Search results for: behavioral-physical and visual methods
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 16868

Search results for: behavioral-physical and visual methods

12878 Investigating the Effect of Orthographic Transparency on Phonological Awareness in Bilingual Children with Dyslexia

Authors: Sruthi Raveendran

Abstract:

Developmental dyslexia, characterized by reading difficulties despite normal intelligence, presents a significant challenge for bilingual children navigating languages with varying degrees of orthographic transparency. This study bridges a critical gap in dyslexia interventions for bilingual populations in India by examining how consistency and predictability of letter-sound relationships in a writing system (orthographic transparency) influence the ability to understand and manipulate the building blocks of sound in language (phonological processing). The study employed a computerized visual rhyme-judgment task with concurrent EEG (electroencephalogram) recording. The task compared reaction times, accuracy of performance, and event-related potential (ERP) components (N170, N400, and LPC) for rhyming and non-rhyming stimuli in two orthographies: English (opaque orthography) and Kannada (transparent orthography). As hypothesized, the results revealed advantages in phonological processing tasks for transparent orthography (Kannada). Children with dyslexia were faster and more accurate when judging rhymes in Kannada compared to English. This suggests that a language with consistent letter-sound relationships (transparent orthography) facilitates processing, especially for tasks that involve manipulating sounds within words (rhyming). Furthermore, brain activity measured by event-related potentials (ERP) showed less effort required for processing words in Kannada, as reflected by smaller N170, N400, and LPC amplitudes. These findings highlight the crucial role of orthographic transparency in optimizing reading performance for bilingual children with dyslexia. These findings emphasize the need for language-specific intervention strategies that consider the unique linguistic characteristics of each language. While acknowledging the complexity of factors influencing dyslexia, this research contributes valuable insights into the impact of orthographic transparency on phonological awareness in bilingual children. This knowledge paves the way for developing tailored interventions that promote linguistic inclusivity and optimize literacy outcomes for children with dyslexia.

Keywords: developmental dyslexia, phonological awareness, rhyme judgment, orthographic transparency, Kannada, English, N170, N400, LPC

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12877 Exploring Antimicrobial Resistance in the Lung Microbial Community Using Unsupervised Machine Learning

Authors: Camilo Cerda Sarabia, Fernanda Bravo Cornejo, Diego Santibanez Oyarce, Hugo Osses Prado, Esteban Gómez Terán, Belén Diaz Diaz, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

Abstract:

Antimicrobial resistance (AMR) represents a significant and rapidly escalating global health threat. Projections estimate that by 2050, AMR infections could claim up to 10 million lives annually. Respiratory infections, in particular, pose a severe risk not only to individual patients but also to the broader public health system. Despite the alarming rise in resistant respiratory infections, AMR within the lung microbiome (microbial community) remains underexplored and poorly characterized. The lungs, as a complex and dynamic microbial environment, host diverse communities of microorganisms whose interactions and resistance mechanisms are not fully understood. Unlike studies that focus on individual genomes, analyzing the entire microbiome provides a comprehensive perspective on microbial interactions, resistance gene transfer, and community dynamics, which are crucial for understanding AMR. However, this holistic approach introduces significant computational challenges and exposes the limitations of traditional analytical methods such as the difficulty of identifying the AMR. Machine learning has emerged as a powerful tool to overcome these challenges, offering the ability to analyze complex genomic data and uncover novel insights into AMR that might be overlooked by conventional approaches. This study investigates microbial resistance within the lung microbiome using unsupervised machine learning approaches to uncover resistance patterns and potential clinical associations. it downloaded and selected lung microbiome data from HumanMetagenomeDB based on metadata characteristics such as relevant clinical information, patient demographics, environmental factors, and sample collection methods. The metadata was further complemented by details on antibiotic usage, disease status, and other relevant descriptions. The sequencing data underwent stringent quality control, followed by a functional profiling focus on identifying resistance genes through specialized databases like Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. Subsequent analyses employed unsupervised machine learning techniques to unravel the structure and diversity of resistomes in the microbial community. Some of the methods employed were clustering methods such as K-Means and Hierarchical Clustering enabled the identification of sample groups based on their resistance gene profiles. The work was implemented in python, leveraging a range of libraries such as biopython for biological sequence manipulation, NumPy for numerical operations, Scikit-learn for machine learning, Matplotlib for data visualization and Pandas for data manipulation. The findings from this study provide insights into the distribution and dynamics of antimicrobial resistance within the lung microbiome. By leveraging unsupervised machine learning, we identified novel resistance patterns and potential drivers within the microbial community.

Keywords: antibiotic resistance, microbial community, unsupervised machine learning., sequences of AMR gene

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12876 Enhancing Audience Engagement: Informal Music Learning During Classical Concerts

Authors: Linda Dusman, Linda Baker

Abstract:

The Bearman Study of Audience Engagement examined the potential for real-time music education during online symphony orchestra concerts. It follows on the promising results of a preliminary study of STEAM (Science, Technology, Engineering, Arts, and Mathematics) education during live concerts, funded by the National Science Foundation with the Baltimore Symphony Orchestra. For the Bearman Study, audience groups were recruited to attend two previously recorded concerts of the National Orchestral Institute (NOI) in 2020 or the Utah Symphony in 2021. They used a smartphone app called EnCue to present real-time program notes about the music being performed. Short notes along with visual information (photos and score fragments) were designed to provide historical, cultural, biographical, and theoretical information at specific moments in the music where that information would be most pertinent, generally spaced 2-3 minutes apart to avoid distraction. The music performed included Dvorak Symphony No. 8 and Mahler Symphony No. 5 at NOI, and Mendelssohn Scottish Symphony and Richard Strauss Metamorphosen with the Utah Symphony, all standard repertoire for symphony orchestras. During each phase of the study (2020 and 2021), participants were randomly assigned to use the app to view program notes during the first concert or to use the app during the second concert. A total of 139 participants (67 in 2020 and 72 in 2021) completed three online questionnaires, one before attending the first concert, one immediately after the concert, and the third immediately after the second concert. Questionnaires assessed demographic background, expertise in music, engagement during the concert, learning of content about the composers and the symphonies, and interest in the future use of the app. In both phases of the study, participants demonstrated that they learned content presented on the app, evidenced by the fact that their multiple-choice test scores were significantly higher when they used the app than when they did not. In addition, most participants indicated that using the app enriched their experience of the concert. Overall, they were very positive about their experience using the app for real-time learning and they expressed interest in using it in the future at both live and streaming concerts. Results confirmed that informal real-time learning during concerts is possible and can generate enhanced engagement and interest in classical music.

Keywords: audience engagement, informal education, music technology, real-time learning

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12875 Integration Between Seismic Planning and Urban Planning for Improving the City Image of Tehran - Case of Tajrish

Authors: Samira Eskandari

Abstract:

The image of Tehran has been impacted in recent years due to poor urban management and fragmented governance. There is no cohesive urban beautification framework in Tehran to enforce builders take aesthetic factors seriously when design and construct new buildings. The existing guidelines merely provide people with recommendations, not regulations. Obviously, Tehran needs a more comprehensive and strict urban beautification framework to restore its image. The damaged image has impacted the city’s social, economic and environmental growth. This research aims to find and examine a solution by which the employment of urban beautification regulation would be guaranteed, and city image would be organized. The methodology is based on a qualitative approach associated with analytical methods, in-depth surveys and interviews with Tehran citizens, authorities and experts, and use of academic resources as well as simulation. As a result, one practical solution is to incorporate aesthetic guidelines into a survival-related framework like a seismic guideline. Tehran is a seismic site, and all the buildings in Tehran have to be retrofitted against earthquake during construction. Hence, by integrating seismic regulations and aesthetic disciplines, urban beautification will be somehow guaranteed. Besides, the seismic image can turn into Tehran’s brand and enhances city identity. This research is trying to increase the social, environmental, and economic interconnectedness between urban planning and seismic planning by the usage of landscape architecture methods. As a case study, the potential outcomes are simulated in Tajrish, a suburb located in the north of Tehran. The result is that, by the redefinition of the morphology of seismic retrofitting systems, used in the significant city image elements, and re-function them in accordance with the Iranian culture and traditions, the city image would become more harmonized and legible.

Keywords: earthquake, retrofitting systems, Tehran image, urban beautification

Procedia PDF Downloads 135
12874 Machine Learning Based Anomaly Detection in Hydraulic Units of Governors in Hydroelectric Power Plants

Authors: Mehmet Akif Bütüner, İlhan Koşalay

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Hydroelectric power plants (HEPPs) are renewable energy power plants with the highest installed power in the world. While the control systems operating in these power plants ensure that the system operates at the desired operating point, it is also responsible for stopping the relevant unit safely in case of any malfunction. While these control systems are expected not to miss signals that require stopping, on the other hand, it is desired not to cause unnecessary stops. In traditional control systems including modern systems with SCADA infrastructure, alarm conditions to create warnings or trip conditions to put relevant unit out of service automatically are usually generated with predefined limits regardless of different operating conditions. This approach results in alarm/trip conditions to be less likely to detect minimal changes which may result in serious malfunction scenarios in near future. With the methods proposed in this research, routine behavior of the oil circulation of hydraulic governor of a HEPP will be modeled with machine learning methods using historical data obtained from SCADA system. Using the created model and recently gathered data from control system, oil pressure of hydraulic accumulators will be estimated. Comparison of this estimation with the measurements made and recorded instantly by the SCADA system will help to foresee failure before becoming worse and determine remaining useful life. By using model outputs, maintenance works will be made more planned, so that undesired stops are prevented, and in case of any malfunction, the system will be stopped or several alarms are triggered before the problem grows.

Keywords: hydroelectric, governor, anomaly detection, machine learning, regression

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12873 Basins of Attraction for Quartic-Order Methods

Authors: Young Hee Geum

Abstract:

We compare optimal quartic order method for the multiple zeros of nonlinear equations illustrating the basins of attraction. To construct basins of attraction effectively, we take a 600×600 uniform grid points at the origin of the complex plane and paint the initial values on the basins of attraction with different colors according to the iteration number required for convergence.

Keywords: basins of attraction, convergence, multiple-root, nonlinear equation

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12872 Responding to the Mental Health Service Needs of Rural-to-Urban Migrant Workers in China: Current Situation and Future Directions

Authors: Yujun Liu, Maosheng Ran

Abstract:

Background: Chinese rural-to-urban migrant workers’ mental health problems raise attentions from different social sectors. However, situation of present mental health services provided to this population has not been discovered. This study attempts to describe the current mental health service situation, identify the gaps and give the future directions based on the quantitative data. Methods: Questionnaire surveys were conducted among 2017 rural-to-urban migrant workers in 13 cities and 100 social work service organizations in 5 cities in 2014. Data was collected by face-to-face structured interview by trained interviewers. Findings: Migrant workers’ mental health status was not good. Compared to the severity of mental distress, mental health service for this population was lacking and insufficient, which accounted for only 14.4% of all services in our sample. And the group work and case work were the most frequently-used methods. By estimating a series of regression models, we revealed that life experiences and working conditions were significantly associated with migrant workers’ mental health status. Therefore, the macro social work practices aimed at this whole group were advocated to promote their mental wellbeing. That is, practitioners should not only focus on the improvement of migrant workers’ emotion management capacity, but also pay attention to raise awareness and improve their living and working condition; not only concentrate on the solving of individuals’ dilemma, but also promote gradual reformation of present labor regime and hukou system in China.

Keywords: Chinese rural-to-urban migrant workers, macro social work practice, mental health service needs, mental health status

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12871 Cutting Plane Methods for Integer Programming: NAZ Cut and Its Variations

Authors: A. Bari

Abstract:

Integer programming is a branch of mathematical programming techniques in operations research in which some or all of the variables are required to be integer valued. Various cuts have been used to solve these problems. We have also developed cuts known as NAZ cut & A-T cut to solve the integer programming problems. These cuts are used to reduce the feasible region and then reaching the optimal solution in minimum number of steps.

Keywords: Integer Programming, NAZ cut, A-T cut, Cutting plane method

Procedia PDF Downloads 367
12870 Assessing Renewal Needs of Urban Water Infrastructure Systems: Case Study of Linköping in Sweden

Authors: Eman Hegazy, Stefan Anderberg, Joakim Krook

Abstract:

Urban water infrastructure systems are central to functioning cities. For securing a continuous and efficient supply of the systems services, continuous investment, maintenance, and renewal are needed. Neglecting maintenance and renewal can lead to recurrent breakdown problems as systems age, which makes it more and more difficult to secure efficient long-term supply. Globally, many cities struggle with aging water infrastructure, often due to competing funding priorities. Investment in maintenance and renewal is not prioritized. The problem primarily stems from the challenge of reaping the benefits of investments promptly. The long-term benefits gained from investing in the renewal of water infrastructure may be achievable in the long run, resulting in the oversight of such investments. This leads to a build-up of "renewal debt" for future generations to inherit. Addressing this issue is difficult due to various contributing factors and the complex nature of the systems. The study aims to contribute to an increased understanding of the long-term management challenges of urban water infrastructure, the development of improved maintenance and renewal strategies through the examination of water infrastructure management, and the assessment of the adequacy of the maintenance and renewal in a case study, the city of Linköping, Sweden. Employing a multi-methods approach, this study utilized both qualitative and quantitative methods, including interviews, workshops, and data analysis. The findings of the study provided insights into the current status of the water and sewerage networks in Linkoping, highlighting the risks to ensuring reliable and sustainable water supply and discussing strategies for improving maintenance and renewal.

Keywords: case study, infrastructure management, renewal needs, Sweden, urban water infrastructure

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12869 Deubiquitinase USP35 Regulates Mitosis Progression by Blocking CDH1-Mediated Degradation of Aurora B.

Authors: Jinyoung Park, Eun Joo Song

Abstract:

Introduction: Deubiquitinating enzymes (DUBs) are proteases that cleave ubiquitin or ubiquitin-like modifications on substrates. Deubiquitination could regulate cellular physiology, such as signal transduction, DNA damage and repair, and cell cycle progression. Although more than 100 DUBs are encoded in the human and the importance of DUBs has been realized, the functions of most DUBs are unknown. This study aims to identify the molecular mechanism by which deubiquitinating enzyme USP35 regulates cell cycle progression for the first time. Methods: USP35 RNAi was mainly used to identify the function of USP35 in cell cycle progression. To find substrates of USP35, we analyzed protein-protein interaction using LC-MS. Several biological methods, such as ubiquitination assay, cell synchronization, immunofluorescence, and immunoprecipitation assay were used to investigate the exact mechanism by which USP35 affects successful completion of mitosis. Results: USP35 knockdown caused not only reduction of mitotic cell number but also induction of mitotic cells with abnormal spindle formation. Actually, cell proliferation was decreased by USP35 knockdown. Interestingly, we found that loss of USP35 decreased the stability and expression of Aurora B, a member of chromosomal passenger complex (CPC), and the phosphorylation of its substrate. Indeed, USP35 interacted with Aurora B and deubiquitinated it. In addition, USP35 knockdown induced abnormal localization of Aurora B in mitotic cells. Finally, CDH1-mediated ubiquitination of Aurora B level was rescued by USP35 overexpression, but not inactive form of USP35, USP35 C450A. Discussion: Our findings suggest that USP35 regulates Aurora B-mediated mitotic spindle assembly and G2-M transition by blocking CDH1-induced degradation of Aurora B.

Keywords: USP35, HSP90, Aurora B, cell cycle progression

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12868 The Effect of Bath Composition for Hot-Dip Aluminizing of AISI 4140 Steel

Authors: Aptullah Karakas, Murat Baydogan

Abstract:

Hot-dip aluminizing (HDA) is one of the several aluminizing methods to form a wear-, corrosion- and oxidation-resistant aluminide layers on the surface. In this method, the substrate is dipped into a molten aluminum bath, hold in the bath for several minutes, and cooled down to the room temperature in air. A subsequent annealing after the HDA process is generally performed. The main advantage of HDA is its very low investment cost in comparison with other aluminizing methods such as chemical vapor deposition (CVD), pack aluminizing and metalizing. In the HDA process, Al or Al-Si molten baths are mostly used. However, in this study, three different Al alloys such as Al4043 (Al-Mg), Al5356 (Al-Si) and Al7020 (Al-Zn) were used as the molten bath in order to see their effects on morphological and mechanical properties of the resulting aluminide layers. AISI 4140 low alloyed steel was used as the substrate. Parameters of the HDA process were bath composition, bath temperature, and dipping time. These parameters were considered within a Taguchi L9 orthogonal array. After the HDA process and subsequent diffusion annealing, coating thickness measurement, microstructural analysis and hardness measurement of the aluminide layers were conducted. The optimum process parameters were evaluated according to coating morphology, such as cracks, Kirkendall porosity and hardness of the coatings. According to the results, smooth and clean aluminide layer with less Kirkendall porosity and cracks were observed on the sample, which was aluminized in the molten Al7020 bath at 700 C for 10 minutes and subsequently diffusion annealed at 750 C. Hardness of the aluminide layer was in between 1100-1300 HV and the coating thickness was approximately 400 µm. The results were promising such that a hard and thick aluminide layer with less Kirkendall porosity and cracks could be formed. It is, therefore, concluded that Al7020 bath may be used in the HDA process of AISI 4140 steel substrate.

Keywords: hot-dip aluminizing, microstructure, hardness measurement, diffusion annealing

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12867 Determinants of Healthcare Team Effectiveness in Subterranean Settings: A Mixed-Methods Study

Authors: Nasra Idilbi, Jalal Tarabeia, Layalleh Masalha, Heiam Shoufani Kassis, Gizell Green

Abstract:

Background: Healthcare professionals working in underground facilities face unique challenges affecting their physical and mental health and team effectiveness. We aimed to examine how an underground work environment affects the physical and mental health and effectiveness of a multi-professional medical team in a medical center under continuous war threats and the contribution of various demographic and professional characteristics. Methods: A cross-sectional survey was disseminated electronically. The questionnaire assessed team effectiveness, the quality of the work, and the health symptoms reported by the team while working in the underground complex. Results: In total, 270 healthcare workers (mean age 40 years, 75.6% females, 88.4% nurses) completed the questionnaire. Women reported statistically significantly higher mean scores of physical strain, fatigue, and eye irritation associated with the work environment compared to men. Multiple regression analysis revealed that psychological distress, noise, and lighting in the underground compound significantly influenced team effectiveness. The qualitative analysis revealed two key themes: the mental health impact of working in an underground environment and the effects of noise and lighting on staff performance. Nurses reported feelings of suffocation, claustrophobia, and difficulty concentrating due to the enclosed space, with some expressing heightened stress levels that impaired their ability to work effectively and safely. Female staff reported more pronounced symptoms of physical strain, fatigue, and eye irritation. Additionally, the underground complex’s poor noise absorption created a highly disruptive work environment, while inadequate lighting hindered accurate patient assessments, leading to potential errors. These challenges were exacerbated by physical symptoms like headaches and nausea, which further impacted job performance. The findings underscore the significant role of environmental factors in influencing both mental health and operational effectiveness, aligning with quantitative data on the predictors of team performance. Conclusions: The underground work environment is crucial in influencing healthcare team effectiveness, with psychological distress, noise, and lighting as key factors. The study highlights the importance of creating a comfortable work environment to foster team efficiency. The findings provide valuable insights for managers in underground healthcare facilities to optimize team performance and well-being.

Keywords: team effectiveness, underground settings, healthcare, environmental factors, a mixed-methods study

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12866 Policy and System Research for Health of Ageing Population

Authors: Sehrish Ather

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Introduction: To improve organizational achievements through the production of new knowledge, health policy and system research is the basic requirement. An aging population is always the source of the increased burden of chronic diseases, disabilities, mental illnesses, and other co-morbidities; therefore the provision of quality health care services to every group of the population should be achieved by making strong policy and system research for the betterment of health care system. Unfortunately, the whole world is lacking policies and system research for providing health care to their elderly population. Materials and Methods: A literature review of published studies on aging diseases was done, ranging from the year 2011-2018. Geriatric, population, health policy, system, and research were the key terms used for the search. Databases searched were Google Scholar, PubMed, Science Direct, Ovid, and Research Gate. Grey literature was searched from various websites, including IHME, Library of the University of Lahore, World Health Organization (Ageing and Life Course), and Personal communication with Neuro-physicians. After careful reviewing published and un-published information, it was decided to carry on with commentary. Results and discussion: Most of the published studies have highlighted the need to advocate the funders of health policy and stakeholders of healthcare system research, and it was detected as a major issue, research on policy and healthcare system to provide health care to 'geriatric population' was found as highly neglected area. Conclusion: It is concluded that physicians are more involved with the policy and system research regarding any type of diseases, but scientists and researchers of basic and social science are less likely to be involved in methods used for health policy and system research due to lack of funding and resources. Therefore ageing diseases should be considered as a priority, and comprehensive policy and system research should be initiated for diseases of the geriatric population.

Keywords: geriatric population, health care system, health policy, system research

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12865 A Mixed Methods Research Design for the Development of the Xenia Higher Education Institutions' Inclusiveness Index

Authors: Achilles Kameas, Eleni Georgakakou, Anna Lisa Amodeo, Aideen Quilty, Aisling Malone, Roberta Albertazzi, Moises Carmona, Concetta Esposito, Ruben David Fernandez Carrasco, Carmela Ferrara, Francesco Garzillo, Mojca Pusnik, Maria Cristina Scarano

Abstract:

While researchers, especially in academia, study and research the phenomena of inclusion of sexual minority and gender marginalized groups, seldom the European Higher Education Institutions (HEI) act on lowering the cultural and educational barriers to their proactive inclusion. The challenge in European HEIs is that gender, and sexual orientation discrimination remains an issue not adequately addressed. Following a mixed methods research design of quantitative and qualitative research techniques and tools, which is applied in five (5) European countries (Italy, Greece, Ireland, Slovenia, and Spain) and that combines desk research, evaluation, and weighting processes for a Matrix-based on Objective indicators and Survey for students and staff of the HEI to gauge the perception of inclusiveness in the HEI context, XENIA HEI Inclusiveness Index is an instrument that will allow universities to gauge and assess their inclusiveness in the domain of discrimination and exclusion based on gender identity and sexual orientation. The index will allow capturing the depth and reach of policies, programmes, and initiatives of HEIs in tackling the phenomena and dynamics of exclusion of LGBT+ (lesbian, gay, bisexual, trans, and other marginalized groups on the basis of gender and sexual identity) and cisgender women exposed to the risk of discrimination.

Keywords: gender identity, higher education, LGBT+ rights, XENIA inclusiveness index

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12864 Protective Effect of Rosemary Extract against Toxicity Induced by Egyptian Naja haje Venom

Authors: Walaa H. Salama, Azza M. Abdel-Aty, Afaf S. Fahmy

Abstract:

Background: Egyptian Cobra; Naja haje (Elapidae) is one of most common snakes, widely distributed in Egypt and its envenomation causes multi-organ failure leading to rapid death. Thus, Different medicinal plants showed a protective effect against venom toxicity and may complement the conventional antivenom therapy. Aim: The present study was designed to assess both the antioxidant capacity of methanolic extract of rosemary leaves and evaluate the neutralizing ability of the extract against hepatotoxicity induced by Naja haje venom. Methods: The total phenolic and flavonoid contents and the antioxidant capacity of the methanolic rosemary extract were estimated by DPPH and ABTS Scavenging methods. In addition, the rosemary extract were assessed for anti-venom properties under in vitro and in vivo standard assays. Results: The rosemary extract had high total phenolic and flavonoid content as 12 ± 2 g of gallic acid equivalent per 100 gram of dry weight (g GAE/100g dw) and 5.5 ± 0.8 g of catechin equivalent per 100 grams of dry weight (g CE/100g dw), respectively. In addition, the rosemary extract showed high antioxidant capacity. Furthermore, The rosemary extract were inhibited in vitro the enzymatic activities of phospholipase A₂, L-amino acid oxidase, and hyaluronidase of the venom in a dose-dependent manner. Moreover, indirect hemolytic activity, hepatotoxicity induced by venom were completely neutralized as shown by histological studies. Conclusion: The phenolic compounds of rosemary extract with potential antioxidant activity may be considered as a promising candidate for future therapeutics in snakebite therapy.

Keywords: antioxidant activity, neutralization, phospholipase A₂ enzyme, snake venom

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12863 A Literature Review on the Use of Information and Communication Technology within and between Emergency Medical Teams during a Disaster

Authors: Badryah Alshehri, Kevin Gormley, Gillian Prue, Karen McCutcheon

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In a disaster event, sharing patient information between the pre-hospitals Emergency Medical Services (EMS) and Emergency Department (ED) hospitals is a complex process during which important information may be altered or lost due to poor communication. The aim of this study was to critically discuss the current evidence base in relation to communication between pre-EMS hospital and ED hospital professionals by the use of Information and Communication Systems (ICT). This study followed the systematic approach; six electronic databases were searched: CINAHL, Medline, Embase, PubMed, Web of Science, and IEEE Xplore Digital Library were comprehensively searched in January 2018 and a second search was completed in April 2020 to capture more recent publications. The study selection process was undertaken independently by the study authors. Both qualitative and quantitative studies were chosen that focused on factors which are positively or negatively associated with coordinated communication between pre-hospital EMS and ED teams in a disaster event. These studies were assessed for quality and the data were analysed according to the key screening themes which emerged from the literature search. Twenty-two studies were included. Eleven studies employed quantitative methods, seven studies used qualitative methods, and four studies used mixed methods. Four themes emerged on communication between EMTs (pre-hospital EMS and ED staff) in a disaster event using the ICT. (1) Disaster preparedness plans and coordination. This theme reported that disaster plans are in place in hospitals, and in some cases, there are interagency agreements with pre-hospital and relevant stakeholders. However, the findings showed that the disaster plans highlighted in these studies lacked information regarding coordinated communications within and between the pre-hospital and hospital. (2) Communication systems used in the disaster. This theme highlighted that although various communication systems are used between and within hospitals and pre-hospitals, technical issues have influenced communication between teams during disasters. (3) Integrated information management systems. This theme suggested the need for an integrated health information system which can help pre-hospital and hospital staff to record patient data and ensure the data is shared. (4) Disaster training and drills. While some studies analysed disaster drills and training, the majority of these studies were focused on hospital departments other than EMTs. These studies suggest the need for simulation disaster training and drills, including EMTs. This review demonstrates that considerable gaps remain in the understanding of the communication between the EMS and ED hospitals staff in relation to response in disasters. The review shows that although different types of ICTs are used, various issues remain which affect coordinated communication among the relevant professionals.

Keywords: communication, emergency communication services, emergency medical teams, emergency physicians, emergency nursing, paramedics, information and communication technology, communication systems

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12862 Evaluation of Antibiotic Resistance Profiles of Staphlyococci Isolated from Various Clinical Specimens

Authors: Recep Kesli, Merih Simsek, Cengiz Demir, Onur Turkyilmaz

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Objective: Goal of this study was to determine the antibiotic resistance of Staphylococcus aureus (S. aureus) and Methicillin resistant staphylococcus aureus (MRSA) strains isolated at Medical Microbiology Laboratory of ANS Application and Research Hospital, Afyon Kocatepe University, Turkey. Methods: S. aureus strains isolated between October 2012 and September 2016, from various clinical specimens were evaluated retrospectively. S. aureus strains were identified by both the conventional methods and automated identification system -VITEK 2 (bio-Mérieux, Marcy l’etoile, France), and Meticillin resistance was verified using oxacillin disk with disk-diffusion method. Antibiotic resistance testing was performed by Kirby-Bauer disc diffusion method according to CLSI criteria, and intermediate susceptible strains were considered as resistant. Results: Seven hundred S.aureus strains which were isolated from various clinical specimens were included in this study. These strains were mostly isolated from blood culture, tissue, wounds and bronchial aspiration. All of 306 (43,7%) were oxacillin resistant. While all the S.aureus strains were found to be susceptible to vancomycin, teicoplanin, daptomycin and linezolid, 38 (9.6 %), 77 (19.5 %), 116 (29.4 %), 152 (38.6 %) and 28 (7.1 %) were found to be resistant aganist to clindamycin, erythromycin, gentamicin, tetracycline and sulfamethoxazole/trimethoprim, retrospectively. Conclusions: Comparing to the Methicillin sensitive staphylococcus aureus (MSSA) strains, increased resistance rates of, trimethoprim-sulfamethoxazole, clindamycin, erythromycin, gentamicin, and tetracycline were observed among the MRSA strains. In this study, the most effective antibiotic on the total of strains was found to be trimethoprim-sulfamethoxazole, the least effective antibiotic on the total of strains was found to be tetracycline.

Keywords: antibiotic resistance, MRSA, Staphylococcus aureus, VITEK 2

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12861 Federated Knowledge Distillation with Collaborative Model Compression for Privacy-Preserving Distributed Learning

Authors: Shayan Mohajer Hamidi

Abstract:

Federated learning has emerged as a promising approach for distributed model training while preserving data privacy. However, the challenges of communication overhead, limited network resources, and slow convergence hinder its widespread adoption. On the other hand, knowledge distillation has shown great potential in compressing large models into smaller ones without significant loss in performance. In this paper, we propose an innovative framework that combines federated learning and knowledge distillation to address these challenges and enhance the efficiency of distributed learning. Our approach, called Federated Knowledge Distillation (FKD), enables multiple clients in a federated learning setting to collaboratively distill knowledge from a teacher model. By leveraging the collaborative nature of federated learning, FKD aims to improve model compression while maintaining privacy. The proposed framework utilizes a coded teacher model that acts as a reference for distilling knowledge to the client models. To demonstrate the effectiveness of FKD, we conduct extensive experiments on various datasets and models. We compare FKD with baseline federated learning methods and standalone knowledge distillation techniques. The results show that FKD achieves superior model compression, faster convergence, and improved performance compared to traditional federated learning approaches. Furthermore, FKD effectively preserves privacy by ensuring that sensitive data remains on the client devices and only distilled knowledge is shared during the training process. In our experiments, we explore different knowledge transfer methods within the FKD framework, including Fine-Tuning (FT), FitNet, Correlation Congruence (CC), Similarity-Preserving (SP), and Relational Knowledge Distillation (RKD). We analyze the impact of these methods on model compression and convergence speed, shedding light on the trade-offs between size reduction and performance. Moreover, we address the challenges of communication efficiency and network resource utilization in federated learning by leveraging the knowledge distillation process. FKD reduces the amount of data transmitted across the network, minimizing communication overhead and improving resource utilization. This makes FKD particularly suitable for resource-constrained environments such as edge computing and IoT devices. The proposed FKD framework opens up new avenues for collaborative and privacy-preserving distributed learning. By combining the strengths of federated learning and knowledge distillation, it offers an efficient solution for model compression and convergence speed enhancement. Future research can explore further extensions and optimizations of FKD, as well as its applications in domains such as healthcare, finance, and smart cities, where privacy and distributed learning are of paramount importance.

Keywords: federated learning, knowledge distillation, knowledge transfer, deep learning

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12860 Digital System Design for Strategic Improvement Planning in Education: A Socio-Technical and Iterative Design Approach

Authors: Neeley Current, Fatih Demir, Kenneth Haggerty, Blake Naughton, Isa Jahnke

Abstract:

Educational systems seek reform using data-intensive continuous improvement processes known as strategic improvement plans (SIPs). Schools turn to digital systems to monitor, analyze and report SIPs. One technical challenge of these digital systems focuses on integrating a highly diverse set of data sources. Another challenge is to create a learnable sociotechnical system to help administrators, principals and teachers add, manipulate and interpret data. This study explores to what extent one particular system is usable and useful for strategic planning activities and whether intended users see the benefit of the system achieve the goal of improving workflow related to strategic planning in schools. In a three-phase study, researchers used sociotechnical design methods to understand the current workflow, technology use, and processes of teachers and principals surrounding their strategic improvement planning. Additionally, design review and task analysis usability methods were used to evaluate task completion, usability, and user satisfaction of the system. The resulting socio-technical models illustrate the existing work processes and indicate how and at which places in the workflow the newly developed system could have an impact. The results point to the potential of the system but also indicate that it was initially too complicated for use. However, the diverse users see the potential benefits, especially to overcome the diverse set of data sources, and that the system could fill a gap for schools in planning and conducting strategic improvement plans.

Keywords: continuous improvement process, education reform, strategic improvement planning, sociotechnical design, software development, usability

Procedia PDF Downloads 299
12859 Competitors’ Influence Analysis of a Retailer by Using Customer Value and Huff’s Gravity Model

Authors: Yepeng Cheng, Yasuhiko Morimoto

Abstract:

Customer relationship analysis is vital for retail stores, especially for supermarkets. The point of sale (POS) systems make it possible to record the daily purchasing behaviors of customers as an identification point of sale (ID-POS) database, which can be used to analyze customer behaviors of a supermarket. The customer value is an indicator based on ID-POS database for detecting the customer loyalty of a store. In general, there are many supermarkets in a city, and other nearby competitor supermarkets significantly affect the customer value of customers of a supermarket. However, it is impossible to get detailed ID-POS databases of competitor supermarkets. This study firstly focused on the customer value and distance between a customer's home and supermarkets in a city, and then constructed the models based on logistic regression analysis to analyze correlations between distance and purchasing behaviors only from a POS database of a supermarket chain. During the modeling process, there are three primary problems existed, including the incomparable problem of customer values, the multicollinearity problem among customer value and distance data, and the number of valid partial regression coefficients. The improved customer value, Huff’s gravity model, and inverse attractiveness frequency are considered to solve these problems. This paper presents three types of models based on these three methods for loyal customer classification and competitors’ influence analysis. In numerical experiments, all types of models are useful for loyal customer classification. The type of model, including all three methods, is the most superior one for evaluating the influence of the other nearby supermarkets on customers' purchasing of a supermarket chain from the viewpoint of valid partial regression coefficients and accuracy.

Keywords: customer value, Huff's Gravity Model, POS, Retailer

Procedia PDF Downloads 126
12858 The Mechanism Underlying Empathy-Related Helping Behavior: An Investigation of Empathy-Attitude- Action Model

Authors: Wan-Ting Liao, Angela K. Tzeng

Abstract:

Empathy has been an important issue in psychology, education, as well as cognitive neuroscience. Empathy has two major components: cognitive and emotional. Cognitive component refers to the ability to understand others’ perspectives, thoughts, and actions, whereas emotional component refers to understand how others feel. Empathy can be induced, attitude can then be changed, and with enough attitude change, helping behavior can occur. This finding leads us to two questions: is attitude change really necessary for prosocial behavior? And, what roles cognitive and affective empathy play? For the second question, participants with different psychopathic personality (PP) traits are critical because high PP people were found to suffer only affective empathy deficit. Their cognitive empathy shows no significant difference from the control group. 132 college students voluntarily participated in the current three-stage study. Stage 1 was to collect basic information including Interpersonal Reactivity Index (IRI), Psychopathic Personality Inventory-Revised (PPI-R), Attitude Scale, Visual Analogue Scale (VAS), and demographic data. Stage two was for empathy induction with three controversial scenarios, namely domestic violence, depression with a suicide attempt, and an ex-offender. Participants read all three stories and then rewrite the stories by one of two perspectives (empathetic vs. objective). They would then complete the VAS and Attitude Scale one more time for their post-attitude and emotional status. Three IVs were introduced for data analysis: PP (High vs. Low), Responsibility (whether or not the character is responsible for what happened), and Perspective-taking (Empathic vs. Objective). Stage 3 was for the action. Participants were instructed to freely use the 17 tokens they received as donations. They were debriefed and interviewed at the end of the experiment. The major findings were people with higher empathy tend to take more action in helping. Attitude change is not necessary for prosocial behavior. The controversy of the scenarios and how familiar participants are towards target groups play very important roles. Finally, people with high PP tend to show more public prosocial behavior due to their affective empathy deficit. Pre-existing value and belief as well as recent dramatic social events seem to have a big impact and possibly reduce the effect of the independent variables (IV) in our paradigm.

Keywords: empathy, cognitive, emotional, psychopathy

Procedia PDF Downloads 133
12857 Navigating a Changing Landscape: Opportunities for Research Managers

Authors: Samba Lamine Cisse, Cheick Oumar Tangara, Seynabou Sissoko, Mahamadou Diakite, Seydou Doumbia

Abstract:

Introduction: Over the past two decades, the world has been constantly changing, with new trends in project management. These trends are transforming the methods and priorities of research project management. They include the rise of digital technologies, multidisciplinary, open science, and the pressure for high-impact results. Managers, therefore, find themselves at a crossroads between the challenges and opportunities offered by these new trends. This paper aims to identify the challenges and opportunities they face while proposing strategies for effectively navigating this dynamic context. Methodology: This is a qualitative study based on an analysis of the challenges and opportunities facing the University Clinical Research Center in terms of new technologies and project management methods. This blended approach provides an overview of emerging trends and practices. Results: This article shows how research managers can turn new research trends in their favor and how they can adapt to the changes they face to optimize the productivity of research teams while ensuring the quality and ethics of the work. It also explores the importance of developing skills in data management, international collaboration, and innovation management. Finally, it proposes strategies for responding effectively to the challenges posed by these new trends while strengthening the position of research managers as essential facilitators of scientific progress. Conclusion: Navigating this changing landscape requires research managers to be highly flexible and able to anticipate the realities of their institution. By adopting modern project management methodologies and cultivating a culture of innovation, they can turn challenges into opportunities and propel research toward new horizons. This paper provides a strategic framework for overcoming current obstacles and capitalizing on future developments in research.

Keywords: new trends, research management, opportunities, challenges

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12856 Knowledge of Trauma-Informed Practice: A Mixed Methods Exploratory Study with Educators of Young Children

Authors: N. Khodarahmi, L. Ford

Abstract:

Decades of research on the impact of trauma in early childhood suggest severe risks to the mental health, emotional, social and physical development of a young child. Trauma-exposed students can pose a variety of different levels of challenges to schools and educators of young children and to date, few studies have addressed ECE teachers’ role in providing trauma support. The present study aims to contribute to this literature by exploring the beliefs of British Columbia’s (BC) early childhood education (ECE) teachers in their level of readiness and capability to work within a trauma-informed practice (TIP) framework to support their trauma-exposed students. Through a sequential, mix-methods approach, a self-report questionnaire and semi-structured interviews will be used to gauge BC ECE teachers’ knowledge of TIP, their preparedness, and their ability in using this framework to support their most vulnerable students. Teacher participants will be recruited through the ECEBC organization and various school districts in the Greater Vancouver Area. Questionnaire data will be primarily collected through an online survey tool whereas interviews will be taking place in-person and audio-recorded. Data analysis of survey responses will be largely descriptive, whereas interviews, once transcribed, will be employing thematic content analysis to generate themes from teacher responses. Ultimately, this study hopes to highlight the necessity of utilizing the TIP framework in BC ECE classrooms in order to support both trauma-exposed students and provide essential resources to compassionate educators of young children.

Keywords: early childhood education, early learning classrooms, refugee students, trauma-exposed students, trauma-informed practice

Procedia PDF Downloads 142
12855 Optimizing Nitrogen Fertilizer Application in Rice Cultivation: A Decision Model for Top and Ear Dressing Dosages

Authors: Ya-Li Tsai

Abstract:

Nitrogen is a vital element crucial for crop growth, significantly influencing crop yield. In rice cultivation, farmers often apply substantial nitrogen fertilizer to maximize yields. However, excessive nitrogen application increases the risk of lodging and pest infestation, leading to yield losses. Additionally, conventional flooded irrigation methods consume significant water resources, necessitating precise agricultural and intelligent water management systems. In this study, it leveraged physiological data and field images captured by unmanned aerial vehicles, considering fertilizer treatment and irrigation as key factors. Statistical models incorporating rice physiological data, yield, and vegetation indices from image data were developed. Missing physiological data were addressed using multiple imputation and regression methods, and regression models were established using principal component analysis and stepwise regression. Target nitrogen accumulation at key growth stages was identified to optimize fertilizer application, with the difference between actual and target nitrogen accumulation guiding recommendations for ear dressing dosage. Field experiments conducted in 2022 validated the recommended ear dressing dosage, demonstrating no significant difference in final yield compared to traditional fertilizer levels under alternate wetting and drying irrigation. These findings highlight the efficacy of applying recommended dosages based on fertilizer decision models, offering the potential for reduced fertilizer use while maintaining yield in rice cultivation.

Keywords: intelligent fertilizer management, nitrogen top and ear dressing fertilizer, rice, yield optimization

Procedia PDF Downloads 89
12854 Epidemiological profile of Tuberculosis Disease in Meknes, Morocco. Descriptive analysis, 2016-2020

Authors: Authors: A. Lakhal, M. Bahalou, A. Khattabi

Abstract:

Introduction: Tuberculosis is one of the world's deadliest infectious diseases. In Morocco, a total of 30,636 cases of Tuberculosis, all forms combined, were reported in 2015, representing an incidence of 89 cases per 100,000 population. The number of deaths from tuberculosis (TB) was 656 cases. In the prefecture of Meknes, its incidence remains high compared to the national level. The objective of this work is to describe the epidemiological profile of tuberculosis in the prefecture of Meknes. Methods: It is a descriptive analysis of TB cases reported between 2016 and 2020 at the regional diagnostic center of tuberculosis and respiratory diseases. We performed analysis by using Microsoft Excel and EpiInfo 7. Results: Epidemiological data from 2016 to 2020 report a total of 4100 new cases of all forms of tuberculosis, with an average of 820 new cases per year. The median age is 32 years. There is a clear male predominance, on average 58% of cases are male and 42% female. The incidence rate of bacteriologically confirmed tuberculosis per 100,000 inhabitants has increased from 35 cases per 100,000 inhabitants in 2016 to 39.4 cases per 100,000 inhabitants in 2020. The confirmation rate for pulmonary tuberculosis decreased from 84% in 2016 to 75% in 2020. Pulmonary involvement predominates by an average of 46%, followed by lymph node involvement 29%and pleural involvement by an average of 10%. Digestive, osteoarticular, genitourinary, and meningeal involvement occurs in 8% of cases. Primary tuberculosis infection occurs in an average of 0.5% of cases. The proportion of HIV-TB co-infections was 2.8 in 2020. Conclusion: The incidence of tuberculosis in Meknes remains high compared to the national level. Thus, it is imperative to reinforce the earlier detection; improve the contact tracing, detection methods of cases for their confirmation and treatment, and to reduce the proportion of the lost to follow up as well.

Keywords: tuberculosis, epidemiological profile, meknes, morocco

Procedia PDF Downloads 159
12853 Study on Improvement the Performance of Construction Project Using Lean Principles

Authors: Sumaya Adina

Abstract:

The productivity of the construction industry has faced numerous challenges, rising costs, and scarce resources over the past forty years; therefore, one approach for improving and enhancing the framework is the use of lean techniques. Lean method outcomes from the use of a brand-form of manufacturing control in production. At a time when sustainability and efficiency are essential, lean offers a clear path to make the construction industry fit for the future. An excessive number of construction professionals and experts have efficiently optimised development initiatives using lean construction (LC) techniques to reduce waste, maximise value creation, and focus on the process that creates real added value and continuous improvement, strengthening flexibility and adaptability. The present research has been undertaken to study the improvement in the performance of construction projects using lean principles. The study work is divided into three stages. Initially, a questionnaire survey was conducted on visual management techniques to improve the performance of the construction projects. The questionnaire was distributed to civil engineers, architects, site managers, project managers, and full-time executives, with nearly 100 questionnaires shared with respondents. A total of 83 responses were received to determine the reliability of the data, and analysis was done using SPSS software. In the second stage, the impact of value stream mapping on the real-time project is determined and its performance in the form of time and cost reduction is evaluated. The case study examines a bunker-building project located in Kabul Afghanistan; the project was planned conventionally without considering the lean concepts. To reduce overall kinds of waste in the project, a plan was developed using the Vico Control software to visualize the value stream of the project. Finally, the impact of value stream mapping on the project's total cash flow is evaluated and compared by plotting the total cash flow curve using Vico software. As a result, labour costs were reduced by 33%. The duration of the project was reduced by 17% reducing the duration of the project also improved the cash flow of the entire project by 14% and increased the cash flow from negative 67% to negative 44%.

Keywords: lean construction, cost and time overrun, value stream mapping, construction effeciency

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12852 Chemiluminescent Detection of Microorganisms in Food/Drug Product Using Reducing Agents and Gold Nanoplates

Authors: Minh-Phuong Ngoc Bui, Abdennour Abbas

Abstract:

Microbial spoilage of food/drug has been a constant nuisance and an unavoidable problem throughout history that affects food/drug quality and safety in a variety of ways. A simple and rapid test of fungi and bacteria in food/drugs and environmental clinical samples is essential for proper management of contamination. A number of different techniques have been developed for detection and enumeration of foodborne microorganism including plate counting, enzyme-linked immunosorbent assay (ELISA), polymer chain reaction (PCR), nucleic acid sensor, electrical and microscopy methods. However, the significant drawbacks of these techniques are highly demand of operation skills and the time and cost involved. In this report, we introduce a rapid method for detection of bacteria and fungi in food/drug products using a specific interaction between a reducing agent (tris(2-carboxylethyl)phosphine (TCEP)) and the microbial surface proteins. The chemical reaction was transferred to a transduction system using gold nanoplates-enhanced chemiluminescence. We have optimized our nanoplates synthetic conditions, characterized the chemiluminescence parameters and optimized conditions for the microbial assay. The new detection method was applied for rapid detection of bacteria (E.coli sp. and Lactobacillus sp.) and fungi (Mucor sp.), with limit of detection as low as single digit cells per mL within 10 min using a portable luminometer. We expect our simple and rapid detection method to be a powerful alternative to the conventional plate counting and immunoassay methods for rapid screening of microorganisms in food/drug products.

Keywords: microorganism testing, gold nanoplates, chemiluminescence, reducing agents, luminol

Procedia PDF Downloads 301
12851 The Use of Microbiological Methods to Reduce Aflatoxin M1 in Cheese

Authors: Bruna Goncalves, Jennifer Henck, Romulo Uliana, Eliana Kamimura, Carlos Oliveira, Carlos Corassin

Abstract:

Studies have shown evidence of human exposure to aflatoxin M1 due to the consumption of contaminated milk and dairy products (mainly cheeses). This poses a great risk to public health, since milk and milk products are frequently consumed by a portion of the population considered immunosuppressed, children and the elderly. Knowledge of the negative impacts of aflatoxins on health and economics has led to investigations of strategies to prevent their formation in food, as well as to eliminate, inactivate or reduce the bioavailability of these toxins in contaminated products This study evaluated the effect of microbiological methods using lactic acid bacteria on aflatoxin M1 (AFM1) reduction in Minas Frescal cheese (typical Brazilian product, being among the most consumed cheeses in Brazil) spiked with 1 µg/L AFM1. Inactivated lactic acid bacteria (0,5%, v/v de L. rhamnosus e L. lactis) were added during the cheese production process. Nine cheeses were produced, divided into three treatments: negative controls (without AFM1 or lactic acid bacteria), positive controls (AFM1 only), and lactic acid bacteria + AFM1. Samples of cheese were collected on days 2, 10, 20 and 30 after the date of production and submitted to composition analyses and determination of AFM1 by high-performance liquid chromatography. The reductions of AFM1 in cheese by lactic acid bacteria at the end of the trial indicate a potential application of inactivated lactic acid bacteria in reducing the bioavailability of AFM1 in Minas frescal cheese without physical-chemical and microbiological modifications during the 30-day experimental period. The authors would like to thank São Paulo Research Foundation – FAPESP (grants #2017/20081-6 and #2017/19683-1).

Keywords: aflatoxin, milk, minas frescal cheese, decontamination

Procedia PDF Downloads 197
12850 Soil-Less Misting System: A Technology for Hybrid Seed Production in Tomato (Lycopersicon esculentum Mill.).

Authors: K. D. Rajatha, S. Rajendra Prasad, N. Nethra

Abstract:

Aeroponics is one of the advanced techniques to cultivate plants without soil with minimal water and nutrient consumption. This is the technology which could bring the vertical growth in agriculture. It is an eco-friendly approach widely used for commercial cultivation of vegetables to obtain the supreme quality and yield. In this context, to harvest potentiality of the technology, an experiment was designed to evaluate the suitability of the aeroponics method over the conventional method for hybrid seed production of tomato. The experiment was carried out under Completely Randomized Design with Factorial (FCRD) concept with three replications during the year 2017-18 at UAS, GKVK Bengaluru. Nutrients and pH were standardized; among the six different nutrient solutions, the crop performance was better in Hoagland’s solution with pH between 5.5-7. The results of the present study revealed that between TAG1F and TAG2F parental lines, TAG1F performed better in both the methods of seed production. Among the methods, aeroponics showed better performance for the quality parameters except for plant spread, due to better availability of nutrients and aeration, huge root biomass in aeroponics. Aeroponics method showed significantly higher plant length (124.9 cm), plant growth rate (0.669), seedling survival rate (100%), early flowering (27.5 days), highest fruit weight (121.5 g), 100 seed weight (0.373 g) and total seed yield plant⁻¹ (11.68 g) compared to the conventional method. By providing the best environment for plant growth, the genetically best possible plant could be grown, thus complete potentiality of the plant could be harvested. Hence, aeroponics could be a promising tool for quality and healthy hybrid seed production throughout the year within protected cultivation.

Keywords: aeroponics, Hoagland’s solution, hybrid seed production, Lycopersicon esculentum

Procedia PDF Downloads 104
12849 Tool for Maxillary Sinus Quantification in Computed Tomography Exams

Authors: Guilherme Giacomini, Ana Luiza Menegatti Pavan, Allan Felipe Fattori Alves, Marcela de Oliveira, Fernando Antonio Bacchim Neto, José Ricardo de Arruda Miranda, Seizo Yamashita, Diana Rodrigues de Pina

Abstract:

The maxillary sinus (MS), part of the paranasal sinus complex, is one of the most enigmatic structures in modern humans. The literature has suggested that MSs function as olfaction accessories, to heat or humidify inspired air, for thermoregulation, to impart resonance to the voice and others. Thus, the real function of the MS is still uncertain. Furthermore, the MS anatomy is complex and varies from person to person. Many diseases may affect the development process of sinuses. The incidence of rhinosinusitis and other pathoses in the MS is comparatively high, so, volume analysis has clinical value. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure, which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust, and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression, and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to quantify MS volume proved to be robust, fast, and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to automatically quantify MS volume proved to be robust, fast and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases.

Keywords: maxillary sinus, support vector machine, region growing, volume quantification

Procedia PDF Downloads 504