Search results for: pharmaceutical procurement supplier selection criteria
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5624

Search results for: pharmaceutical procurement supplier selection criteria

854 Music Listening in Dementia: Current Developments and the Potential for Automated Systems in the Home: Scoping Review and Discussion

Authors: Alexander Street, Nina Wollersberger, Paul Fernie, Leonardo Muller, Ming Hung HSU, Helen Odell-Miller, Jorg Fachner, Patrizia Di Campli San Vito, Stephen Brewster, Hari Shaji, Satvik Venkatesh, Paolo Itaborai, Nicolas Farina, Alexis Kirke, Sube Banerjee, Eduardo Reck Miranda

Abstract:

Escalating neuropsychiatric symptoms (NPS) in people with dementia may lead to earlier care home admission. Music listening has been reported to stimulate cognitive function, potentially reducing agitation in this population. We present a scoping review, reporting on current developments and discussing the potential for music listening with related technology in managing agitation in dementia care. Of two searches for music listening studies, one focused on older people or people living with dementia where music listening interventions, including technology, were delivered in participants’ homes or in institutions to address neuropsychiatric symptoms, quality of life and independence. The second included any population focusing on the use of music technology for health and wellbeing. In search one 70/251 full texts were included. The majority reported either statistical significance (6, 8.5%), significance (17, 24.2%) or improvements (26, 37.1%). Agitation was specifically reported in 36 (51.4%). The second search included 51/99 full texts, reporting improvement (28, 54.9%), significance (11, 21.5%), statistical significance (1, 1.9%) and no difference compared to the control (6, 11.7%). The majority in the first focused on mood and agitation, and the second on mood and psychophysiological responses. Five studies used AI or machine learning systems to select music, all involving healthy controls and reporting benefits. Most studies in both reviews were not conducted in a home environment (review 1 = 12; 17.1%; review 2 = 11; 21.5%). Preferred music listening may help manage NPS in the care home settings. Based on these and other data extracted in the review, a reasonable progression would be to co-design and test music listening systems and protocols for NPS in all settings, including people’s homes. Machine learning and automated technology for music selection and arousal adjustment, driven by live biodata, have not been explored in dementia care. Such approaches may help deliver the right music at the appropriate time in the required dosage, reducing the use of medication and improving quality of life.

Keywords: music listening, dementia, agitation, scoping review, technology

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853 The Influence of Destination Image on Tourists' Experience at Osun Osogbo World Heritage Site

Authors: Bola Adeleke, Kayode Ogunsusi

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Heritage sites have evolved to preserve culture and heritage and also to educate and entertain tourists. Tourist travel decisions and behavior are influenced by destination image and value of the experience of tourists. Perceived value is one of the important tools for securing a competitive edge in tourism destinations. The model of Ritchie and Crouch distinguished 36 attributes of competitiveness which are classified into five factors which are quality of experience, touristic attractiveness, environment and infrastructure, entertainment/outdoor activities and cultural traditions. The study extended this model with a different grouping of the determinants of destination competitiveness. The theoretical framework used for this study assumes that apart from attractions already situated in the grove, satisfaction with destination common service, and entertainment and events, can all be used in creating a positive image for/and in attracting customers (destination selection) to visit Osun Sacred Osogbo Grove during and after annual celebrations. All these will impact positively on travel experience of customers as well as their spiritual fulfillment. Destination image has a direct impact on tourists’ satisfaction which consequently impacts on tourists’ likely future behavior on whether to revisit a cultural destination or not. The study investigated the variables responsible for destination image competitiveness of the Heritage Site; assessed the factors enhancing the destination image; and evaluated the perceived value realized by tourists from their cultural experience at the grove. A complete enumeration of tourists above 18 years of age who visited the Heritage Site within the month of March and April 2017 was taken. 240 respondents, therefore, were used for the study. The structured questionnaire with 5 Likert scales was administered. Five factors comprising 63 variables were used to determine the destination image competitiveness through principal component analysis, while multiple regressions were used to evaluate perceived value of tourists at the grove. Results revealed that 11 out of the 12 variables determining the destination image competitiveness were significant in attracting tourists to the grove. From the R-value, all factors predicted tourists’ value of experience strongly (R= 0.936). The percentage variance of customer value was explained by 87.70% of the variance of destination common service, entertainment and event satisfaction, travel environment satisfaction and spiritual satisfaction, with F-value being significant at 0.00. Factors with high alpha value contributed greatly to adding value to enhancing destination and tourists’ experience. 11 variables positively predicted tourist value with significance. Managers of Osun World Heritage Site should improve on variables critical to adding values to tourists’ experience.

Keywords: competitiveness, destination image, Osun Osogbo world heritage site, tourists

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852 Dependence of Androgen Status in Men with Primary Hypothyroidism on Duration and Condition of Compensation

Authors: Krytskyy T.

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Introduction: The role of androgen deficiency in men as a factor in the pathogenesis of many somatic diseases is unmistakable. The interaction of thyroid and sex hormones with hypothyroidism in men is still the subject of discussions. The purpose of the study is to assess the androgen status of men with primary hypothyroidism, depending on its duration and the state of compensation. Materials and methods: 45 men with primary hypothyroidism aged 35 to 60 years, as well as 25 healthy men, who formed a control group, were under supervision. A selection of men for examination was conducted in the process of outpatient and in-patient treatment at the endocrinology department of the University Hospital in Ternopil. The functional state of the pituitary-gonadal system was evaluated in order to characterize the androgen status of patients. The concentration of follicle stimulating hormone, luteinizing hormone, prolactin, thyroid-stimulating hormone was determined in blood with the help of enzyme-linked method. Also, the content of hormones: total testosterone, linking sex hormones globulin were determined. Results: Reduced total testosterone (TT) content was found in 42.2% of patients with hypothyroidism. Herewith in 17.8% of patients, blood TT levels were lower than 8.0 nmol / L, and in 11 (24.4%) men, the rate was in the range of 8.0 to 12.0 nmol / L. Based on the results of the determination of the content of free testosterone (FT), the frequency of laboratory hypogonadism in men with hypothyroidism was higher than the results of the determination of TT. The degree of compensation of hypothyroidism probably did not affect the average levels of gonadotropic and sex hormones. Conclusions: Reduced total testosterone content was found in 42.2% of patients with primary hypothyroidism. Herewith, in 17.8% of patients blood TT levels were lower than 8.0 nmol / L, which is a sign of absolute deficiency of testosterone, and in 24.4% of men the rate ranged from 8.0 to 12.0 nmol / l , indicating partial androgen deficiency. Linking sex hormones globulin levels were believed to be lower in 46.7% of patients with hypothyroidism compared to control group. The average levels of E2 in the examined patients did not significantly differ from the mean of control group. FSH, LH, and prolactin levels in men with hypothyroidism were within the normal age limits and probably did not differ from those of control group. The degree of compensation of hypothyroidism probably did not affect the average levels of gonadotropic and sex hormones. The mean LH content in the blood was significantly increased in men with a duration of hypothyroidism up to 5 years and did not differ from that of the control group and in men with a duration of hypothyroidism over 5 years. In men with hypothyroidism, a probable reduction in T / LH coefficient is found. The obtained data may indicate a combined lesion of the central and peripheral parts of the pituitary-gonadal system in men with hypothyroidism.

Keywords: androgenic status, hypothyroidism, testosterone, linking sex hormones globulin

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851 Challenges of Blockchain Applications in the Supply Chain Industry: A Regulatory Perspective

Authors: Pardis Moslemzadeh Tehrani

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Due to the emergence of blockchain technology and the benefits of cryptocurrencies, intelligent or smart contracts are gaining traction. Artificial intelligence (AI) is transforming our lives, and it is being embraced by a wide range of sectors. Smart contracts, which are at the heart of blockchains, incorporate AI characteristics. Such contracts are referred to as "smart" contracts because of the underlying technology that allows contracting parties to agree on terms expressed in computer code that defines machine-readable instructions for computers to follow under specific situations. The transmission happens automatically if the conditions are met. Initially utilised for financial transactions, blockchain applications have since expanded to include the financial, insurance, and medical sectors, as well as supply networks. Raw material acquisition by suppliers, design, and fabrication by manufacturers, delivery of final products to consumers, and even post-sales logistics assistance are all part of supply chains. Many issues are linked with managing supply chains from the planning and coordination stages, which can be implemented in a smart contract in a blockchain due to their complexity. Manufacturing delays and limited third-party amounts of product components have raised concerns about the integrity and accountability of supply chains for food and pharmaceutical items. Other concerns include regulatory compliance in multiple jurisdictions and transportation circumstances (for instance, many products must be kept in temperature-controlled environments to ensure their effectiveness). Products are handled by several providers before reaching customers in modern economic systems. Information is sent between suppliers, shippers, distributors, and retailers at every stage of the production and distribution process. Information travels more effectively when individuals are eliminated from the equation. The usage of blockchain technology could be a viable solution to these coordination issues. In blockchains, smart contracts allow for the rapid transmission of production data, logistical data, inventory levels, and sales data. This research investigates the legal and technical advantages and disadvantages of AI-blockchain technology in the supply chain business. It aims to uncover the applicable legal problems and barriers to the use of AI-blockchain technology to supply chains, particularly in the food industry. It also discusses the essential legal and technological issues and impediments to supply chain implementation for stakeholders, as well as methods for overcoming them before releasing the technology to clients. Because there has been little research done on this topic, it is difficult for industrial stakeholders to grasp how blockchain technology could be used in their respective operations. As a result, the focus of this research will be on building advanced and complex contractual terms in supply chain smart contracts on blockchains to cover all unforeseen supply chain challenges.

Keywords: blockchain, supply chain, IoT, smart contract

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850 Application of the Building Information Modeling Planning Approach to the Factory Planning

Authors: Peggy Näser

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Factory planning is a systematic, objective-oriented process for planning a factory, structured into a sequence of phases, each of which is dependent on the preceding phase and makes use of particular methods and tools, and extending from the setting of objectives to the start of production. The digital factory, on the other hand, is the generic term for a comprehensive network of digital models, methods, and tools – including simulation and 3D visualisation – integrated by a continuous data management system. Its aim is the holistic planning, evaluation and ongoing improvement of all the main structures, processes and resources of the real factory in conjunction with the product. Digital factory planning has already become established in factory planning. The application of Building Information Modeling has not yet been established in factory planning but has been used predominantly in the planning of public buildings. Furthermore, this concept is limited to the planning of the buildings and does not include the planning of equipment of the factory (machines, technical equipment) and their interfaces to the building. BIM is a cooperative method of working, in which the information and data relevant to its lifecycle are consistently recorded, managed and exchanged in a transparent communication between the involved parties on the basis of digital models of a building. Both approaches, the planning approach of Building Information Modeling and the methodical approach of the Digital Factory, are based on the use of a comprehensive data model. Therefore it is necessary to examine how the approach of Building Information Modeling can be extended in the context of factory planning in such a way that an integration of the equipment planning, as well as the building planning, can take place in a common digital model. For this, a number of different perspectives have to be investigated: the equipment perspective including the tools used to implement a comprehensive digital planning process, the communication perspective between the planners of different fields, the legal perspective, that the legal certainty in each country and the quality perspective, on which the quality criteria are defined and the planning will be evaluated. The individual perspectives are examined and illustrated in the article. An approach model for the integration of factory planning into the BIM approach, in particular for the integrated planning of equipment and buildings and the continuous digital planning is developed. For this purpose, the individual factory planning phases are detailed in the sense of the integration of the BIM approach. A comprehensive software concept is shown on the tool. In addition, the prerequisites required for this integrated planning are presented. With the help of the newly developed approach, a better coordination between equipment and buildings is to be achieved, the continuity of the digital factory planning is improved, the data quality is improved and expensive implementation errors are avoided in the implementation.

Keywords: building information modeling, digital factory, digital planning, factory planning

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849 Efficient Estimation of Maximum Theoretical Productivity from Batch Cultures via Dynamic Optimization of Flux Balance Models

Authors: Peter C. St. John, Michael F. Crowley, Yannick J. Bomble

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Production of chemicals from engineered organisms in a batch culture typically involves a trade-off between productivity, yield, and titer. However, strategies for strain design typically involve designing mutations to achieve the highest yield possible while maintaining growth viability. Such approaches tend to follow the principle of designing static networks with minimum metabolic functionality to achieve desired yields. While these methods are computationally tractable, optimum productivity is likely achieved by a dynamic strategy, in which intracellular fluxes change their distribution over time. One can use multi-stage fermentations to increase either productivity or yield. Such strategies would range from simple manipulations (aerobic growth phase, anaerobic production phase), to more complex genetic toggle switches. Additionally, some computational methods can also be developed to aid in optimizing two-stage fermentation systems. One can assume an initial control strategy (i.e., a single reaction target) in maximizing productivity - but it is unclear how close this productivity would come to a global optimum. The calculation of maximum theoretical yield in metabolic engineering can help guide strain and pathway selection for static strain design efforts. Here, we present a method for the calculation of a maximum theoretical productivity of a batch culture system. This method follows the traditional assumptions of dynamic flux balance analysis: that internal metabolite fluxes are governed by a pseudo-steady state and external metabolite fluxes are represented by dynamic system including Michealis-Menten or hill-type regulation. The productivity optimization is achieved via dynamic programming, and accounts explicitly for an arbitrary number of fermentation stages and flux variable changes. We have applied our method to succinate production in two common microbial hosts: E. coli and A. succinogenes. The method can be further extended to calculate the complete productivity versus yield Pareto surface. Our results demonstrate that nearly optimal yields and productivities can indeed be achieved with only two discrete flux stages.

Keywords: A. succinogenes, E. coli, metabolic engineering, metabolite fluxes, multi-stage fermentations, succinate

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848 Implementation of Correlation-Based Data Analysis as a Preliminary Stage for the Prediction of Geometric Dimensions Using Machine Learning in the Forming of Car Seat Rails

Authors: Housein Deli, Loui Al-Shrouf, Hammoud Al Joumaa, Mohieddine Jelali

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When forming metallic materials, fluctuations in material properties, process conditions, and wear lead to deviations in the component geometry. Several hundred features sometimes need to be measured, especially in the case of functional and safety-relevant components. These can only be measured offline due to the large number of features and the accuracy requirements. The risk of producing components outside the tolerances is minimized but not eliminated by the statistical evaluation of process capability and control measurements. The inspection intervals are based on the acceptable risk and are at the expense of productivity but remain reactive and, in some cases, considerably delayed. Due to the considerable progress made in the field of condition monitoring and measurement technology, permanently installed sensor systems in combination with machine learning and artificial intelligence, in particular, offer the potential to independently derive forecasts for component geometry and thus eliminate the risk of defective products - actively and preventively. The reliability of forecasts depends on the quality, completeness, and timeliness of the data. Measuring all geometric characteristics is neither sensible nor technically possible. This paper, therefore, uses the example of car seat rail production to discuss the necessary first step of feature selection and reduction by correlation analysis, as otherwise, it would not be possible to forecast components in real-time and inline. Four different car seat rails with an average of 130 features were selected and measured using a coordinate measuring machine (CMM). The run of such measuring programs alone takes up to 20 minutes. In practice, this results in the risk of faulty production of at least 2000 components that have to be sorted or scrapped if the measurement results are negative. Over a period of 2 months, all measurement data (> 200 measurements/ variant) was collected and evaluated using correlation analysis. As part of this study, the number of characteristics to be measured for all 6 car seat rail variants was reduced by over 80%. Specifically, direct correlations for almost 100 characteristics were proven for an average of 125 characteristics for 4 different products. A further 10 features correlate via indirect relationships so that the number of features required for a prediction could be reduced to less than 20. A correlation factor >0.8 was assumed for all correlations.

Keywords: long-term SHM, condition monitoring, machine learning, correlation analysis, component prediction, wear prediction, regressions analysis

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847 The Relationships between AntimüLlerian Hormone, Androgens and Ovarian Reserve in Non-Obese East Indian Women with and without Polycystic Ovary Syndrome

Authors: Dipanshu Sur, Ratnabali Chakravorty, Rimi Pal, Siddhartha Chatterjee, Joyshree Chaterjee, Amal Mallik

Abstract:

Background: Polycystic ovary syndrome (PCOS) is a common endocrine disease in reproductive women with a complex hormonal disturbance that affects the menstrual cycle and leads to metabolic consequences in later life. Hyperandrogenaemia is noticeable features of PCOS and influence the process of folliculogenesis in women. The levels of Antimüllerian Hormone (AMH) reflect the number of pre-antral follicles and thus are a marker of oocyte pool – germinal reserve of the ovary for reproduction. Besides its utilization in IVF (In-vitro fertilization), determination of AMH may serve as an additional marker in the diagnostics of PCOS, where increased AMH levels reflect the severity of the disease. The positive correlation of serum AMH with the number of antral follicles was found also in patients with PCOS. Objective: The objective of this study was to investigate the relationship between AMH androgens and whether AMH contributes to altered folliculogenesis in non-obese women with PCOS. Methods: We designed a prospective study which included a total of 65 IVF individuals. It enrolled 26 cases of PCOS based on 2003 Rotterdam criteria and 39 ovulatory normal- non PCOS, healthy, age-matched controls. AMH levels and ovarian morphology were assessed. The relationships between AMH and androgenaemia in patients with and without PCOS were studied. Results: Mean age of PCOS patients were slightly higher than controls (32±4 and 28±3 years, respectively). AMH generally increased with antral follicle count (AFC) [P=0.001], testosterone, and luteinising hormone, and decreased with age, and serum sex hormone binding globulin (SHBG). No significant relationships were found between circulating AMH levels and BMI between PCOS and non-PCOS patients. The calculation of AMH production per antral follicle (AMH/AF) showed that there was a significant difference in median AMH/AF between PCOS and non-PCOS (P =0.001). Both PCOS and non-PCOS groups showed a very similar increase in AMH with increases in AFC, but the PCOS patients had consistently higher AMH across all AFC levels. Conclusions: These observations indicate that there is a connection between AMH and androgens levels between PCOS and non-PCOS East Indian women. Excessive granulosa cell activity may be implicated in the abnormal follicular dynamic of the syndrome. They are higher in women with PCOS and, on the other hand, very low in women with an ovarian failure.

Keywords: anti-Mullerian hormone, polycystic ovary syndrome, antral follicle count, androgens

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846 A Double-Blind, Randomized, Controlled Trial on N-Acetylcysteine for the Prevention of Acute Kidney Injury in Patients Undergoing Allogeneic Hematopoietic Stem Cell Transplantation

Authors: Sara Ataei, Molouk Hadjibabaie, Amirhossein Moslehi, Maryam Taghizadeh-Ghehi, Asieh Ashouri, Elham Amini, Kheirollah Gholami, Alireza Hayatshahi, Mohammad Vaezi, Ardeshir Ghavamzadeh

Abstract:

Acute kidney injury (AKI) is one of the complications of hematopoietic stem cell transplantation and is associated with increased mortality. N-acetylcysteine (NAC) is a thiol compound with antioxidant and vasodilatory properties that has been investigated for the prevention of AKI in several clinical settings. In the present study, we evaluated the effects of intravenous NAC on the prevention of AKI in allogeneic hematopoietic stem cell transplantation patients. A double-blind randomized placebo-controlled trial was conducted, and 80 patients were recruited to receive 100 mg/kg/day NAC or placebo as intermittent intravenous infusion from day -6 to day +15. AKI was determined on the basis of the Risk-Injury-Failure-Loss-Endstage renal disease and AKI Network criteria as the primary outcome. We assessed urine neutrophil gelatinase-associated lipocalin (uNGAL) on days -6, -3, +3, +9, and +15 as the secondary outcome. Moreover, transplant-related outcomes and NAC adverse reactions were evaluated during the study period. Statistical analysis was performed using appropriate parametric and non-parametric methods including Kaplan–Meier for AKI and generalized estimating equation for uNGAL. At the end of the trial, data from 72 patients were analyzed (NAC: 33 patients and placebo: 39 patients). Participants of each group were not different considering baseline characteristics. AKI was observed in 18% of NAC recipients and 15% of placebo group patients, and the occurrence pattern was not significantly different (p = 0.73). Moreover, no significant difference was observed between groups for uNGAL measures (p = 0.10). Transplant-related outcomes were similar for both groups, and all patients had successful engraftment. Three patients did not tolerate NAC because of abdominal pain, shortness of breath and rash with pruritus and were dropped from the intervention group before transplantation. However, the frequency of adverse reactions was not significantly different between groups. In conclusion, our findings could not show any clinical benefits from high-dose NAC particularly for AKI prevention in allogeneic hematopoietic stem cell transplantation patients.

Keywords: acute kidney injury, N-acetylcysteine, hematopoietic stem cell transplantation, urine neutrophil gelatinase-associated lipocalin, randomized controlled trial

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845 A Comprehensive Review on Structural Properties and Erection Benefits of Large Span Stressed-Arch Steel Truss Industrial Buildings

Authors: Anoush Saadatmehr

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Design and build of large clear span structures have always been demanding in the construction industry targeting industrial and commercial buildings around the world. The function of these spectacular structures encompasses distinguished types of building such as aircraft and airship hangars, warehouses, bulk storage buildings, sports and recreation facilities. From an engineering point of view, there are various types of steel structure systems that are often adopted in large-span buildings like conventional trusses, space frames and cable-supported roofs. However, this paper intends to investigate and review an innovative light, economic and quickly erected large span steel structure renowned as “Stressed-Arch,” which has several advantages over the other common types of structures. This patented system integrates the use of cold-formed hollow section steel material with high-strength pre-stressing strands and concrete grout to establish an arch shape truss frame anywhere there is a requirement to construct a cost-effective column-free space for spans within the range of 60m to 180m. In this study and firstly, the main structural properties of the stressed-arch system and its components are discussed technically. These features include nonlinear behavior of truss chords during stress-erection, the effect of erection method on member’s compressive strength, the rigidity of pre-stressed trusses to overcome strict deflection criteria for cases with roof suspended cranes or specialized front doors and more importantly, the prominent lightness of steel structure. Then, the effects of utilizing pre-stressing strands to safeguard a smooth process of installation of main steel members and roof components and cladding are investigated. In conclusion, it is shown that the Stressed-Arch system not only provides an optimized light steel structure up to 30% lighter than its conventional competitors but also streamlines the process of building erection and minimizes the construction time while preventing the risks of working at height.

Keywords: large span structure, pre-stressed steel truss, stressed-arch building, stress-erection, steel structure

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844 Selection of Qualitative Research Strategy for Bullying and Harassment in Sport

Authors: J. Vveinhardt, V. B. Fominiene, L. Jeseviciute-Ufartiene

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Relevance of Research: Qualitative research is still regarded as highly subjective and not sufficiently scientific in order to achieve objective research results. However, it is agreed that a qualitative study allows revealing the hidden motives of the research participants, creating new theories, and highlighting the field of problem. There is enough research done to reveal these qualitative research aspects. However, each research area has its own specificity, and sport is unique due to the image of its participants, who are understood as strong and invincible. Therefore, a sport participant might have personal issues to recognize himself as a victim in the context of bullying and harassment. Accordingly, researcher has a dilemma in general making to speak a victim in sport. Thus, ethical aspects of qualitative research become relevant. The plenty fields of sport make a problem determining the sample size of research. Thus, the corresponding problem of this research is which and why qualitative research strategies are the most suitable revealing the phenomenon of bullying and harassment in sport. Object of research is qualitative research strategy for bullying and harassment in sport. Purpose of the research is to analyze strategies of qualitative research selecting suitable one for bullying and harassment in sport. Methods of research were scientific research analyses of qualitative research application for bullying and harassment research. Research Results: Four mane strategies are applied in the qualitative research; inductive, deductive, retroductive, and abductive. Inductive and deductive strategies are commonly used researching bullying and harassment in sport. The inductive strategy is applied as quantitative research in order to reveal and describe the prevalence of bullying and harassment in sport. The deductive strategy is used through qualitative methods in order to explain the causes of bullying and harassment and to predict the actions of the participants of bullying and harassment in sport and the possible consequences of these actions. The most commonly used qualitative method for the research of bullying and harassment in sports is semi-structured interviews in speech and in written. However, these methods may restrict the openness of the participants in the study when recording on the dictator or collecting incomplete answers when the participant in the survey responds in writing because it is not possible to refine the answers. Qualitative researches are more prevalent in terms of technology-defined research data. For example, focus group research in a closed forum allows participants freely interact with each other because of the confidentiality of the selected participants in the study. The moderator can purposefully formulate and submit problem-solving questions to the participants. Hence, the application of intelligent technology through in-depth qualitative research can help discover new and specific information on bullying and harassment in sport. Acknowledgement: This research is funded by the European Social Fund according to the activity ‘Improvement of researchers’ qualification by implementing world-class R&D projects of Measure No. 09.3.3-LMT-K-712.

Keywords: bullying, focus group, harassment, narrative, sport, qualitative research

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843 Development of a 3D Model of Real Estate Properties in Fort Bonifacio, Taguig City, Philippines Using Geographic Information Systems

Authors: Lyka Selene Magnayi, Marcos Vinas, Roseanne Ramos

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As the real estate industry continually grows in the Philippines, Geographic Information Systems (GIS) provide advantages in generating spatial databases for efficient delivery of information and services. The real estate sector is not only providing qualitative data about real estate properties but also utilizes various spatial aspects of these properties for different applications such as hazard mapping and assessment. In this study, a three-dimensional (3D) model and a spatial database of real estate properties in Fort Bonifacio, Taguig City are developed using GIS and SketchUp. Spatial datasets include political boundaries, buildings, road network, digital terrain model (DTM) derived from Interferometric Synthetic Aperture Radar (IFSAR) image, Google Earth satellite imageries, and hazard maps. Multiple model layers were created based on property listings by a partner real estate company, including existing and future property buildings. Actual building dimensions, building facade, and building floorplans are incorporated in these 3D models for geovisualization. Hazard model layers are determined through spatial overlays, and different scenarios of hazards are also presented in the models. Animated maps and walkthrough videos were created for company presentation and evaluation. Model evaluation is conducted through client surveys requiring scores in terms of the appropriateness, information content, and design of the 3D models. Survey results show very satisfactory ratings, with the highest average evaluation score equivalent to 9.21 out of 10. The output maps and videos obtained passing rates based on the criteria and standards set by the intended users of the partner real estate company. The methodologies presented in this study were found useful and have remarkable advantages in the real estate industry. This work may be extended to automated mapping and creation of online spatial databases for better storage, access of real property listings and interactive platform using web-based GIS.

Keywords: geovisualization, geographic information systems, GIS, real estate, spatial database, three-dimensional model

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842 Delving into the Concept of Social Capital in the Smart City Research

Authors: Atefe Malekkhani, Lee Beattie, Mohsen Mohammadzadeh

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Unprecedented growth of megacities and urban areas all around the world have resulted in numerous risks, concerns, and problems across various aspects of urban life, including environmental, social, and economic domains like climate change, spatial and social inequalities. In this situation, ever-increasing progress of technology has created a hope for urban authorities that the negative effects of various socio-economic and environmental crises can potentially be mitigated with the use of information and communication technologies. The concept of 'smart city' represents an emerging solution to urban challenges arising from increased urbanization using ICTs. However, smart cities are often perceived primarily as technological initiatives and are implemented without considering the social and cultural contexts of cities and the needs of their residents. The implementation of smart city projects and initiatives has the potential to (un)intentionally exacerbate pre-existing social, spatial, and cultural segregation. Investigating the impact of smart city on social capital of people who are users of smart city systems and with governance as policymakers is worth exploring. The importance of inhabitants to the existence and development of smart cities cannot be overlooked. This concept has gained different perspectives in the smart city studies. Reviewing the literature about social capital and smart city show that social capital play three different roles in smart city development. Some research indicates that social capital is a component of a smart city and has embedded in its dimensions, definitions, or strategies, while other ones see it as a social outcome of smart city development and point out that the move to smart cities improves social capital; however, in most cases, it remains an unproven hypothesis. Other studies show that social capital can enhance the functions of smart cities, and the consideration of social capital in planning smart cities should be promoted. Despite the existing theoretical and practical knowledge, there is a significant research gap reviewing the knowledge domain of smart city studies through the lens of social capital. To shed light on this issue, this study aims to explore the domain of existing research in the field of smart city through the lens of social capital. This research will use the 'Preferred Reporting Items for Systematic Reviews and Meta-Analyses' (PRISMA) method to review relevant literature, focusing on the key concepts of 'Smart City' and 'Social Capital'. The studies will be selected Web of Science Core Collection, using a selection process that involves identifying literature sources, screening and filtering studies based on titles, abstracts, and full-text reading.

Keywords: smart city, urban digitalisation, ICT, social capital

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841 High Resolution Satellite Imagery and Lidar Data for Object-Based Tree Species Classification in Quebec, Canada

Authors: Bilel Chalghaf, Mathieu Varin

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Forest characterization in Quebec, Canada, is usually assessed based on photo-interpretation at the stand level. For species identification, this often results in a lack of precision. Very high spatial resolution imagery, such as DigitalGlobe, and Light Detection and Ranging (LiDAR), have the potential to overcome the limitations of aerial imagery. To date, few studies have used that data to map a large number of species at the tree level using machine learning techniques. The main objective of this study is to map 11 individual high tree species ( > 17m) at the tree level using an object-based approach in the broadleaf forest of Kenauk Nature, Quebec. For the individual tree crown segmentation, three canopy-height models (CHMs) from LiDAR data were assessed: 1) the original, 2) a filtered, and 3) a corrected model. The corrected CHM gave the best accuracy and was then coupled with imagery to refine tree species crown identification. When compared with photo-interpretation, 90% of the objects represented a single species. For modeling, 313 variables were derived from 16-band WorldView-3 imagery and LiDAR data, using radiance, reflectance, pixel, and object-based calculation techniques. Variable selection procedures were employed to reduce their number from 313 to 16, using only 11 bands to aid reproducibility. For classification, a global approach using all 11 species was compared to a semi-hierarchical hybrid classification approach at two levels: (1) tree type (broadleaf/conifer) and (2) individual broadleaf (five) and conifer (six) species. Five different model techniques were used: (1) support vector machine (SVM), (2) classification and regression tree (CART), (3) random forest (RF), (4) k-nearest neighbors (k-NN), and (5) linear discriminant analysis (LDA). Each model was tuned separately for all approaches and levels. For the global approach, the best model was the SVM using eight variables (overall accuracy (OA): 80%, Kappa: 0.77). With the semi-hierarchical hybrid approach, at the tree type level, the best model was the k-NN using six variables (OA: 100% and Kappa: 1.00). At the level of identifying broadleaf and conifer species, the best model was the SVM, with OA of 80% and 97% and Kappa values of 0.74 and 0.97, respectively, using seven variables for both models. This paper demonstrates that a hybrid classification approach gives better results and that using 16-band WorldView-3 with LiDAR data leads to more precise predictions for tree segmentation and classification, especially when the number of tree species is large.

Keywords: tree species, object-based, classification, multispectral, machine learning, WorldView-3, LiDAR

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840 Enhancing Fault Detection in Rotating Machinery Using Wiener-CNN Method

Authors: Mohamad R. Moshtagh, Ahmad Bagheri

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Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

Procedia PDF Downloads 81
839 Quality by Design in the Optimization of a Fast HPLC Method for Quantification of Hydroxychloroquine Sulfate

Authors: Pedro J. Rolim-Neto, Leslie R. M. Ferraz, Fabiana L. A. Santos, Pablo A. Ferreira, Ricardo T. L. Maia-Jr., Magaly A. M. Lyra, Danilo A F. Fonte, Salvana P. M. Costa, Amanda C. Q. M. Vieira, Larissa A. Rolim

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Initially developed as an antimalarial agent, hydroxychloroquine (HCQ) sulfate is often used as a slow-acting antirheumatic drug in the treatment of disorders of connective tissue. The United States Pharmacopeia (USP) 37 provides a reversed-phase HPLC method for quantification of HCQ. However, this method was not reproducible, producing asymmetric peaks in a long analysis time. The asymmetry of the peak may cause an incorrect calculation of the concentration of the sample. Furthermore, the analysis time is unacceptable, especially regarding the routine of a pharmaceutical industry. The aiming of this study was to develop a fast, easy and efficient method for quantification of HCQ sulfate by High Performance Liquid Chromatography (HPLC) based on the Quality by Design (QbD) methodology. This method was optimized in terms of peak symmetry using the surface area graphic as the Design of Experiments (DoE) and the tailing factor (TF) as an indicator to the Design Space (DS). The reference method used was that described at USP 37 to the quantification of the drug. For the optimized method, was proposed a 33 factorial design, based on the QbD concepts. The DS was created with the TF (in a range between 0.98 and 1.2) in order to demonstrate the ideal analytical conditions. Changes were made in the composition of the USP mobile-phase (USP-MP): USP-MP: Methanol (90:10 v/v, 80:20 v/v and 70:30 v/v), in the flow (0.8, 1.0 and 1.2 mL) and in the oven temperature (30, 35, and 40ºC). The USP method allowed the quantification of drug in a long time (40-50 minutes). In addition, the method uses a high flow rate (1,5 mL.min-1) which increases the consumption of expensive solvents HPLC grade. The main problem observed was the TF value (1,8) that would be accepted if the drug was not a racemic mixture, since the co-elution of the isomers can become an unreliable peak integration. Therefore, the optimization was suggested in order to reduce the analysis time, aiming a better peak resolution and TF. For the optimization method, by the analysis of the surface-response plot it was possible to confirm the ideal setting analytical condition: 45 °C, 0,8 mL.min-1 and 80:20 USP-MP: Methanol. The optimized HPLC method enabled the quantification of HCQ sulfate, with a peak of high resolution, showing a TF value of 1,17. This promotes good co-elution of isomers of the HCQ, ensuring an accurate quantification of the raw material as racemic mixture. This method also proved to be 18 times faster, approximately, compared to the reference method, using a lower flow rate, reducing even more the consumption of the solvents and, consequently, the analysis cost. Thus, an analytical method for the quantification of HCQ sulfate was optimized using QbD methodology. This method proved to be faster and more efficient than the USP method, regarding the retention time and, especially, the peak resolution. The higher resolution in the chromatogram peaks supports the implementation of the method for quantification of the drug as racemic mixture, not requiring the separation of isomers.

Keywords: analytical method, hydroxychloroquine sulfate, quality by design, surface area graphic

Procedia PDF Downloads 639
838 Community Re-Integrated Soldiers’ Perceptions of Barriers and Facilitators to A Home-Based Physical Rehabilitation Programme Following Lower-Limb Amputation

Authors: Ashan Wijekoon, Abi Beane, Subashini Jayawardana

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Background: Soldiers' physical rehabilitation and long term health status has been hindered due to limited investment in and access to rehabilitation services. Home-based rehabilitation programmes could offer a potentially feasible alternative to facilitate long-term recovery. Objectives: To explore Sri Lankan soldiers' perceptions of barriers and facilitators to a home-based physical rehabilitation programme.Methods and Materials: We conducted qualitative semi-structured interviews with community re-integrated army veterans who had undergone unilateral lower limb amputation following war related trauma. Veterans were identified from five districts of Sri Lanka, based on a priori knowledge of veteran community settlements (Disabled Category Registry) obtained from Directorate of Rehabilitation, MoD, Sri Lanka. Individuals were stratified for purposive selection. The interview guide was developed from existing methods and adapted for context. Verbatim transcripts of interviews were analyzed for emerging themes using an inductive approach. Following consent, participants met the researcher (AW- a trained physiotherapist fluent in Sinhalese). Results: Twenty-five Interviews were conducted, totaling 7.2 hours of new data (Mean±SD: 0.28±0.11). All participants were male, aged 30-55 years (Mean±SD: 46.1±7.4), and had experienced traumatic amputation as a result of conflict. Twenty-four sub themes were identified. Inadequate space for exercises, absence of equipment and assistance to conduct the exercises at home, alongside absence of community healthcare services were all barriers. Burden of comorbidities, including chronic pain and disability level, were also barriers. Social support systems, including soldier societies, family, and kinship with other amputees, were seen as facilitators to an at-home programme. Motivation for independence was a strong indicator of engagement. Conclusion: Environment, chronic pain, and absence of well-established community health services were key barriers. Family and soldier support was a facilitator. Engagement with community healthcare providers (physiotherapist and primary care physicians) will be essential to the success of an at-home rehabilitation program.

Keywords: physical rehabilitation, home-based, soldiers, disability, lower-limb amputation, qualitative

Procedia PDF Downloads 170
837 Two-Stage Estimation of Tropical Cyclone Intensity Based on Fusion of Coarse and Fine-Grained Features from Satellite Microwave Data

Authors: Huinan Zhang, Wenjie Jiang

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Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

Procedia PDF Downloads 63
836 Personalized Infectious Disease Risk Prediction System: A Knowledge Model

Authors: Retno A. Vinarti, Lucy M. Hederman

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This research describes a knowledge model for a system which give personalized alert to users about infectious disease risks in the context of weather, location and time. The knowledge model is based on established epidemiological concepts augmented by information gleaned from infection-related data repositories. The existing disease risk prediction research has more focuses on utilizing raw historical data and yield seasonal patterns of infectious disease risk emergence. This research incorporates both data and epidemiological concepts gathered from Atlas of Human Infectious Disease (AHID) and Centre of Disease Control (CDC) as basic reasoning of infectious disease risk prediction. Using CommonKADS methodology, the disease risk prediction task is an assignment synthetic task, starting from knowledge identification through specification, refinement to implementation. First, knowledge is gathered from AHID primarily from the epidemiology and risk group chapters for each infectious disease. The result of this stage is five major elements (Person, Infectious Disease, Weather, Location and Time) and their properties. At the knowledge specification stage, the initial tree model of each element and detailed relationships are produced. This research also includes a validation step as part of knowledge refinement: on the basis that the best model is formed using the most common features, Frequency-based Selection (FBS) is applied. The portion of the Infectious Disease risk model relating to Person comes out strongest, with Location next, and Weather weaker. For Person attribute, Age is the strongest, Activity and Habits are moderate, and Blood type is weakest. At the Location attribute, General category (e.g. continents, region, country, and island) results much stronger than Specific category (i.e. terrain feature). For Weather attribute, Less Precise category (i.e. season) comes out stronger than Precise category (i.e. exact temperature or humidity interval). However, given that some infectious diseases are significantly more serious than others, a frequency based metric may not be appropriate. Future work will incorporate epidemiological measurements of disease seriousness (e.g. odds ratio, hazard ratio and fatality rate) into the validation metrics. This research is limited to modelling existing knowledge about epidemiology and chain of infection concepts. Further step, verification in knowledge refinement stage, might cause some minor changes on the shape of tree.

Keywords: epidemiology, knowledge modelling, infectious disease, prediction, risk

Procedia PDF Downloads 242
835 Cultural Heritage Resources for Tourism, Two Countries – Two Approaches: A Comparative Analysis of Cultural Tourism Products in Turkey and Austria

Authors: Irfan Arikan, George Christian Steckenbauer

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Turkey and Austria are examples for highly developed tourism destinations, where tourism providers use cultural heritage and regional natural resources to develop modern tourism products in order to be successful on increasingly competitive international tourism markets. The use and exploitation of these resources follow on the one hand international standards of tourism marketing (as ‘sustainability’). Therefore, we find highly comparable internationalized products in these destinations (like hotel products, museums, spas etc.). On the other hand, development standards and processes strongly depend on local, regional and national cultures, which influence the way how people work, cooperate, think and create. Thus, cultural factors also influence the attitude towards cultural heritage and natural resources and the way, how these resources are used for the creation of tourism products. This leads to differences in the development of tourism products on several levels: 1. In the selection of cultural heritage and natural resources for the product development process 2. In the processes, how tourism products are created 3. In the way, how providers and marketing organisations work with tourism products based on cultural heritage or natural resources. Aim of this paper is to discover differences in these dimensions by analysing and comparing examples of tourism products in Turkey and Austria, both countries with a highly developed, high professional tourism industry and rich experience of stakeholders in tourism industry in the field of product development and marketing. The cases are selected from the following fields: + Cultural tourism / heritage tourism + City tourism + Industrial heritage tourism + Nature and outdoor tourism + Health tourism The cases are analysed based on available secondary data (as several cases are scientifically described) and expert interviews with local and regional stakeholders of tourism industry and tourism experts. The available primary and secondary data will be analysed and displayed in a comparative structure that allows to derive answers to the above stated research question. The result of the project therefore will be a more precise picture about the influence of cultural differences on the use and exploitation of resources in the field of tourism that allows developing recommendations for tourism industry, which must be taken into consideration to assure cultural and natural resources are treated in a sustainable and responsible way. The authors will edit these culture-cross recommendations in form of a ‘check-list’ that can be used as a ‘guideline’ for tourism professionals in the field of product development and marketing and therefore connects theoretical research to the field of practical application and closes the gap between academic research and the field of tourism practice.

Keywords: cultural heritage, natural resources, Austria, Turkey

Procedia PDF Downloads 493
834 Nurses as Being Participants of Sexual Health of Women

Authors: Malika Turganova, Aigul Abduldayeva

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Modern conditions require nursing innovations at the primary ambulatory stage in the health system of Kazakhstan. There is a growing need for nurses involved in before-doctor attendance for preventive interview with a female population about reproductive health. We conducted questionnaire survey of the population of Astana in 2015. Questionnaires were drawn up according to the criteria of sexual health of World Health Organization. 3593 respondents out of 8000 questionnaires agreed to answer the questions anonymously, mM=±2,1. The average age of women comprised 37,4±11,2, Ме=31,7 years of age. Analysis of awareness about marriage hygiene revealed that 72,7% of respondents did not receive information about marriage hygiene and 89,1% respondents consider it more advisable before marriage. 45,9% of respondents specified the internet as a source of information on marriage hygiene issues, 24,5% of respondents pointed out friends, and 21,5% specified doctor. Comparing female age groups under and after 40 years old we see that proportion of cases when parents provide information about marriage hygiene issues comprises 4.3% (χ2 =9.8, p<0.05). The most important factor of preservation of women reproductive health is handling a problem of unwanted pregnancy. The responsibility lies equally in men and women. Data analysis of contraceptive methods by ranking showed three most frequently used methods: contraception sheath – 29.3%, then coitus interruptus – 18.7% and hormonal preparations – 16.9%. The most important factor of women's reproductive health preservation is a solving of the problem of unwanted pregnancy, and in this respect, the responsibility lies equally in men and women. Analyzing obtained data on contraceptive methods by ranking three of the most frequently used methods are condoms – 29,3%, then coitus interruptus – 18,7% and hormonal preparations – 16,9%. Additional oral survey of the population showed a low level of informational support of female population by family physicians, health care professionals of educational organizations (schools, universities, and colleges) about hormonal contraceptive. Females of both age groups used to think that hormonal contraceptives cause collateral damage such as blastoma, cancer, increased body weight, varix dilatation of lower limbs. Satisfaction with the frequency of sexual relations of the respondents comprised 57,6%. At that, women under 40 years of age are the most satisfied women among age groups (χ2 =5,8, p<0,05).

Keywords: nurse, public health service of Kazakhstan, reproductive and sexual health, trust of population

Procedia PDF Downloads 275
833 Prevalence of ESBL E. coli Susceptibility to Oral Antibiotics in Outpatient Urine Culture: Multicentric, Analysis of Three Years Data (2019-2021)

Authors: Mazoun Nasser Rashid Al Kharusi, Nada Al Siyabi

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Objectives: The main aim of this study is to Find the rate of susceptibility of ESBL E. coli causing UTI to oral antibiotics. Secondary objectives: Prevalence of ESBL E. coli from community urine samples, identify the best empirical oral antibiotics with the least resistance rate for UTI and identify alternative oral antibiotics for testing and utilization. Methods: This study is a retrospective descriptive study of the last three years in five major hospitals in Oman (Khowla Hospital, AN’Nahdha Hospital, Rustaq Hospital, Nizwa Hospital, and Ibri Hospital) equipped with a microbiologist. Inclusion criteria include all eligible outpatient urine culture isolates, excluding isolates from admitted patients with hospital-acquired urinary tract infections. Data was collected through the MOH database. The MOH hospitals are using different types of testing, automated methods like Vitek2 and manual methods. Vitek2 machine uses the principle of the fluorogenic method for organism identification and a turbidimetric method for susceptibility testing. The manual method is done by double disc diffusion for identifying ESBL and the disc diffusion method is for antibiotic susceptibility. All laboratories follow the clinical laboratory science institute (CLSI) guidelines. Analysis was done by SPSS statistical package. Results: Total urine cultures were (23048). E. coli grew in (11637) 49.6% of the urine, whereas (2199) 18.8% of those were confirmed as ESBL. As expected, the resistance rate to amoxicillin and cefuroxime is 100%. Moreover, the susceptibility of those ESBL-producing E. coli to nitrofurantoin, trimethoprim+sulfamethoxazole, ciprofloxacin and amoxicillin-clavulanate is progressing over the years; however, still low. ESBL E. coli was predominating in the female gender and those aged 66-74 years old throughout all the years. Other oral antibiotic options need to be explored and tested so that we add to the pool of oral antibiotics for ESBL E. coli causing UTI in the community. Conclusion: High rate of ESBL E. coli in urine from the community. The high resistance rates to oral antibiotics highlight the need for alternative treatment options for UTIs caused by these bacteria. Further research is needed to identify new and effective treatments for UTIs caused by ESBL-E. Coli.

Keywords: UTI, ESBL, oral antibiotics, E. coli, susceptibility

Procedia PDF Downloads 93
832 The Significance of Childhood in Shaping Family Microsystems from the Perspective of Biographical Learning: Narratives of Adults

Authors: Kornelia Kordiak

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The research is based on a biographical approach and serves as a foundation for understanding individual human destinies through the analysis of the context of life experiences. It focuses on the significance of childhood in shaping family micro-worlds from the perspective of biographical learning. In this case, the family micro-world is interpreted as a complex of beliefs and judgments about elements of the ‘total universe’ based on the individual's experiences. The main aim of the research is to understand the importance of childhood in shaping family micro-worlds from the perspective of reflection on biographical learning. Additionally, it contributes to a deeper understanding of the familial experiences of the studied individuals who form these family micro-worlds and the course of the biographical learning process in the subjects. Biographical research aligns with an interpretative paradigm, where individuals are treated as active interpreters of the world, giving meaning to their experiences and actions based on their own values and beliefs. The research methods used in the project—narrative interview method and analysis of personal documents—enable obtaining a multidimensional perspective on the phenomenon under study. Narrative interviews serve as the main data collection method, allowing researchers to delve into various life contexts of individuals. Analysis of these narratives identifies key moments and life patterns, as well as discovers the significance of childhood in shaping family micro-worlds. Moreover, analysis of personal documents such as diaries or photographs enriches the understanding of the studied phenomena by providing additional contexts and perspectives. The research will be conducted in three phases: preparatory, main, and final. The anticipated schedule includes preparation of research tools, selection of research sample, conducting narrative interviews and analysis of personal documents, as well as analysis and interpretation of collected research material. The narrative interview method and document analysis will be utilized to capture various contexts and interpretations of childhood experiences and family relations. The research will contribute to a better understanding of family dynamics and individual developmental processes. It will allow for the identification and understanding of mechanisms of biographical learning and their significance in shaping identity and family relations. Analysis of adult narratives will enable the identification of factors determining patterns of behavior and attitudes in adult life, which may have significant implications for pedagogical practice.

Keywords: childhood, adulthood, biographical learning, narrative interview, analysis of personal documents, family micro-worlds

Procedia PDF Downloads 31
831 Electron Density Discrepancy Analysis of Energy Metabolism Coenzymes

Authors: Alan Luo, Hunter N. B. Moseley

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Many macromolecular structure entries in the Protein Data Bank (PDB) have a range of regional (localized) quality issues, be it derived from x-ray crystallography, Nuclear Magnetic Resonance (NMR) spectroscopy, or other experimental approaches. However, most PDB entries are judged by global quality metrics like R-factor, R-free, and resolution for x-ray crystallography or backbone phi-psi distribution statistics and average restraint violations for NMR. Regional quality is often ignored when PDB entries are re-used for a variety of structurally based analyses. The binding of ligands, especially ligands involved in energy metabolism, is of particular interest in many structurally focused protein studies. Using a regional quality metric that provides chemically interpretable information from electron density maps, a significant number of outliers in regional structural quality was detected across x-ray crystallographic PDB entries for proteins bound to biochemically critical ligands. In this study, a series of analyses was performed to evaluate both specific and general potential factors that could promote these outliers. In particular, these potential factors were the minimum distance to a metal ion, the minimum distance to a crystal contact, and the isotropic atomic b-factor. To evaluate these potential factors, Fisher’s exact tests were performed, using regional quality criteria of outlier (top 1%, 2.5%, 5%, or 10%) versus non-outlier compared to a potential factor metric above versus below a certain outlier cutoff. The results revealed a consistent general effect from region-specific normalized b-factors but no specific effect from metal ion contact distances and only a very weak effect from crystal contact distance as compared to the b-factor results. These findings indicate that no single specific potential factor explains a majority of the outlier ligand-bound regions, implying that human error is likely as important as these other factors. Thus, all factors, including human error, should be considered when regions of low structural quality are detected. Also, the downstream re-use of protein structures for studying ligand-bound conformations should screen the regional quality of the binding sites. Doing so prevents misinterpretation due to the presence of structural uncertainty or flaws in regions of interest.

Keywords: biomacromolecular structure, coenzyme, electron density discrepancy analysis, x-ray crystallography

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830 Design-Based Elements to Sustain Participant Activity in Massive Open Online Courses: A Case Study

Authors: C. Zimmermann, E. Lackner, M. Ebner

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Massive Open Online Courses (MOOCs) are increasingly popular learning hubs that are boasting considerable participant numbers, innovative technical features, and a multitude of instructional resources. Still, there is a high level of evidence showing that almost all MOOCs suffer from a declining frequency of participant activity and fairly low completion rates. In this paper, we would like to share the lessons learned in implementing several design patterns that have been suggested in order to foster participant activity. Our conclusions are based on experiences with the ‘Dr. Internet’ MOOC, which was created as an xMOOC to raise awareness for a more critical approach to online health information: participants had to diagnose medical case studies. There is a growing body of recommendations (based on Learning Analytics results from earlier xMOOCs) as to how the decline in participant activity can be alleviated. One promising focus in this regard is instructional design patterns, since they have a tremendous influence on the learner’s motivation, which in turn is a crucial trigger of learning processes. Since Medieval Age storytelling, micro-learning units and specific comprehensible, narrative structures were chosen to animate the audience to follow narration. Hence, MOOC participants are not likely to abandon a course or information channel when their curiosity is kept at a continuously high level. Critical aspects that warrant consideration in this regard include shorter course duration, a narrative structure with suspense peaks (according to the ‘storytelling’ approach), and a course schedule that is diversified and stimulating, yet easy to follow. All of these criteria have been observed within the design of the Dr. Internet MOOC: 1) the standard eight week course duration was shortened down to six weeks, 2) all six case studies had a special quiz format and a corresponding resolution video which was made available in the subsequent week, 3) two out of six case studies were split up in serial video sequences to be presented over the span of two weeks, and 4) the videos were generally scheduled in a less predictable sequence. However, the statistical results from the first run of the MOOC do not indicate any strong influences on the retention rate, so we conclude with some suggestions as to why this might be and what aspects need further consideration.

Keywords: case study, Dr. internet, experience, MOOCs, design patterns

Procedia PDF Downloads 268
829 Is the Addition of Computed Tomography with Angiography Superior to a Non-Contrast Neuroimaging Only Strategy for Patients with Suspected Stroke or Transient Ischemic Attack Presenting to the Emergency Department?

Authors: Alisha M. Ebrahim, Bijoy K. Menon, Eddy Lang, Shelagh B. Coutts, Katie Lin

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Introduction: Frontline emergency physicians require clear and evidence-based approaches to guide neuroimaging investigations for patients presenting with suspected acute stroke or transient ischemic attack (TIA). Various forms of computed tomography (CT) are currently available for initial investigation, including non-contrast CT (NCCT), CT angiography head and neck (CTA), and CT perfusion (CTP). However, there is uncertainty around optimal imaging choice for cost-effectiveness, particularly for minor or resolved neurological symptoms. In addition to the cost of CTA and CTP testing, there is also a concern for increased incidental findings, which may contribute to the burden of overdiagnosis. Methods: In this cross-sectional observational study, analysis was conducted on 586 anonymized triage and diagnostic imaging (DI) reports for neuroimaging orders completed on patients presenting to adult emergency departments (EDs) with a suspected stroke or TIA from January-December 2019. The primary outcome of interest is the diagnostic yield of NCCT+CTA compared to NCCT alone for patients presenting to urban academic EDs with Canadian Emergency Department Information System (CEDIS) complaints of “symptoms of stroke” (specifically acute stroke and TIA indications). DI reports were coded into 4 pre-specified categories (endorsed by a panel of stroke experts): no abnormalities, clinically significant findings (requiring immediate or follow-up clinical action), incidental findings (not meeting prespecified criteria for clinical significance), and both significant and incidental findings. Standard descriptive statistics were performed. A two-sided p-value <0.05 was considered significant. Results: 75% of patients received NCCT+CTA imaging, 21% received NCCT alone, and 4% received NCCT+CTA+CTP. The diagnostic yield of NCCT+CTA imaging for prespecified clinically significant findings was 24%, compared to only 9% in those who received NCCT alone. The proportion of incidental findings was 30% in the NCCT only group and 32% in the NCCT+CTA group. CTP did not significantly increase the yield of significant or incidental findings. Conclusion: In this cohort of patients presenting with suspected stroke or TIA, an NCCT+CTA neuroimaging strategy had a higher diagnostic yield for clinically significant findings than NCCT alone without significantly increasing the number of incidental findings identified.

Keywords: stroke, diagnostic yield, neuroimaging, emergency department, CT

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828 Decision-Tree-Based Foot Disorders Classification Using Demographic Variable

Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi

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Background:-Due to the essential role of the foot in movement, foot disorders (FDs) have significant impacts on activity and quality of life. Many studies confirmed the association between FDs and demographic characteristics. On the other hand, recent advances in data collection and statistical analysis led to an increase in the volume of databases. Analysis of patient’s data through the decision tree can be used to explore the relationship between demographic characteristics and FDs. Significance of the study: This study aimed to investigate the relationship between demographic characteristics with common FDs. The second purpose is to better inform foot intervention, we classify FDs based on demographic variables. Methodologies: We analyzed 2323 subjects with pes-planus (PP), pes-cavus (PC), hallux-valgus (HV) and plantar-fasciitis (PF) who were referred to a foot therapy clinic between 2015 and 2021. Subjects had to fulfill the following inclusion criteria: (1) weight between 14 to 150 kilogram, (2) height between 30 to 220, (3) age between 3 to 100 years old, and (4) BMI between 12 to 35. Medical archives of 2323 subjects were recorded retrospectively and all the subjects examined by an experienced physician. Age and BMI were classified into five and four groups, respectively. 80% of the data were randomly selected as training data and 20% tested. We build a decision tree model to classify FDs using demographic characteristics. Findings: Results demonstrated 981 subjects from 2323 (41.9%) of people who were referred to the clinic with FDs were diagnosed as PP, 657 (28.2%) PC, 628 (27%) HV and 213 (9%) identified with PF. The results revealed that the prevalence of PP decreased in people over 18 years of age and in children over 7 years. In adults, the prevalence depends first on BMI and then on gender. About 10% of adults and 81% of children with low BMI have PP. There is no relationship between gender and PP. PC is more dependent on age and gender. In children under 7 years, the prevalence was twice in girls (10%) than boys (5%) and in adults over 18 years slightly higher in men (62% vs 57%). HV increased with age in women and decreased in men. Aging and obesity have increased the prevalence of PF. We conclude that the accuracy of our approach is sufficient for most research applications in FDs. Conclusion:-The increased prevalence of PP in children is probably due to the formation of the arch of the foot at this age. Increasing BMI by applying high pressure on the foot can increase the prevalence of this disorder in the foot. In PC, the Increasing prevalence of PC from women to men with age may be due to genetics and innate susceptibility of men to this disorder. HV is more common in adult women, which may be due to environmental reasons such as shoes, and the prevalence of PF in obese adult women may also be due to higher foot pressure and housekeeping activities.

Keywords: decision tree, demographic characteristics, foot disorders, machine learning

Procedia PDF Downloads 263
827 Fabric-Reinforced Cementitious Matrix (FRCM)-Repaired Corroded Reinforced Concrete (RC) Beams under Monotonic and Fatigue Loads

Authors: Mohammed Elghazy, Ahmed El Refai, Usama Ebead, Antonio Nanni

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Rehabilitating corrosion-damaged reinforced concrete (RC) structures has been accomplished using various techniques such as steel plating, external post-tensioning, and external bonding of fiber reinforced polymer (FRP) composites. This paper reports on the use of an innovative technique to strengthen corrosion-damaged RC structures using fabric-reinforced cementitious matrix (FRCM) composites. FRCM consists of dry-fiber fabric embedded in cement-based matrix. Twelve large-scale RC beams were constructed and tested in flexural monotonic and fatigue loads. Prior to testing, ten specimens were subjected to accelerated corrosion process for 140 days leading to an average mass loss in the tensile steel bars of 18.8 %. Corrosion was restricted to the main reinforcement located in the middle third of the beam span. Eight corroded specimens were repaired and strengthened while two virgin and two corroded-unrepaired/unstrengthened beams were used as benchmarks for comparison purpose. The test parameters included the FRCM materials (Carbon-FRCM, PBO-FRCM), the number of FRCM plies, the strengthening scheme, and the type of loading (monotonic and fatigue). The effects of the pervious parameters on the flexural response, the mode of failure, and the fatigue life were reported. Test results showed that corrosion reduced the yield and ultimate strength of the beams. The corroded-unrepaired specimen failed to meet the provisions of the ACI-318 code for crack width criteria. The use of FRCM significantly increased the ultimate strength of the corroded specimen by 21% and 65% more than that of the corroded-unrepaired specimen. Corrosion significantly decreased the fatigue life of the corroded-unrepaired beam by 77% of that of the virgin beam. The fatigue life of the FRCM repaired-corroded beams increased to 1.5 to 3.8 times that of the corroded-unrepaired beam but was lower than that of the virgin specimen. The specimens repaired with U-wrapped PBO-FRCM strips showed higher fatigue life than those repaired with the end-anchored bottom strips having similar number of PBO-FRCM-layers. PBO-FRCM was more effective than Carbon-FRCM in restoring the fatigue life of the corroded specimens.

Keywords: corrosion, concrete, fabric-reinforced cementitious matrix (FRCM), fatigue, flexure, repair

Procedia PDF Downloads 296
826 In silico Designing of Imidazo [4,5-b] Pyridine as a Probable Lead for Potent Decaprenyl Phosphoryl-β-D-Ribose 2′-Epimerase (DprE1) Inhibitors as Antitubercular Agents

Authors: Jineetkumar Gawad, Chandrakant Bonde

Abstract:

Tuberculosis (TB) is a major worldwide concern whose control has been exacerbated by HIV, the rise of multidrug-resistance (MDR-TB) and extensively drug resistance (XDR-TB) strains of Mycobacterium tuberculosis. The interest for newer and faster acting antitubercular drugs are more remarkable than any time. To search potent compounds is need and challenge for researchers. Here, we tried to design lead for inhibition of Decaprenyl phosphoryl-β-D-ribose 2′-epimerase (DprE1) enzyme. Arabinose is an essential constituent of mycobacterial cell wall. DprE1 is a flavoenzyme that converts decaprenylphosphoryl-D-ribose into decaprenylphosphoryl-2-keto-ribose, which is intermediate in biosynthetic pathway of arabinose. Latter, DprE2 converts keto-ribose into decaprenylphosphoryl-D-arabinose. We had a selection of 23 compounds from azaindole series for computational study, and they were drawn using marvisketch. Ligands were prepared using Maestro molecular modeling interface, Schrodinger, v10.5. Common pharmacophore hypotheses were developed by applying dataset thresholds to yield active and inactive set of compounds. There were 326 hypotheses were developed. On the basis of survival score, ADRRR (Survival Score: 5.453) was selected. Selected pharmacophore hypotheses were subjected to virtual screening results into 1000 hits. Hits were prepared and docked with protein 4KW5 (oxydoreductase inhibitor) was downloaded in .pdb format from RCSB Protein Data Bank. Protein was prepared using protein preparation wizard. Protein was preprocessed, the workspace was analyzed using force field OPLS 2005. Glide grid was generated by picking single atom in molecule. Prepared ligands were docked with prepared protein 4KW5 using Glide docking. After docking, on the basis of glide score top-five compounds were selected, (5223, 5812, 0661, 0662, and 2945) and the glide docking score (-8.928, -8.534, -8.412, -8.411, -8.351) respectively. There were interactions of ligand and protein, specifically HIS 132, LYS 418, TRY 230, ASN 385. Pi-pi stacking was observed in few compounds with basic Imidazo [4,5-b] pyridine ring. We had basic azaindole ring in parent compounds, but after glide docking, we received compounds with Imidazo [4,5-b] pyridine as a basic ring. That might be the new lead in the process of drug discovery.

Keywords: DprE1 inhibitors, in silico drug designing, imidazo [4, 5-b] pyridine, lead, tuberculosis

Procedia PDF Downloads 156
825 Optimization of Chitosan Membrane Production Parameters for Zinc Ion Adsorption

Authors: Peter O. Osifo, Hein W. J. P. Neomagus, Hein V. D. Merwe

Abstract:

Chitosan materials from different sources of raw materials were characterized in order to determine optimal preparation conditions and parameters for membrane production. The membrane parameters such as molecular weight, viscosity, and degree of deacetylation were used to evaluate the membrane performance for zinc ion adsorption. The molecular weight of the chitosan was found to influence the viscosity of the chitosan/acetic acid solution. An increase in molecular weight (60000-400000 kg.kmol-1) of the chitosan resulted in a higher viscosity (0.05-0.65 Pa.s) of the chitosan/acetic acid solution. The effect of the degree of deacetylation on the viscosity is not significant. The effect of the membrane production parameters (chitosan- and acetic acid concentration) on the viscosity is mainly determined by the chitosan concentration. For higher chitosan concentrations, a membrane with a better adsorption capacity was obtained. The membrane adsorption capacity increases from 20-130 mg Zn per gram of wet membrane for an increase in chitosan concentration from 2-7 mass %. Chitosan concentrations below 2 and above 7.5 mass % produced membranes that lack good mechanical properties. The optimum manufacturing conditions including chitosan concentration, acetic acid concentration, sodium hydroxide concentration and crosslinking for chitosan membranes within the workable range were defined by the criteria of adsorption capacity and flux. The adsorption increases (50-120 mg.g-1) as the acetic acid concentration increases (1-7 mass %). The sodium hydroxide concentration seems not to have a large effect on the adsorption characteristics of the membrane however, a maximum was reached at a concentration of 5 mass %. The adsorption capacity per gram of wet membrane strongly increases with the chitosan concentration in the acetic acid solution but remains constant per gram of dry chitosan. The optimum solution for membrane production consists of 7 mass % chitosan and 4 mass % acetic acid in de-ionised water. The sodium hydroxide concentration for phase inversion is at optimum at 5 mass %. The optimum cross-linking time was determined to be 6 hours (Percentage crosslinking of 18%). As the cross-linking time increases the adsorption of the zinc decreases (150-50 mg.g-1) in the time range of 0 to 12 hours. After a crosslinking time of 12 hours, the adsorption capacity remains constant. This trend is comparable to the effect on flux through the membrane. The flux decreases (10-3 L.m-2.hr-1) with an increase in crosslinking time range of 0 to 12 hours and reaches a constant minimum after 12 hours.

Keywords: chitosan, membrane, waste water, heavy metal ions, adsorption

Procedia PDF Downloads 388