Search results for: disease modeling

Authors: Farzaneh Badinlou, Reza Kormi-Nouri, Monika Knopf, Kamal Kharrazi

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When we teach, we have two critical elements at our disposal to help students: learning styles as well as testing styles. There are many different ways in which educators can effectively teach their students; verbal learning and experience-based learning. Lecture as a form of verbal learning style is a traditional arrangement in which teachers are more active and share information verbally with students. In experienced-based learning as the process of through, students learn actively through hands-on learning materials and observing teachers or others. Meanwhile, standard testing or assessment is the way to determine progress toward proficiency. Teachers and instructors mainly use essay (requires written responses), multiple choice questions (includes the correct answer and several incorrect answers as distractors), or open-ended questions (respondents answers it with own words). The current study focused on exploring an effective teaching style and testing methods as the function of age over school ages. In the present study, totally 410 participants were selected randomly from four grades (2ⁿᵈ, 4ᵗʰ, 6ᵗʰ, and 8ᵗʰ). Each subject was tested individually in one session lasting around 50 minutes. In learning tasks, the participants were presented three different instructions for learning materials (learning by doing, learning by observing, and learning by listening). Then, they were tested via different standard assessments as free recall, cued recall, and recognition tasks. The results revealed that generally students remember more of what they do and what they observe than what they hear. The age effect was more pronounced in learning by doing than in learning by observing, and learning by listening, becoming progressively stronger in the free-recall, cued-recall, and recognition tasks. The findings of this study indicated that learning by doing and free recall task is more age sensitive, suggesting that both of them are more strategic and more affected by developmental differences. Pedagogically, these results denoted that learning by modeling and engagement in program activities have the special role for learning. Moreover, the findings indicated that the multiple-choice questions can produce the best performance for school-aged children but is less age-sensitive. By contrast, the essay as essay can produce the lowest performance but is more age-sensitive. It will be very helpful for educators to know that what types of learning styles and test methods are most effective for students in each school grade.

Keywords: experience-based learning, learning style, school-aged children, testing methods, verbal learning

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Authors: Coriolano Salvini, Ambra Giovannelli

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The use of renewable energy sources for electric power production leads to reduced CO2 emissions and contributes to improving the domestic energy security. On the other hand, the intermittency and unpredictability of their availability poses relevant problems in fulfilling safely and in a cost efficient way the load demand along the time. Significant benefits in terms of “grid system applications”, “end-use applications” and “renewable applications” can be achieved by introducing energy storage systems. Among the currently available solutions, CAES (Compressed Air Energy Storage) shows favorable features. Small-medium size plants equipped with artificial air reservoirs can constitute an interesting option to get efficient and cost-effective distributed energy storage systems. The present paper is addressed to the design and off-design analysis of the compression system of small size CAES plants suited to absorb electric power in the range of hundreds of kilowatt. The system of interest is constituted by an intercooled (in case aftercooled) multi-stage reciprocating compressor and a man-made reservoir obtained by connecting large diameter steel pipe sections. A specific methodology for the system preliminary sizing and off-design modeling has been developed. Since during the charging phase the electric power absorbed along the time has to change according to the peculiar CAES requirements and the pressure ratio increases continuously during the filling of the reservoir, the compressor has to work at variable mass flow rate. In order to ensure an appropriately wide range of operations, particular attention has been paid to the selection of the most suitable compressor capacity control device. Given the capacity regulation margin of the compressor and the actual level of charge of the reservoir, the proposed approach allows the instant-by-instant evaluation of minimum and maximum electric power absorbable from the grid. The developed tool gives useful information to appropriately size the compression system and to manage it in the most effective way. Various cases characterized by different system requirements are analysed. Results are given and widely discussed.

Keywords: artificial air storage reservoir, compressed air energy storage (CAES), compressor design, compression system management.

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Authors: Paresh Patel, Priya Patel, Vaidehi Sorathiya, Navin Sheth

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The aim of present work was to fabricate Salmeterol Xinafoate (SX) metered dose inhaler (MDI) for asthma and to evaluate the SX loaded solid lipid nanoparticles (SLNs) for pulmonary delivery. Solid lipid nanoparticles can be used to deliver particles to the lungs via MDI. A modified solvent emulsification diffusion technique was used to prepare Salmeterol Xinafoate loaded solid lipid nanoparticles by using compritol 888 ATO as lipid, tween 80 as surfactant, D-mannitol as cryoprotecting agent and L-leucine was used to improve aerosolization behaviour. Box-Behnken design was applied with 17 runs. 3-D surface response plots and contour plots were drawn and optimized formulation was selected based on minimum particle size and maximum % EE. % yield, in vitro diffusion study, scanning electron microscopy, X-ray diffraction, DSC, FTIR also characterized. Particle size, zeta potential analyzed by Zetatrac particle size analyzer and aerodynamic properties was carried out by cascade impactor. Pre convulsion time was examined for control group, treatment group and compare with marketed group. MDI was evaluated for leakage test, flammability test, spray test and content per puff. By experimental design, particle size and % EE found to be in range between 119-337 nm and 62.04-76.77% by solvent emulsification diffusion technique. Morphologically, particles have spherical shape and uniform distribution. DSC & FTIR study showed that no interaction between drug and excipients. Zeta potential shows good stability of SLNs. % respirable fraction found to be 52.78% indicating reach to the deep part of lung such as alveoli. Animal study showed that fabricated MDI protect the lungs against histamine induced bronchospasm in guinea pigs. MDI showed sphericity of particle in spray pattern, 96.34% content per puff and non-flammable. SLNs prepared by Solvent emulsification diffusion technique provide desirable size for deposition into the alveoli. This delivery platform opens up a wide range of treatment application of pulmonary disease like asthma via solid lipid nanoparticles.

Keywords: salmeterol xinafoate, solid lipid nanoparticles, box-behnken design, solvent emulsification diffusion technique, pulmonary delivery

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Authors: Renata Martins Pacheco, João Claro

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Wildfires are becoming an increasing concern worldwide, causing substantial social, economic, and environmental disruptions. This situation is especially relevant in Mediterranean-climate regions, present in all the five continents of the world, in which fire is not only a natural component of the environment but also perhaps one of the most important evolutionary forces. The rise in wildfire occurrences and their associated impacts suggests the need for identifying knowledge gaps and enhancing the basis of scientific evidence on how managers and policymakers may act effectively to address them. Considering that the main goal of a systematic map is to collate and catalog a body of evidence to describe the state of knowledge for a specific topic, it is a suitable approach to be used for this purpose. In this context, the aim of this study is to systematically map the research trends in wildfire management practices in Mediterranean-climate regions. A total of 201 wildfire management studies were analyzed and systematically mapped in terms of their: Year of publication; Place of study; Scientific outlet; Research area (Web of Science) or Research field (Scopus); Wildfire phase; Central research topic; Main objective of the study; Research methods; and Main conclusions or contributions. The results indicate that there is an increasing number of studies being developed on the topic (most from the last 10 years), but more than half of them are conducted in few Mediterranean countries (60% of the analyzed studies were conducted in Spain, Portugal, Greece, Italy or France), and more than 50% are focused on pre-fire issues, such as prevention and fuel management. In contrast, only 12% of the studies focused on “Economic modeling” or “Human factors and issues,” which suggests that the triple bottom line of the sustainability argument (social, environmental, and economic) is not being fully addressed by fire management research. More than one-fourth of the studies had their objective related to testing new approaches in fire or forest management, suggesting that new knowledge is being produced on the field. Nevertheless, the results indicate that most studies (about 84%) employed quantitative research methods, and only 3% of the studies used research methods that tackled social issues or addressed expert and practitioner’s knowledge. Perhaps this lack of multidisciplinary studies is one of the factors hindering more progress from being made in terms of reducing wildfire occurrences and their impacts.

Keywords: wildfire, Mediterranean-climate regions, management, policy

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Authors: Z. Sun

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Health communication is essential in promoting healthy lifestyles, managing disease conditions, and eventually reducing health disparities. The key elements of successful health communication always include the development of communication strategies to engage people in thinking about their health, inform them about healthy choices, persuade them to adopt safe and healthy behaviours, and eventually achieve public health objectives. The use of 'Narrative' is recognised as a kind of health communication strategy to enhance personal and public health due to its potential persuasive effect in motivating and supporting individuals change their beliefs and behaviours by inviting them into a narrative world, breaking down their cognitive and emotional resistance and enhance their acceptance of the ideas portrayed in narratives. Meanwhile, the popularity of social media has provided a novel means of communication for both healthcare stakeholders, and a special group of active social media users (influencers) have started playing a pivotal role in providing health ‘solutions’. Such individuals are often referred to as ‘influencers’ because of their central position in the online communication system and the persuasive effect their actions may have on audiences. They may have established a positive rapport with their audience, earned trust and credibility in a specific area, and thus, their audience considers the information they delivered to be authentic and influential. To our best knowledge, to date, there is no published research that examines the effect of diabetes narratives presented by social media influencers and their impacts on health-related outcomes. The primary aim of this study is to investigate the diabetes narratives presented by social media influencers in the UK because of the new dimension they bring to health communication and the potential impact they may have on audiences' health outcomes. This study is situated within the interpretivist and narrative paradigms. A mixed methodology combining both quantitative and qualitative approaches has been adopted. Qualitative data has been derived to provide a better understanding of influencers’ personal experiences and how they construct meanings and make sense of their world, while quantitative data has been accumulated to identify key social media influencers in the UK and measure the impact of diabetes narratives on audiences. Twitter has been chosen as the social media platform to initially identify key influencers. Two groups of participants are the top 10 key social media influencers in the UK and 100 audiences of each influencer, which means a total of 1000 audiences have been invited. This paper is going to discuss, first of all, the background of the research under the context of health communication; Secondly, the necessity and contribution of this research; then, the major research questions being explored; and finally, the methods to be used.

Keywords: diabetes, health communication, narratives, social media influencers

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Authors: John-Nelson Ekumah, Selorm Yao-Say Solomon Adade, Mingming Zhong, Yufan Sun, Qiufang Liang, Muhammad Safiullah Virk, Xorlali Nunekpeku, Nana Adwoa Nkuma Johnson, Bridget Ama Kwadzokpui, Xiaofeng Ren

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Enhancing starch gel strength and stability is crucial. However, traditional gel property assessment methods are destructive, time-consuming, and resource-intensive. Thus, understanding ethanol treatment effects on kudzu starch gel strength and developing a rapid, nondestructive gel strength assessment method is essential for optimizing the treatment process and ensuring product quality consistency. This study investigated the effects of different ethanol concentrations on the microstructure of kudzu starch gels using a comprehensive microstructural analysis. We also developed a nondestructive method for predicting gel strength and classifying treatment levels using near-infrared (NIR) spectroscopy, and advanced data analytics. Scanning electron microscopy revealed progressive network densification and pore collapse with increasing ethanol concentration, correlating with enhanced mechanical properties. NIR spectroscopy, combined with various variable selection methods (CARS, GA, and UVE) and modeling algorithms (PLS, SVM, and ELM), was employed to develop predictive models for gel strength. The UVE-SVM model demonstrated exceptional performance, with the highest R² values (Rc = 0.9786, Rp = 0.9688) and lowest error rates (RMSEC = 6.1340, RMSEP = 6.0283). Pattern recognition algorithms (PCA, LDA, and KNN) successfully classified gels based on ethanol treatment levels, achieving near-perfect accuracy. This integrated approach provided a multiscale perspective on ethanol-induced starch gel modification, from molecular interactions to macroscopic properties. Our findings demonstrate the potential of NIR spectroscopy, coupled with advanced data analysis, as a powerful tool for rapid, nondestructive quality assessment in starch gel production. This study contributes significantly to the understanding of starch modification processes and opens new avenues for research and industrial applications in food science, pharmaceuticals, and biomaterials.

Keywords: kudzu starch gel, near-infrared spectroscopy, gel strength prediction, support vector machine, pattern recognition algorithms, ethanol treatment

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Authors: Margo O'Sullivan, Xuefeng Chen, Qi Zhao, J. Jiang, Ning Fu

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Early childhood development, or ECD, is about the 'whole child' – the physical, social and emotional, cognitive thinking and language progression of each young individual. Overwhelming evidence is now available to support investment in Early Childhood Development internationally, attendance at ECD leads to: improved learning outcomes; improved completion and reduced less dropout rates; and most notably, Professor Heckman, Nobel Laureate’s, findings that for every dollar invested, there is an economic return of up to 17%. Notably, ECD has been included in the 2015-2030 Sustainable Development Goals. The Government of China (GOC) has embraced this research and in 2010, State Council, announced focus on ECD setting a target to provide access to ECD for 85% of 3-6 year olds by 2020; to date, the target has surpassed expectations and reached 70.4%. GoC is also increasingly focusing on the even more critical 0-3 age group, when the plasticity of the brain is at its peak and neurons form connections as fast as 1,000 per second. Key to ECD are parents and caregivers of young children, with parental education critical to fully exploiting the significant potential of the early years of children. In China, with such vast numbers, one in seven pre-school age children in the world live in China, the Ministry of Education (MoE) and the National Centre for Education Technology, explored how to best provide parental education and provide key child developmental related knowledge to parents and caregivers. In response, MoE and UNICEF created a resource for parenting information that began with a computer website in 2012, followed by piloting a kiosk service in 2013 for parents in remote areas without access to the internet, and then a mobile phone application in 2014. The resource includes 269 ECD messages and 200 micro-videos covering critical issues of early childhood development from birth to age 6 years: daily care, nutrition and feeding, disease prevention, immunization, development and education, and safety and protection. To date, there have been 397,599 unique views on the website, and data for the mobile app currently being analysed (Links: http://yuer.cbern.gov.cn/; App: https://appsto.re/cn/OiKPZ.i). This paper will explore the development of this resource, its use by parents and the public, efforts to assess the effectiveness in improving parenting and child development, and future plans to roll an updated version in 2016 to all parents.

Keywords: early childhood development, mobile apps for education, parental education, China

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Authors: Uswah Ahmad Khan, Muhammad Moazam Fraz, Humayoon Shafique Satti, Qasim Aziz

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Approximately 10-14% of the global population experiences a functional disorder known as irritable bowel syndrome (IBS). The disorder is defined by persistent abdominal pain and an irregular bowel pattern. IBS significantly impairs work productivity and disrupts patients' daily lives and activities. Although IBS is widespread, there is still an incomplete understanding of its underlying pathophysiology. This study aims to help characterize the phenotype of IBS patients by differentiating the comorbidities found in IBS patients from those in non-IBS patients using machine learning algorithms. In this study, we extracted samples coding for IBS from the UK BioBank cohort and randomly selected patients without a code for IBS to create a total sample size of 18,000. We selected the codes for comorbidities of these cases from 2 years before and after their IBS diagnosis and compared them to the comorbidities in the non-IBS cohort. Machine learning models, including Decision Trees, Gradient Boosting, Support Vector Machine (SVM), AdaBoost, Logistic Regression, and XGBoost, were employed to assess their accuracy in predicting IBS. The most accurate model was then chosen to identify the features associated with IBS. In our case, we used XGBoost feature importance as a feature selection method. We applied different models to the top 10% of features, which numbered 50. Gradient Boosting, Logistic Regression and XGBoost algorithms yielded a diagnosis of IBS with an optimal accuracy of 71.08%, 71.427%, and 71.53%, respectively. Among the comorbidities most closely associated with IBS included gut diseases (Haemorrhoids, diverticular diseases), atopic conditions(asthma), and psychiatric comorbidities (depressive episodes or disorder, anxiety). This finding emphasizes the need for a comprehensive approach when evaluating the phenotype of IBS, suggesting the possibility of identifying new subsets of IBS rather than relying solely on the conventional classification based on stool type. Additionally, our study demonstrates the potential of machine learning algorithms in predicting the development of IBS based on comorbidities, which may enhance diagnosis and facilitate better management of modifiable risk factors for IBS. Further research is necessary to confirm our findings and establish cause and effect. Alternative feature selection methods and even larger and more diverse datasets may lead to more accurate classification models. Despite these limitations, our findings highlight the effectiveness of Logistic Regression and XGBoost in predicting IBS diagnosis.

Keywords: comorbidities, disease association, irritable bowel syndrome (IBS), predictive analytics

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Authors: Lillian Musila, Valerie Oundo, Daniel Erwin, Willie Sang

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Staphylococcus aureus infections are a major cause of nosocomial infections in Kenya. Methicillin resistant S. aureus (MRSA) infections are a significant burden to public health and are associated with considerable morbidity and mortality. At a hospital in Western Kenya two clusters of MRSA cases emerged within short periods of time. In this study we explored whether these clusters represented a nosocomial outbreak by characterizing the isolates using phenotypic and molecular assays and examining epidemiological data to identify possible transmission patterns. Specimens from the site of infection of the subjects were collected, cultured and S. aureus isolates identified phenotypically and confirmed by APIStaph™. MRSA were identified by cefoxitin disk screening per CLSI guidelines. MRSA were further characterized based on their antibiotic susceptibility patterns and spa gene typing. Characteristics of cases with MRSA isolates were compared with those with MSSA isolated around the same time period. Two cases of MRSA infection were identified in the two week period between 21 April and 4 May 2015. A further 2 MRSA isolates were identified on the same day on 7 September 2015. The antibiotic resistance patterns of the two MRSA isolates in the 1st cluster of cases were different suggesting that these were distinct isolates. One isolate had spa type t2029 and the other had a novel spa type. The 2 isolates were obtained from urine and an open skin wound. In the 2nd cluster of MRSA isolates, the antibiotic susceptibility patterns were similar but isolates had different spa types: one was t037 and the other a novel spa type different from the novel MRSA spa type in the first cluster. Both cases in the second cluster were admitted into the hospital but one infection was community- and the other hospital-acquired. Only one of the four MRSA cases was classified as an HAI from an infection acquired post-operatively. When compared to other S. aureus strains isolated within the same time period from the same hospital only one spa type t2029 was found in both MRSA and non-MRSA strains. None of the cases infected with MRSA in the two clusters shared any common epidemiological characteristic such as age, sex or known risk factors for MRSA such as prolonged hospitalization or institutionalization. These data suggest that the observed MRSA clusters were multi strain clusters and not an outbreak of a single strain. There was no clear relationship between the isolates by spa type suggesting that no transmission was occurring within the hospital between these cluster cases but rather that the majority of the MRSA strains were circulating in the community. There was high diversity of spa types among the MRSA strains with none of the isolates sharing spa types. Identification of disease clusters in space and time is critical for immediate infection control action and patient management. Spa gene typing is a rapid way of confirming or ruling out MRSA outbreaks so that costly interventions are applied only when necessary.

Keywords: cluster, Kenya, MRSA, spa typing

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Authors: Newton Muhury, Armando A. Apan, Tek Maraseni

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This study modelled the relationships between vegetation response and available water below the soil surface using the Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS) generated Normalised Difference Vegetation Index (NDVI) and soil water content (SWC) data. The Soil & Water Assessment Tool (SWAT) interface known as ArcSWAT was used in ArcGIS for the groundwater analysis. The SWAT model was calibrated and validated in SWAT-CUP software using 10 years (2001-2010) of monthly streamflow data. The average Nash-Sutcliffe Efficiency during the calibration and validation was 0.54 and 0.51, respectively, indicating that the model performances were good. Twenty years (2001-2020) of monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) and soil water content for 43 sub-basins were analysed using the WEKA, machine learning tool with a selection of two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The modelling results show that different types of vegetation response and soil water content vary in the dry and wet season. For example, the model generated high positive relationships (r=0.76, 0.73, and 0.81) between the measured and predicted NDVI values of all vegetation in the study area against the groundwater flow (GW), soil water content (SWC), and the combination of these two variables, respectively, during the dry season. However, these relationships were reduced by 36.8% (r=0.48) and 13.6% (r=0.63) against GW and SWC, respectively, in the wet season. On the other hand, the model predicted a moderate positive relationship (r=0.63) between shrub vegetation type and soil water content during the dry season, which was reduced by 31.7% (r=0.43) during the wet season. Our models also predicted that vegetation in the top location (upper part) of the sub-basin is highly responsive to GW and SWC (r=0.78, and 0.70) during the dry season. The results of this study indicate the study region is suitable for seasonal crop production in dry season. Moreover, the results predicted that the growth of vegetation in the top-point location is highly dependent on groundwater flow in both dry and wet seasons, and any instability or long-term drought can negatively affect these floodplain vegetation communities. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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Authors: Moustafa Osman Mohammed

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Integration sustainability outcomes give attention to construction ecology in the design review of urban environments to comply with Earth’s System that is composed of integral parts of the (i.e., physical, chemical and biological components). Naturally, exchange patterns of industrial ecology have consistent and periodic cycles to preserve energy flows and materials in Earth’s System. When engineering topology is affecting internal and external processes in system networks, it postulated the valence of the first-level spatial outcome (i.e., project compatibility success). These instrumentalities are dependent on relating the second-level outcome (i.e., participant security satisfaction). Construction ecology approach feedback energy from resources flows between biotic and abiotic in the entire Earth’s ecosystems. These spatial outcomes are providing an innovation, as entails a wide range of interactions to state, regulate and feedback “topology” to flow as “interdisciplinary equilibrium” of ecosystems. The interrelation dynamics of ecosystems are performing a process in a certain location within an appropriate time for characterizing their unique structure in “equilibrium patterns”, such as biosphere and collecting a composite structure of many distributed feedback flows. These interdisciplinary systems regulate their dynamics within complex structures. These dynamic mechanisms of the ecosystem regulate physical and chemical properties to enable a gradual and prolonged incremental pattern to develop a stable structure. The engineering topology of construction ecology for integration sustainability outcomes offers an interesting tool for ecologists and engineers in the simulation paradigm as an initial form of development structure within compatible computer software. This approach argues from ecology, resource savings, static load design, financial other pragmatic reasons, while an artistic/architectural perspective, these are not decisive. The paper described an attempt to unify analytic and analogical spatial modeling in developing urban environments as a relational setting, using optimization software and applied as an example of integrated industrial ecology where the construction process is based on a topology optimization approach.

Keywords: construction ecology, industrial ecology, urban topology, environmental planning

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Authors: E. Isaac, I. Jalo, Y. Alkali, A. Ajani, A. Rasaki, Y. Jibrin, K. Mustapha, A. Ayuba, S. Charanchi, H. Danlami

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Introduction: Hepatitis B infection continues to be a serious global health problem with about 2 billion people infected worldwide, many of these in sub-Saharan Africa. Nigeria is one of the countries with the highest incidence, with a prevalence of 10-15%. Methods: Records of Hepatitis B surface and envelope antigen test results in adults in Federal Teaching Hospital, Gombe between May 2000 and May 2015 were retrieved and analyzed. Findings: Adult out-patient consultations and in-patient admissions were 343,083 and 67,761 respectively, accounting for 87% of total. Hepatitis B surface antigenaemia was tested for in 23,888 adults and children. 88.9% (21240) were adults. Males constituted 56% (11902/21240) and females 44% (9211/21240). 5104 (24.0%) of tested individuals were 19-25years; 12,039 (56.7%) 26-45years; 21119 (9.0%) 46-55years; 2.8% (590/21240) and 766 (3.6%) >65years. Among adult males, 17% (2133/11902) was contributed by ages 19-25. 58% (7017/11902), 11.9% (1421/11902), 6.4% (765/11902) and 4.7% (563/11902) of males were 26-45 years old, 46-55 years old and 56-65 years and >65year old respectively. Adults aged 19-25years, 26-45 years, 46-55years, 56-65 and > 65years each constituted 32% (2966/9211); 54.4% (5009/9211); 7.4% (684/9211), 3.8% (350/9211) and 2.2% (201/9211) of females respectively. 16.2% (3431/21,240) demonstrated Hepatitis B surface antigenaemia. The sero-positivity rate was 16.9% (865//5104) between 19-25years, 21.2% (2559/12,039) among 26-45year old individuals. 17.9% (377/2111); 14.1% (83/590) and 7.3% (56/766) of 46-55year old, 56-65year old and >65year old individuals screened were seropositive. The highest sero-positivity rate was found in male young adults aged 19-25years 27.9% (398/1426) and lowest in elderly males 7.4% (28/377). HBe antigen testing rate among HbSAg seropositive individuals was 97.3% (3338/3431). Males constituted 59.7% (1992/3338) and females 40.3% (1345/3338). 25.3% (844/3338) were aged 19-25years; 61.1% (2039/3338) 26-45years; 10.2% (340/3338) 46-55years; 2.7% (90/3338) 56-65years and 0.7% >65years old. HB e antigenaemia was positive in 8.2% (275/3338) of those tested. 41% (113/275); 50.2% (138/275); 5.4% (15/275); 1.8% (5/275) and 1.1 (3/275) of HB e sero-positivity was among age groups 19-25, 26-45, 46-55, 56-65 and > 65year old individuals. Dual sero-positivity rate was highest 13% (113/844) in young adults 19-25years and lowest between 46-55years; 15/340 (4.4%). 4.2% (15/360); 13.5% (69/512); 6.7% (90/1348); 4.6% (10/214); 5% (2/40) and 6.7% (1/15) of males aged 19-25; 26-45; 46-55; 56-65; and >65years had HB e antigenaemia respectively. Among females - 27/293 (9.2%) aged 19-25; 26/500 (5.2%) 26-45; 2/84 (2.4%) 46-55; 1/12 (8.3%) 56-65 and 1/9(11.1%) >65years had dual antigenaemia. In women of childbearing age, 6.9% (53/793) had a dual carriage. Conclusion: Dual hepatitis B surface and envelope antigenaemia are highest in young adult males. This will have significant implications for the development of chronic liver disease and hepatocellular carcinoma.

Keywords: adult, Hepatitis B, Nigeria, dual carriage

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Authors: Maria Sciammarella, Uttam M. Shrestha, Youngho Seo, Grant T. Gullberg, Elias H. Botvinick

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Background: Myocardial perfusion imaging (MPI) is typically performed with static imaging protocols and visually assessed for perfusion defects based on the relative intensity distribution. Dynamic cardiac SPECT, on the other hand, is a new imaging technique that is based on time varying information of radiotracer distribution, which permits quantification of myocardial blood flow (MBF). In this abstract, we report a progress and current status of dynamic cardiac SPECT using conventional gamma camera (Infinia Hawkeye 4, GE Healthcare) for estimation of myocardial blood flow and coronary flow reserve. Methods: A group of patients who had high risk of coronary artery disease was enrolled to evaluate our methodology. A low-dose/high-dose rest/pharmacologic-induced-stress protocol was implemented. A standard rest and a standard stress radionuclide dose of ⁹⁹ᵐTc-tetrofosmin (140 keV) was administered. The dynamic SPECT data for each patient were reconstructed using the standard 4-dimensional maximum likelihood expectation maximization (ML-EM) algorithm. Acquired data were used to estimate the myocardial blood flow (MBF). The correspondence between flow values in the main coronary vasculature with myocardial segments defined by the standardized myocardial segmentation and nomenclature were derived. The coronary flow reserve, CFR, was defined as the ratio of stress to rest MBF values. CFR values estimated with SPECT were also validated with dynamic PET. Results: The range of territorial MBF in LAD, RCA, and LCX was 0.44 ml/min/g to 3.81 ml/min/g. The MBF between estimated with PET and SPECT in the group of independent cohort of 7 patients showed statistically significant correlation, r = 0.71 (p < 0.001). But the corresponding CFR correlation was moderate r = 0.39 yet statistically significant (p = 0.037). The mean stress MBF value was significantly lower for angiographically abnormal than that for the normal (Normal Mean MBF = 2.49 ± 0.61, Abnormal Mean MBF = 1.43 ± 0. 0.62, P < .001). Conclusions: The visually assessed image findings in clinical SPECT are subjective, and may not reflect direct physiologic measures of coronary lesion. The MBF and CFR measured with dynamic SPECT are fully objective and available only with the data generated from the dynamic SPECT method. A quantitative approach such as measuring CFR using dynamic SPECT imaging is a better mode of diagnosing CAD than visual assessment of stress and rest images from static SPECT images Coronary Flow Reserve.

Keywords: dynamic SPECT, clinical SPECT/CT, selective coronary angiograph, ⁹⁹ᵐTc-Tetrofosmin

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Authors: Soon Young Choi, Chan Hwan Kim, Chan Hong Park, Hyung Rae Kim, Myoung Hoon Lee, Hyeon-Yeong Park

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We performed the marine magnetic, bathymetry and seismic survey at the TA22 seamount (in the Lau basin, SW Pacific) for finding the submarine hydrothermal deposits in October 2009. We acquired magnetic and bathymetry data sets by suing Overhouser Proton Magnetometer SeaSPY (Marine Magnetics Co.), Multi-beam Echo Sounder EM120 (Kongsberg Co.). We conducted the data processing to obtain detailed seabed topography, magnetic anomaly, reduction to the pole (RTP) and magnetization. Based on the magnetic properties result, we analyzed submarine geology structure of TA22 seamount with post-processed seismic profile. The detailed bathymetry of the TA22 seamount showed the left and right crest parts that have caldera features in each crest central part. The magnetic anomaly distribution of the TA22 seamount regionally displayed high magnetic anomalies in northern part and the low magnetic anomalies in southern part around the caldera features. The RTP magnetic anomaly distribution of the TA22 seamount presented commonly high magnetic anomalies in the each caldera central part. Also, it represented strong anomalies at the inside of caldera rather than outside flank of the caldera. The magnetization distribution of the TA22 seamount showed the low magnetization zone in the center of each caldera, high magnetization zone in the southern and northern east part. From analyzed the seismic profile map, The TA22 seamount area is showed for the inferred small mounds inside each caldera central part and it assumes to make possibility of sills by the magma in cases of the right caldera. Taking into account all results of this study (bathymetry, magnetic anomaly, RTP, magnetization, seismic profile) with rock samples at the left caldera area in 2009 survey, we suppose the possibility of hydrothermal deposits at mounds in each caldera central part and at outside flank of the caldera representing the low magnetization zone. We expect to have the better results by combined modeling from this study data with the other geological data (ex. detailed gravity, 3D seismic, petrologic study results and etc).

Keywords: detailed bathymetry, magnetic anomaly, seamounts, seismic profile, SW Pacific

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Authors: A. Julio, R. Caparica, S. Costa Lima, S. Reis, J. G. Costa, P. Fonte, T. Santos De Almeida

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The Mycobacterium leprae causes a chronic and infectious disease called leprosy, which the most common symptoms are peripheral neuropathy and deformation of several parts of the body. The pharmacological treatment of leprosy is a combined therapy with three different drugs, rifampicin, clofazimine, and dapsone. However, clofazimine and dapsone have poor solubility in water and also low bioavailability. Thus, it is crucial to develop strategies to overcome such drawbacks. The use of ionic liquids (ILs) may be a strategy to overcome the low solubility since they have been used as solubility promoters. ILs are salts, liquid below 100 ºC or even at room temperature, that may be placed in water, oils or hydroalcoholic solutions. Another approach may be the encapsulation of drugs into polymeric nanoparticles, which improves their bioavailability. In this study, two different classes of ILs were used, the imidazole- and the choline-based ionic liquids, as solubility enhancers of the poorly soluble antileprotic drugs. Thus, after the solubility studies, it was developed IL-PLGA nanoparticles hybrid systems to deliver such drugs. First of all, the solubility studies of clofazimine and dapsone were performed in water and in water: IL mixtures, at ILs concentrations where cell viability is maintained, at room temperature for 72 hours. For both drugs, it was observed an improvement on the drug solubility and [Cho][Phe] showed to be the best solubility enhancer, especially for clofazimine, where it was observed a 10-fold improvement. Later, it was produced nanoparticles, with a polymeric matrix of poly(lactic-co-glycolic acid) (PLGA) 75:25, by a modified solvent-evaporation W/O/W double emulsion technique in the presence of [Cho][Phe]. Thus, the inner phase was an aqueous solution of 0.2 % (v/v) of the above IL with each drug to its maximum solubility determined on the previous study. After the production, the nanosystem hybrid was physicochemically characterized. The produced nanoparticles had a diameter of around 580 nm and 640 nm, for clofazimine and dapsone, respectively. Regarding the polydispersity index, it was in agreement of the recommended value of this parameter for drug delivery systems (around 0.3). The association efficiency (AE) of the developed hybrid nanosystems demonstrated promising AE values for both drugs, given their low solubility (64.0 ± 4.0 % for clofazimine and 58.6 ± 10.0 % for dapsone), that prospects the capacity of these delivery systems to enhance the bioavailability and loading of clofazimine and dapsone. Overall, the study achievement may signify an upgrading of the patient’s quality of life, since it may mean a change in the therapeutic scheme, not requiring doses of drug so high to obtain a therapeutic effect. The authors would like to thank Fundação para a Ciência e a Tecnologia, Portugal (FCT/MCTES (PIDDAC), UID/DTP/04567/2016-CBIOS/PRUID/BI2/2018).

Keywords: ionic liquids, ionic liquids-PLGA nanoparticles hybrid systems, leprosy treatment, solubility

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Authors: Emmanuel Ikechuckwu Onwubuya, Afees Adebayo Oladejo

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Background: The use of medicinal plants in the treatment of chronic diseases especially myocardial infarction, is gaining wide acceptance globally. Andrographis paniculata (Acanthaceae) is a medicinal plant commonly known as the king of bitters in Nigeria and has been acclaimed for several therapeutic activities. Materials and methods: This study investigated the cardio-protective effect of the leaf extract of A. paniculata in isoproterenol-induced myocardial infarction. Fresh green leaves of A paniculata were harvested from the Faculty of Agriculture farmland, Nnamdi Azikiwe University, Awka, Nigeria. Identification and authentication of the plant were carried out at the Department of Botany, Nnamdi Azikiwe University and a voucher specimen was deposited at the herbarium. The plant material was then shredded, air-dried under shade and pulverized. The fine powders obtained were weighed and extraction was done via a solvent combination of water and ethanol (3:7) for 72 hr via maceration. The filtrate gotten was evaporated to dryness to obtain the ethanol extract, which was used for further bioassay study. The bioactive constituents of the plant extract were quantitatively analyzed by Gas chromatography-mass spectrometry (GC-MS). The animals were administered the extract of A. paniculata orally for seven days at a divided dose of 100 mg/kg, 200 mg/kg and 400 mg/kg body weights. On the eighth day, myocardial infarction was induced through subcutaneous administration of isoproterenol at a dose of 150 mg/kg/day diluted in 2 ml of saline on two consecutive days. Subsequently, the blood pressures were monitored and blood was collected for bioassay studies. Results: The results of the study showed that the leaf extract of A. paniculata was rich in Dodecanoic acid (8.261%), 4-Dibenzofuranamine (6.03%), Cyclotrisiloxane (4.679 %). The findings also showed a significant decrease (p>0.05) in the Mean arterial blood pressure, heart rate, aspartate transaminase, alanine transaminase, creatinine kinase and lactate dehydrogenase activities of the treatment group compared with the untreated control group while the antioxidant (superoxide dismutase, catalase and glutathione) activities were significantly increased in the treatment group, compared with the untreated control group. Conclusion: The findings of this work have shown that the leaf of A. paniculata was rich in bioactive compounds, which could be synthesized to produce plant-based products to fight cardiovascular diseases, especially myocardial infarction.

Keywords: cardiovascular disease, myocardial infarction, medicinal plant, andrographis paniculata, isoproterenol

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Authors: Reena Aggarwal

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The use of textile chemicals in the various pre and post-textile manufacturing processes has made the textile industry conscious of its negative contribution to environmental pollution. Popular environmentally friendly fibers such as recycled polyester and organic cotton have been now increasingly used by fabrics and apparel manufacturers. However, after these textiles or the finished apparel are manufactured, they have to be dyed in the same chemical dyes that are harmful and toxic to the environment. Dyeing is a major area of concern for the environment as well as for people who have chemical sensitivities as it may cause nausea, breathing difficulties, seizures, etc. Ayurvastra or herbal medical textiles are one step ahead of the organic lifestyle, which supports the core concept of holistic well-being and also eliminates the impact of harmful chemicals and pesticides. There is a wide range of herbs that can be used not only for dyeing but also for providing medicinal properties to the textiles like antibacterial, antifungal, antiseptic, antidepressant and for treating insomnia, skin diseases, etc. The concept of herbal dyeing of fabric is to manifest herbal essence in every aspect of clothing, i.e., from production to end-use, additionally to eliminate the impact of harmful chemical dyes and chemicals which are known to result in problems like skin rashes, headache, trouble concentrating, nausea, diarrhea, fatigue, muscle and joint pain, dizziness, difficulty breathing, irregular heartbeat and seizures. Herbal dyeing or finishing on textiles will give an extra edge to the textiles as it adds an extra function to the fabric. The herbal extracts can be applied to the textiles by a simple process like the pad dry cure method and mainly acts on the human body through the skin for aiding in the treatment of disease or managing the medical condition through its herbal properties. This paper, therefore, delves into producing Ayurvastra, which is a perfect amalgamation of cloth and wellness. The aim of the paper is to design and create herbal disposable and non-disposable medical textile products acting mainly topically (through the skin) for providing medicinal properties/managing medical conditions. Keeping that in mind, a range of antifungal socks and antibacterial napkins treated with turmeric and aloe vera were developed, which are recommended for the treatment of fungal and bacterial infections, respectively. Both Herbal Antifungal socks and Antibacterial napkins have proved to be efficient enough in managing and treating fungal and bacterial infections of the skin, respectively.

Keywords: ayurvastra, ayurveda, herbal, pandemic, sustainable

Procedia PDF Downloads 118

Authors: Amritee Bora, B. S. Mipun

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Land degradation is often used to describe the land environmental phenomena that reduce land’s original productivity both qualitatively and quantitatively. The study of land degradation vulnerability primarily deals with “Environmentally Sensitive Areas” (ESA) and the amount of topsoil loss due to erosion. In many studies, it is observed that the assessment of the existing status of land degradation is used to represent the vulnerability. Moreover, it is also noticed that in most studies, the primary emphasis of land degradation vulnerability is to assess its sensitivity to soil erosion only. However, the concept of land degradation vulnerability can have different objectives depending upon the perspective of the study. It shows the extent to which changes in land use land cover can imprint their effect on the land. In other words, it represents the susceptibility of a piece of land to degrade its productive quality permanently or in the long run. It is also important to mention that the vulnerability of land degradation is not a single factor outcome. It is a probability assessment to evaluate the status of land degradation and needs to consider both biophysical and human induce parameters. To avoid the complexity of the previous models in this regard, the present study has emphasized on to generate a simplified model to assess the land degradation vulnerability in terms of its current human population pressure, land use practices, and existing biophysical conditions. It is a “Mixed-Method” termed as the land degradation vulnerability index (LDVi). It was originally inspired by the MEDALUS model (Mediterranean Desertification and Land Use), 1999, and Farazadeh’s 2007 revised version of it. It has followed the guidelines of Space Application Center, Ahmedabad / Indian Space Research Organization for land degradation vulnerability. The model integrates the climatic index (Ci), vegetation index (Vi), erosion index (Ei), land utilization index (Li), population pressure index (Pi), and cover management index (CMi) by giving equal weightage to each parameter. The final result shows that the very high vulnerable zone primarily indicates three (3) prominent circumstances; land under continuous population pressure, high concentration of human settlement, and high amount of topsoil loss due to surface runoff within the study sites. As all the parameters of the model are amalgamated with equal weightage further with the help of regression analysis, the LDVi model also provides a strong grasp of each parameter and how far they are competent to trigger the land degradation process.

Keywords: population pressure, land utilization, soil erosion, land degradation vulnerability

Procedia PDF Downloads 153

Authors: Inês N. Peça , A. Bicho, Rui Gardner, M. Margarida Cardoso

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Inorganic/organic nanocomplexes offer tremendous scope for future biomedical applications, including imaging, disease diagnosis and drug delivery. The combination of Fe3O4 with biocompatible polymers to produce smart drug delivery systems for use in pharmaceutical formulation present a powerful tool to target anti-cancer drugs to specific tumor sites through the application of an external magnetic field. In the present study, we focused on the evaluation of the effect of the magnetic field application time on the rate of drug release from iron oxide polymeric nanoparticles. Doxorubicin, an anticancer drug, was selected as the model drug loaded into the nanoparticles. Nanoparticles composed of poly(d-lactide-co-glycolide (PLGA), a biocompatible polymer already approved by FDA, containing iron oxide nanoparticles (MNP) for magnetic targeting and doxorubicin (DOX) were synthesized by the o/w solvent extraction/evaporation method and characterized by scanning electron microscopy (SEM), by dynamic light scattering (DLS), by inductively coupled plasma-atomic emission spectrometry and by Fourier transformed infrared spectroscopy. The produced particles yielded smooth surfaces and spherical shapes exhibiting a size between 400 and 600 nm. The effect of the magnetic doxorubicin loaded PLGA nanoparticles produced on cell viability was investigated in mammalian CHO cell cultures. The results showed that unloaded magnetic PLGA nanoparticles were nontoxic while the magnetic particles without polymeric coating show a high level of toxicity. Concerning the therapeutic activity doxorubicin loaded magnetic particles cause a remarkable enhancement of the cell inhibition rates compared to their non-magnetic counterpart. In vitro drug release studies performed under a non-permanent magnetic field show that the application time and the on/off cycle duration have a great influence with respect to the final amount and to the rate of drug release. In order to determine the mechanism of drug release, the data obtained from the release curves were fitted to the semi-empirical equation of the the Korsmeyer-Peppas model that may be used to describe the Fickian and non-Fickian release behaviour. Doxorubicin release mechanism has shown to be governed mainly by Fickian diffusion. The results obtained show that the rate of drug release from the produced magnetic nanoparticles can be modulated through the magnetic field time application.

Keywords: drug delivery, magnetic nanoparticles, PLGA nanoparticles, controlled release rate

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Authors: Shusmita Khan, Shams El Arifeen, Kanta Jamil

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Background: Nutrition transition in Bangladesh has progressed across various relevant socio-demographic contextual issues. For a developing country like Bangladesh, its is believed that, overnutrition is less prevalent than undernutrition. However, recent evidence suggests that a rapid shift is taking place where overweight is subduing underweight. With this rapid increase, for Bangladesh, it will be challenging to achieve the global agenda on halting overweight and obesity. Methods: A secondary analysis was performed from six successive national demographic and health surveys to get the trend on undernutrition and overnutrition for women from reproductive age. In addition, national relevant policy papers were reviewed to determine the countries readiness for whole of the systems approach to tackle this epidemic. Results: Over the last decade, the proportion of women with low body mass index (BMI<18.5), an indicator of undernutrition, has decreased markedly from 34% to 19%. However, the proportion of overweight women (BMI ≥25) increased alarmingly from 9% to 24% over the same period. If the WHO cutoff for public health action (BMI ≥23) is used, the proportion of overweight women has increased from 17% in 2004 to 39% in 2014. The increasing rate of obesity among women is a major challenge to obstetric practice for both women and fetuses. In the long term, overweight women are also at risk of future obesity, diabetes, hyperlipidemia, hypertension, and heart disease. These diseases have serious impact on health care systems. Costs associated with overweight and obesity involves direct and indirect costs. Direct costs include preventive, diagnostic, and treatment services related to obesity. Indirect costs relate to morbidity and mortality costs including productivity. Looking at the Bangladesh Health Facility Survey, it is found that the country is bot prepared for providing nutrition-related health services, regarding prevention, screening, management and treatment. Therefore, if this nutrition transition is not addressed properly, Bangladesh will not be able to achieve the target of the NCD global monitoring framework of the WHO. Conclusion: Addressing this nutrition transition requires contending ‘malnutrition in all its forms’ and addressing it with integrated approaches. Whole of the systems action is required at all levels—starting from improving multi-sectoral coordination to scaling up nutrition-specific and nutrition-sensitive mainstreamed interventions keeping health system in mind.

Keywords: nutrition transition, Bangladesh, health system, undernutrition, overnutrition, obesity

Procedia PDF Downloads 273

Authors: Angel Champion

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Chemotherapy and radiation use an acidified approach to induce apoptosis, which only kills mature cancer cells while resulting in gene and cell damage with significant levels of toxicity in tumor-affected tissues and organs. The acid approach, where the cells exterminated are not differentiated, induces the disappearance of white blood cells from the blood. This increases susceptibility to infection in severe forms of cancer spread. However, chemotherapy and radiation cannot kill cancer stem cells that metastasize, being the leading cause of 98% of cancer fatalities. With over 12 million new cancer cases symptomatic each year, including common malignancies such as Hepatocellular Carcinoma (HCC), this study aims to assess the bioactive constituents and phytochemical composition of Taraxacum Officinale (Dandelion). This analysis enables pharmaceutical quality and potency to be applied to studies on cancer cell proliferation and apoptosis. A phytochemical screening is carried out to identify the antioxidant components of Dandelion root, stem, and flower extract. The constituents tested for are phlorotannins, carbohydrates, glycosides, saponins, flavonoids, alkaloids, sterols, triterpenes, and anthraquinone glycosides. To conserve the existing phenolic compounds, a portion of the constituent tests will be examined with an acid, alcohol, or aqueous solvent. As a result, the qualitative and quantitative variations within the Dandelion extract that measure uniform effective potency are vital to the conformity for producing medicinal products. These medicines will be constructed with a consistent, uniform composition that physicians can use to control and effectively eradicate malignant diseases safely. Taraxacum Officinale's phytochemical composition comprises a highly-graded potency due to present bioactive contents that will essentially drive out malignant disease within the human body. Its high potency rate is powerful enough to eliminate both mature cancer cells and cancer stem cells without the cell and gene damage induced by chemotherapy and radiation. Correspondingly, the high margins of cancer mortality on a global scale are mitigated. This remarkable contribution to modern therapeutics will essentially optimize the margins of natural products and their derivatives, which account for 50% of pharmaceuticals in modern therapeutics, while preventing the adverse effects of radiation and chemotherapy drugs.

Keywords: antioxidant, apoptosis, metastasize, phytochemical, proliferation, potency

Procedia PDF Downloads 58

Authors: Bao Li, Aike Qiao, Gaoyang Li, Youjun Liu

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Background: Lumped parameter model (LPM) is a common numerical model for hemodynamic calculation. LPM uses circuit elements to simulate the human blood circulatory system. Physiological indicators and characteristics can be acquired through the model. However, due to the different physiological indicators of each individual, parameters in LPM should be personalized in order for convincing calculated results, which can reflect the individual physiological information. This study aimed to develop an automatic and effective optimization method to personalize the parameters in LPM of the blood circulatory system, which is of great significance to the numerical simulation of individual hemodynamics. Methods: A closed-loop LPM of the human blood circulatory system that is applicable for most persons were established based on the anatomical structures and physiological parameters. The patient-specific physiological data of 5 volunteers were non-invasively collected as personalized objectives of individual LPM. In this study, the blood pressure and flow rate of heart, brain, and limbs were the main concerns. The collected systolic blood pressure, diastolic blood pressure, cardiac output, and heart rate were set as objective data, and the waveforms of carotid artery flow and ankle pressure were set as objective waveforms. Aiming at the collected data and waveforms, sensitivity analysis of each parameter in LPM was conducted to determine the sensitive parameters that have an obvious influence on the objectives. Simulated annealing was adopted to iteratively optimize the sensitive parameters, and the objective function during optimization was the root mean square error between the collected waveforms and data and simulated waveforms and data. Each parameter in LPM was optimized 500 times. Results: In this study, the sensitive parameters in LPM were optimized according to the collected data of 5 individuals. Results show a slight error between collected and simulated data. The average relative root mean square error of all optimization objectives of 5 samples were 2.21%, 3.59%, 4.75%, 4.24%, and 3.56%, respectively. Conclusions: Slight error demonstrated good effects of optimization. The individual modeling algorithm developed in this study can effectively achieve the individualization of LPM for the blood circulatory system. LPM with individual parameters can output the individual physiological indicators after optimization, which are applicable for the numerical simulation of patient-specific hemodynamics.

Keywords: blood circulatory system, individual physiological indicators, lumped parameter model, optimization algorithm

Procedia PDF Downloads 128

Authors: Suleman Maliha, Suleman Sidra

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Obstructive sleep apnea (OSA) is a sleep disorder that can result in behavioral and psychomotor impairments in children. The classical treatment modalities for OSA have been continuous positive airway pressure and adenotonsillectomy. However, orthodontic intervention through rapid maxillary expansion (RME) has also been commonly used to manage skeletal transverse maxillary discrepancies. Aim and objectives: The aim of this study is to determine the efficacy of rapid maxillary expansion in paediatric patients with obstructive sleep apnea by assessing pre and post-treatment mean apnea-hypopnea index (AHI) and oxygen saturations. Methodology: Literature was identified through a rigorous search of the Embase, Pubmed, and CINAHL databases. Articles published from 2012 onwards were selected. The inclusion criteria consisted of patients aged 18 years and under with no systemic disease, adenotonsillar surgery, or hypertrophy who are undergoing RME with AHI measurements before and after treatment. In total, six suitable papers were identified. Results: Three studies assessed patients pre and post-RME at 12 months. The first study consisted of 15 patients with an average age of 7.5 years. Following treatment, they found that RME resulted in both higher oxygen saturations (+ 5.3%) and improved AHI (- 4.2 events). The second study assessed 11 patients aged 5–8 years and also noted improvements, with mean AHI reduction from 6.1 to 2.4 and oxygen saturations increasing from 93.1% to 96.8%. The third study reviewed 14 patients aged 6–9 years and similarly found an AHI reduction from 5.7 to 4.4 and an oxygen saturation increase from 89.8% to 95.5%. All modifications noted in these studies were statistically significant. A long-term study reviewed 23 patients aged 6–12 years post-RME treatment on an annual basis for 12 years. They found that the mean AHI reduced from 12.2 to 0.4, with improved oxygen saturations from 78.9% to 95.1%. Another study assessed 19 patients aged 9-12 years at two months into RME and four months post-treatment. Improvements were also noted at both stages, with an overall reduction of the mean AHI from 16.3 to 0.8 and an overall increase in oxygen saturations from 77.9% to 95.4%. The final study assessed 26 children aged 7-11 years on completion of individual treatment and found an AHI reduction from 6.9 to 5.3. However, the oxygen saturation remained stagnant at 96.0%, but this was not clinically significant. Conclusion: Overall, the current evidence suggests that RME is a promising treatment option for paediatric patients with OSA. It can provide efficient and conservative treatment; however, early diagnosis is crucial. As there are various factors that could be contributing to OSA, it is important that each case is treated on its individual merits. Going forward, there is a need for more randomized control trials with larger cohorts being studied. Research into the long-term effects of RME and potential relapse amongst cases would also be useful.

Keywords: orthodontics, sleep apnea, maxillary expansion, review

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Authors: N. Khursheed, M. Fatima, S. Jamal, A. Raza, S. Rattani, Q. Ahsan, A. Rasheed, M. Jawed

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Introduction: Antibiotics are among the commonly prescribed medicines to treat bacterial infections. Their misuse intensifies resistance, and overuse incurs heavy losses to the healthcare system in terms of increased treatment costs and enhanced disease burden. Studies show that 40% of empirically used antibiotics are irrationally utilized. The objective of this study was to evaluate prescribing pattern of antibiotics at six public sector tertiary care hospitals across Pakistan. Methods: A multicenter cross-sectional point prevalence survey (PPS) was conducted in selected wards of six public sector tertiary care hospitals in Pakistan as part of the Clinical Engagement program by Fleming Fund Country Grant Pakistan in collaboration with Indus Hospital & Health Network (IHHN) from February to March 2021, these included Jinnah Postgraduate Medical Center and Dr. Ruth K. M. Pfau Civil Hospital from Karachi, Sheikh Zayed Hospital Lahore, Nishtar Medical University Hospital Multan, Medical Teaching Institute Hayatabad Medical Complex Peshawar, and Provincial Headquarters Hospital Gilgit. WHO PPS methodology was used for data collection (Hospital, ward, and patient level data was collected). Data was entered into the open-source Kobo Collect application and was analyzed using SPSS (version 22.0). Findings: Medical records of 837 in-patients were surveyed, of which the prevalence of antibiotics use was 78.5%. The most commonly prescribed antimicrobial was Ceftriaxone (21.7%) which is categorized in the Watch group of WHO AWaRe Classification, followed by Metronidazole (17.3%), Cefoperazone/Sulbactam (8.4%), Co-Amoxiclav (6.3%) and Piperacillin/Tazobactam (5.9%). The antibiotics were prescribed largely for surgical prophylaxis (36.7%), followed by community-acquired infections (24.7%). One antibiotic was prescribed to 46.7%, two to 39.9%, and three or more to 12.5 %. Two of six (30%) hospitals had functional drug and therapeutic committees, three (50%) had infection prevention and control committees, and one facility had an antibiotic formulary. Conclusion: Findings demonstrate high consumption of broad-spectrum antimicrobials and emphasizes the importance of expanding the antimicrobial stewardship program. Mentoring clinical teams will help to rationalize antimicrobial use.

Keywords: antimicrobial resistance, antimicrobial stewardship, point prevalence survey, antibiotics

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Authors: Misuk Kim, Seokho Kang, Jehyuk Lee, Hyunchang Cho, Sungzoon Cho

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In semiconductor manufacturing, virtual metrology (VM) refers to methods to predict properties of a wafer based on machine parameters and sensor data of the production equipment, without performing the (costly) physical measurement of the wafer properties (Wikipedia). Additional benefits include avoidance of human bias and identification of important factors affecting the quality of the process which allow improving the process quality in the future. It is however rare to find VM applied to other areas of manufacturing. In this work, we propose to use VM to copper clad laminate (CCL) manufacturing. CCL is a core element of a printed circuit board (PCB) which is used in smartphones, tablets, digital cameras, and laptop computers. The manufacturing of CCL consists of three processes: Treating, lay-up, and pressing. Treating, the most important process among the three, puts resin on glass cloth, heat up in a drying oven, then produces prepreg for lay-up process. In this process, three important quality factors are inspected: Treated weight (T/W), Minimum Viscosity (M/V), and Gel Time (G/T). They are manually inspected, incurring heavy cost in terms of time and money, which makes it a good candidate for VM application. We developed prediction models of the three quality factors T/W, M/V, and G/T, respectively, with process variables, raw material, and environment variables. The actual process data was obtained from a CCL manufacturer. A variety of variable selection methods and learning algorithms were employed to find the best prediction model. We obtained prediction models of M/V and G/T with a high enough accuracy. They also provided us with information on “important” predictor variables, some of which the process engineers had been already aware and the rest of which they had not. They were quite excited to find new insights that the model revealed and set out to do further analysis on them to gain process control implications. T/W did not turn out to be possible to predict with a reasonable accuracy with given factors. The very fact indicates that the factors currently monitored may not affect T/W, thus an effort has to be made to find other factors which are not currently monitored in order to understand the process better and improve the quality of it. In conclusion, VM application to CCL’s treating process was quite successful. The newly built quality prediction model allowed one to reduce the cost associated with actual metrology as well as reveal some insights on the factors affecting the important quality factors and on the level of our less than perfect understanding of the treating process.

Keywords: copper clad laminate, predictive modeling, quality control, virtual metrology

Procedia PDF Downloads 344

Authors: Javed Mohammed

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Right now, bio-medical infrastructure lags well behind the curve. Our healthcare system is dispersed and disjointed; medical records are a bit of a mess; and we do not yet have the capacity to store and process the crazy amounts of data coming our way from widespread whole-genome sequencing. And then there are privacy issues. Despite these infrastructure challenges, some researchers are plunging into bio medical Big Data now, in hopes of extracting new and actionable knowledge. They are doing delving into molecular-level data to discover bio markers that help classify patients based on their response to existing treatments; and pushing their results out to physicians in novel and creative ways. Computer scientists and bio medical researchers are able to transform data into models and simulations that will enable scientists for the first time to gain a profound under-standing of the deepest biological functions. Solving biological problems may require High-Performance Computing HPC due either to the massive parallel computation required to solve a particular problem or to algorithmic complexity that may range from difficult to intractable. Many problems involve seemingly well-behaved polynomial time algorithms (such as all-to-all comparisons) but have massive computational requirements due to the large data sets that must be analyzed. High-throughput techniques for DNA sequencing and analysis of gene expression have led to exponential growth in the amount of publicly available genomic data. With the increased availability of genomic data traditional database approaches are no longer sufficient for rapidly performing life science queries involving the fusion of data types. Computing systems are now so powerful it is possible for researchers to consider modeling the folding of a protein or even the simulation of an entire human body. This research paper emphasizes the computational biology's growing need for high-performance computing and Big Data. It illustrates this article’s indispensability in meeting the scientific and engineering challenges of the twenty-first century, and how Protein Folding (the structure and function of proteins) and Phylogeny Reconstruction (evolutionary history of a group of genes) can use HPC that provides sufficient capability for evaluating or solving more limited but meaningful instances. This article also indicates solutions to optimization problems, and benefits Big Data and Computational Biology. The article illustrates the Current State-of-the-Art and Future-Generation Biology of HPC Computing with Big Data.

Keywords: high performance, big data, parallel computation, molecular data, computational biology

Procedia PDF Downloads 356

Authors: Yu-Wen Chen, Szu-Wei Huang, Chung-Hsiang Mu, Kelvin Cheng

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This paper developed a data-driven based model to deal with the causality between the Continuous Emission Monitoring System (CEMS, by Environmental Protection Administration, Taiwan) in industrial factories, and the air quality around environment. Compared to the heavy burden of traditional numerical models of regional weather and air pollution simulation, the lightweight burden of the proposed model can provide forecasting hourly with current observations of weather, air pollution and emissions from factories. The observation data are included wind speed, wind direction, relative humidity, temperature and others. The observations can be collected real time from Open APIs of civil IoT Taiwan, which are sourced from 439 weather stations, 10,193 qualitative air stations, 77 national quantitative stations and 140 CEMS quantitative industrial factories. This study completed a causal inference engine and gave an air pollution forecasting for the next 12 hours related to local industrial factories. The outcomes of the pollution forecasting are produced hourly with a grid resolution of 1km*1km on IIoTC (Industrial Internet of Things Cloud) and saved in netCDF4 format. The elaborated procedures to generate forecasts comprise data recalibrating, outlier elimination, Kriging Interpolation and particle tracking and random walk techniques for the mechanisms of diffusion and advection. The solution of these equations reveals the causality between factories emission and the associated air pollution. Further, with the aid of installed real-time flue emission (Total Suspension Emission, TSP) sensors and the mentioned forecasted air pollution map, this study also disclosed the converting mechanism between the TSP and PM2.5/PM10 for different region and industrial characteristics, according to the long-term data observation and calibration. These different time-series qualitative and quantitative data which successfully achieved a causal inference engine in cloud for factory management control in practicable. Once the forecasted air quality for a region is marked as harmful, the correlated factories are notified and asked to suppress its operation and reduces emission in advance.

Keywords: continuous emission monitoring system, total suspension particulates, causal inference, air pollution forecast, IoT

Procedia PDF Downloads 74

Authors: Ana M. Lara, Manuela Llano, Felipe Gaitán, Rosa H. Bustos, Ana Maria Perdomo-Arciniegas, Ximena Bonilla

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Umbilical cord blood is used as a source of progenitor and stem cells for the regeneration of the hematopoietic and immune system to treat patients with different hematological or non-hematological diseases. This stem cell source represents an advantage over the use of bone marrow or mobilized peripheral blood because it has a lower incidence rate of graft-versus-host disease, probably due to fewer immunological compatibility restrictions. However, its low cellular dose limits its use in pediatric patients. This work proposes the standardization of a cell expansion technique to compensate for the dose of infused cells through the ex-vivo manipulation of hematopoietic progenitor cells from umbilical cord blood before transplantation. The expansion model is carried out through co-cultures with mesenchymal stem cells (MSC) from bone marrow (BM) and less explored fetal tissues such as Wharton's jelly (WJ) and umbilical cord blood (UCB). Initially, a master cell bank of primary mesenchymal stem cells isolated from different sources was established and characterized following International Society of Cell Therapies (ISCT) indications. Additionally, we assessed the effect of a short 25 Gy cycle of gamma irradiation on cell cycle arrest of mesenchymal cells over the support capacity for the expansion of hematopoietic stem cells from umbilical cord blood was evaluated. The results show that co-cultures with MSC from WJ and UCB allow the cellular dose of HSPC to be maximized between 5 and 16 times having a similar support capacity as BM. In addition, was evaluated the hematopoietic stem progenitor cell's HSPC functionality through the evaluation of migration capacity, their differentiation capacity during culture time by flow cytometry to evaluate the expression of membrane markers associated with lineage-committed progenitors, their clonogenic potential, and the evaluation of secretome profile in the expansion process was evaluated. So far, the treatment with gamma irradiation maintains the hematopoietic support capacity of mesenchymal stem cells from the three sources studied compared to treatments without irradiation, favoring the use of fetal tissues that are generally waste to obtain mesenchymal cell lines for ex-vivo expansion systems. With the results obtained, a standardized protocol that will contribute to the development of ex-vivo expansion with MSC on a larger scale will be achieved, enabling its clinical use and expanding its application in adults.

Keywords: ex-vivo expansion, hematopoietic stem cells, hematopoietic stem cell transplantation, mesenchymal stem cells, umbilical cord blood

Procedia PDF Downloads 105

Authors: Liane J. Ioannou, Jonathan Serpell, Joanne Dean, Cino Bendinelli, Jenny Gough, Dean Lisewski, Julie Miller, Win Meyer-Rochow, Stan Sidhu, Duncan Topliss, David Walters, John Zalcberg, Susannah Ahern

Abstract:

Background: The occurrence of thyroid cancer is increasing throughout the developed world, including Australia and New Zealand, and since the 1990s has become the fastest increasing malignancy. Following the success of a number of institutional databases that monitor outcomes after thyroid surgery, the Australian and New Zealand Endocrine Surgeons (ANZES) agreed to auspice the development of a bi-national thyroid cancer registry. Objectives: To establish a bi-national population-based clinical quality registry with the aim of monitoring and improving the quality of care provided to patients diagnosed with thyroid cancer in Australia and New Zealand. Patients and Methods: The Australian and New Zealand Thyroid Cancer Registry (ANZTCR) captures clinical data for all patients, over the age of 18 years, diagnosed with thyroid cancer, confirmed by histopathology report, that have been diagnosed, assessed or treated at a contributing hospital. Data is collected by endocrine surgeons using a web-based interface, REDCap, primarily via direct data entry. Results: A multi-disciplinary Steering Committee was formed, and with operational support from Monash University the ANZTCR was established in early 2017. The pilot phase of the registry is currently operating in Victoria, New South Wales, Queensland, Western Australia and South Australia, with over 30 sites expected to come on board across Australia and New Zealand in 2018. A modified-Delphi process was undertaken to determine the key quality indicators to be reported by the registry, and a minimum dataset was developed comprising information regarding thyroid cancer diagnosis, pathology, surgery, and 30-day follow up. Conclusion: There are very few established thyroid cancer registries internationally, yet clinical quality registries have shown valuable outcomes and patient benefits in other cancers. The establishment of the ANZTCR provides the opportunity for Australia and New Zealand to further understand the current practice in the treatment of thyroid cancer and reasons for variation in outcomes. The engagement of endocrine surgeons in supporting this initiative is crucial. While the pilot registry has a focus on early clinical outcomes, it is anticipated that future collection of longer-term outcome data particularly for patients with the poor prognostic disease will add significant further value to the registry.

Keywords: thyroid cancer, clinical registry, population health, quality improvement

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Authors: Sangwoo Han, Saeed Khaleghi Rahimian, Ying Liu

Abstract:

Vehicle electrification is gaining momentum, and many car manufacturers promise to deliver more electric vehicle (EV) models to consumers in the coming years. In controlling the battery pack, the battery management system (BMS) must maintain optimal battery performance while ensuring the safety of a battery pack. Tasks related to battery performance include determining state-of-charge (SOC), state-of-power (SOP), state-of-health (SOH), cell balancing, and battery charging. Safety related functions include making sure cells operate within specified, static and dynamic voltage window and temperature range, derating power, detecting faulty cells, and warning the user if necessary. The BMS often utilizes an RC circuit model to model a Li-ion cell because of its robustness and low computation cost among other benefits. Because an equivalent circuit model such as the RC model is not a physics-based model, it can never be a prognostic model to predict battery state-of-health and avoid any safety risk even before it occurs. A physics-based Li-ion cell model, on the other hand, is more capable at the expense of computation cost. To avoid the high computation cost associated with a full-order model, many researchers have demonstrated the use of a single particle model (SPM) for BMS applications. One drawback associated with the single particle modeling approach is that it forces to use the average current density in the calculation. The SPM would be appropriate for simulating drive cycles where there is insufficient time to develop a significant current distribution within an electrode. However, under a continuous or high-pulse electrical load, the model may fail to predict cell voltage or Li⁺ plating potential. To overcome this issue, a multi-particle reduced-order model is proposed here. The use of multiple particles combined with either linear or nonlinear charge-transfer reaction kinetics enables to capture current density distribution within an electrode under any type of electrical load. To maintain computational complexity like that of an SPM, governing equations are solved sequentially to minimize iterative solving processes. Furthermore, the model is validated against a full-order model implemented in COMSOL Multiphysics.

Keywords: battery management system, physics-based li-ion cell model, reduced-order model, single-particle and multi-particle model

Procedia PDF Downloads 97