Search results for: quiz database

Authors: Biruk Wolde, Atalay Ayele, Yonatan Garkabo, Trufat Hailmariam, Zemenu Germewu

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A comprehensive three-dimensional (3D) geological modeling and engineering geological characterization of shallow subsurface soils and rocks are essential for a wide range of geotechnical and seismological engineering applications, particularly in urban environments. The spatial distribution and geological variation of the shallow subsurface of Addis Ababa city have not been studied so far in terms of geological and geotechnical modeling. This study aims at the construction of a 3D geological model, as well as provides awareness into the engineering geological characteristics of shallow subsurface soil and rock of Addis Ababa city. The 3D geological model was constructed by using more than 1500 geotechnical boreholes, well-drilling data, and geological maps. A well-known geostatistical kriging 3D interpolation algorithm was applied to visualize the spatial distribution and geological variation of the shallow subsurface. Due to the complex nature of geological formations, vertical and lateral variation of the geological profiles horizons-solid command has been selected via the Groundwater Modelling System (GMS) graphical user interface software. For the engineering geological characterization of typical soils and rocks, both index and engineering laboratory tests have been used. The geotechnical properties of soil and rocks vary from place to place due to the uneven nature of subsurface formations observed in the study areas. The constructed model ascertains the thickness, extent, and 3D distribution of the important geological units of the city. This study is the first comprehensive research work on 3D geological modeling and subsurface characterization of soils and rocks in Addis Ababa city, and the outcomes will be important for further future research on subsurface conditions in the city. Furthermore, these findings provide a reference for developing a geo-database for the city.

Keywords: 3d geological modeling, addis ababa, engineering geology, geostatistics, horizons-solid

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Authors: Sekena H. Abd El-Aziem, Heba A. M. Abd El-Kader, Sally S. Alam, Othman E. Othman

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Growth hormone (GH) is an anabolic hormone synthesized and secreted by the somatotroph cells of the anterior lobe of the pituitary gland in a circadian and pulsatile manner, the pattern of which plays an important role in postnatal longitudinal growth and development, tissue growth, lactation, reproduction as well as protein, lipid and carbohydrate metabolism. The aim of this study was to detect the genetic polymorphism of GH gene in five camel breeds reared in Egypt; Sudany, Somali, Mowaled, Maghrabi and Falahy, using PCR-RFLP technique. Also this work aimed to identify the single nucleotide polymorphism between different genotypes detected in these camel breeds. The amplified fragment of camel GH at 613-bp was digested with the restriction enzyme MspI and the result revealed the presence of three different genotypes; CC, CT and TT in tested breeds and significant differences were recorded in the genotype frequencies between these camel breeds. The result showed that the Maghrabi breed that is classified as a dual purpose camels had higher frequency for allele C (0.75) than those in the other tested four breeds. The sequence analysis declared the presence of a SNP (C→T) at position 264 in the amplified fragment which is responsible for the destruction of the restriction site C^CGG and consequently the appearance of two different alleles C and T. The nucleotide sequences of camel GH alleles T and C were submitted to nucleotide sequences database NCBI/Bankit/GenBank and have accession numbers: KP143517 and KP143518, respectively. It is concluded that only one SNP C→T was detected in GH gene among the five tested camel breeds reared in Egypt and this nucleotide substitution can be used as a marker for the genetic biodiversity between camel breeds reared in Egypt. Also, due to the possible association between allele C and higher growth rate, we can used it in MAS for camels and enter the camels possess this allele in breeding program as a way for enhancement of growth trait in camel breeds reared in Egypt.

Keywords: camel breeds in Egypt, GH, PCR-RFLP, SNPs

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Authors: Chaebong Kim, Yongmin Cho, Minkyung Han, Mooyoung Kim, KooSang Kim

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Background: Air pollution from global warming has a considerable influence on respiratory disease and atopic dermatitis (AD). Present studies base on a hypothesis about correlation between air pollutant and AD, and the results are analyzed from various points of view. Objectives: This study aimed to integrate the relevant researches for air pollutant and AD, and to perform the systematic literature review and meta-analysis to provide the basis of air pollutant control. Methods: Research materials were collected from original articles published in English academic journals including medicine, nursing and health science from August 1 to 31, 2016. We collected the materials from Pubmed, Medline, Embase, Cochrane Central database with Prisma (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) based on the Cochrane Systematic Review Manual, and performed the evaluation and analysis for selected materials. We got the research results for risk of bias using Rev-Man ver. 5.2, and meta analyses using STATA. Results: The prevalence of infantile atopic dermatitis were 1.05 times higher than other groups who were exposed to air pollution, and exposure to NO2 (1.08, 95% CI: 1.02 – 1.14), O3 (1.09, 95% CI: 1.04 – 1.15), SO2 (1.07, 95% CI: 1.02 – 1.12) in subgroup air pollutant was considerably associated with infantile atopic dermatitis. The prevalence of infantile atopic dermatitis was 1.03 times higher than other groups who were exposed to PM2.5, but the results were not statistically similar. Conclusion: Health effect from environmental pollution risen people’s interest in environmental diseases. Air pollutant was associated with AD in this study, but selected literature was based on non-RCT (Randomized Controlled Trial) study. Therefore, there was a limit in study method including control, matching, and correction of confounding variables. For clear conclusion, it is necessary to develop the appropriate tool for object of study and clear standard to measure of air pollutant.

Keywords: air pollution, atopic dermatitis, children, meta-analysis

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Authors: Felix Eyben, Simon Schaffrath, Markus Feldmann

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A building should maximize the potential for use through its design. Therefore, flexible use is always important when designing a steel structure. To create flexibility, steel beams with web openings are increasingly used, because these offer the advantage that cables, pipes and other technical equipment can easily be routed through without detours, allowing for more space-saving and aesthetically pleasing construction. This can also significantly reduce the height of ceiling systems. Until now, beams with web openings were not explicitly considered in the European standard. However, this is to be done with the new EN 1993-1-13, in which design rules for different opening forms are defined. In order to further develop the design concepts, beams with web openings under bending are therefore to be investigated in terms of damage mechanics as part of a German national research project aiming to optimize the verifications for steel structures based on a wider database and a validated damage prediction. For this purpose, first, fundamental factors influencing the load-bearing behavior of girders with web openings under bending load were investigated numerically without taking material damage into account. Various parameter studies were carried out for this purpose. For example, the factors under study were the opening shape, size and position as well as structural aspects as the span length, arrangement of stiffeners and loading situation. The load-bearing behavior is evaluated using resulting load-deformation curves. These results are compared with the design rules and critically analyzed. Experimental tests are also planned based on these results. Moreover, the implementation of damage mechanics in the form of the modified Bai-Wierzbicki model was examined. After the experimental tests will have been carried out, the numerical models are validated and further influencing factors will be investigated on the basis of parametric studies.

Keywords: damage mechanics, finite element, steel structures, web openings

Procedia PDF Downloads 146

Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan

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Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of Big Data Technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centers or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through Vader and Roberta model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and TFIDF Vectorization, and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.

Keywords: counter vectorization, convolutional neural network, crawler, data technology, long short-term memory, web scraping, sentiment analysis

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Authors: Apostolos Kalatzis, Ashish Teotia, Vishnunarayan Girishan Prabhu, Laura Stanley

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Emotions are functional behaviors influenced by thoughts, stimuli, and other factors that induce neurophysiological changes in the human body. Understanding and classifying emotions are challenging as individuals have varying perceptions of their environments. Therefore, it is crucial that there are publicly available databases and virtual reality (VR) based environments that have been scientifically validated for assessing emotional classification. This study utilized two commercially available VR applications (Guided Meditation VR™ and Richie’s Plank Experience™) to induce acute stress and calm state among participants. Subjective and objective measures were collected to create a validated multimodal dataset and classification scheme for affective state classification. Participants’ subjective measures included the use of the Self-Assessment Manikin, emotional cards and 9 point Visual Analogue Scale for perceived stress, collected using a Virtual Reality Assessment Tool developed by our team. Participants’ objective measures included Electrocardiogram and Respiration data that were collected from 25 participants (15 M, 10 F, Mean = 22.28  4.92). The features extracted from these data included heart rate variability components and respiration rate, both of which were used to train two machine learning models. Subjective responses validated the efficacy of the VR applications in eliciting the two desired affective states; for classifying the affective states, a logistic regression (LR) and a support vector machine (SVM) with a linear kernel algorithm were developed. The LR outperformed the SVM and achieved 93.8%, 96.2%, 93.8% leave one subject out cross-validation accuracy, precision and recall, respectively. The VR assessment tool and data collected in this study are publicly available for other researchers.

Keywords: affective computing, biosignals, machine learning, stress database

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Authors: Hui Wang

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Traditional collection building approaches are limited in breadth and scope and are not necessarily suitable for multidisciplinary fields development in the institutes of the Chinese Academy of Sciences. The increasing of multidisciplinary fields researches require a viable approach to collection development in these libraries. This study uses qualitative and quantitative analysis to assess collection. The quantitative analysis consists of three levels of evaluation, which including realistic demand, potential demand and trend demand analysis. For one institute, three samples were separately selected from the object institute, more than one international top institutes in highly relative research fields and future research hotspots. Each sample contains an appropriate number of papers published in recent five years. Several keywords and the organization names were reasonably combined to search in commercial databases and the institutional repositories. The publishing information and citations in the bibliographies of these papers were selected to build the dataset. One weighted evaluation model and citation analysis were used to calculate the demand intensity index of every journal and book. Principal Investigator selector and database traffic provide a qualitative evidence to describe the demand frequency. The demand intensity, demand frequency and academic committee recommendations were comprehensively considered to recommend collection development. The collection gaps or weaknesses were ascertained by comparing the current collection and the recommend collection. This approach was applied in more than 80 institutes’ libraries in Chinese Academy of Sciences in the past three years. The evaluation results provided an important evidence for collections building in the second year. The latest user survey results showed that the updated collection’s capacity to support research in a multidisciplinary subject area have increased significantly.

Keywords: citation analysis, collection assessment, collection development, quantitative analysis

Procedia PDF Downloads 192

Authors: Taha SamadSoltani, Peyman Rezaei Hachesu, Marjan GhaziSaeedi, Maryam Zolnoori

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Introduction: Data mining defined as a process to find patterns and relationships along data in the database to build predictive models. Application of data mining extended in vast sectors such as the healthcare services. Medical data mining aims to solve real-world problems in the diagnosis and treatment of diseases. This method applies various techniques and algorithms which have different accuracy and precision. The purpose of this study was to apply knowledge discovery and data mining techniques for the diagnosis of asthma based on patient symptoms and history. Method: Data mining includes several steps and decisions should be made by the user which starts by creation of an understanding of the scope and application of previous knowledge in this area and identifying KD process from the point of view of the stakeholders and finished by acting on discovered knowledge using knowledge conducting, integrating knowledge with other systems and knowledge documenting and reporting.in this study a stepwise methodology followed to achieve a logical outcome. Results: Sensitivity, Specifity and Accuracy of KNN, SVM, Naïve bayes, NN, Classification tree and CN2 algorithms and related similar studies was evaluated and ROC curves were plotted to show the performance of the system. Conclusion: The results show that we can accurately diagnose asthma, approximately ninety percent, based on the demographical and clinical data. The study also showed that the methods based on pattern discovery and data mining have a higher sensitivity compared to expert and knowledge-based systems. On the other hand, medical guidelines and evidence-based medicine should be base of diagnostics methods, therefore recommended to machine learning algorithms used in combination with knowledge-based algorithms.

Keywords: asthma, datamining, classification, machine learning

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Authors: Enrique Claver Cortés, Bartolomé Marco Lajara, Eduardo Sánchez García, Pedro Seva Larrosa, Encarnación Manresa Marhuenda, Lorena Ruiz Fernández, Esther Poveda Pareja

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In recent decades, the analysis of the effects of clustering as an essential factor for the development of innovations and the competitiveness of enterprises has raised great interest in different areas. Nowadays, companies have access to almost all tangible and intangible resources located and/or developed in any country in the world. However, despite the obvious advantages that this situation entails for companies, their geographical location has shown itself, increasingly clearly, to be a fundamental factor that positively influences their innovative performance and competitiveness. Industrial clusters could represent a unique level of analysis, positioned between the individual company and the industry, which makes them an ideal unit of analysis to determine the effects derived from company membership of a cluster. Also, the absorptive capacity (hereinafter 'AC') can mediate the process of innovation development by companies located in a cluster. The transformation and exploitation of knowledge could have a mediating effect between knowledge acquisition and innovative performance. The main objective of this work is to determine the key factors that affect the degree of generation and use of knowledge from the environment by companies and, consequently, their innovative performance and competitiveness. The elements analyzed are the companies' membership of a cluster and the AC. To this end, 30 most relevant papers published on this subject in the "Web of Science" database have been reviewed. Our findings show that, within a cluster, the knowledge coming from the companies' environment can significantly influence their innovative performance and competitiveness, although in this relationship, the degree of access and exploitation of the companies to this knowledge plays a fundamental role, which depends on a series of elements both internal and external to the company.

Keywords: absorptive capacity, clusters, innovation, knowledge

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Authors: L. Melzerová, T. Janda, M. Šejnoha, J. Šejnoha

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Two finite element (FEM) models are presented in this paper to address the random nature of the response of glued timber structures made of wood segments with variable elastic moduli evaluated from 3600 indentation measurements. This total database served to create the same number of ensembles as was the number of segments in the tested beam. Statistics of these ensembles were then assigned to given segments of beams and the Latin Hypercube Sampling (LHS) method was called to perform 100 simulations resulting into the ensemble of 100 deflections subjected to statistical evaluation. Here, a detailed geometrical arrangement of individual segments in the laminated beam was considered in the construction of two-dimensional FEM model subjected to in four-point bending to comply with the laboratory tests. Since laboratory measurements of local elastic moduli may in general suffer from a significant experimental error, it appears advantageous to exploit the full scale measurements of timber beams, i.e. deflections, to improve their prior distributions with the help of the Bayesian statistical method. This, however, requires an efficient computational model when simulating the laboratory tests numerically. To this end, a simplified model based on Mindlin’s beam theory was established. The improved posterior distributions show that the most significant change of the Young’s modulus distribution takes place in laminae in the most strained zones, i.e. in the top and bottom layers within the beam center region. Posterior distributions of moduli of elasticity were subsequently utilized in the 2D FEM model and compared with the original simulations.

Keywords: Bayesian inference, FEM, four point bending test, laminated timber, parameter estimation, prior and posterior distribution, Young’s modulus

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Authors: Arman Kishan, Mark Haft, Steve Li, Duc Nguyen, Dawn Laporte

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Objective: Patients with Type 2 diabetes (T2DM) often face higher postoperative complication rates. Limited data exist on outcomes in T2DM patients undergoing carpal tunnel release (CTR). This study aims to compare complication rates between endoscopic CTR (ECTR) and open CTR (OCTR) in patients with T2DM. Methods: This was a retrospective cohort study using the TriNetX database of 56741 patients with T2DM undergoing ECTR (N= 14,949) or OCTR (N= 41,792). Demographic data, medical comorbidities, and complication rates were analyzed. We used multivariable analysis to identify differences in postoperative complication rates between the two treatment methods in patients with T2DM. Results: Patients with T2DM undergoing ECTR had a significantly lower incidence of 90-day wound infection (p < 0.001), 90-day wound dehiscence (p < 0.001), and nerve injury (p < 0.001) when compared to patients who underwent OCTR. After matching, there was a significantly higher number of T2DM patients undergoing ECTR who had peripheral vascular disease (p = 0.045) and hypertension (p = 0.020) when compared to the OCTR group. These patients also had a lower incidence of fluid and electrolyte disorders (p = 0.002) and chronic blood loss anemia (p = 0.025). Conclusion: ECTR presents a superior choice for T2DM patients undergoing CTR, yielding significantly lower rates of wound infection, wound dehiscence, and nerve injury within 90 days post-surgery—reducing the risk by 31%, 48%, and 59%, respectively. These findings support the adoption of ECTR as the preferred method in this patient population, potentially leading to improved postoperative outcomes.

Keywords: endoscopic treatment of carpal tunnel syndrome, open treatment of carpal tunnel syndrome, carpal tunnel syndrome, postoperative complications in patients with diabetes mellitus

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Authors: Auwal Garba, Rabiu Maijama’a, Abdullahi Muhammad Jalam

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Variability in climate has affected the agricultural production all over the globe. This concern has motivated important changes in the field of research during the last decade. Climate variability is believed to have declining effects towards rice production in Nigeria. This study examined climate variability and its impact on rice productivity in Dass Local Government Area, Bauchi State, by employing Linear Trend Model (LTM), analysis of variance (ANOVA) and regression analysis. Annual seasonal data of the climatic variables for temperature (min. and max), rainfall, and solar radiation from 1990 to 2015 were used. Results confirmed that 74.4% of the total variation in rice yield in the study area was explained by the changes in the independent variables. That is to say, temperature (minimum and maximum), rainfall, and solar radiation explained rice yield with 74.4% in the study area. Rising mean maximum temperature would lead to reduction in rice production while moderate increase in mean minimum temperature would be advantageous towards rice production, and the persistent rise in the mean maximum temperature, in the long run, will have more negatively affect rice production in the future. It is, therefore, important to promote agro-meteorological advisory services, which will be useful in farm planning and yield sustainability. Closer collaboration among the meteorologist and agricultural scientist is needed to increase the awareness about the existing database, crop weather models among others, with a view to reaping the full benefits of research on specific problems and sustainable yield management and also there should be a special initiative by the ADPs (State Agricultural Development Programme) towards promoting best agricultural practices that are resilient to climate variability in rice production and yield sustainability.

Keywords: climate variability, impact, productivity, rice

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Authors: Hyelim Park, Juan Martin Zorrilla

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Climate change influences very widely and in various ways ocean ecosystem functioning. The consequences of climate change on marine ecosystems are an increase in temperature and irregular behavior of some solute concentrations. These changes would affect fisheries catches in several ways. Our aim is to assess the quantitative contribution change of fishery catches along the time and express them through four environment variables: Sea Surface Temperature (SST4) and the concentrations of Chlorophyll (CHL), Particulate Inorganic Carbon (PIC) and Particulate Organic Carbon (POC) at two spatial scales: Global and the nineteen FAO Major Fishing Areas divisions. Data collection was based on the FAO FishStatJ 2014 database as well as MODIS Aqua satellite observations from 2002 to 2012. Some data had to be corrected and interpolated using some existing methods. As the results, a multivariable regression model for average Global fisheries captures contained temporal mean of SST4, standard deviation of SST4, standard deviation of CHL and standard deviation of PIC. Global vector auto-regressive (VAR) model showed that SST4 was a statistical cause of global fishery capture. To accommodate varying conditions in fishery condition and influence of climate change variables, a model was constructed for each FAO major fishing area. From the management perspective it should be recognized some limitations of the FAO marine areas division that opens to possibility to the discussion of the subdivision of the areas into smaller units. Furthermore, it should be treated that the contribution changes of fishery species and the possible environment factor for specific species at various scale levels.

Keywords: fisheries-catch, FAO FishStatJ, MODIS Aqua, sea surface temperature (SST), chlorophyll, particulate inorganic carbon (PIC), particulate organic carbon (POC), VAR, granger causality

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Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. It also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Gary Young, David Zepeda, Gilbert Nyaga

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This study investigated whether vertical integration of hospitals and physicians is associated with better care for patients with cardiac conditions. A dramatic change in the U.S. hospital industry is the integration of hospital and physicians through hospital acquisition of physician practices. Yet, there is little evidence regarding whether this form of vertical integration leads to better operational performance of hospitals. The study was conducted as an observational investigation based on a pooled, cross-sectional database. The study sample comprised over hospitals in the State of California. The time frame for the study was 2010 to 2012. The key performance measure was hospitals’ degree of compliance with performance criteria set out by the federal government for managing patients with cardiac conditions. These criteria relate to the types of clinical tests and medications that hospitals should follow for cardiac patients but hospital compliance requires the cooperation of a hospital’s physicians. Data for this measure was obtained from a federal website that presents performance scores for U.S. hospitals. The key independent variable was the percentage of cardiologists that a hospital employs (versus cardiologists who are affiliated but not employed by the hospital). Data for this measure was obtained from the State of California which requires hospitals to report financial and operation data each year including numbers of employed physicians. Other characteristics of hospitals (e.g., information technology for cardiac care, volume of cardiac patients) were also evaluated as possible complements or substitutes for physician employment by hospitals. Additional sources of data included the American Hospital Association and the U.S. Census. Empirical models were estimated with generalized estimating equations (GEE). Findings suggest that physician employment is positively associated with better hospital performance for cardiac care. However, findings also suggest that information technology is a substitute for physician employment.

Keywords: physician employment, hospitals, verical integration, cardiac care

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Authors: Lani Fraizer

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Increasingly, individuals from diverse professional and academic backgrounds are making a conscious choice to pursue careers related to social change; a sophisticated understanding of social entrepreneur education is becoming ever more important. Social entrepreneurs are impassioned change makers who characteristically combine leadership and entrepreneurial spirits to problem solve social ills affecting our planet. Generating partnership opportunities and nurturing them is an important part of their change-making work. Faced with the complexities of these partnerships, social entrepreneurs and people who work with them need to be well prepared to tackle new and unforeseen challenges faced. As partnerships become even more critical to advance initiatives at scale, for example, understanding the partnership brokering role is even more important for educators who prepare these leaders to establish and sustain multi-stakeholder partnerships. This paper aims to provide practitioners in social entrepreneurship with enhanced knowledge of partnership brokering and identify directions for future research. A literature review search from January 1977 to May 2015 was conducted using the combined keywords ‘partnership brokering’ and ‘social entrepreneurship’ via WorldCat, one of the largest database catalogs in the world with collections of more than 10,000 worldwide. This query focused on literature written in the English language and analyzed solely the role of partnership brokering in social entrepreneurship. The synthesis of the literature review found three main themes emerging: the need for more professional awareness of partnership brokering and its value add in systems change-making work, the need for more knowledge on developing partnership brokering competencies, and the need for more applied research in the area of partnership brokering and how it is practiced by practitioners in social entrepreneurship. The results of the review serve to emphasize and reiterate the importance of partnership brokers in social entrepreneurship work, and act as a reminder of the need for further scholarly research in this area to bridge the gap between practice and research.

Keywords: partnership brokering, leadership, social entrepreneurship, systems changemaking

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Authors: Deginet Aklilu, Tianqi Wang, Endwoke Amsalu, Wei Feng, Zhiwei Li, Xia Li, Lixin Tao, Yanxia Luo, Moning Guo, Xiangtong Liu, Xiuhua Guo

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Extreme temperature-related cardiovascular diseases (CVDs) have become a growing public health concern. However, the impact of temperature on the cause of specific CVDs has not been well studied in the study area. The objective of this study was to assess the impact of temperature on cause-specific cardiovascular hospital admissions in Beijing, China. We obtained data from 172 large general hospitals from the Beijing Public Health Information Center Cardiovascular Case Database and China. Meteorological Administration covering 16 districts in Beijing from 2013 to 2017. We used a time-stratified case crossover design with a distributed lag nonlinear model (DLNM) to derive the impact of temperature on CVD in hospitals back to 27 days on CVD admissions. The temperature data were stratified as cold (extreme and moderate ) and hot (moderate and extreme ). Within five years (January 2013-December 2017), a total of 460,938 (male 54.9% and female 45.1%) CVD admission cases were reported. The exposure-response relationship for hospitalization was described by a "J" shape for the total and cause-specific. An increase in the six-day moving average temperature from moderate hot (30.2 °C) to extreme hot (36.9 °C) resulted in a significant increase in CVD admissions of 16.1%(95% CI = 12.8%-28.9%). However, the effect of cold temperature exposure on CVD admissions over a lag time of 0-27 days was found to be non significant, with a relative risk of 0.45 (95% CI = 0.378-0.55) for extreme cold (-8.5 °C)and 0.53 (95% CI = 0.47-0.60) for moderate cold (-5.6 °C). The results of this study indicate that exposure to extremely high temperatures is highly associated with an increase in cause-specific CVD admissions. These finding may guide to create and raise awareness of the general population, government and private sectors regarding on the effects of current weather conditions on CVD.

Keywords: admission, Beijing, cardiovascular diseases, distributed lag non linear model, temperature

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Authors: Betül Sönmez, Aytolan Yıldırım

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Objective: This systematic review aims to methodically analyze studies regarding mobbing behavior prevalence, individuals performing this behavior and the effects of mobbing on Turkish nurses. Background: Worldwide reports on mobbing cases have increased in the past years, a similar trend also observable in Turkey. It has been demonstrated that among healthcare workers, mobbing is significantly widespread in nurses. The number of studies carried out in this regard has also increased. Method: The main criteria for choosing articles in this systematic review were nurses located in Turkey, regardless of any specific date. In November 2014, a search using the keywords 'mobbing, bullying, psychological terror/violence, emotional violence, nurses, healthcare workers, Turkey' in PubMed, Science Direct, Ebscohost, National Thesis Centre database and Google search engine led to 71 studies in this field. 33 studies were not met the inclusion criteria specified for this study. Results: The findings were obtained using the results of 38 studies carried out in the past 13 years in Turkey, a large sample consisting of 8,877 nurses. Analysis of the incidences of mobbing behavior revealed a broad spectrum, ranging from none-slight experiences to 100% experiences. The most frequently observed mobbing behaviors include attacking personality, blocking communication and attacking professional and social reputation. Victims mostly experienced mobbing from their managers, the most common consequence of these actions being psychological effects. Conclusions: The results of studies with various scales indicate exposure of nurses to similar mobbing behavior. The high frequency of exposure of nurses to mobbing behavior in such a large sample highlights the importance of considering this issue in terms of individual and institutional consequences that adversely affect the performance of nurses.

Keywords: mobbing, bullying, workplace violence, nurses, Turkey

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Authors: Kai-Yao Huang, Tzong-Yi Lee, Pin-Hao Ho, Tzu-Hao Chang, Cheng-Wei Chang

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Background: Human cytomegalovirus (HCMV) infects much people around the world, and there were many researches mention that many diseases were caused by HCMV. To understand the mechanism of HCMV lead to diseases during infection. We observe a microRNA (miRNA) – miRNA interaction between HCMV and host during infection. We found HCMV miRNA sequence component complementary with host miRNA precursors, and we also found that the host miRNA abundances were decrease in HCMV infection. Hence, we focus on the host miRNA which may target by the other HCMV miRNA to find theirs target mRNAs expression and analysis these mRNAs affect what kind of signaling pathway. Interestingly, we found the affected mRNA play an important role in some diseases related pathways, and these diseases had been annotated by HCMV infection. Results: From our analysis procedure, we found 464 human miRNAs might be targeted by 26 HCMV miRNAs and there were 291 human miRNAs shows the concordant decrease trend during HCMV infection. For case study, we found hcmv-miR-US22-5p may regulate hsa-mir-877 and we analysis the KEGG pathway which built by hsa-mir-877 validate target mRNA. Additionally, through survey KEGG Disease database found that these mRNA co-regulate some disease related pathway for instance cancer, nerve disease. However, there were studies annotated that HCMV infection casuse cancer and Alzheimer. Conclusions: This work supply a different scenario of miRNA target interactions(MTIs). In previous study assume miRNA only target to other mRNA. Here we wonder there is possibility that miRNAs might regulate non-mRNA targets, like other miRNAs. In this study, we not only consider the sequence similarity with HCMV miRNAs and human miRNA precursors but also the expression trend of these miRNAs. Then we analysis the human miRNAs validate target mRNAs and its associated KEGG pathway. Finally, we survey related works to validate our investigation.

Keywords: human cytomegalovirus, HCMV, microRNA, miRNA

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Authors: Hui-Chi Huang, Su-Ju Yang, Ching-Wei Lin, Jui-Yao Tsai, Liang-Yiang

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Background: The most common serious complication following acute stroke is pneumonia. It has been associated with the increased morbidity, mortality, and medical cost after acute stroke in elderly patients. Purpose: The aim of this retrospective study was to investigate the relationship between stroke patients, risk factors of pneumonia, and one-year survival rates in a group of patients, in a tertiary referal center in Northern Taiwan. Methods: From January 2012 to December 2013, a total of 1730 consecutively administered stroke patients were recruited. The Survival analysis and multivariate regression analyses were used to examine the predictors for the one-year survival in stroke patients of a stroke registry database from northern Taiwan. Results: The risk of stroke mortality increased with age≧ 75 (OR=2.305, p < .0001), cancer (OR=3.221, p=<.0001), stayed in intensive care unit (ICU) (OR=2.28, p <.0006), dysphagia (OR=5.026, p<.0001), without speech therapy(OR=0.192, p < .0001),serum albumin < 2.5(OR=0.322, p=.0053) , eGFR > 60(OR=0.438, p <. 0001), admission NIHSS >11(OR=1.631, p=.0196), length of hospitalization (d) > 30(OR=0.608, p=.0227), and stroke subtype (OR=0.506, p=.0032). After adjustment of confounders, pneumonia was not significantly associated with the risk of mortality. However, it is most likely to develop in patients who are age ≧ 75, dyslipidemia , coronary artery disease , albumin < 2.5 , eGFR <60 , ventilator use , stay in ICU , dysphagia, without speech therapy , urinary tract infection , Atrial fibrillation , Admission NIHSS > 11, length of hospitalization > 30(d) , stroke severity (mRS=3-5) ,stroke Conclusion: In this study, different from previous research findings, we found that elderly age, severe neurological deficit and rehabilitation therapy were significantly associated with Post-stroke Pneumonia. However, specific preventive strategies are needed to target the high risk groups to improve their long-term outcomes after acute stroke. These findings could open new avenues in the management of stroke patients.

Keywords: stroke, risk, pneumonia, survival

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Authors: Avirup Chowdhury, Angus K. McFadyen, Linsey Batchelor

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Blood cultures (BCs) are an important aspect of management of the septic patient, identifying the underlying pathogen and its antibiotic sensitivities. However, while the current literature outlines indications for initial BCs to be taken, there is little guidance for repeat sampling in the following 5-day period and little information on how antibiotic use can affect the usefulness of this investigation. A retrospective cohort study was conducted using inpatients who had undergone 2 or more BCs within 5 days between April 2016 and April 2017 at a 400-bed hospital in the west of Scotland and received antibiotic therapy between the first and second BCs. The data for BC sampling was collected from the electronic microbiology database, and cross-referenced with data from the hospital electronic prescribing system. Overall, 283 BCs were included in the study, taken from 92 patients (mean 3.08 cultures per patient, range 2-10). All 92 patients had initial BCs, of which 83 were positive (90%). 65 had a further sample within 24 hours of commencement of antibiotics, with 35 positive (54%). 23 had samples within 24-48 hours, with 4 (17%) positive; 12 patients had sampling at 48-72 hours, 12 at 72-96 hours, and 10 at 96-120 hours, with none positive. McNemar’s Exact Test was used to calculate statistical significance for patients who received blood cultures in multiple time blocks (Initial, < 24h, 24-120h, > 120h). For initial vs. < 24h-post BCs (53 patients tested), the proportion of positives fell from 46/53 to 29/53 (one-tailed P=0.002, OR 3.43, 95% CI 1.48-7.96). For initial vs 24-120h (n=42), the proportions were 38/42 and 4/42 respectively (P < 0.001, OR 35.0, 95% CI 4.79-255.48). For initial vs > 120h (n=36), these were 33/36 and 2/36 (P < 0.001,OR ∞). These were also calculated for a positive in initial or < 24h vs. 24-120h (n=42), with proportions of 41/42 and 4/42 (P < 0.001, OR 38.0, 95% CI 5.22-276.78); and for initial or < 24h vs > 120h (n=36), with proportions of 35/36 and 2/36 respectively (P < 0.001, OR ∞). This data appears to show that taking an initial BC followed by a BC within 24 hours of antibiotic commencement would maximise blood culture yield while minimising the risk of false negative results. This could potentially remove the need for as many as 46% of BC samples without adversely affecting patient care. BC yield decreases sharply after 48 hours of antibiotic use, and may not provide any clinically useful information after this time. Further multi-centre studies would validate these findings, and provide a foundation for future health policy generation.

Keywords: antibiotics, blood culture, efficacy, inpatient

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Authors: Odunayo S. Faluse, Roger Telfer

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Customer relationship management is a business strategy that is centred on the idea that ‘Customer is the driving force of any business’ i.e. Customer is placed in a central position in any business. However, this belief coupled with the advancement in information technology in the past twenty years has experienced a change. In any form of business today it can be concluded that customers are the modern dictators to whom the industry always adjusts its business operations due to the increase in availability of information, intense market competition and ever growing negotiating ideas of customers in the process of buying and selling. The most vital role of any organization is to satisfy or meet customer’s needs and demands, which eventually determines customer’s long-term value to the industry. Therefore, this paper analyses and describes the application of customer relationship management operational strategies in some of the major industries in business. Both developed and up-coming companies nowadays value the quality of customer services and client’s loyalty, they also recognize the customers that are not very sensitive when it comes to changes in price and thereby realize that attracting new customers is more tasking and expensive than retaining the existing customers. However, research shows that several factors have recently amounts to the sudden rise in the execution of CRM strategies in the marketplace, such as a diverted attention of some organization towards integrating ideas in retaining existing customers rather than attracting new one, gathering data about customers through the use of internal database system and acquiring of external syndicate data, also exponential increase in technological intelligence. Apparently, with this development in business operations, CRM research in Academia remain nascent; hence this paper gives detailed critical analysis of the recent advancement in the use of CRM and key research opportunities for future development in using the implementation of CRM as a determinant factor for successful business optimization.

Keywords: agriculture, banking, business strategies, CRM, education, healthcare

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Authors: Nighat Bakhtiar, Ali Raza Khan, Shahid Khan Khattak, Aamir Ali Syed

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Introduction: Chemoradiation followed by resection has been the standard therapy for resectable (cT1-4aN0-3M0) esophageal carcinoma. The optimal surgical approach remains a matter of debate. Therefore, the purpose of this study was to share our experiences of minimal invasive esophagectomies concerning morbidity, mortality and oncological quality. This study aims to enlighten the world about the surgical outcomes after minimally invasive esophagectomy at Shaukat Khanum Hospital Lahore. Objective: The purpose of this study is to review an institutional experience of Surgical outcomes of Minimal Invasive esophagectomies for esophageal cancer. Methodology: This retrospective study was performed after ethical approval at Shaukat Khanum Memorial Cancer Hospital and Research Centre (SKMCH&RC) Pakistan. Patients who underwent Minimal Invasive esophagectomies for esophageal cancer from March 2018 to March 2023 were selected. Data was collected through the human information system (HIS) electronic database of SKMCH&RC. Data was described using mean and median with minimum and maximum values for quantitative variables. For categorical variables, a number of observations and percentages were reported. Results: A total of 621 patients were included in the study, with the mean age of the patient was 39 years, ranging between 18-58 years. Mean Body Mass Index of patients was 21.2.1±4.1. Neo-adjuvant chemoradiotherapy was given to all patients. The mean operative time was 210.36 ± 64.51 minutes, and the mean blood loss was 121 milliliters. There was one mortality in 90 days, while the mean postoperative hospital stay was 6.58 days with a 4.64 standard deviation. The anastomotic leak rate was 4.2%. Chyle leak was observed in 12 patients. Conclusion: The minimal invasive technique is a safe approach for esophageal cancers, with minimal complications and fast recovery.

Keywords: minimal invasive, esophagectomy, laparscopic, cancer

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Authors: Rimel Mwamba, Mohan Gundeti

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Introduction: The use of robot-assisted laparoscopic surgeries (RALS) has largely increased in recent years, offering faster and safer treatment options for pediatric patients. In the field of urology, RALS has shown a significant advantage over laparoscopic and open surgeries but continues to be controversial in pediatric cases due to limited comprehensive data on its use. Methods: In this review, we aim to summarize the factors associated with RALS use in pediatric cases involving pyeloplasty, ureteral reimplantation, heminephrectomy, and lower urinary tract reconstruction. We used PubMed, EMBASE, and the Cochrane Database of Systematic Reviews to systematically search for literature on the topic. We then critically assessed and compiled data on RALS outcomes, complications, and associated factors. Results: To date, numerous comparative studies have been conducted on pediatric RALS, with only one randomized control trial investigating the nuances of robotic use against standard of care treatments. These robotic approaches have shown promise in post-surgical outcomes for pediatric patients undergoing upper and lower urinary tract reconstruction. Barriers to use still persist, however, showcasing a need to increase access to the technology, refine instruments for pediatric use, address cost barriers, and provide proper training for surgeons. Conclusion: RALS providesan opportunity to improve pediatric patient outcomes for numerous urologic complications. Additional studies are required to better compare the use of RALS with current standard practices. Due to the difficult nature of conducting randomized control trials, additional prospective observational studies are needed.

Keywords: pediatric urology, robot-assisted laparoscopic surgeries (RALS), pyeloplasty, ureteral reimplantation, heminephrectomy, and lower urinary tract reconstruction

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Authors: Gertrude I. Hewapathirana, Loi A. Nguyen, Mohammed M. Mostafa

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Artificial intelligence (AI) technologies and tools are swiftly integrating into many functions of all organizations as a competitive drive to enhance innovations, productivity, efficiency, faster and precise decision making to keep up with rapid changes in the global business arena. Despite increasing research on AI technologies in production, manufacturing, and information management, AI in human resource disciplines is still lagging. Though a few research studies on HR informatics, recruitment, and HRM in general, how to integrate AI in other HR functional disciplines (e.g., compensation, training, mentoring and coaching, employee motivation) is rarely researched. Many inconsistencies of research hinder developing up-to-date knowledge on AI in HR disciplines. Therefore, exploring eight research questions, using bibliometric network analysis combined with a meta-analysis of published research literature. The authors attempt to generate knowledge on the role of AI in improving the efficiency of HR functional disciplines. To advance the knowledge for the benefit of researchers, academics, policymakers, and practitioners, the study highlights the types of AI innovations and outcomes, trends, gaps, themes and topics, fast-moving disciplines, key players, and future directions.AI in HR informatics in high tech firms is the dominant theme in many research publications. While there is increasing attention from researchers and practitioners, there are many gaps between the promise, potential, and real AI applications in HR disciplines. A higher knowledge gap raised many unanswered questions regarding legal, ethical, and morale aspects of AI in HR disciplines as well as the potential contributions of AI in HR disciplines that may guide future research directions. Though the study provides the most current knowledge, it is limited to peer-reviewed empirical, theoretical, and conceptual research publications stored in the WoS database. The implications for theory, practice, and future research are discussed.

Keywords: artificial intelligence, human resources, bibliometric analysis, research directions

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Authors: Claudeny Simone Alves Santana, Alexandre Simas De Medeiros, Marcelino Aurélio Vieira Da Silva

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The aim of the study was to assess the performance of pavements over time, considering the principles of Life Cycle Assessment (LCA) and the ability to withstand vehicle loads and associated environmental impacts. Within the study boundary, pavement design was conducted using the Mechanistic-Empirical Method, adopting criteria based on pavement cracking and wheel path rutting while also considering factors such as soil characteristics, material thickness, and the distribution of forces exerted by vehicles. The Ecoinvent® 3.6 database and SimaPro® software were employed to calculate emissions, and SICRO 3 information was used to estimate costs. Consequently, the study sought to identify the service that had the greatest impact on greenhouse gas emissions. The results were compared for design life periods of 10 and 30 years, considering structural performance and load-bearing capacity. Additionally, environmental impacts in terms of CO2 emissions per standard axle and construction costs in dollars per standard axle were analyzed. Based on the conducted analyses, it was possible to determine which pavement exhibited superior performance over time, considering technical, environmental, and economic criteria. One of the findings indicated that the mechanical characteristics of the soils used in the pavement layer directly influence the thickness of the pavement and the quantity of greenhouse gases, with a difference of approximately 7000 Kg CO2 Eq. The transportation service was identified as having the most significant negative impact. Other notable observations are that the study can contribute to future project guidelines and assist in decision-making regarding the selection of the most suitable pavement in terms of durability, load-bearing capacity, and sustainability.

Keywords: life cycle assessment, greenhouse gases, urban paving, service cost

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Authors: Roya Pournaghi

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Measuring the extent of daily use of the libraries study space is of utmost significance in order to develop, re-organize and maintain the efficiency of the study space. The current study aimed to employ GIS in analyzing the study halls space of the document center and central library of Tehran University and determine the extent of use of the study chairs and desks by the students-intended users. This combination of survey methods - descriptive design system. In order to collect the required data and a description of the method, To implement and entering data into ArcGIS software. It also analyzes the data and displays the results on the library floor map design method were used. And spatial database design and plan has been done at the Central Library of Tehran University through the amount of space used by members of the Library and Information halls plans. Results showed that Biruni's hall is allocated the highest occupancy rate to tables and chairs compared to other halls. In the Hall of Science and Technology, with an average occupancy rate of 0.39 in the tables represents the lowest users and Rashid al-Dins hall, and Science and Technology’s hall with an average occupancy rate (0.40) represents the lowest users of seats. In this study, the comparison of the space is occupied at different period as a study’s hall in the morning, evenings, afternoons, and several months was performed through GIS. This system analyzed the space relationship effectively and efficiently. The output of this study can be used by administrators and librarians to determine the exact amount of using the Equipment of study halls and librarians can use the output map to design more efficient space at the library.

Keywords: geospatial information system, spatial analysis, reading room, academic libraries, library’s user, central library of Tehran university

Procedia PDF Downloads 213

Authors: Xiao-Yan Li, Takashi Hashimoto, Guanhong Li, Shuo Yang

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In Japanese, onomatopoeia is an important element in the lively expression of feelings and experiences. It is very difficult for students of Japanese to acquire onomatopoeia, especially, its nuances. In this paper, based on traditional L2 learning theories, we propose a new method to improve the efficiency of teaching the nuances – both explicit and tacit - to non-native speakers of Japanese. The method for teaching the tacit nuances of onomatopoeia consists of three elements. First is to teach the formal rules representing the explicit nuances of onomatopoeic words. Second is to have the students create new onomatopoeic words by utilizing those formal rules. The last element is to provide feedback by evaluating the onomatopoeias created. Our previous study used five-grade relative estimation. However students were confused about the five-grade system, because they could not understand the evaluation criteria only based on a figure. In this new system, then, we built an evaluation database through native speakers’ narrative interpretation. We asked Japanese native speakers to describe their awareness of the nuances of onomatopoeia in writing. Then they voted on site and defined priorities for showing to learners on the system. To verify the effectiveness of the proposed method and the learning system, we conducted a preliminary experiment involving two groups of subjects. While Group A got feedback about the appropriateness of their onomatopoeic constructions from the native speakers’ narrative interpretation, Group B got feedback just in the form of the five-grade relative estimation. A questionnaire survey administered to all of the learners clarified our learning system availability and also identified areas that should be improved. Repetitive learning of word-formation rules, creating new onomatopoeias and gaining new awareness from narrative interpretation is the total process used to teach the explicit and tacit nuances of onomatopoeia.

Keywords: onomatopoeia, tacit nuance, narrative interpretation, e-learning system, second language teaching

Procedia PDF Downloads 381

Authors: Riaz A. Agha, Alexander J. Fowler, Seon-Young Lee, Buket Gundogan, Katharine Whitehurst, Harkiran K. Sagoo, Kyung Jin Lee Jeong, Douglas G. Altman, Dennis P. Orgill

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Introduction: Case Series are an important and common study type. Currently, no guideline exists for reporting case series and there is evidence of key data being missed from such reports. We propose to develop a reporting guideline for case series using a methodologically robust technique. The first step in this process is a systematic review of literature relevant to the reporting deficiencies of case series. Methods: A systematic review of methodological and reporting quality in surgical case series was performed. The electronic search strategy was developed by an information specialist and included MEDLINE, EMBASE, Cochrane Methods Register, Science Citation index and Conference Proceedings Citation index, from the start of indexing until 5th November 2014. Independent screening, eligibility assessments and data extraction was performed. Included articles were analyzed for five areas of deficiency: failure to use standardized definitions missing or selective data transparency or incomplete reporting whether alternate study designs were considered. Results: The database searching identified 2,205 records. Through the process of screening and eligibility assessments, 92 articles met inclusion criteria. Frequency of methodological and reporting issues identified was a failure to use standardized definitions (57%), missing or selective data (66%), transparency, or incomplete reporting (70%), whether alternate study designs were considered (11%) and other issues (52%). Conclusion: The methodological and reporting quality of surgical case series needs improvement. Our data shows that clear evidence-based guidelines for the conduct and reporting of a case series may be useful to those planning or conducting them.

Keywords: case series, reporting quality, surgery, systematic review

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Authors: Amalia Ardeljan, Lexi Frankel, Divesh Manjani, Gabriela Santizo, Maximillian Guerra, Omar Rashid

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Introduction: Cytomegalovirus (CMV) infection is a widespread infection affecting between 60-70% of people in industrialized countries. CMV has been previously correlated with a higher incidence of Hodgkin Lymphoma compared to noninfected persons. Research regarding prior CMV infection and subsequent lymphoma development is still controversial. With limited evidence, further research is needed in order to understand the relationship between previous CMV infection and subsequent lymphoma development. This study assessed the effect of CMV infection and the incidence of lymphoma afterward. Methods: A retrospective cohort study (2010-2019) was conducted through a Health Insurance Portability and Accountability Act (HIPAA) compliant national database and conducted using International Classification of Disease (ICD) 9th,10th codes, and Current Procedural Terminology (CPT) codes. These were used to identify lymphoma diagnosis in a previously CMV infected population. Patients were matched for age range and Charlson Comorbidity Index (CCI). A chi-squared test was used to assess statistical significance. Results: A total number of 14,303 patients was obtained in the CMV infected group as well as in the control population (matched by age range and CCI score). Subsequent lymphoma development was seen at a rate of 11.44% (1,637) in the CMV group and 5.74% (822) in the control group, respectively. The difference was statistically significant by p= 2.2x10-16, odds ratio = 2.696 (95% CI 2.483- 2.927). In an attempt to stratify the population by antiviral medication exposure, the outcomes were limited by the decreased number of members exposed to antiviral medication in the control population. Conclusion: This study shows a statistically significant correlation between prior CMV infection and an increased incidence of lymphoma afterward. Further exploration is needed to identify the potential carcinogenic mechanism of CMV and whether the results are attributed to a confounding bias.

Keywords: cytomegalovirus, lymphoma, cancer, microbiology

Procedia PDF Downloads 205