374 DEEPMOTILE: Motility Analysis of Human Spermatozoa Using Deep Learning in Sri Lankan Population

Authors: Chamika Chiran Perera, Dananjaya Perera, Chirath Dasanayake, Banuka Athuraliya

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Male infertility is a major problem in the world, and it is a neglected and sensitive health issue in Sri Lanka. It can be determined by analyzing human semen samples. Sperm motility is one of many factors that can evaluate male’s fertility potential. In Sri Lanka, this analysis is performed manually. Manual methods are time consuming and depend on the person, but they are reliable and it can depend on the expert. Machine learning and deep learning technologies are currently being investigated to automate the spermatozoa motility analysis, and these methods are unreliable. These automatic methods tend to produce false positive results and false detection. Current automatic methods support different techniques, and some of them are very expensive. Due to the geographical variance in spermatozoa characteristics, current automatic methods are not reliable for motility analysis in Sri Lanka. The suggested system, DeepMotile, is to explore a method to analyze motility of human spermatozoa automatically and present it to the andrology laboratories to overcome current issues. DeepMotile is a novel deep learning method for analyzing spermatozoa motility parameters in the Sri Lankan population. To implement the current approach, Sri Lanka patient data were collected anonymously as a dataset, and glass slides were used as a low-cost technique to analyze semen samples. Current problem was identified as microscopic object detection and tackling the problem. YOLOv5 was customized and used as the object detector, and it achieved 94 % mAP (mean average precision), 86% Precision, and 90% Recall with the gathered dataset. StrongSORT was used as the object tracker, and it was validated with andrology experts due to the unavailability of annotated ground truth data. Furthermore, this research has identified many potential ways for further investigation, and andrology experts can use this system to analyze motility parameters with realistic accuracy.

Keywords: computer vision, deep learning, convolutional neural networks, multi-target tracking, microscopic object detection and tracking, male infertility detection, motility analysis of human spermatozoa

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373 Yield Loss Estimation Using Multiple Drought Severity Indices

Authors: Sara Tokhi Arab, Rozo Noguchi, Tofeal Ahamed

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Drought is a natural disaster that occurs in a region due to a lack of precipitation and high temperatures over a continuous period or in a single season as a consequence of climate change. Precipitation deficits and prolonged high temperatures mostly affect the agricultural sector, water resources, socioeconomics, and the environment. Consequently, it causes agricultural product loss, food shortage, famines, migration, and natural resources degradation in a region. Agriculture is the first sector affected by drought. Therefore, it is important to develop an agricultural drought risk and loss assessment to mitigate the drought impact in the agriculture sector. In this context, the main purpose of this study was to assess yield loss using composite drought indices in the drought-affected vineyards. In this study, the CDI was developed for the years 2016 to 2020 by comprising five indices: the vegetation condition index (VCI), temperature condition index (TCI), deviation of NDVI from the long-term mean (NDVI DEV), normalized difference moisture index (NDMI) and precipitation condition index (PCI). Moreover, the quantitative principal component analysis (PCA) approach was used to assign a weight for each input parameter, and then the weights of all the indices were combined into one composite drought index. Finally, Bayesian regularized artificial neural networks (BRANNs) were used to evaluate the yield variation in each affected vineyard. The composite drought index result indicated the moderate to severe droughts were observed across the Kabul Province during 2016 and 2018. Moreover, the results showed that there was no vineyard in extreme drought conditions. Therefore, we only considered the severe and moderated condition. According to the BRANNs results R=0.87 and R=0.94 in severe drought conditions for the years of 2016 and 2018 and the R= 0.85 and R=0.91 in moderate drought conditions for the years of 2016 and 2018, respectively. In the Kabul Province within the two years drought periods, there was a significate deficit in the vineyards. According to the findings, 2018 had the highest rate of loss almost -7 ton/ha. However, in 2016 the loss rates were about – 1.2 ton/ha. This research will support stakeholders to identify drought affect vineyards and support farmers during severe drought.

Keywords: grapes, composite drought index, yield loss, satellite remote sensing

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372 Improvement of Greenhouse Gases Bio-Fixation by Microalgae Using a “Plasmon-Enhanced Photobioreactor”

Authors: Francisco Pereira, António Augusto Vicente, Filipe Vaz, Joel Borges, Pedro Geada

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Light is a growth-limiting factor in microalgae cultivation, where factors like spectral components, intensity, and duration, often characterized by its wavelength, are well-reported to have a substantial impact on cell growth rates and, consequently, photosynthetic performance and mitigation of CO2, one of the most significant greenhouse gases (GHGs). Photobioreactors (PBRs) are commonly used to grow microalgae under controlled conditions, but they often fail to provide an even light distribution to the cultures. For this reason, there is a pressing need for innovations aiming at enhancing the efficient utilization of light. So, one potential approach to address this issue is by implementing plasmonic films, such as the localized surface plasmon resonance (LSPR). LSPR is an optical phenomenon connected to the interaction of light with metallic nanostructures. LSPR excitation is characterized by the oscillation of unbound conduction electrons of the nanoparticles coupled with the electromagnetic field from incident light. As a result of this excitation, highly energetic electrons and a strong electromagnetic field are generated. These effects lead to an amplification of light scattering, absorption, and extinction of specific wavelengths, contingent on the nature of the employed nanoparticle. Thus, microalgae might benefit from this biotechnology as it enables the selective filtration of inhibitory wavelengths and harnesses the electromagnetic fields produced, which could lead to enhancements in both biomass and metabolite productivity. This study aimed at implementing and evaluating a “plasmon-enhanced PBR”. The goal was to utilize LSPR thin films to enhance the growth and CO2 bio-fixation rate of Chlorella vulgaris. The internal/external walls of the PBRs were coated with a TiO2 matrix containing different nanoparticles (Au, Ag, and Au-Ag) in order to evaluate the impact of this approach on microalgae’s performance. Plasmonic films with distinct compositions resulted in different Chlorella vulgaris growth, ranging from 4.85 to 6.13 g.L-1. The highest cell concentrations were obtained with the metallic Ag films, demonstrating a 14% increase compared to the control condition. Moreover, it appeared to be no differences in growth between PBRs with inner and outer wall coatings. In terms of CO2 bio-fixation, distinct rates were obtained depending on the coating applied, ranging from 0.42 to 0.53 gCO2L-1d-1. Ag coating was demonstrated to be the most effective condition for carbon fixation by C. vulgaris. The impact of LSPR films on the biochemical characteristics of biomass (e.g., proteins, lipids, pigments) was analysed as well. Interestingly, Au coating yielded the most significant enhancements in protein content and total pigments, with increments of 15 % and 173 %, respectively, when compared to the PBR without any coating (control condition). Overall, the incorporation of plasmonic films in PBRs seems to have the potential to improve the performance and efficiency of microalgae cultivation, thereby representing an interesting approach to increase both biomass production and GHGs bio-mitigation.

Keywords: CO₂ bio-fixation, plasmonic effect, photobioreactor, photosynthetic microalgae

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371 Design and Synthesis of an Organic Material with High Open Circuit Voltage of 1.0 V

Authors: Javed Iqbal

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The growing need for energy by the human society and depletion of conventional energy sources demands a renewable, safe, infinite, low-cost and omnipresent energy source. One of the most suitable ways to solve the foreseeable world’s energy crisis is to use the power of the sun. Photovoltaic devices are especially of wide interest as they can convert solar energy to electricity. Recently the best performing solar cells are silicon-based cells. However, silicon cells are expensive, rigid in structure and have a large timeline for the payback of cost and electricity. Organic photovoltaic cells are cheap, flexible and can be manufactured in a continuous process. Therefore, organic photovoltaic cells are an extremely favorable replacement. Organic photovoltaic cells utilize sunlight as energy and convert it into electricity through the use of conductive polymers/ small molecules to separate electrons and electron holes. A major challenge for these new organic photovoltaic cells is the efficiency, which is low compared with the traditional silicon solar cells. To overcome this challenge, usually two straightforward strategies have been considered: (1) reducing the band-gap of molecular donors to broaden the absorption range, which results in higher short circuit current density (JSC) of devices, and (2) lowering the highest occupied molecular orbital (HOMO) energy of molecular donors so as to increase the open-circuit voltage (VOC) of applications devices.8 Keeping in mind the cost of chemicals it is hard to try many materials on test basis. The best way is to find the suitable material in the bulk. For this purpose, we use computational approach to design molecules based on our organic chemistry knowledge and determine their physical and electronic properties. In this study, we did DFT calculations with different options to get high open circuit voltage and after getting suitable data from calculation we finally did synthesis of a novel D–π–A–π–D type low band-gap small molecular donor material (ZOPTAN-TPA). The Aarylene vinylene based bis(arylhalide) unit containing a cyanostilbene unit acts as a low-band- gap electron-accepting block, and is coupled with triphenylamine as electron-donating blocks groups. The motivation for choosing triphenylamine (TPA) as capped donor was attributed to its important role in stabilizing the separated hole from an exciton and thus improving the hole-transporting properties of the hole carrier.3 A π-bridge (thiophene) is inserted between the donor and acceptor unit to reduce the steric hindrance between the donor and acceptor units and to improve the planarity of the molecule. The ZOPTAN-TPA molecule features a low HOMO level of 5.2 eV and an optical energy gap of 2.1 eV. Champion OSCs based on a solution-processed and non-annealed active-material blend of [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) and ZOPTAN-TPA in a mass ratio of 2:1 exhibits a power conversion efficiency of 1.9 % and a high open-circuit voltage of over 1.0 V.

Keywords: high open circuit voltage, donor, triphenylamine, organic solar cells

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370 Superparamagnetic Core Shell Catalysts for the Environmental Production of Fuels from Renewable Lignin

Authors: Cristina Opris, Bogdan Cojocaru, Madalina Tudorache, Simona M. Coman, Vasile I. Parvulescu, Camelia Bala, Bahir Duraki, Jeroen A. Van Bokhoven

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The tremendous achievements in the development of the society concretized by more sophisticated materials and systems are merely based on non-renewable resources. Consequently, after more than two centuries of intensive development, among others, we are faced with the decrease of the fossil fuel reserves, an increased impact of the greenhouse gases on the environment, and economic effects caused by the fluctuations in oil and mineral resource prices. The use of biomass may solve part of these problems, and recent analyses demonstrated that from the perspective of the reduction of the emissions of carbon dioxide, its valorization may bring important advantages conditioned by the usage of genetic modified fast growing trees or wastes, as primary sources. In this context, the abundance and complex structure of lignin may offer various possibilities of exploitation. However, its transformation in fuels or chemicals supposes a complex chemistry involving the cleavage of C-O and C-C bonds and altering of the functional groups. Chemistry offered various solutions in this sense. However, despite the intense work, there are still many drawbacks limiting the industrial application. Thus, the proposed technologies considered mainly homogeneous catalysts meaning expensive noble metals based systems that are hard to be recovered at the end of the reaction. Also, the reactions were carried out in organic solvents that are not acceptable today from the environmental point of view. To avoid these problems, the concept of this work was to investigate the synthesis of superparamagnetic core shell catalysts for the fragmentation of lignin directly in the aqueous phase. The magnetic nanoparticles were covered with a nanoshell of an oxide (niobia) with a double role: to protect the magnetic nanoparticles and to generate a proper (acidic) catalytic function and, on this composite, cobalt nanoparticles were deposed in order to catalyze the C-C bond splitting. With this purpose, we developed a protocol to prepare multifunctional and magnetic separable nano-composite Co@Nb2O5@Fe3O4 catalysts. We have also established an analytic protocol for the identification and quantification of the fragments resulted from lignin depolymerization in both liquid and solid phase. The fragmentation of various lignins occurred on the prepared materials in high yields and with very good selectivity in the desired fragments. The optimization of the catalyst composition indicated a cobalt loading of 4wt% as optimal. Working at 180 oC and 10 atm H2 this catalyst allowed a conversion of lignin up to 60% leading to a mixture containing over 96% in C20-C28 and C29-C37 fragments that were then completely fragmented to C12-C16 in a second stage. The investigated catalysts were completely recyclable, and no leaching of the elements included in the composition was determined by inductively coupled plasma optical emission spectrometry (ICP-OES).

Keywords: superparamagnetic core-shell catalysts, environmental production of fuels, renewable lignin, recyclable catalysts

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369 Open Source Cloud Managed Enterprise WiFi

Authors: James Skon, Irina Beshentseva, Michelle Polak

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Wifi solutions come in two major classes. Small Office/Home Office (SOHO) WiFi, characterized by inexpensive WiFi routers, with one or two service set identifiers (SSIDs), and a single shared passphrase. These access points provide no significant user management or monitoring, and no aggregation of monitoring and control for multiple routers. The other solution class is managed enterprise WiFi solutions, which involve expensive Access Points (APs), along with (also costly) local or cloud based management components. These solutions typically provide portal based login, per user virtual local area networks (VLANs), and sophisticated monitoring and control across a large group of APs. The cost for deploying and managing such managed enterprise solutions is typically about 10 fold that of inexpensive consumer APs. Low revenue organizations, such as schools, non-profits, non-government organizations (NGO's), small businesses, and even homes cannot easily afford quality enterprise WiFi solutions, though they may need to provide quality WiFi access to their population. Using available lower cost Wifi solutions can significantly reduce their ability to provide reliable, secure network access. This project explored and created a new approach for providing secured managed enterprise WiFi based on low cost hardware combined with both new and existing (but modified) open source software. The solution provides a cloud based management interface which allows organizations to aggregate the configuration and management of small, medium and large WiFi solutions. It utilizes a novel approach for user management, giving each user a unique passphrase. It provides unlimited SSID's across an unlimited number of WiFI zones, and the ability to place each user (and all their devices) on their own VLAN. With proper configuration it can even provide user local services. It also allows for users' usage and quality of service to be monitored, and for users to be added, enabled, and disabled at will. As inferred above, the ultimate goal is to free organizations with limited resources from the expense of a commercial enterprise WiFi, while providing them with most of the qualities of such a more expensive managed solution at a fraction of the cost.

Keywords: wifi, enterprise, cloud, managed

Procedia PDF Downloads 73
368 Development of Biosensor Chip for Detection of Specific Antibodies to HSV-1

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 407
367 Smart Defect Detection in XLPE Cables Using Convolutional Neural Networks

Authors: Tesfaye Mengistu

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Power cables play a crucial role in the transmission and distribution of electrical energy. As the electricity generation, transmission, distribution, and storage systems become smarter, there is a growing emphasis on incorporating intelligent approaches to ensure the reliability of power cables. Various types of electrical cables are employed for transmitting and distributing electrical energy, with cross-linked polyethylene (XLPE) cables being widely utilized due to their exceptional electrical and mechanical properties. However, insulation defects can occur in XLPE cables due to subpar manufacturing techniques during production and cable joint installation. To address this issue, experts have proposed different methods for monitoring XLPE cables. Some suggest the use of interdigital capacitive (IDC) technology for online monitoring, while others propose employing continuous wave (CW) terahertz (THz) imaging systems to detect internal defects in XLPE plates used for power cable insulation. In this study, we have developed models that employ a custom dataset collected locally to classify the physical safety status of individual power cables. Our models aim to replace physical inspections with computer vision and image processing techniques to classify defective power cables from non-defective ones. The implementation of our project utilized the Python programming language along with the TensorFlow package and a convolutional neural network (CNN). The CNN-based algorithm was specifically chosen for power cable defect classification. The results of our project demonstrate the effectiveness of CNNs in accurately classifying power cable defects. We recommend the utilization of similar or additional datasets to further enhance and refine our models. Additionally, we believe that our models could be used to develop methodologies for detecting power cable defects from live video feeds. We firmly believe that our work makes a significant contribution to the field of power cable inspection and maintenance. Our models offer a more efficient and cost-effective approach to detecting power cable defects, thereby improving the reliability and safety of power grids.

Keywords: artificial intelligence, computer vision, defect detection, convolutional neural net

Procedia PDF Downloads 89
366 Estimation of Forces Applied to Forearm Using EMG Signal Features to Control of Powered Human Arm Prostheses

Authors: Faruk Ortes, Derya Karabulut, Yunus Ziya Arslan

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Myoelectric features gathering from musculature environment are considered on a preferential basis to perceive muscle activation and control human arm prostheses according to recent experimental researches. EMG (electromyography) signal based human arm prostheses have shown a promising performance in terms of providing basic functional requirements of motions for the amputated people in recent years. However, these assistive devices for neurorehabilitation still have important limitations in enabling amputated people to perform rather sophisticated or functional movements. Surface electromyogram (EMG) is used as the control signal to command such devices. This kind of control consists of activating a motion in prosthetic arm using muscle activation for the same particular motion. Extraction of clear and certain neural information from EMG signals plays a major role especially in fine control of hand prosthesis movements. Many signal processing methods have been utilized for feature extraction from EMG signals. The specific objective of this study was to compare widely used time domain features of EMG signal including integrated EMG(IEMG), root mean square (RMS) and waveform length(WL) for prediction of externally applied forces to human hands. Obtained features were classified using artificial neural networks (ANN) to predict the forces. EMG signals supplied to process were recorded during only type of muscle contraction which is isometric and isotonic one. Experiments were performed by three healthy subjects who are right-handed and in a range of 25-35 year-old aging. EMG signals were collected from muscles of the proximal part of the upper body consisting of: biceps brachii, triceps brachii, pectorialis major and trapezius. The force prediction results obtained from the ANN were statistically analyzed and merits and pitfalls of the extracted features were discussed with detail. The obtained results are anticipated to contribute classification process of EMG signal and motion control of powered human arm prosthetics control.

Keywords: assistive devices for neurorehabilitation, electromyography, feature extraction, force estimation, human arm prosthesis

Procedia PDF Downloads 350
365 The Gezi Park Protests in the Columns

Authors: Süleyman Hakan Yilmaz, Yasemin Gülsen Yilmaz

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The Gezi Park protests of 2013 have significantly changed the Turkish agenda and its effects have been felt historically. The protests, which rapidly spread throughout the country, were triggered by the proposal to recreate the Ottoman Army Barracks to function as a shopping mall on Gezi Park located in Istanbul’s Taksim neighbourhood despite the oppositions of several NGOs and when trees were cut in the park for this purpose. Once the news that construction vehicles entered the park on May 27 spread on social media, activists moved into the park to stop the demolition, against whom the police used disproportioned force. With this police intervention and the then prime-minister Tayyip Erdoğan's insistent statements about the construction plans, the protests turned into anti-government demonstrations, which then spread to the rest of the country, mainly in big cities like Ankara and Izmir. According to the Ministry of Internal Affairs’ June 23rd reports, 2.5 million people joined the demonstrations in 79 provinces, that is all of them, except for the provinces of Bayburt and Bingöl, while even more people shared their opinions via social networks. As a result of these events, 8 civilians and 2 security personnel lost their lives, namely police chief Mustafa Sarı, police officer Ahmet Küçükdağ, citizens Mehmet Ayvalıtaş, Abdullah Cömert, Ethem Sarısülük, Ali İsmail Korkmaz, Ahmet Atakan, Berkin Elvan, Burak Can Karamanoğlu, Mehmet İstif, and Elif Çermik, and 8163 more were injured. Besides being a turning point in Turkish history, the Gezi Park protests also had broad repercussions in both in Turkish and in global media, which focused on Turkey throughout the events. Our study conducts content analysis of three Turkish reporting newspapers with varying ideological standpoints, Hürriyet, Cumhuriyet ve Yeni Şafak, in order to reveal their basic approach to columns casting in context of the Gezi Park protests. Columns content relating to the Gezi protests were treated and analysed for this purpose. The aim of this study is to understand the social effects of the Gezi Park protests through media samples with varying political attitudes towards news casting.

Keywords: Gezi Park, media, news casting, columns

Procedia PDF Downloads 413
364 A POX Controller Module to Collect Web Traffic Statistics in SDN Environment

Authors: Wisam H. Muragaa, Kamaruzzaman Seman, Mohd Fadzli Marhusin

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Software Defined Networking (SDN) is a new norm of networks. It is designed to facilitate the way of managing, measuring, debugging and controlling the network dynamically, and to make it suitable for the modern applications. Generally, measurement methods can be divided into two categories: Active and passive methods. Active measurement method is employed to inject test packets into the network in order to monitor their behaviour (ping tool as an example). Meanwhile the passive measurement method is used to monitor the traffic for the purpose of deriving measurement values. The measurement methods, both active and passive, are useful for the collection of traffic statistics, and monitoring of the network traffic. Although there has been a work focusing on measuring traffic statistics in SDN environment, it was only meant for measuring packets and bytes rates for non-web traffic. In this study, a feasible method will be designed to measure the number of packets and bytes in a certain time, and facilitate obtaining statistics for both web traffic and non-web traffic. Web traffic refers to HTTP requests that use application layer; while non-web traffic refers to ICMP and TCP requests. Thus, this work is going to be more comprehensive than previous works. With a developed module on POX OpenFlow controller, information will be collected from each active flow in the OpenFlow switch, and presented on Command Line Interface (CLI) and wireshark interface. Obviously, statistics that will be displayed on CLI and on wireshark interfaces include type of protocol, number of bytes and number of packets, among others. Besides, this module will show the number of flows added to the switch whenever traffic is generated from and to hosts in the same statistics list. In order to carry out this work effectively, our Python module will send a statistics request message to the switch requesting its current ports and flows statistics in every five seconds; while the switch will reply with the required information in a message called statistics reply message. Thus, POX controller will be notified and updated with any changes could happen in the entire network in a very short time. Therefore, our aim of this study is to prepare a list for the important statistics elements that are collected from the whole network, to be used for any further researches; particularly, those that are dealing with the detection of the network attacks that cause a sudden rise in the number of packets and bytes like Distributed Denial of Service (DDoS).

Keywords: mininet, OpenFlow, POX controller, SDN

Procedia PDF Downloads 214
363 The Comparative Study of Attitudes toward Entrepreneurial Intention between ASEAN and Europe: An Analysis Using GEM Data

Authors: Suchart Tripopsakul

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This paper uses data from the Global Entrepreneurship Monitor (GEM) to investigate the difference of attitudes towards entrepreneurial intention (EI). EI is generally assumed to be the single most relevant predictor of entrepreneurial behavior. The aim of this paper is to examine a range of attitudes effect on individual’s intent to start a new venture. A cross-cultural comparison between Asia and Europe is used to further investigate the possible differences between potential entrepreneurs from these distinct national contexts. The empirical analysis includes a GEM data set of 10 countries (n = 10,306) which was collected in 2013. Logistic regression is used to investigate the effect of individual’s attitudes on EI. Independent variables include individual’s perceived capabilities, the ability to recognize business opportunities, entrepreneurial network, risk perceptions as well as a range of socio-cultural attitudes. Moreover, a cross-cultural comparison of the model is conducted including six ASEAN (Malaysia, Indonesia, Philippines, Singapore, Vietnam and Thailand) and four European nations (Spain, Sweden, Germany, and the United Kingdom). The findings support the relationship between individual’s attitudes and their entrepreneurial intention. Individual’s capability, opportunity recognition, networks and a range of socio-cultural perceptions all influence EI significantly. The impact of media attention on entrepreneurship and was found to influence EI in ASEAN, but not in Europe. On the one hand, Fear of failure was found to influence EI in Europe, but not in ASEAN. The paper develops and empirically tests attitudes toward Entrepreneurial Intention between ASEAN and Europe. Interestingly, fear of failure was found to have no significant effect in ASEAN, and the impact of media attention on entrepreneurship and was found to influence EI in ASEAN. Moreover, the resistance of ASEAN entrepreneurs to the otherwise high rates of fear of failure and high impact of media attention are proposed as independent variables to explain the relatively high rates of entrepreneurial activity in ASEAN as reported by GEM. The paper utilizes a representative sample of 10,306 individuals in 10 countries. A range of attitudes was found to significantly influence entrepreneurial intention. Many of these perceptions, such as the impact of media attention on entrepreneurship can be manipulated by government policy. The paper also suggests strategies by which Asian economy in particular can benefit from their apparent high impact of media attention on entrepreneurship.

Keywords: an entrepreneurial intention, attitude, GEM, ASEAN and Europe

Procedia PDF Downloads 285
362 A Survey Proposal towards Holistic Management of Schizophrenia

Authors: Pronab Ganguly, Ahmed A. Moustafa

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Holistic management of schizophrenia involves mainstream pharmacological intervention, complimentary medicine intervention, therapeutic intervention and other psychosocial factors such as accommodation, education, job training, employment, relationship, friendship, exercise, overall well-being, smoking, substance abuse, suicide prevention, stigmatisation, recreation, entertainment, violent behaviour, arrangement of public trusteeship and guardianship, day-day-living skill, integration with community, and management of overweight due to medications and other health complications related to medications amongst others. Our review shows that there is no integrated survey by combining all these factors. An international web-based survey was conducted to evaluate the significance of all these factors and present them in a unified manner. It is believed this investigation will contribute positively towards holistic management of schizophrenia. There will be two surveys. In the pharmacological intervention survey, five popular drugs for schizophrenia will be chosen and their efficacy as well as harmful side effects will be evaluated on a scale of 0 -10. This survey will be done by psychiatrists. In the second survey, each element of therapeutic intervention and psychosocial factors will be evaluated according to their significance on a scale of 0 - 10. This survey will be done by care givers, psychologists, case managers and case workers. For the first survey, professional bodies of psychiatrists in English speaking countries will be contacted to request them to ask their members to participate in the survey. For the second survey, professional bodies of clinical psychologist and care givers in English speaking countries will be contacted to request them to ask their members to participate in the survey. Additionally, for both the surveys, relevant professionals will be contacted through personal contact networks. For both the surveys, mean, mode, median, standard deviation and net promoter score will be calculated for each factor and then presented in a statistically significant manner. Subsequently each factor will be ranked according to their statistical significance. Additionally, country specific variation will be highlighted to identify the variation pattern. The results of these surveys will identify the relative significance of each type of pharmacological intervention, each type of therapeutic intervention and each type of psychosocial factor. The determination of this relative importance will definitely contribute to the improvement in quality of life for individuals with schizophrenia.

Keywords: schizophrenia, holistic management, antipsychotics, quality of life

Procedia PDF Downloads 128
361 Digital Immunity System for Healthcare Data Security

Authors: Nihar Bheda

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Protecting digital assets such as networks, systems, and data from advanced cyber threats is the aim of Digital Immunity Systems (DIS), which are a subset of cybersecurity. With features like continuous monitoring, coordinated reactions, and long-term adaptation, DIS seeks to mimic biological immunity. This minimizes downtime by automatically identifying and eliminating threats. Traditional security measures, such as firewalls and antivirus software, are insufficient for enterprises, such as healthcare providers, given the rapid evolution of cyber threats. The number of medical record breaches that have occurred in recent years is proof that attackers are finding healthcare data to be an increasingly valuable target. However, obstacles to enhancing security include outdated systems, financial limitations, and a lack of knowledge. DIS is an advancement in cyber defenses designed specifically for healthcare settings. Protection akin to an "immune system" is produced by core capabilities such as anomaly detection, access controls, and policy enforcement. Coordination of responses across IT infrastructure to contain attacks is made possible by automation and orchestration. Massive amounts of data are analyzed by AI and machine learning to find new threats. After an incident, self-healing enables services to resume quickly. The implementation of DIS is consistent with the healthcare industry's urgent requirement for resilient data security in light of evolving risks and strict guidelines. With resilient systems, it can help organizations lower business risk, minimize the effects of breaches, and preserve patient care continuity. DIS will be essential for protecting a variety of environments, including cloud computing and the Internet of medical devices, as healthcare providers quickly adopt new technologies. DIS lowers traditional security overhead for IT departments and offers automated protection, even though it requires an initial investment. In the near future, DIS may prove to be essential for small clinics, blood banks, imaging centers, large hospitals, and other healthcare organizations. Cyber resilience can become attainable for the whole healthcare ecosystem with customized DIS implementations.

Keywords: digital immunity system, cybersecurity, healthcare data, emerging technology

Procedia PDF Downloads 52
360 Research on Quality Assurance in African Higher Education: A Bibliometric Mapping from 1999 to 2019

Authors: Luís M. João, Patrício Langa

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The article reviews the literature on quality assurance (QA) in African higher education studies (HES) conducted through a bibliometric mapping of published papers between 1999 and 2019. Specifically, the article highlights the nuances of knowledge production in four scientific databases: Scopus, Web of Science (WoS), African Journal Online (AJOL), and Google Scholar. The analysis included 531 papers, of which 127 are from Scopus, 30 are from Web of Science, 85 are from African Journal Online, and 259 are from Google Scholar. In essence, 284 authors wrote these papers from 231 institutions and 69 different countries (i.e., Africa=54 and outside Africa=15). Results indicate the existing knowledge. This analysis allows the readers to understand the growth and development of the field during the two-decade period, identify key contributors, and observe potential trends or gaps in the research. The paper employs bibliometric mapping as its primary analytical lens. By utilizing this method, the study quantitatively assesses the publications related to QA in African HES, helping to identify patterns, collaboration networks, and disparities in research output. The bibliometric approach allows for a systematic and objective analysis of large datasets, offering a comprehensive view of the knowledge production in the field. Furthermore, the study highlights the lack of shared resources available to enhance quality in higher education institutions (HEIs) in Africa. This finding underscores the importance of promoting collaborative research efforts, knowledge exchange, and capacity building within the region to improve the overall quality of higher education. The paper argues that despite the growing quantity of QA research in African higher education, there are challenges related to citation impact and access to high-impact publication avenues for African researchers. It emphasises the need to promote collaborative research and resource-sharing to enhance the quality of HEIs in Africa. The analytical lenses of bibliometric mapping and the examination of publication players' scenarios contribute to a comprehensive understanding of the field and its implications for African higher education.

Keywords: Africa, bibliometric research, higher education studies, quality assurance, scientific database, systematic review

Procedia PDF Downloads 31
359 Monitoring of Formaldehyde over Punjab Pakistan Using Car Max-Doas and Satellite Observation

Authors: Waqas Ahmed Khan, Faheem Khokhaar

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Air pollution is one of the main perpetrators of climate change. GHGs cause melting of glaciers and cause change in temperature and heavy rain fall many gasses like Formaldehyde is not direct precursor that damage ozone like CO2 or Methane but Formaldehyde (HCHO) form glyoxal (CHOCHO) that has effect on ozone. Countries around the globe have unique air quality monitoring protocols to describe local air pollution. Formaldehyde is a colorless, flammable, strong-smelling chemical that is used in building materials and to produce many household products and medical preservatives. Formaldehyde also occurs naturally in the environment. It is produced in small amounts by most living organisms as part of normal metabolic processes. Pakistan lacks the monitoring facilities on larger scale to measure the atmospheric gasses on regular bases. Formaldehyde is formed from Glyoxal and effect mountain biodiversity and livelihood. So its monitoring is necessary in order to maintain and preserve biodiversity. Objective: Present study is aimed to measure atmospheric HCHO vertical column densities (VCDs) obtained from ground-base and compute HCHO data in Punjab and elevated areas (Rawalpindi & Islamabad) by satellite observation during the time period of 2014-2015. Methodology: In order to explore the spatial distributing of H2CO, various fields campaigns including international scientist by using car Max-Doas. Major focus was on the cities along national highways and industrial region of Punjab Pakistan. Level 2 data product of satellite instruments OMI retrieved by differential optical absorption spectroscopy (DOAS) technique are used. Spatio-temporal distribution of HCHO column densities over main cities and region of Pakistan has been discussed. Results: Results show the High HCHO column densities exceeding permissible limit over the main cities of Pakistan particularly the areas with rapid urbanization and enhanced economic growth. The VCDs value over elevated areas of Pakistan like Islamabad, Rawalpindi is around 1.0×1016 to 34.01×1016 Molecules’/cm2. While Punjab has values revolving around the figure 34.01×1016. Similarly areas with major industrial activity showed high amount of HCHO concentrations. Tropospheric glyoxal VCDs were found to be 4.75 × 1015 molecules/cm2. Conclusion: Results shows that monitoring site surrounded by Margalla hills (Islamabad) have higher concentrations of Formaldehyde. Wind data shows that industrial areas and areas having high economic growth have high values as they provide pathways for transmission of HCHO. Results obtained from this study would help EPA, WHO and air protection departments in order to monitor air quality and further preservation and restoration of mountain biodiversity.

Keywords: air quality, formaldehyde, Max-Doas, vertical column densities (VCDs), satellite instrument, climate change

Procedia PDF Downloads 196
358 Object-Scene: Deep Convolutional Representation for Scene Classification

Authors: Yanjun Chen, Chuanping Hu, Jie Shao, Lin Mei, Chongyang Zhang

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Traditional image classification is based on encoding scheme (e.g. Fisher Vector, Vector of Locally Aggregated Descriptor) with low-level image features (e.g. SIFT, HoG). Compared to these low-level local features, deep convolutional features obtained at the mid-level layer of convolutional neural networks (CNN) have richer information but lack of geometric invariance. For scene classification, there are scattered objects with different size, category, layout, number and so on. It is crucial to find the distinctive objects in scene as well as their co-occurrence relationship. In this paper, we propose a method to take advantage of both deep convolutional features and the traditional encoding scheme while taking object-centric and scene-centric information into consideration. First, to exploit the object-centric and scene-centric information, two CNNs that trained on ImageNet and Places dataset separately are used as the pre-trained models to extract deep convolutional features at multiple scales. This produces dense local activations. By analyzing the performance of different CNNs at multiple scales, it is found that each CNN works better in different scale ranges. A scale-wise CNN adaption is reasonable since objects in scene are at its own specific scale. Second, a fisher kernel is applied to aggregate a global representation at each scale and then to merge into a single vector by using a post-processing method called scale-wise normalization. The essence of Fisher Vector lies on the accumulation of the first and second order differences. Hence, the scale-wise normalization followed by average pooling would balance the influence of each scale since different amount of features are extracted. Third, the Fisher vector representation based on the deep convolutional features is followed by a linear Supported Vector Machine, which is a simple yet efficient way to classify the scene categories. Experimental results show that the scale-specific feature extraction and normalization with CNNs trained on object-centric and scene-centric datasets can boost the results from 74.03% up to 79.43% on MIT Indoor67 when only two scales are used (compared to results at single scale). The result is comparable to state-of-art performance which proves that the representation can be applied to other visual recognition tasks.

Keywords: deep convolutional features, Fisher Vector, multiple scales, scale-specific normalization

Procedia PDF Downloads 314
357 Statistical Pattern Recognition for Biotechnological Process Characterization Based on High Resolution Mass Spectrometry

Authors: S. Fröhlich, M. Herold, M. Allmer

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Early stage quantitative analysis of host cell protein (HCP) variations is challenging yet necessary for comprehensive bioprocess development. High resolution mass spectrometry (HRMS) provides a high-end technology for accurate identification alongside with quantitative information. Hereby we describe a flexible HRMS assay platform to quantify HCPs relevant in microbial expression systems such as E. Coli in both up and downstream development by means of MVDA tools. Cell pellets were lysed and proteins extracted, purified samples not further treated before applying the SMART tryptic digest kit. Peptides separation was optimized using an RP-UHPLC separation platform. HRMS-MSMS analysis was conducted on an Orbitrap Velos Elite applying CID. Quantification was performed label-free taking into account ionization properties and physicochemical peptide similarities. Results were analyzed using SIEVE 2.0 (Thermo Fisher Scientific) and SIMCA (Umetrics AG). The developed HRMS platform was applied to an E. Coli expression set with varying productivity and the corresponding downstream process. Selected HCPs were successfully quantified within the fmol range. Analysing HCP networks based on pattern analysis facilitated low level quantification and enhanced validity. This approach is of high relevance for high-throughput screening experiments during upstream development, e.g. for titer determination, dynamic HCP network analysis or product characterization. Considering the downstream purification process, physicochemical clustering of identified HCPs is of relevance to adjust buffer conditions accordingly. However, the technology provides an innovative approach for label-free MS based quantification relying on statistical pattern analysis and comparison. Absolute quantification based on physicochemical properties and peptide similarity score provides a technological approach without the need of sophisticated sample preparation strategies and is therefore proven to be straightforward, sensitive and highly reproducible in terms of product characterization.

Keywords: process analytical technology, mass spectrometry, process characterization, MVDA, pattern recognition

Procedia PDF Downloads 234
356 Hybrid Strategies of Crisis Intervention for Sexualized Violence Using Digital Media

Authors: Katharina Kargel, Frederic Vobbe

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Sexualized violence against children and adolescents using digital media poses particular challenges for practitioners with a focus on crisis intervention (social work, psychotherapy, law enforcement). The technical delimitation of violence increases the burden on those affected and increases the complexity of interdisciplinary cooperation. Urgently needed recommendations for practical action do not yet exist in Germany. Funded by the Federal Ministry of Education and Research, these recommendations for action are being developed in the HUMAN project together with science and practice. The presentation introduces the participatory approach of the HUMAN project. We discuss the application-oriented, casuistic approach of the project and present its results using the example of concrete case-based recommendations for Action. The participants will be presented with concrete prototypical case studies from the project, which will be used to illustrate quality criteria for crisis intervention in cases of sexualized violence using digital media. On the basis of case analyses, focus group interviews and interviews with victims of violence, we present the six central challenges of sexualized violence with the use of digital media, namely: • Diffusion (Ambiguities regarding the extent and significance of violence) , • Transcendence (Space and time independence of the dynamics of violence, omnipresence), • omnipresent anxiety (considering diffusion and transcendence), • being haunted (repeated confrontation with digital memories of violence or the perpetrator), • disparity (conflicts of interpretative power between those affected and the social environment) • simultaneity (of all other factors). We point out generalizable principles with which these challenges can be dealt with professionally. Dealing professionally with sexualized violence using digital media requires a stronger networking of professional actors. A clear distinction must be made between their own mission and the mission of the network partners. Those affected by violence must be shown options for crisis intervention in the context of the aid networks. The different competencies and the professional mission of the offers of help are to be made transparent. The necessity of technical possibilities for deleting abuse images beyond criminal prosecution will be discussed. Those affected are stabilized by multimodal strategies such as a combination of rational emotive therapy, legal support and technical assistance.

Keywords: sexualized violence, intervention, digital media, children and youth

Procedia PDF Downloads 213
355 Single and Sequential Extraction for Potassium Fractionation and Nano-Clay Flocculation Structure

Authors: Chakkrit Poonpakdee, Jing-Hua Tzen, Ya-Zhen Huang, Yao-Tung Lin

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Potassium (K) is a known macro nutrient and essential element for plant growth. Single leaching and modified sequential extraction schemes have been developed to estimate the relative phase associations of soil samples. The sequential extraction process is a step in analyzing the partitioning of metals affected by environmental conditions, but it is not a tool for estimation of K bioavailability. While, traditional single leaching method has been used to classify K speciation for a long time, it depend on its availability to the plants and use for potash fertilizer recommendation rate. Clay mineral in soil is a factor for controlling soil fertility. The change of the micro-structure of clay minerals during various environment (i.e. swelling or shrinking) is characterized using Transmission X-Ray Microscopy (TXM). The objective of this study are to 1) compare the distribution of K speciation between single leaching and sequential extraction process 2) determined clay particle flocculation structure before/after suspension with K+ using TXM. Four tropical soil samples: farming without K fertilizer (10 years), long term applied K fertilizer (10 years; 168-240 kg K2O ha-1 year-1), red soil (450-500 kg K2O ha-1 year-1) and forest soil were selected. The results showed that the amount of K speciation by single leaching method were high in mineral K, HNO3 K, Non-exchangeable K, NH4OAc K, exchangeable K and water soluble K respectively. Sequential extraction process indicated that most K speciations in soil were associated with residual, organic matter, Fe or Mn oxide and exchangeable fractions and K associate fraction with carbonate was not detected in tropical soil samples. In farming long term applied K fertilizer and red soil were higher exchangeable K than farming long term without K fertilizer and forest soil. The results indicated that one way to increase the available K (water soluble K and exchangeable K) should apply K fertilizer and organic fertilizer for providing available K. The two-dimension of TXM image of clay particles suspension with K+ shows that the aggregation structure of clay mineral closed-void cellular networks. The porous cellular structure of soil aggregates in 1 M KCl solution had large and very larger empty voids than in 0.025 M KCl and deionized water respectively. TXM nanotomography is a new technique can be useful in the field as a tool for better understanding of clay mineral micro-structure.

Keywords: potassium, sequential extraction process, clay mineral, TXM

Procedia PDF Downloads 269
354 Mechanism of Action of New Sustainable Flame Retardant Additives in Polyamide 6,6

Authors: I. Belyamani, M. K. Hassan, J. U. Otaigbe, W. R. Fielding, K. A. Mauritz, J. S. Wiggins, W. L. Jarrett

Abstract:

We have investigated the flame-retardant efficiency of special new phosphate glass (P-glass) compositions having different glass transition temperatures (Tg) on the processing conditions of polyamide 6,6 (PA6,6) and the final hybrid flame retardancy (FR). We have showed that the low Tg P glass composition (i.e., ILT 1) is a promising flame retardant for PA6,6 at a concentration of up to 15 wt. % compared to intermediate (IIT 3) and high (IHT 1) Tg P glasses. Cone calorimetry data showed that the ILT 1 decreased both the peak heat release rate and the total heat amount released from the PA6,6/ILT 1 hybrids, resulting in an efficient formation of a glassy char layer. These intriguing findings prompted to address several questions concerning the mechanism of action of the different P glasses studied. The general mechanism of action of phosphorous based FR additives occurs during the combustion stage by enhancing the morphology of the char and the thermal shielding effect. However, the present work shows that P glass based FR additives act during melt processing of PA6,6/P glass hybrids. Dynamic mechanical analysis (DMA) revealed that the Tg of PA6,6/ILT 1 was significantly shifted to a lower Tg (~65 oC) and another transition appeared at high temperature (~ 166 oC), thus indicating a strong interaction between PA6,6 and ILT 1. This was supported by a drop in the melting point and crystallinity of the PA6,6/ILT 1 hybrid material as detected by differential scanning calorimetry (DSC). The dielectric spectroscopic investigation of the networks’ molecular level structural variations (i.e. hybrids chain motion, Tg and sub-Tg relaxations) agreed very well with the DMA and DSC findings; it was found that the three different P glass compositions did not show any effect on the PA6,6 sub-Tg relaxations (related to the NH2 and OH chain end groups motions). Nevertheless, contrary to IIT 3 and IHT 1 based hybrids, the PA6,6/ILT 1 hybrid material showed an evidence of splitting the PA6,6 Tg relaxations into two peaks. Finally, the CPMAS 31P-NMR data confirmed the miscibility between ILT 1 and PA6,6 at the molecular level, as a much larger enhancement in cross-polarization for the PA6,6/15%ILT 1 hybrids was observed. It can be concluded that compounding low Tg P-glass (i.e. ILT 1) with PA6,6 facilitates hydrolytic chain scission of the PA6,6 macromolecules through a potential chemical interaction between phosphate and the alpha-Carbon of the amide bonds of the PA6,6, leading to better flame retardant properties.

Keywords: broadband dielectric spectroscopy, composites, flame retardant, polyamide, phosphate glass, sustainable

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