Search results for: feature extraction multispectral

Authors: Abdal-Hafeez Alhussein

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Artificial Intelligence (AI) has become a transformative force in the field of information technologies, reshaping how data is processed, analyzed, and utilized across various domains. This paper explores the multifaceted applications of AI within information technology, focusing on three key areas: automation, scalability, and data-driven decision-making. We delve into how AI-powered automation is optimizing operational efficiency in IT infrastructures, from automated network management to self-healing systems that reduce downtime and enhance performance. Scalability, another critical aspect, is addressed through AI’s role in cloud computing and distributed systems, enabling the seamless handling of increasing data loads and user demands. Additionally, the paper highlights the use of AI in cybersecurity, where real-time threat detection and adaptive response mechanisms significantly improve resilience against sophisticated cyberattacks. In the realm of data analytics, AI models—especially machine learning and natural language processing—are driving innovation by enabling more precise predictions, automated insights extraction, and enhanced user experiences. The paper concludes with a discussion on the ethical implications of AI in information technologies, underscoring the importance of transparency, fairness, and responsible AI use. It also offers insights into future trends, emphasizing the potential of AI to further revolutionize the IT landscape by integrating with emerging technologies like quantum computing and IoT.

Keywords: artificial intelligence, information technology, automation, scalability

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Authors: Sally Shepherd, Jessica Wong, David Read

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Traumatic brachiocephalic artery aneurysm is a rare injury that typically occurs as a result of a blunt chest injury. A 19-year-old female sustained a head-on, high speed motor vehicle crash into a tree. Upon release after 45 minutes of entrapment, she was tachycardic but normotensive, with a significant seatbelt sign across her chest and open deformed right thigh with weak pulses in bilateral lower limbs. A chest XR showed mild upper mediastinal widening. A CT trauma series plus gated CT chest revealed a grade 3a aortic arch transection with brachiocephalic pseudoaneurysm. Endovascular repair of the brachiocephalic artery was attempted post-presentation but was unsuccessful as the first stent migrated to the infrarenal abdominal aorta and the second stent across the brachiocephalic artery origin had a persistent leak at the base. She was transferred to Intensive Care for strict blood pressure control. She returned to theatre 5 hours later for a median sternotomy, aortic arch repair with an 8mm graft extraction, and excision of the innominate artery pseudoaneurysm. She had an uncomplicated post-operative recovery. This case highlights that brachiocephalic artery injury is a rare but potentially lethal injury as a result of blunt chest trauma. Safe management requires a combined Vascular and Cardiothoracic team approach, as stenting alone may be insufficient.

Keywords: blunt chest injury, Brachiocephalic aneurysm, innominate artery, trauma

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Authors: Thomas Okechukwu Onah, Onyekachi Marcel Egwuagu

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Zero-surface temperature, which controlled the cooling profile, was modeled and used to investigate the effect of process parameters on the hot-rolled steel plates. The parameters include impingement gaps of 40mm to 70mm; pipe diameters of 20mm to 45mm feeding jet nozzle with 30 holes of 8mm diameters each; and flow rates within 2.896x10-⁶m³/s and 3.13x10-⁵m³/s. The developed simulation model of the Zero-Surface Temperature, upon validation, showed 99% prediction accuracy with dimensional homogeneity established. The evaluated Zero-Surface temperature of Controlled Water Jet Impingement Steel plates showed a high cooling rate of 36.31 Celsius degree/sec at an optimal cooling nozzle diameter of 20mm, impingement gap of 70mm and a flow rate of 1.77x10-⁵m³/s resulting in Reynold's number 2758.586, in the turbulent regime was obtained. It was also deduced that as the nozzle diameter was increasing, the impingement gap was reducing. This achieved a faster rate of cooling to an optimum temperature of 300oC irrespective of the starting surface cooling temperature. The results additionally showed that with a tested-plate initial temperature of 550oC, a controlled cooling temperature of about 160oC produced a film and nucleated boiling heat extraction that was particularly beneficial at the end of controlled cooling and influenced the microstructural properties of the test plates.

Keywords: temperature, mechanistic-model, plates, impingements, dimensionless-numbers

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Authors: Abderrahim Cheriguene, Fatiha Arioui

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The experimental study focuses on the extraction of pectin, whey protein and gelatin, and the study of their functional properties. Microbiological, physicochemical and sensory approach integrated has been implanted to study the effect of the incorporation of these natural food additives in the matrix of a fermented milk type set yogurt, to study the stability of the product during the periods of fermentation and post-acidification over a period of 21 days at 4°C. Pectin was extracted in hot HCl solution. Thermo-precipitation was carried out to obtain the whey proteins while the gelatin was extracted by hydrolysis of the collagen from bovine ossein. The fermented milk was prepared by varying the concentration of the incorporated additives. The measures and controls carried performed periodically on fermented milk experimental tests were carried out: pH, acidity, viscosity, the enumeration of Streptococcus thermophilus, cohesiveness, adhesiveness, taste, aftertaste, whey exudation, and odor. It appears that the acidity, viscosity, and number of Streptococcus thermophilus increased with increasing concentration of additive added in the experimental tests. Indeed, it seems clear that the quality of fermented milk and storability is more improved than the incorporation rate is high. The products showed a better test and a firmer texture limiting the whey exudation.

Keywords: fermented milk, pectin, gelatin, whey proteins, functional properties, quality, conservation, valorization

Procedia PDF Downloads 136

Authors: Elham Allahmoradi, Bahman Allahmoradi, Ali Bonyadi Naeini

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Complex systems have many aspects. A variety of methods have been developed to analyze these systems. The most efficient of these methods should not only be simple, but also provide useful and comprehensive information about many aspects of the system. Matrix methods are considered the most commonly methods used to analyze and design systems. Each matrix method can examine a particular aspect of the system. If these methods are combined, managers can access to more comprehensive and broader information about the system. This study was conducted in four steps. In the first step, a process model of a real project has been extracted through IDEF3. In the second step, activity levels have been attained by writing a process model in the form of a design structure matrix (DSM) and sorting it through triangulation algorithm (TA). In the third step, sub-processes have been obtained by writing the process model in the form of an interface structure matrix (ISM) and clustering it through cluster identification algorithm (CIA). In the fourth step, a mixed model has been developed to provide a unified picture of the project structure through the simultaneous presentation of activities and sub-processes. Finally, the paper is completed with a conclusion.

Keywords: integrated definition for process description capture (IDEF3) method, design structure matrix (DSM), interface structure matrix (ism), mixed matrix model, activity level, sub-process

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Authors: Mohammad Abotalib, Hamid Alhamadi

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In Kuwait, electricity is generated from two primary sources that are heavy fuel combustion and natural gas combustion. As Kuwait relies mainly on petroleum-based products for electricity generation, identifying and understanding the environmental trade-off of such operations should be carefully investigated. The life cycle assessment (LCA) tool is applied to identify the potential environmental impact of electricity generation under three scenarios by considering the material flow in various stages involved, such as raw-material extraction, transportation, operations, and waste disposal. The three scenarios investigated represent current and futuristic electricity grid mixes. The analysis targets six environmental impact categories: (1) global warming potential (GWP), (2) acidification potential (AP), (3) water depletion (WD), (4) acidification potential (AP), (4) eutrophication potential (EP), (5) human health particulate matter (HHPM), and (6) smog air (SA) per one kWh of electricity generated. Results indicate that one kWh of electricity generated would have a GWP (881-1030) g CO₂-eq, mainly from the fuel combustion process, water depletion (0.07-0.1) m³ of water, about 68% from cooling processes, AP (15.3-17.9) g SO₂-eq, EP (0.12-0.14) g N eq., HHPA (1.13- 1.33)g PM₂.₅ eq., and SA (64.8-75.8) g O₃ eq. The variation in results depend on the scenario investigated. It can be observed from the analysis that introducing solar photovoltaic and wind to the electricity grid mix improves the performance of scenarios 2 and 3 where 15% of the electricity comes from renewables correspond to a further decrease in LCA results.

Keywords: energy, functional uni, global warming potential, life cycle assessment, energy, functional unit

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Authors: Sayanti Kar, Amitava Ghosh, Pritam Aitch, Gupinath Bhandari

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An extensive seasonal analysis of wastewater had been done from outfalls of river Ganga in Howrah, Hooghly, 24 PGS (N) District, West Bengal, India during 2017. The morphological parameters of Bitter gourd (Momordica charantia L.) were estimated under wastewater treatment. An approach to study the activity within the range of low molecular weight peptide 3-0.5 kDa were taken through its extraction and purification by ion exchange resin column, cation, and anion exchanger. HPLC analysis had been done for both in wastewater treated and untreated plants. The antioxidant activity by using DPPH and germination percentage in control and treated plants were also determined in relation to wastewater effect. The inhibition of growth and its parameters were maximum in pre-monsoon in comparing to post-monsoon and monsoon season. The study also helped to explore the effect of wastewater on the peptidome of Bitter gourd (Momordica charantia L.). Some of these low molecular weight peptide(s) (3-0.5 kDa) also inhibited during wastewater treatment. Expression of particular peptide(s) or absence of some peptide(s) in chromatogram indicated the adverse effects on plants which may be the indication of stressful condition. Pre monsoon waste water was found to create more impact than other two.

Keywords: bitter gourd (Momordica charantia l.), low molecular weight peptide, river ganga, waste water

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Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

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In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

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Authors: Maíra O. Palm, Cintia Marangoni, Ozair Souza, Noeli Sellin

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Wastes from a vegetal extracts industry (cocoa, oak, Guarana and mate) were characterized by particle size, proximate and ultimate analysis, lignocellulosic fractions, high heating value, thermal analysis (Thermogravimetric analysis – TGA, and Differential thermal analysis - DTA) and energy density to evaluate their potential as biomass in the form of briquettes for power generation. All wastes presented adequate particle sizes to briquettes production. The wastes showed high moisture content, requiring previous drying for use as briquettes. Cocoa and oak wastes had the highest volatile matter contents with maximum mass loss at 310 ºC and 450 ºC, respectively. The solvents used in the aroma extraction process influenced in the moisture content of the wastes, which was higher for mate due to water has been used as solvent. All wastes showed an insignificant loss mass after 565 °C, hence resulting in low ash content. High carbon and hydrogen contents and low sulfur and nitrogen contents were observed ensuring a low generation of sulfur and nitrous oxides. Mate and cocoa exhibited the highest carbon and lignin content, and high heating value. The dried wastes had high heating value, from 17.1 MJ/kg to 20.8 MJ/kg. The results indicate the energy potential of wastes for use as fuel in power generation.

Keywords: agro-industrial waste, biomass, briquettes, combustion

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Authors: Angela Fabris, Joerg Helbig

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Our paper deals with feature films set in Venice which focus on the influence of Italian life style on anglophone characters. Usually, these films emphasize the different cultures and mentalities of Italian and British (or American) people. More often than not, these encounters result in a profound change of the anglophone characters' attitude towards romance and sensuality. A case in point is David Lean's Summer Madness (UK 1955). This film recounts the love affair between the American tourist Jane Hudson (Katherine Hepburn) and the Venetian antique shop owner Renato de Rossi (Rossano Brazzi). Jane is a spinster in her mid-forties who longs for love and romance. The chance arrives when she meets Renato who feels attracted to her. Jane's immediate reaction, however, is to reject Renato's advances. What follows is a struggle between the strict morality of a puritan upbringing and the irresitable charm of Mediterranean temptations. Similar conflicts can be found in many other movies. Apart from Summer Madness we will discuss Aldo Lado's Chi l'ha vista morire? (It 1972), Nicolas Roeg's Don't Look Now (UK/It 1973) and Paul Schrader's The Comfort of Strangers (It/UK/USA 1990). Our paper raises the question whether or not these and other films present false stereotypes and chlichés. The paper is part of our large-scale research project which explores the history of erotic cinema in Italy and England.

Keywords: culture clash, erotic cinema, film, Venice

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Authors: Milagros Jaén-Vargas, Javier García Martínez, Karla Miriam Reyes Leiva, María Fernanda Trujillo-Guerrero, Francisco Fernandes, Sérgio Barroso Gonçalves, Miguel Tavares Silva, Daniel Simões Lopes, José Javier Serrano Olmedo

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Human Activity Recognition (HAR) is having a growing impact in creating new applications and is responsible for emerging new technologies. Also, the use of wearable sensors is an important key to exploring the human body's behavior when performing activities. Hence, the use of these dispositive is less invasive and the person is more comfortable. In this study, a database that includes three activities is used. The activities were acquired from inertial measurement unit sensors (IMU) and motion capture systems (MOCAP). The main objective is differentiating the performance from four Deep Learning (DL) models: Deep Neural Network (DNN), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and hybrid model Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM), when considering acceleration, velocity and position and evaluate if integrating the IMU acceleration to obtain velocity and position represent an increment in performance when it works as input to the DL models. Moreover, compared with the same type of data provided by the MOCAP system. Despite the acceleration data is cleaned when integrating, results show a minimal increase in accuracy for the integrated signals.

Keywords: HAR, IMU, MOCAP, acceleration, velocity, position, feature maps

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Authors: Mirjana Dragas, Marli Gonan Bozac, Morena Paulisic

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Corporate social responsibility (CSR) is a balance between strategic and financial goals of companies, as well as social needs. The integration of competitive strategy and CSR in food and beverage industry has allowed companies to find new sources of competitive advantage. The paper discusses the fact that socially responsible companies encourage co-operation with socially responsible suppliers in order to strengthen market competitiveness. In addition to the descriptive interpretation of the results obtained by a questionnaire, factor analysis was used, while principal components analysis was applied as a factor extraction method. The research results based on two multiple regression analyses show that: (1) selecting the CSR supplier explains a statistically significant part of the variance of the results on the scale of financial aspects of competitiveness (as much as 44.7% of the explained variance); and (2) selecting the CSR supplier is a significant predictor of non-financial aspects of competitiveness (explains 43.9% of the variance of the results on the scale of non-financial aspects of competitiveness). A successful competitive strategy must ultimately support the growth strategy. This implies an analytical approach to finding factors that influence competitiveness through socially sustainable solutions and satisfactory top management decisions.

Keywords: competitiveness, corporate social responsibility, food and beverage industry, supply chain decision making

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Authors: Reshmita Nath

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In this study, we investigate the spatiotemporal characteristics of drought in India and its impact on agriculture during the summer season (April to September). For our analysis, we have used Standardized Precipitation Evapotranspiration Index (SPEI) datasets between 1982 and 2012 at six-month timescale. Based on the criteria SPEI<-1 we obtain the vulnerability map and have found that the Humid subtropical Upper Middle Gangetic Plain (UMGP) region is highly drought prone with an occurrence frequency of 40-45%. This UMGP region contributes at least 18-20% of India’s annual cereal production. Not only the probability, but the region becomes more and more drought-prone in the recent decades. Moreover, the cereal production in the UMGP has experienced a gradual declining trend from 2000 onwards and this feature is consistent with the increase in drought affected areas from 20-25% to 50-60%, before and after 2000, respectively. The higher correlation coefficient (-0.69) between the changes in cereal production and drought affected areas confirms that at least 50% of the agricultural (cereal) losses is associated with drought. While analyzing the individual impact of precipitation and surface temperature anomalies on SPEI (6), we have found that in the UMGP region surface temperature plays the primary role in lowering of SPEI. The linkage is further confirmed by the correlation analysis between the SPEI (6) and surface temperature rise, which exhibits strong negative values in the UMGP region. Higher temperature might have caused more evaporation and drying, which therefore increases the area affected by drought in the recent decade.

Keywords: drought, agriculture, SPEI, Indo-Gangetic plain

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Authors: Rupinder Kaur, Parmjit S. Panesar, Ram S. Singh

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Whey is the lactose rich by-product of the dairy industry, having good amount of nutrient reservoir. Most abundant nutrients are lactose, soluble proteins, lipids and mineral salts. Disposing of whey by most of milk plants which do not have proper pre-treatment system is the major issue. As a result of which, there can be significant loss of potential food and energy source. Thus, whey has been explored as the substrate for the synthesis of different value added products such as enzymes. β-galactosidase is one of the important enzymes and has become the major focus of research due to its ability to catalyze both hydrolytic as well as transgalactosylation reaction simultaneously. The enzyme is widely used in dairy industry as it catalyzes the transformation of lactose to glucose and galactose, making it suitable for the lactose intolerant people. The enzyme is intracellular in both bacteria and yeast, whereas for molds, it has an extracellular location. The present work was carried to utilize the whey for the production of β-galactosidase enzyme using both yeast and fungal cultures. The yeast isolate Kluyveromyces marxianus WIG2 and various fungal strains have been used in the present study. Different disruption techniques have also been investigated for the extraction of the enzyme produced intracellularly from yeast cells. Among the different methods tested for the disruption of yeast cells, SDS-chloroform showed the maximum β-galactosidase activity. In case of the tested fungal cultures, Aureobasidium pullulans NCIM 1050, was observed to be the maximum extracellular enzyme producer.

Keywords: β-galactosidase, fungus, yeast, whey

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Authors: Svetlana Ignatjeva, Jelena Slesareva

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The aim of the study is development and adaptation of the method to analyze and quantify the indicators characterizing the relationship between a company and its employees. Diagnostics of such indicators is one of the most complex and actual issues in psychology of labour. The offered method is based on the questionnaire; its indicators reflect cognitive, affective and connotative components of socio-psychological attitude of employees to be as efficient as possible in their professional activities. This approach allows measure not only the selected factors but also such parameters as cognitive and behavioural dissonances. Adaptation of the questionnaire includes factor structure analysis and suitability analysis of phenomena indicators measured in terms of internal consistency of individual factors. Structural validity of the questionnaire was tested by exploratory factor analysis. Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Factor analysis allows reduce dimension of the phenomena moving from the indicators to aggregative indexes and latent variables. Aggregative indexes are obtained as the sum of relevant indicators followed by standardization. The coefficient Cronbach's Alpha was used to assess the reliability-consistency of the questionnaire items. The two-step cluster analysis in the space of allocated factors allows classify employees according to their attitude to work in the company. The results of psychometric testing indicate possibility of using the developed technique for the analysis of employees’ attitude towards their work in companies and development of recommendations on their optimization.

Keywords: involved in the organization, loyalty, organizations, method

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Authors: Sahar Heidary, Ramin Ghasemi Shayan

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The overall goal Monte Carlo N-atom radioactivity transference PC program (MCNP4C) was done for the regeneration of x-ray groups in diagnostic radiology and mammography. The electrons were transported till they slow down and stopover in the target. Both bremsstrahlung and characteristic x-ray creation were measured in this study. In this issue, the x-ray spectra forecast by several computational models recycled in the diagnostic radiology and mammography energy kind have been calculated by appraisal with dignified spectra and their outcome on the scheming of absorbed dose and effective dose (ED) told to the adult ORNL hermaphroditic phantom quantified. This comprises practical models (TASMIP and MASMIP), semi-practical models (X-rayb&m, X-raytbc, XCOMP, IPEM, Tucker et al., and Blough et al.), and Monte Carlo modeling (EGS4, ITS3.0, and MCNP4C). Images got consuming synchrotron radiation (SR) and both screen-film and the CR system were related with images of the similar trials attained with digital mammography equipment. In sight of the worthy feature of the effects gained, the CR system was used in two mammographic inspections with SR. For separately mammography unit, the capability acquiesced bilateral mediolateral oblique (MLO) and craniocaudal(CC) mammograms attained in a woman with fatty breasts and a woman with dense breasts. Referees planned the common groups and definite absences that managed to a choice to miscarry the part that formed the scientific imaginings.

Keywords: mammography, monte carlo, effective dose, radiology

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Authors: Monika Szymańska-Czerwińsk, Kinga Zaręba-Marchewka, Krzysztof Niemczuk

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Chlamydiaceae are Gram-negative bacteria distributed worldwide in animals and humans. One of them is Chlamydia gallinacea recently discovered. Available data show that C. gallinacea is dominant chlamydial agent found in poultry in European and Asian countries. The aim of the studies was screening of poultry flocks in order to evaluate frequency of C. gallinacea shedding and genetic diversity. Sampling was conducted in different regions of Poland in 2019-2020. Overall, 1466 cloacal/oral swabs were collected in duplicate from 146 apparently healthy poultry flocks including chickens, turkeys, ducks, geese and quails. Dry swabs were used for DNA extraction. DNA extracts were screened using a Chlamydiaceae 23S rRNA real-time PCR assay. To identify Chlamydia species, specific real-time PCR assays were performed. Furthermore, selected samples were used for sequencing based on ompA gene fragments and variable domains (VD1-2, VD3-4). In total, 10.3% of the tested flocks were Chlamydiaceae-positive (15/146 farms). The presence of Chlamydiaceae was confirmed mainly in chickens (13/92 farms) but also in turkey (1/19 farms) and goose (1/26 farms) flocks. Eleven flocks were identified as C. gallinacea-positive while four flocks remained unclassified. Phylogenetic analysis revealed at least 16 genetic variants of C. gallinacea. Research showed that Chlamydiaceae occur in a poultry flock in Poland. The strains of C. gallinacea as dominant species show genetic variability.

Keywords: C. gallinacea, emerging agent, poultry, real-time PCR

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Authors: M. Eckert, D. Mendes, J P. Gonçalves, C. Moço, M. Oliveira

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The intensive extraction of natural aggregates leads to both depletion of natural resources and unwanted environmental impacts. On the other hand, uncontrolled disposal of Construction and Demolition Wastes (C&DW) causes the lifetime reduction of landfills. It is known that the European Union produces, each year, about 850 million tons of C&DW. For all the member States of the European Union, one of the milestones to be reached by 2020, according to the Resource Efficiency Roadmap (COM (2011) 571) of the European Commission, is to recycle 70% of the C&DW. In this work, properties of different types of recycled C&DW aggregates and natural aggregates were compared. Assays were performed according to European Standards (EN 13285; EN 13242+A1; EN 12457-4; EN 12620; EN 13139) for the characterization of there: physical, mechanical and chemical properties. Not standardized tests such as water absorption over time, mass stability and post compaction sieve analysis were also carried out. The tested recycled C&DW aggregates were classified according to the requirements of the European Standards regarding there potential use in concrete, mortar, unbound layers of road pavements and embankments. The results of the physical and mechanical properties of recycled C&DW aggregates indicated, in general, lower quality properties when compared to natural aggregates, particularly, for concrete preparation and unbound layers of road pavements. The results of the chemical properties attested that the C&DW aggregates constitute no environmental risk. It was concluded that recycled aggregates produced from C&DW have the potential to be used in many applications.

Keywords: recycled aggregate, sustainability, aggregate properties, European Standard Classification

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Authors: Sara Taghdisi, M. Mirmohammadi, M. Mokhtarian

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In 2013, the World Health Organization announced the cases of Cutaneous leishmaniasis infection in Iran between 69,000 to 113,000. The most common chemical drugs for Cutaneous leishmaniasis treatment are sodium stibogluconate, and meglumine antimonate, which not only have relatively many side effects, but also some species of the Leishmania genus have become resistant to them .The most prominent compound existing in different parts of the cotton plant is a yellow polyphenol called Gossypol. Gossypol is an extremely valuable compound and has anti-cancer properties. In the current project, Gossypol was extracted with a liquid-liquid extraction method in 120 minutes in the presence of Phosphoric acid from the cotton seed oil of Golestan beach varieties, then got crystallized in darkness using Acetic acid and isolated as Gossypol Acetic acid. The efficiency of the extracted crystal was obtained at 0.12+- 1.28. the cotton plant could be efficient in the treatment of Cutaneous leishmaniasis. The extract of the green-leaf cotton boll of Jargoyeh varieties was tested as an ointment on the target group of patients suffering from Cutaneous leishmaniasis resistant to drugs esistant to drugs by our colleagues in the research team. The results showed the Pearson's correlation coefficient of 0.72 between the two variables of wound diameter and the extract use over time which indicated the positive effect of this extract on the treatment of Cutaneous leishmaniasis was resistant to drugs.

Keywords: cottonseed oil, crystallization, gossypol, green-leaf

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Authors: Vinay Agrawal, Suyash Garg, Ravindra Nagar, Vinay Chandwani

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Open ground storey with floating columns is a typical feature in the modern multistory constructions in urban India. Such features are very much undesirable in buildings built in seismically active areas. The present study proposes a feasible solution to mitigate the effects caused due to non-uniformity of stiffness and discontinuity in load path and to simultaneously hold the functional use of the open storey particularly under the floating column, through a combination of various lateral strengthening systems. An investigation is performed on an example building with nine different analytical models to bring out the importance of recognising the presence of open ground storey and floating columns. Two separate analyses on various models of the building namely, the equivalent static analysis and the response spectrum analysis as per IS: 1893-2002 were performed. Various measures such as incorporation of Chevron bracings and shear walls, strengthening the columns in the open ground storey, and their different combinations were examined. The analysis shows that, in comparison to two short ones separated by interconnecting beams, the structural walls are most effective when placed at the periphery of the buildings and used as one long structural wall. Further, it can be shown that the force transfer from floating columns becomes less horizontal when the Chevron Bracings are placed just below them, thereby reducing the shear forces in the beams on which the floating column rests.

Keywords: equivalent static analysis, floating column, open ground storey, response spectrum analysis, shear wall, stiffness irregularity

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Authors: V. C. Santos-Ebinuma, J. F. B. Pereira, M. F. S. Teixeira, A. Pessoa Jr., P. Jauregi

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There is worldwide interest in process development for colorants production from natural sources. Microorganisms provide an alternative source of natural colorants which can be produced by cultivation technology and extracted from fermented broth. The aim of the present work was to study the recovery of red colorants from fermented broth of Penicillium purpurogenum DPUA 1275 using the technique of Colloidal Gas Aphrons (CGA); CGA are surfactant-stabilized microbubbles generated by intense stirring of a surfactant solution. CGA were generated by the cationic, hexadecyl trimethyl ammonium bromide (CTAB) surfactant. Firstly, experiments were carried out at different surfactant/fermented broth volumetric ratios (VCGA/VFB, VRATIO) varying between 3 and 18 at pH 6.9. Secondly, the experiments were carried out at VRATIO of 6 and 12 in different pH, namely, 6.9, 8.0, 9.0 and 10.0. The first results of recovery showed that an increase in the VRATIO from 3 to 6 and 12 promoted an increase as recovery as partition coefficient. However, at VRATIO of 18 the lowest partition coefficient was obtained. The best results were achieved at VRATIO of 6 and 12, namely recovery, Re, around 60% and partition coefficient, K, of 2.5 and 3.0 to 6 and 12 VRATIO, respectively. The second set of experiments showed that the pH 9.0 promoted the best results at VRATIO of 12 as follow: Re=70%, K=5.39, proteins and sugar selectivity (SePROT, 3.75 and SeSUGAR, 7.20, respectively). These results indicate that with CTAB the recovery is mainly driven by electrostatic interactions. In conclusion, the results above show that CGA employing a cationic surfactant is a promissory technique and it can be used as the first step of purification to recovery red colorants from fermented broth.

Keywords: liquid-liquid extraction, colloidal gas aphrons, recovery, natural colorants

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Authors: Chen Bo, Wen Zengping

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Based on the results of previous studies, we focus on the research of real ground motion selection and scaling method for structural performance-based seismic evaluation using nonlinear dynamic analysis. The input of earthquake ground motion should be determined appropriately to make them compatible with the site-specific hazard level considered. Thus, an optimized selection and scaling method are established including the use of not only Monte Carlo simulation method to create the stochastic simulation spectrum considering the multivariate lognormal distribution of target spectrum, but also a spectral shape parameter. Its applications in structural fragility analysis are demonstrated through case studies. Compared to the previous scheme with no consideration of the uncertainty of target spectrum, the method shown here can make sure that the selected records are in good agreement with the median value, standard deviation and spectral correction of the target spectrum, and greatly reveal the uncertainty feature of site-specific hazard level. Meanwhile, it can help improve computational efficiency and matching accuracy. Given the important infection of target spectrum’s uncertainty on structural seismic fragility analysis, this work can provide the reasonable and reliable basis for structural seismic evaluation under scenario earthquake environment.

Keywords: ground motion selection, scaling method, seismic fragility analysis, spectral shape

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Authors: Hao Wang, Shengchun Wang, Weidong Wang

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On the influence of train vibration and environmental noise on the measurement of track wear, we proposed a method for automatic extraction of circular arc on the inner or outer side of the rail waist and achieved the high-precision registration of rail profile. Firstly, a polynomial fitting method based on truncated residual histogram was proposed to find the optimal fitting curve of the profile and reduce the influence of noise on profile curve fitting. Then, based on the curvature distribution characteristics of the fitting curve, the interval search algorithm based on dynamic window’s maximum curvature entropy was proposed to realize the automatic segmentation of small circular arc. At last, we fit two circle centers as matching reference points based on small circular arcs on both sides and realized the alignment from the measured profile to the standard designed profile. The static experimental results show that the mean and standard deviation of the method are controlled within 0.01mm with small measurement errors and high repeatability. The dynamic test also verified the repeatability of the method in the train-running environment, and the dynamic measurement deviation of rail wear is within 0.2mm with high repeatability.

Keywords: curvature entropy, profile registration, rail wear, structured light, train-running

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Authors: Huawei Bai, Jianguo Yao, Fellow, IEEE

Abstract:

Atrial fibrillation (AF) is the most common form of heart arrhythmia and is closely associated with mortality and morbidity in heart failure, stroke, and coronary artery disease. The development of single spot optical sensors enables widespread photoplethysmography (PPG) screening, especially for AF, since it represents a more convenient and noninvasive approach. To our knowledge, most existing studies based on public and unbalanced datasets can barely handle the multiple noises sources in the real world and, also, lack interpretability. In this paper, we construct a large- scale PPG dataset using measurements collected from PPG wrist- watch devices worn by volunteers and propose an attention-based two-stream heterogeneous neural network (TSHNN). The first stream is a hybrid neural network consisting of a three-layer one-dimensional convolutional neural network (1D-CNN) and two-layer attention- based bidirectional long short-term memory (Bi-LSTM) network to learn representations from temporally sampled signals. The second stream extracts latent representations from the PPG time-frequency spectrogram using a five-layer CNN. The outputs from both streams are fed into a fusion layer for the outcome. Visualization of the attention weights learned demonstrates the effectiveness of the attention mechanism against noise. The experimental results show that the TSHNN outperforms all the competitive baseline approaches and with 98.09% accuracy, achieves state-of-the-art performance.

Keywords: PPG wearables, atrial fibrillation, feature fusion, attention mechanism, hyber network

Procedia PDF Downloads 121

Authors: Emma Carr, Jennifer Morrison, Peter Walker

Abstract:

Background: Due to COVID-19, there was a significant reduction in the number of children being treated under general anaesthetic (GA) within the health board, which led to a backlog of referrals. The referrals were being triaged and added to a waiting list in order of priority -determined by the information given. By implementing a checklist, it is anticipated that at least 70% of referrals will have the majority of the information required to effectively prioritise patients. The gold standard, as defined in ‘Guidelines For The Management Of Children Referred For Dental Extractions Under General Anaesthesia’, indicates that all referrals should mention: (i) Inability of the child to cooperate, (ii) Previously tried anxiety management techniques, (iii) Existence of psychological disorders, (iv) Presence of acute dental infection, (v) Requirement for extractions in multiple quadrants. Method: 130 referrals were examined over three months and compared to the recommended standard. A letter was emailed to referring dentists within Ayrshire & Arran outlining the recommended information to be included within the referral. The second round of data collection was then carried out, which involved an examination of 105 referrals. Results: The first round revealed that only 28% of referrals mentioned at least four defined standards outlined above. Following issuing a checklist to all dentists, this increased to 72%. Conclusion: As many of the children referred for extractions under GA have suffered pain and infection because of dental caries, it is important that delay of treatment is minimised, where possible. The implementation of a standardised checklist has enabled more effective prioritisation of patients.

Keywords: caries, dentistry, general anaesthetic, paediatrics

Procedia PDF Downloads 109

Authors: Ibrahim Ilker Ozyigit, Fatih Tabanli, Sezin Adinir

Abstract:

In this study, Ascochyta blight resistance was investigated in 34 registered chickpea varieties, which are widely planting in different regions of Turkey. For this aim, molecular marker techniques, such as STMS, RAPD and ISSR were used. Ta2, Ta146 and Ts54 primers were used for STMS, while UBC733 and UBC681 primers for RAPD, and UBC836 and UBC858 primers for ISSR. Ta2, Ts54 and Ta146 (STMS), and UBC733 (RAPD) primers demonstrated the distinctive feature for Ascochyta blight resistance. Ta2, Ts54 and Ta146 primers yielded the quite effective results in detection of resistant and sensitive varieties. Besides, UBC 733 primer distinguished all kinds of standard did not give any reliable results for other varieties since it demonstrated all as resistant. In addition, monomorphic bands were obtained from UBC681 (RAPD), and UBC836 and UBC858 (ISSR) primers, not demonstrating reliable results in detection of resistance against Ascochyta blight disease. Obtained results informed us about both disease resistance and genetic diversity in registered Turkish chickpea varieties. This project was funded through the Scientific Research Projects of Marmara University under Grant Number FEN-C-YLP-070617-0365 and The Scientific and Technological Research Council of Turkey (TUBITAK) under Grant Number 113O070.

Keywords: plant genetics, ISSR, RAPD, STMS

Procedia PDF Downloads 199

Authors: Walid Moudani

Abstract:

The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

Procedia PDF Downloads 410

Authors: Ahmed R. Ballil

Abstract:

Heat exchangers are devices used to transfer heat between two fluids. These devices are utilized in many engineering and industrial applications such as heating, cooling, condensation and boiling processes. The fluids might be in direct contact (mixed), or they separated by a solid wall to avoid mixing. In the present paper, interactive computer-aided design of shell and tube heat exchangers is developed using Visual Basic computer code as a framework. This design is based on the Bell-Delaware method, which is one of the very well known methods reported in the literature for the design of shell and tube heat exchangers. Physical properties for either the tube or the shell side fluids are internally evaluated by calling on an enormous data bank composed of more than a hundred fluid compounds. This contributes to increase the accuracy of the present design. The international system of units is considered in the developed computer program. The present design has an added feature of being capable of performing modification based upon a preset design criterion, such that an optimum design is obtained at satisfying constraints set either by the user or by the method itself. Also, the present code is capable of giving an estimate of the approximate cost of the heat exchanger based on the predicted surface area of the exchanger evaluated by the program. Finally, the present thermal and hydraulic design code is tested for accuracy and consistency against some of existed and approved designs of shell and tube heat exchangers.

Keywords: bell-delaware method, heat exchangers, shell and tube, thermal and hydraulic design

Procedia PDF Downloads 148

Authors: Babak Azari, Afshin Pourahmad, Babak Sadeghi, Masuod Mokhtari

Abstract:

In this work, Equisetnm arvense plant extract was used for preparing amorphous SiO₂. For preparing of SiO₂/zeolitic imidazolate framework-8 (ZIF-8) nanocomposite by solvothermal method, the synthesized SiO₂ was added to the synthesis mixture ZIF-8. The nanocomposite was characterized using a range of techniques. The photocatalytic activity of SiO₂/ZIF-8 was investigated systematically by degrading crystal violet as a cationic dye under Ultraviolet light irradiation. Among synthesized samples (SiO₂, ZIF-8 and SiO₂/ZIF-8), the SiO₂/ZIF-8 exhibited the highest photocatalytic activity and improved stability compared to pure SiO₂ and ZIF-8. As evidenced by Scanning Electron Microscopy and Transmission electron microscopy images, ZIF-8 particles without aggregation are located over SiO₂. The SiO₂ not only provides structured support for ZIF-8 but also prevents the aggregation of ZIF-8 Metal-organic framework in comparison to the isolated ZIF-8. The superior activity of this photocatalyst was attributed to the synergistic effects from SiO₂ owing to (I) an electron acceptor (from ZIF-8) and an electron donor (to O₂ molecules), (II) preventing recombination of electron-hole in ZIF-8, and (III) maximum interfacial contact ZIF-8 with the SiO₂ surface without aggregation or prevent the accumulation of ZIF-8. The results demonstrate that holes (h+) and •O₂- are primary reactive species involved in the photocatalytic oxidation process. Moreover, the SiO₂/ZIF-8 photocatalyst did not show any obvious loss of photocatalytic activity during five-cycle tests, which indicates that the heterostructured photocatalyst was highly stable and could be used repeatedly.

Keywords: nano, zeolit, potocatalist, nanocomposite

Procedia PDF Downloads 83

Authors: Simone Leonardi, Luca Ardito

Abstract:

Micro-influencers are effective elements in the marketing strategies of companies and institutions because of their capability to create an hyper-engaged audience around a specific topic of interest. In recent years, many scientific approaches and commercial tools have handled the task of detecting this type of social media users. These strategies adopt solutions ranging from rule based machine learning models to deep neural networks and graph analysis on text, images, and account information. This work compares the existing solutions and proposes an ensemble method to generalize them with different input data and social media platforms. The deployed solution combines deep learning models on unstructured data with statistical machine learning models on structured data. We retrieve both social media accounts information and multimedia posts on Twitter and Instagram. These data are mapped into feature vectors for an eXtreme Gradient Boosting (XGBoost) classifier. Sixty different topics have been analyzed to build a rule based gold standard dataset and to compare the performances of our approach against baseline classifiers. We prove the effectiveness of our work by comparing the accuracy, precision, recall, and f1 score of our model with different configurations and architectures. We obtained an accuracy of 0.91 with our best performing model.

Keywords: deep learning, gradient boosting, image processing, micro-influencers, NLP, social media

Procedia PDF Downloads 183