Search results for: regional vector

Authors: David F. Nettleton, Elodie Bugnicourt, Christian Wasiak, Alejandro Rosales

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In this presentation, preliminary results are given for the modeling and calibration of two different industrial winding MIMO (Multiple Input Multiple Output) processes using machine learning techniques. In contrast to previous approaches which have typically used ‘black-box’ linear statistical methods together with a definition of the mechanical behavior of the process, we use non-linear machine learning algorithms together with a ‘white-box’ rule induction technique to create a supervised model of the fitting error between the expected and real force measures. The final objective is to build a precise model of the winding process in order to control de-tension of the material being wound in the first case, and the friction of the material passing through the die, in the second case. Case 1, Tension Control of a Winding Process. A plastic web is unwound from a first reel, goes over a traction reel and is rewound on a third reel. The objectives are: (i) to train a model to predict the web tension and (ii) calibration to find the input values which result in a given tension. Case 2, Friction Force Control of a Micro-Pullwinding Process. A core+resin passes through a first die, then two winding units wind an outer layer around the core, and a final pass through a second die. The objectives are: (i) to train a model to predict the friction on die2; (ii) calibration to find the input values which result in a given friction on die2. Different machine learning approaches are tested to build models, Kernel Ridge Regression, Support Vector Regression (with a Radial Basis Function Kernel) and MPART (Rule Induction with continuous value as output). As a previous step, the MPART rule induction algorithm was used to build an explicative model of the error (the difference between expected and real friction on die2). The modeling of the error behavior using explicative rules is used to help improve the overall process model. Once the models are built, the inputs are calibrated by generating Gaussian random numbers for each input (taking into account its mean and standard deviation) and comparing the output to a target (desired) output until a closest fit is found. The results of empirical testing show that a high precision is obtained for the trained models and for the calibration process. The learning step is the slowest part of the process (max. 5 minutes for this data), but this can be done offline just once. The calibration step is much faster and in under one minute obtained a precision error of less than 1x10-3 for both outputs. To summarize, in the present work two processes have been modeled and calibrated. A fast processing time and high precision has been achieved, which can be further improved by using heuristics to guide the Gaussian calibration. Error behavior has been modeled to help improve the overall process understanding. This has relevance for the quick optimal set up of many different industrial processes which use a pull-winding type process to manufacture fibre reinforced plastic parts. Acknowledgements to the Openmind project which is funded by Horizon 2020 European Union funding for Research & Innovation, Grant Agreement number 680820

Keywords: data model, machine learning, industrial winding, calibration

Procedia PDF Downloads 241

Authors: Glauberto S. Quirino, Emanuelly V. Pereira, Amana S. Figueiredo, Antonia T. F. Santos, Paulo R. A. Firmino, Denise F. F. Barbosa, Caroline B. Q. Aquino, Eveliny S. Martins, Cinthia G. P. Calou, Ana K. B. Pinheiro

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Introduction: During pregnancy there are adjustments in the physical, emotional, existential and sexual areas, which may contribute to changes in sexual behavior. The objective was to analyze the sexual behavior of pregnant women. Methods: Quantitative, exploratory-descriptive study, approved by the Ethics and Research Committee of the Regional University of Cariri. For data collection, it was used the Sexuality Questionnaire in Gestation and Sexual Quotient - Female Version. It was carried out in public institutions in the urban and rural areas of three municipalities of the Metropolitan Region of Cariri, south of Ceará, Brazil from February to September 2016. The sampling was proportional stratified by convenience. A total of 815 pregnant women who were literate and aged 20 years or over were broached. 461 pregnant women were excluded because of high risk, adolescence, saturation of the extract, incomplete filling of the instrument, mental and physical handicap, without sexual partner, and the sample was 354 pregnant. The data were grouped, organized and analyzed in the statistical program R Studio (version 386 3.2.4). Descriptive frequency statistics and non-parametric tests were used to analyze the variables, and the results were shown in graphs and tables. Results: The women presented a minimum age of 20, maximum 35 and average of 26.9 years, predominantly urban area residents, with a monthly income of up to one minimum wage (US$ 275,00), high school, catholic, with fixed partner, heterosexuals, multiparous, multiple sexual partners throughout life and with the beginning of sexual life in adolescence (median age 17 years). There was a reduction in sexual practices (67%) and when they were performed, they were more frequent in the first trimester (79.7%) and less frequent in the third trimester (30.5%). Preliminary sexual practices did not change and were more frequent in the second trimester (46.6%). Throughout the gestational trimesters, the partner was referred as the main responsible for the sexual initiative. The women performed vaginal sex (97.7%) and provided greater pleasure (42.8%) compared to non-penetrative sex (53.9%) (oral sex and masturbation). There was also a reduction in the sexual disposition of pregnant women (90.7%) and partner (72.9%), mainly in the first trimester (78.8%), and sexual positions. Sexual performance ranged from regular to good (49.7%). Level of schooling, marital status, sexual orientation of the pregnant woman and the partner, sexual practices and positions, preliminaries, frequency of sexual practices and importance attributed to them were variables that influenced negatively sexual performance and satisfaction. It is concluded that pregnancy negatively changes the sexual behavior of the women and it is suggested to further investigations and approach of the partner, in order to clarify the influence of these variables on the sexual function and subsidize intervention strategies, with a view to the integrality of sexual and reproductive health.

Keywords: obstetric nursing, pregnant women, sexual behavior, women's health

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Authors: Aliaksandr Volchak, Мaryna Barushka

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The territory of Belarus is studied quite well in terms of hydrology but runoff fluctuations over time require more detailed research in order to forecast changes in rivers runoff in future. Generally, river runoff is shaped by natural climatic factors, but man-induced impact has become so big lately that it can be compared to natural processes in forming runoffs. In Belarus, a heavy man load on the environment was caused by large-scale land reclamation in the 1960s. Lands of southern Belarus were reclaimed most, which contributed to changes in runoff. Besides, global warming influences runoff. Today we observe increase in air temperature, decrease in precipitation, changes in wind velocity and direction. These result from cyclic climate fluctuations and, to some extent, the growth of concentration of greenhouse gases in the air. Climate change affects Belarus’s water resources in different ways: in hydropower industry, other water-consuming industries, water transportation, agriculture, risks of floods. In this research we have done an assessment of river runoff according to the scenarios of climate change and global climate forecast presented in the 4th and 5th Assessment Reports conducted by Intergovernmental Panel on Climate Change (IPCC) and later specified and adjusted by experts from Vilnius Gediminas Technical University with the use of a regional climatic model. In order to forecast changes in climate and runoff, we analyzed their changes from 1962 up to now. This period is divided into two: from 1986 up to now in comparison with the changes observed from 1961 to 1985. Such a division is a common world-wide practice. The assessment has revealed that, on the average, changes in runoff are insignificant all over the country, even with its irrelevant increase by 0.5 – 4.0% in the catchments of the Western Dvina River and north-eastern part of the Dnieper River. However, changes in runoff have become more irregular both in terms of the catchment area and inter-annual distribution over seasons and river lengths. Rivers in southern Belarus (the Pripyat, the Western Bug, the Dnieper, the Neman) experience reduction of runoff all year round, except for winter, when their runoff increases. The Western Bug catchment is an exception because its runoff reduces all year round. Significant changes are observed in spring. Runoff of spring floods reduces but the flood comes much earlier. There are different trends in runoff changes in spring, summer, and autumn. Particularly in summer, we observe runoff reduction in the south and west of Belarus, with its growth in the north and north-east. Our forecast of runoff up to 2035 confirms the trend revealed in 1961 – 2015. According to it, in the future, there will be a strong difference between northern and southern Belarus, between small and big rivers. Although we predict irrelevant changes in runoff, it is quite possible that they will be uneven in terms of seasons or particular months. Especially, runoff can change in summer, but decrease in the rest seasons in the south of Belarus, whereas in the northern part the runoff is predicted to change insignificantly.

Keywords: assessment, climate fluctuation, forecast, river runoff

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Authors: Xingyu Gao, Qiang Wu

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Patents play a crucial role in protecting innovation and intellectual property. Early prediction of the impact of artificial intelligence (AI) patents helps researchers and companies allocate resources and make better decisions. Understanding the key factors that influence patent impact can assist researchers in gaining a better understanding of the evolution of AI technology and innovation trends. Therefore, identifying highly impactful patents early and providing support for them holds immeasurable value in accelerating technological progress, reducing research and development costs, and mitigating market positioning risks. Despite the extensive research on AI patents, accurately predicting their early impact remains a challenge. Traditional methods often consider only single factors or simple combinations, failing to comprehensively and accurately reflect the actual impact of patents. This paper utilized the artificial intelligence patent database from the United States Patent and Trademark Office and the Len.org patent retrieval platform to obtain specific information on 35,708 AI patents. Using six machine learning models, namely Multiple Linear Regression, Random Forest Regression, XGBoost Regression, LightGBM Regression, Support Vector Machine Regression, and K-Nearest Neighbors Regression, and using early indicators of patents as features, the paper comprehensively predicted the impact of patents from three aspects: technical, social, and economic. These aspects include the technical leadership of patents, the number of citations they receive, and their shared value. The SHAP (Shapley Additive exPlanations) metric was used to explain the predictions of the best model, quantifying the contribution of each feature to the model's predictions. The experimental results on the AI patent dataset indicate that, for all three target variables, LightGBM regression shows the best predictive performance. Specifically, patent novelty has the greatest impact on predicting the technical impact of patents and has a positive effect. Additionally, the number of owners, the number of backward citations, and the number of independent claims are all crucial and have a positive influence on predicting technical impact. In predicting the social impact of patents, the number of applicants is considered the most critical input variable, but it has a negative impact on social impact. At the same time, the number of independent claims, the number of owners, and the number of backward citations are also important predictive factors, and they have a positive effect on social impact. For predicting the economic impact of patents, the number of independent claims is considered the most important factor and has a positive impact on economic impact. The number of owners, the number of sibling countries or regions, and the size of the extended patent family also have a positive influence on economic impact. The study primarily relies on data from the United States Patent and Trademark Office for artificial intelligence patents. Future research could consider more comprehensive data sources, including artificial intelligence patent data, from a global perspective. While the study takes into account various factors, there may still be other important features not considered. In the future, factors such as patent implementation and market applications may be considered as they could have an impact on the influence of patents.

Keywords: patent influence, interpretable machine learning, predictive models, SHAP

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Authors: J. D. Temperman

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Introduction: In particular, in relation to religion, the meaning and scope of freedom of expression have been tested in recent times. This paper investigates the legal justifications for restrictions that have been suggested in this area and asks whether they are sustainable from an international human rights perspective. The universal human rights instruments, particularly the UN International Covenant on Civil and Political Rights (ICCPR), are increasingly geared towards eradicating ‘incitement’ to contingent harms like violence or discrimination, whilst forms of extreme speech that fall short of such incitement are to be protected rather than countered by states. Human Rights Committee’s draft-General Comment on freedom of expression, adopted in 2011, provides another strong indication that this is the envisaged way forward: repealing anti-blasphemy and anti-religious defamation laws, whilst simultaneously increasing efforts to combat ‘incitement’. Within regional human rights frameworks, notably the European Convention system, judgments have in fact supported legal restrictions on both hate speech, holocaust denial, and blasphemy or religious defamation. Major contributions to scholarship: This paper proposes an actus reus for the offense of ‘advocacy of religious hatred that constitutes incitement to discrimination or violence’, as enshrined in Article 20(2) of the UN ICCPR. In underscoring the high threshold of ‘incitement’, the author distinguishes this offense from such notions as ‘blasphemy’ or ‘defamation of religions’. In addition to treating the said provision as a sui generis prohibition, the question is addresses whether a ‘right to be protected against incitement’ may be distilled from the ICCPR. Furthermore, the author will discuss the question of how to judge incitement; notably, is mens rea required to convict someone of incitement, and if so, what degree of mens rea? This analysis also includes the question how to balance content and context factors when addressing alleged instances of incitement, notably what factors make provide for a likelihood that imminent acts of violence or discrimination will ensue from an inciteful speech act? Methodology: This paper takes a double comparative approach: (i) it endeavours to compare and contrast monitoring bodies’ approach to incitement (notably, the UN Human Rights Committee, but also the UN Committee on the Elimination of Racial Discrimination which monitors states’ compliance with Article 4 of ICERD on incitement); and (ii) it endeavours to chart and compare and analyse from an international human rights perspective recent forms of state practice in the field of dealing with incitement (i.e. a comparative legal analysis and vertical human rights analysis of newly emerging incitement legislation in the light of the said international standards). Conclusion: This paper conceptualizes a legal notion – ‘incitement’ – encapsulated in international human rights law that may have a profound bearing on contemporary challenges of radicalization and religious strife.

Keywords: incitement, international human rights law, religious hatred, violence

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Authors: Suzanne Zazycki, Bamidele Osamika, Heather Craska, Kaelyn Conaway, Reena Murphy, Stephanie Spence

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Invasive Plant Species (IPS) are an important component of effective preservation and conservation of natural lands management. IPS are non-native plants which can aggressively encroach upon native species and pose a significant threat to the ecology, public health, and social welfare of a community. The presence of IPS in U.S. nature preserves has caused economic costs, which has estimated to exceed $26 billion a year. While different methods have been identified to control IPS, few methods have been recognized for early detection of IPS. This study examined identified methods for early detection of IPS in Hueston Woods State Nature Preserve. Mixed methods research design was adopted in this four-phased study. The first phase entailed data gathering, the phase described the characteristics and qualities of IPS and the importance of early detection (ED). The second phase explored ED methods, Geographic Information Systems (GIS) and Citizen Science were discovered as ED methods for IPS. The third phase of the study involved the creation of hotspot maps to identify likely areas for IPS growth. While the fourth phase involved testing and evaluating mobile applications that can support the efforts of citizen scientists in IPS detection. Literature reviews were conducted on IPS and ED methods, and four regional experts from ODNR and Miami University were interviewed. A questionnaire was used to gather information about ED methods used across the state. The findings revealed that geospatial methods, including Unmanned Aerial Vehicles (UAVs), Multispectral Satellites (MSS), and Normalized Difference Vegetation Index (NDVI), are not feasible for early detection of IPS, as they require GIS expertise, are still an emerging technology, and are not suitable for every habitat for the ED of IPS. Therefore, Other ED methods options were explored, which include predicting areas where IPS will grow, which can be done through monitoring areas that are like the species’ native habitat. Through literature review and interviews, IPS are known to grow in frequently disturbed areas such as along trails, shorelines, and streambanks. The research team called these areas “hotspots” and created maps of these hotspots specifically for HW NP to support and narrow the efforts of citizen scientists and staff in the ED of IPS. The results further showed that utilizing citizen scientists in the ED of IPS is feasible, especially through single day events or passive monitoring challenges. The study concluded that the creation of hotspot maps to direct the efforts of citizen scientists are effective for the early detection of IPS. Several recommendations were made, among which is the creation of hotspot maps to narrow the ED efforts as citizen scientists continues to work in the preserves and utilize citizen science volunteers to identify and record emerging IPS.

Keywords: early detection, hueston woods state nature preserve, invasive plant species, hotspots

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Authors: Jayden R. Hunter, Alexander J. MacQuarrie, Samantha C. Sheridan, Richard High, Carolyn Waite

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Workplace exercise programs have been recommended to improve the musculoskeletal fitness of paramedics with the aim of reducing injury rates, and while they have shown efficacy in other occupations, they have not been delivered and evaluated in Australian paramedics to our best knowledge. This study investigated the effectiveness of a 6-month workplace exercise program (MedicFit; MF) to improve paramedic fitness with or without health coach (HC) support. A group of regional Australian paramedics (n=76; 43 male; mean ± SD 36.5 ± 9.1 years; BMI 28.0 ± 5.4 kg/m²) were randomised at the station level to either exercise with remote health coach support (MFHC; n=30), exercise without health coach support (MF; n=23), or no-exercise control (CON; n=23) groups. MFHC and MF participants received a 6-month, low-moderate intensity resistance and flexibility exercise program to be performed ƒ on station without direct supervision. Available exercise equipment included dumbbells, resistance bands, Swiss balls, medicine balls, kettlebells, BOSU balls, yoga mats, and foam rollers. MFHC and MF participants were also provided with a comprehensive exercise manual including sample exercise sessions aimed at improving musculoskeletal strength and flexibility which included exercise prescription (i.e. sets, reps, duration, load). Changes to upper-body (push-ups), lower-body (wall squat) and core (plank hold) strength and flexibility (back scratch and sit-reach tests) after the 6-month intervention were analysed using repeated measures ANOVA to compare changes between groups and over time. Upper-body (+20.6%; p < 0.01; partial eta squared = 0.34 [large effect]) and lower-body (+40.8%; p < 0.05; partial eta squared = 0.08 (moderate effect)) strength increased significantly with no interaction or group effects. Changes to core strength (+1.4%; p=0.17) and both upper-body (+19.5%; p=0.56) and lower-body (+3.3%; p=0.15) flexibility were non-significant with no interaction or group effects observed. While upper- and lower-body strength improved over the course of the intervention, providing a 6-month workplace exercise program with or without health coach support did not confer any greater strength or flexibility benefits than exercise testing alone (CON). Although exercise adherence was not measured, it is possible that participants require additional methods of support such as face-to-face exercise instruction and guidance and individually-tailored exercise programs to achieve adequate participation and improvements in musculoskeletal fitness. This presents challenges for more remote paramedic stations without regular face-to-face access to suitably qualified exercise professionals, and future research should investigate the effectiveness of other forms of exercise delivery and guidance for these paramedic officers such as remotely-facilitated digital exercise prescription and monitoring.

Keywords: workplace exercise, paramedic health, strength training, flexibility training

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Authors: Caixia Gao, Chuanrong Li, Lingli Tang, Lingling Ma, Yonggang Qian, Ning Wang

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Knowledge of land surface temperature (LST) is of crucial important in energy balance studies and environment modeling. Satellite thermal infrared (TIR) imagery is the primary source for retrieving LST at the regional and global scales. Due to the combination of atmosphere and land surface of received radiance by TIR sensors, atmospheric effect correction has to be performed to remove the atmospheric transmittance and upwelling radiance. Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG) provides measurements every 15 minutes in 12 spectral channels covering from visible to infrared spectrum at fixed view angles with 3km pixel size at nadir, offering new and unique capabilities for LST, LSE measurements. However, due to its high temporal resolution, the atmosphere correction could not be performed with radiosonde profiles or reanalysis data since these profiles are not available at all SEVIRI TIR image acquisition times. To solve this problem, a two-part six-parameter semi-empirical diurnal temperature cycle (DTC) model has been applied to the temporal interpolation of ECMWF reanalysis data. Due to the fact that the DTC model is underdetermined with ECMWF data at four synoptic times (UTC times: 00:00, 06:00, 12:00, 18:00) in one day for each location, some approaches are adopted in this study. It is well known that the atmospheric transmittance and upwelling radiance has a relationship with water vapour content (WVC). With the aid of simulated data, the relationship could be determined under each viewing zenith angle for each SEVIRI TIR channel. Thus, the atmospheric transmittance and upwelling radiance are preliminary removed with the aid of instantaneous WVC, which is retrieved from the brightness temperature in the SEVIRI channels 5, 9 and 10, and a group of the brightness temperatures for surface leaving radiance (Tg) are acquired. Subsequently, a group of the six parameters of the DTC model is fitted with these Tg by a Levenberg-Marquardt least squares algorithm (denoted as DTC model 1). Although the retrieval error of WVC and the approximate relationships between WVC and atmospheric parameters would induce some uncertainties, this would not significantly affect the determination of the three parameters, td, ts and β (β is the angular frequency, td is the time where the Tg reaches its maximum, ts is the starting time of attenuation) in DTC model. Furthermore, due to the large fluctuation in temperature and the inaccuracy of the DTC model around sunrise, SEVIRI measurements from two hours before sunrise to two hours after sunrise are excluded. With the knowledge of td , ts, and β, a new DTC model (denoted as DTC model 2) is accurately fitted again with these Tg at UTC times: 05:57, 11:57, 17:57 and 23:57, which is atmospherically corrected with ECMWF data. And then a new group of the six parameters of the DTC model is generated and subsequently, the Tg at any given times are acquired. Finally, this method is applied to SEVIRI data in channel 9 successfully. The result shows that the proposed method could be performed reasonably without assumption and the Tg derived with the improved method is much more consistent with that from radiosonde measurements.

Keywords: atmosphere correction, diurnal temperature cycle model, land surface temperature, SEVIRI

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Authors: A. F. Jaber, E. Dean, M. Liu, J. He, D. Sabata, J. Radel

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Background: Stroke is a serious health care concern and a major cause of disability in the United States. This condition impacts the individual’s functional ability to perform daily activities. Predicting functional performance of people with stroke assists health care professionals in optimizing the delivery of health services to the affected individuals. The purpose of this study was to identify significant predictors of Motor FIM and of Cognitive FIM subscores among individuals with stroke after discharge from inpatient rehabilitation (typically 4-6 weeks after stroke onset). A second purpose is to explore the relation among personal characteristics, health status, and functional performance of daily activities within 2 weeks of stroke onset. Methods: This study used a retrospective chart review to conduct a secondary analysis of data obtained from the Healthcare Enterprise Repository for Ontological Narration (HERON) database. The HERON database integrates de-identified clinical data from seven different regional sources including hospital electronic medical record systems of the University of Kansas Health System. The initial HERON data extract encompassed 1192 records and the final sample consisted of 207 participants who were mostly white (74%) males (55%) with a diagnosis of ischemic stroke (77%). The outcome measures collected from HERON included performance scores on the National Institute of Health Stroke Scale (NIHSS), the Glasgow Coma Scale (GCS), and the Functional Independence Measure (FIM). The data analysis plan included descriptive statistics, Pearson correlation analysis, and Stepwise regression analysis. Results: significant predictors of discharge Motor FIM subscores included age, baseline Motor FIM subscores, discharge NIHSS scores, and comorbid electrolyte disorder (R2 = 0.57, p <0.026). Significant predictors of discharge Cognitive FIM subscores were age, baseline cognitive FIM subscores, client cooperative behavior, comorbid obesity, and the total number of comorbidities (R2 = 0.67, p <0.020). Functional performance on admission was significantly associated with age (p < 0.01), stroke severity (p < 0.01), and length of hospital stay (p < 0.05). Conclusions: our findings show that younger age, good motor and cognitive abilities on admission, mild stroke severity, fewer comorbidities, and positive client attitude all predict favorable functional outcomes after inpatient stroke rehabilitation. This study provides health care professionals with evidence to evaluate predictors of favorable functional outcomes early at stroke rehabilitation, to tailor individualized interventions based on their client’s anticipated prognosis, and to educate clients about the benefits of making lifestyle changes to improve their anticipated rate of functional recovery.

Keywords: functional performance, predictors, stroke, recovery

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations of previous approaches, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with attention mechanism. In a previous work on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: transformers, generative ai, gene expression design, classification

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Authors: Karolina Wieczorek, Zofia Przypaśniak

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Climate change is a rapidly growing threat to global health, and part of the responsibility to combat it lies within the healthcare sector itself, including adequate education of future medical professionals. To mitigate the consequences, the General Medical Council (GMC) has equipped medical schools with a list of outcomes regarding sustainability teaching. Students are expected to analyze the impact of the healthcare sector’s emissions on climate change. The delivery of the related teaching content is, however, often inadequate and insufficient time is devoted for exploration of the topics. Teaching curricula lack in-depth exploration of the learning objectives. This study aims to assess the extent and characteristics of climate change and sustainability subjects teaching in the curriculum of a chosen UK medical school (Barts and The London School of Medicine and Dentistry). It compares the data to the national average scores from the Climate Change and Sustainability Teaching (C.A.S.T.) in Medical Education Audit to draw conclusions about teaching on a regional level. This is a single-center audit of the timetabled sessions of teaching in the medical course. The study looked at the academic year 2020/2021 which included a review of all non-elective, core curriculum teaching materials including tutorials, lectures, written resources, and assignments in all five years of the undergraduate and graduate degrees, focusing only on mandatory teaching attended by all students (excluding elective modules). The topics covered were crosschecked with GMC Outcomes for graduates: “Educating for Sustainable Healthcare – Priority Learning Outcomes” as gold standard to look for coverage of the outcomes and gaps in teaching. Quantitative data was collected in form of time allocated for teaching as proxy of time spent per individual outcomes. The data was collected independently by two students (KW and ZP) who have received prior training and assessed two separate data sets to increase interrater reliability. In terms of coverage of learning outcomes, 12 out of 13 were taught (with the national average being 9.7). The school ranked sixth in the UK for time spent per topic and second in terms of overall coverage, meaning the school has a broad range of topics taught with some being explored in more detail than others. For the first outcome 4 out of 4 objectives covered (average 3.5) with 47 minutes spent per outcome (average 84 min), for the second objective 5 out of 5 covered (average 3.5) with 46 minutes spent (average 20), for the third 3 out of 4 (average 2.5) with 10 mins pent (average 19 min). A disproportionately large amount of time is spent delivering teaching regarding air pollution (respiratory illnesses), which resulted in the topic of sustainability in other specialties being excluded from teaching (musculoskeletal, ophthalmology, pediatrics, renal). Conclusions: Currently, there is no coherent strategy on national teaching of climate change topics and as a result an unstandardized amount of time spent on teaching and coverage of objectives can be observed.

Keywords: audit, climate change, sustainability, education

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Authors: Federica Marangio

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This study looks at the triangle of knowledge: research-education-innovation as growth engine of an inclusive and sustainable society, where the research is the strategic process which allows the acquisition of knowledge, innovation appraises the knowledge acquired and the education is the enabling factor of the human capital to create entrepreneurial capital. Where does Italy and China stand in the global geography of innovation? Europe is calling on a smart, inclusive and sustainable growth through a specializing process that looks at the social and economic challenges, able to understand the characteristics of specific geographic areas. It is easily questionable why it is not as simple as it looks to come up with entrepreneurial ideas in all the geographic areas. Seen that the technology plus the human capital should be the means through which is possible to innovate and contribute to the boost of innovation culture, then the young educated people can be seen as the society changing agents and it becomes clear the importance of investigating the skills and competencies that lead to innovation. By starting innovation-based activities, other countries on an international level, are able now to be part of an healthy innovative ecosystem which is the result of a strong growth policy which enables innovation. Analyzing the geography of the innovation on a global scale, comes to light that the innovative entrepreneurship is the process which portrays the competitiveness of the regions in the knowledge-based economy as strategic process able to match intellectual capital and market opportunities. The level of innovative entrepreneurship is not only the result of the endogenous growth ability of the enterprises, but also by significant relations with other enterprises, universities, other centers of education and institutions. To obtain more innovative entrepreneurship is necessary to stimulate more synergy between all these territory actors in order to create, access and value existing and new knowledge ready to be disseminate. This study focuses on individual’s lived experience and the researcher believed that she can’t understand the human actions without understanding the meaning that they attribute to their thoughts, feelings, beliefs and so given she needed to understand the deeper perspectives captured through face-to face interaction. A case study approach will contribute to the betterment of knowledge in this field. This case study will represent a picture of the innovative ecosystem and the entrepreneurial mindset as a key ingredient of endogenous growth and a must for sustainable local and regional development and social cohesion. The case study will be realized analyzing two Chinese companies. A structured set of questions will be asked in order to gain details on what generated success or failure in the different situations with the past and at the moment of the research. Everything will be recorded not to lose important information during the transcription phase. While this work is not geared toward testing a priori hypotheses, it is nevertheless useful to examine whether the projects undertaken by the companies, were stimulated by enabling factors that, as result, enhanced or hampered the local innovation culture.

Keywords: Entrepreneurship, education, geography of innovation, education.

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Authors: Olatokunbo Yakeem

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Human trafficking is a crime against gross violations of human rights. Trafficking in persons is a severe socio-economic dilemma that affects the national and international dimensions. Human trafficking or modern-day-slavery emanated from slavery, and it has been in existence before the 6ᵗʰ century. Today, no country is exempted from dehumanizing human beings, and as a result, it has been an international issue. The United Nations (UN) presented the International Protocol to fight human trafficking worldwide, which brought about the international definition of human trafficking. The protocol is to prevent, suppress, and punish trafficking in persons, especially women and children. The trafficking protocol has a link with transnational organised crime rather than migration. Over a hundred and fifty countries nationwide have enacted their criminal and panel code trafficking legislation from the UN trafficking protocol. Sex trafficking is the most common type of exploitation of women and children. Other forms of this crime involve exploiting vulnerable victims through forced labour, child involvement in warfare, domestic servitude, debt bondage, and organ removal for transplantation. Trafficking of women and children into sexual exploitation represents the highest form of human trafficking than other types of exploitation. Trafficking of women and children can either happen internally or across the border. It affects all kinds of people, regardless of their race, social class, culture, religion, and education levels. However, it is more of a gender-based issue against females. Furthermore, human trafficking can lead to life-threatening infections, mental disorders, lifetime trauma, and even the victim's death. The study's significance is to explore why the root causes of women and children trafficking in Nigeria are based around poverty, entrusting children in the hands of relatives and friends, corruption, globalization, weak legislation, and ignorance. The importance of this study is to establish how the national, regional, and international organisations are using the 3P’s Protection, Prevention, and Prosecution) to tackle human trafficking. The methodology approach for this study will be a qualitative paradigm. The rationale behind this selection is that the qualitative method will identify the phenomenon and interpret the findings comprehensively. The data collection will take the form of semi-structured in-depth interviews through telephone and email. The researcher will use a descriptive thematic analysis to analyse the data by using complete coding. In summary, this study aims to recommend to the Nigerian federal government to include human trafficking as a subject in their educational curriculum for early intervention to prevent children from been coerced by criminal gangs. And the research aims to find the root causes of women and children trafficking. Also, to look into the effectiveness of the strategies in place to eradicate human trafficking globally. In the same vein, the research objective is to investigate how the anti-trafficking bodies such as law enforcement and NGOs collaborate to tackle the upsurge in human trafficking.

Keywords: children, Nigeria, trafficking, women

Procedia PDF Downloads 183

Authors: Pinzhe Zhao

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This study focuses on predicting university students' cheating tendencies using psychological traits and machine learning techniques. Academic dishonesty is a significant issue that compromises the integrity and fairness of educational institutions. While much research has been dedicated to detecting cheating behaviors after they have occurred, there is limited work on predicting such tendencies before they manifest. The aim of this research is to develop a model that can identify students who are at higher risk of engaging in academic misconduct, allowing for earlier interventions to prevent such behavior. Psychological factors are known to influence students' likelihood of cheating. Research shows that traits such as test anxiety, moral reasoning, self-efficacy, and achievement motivation are strongly linked to academic dishonesty. High levels of anxiety may lead students to cheat as a way to cope with pressure. Those with lower self-efficacy are less confident in their academic abilities, which can push them toward dishonest behaviors to secure better outcomes. Students with weaker moral judgment may also justify cheating more easily, believing it to be less wrong under certain conditions. Achievement motivation also plays a role, as students driven primarily by external rewards, such as grades, are more likely to cheat compared to those motivated by intrinsic learning goals. In this study, data on students’ psychological traits is collected through validated assessments, including scales for anxiety, moral reasoning, self-efficacy, and motivation. Additional data on academic performance, attendance, and engagement in class are also gathered to create a more comprehensive profile. Using machine learning algorithms such as Random Forest, Support Vector Machines (SVM), and Long Short-Term Memory (LSTM) networks, the research builds models that can predict students’ cheating tendencies. These models are trained and evaluated using metrics like accuracy, precision, recall, and F1 scores to ensure they provide reliable predictions. The findings demonstrate that combining psychological traits with machine learning provides a powerful method for identifying students at risk of cheating. This approach allows for early detection and intervention, enabling educational institutions to take proactive steps in promoting academic integrity. The predictive model can be used to inform targeted interventions, such as counseling for students with high test anxiety or workshops aimed at strengthening moral reasoning. By addressing the underlying factors that contribute to cheating behavior, educational institutions can reduce the occurrence of academic dishonesty and foster a culture of integrity. In conclusion, this research contributes to the growing body of literature on predictive analytics in education. It offers a approach by integrating psychological assessments with machine learning to predict cheating tendencies. This method has the potential to significantly improve how academic institutions address academic dishonesty, shifting the focus from punishment after the fact to prevention before it occurs. By identifying high-risk students and providing them with the necessary support, educators can help maintain the fairness and integrity of the academic environment.

Keywords: academic dishonesty, cheating prediction, intervention strategies, machine learning, psychological traits, academic integrity

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Authors: Mingqian Zhang

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Tip-enhanced Raman spectroscopy (TERS) is a scanning probe technique for individual objects and structured surfaces investigation that provides a wealth of enhanced spectral information with nanoscale spatial resolution and high detection sensitivity. It has become a powerful and promising chemical and physical information detection method in the nanometer scale. The TERS technique uses a sharp metallic tip regulated in the near-field of a sample surface, which is illuminated with a certain incident beam meeting the excitation conditions of the wave-vector matching. The local electric field, and, consequently, the Raman scattering, from the sample in the vicinity of the tip apex are both greatly tip-enhanced owning to the excitation of localized surface plasmons and the lightning-rod effect. Typically, a TERS setup is composed of a scanning probe microscope, excitation and collection optical configurations, and a Raman spectroscope. In the illumination configuration, an objective lens or a parabolic mirror is always used as the most important component, in order to focus the incident beam on the tip apex for excitation. In this research, a novel TERS setup was built up by introducing a plasmonic lens to the excitation optics as a focusing device. A plasmonic lens with symmetry breaking semi-annular slits corrugated on gold film was designed for the purpose of generating concentrated sub-wavelength light spots with strong longitudinal electric field. Compared to conventional far-field optical components, the designed plasmonic lens not only focuses an incident beam to a sub-wavelength light spot, but also realizes a strong z-component that dominants the electric field illumination, which is ideal for the excitation of tip-enhancement. Therefore, using a PL in the illumination configuration of TERS contributes to improve the detection sensitivity by both reducing the far-field background and effectively exciting the localized electric field enhancement. The FDTD method was employed to investigate the optical near-field distribution resulting from the light-nanostructure interaction. And the optical field distribution was characterized using an scattering-type scanning near-field optical microscope to demonstrate the focusing performance of the lens. The experimental result is in agreement with the theoretically calculated one. It verifies the focusing performance of the plasmonic lens. The optical field distribution shows a bright elliptic spot in the lens center and several arc-like side-lobes on both sides. After the focusing performance was experimentally verified, the designed plasmonic lens was used as a focusing component in the excitation configuration of TERS setup to concentrate incident energy and generate a longitudinal optical field. A collimated linearly polarized laser beam, with along x-axis polarization, was incident from the bottom glass side on the plasmonic lens. The incident light focused by the plasmonic lens interacted with the silver-coated tip apex and enhanced the Raman signal of the sample locally. The scattered Raman signal was gathered by a parabolic mirror and detected with a Raman spectroscopy. Then, the plasmonic lens based setup was employed to investigate carbon nanotubes and TERS experiment was performed. Experimental results indicate that the Raman signal is considerably enhanced which proves that the novel TERS configuration is feasible and promising.

Keywords: longitudinal electric field, plasmonics, raman spectroscopy, tip-enhancement

Procedia PDF Downloads 373

Authors: Geanderson Eduardo Ambrósio, Dênis Antônio Da Cunha, Marcel Viana Pires

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Historically, human development has been based on economic gains associated with intensive energy activities, which often are exhaustive in the emission of Greenhouse Gases (GHGs). It requires the establishment of targets for mitigation of GHGs in order to disassociate the human development from emissions and prevent further climate change. Brazil presents itself as one of the most GHGs emitters and it is of critical importance to discuss such reductions in intra-national framework with the objective of distributional equity to explore its full mitigation potential without compromising the development of less developed societies. This research displays some incipient considerations about which Brazil’s micro-regions should reduce, when the reductions should be initiated and what its magnitude should be. We started with the methodological assumption that human development and GHGs emissions arise in the future as their behavior was observed in the past. Furthermore, we assume that once a micro-region became developed, it is able to maintain gains in human development without the need of keep growing GHGs emissions rates. The human development index and the carbon dioxide equivalent emissions (CO2e) were extrapolated to the year 2050, which allowed us to calculate when the micro-regions will become developed and the mass of GHG’s emitted. The results indicate that Brazil must throw 300 GT CO2e in the atmosphere between 2011 and 2050, of which only 50 GT will be issued by micro-regions before it’s develop and 250 GT will be released after development. We also determined national mitigation targets and structured reduction schemes where only the developed micro-regions would be required to reduce. The micro-region of São Paulo, the most developed of the country, should be also the one that reduces emissions at most, emitting, in 2050, 90% less than the value observed in 2010. On the other hand, less developed micro-regions will be responsible for less impactful reductions, i.e. Vale do Ipanema will issue in 2050 only 10% below the value observed in 2010. Such methodological assumption would lead the country to issue, in 2050, 56.5% lower than that observed in 2010, so that the cumulative emissions between 2011 and 2050 would reduce by 130 GT CO2e over the initial projection. The fact of associating the magnitude of the reductions to the level of human development of the micro-regions encourages the adoption of policies that favor both variables as the governmental planner will have to deal with both the increasing demand for higher standards of living and with the increasing magnitude of reducing emissions. However, if economic agents do not act proactively in local and national level, the country is closer to the scenario in which emits more than the one in which mitigates emissions. The research highlighted the importance of considering the heterogeneity in determining individual mitigation targets and also ratified the theoretical and methodological feasibility to allocate larger share of contribution for those who historically emitted more. It is understood that the proposals and discussions presented should be considered in mitigation policy formulation in Brazil regardless of the adopted reduction target.

Keywords: greenhouse gases, human development, mitigation, intensive energy activities

Procedia PDF Downloads 318

Authors: M. G. Shilina

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The interstate economic interaction phenomenon is complex. ‘Economic integration’, as one of its types, can be explored through the prism of international law, the theories of the world economy, politics and international relations. The most objective study of the phenomenon requires a comprehensive multifactoral approach. In new geopolitical realities, the problems of coexistence and possible interconnection of various mechanisms of interstate economic interaction are actively discussed. Currently, the Eurasian continent states support the direction to economic integration. At the same time, the existing international economic law fragmentation in Eurasia is seen as the important problem. The Eurasian space is characterized by a various types of interstate relations: international agreements (multilateral and bilateral), and a large number of cooperation formats (from discussion platforms to organizations aimed at deep integration). For their harmonization, it is necessary to have a clear vision to the phased international economic relations regulation options. In the conditions of rapid development of international economic relations, the modeling (including prognostic) can be optimally used as the main scientific method for presenting the phenomenon. On the basis of this method, it is possible to form the current situation vision and the best options for further action. In order to determine the most objective version of the integration development, the combination of several approaches were used. The normative legal approach- the descriptive method of legal modeling- was taken as the basis for the analysis. A set of legal methods was supplemented by the international relations science prognostic methods. The key elements of the model are the international economic organizations and states' associations existing in the Eurasian space (the Eurasian Economic Union (EAEU), the European Union (EU), the Shanghai Cooperation Organization (SCO), Chinese project ‘One belt-one road’ (OBOR), the Commonwealth of Independent States (CIS), BRICS, etc.). A general term for the elements of the model is proposed - the interstate interaction mechanisms (IIM). The aim of building a model of current and future Eurasian economic integration is to show optimal options for joint economic development of the states and IIMs. The long-term goal of this development is the new economic and political space, so-called the ‘Great Eurasian Community’. The process of achievement this long-term goal consists of successive steps. Modeling the integration architecture and dividing the interaction into stages led us to the following conclusion: the SCO is able to transform Eurasia into a single economic space. Gradual implementation of the complex phased model, in which the SCO+ plays a key role, will allow building an effective economic integration for all its participants, to create an economically strong community. The model can have practical value for politicians, lawyers, economists and other participants involved in the economic integration process. A clear, systematic structure can serve as a basis for further governmental action.

Keywords: economic integration, The Eurasian Economic Union, The European Union, The Shanghai Cooperation Organization, The Silk Road Economic Belt

Procedia PDF Downloads 149

Authors: Kuo-Kai Lin, Po-Lun Chang

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Background: The Emergency Care Research Institute released a list for the top 10 medical technology hazards in 2017, with the following hazard topping the list: ‘infusion errors can be deadly if simple safety steps are overlooked.’ In addition, hospitals use various assessment items to evaluate the safety of their medical equipment, confirming the importance of medical equipment safety. In recent years, the topic of patient safety has garnered increasing attention. Accordingly, various agencies have established patient safety-related committees to coordinate, collect, and analyze information regarding abnormal events associated with medical practice. Activities to promote and improve employee training have been introduced to diminish the recurrence of medical malpractice. Objective: To allow nursing personnel to acquire the skills needed to operate common medical equipment and update and review such skills whenever necessary to elevate medical care quality and reduce patient injuries caused by medical equipment operation errors. Method: In this study, a quasi-experimental design was adopted and nurses from a regional teaching hospital were selected as the study sample. Online videos instructing the operation method of common medical equipment were made and quick response codes were designed for the nursing personnel to quickly access the videos when necessary. Senior nursing supervisors and equipment experts were invited to formulate a ‘Scale-based Questionnaire for Assessing Nursing Personnel’s Operational Knowledge of Common Medical Equipment’ to evaluate the nursing personnel’s literacy regarding the operation of the medical equipment. From March to October 2017, an employee training on medical equipment operation and a practice course (simulation course) were implemented, after which the effectiveness of the training and practice course were assessed. Results: Prior to and after the training and practice course, the 66 participating nurses scored 58 and 87 on ‘operational knowledge of common medical equipment,’ respectively (showing a significant statistical difference; t = -9.407, p < .001); 53.5 and 86.3 on ‘operational knowledge of 12-lead electrocardiography’ (z = -2.087, p < .01), respectively; 40 and 79.5 on ‘operational knowledge of cardiac defibrillators’ (z = -3.849, p < .001), respectively; 90 and 98 on ‘operational knowledge of Abbott pumps’ (z = -1.841, p = 0.066), respectively; and 8.7 and 13.7 on ‘perceived competence’ (showing a significant statistical difference; t = -2.77, p < .05). In the participating hospital, medical equipment operation errors were observed in both 2016 and 2017. However, since the implementation of the intervention, medical equipment operation errors have not yet been observed up to October 2017, which can be regarded as the secondary outcome of this study. Conclusion: In this study, innovative teaching strategies were adopted to effectively enhance the professional literacy and skills of nursing personnel in operating medical equipment. The training and practice course also elevated the nursing personnel’s related literacy and perceived competence of operating medical equipment. The nursing personnel was thus able to accurately operate the medical equipment and avoid operational errors that might jeopardize patient safety.

Keywords: medical equipment, digital teaching plan, simulation-based teaching plan, operational knowledge, patient safety

Procedia PDF Downloads 138

Authors: Anishur Rahman, Maria Areias, Diogo Simões, Ana Figeuiredo, Filipa Figueiredo, João Nunes

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The circular economy (CE) has gained increased awareness among academics, businesses, and decision-makers as it stimulates resource circularity in the production and consumption systems. A large epistemological study has explored the principles of CE, but scant attention eagerly focused on analysing how CE is evaluated, consented to, and enforced using economic metabolism data and business intelligent framework. Economic metabolism involves the ongoing exchange of materials and energy within and across socio-economic systems and requires the assessment of vast amounts of data to provide quantitative analysis related to effective resource management. Limited concern, the present work has focused on the regional flows pilot region from Portugal. By addressing this gap, this study aims to promote eco-innovation and sustainability in the regions of Intermunicipal Communities Região de Coimbra, Viseu Dão Lafões and Beiras e Serra da Estrela, using this data to find precise synergies in terms of material flows and give companies a competitive advantage in form of valuable waste destinations, access to new resources and new markets, cost reduction and risk sharing benefits. In our work, emphasis on applying artificial intelligence (AI) and, more specifically, on implementing state-of-the-art deep learning algorithms is placed, contributing to construction a business intelligent approach. With the emergence of new approaches generally highlighted under the sub-heading of AI and machine learning (ML), the methods for statistical analysis of complex and uncertain production systems are facing significant changes. Therefore, various definitions of AI and its differences from traditional statistics are presented, and furthermore, ML is introduced to identify its place in data science and the differences in topics such as big data analytics and in production problems that using AI and ML are identified. A lifecycle-based approach is then taken to analyse the use of different methods in each phase to identify the most useful technologies and unifying attributes of AI in manufacturing. Most of macroeconomic metabolisms models are mainly direct to contexts of large metropolis, neglecting rural territories, so within this project, a dynamic decision support model coupled with artificial intelligence tools and information platforms will be developed, focused on the reality of these transition zones between the rural and urban. Thus, a real decision support tool is under development, which will surpass the scientific developments carried out to date and will allow to overcome imitations related to the availability and reliability of data.

Keywords: circular economy, artificial intelligence, economic metabolisms, machine learning

Procedia PDF Downloads 72

Authors: K. M. S. Weerasinghe, A. H. K. Balasooriya, S. L. Ransingha, G. D. Krishantha, R. S. Brhakamanagae, L. C. Wijethilke

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Tomato (Lycopersicon esculentum Mill.) is a major horticultural crop with an estimated global production of over 120 million metric tons and ranks first as a processing crop. The average tomato productivity in Sri Lanka (11 metric tons/ha) is much lower than the world average (24 metric tons/ha).To meet the tomato demand for the increasing population the productivity has to be intensified through the agronomic-techniques. Nutrition is one of the main factors which govern the growth and yield of tomato and the main nutrient source soil affect the plant growth and quality of the produce. Continuous cropping, improper fertilizer usage etc., cause widespread nutrient deficiencies. Therefore synthetic fertilizers and organic manures were introduced to enhance plant growth and maximize the crop yields. In this study, effects of macro and micronutrient supplementations on improvement of growth and yield of tomato were investigated. Selected tomato variety is Maheshi and plants were grown in Regional Agricultural and Research Centre Makadura under the Department of Agriculture recommended (DOA) macro nutrients and various combination of Ontario recommended dosages of secondary and micro fertilizer supplementations. There were six treatments in this experiment and each treatment was replicated in three times and each replicate consisted of six plants. Other than the DOA recommendation, five combinations of Ontario recommended dosage of secondary and micronutrients for tomato were also used as treatments. The treatments were arranged in a Randomized Complete Block Design. All cultural practices were carried out according to the DOA recommendations. The mean data was subjected to the statistical analysis using SAS package and mean separation (Duncan’s Multiple Range test at 5% probability level) procedures. Secondary and micronutrients containing treatments significantly increased most of the growth parameters. Plant height, plant girth, number of leaves, leaf area index etc. Fruits harvested from pots amended with macro, secondary and micronutrients performed best in terms of total yield; yield quality; to pots amended with DOA recommended dosage of fertilizer for tomato. It could be due to the application of all essential macro and micro nutrients that rise in photosynthetic activity, efficient translocation and utilization of photosynthates causing rapid cell elongation and cell division in actively growing region of the plant leading to stimulation of growth and yield were caused. The experiment revealed and highlighted the requirements of essential macro, secondary and micro nutrient fertilizer supplementations for tomato farming. The study indicated that, macro and micro nutrient supplementation practices can influence growth and yield performances of tomato fruits and it is a promising approach to get potential tomato yields.

Keywords: macro and micronutrients, tomato, SAS package, photosynthates

Procedia PDF Downloads 474

Authors: Savas Yildiz

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The article assesses the performance of international aid donors to determine the sub-national distribution of their aid projects dependent on recipient countries’ governance. The present paper extends the scope from a cross-country perspective to a more detailed analysis by looking at the effects of institutional qualities on the sub-national distribution of foreign aid. The analysis examines geo-referenced aid project in 37 countries and 404 regions at the first administrative division level in Sub-Saharan Africa from the World Bank (WB) and the African Development Bank (ADB) that were approved between the years 2000 and 2011. To measure the influence of institutional qualities on the distribution of aid the following measures are used: control of corruption, government effectiveness, regulatory quality and rule of law from the World Governance Indicators (WGI) and the corruption perception index from Transparency International. Furthermore, to assess the importance of ethnic heterogeneity on the sub-national distribution of aid projects, the study also includes interaction terms measuring ethnic fragmentation. The regression results indicate a general skew of aid projects towards regions which hold capital cities, however, being incumbent presidents’ birth region does not increase the allocation of aid projects significantly. Nevertheless, with increasing quality of institutions aid projects are less skewed towards capital regions and the previously estimated coefficients loose significance in most cases. Higher ethnic fragmentation also seems to impede the possibility to allocate aid projects mainly in capital city regions and presidents’ birth places. Additionally, to assess the performance of the WB based on its own proclaimed goal to aim the poor in a country, the study also includes sub-national wealth data from the Demographic and Health Surveys (DSH), and finds that, even with better institutional qualities, regions with a larger share from the richest quintile receive significantly more aid than regions with a larger share of poor people. With increasing ethnic diversity, the allocation of aid projects towards regions where the richest citizens reside diminishes, but still remains high and significant. However, regions with a larger share of poor people still do not receive significantly more aid. This might imply that the sub-national distribution of aid projects increases in general with higher ethnic fragmentation, independent of the diverse regional needs. The results provide evidence that institutional qualities matter to undermine the influence of incumbent presidents on the allocation of aid projects towards their birth regions and capital regions. Moreover, even for countries with better institutional qualities the WB and the ADB do not seem to be able to aim the poor in a country with their aid projects. Even, if one considers need-based variables, such as infant mortality and child mortality rates, aid projects do not seem to be allocated in districts with a larger share of people in need. Therefore, the study provides further evidence using more detailed information on the sub-national distribution of aid projects that aid is not being allocated effectively towards regions with a larger share of poor people to alleviate poverty in recipient countries directly. Institutions do not have any significant influence on the sub-national distribution of aid towards the poor.

Keywords: aid allocation, georeferenced data, institutions, spatial analysis

Procedia PDF Downloads 119

Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

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Authors: Sheikh Nawaz Ali, Pratima Pandey, P. Morthekai, Jyotsna Dubey, Md. Firoze Quamar

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The high mountain glaciers are one of the most sensitive recorders of climate changes, because they have the tendency to respond to the combined effect of snow fall and temperature. The Himalayan glaciers have been studied with a good pace during the last decade. However, owing to its large ecological diversity and geographical vividness, major part of the Indian Himalaya is uninvestigated, and hence the palaeoclimatic patterns as well as the chronology of past glaciations in particular remain controversial for the entire Indian Himalayan transect. Although the Himalayan glaciers are nourished by two important climatic systems viz. the southwest summer monsoon and the mid-latitude westerlies, however, the influence of these systems is yet to be understood. Nevertheless, existing chronology (mostly exposure ages) indicate that irrespective of the geographical position, glaciers seem to grow during enhanced Indian summer monsoon (ISM). The Himalayan mountain glaciers are referred to the third pole or water tower of Asia as they form a huge reservoir of the fresh water supplies for the Asian countries. Mountain glaciers are sensitive probes of the local climate, and, thus, they present an opportunity and a challenge to interpret climates of the past as well as to predict future changes. The principle object of all the palaeoclimatic studies is to develop a futuristic models/scenario. However, it has been found that the glacial chronologies bracket the major phases of climatic events only, and other climatic proxies are sparse in Himalaya. This is the reason that compilation of data for rapid climatic change during the Holocene shows major gaps in this region. The sedimentation in proglacial lakes, conversely, is more continuous and, hence, can be used to reconstruct a more complete record of past climatic variability that is modulated by changing ice volume of the valley glacier. The Himalayan region has numerous proglacial lacustrine deposits formed during the late Quaternary period. However, there are only few such deposits which have been studied so far. Therefore, this is the high time when efforts have to be made to systematically map the moraines located in different climatic zones, reconstruct the local and regional moraine stratigraphy and use multiple dating techniques to bracket the events of glaciation. Besides this, emphasis must be given on carrying multiproxy studies on the lacustrine sediments that will provide a high resolution palaeoclimatic data from the alpine region of the Himalaya. Although the Himalayan glaciers fluctuated in accordance with the changing climatic conditions (natural forcing), however, it is too early to arrive at any conclusion. It is very crucial to generate multiproxy data sets covering wider geographical and ecological domains taking into consideration multiple parameters that directly or indirectly influence the glacier mass balance as well as the local climate of a region.

Keywords: glacial chronology, palaeoclimate, multiproxy, Himalaya

Procedia PDF Downloads 263

Authors: Ana Alvarenga De Castro

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Food sovereignty has been brought by the international peasants’ movement, La Via Campesina, as a precondition to food security, speaking about the right of each nation to keep its own supply of foods respecting cultural, sustainable practices and productive diversity. The political conceptualization nowadays goes beyond saying that this term is about achieving the rights of farmers to control the food systems according to local specificities, and about equality in the access to natural resources and quality food. The current feminization of agroecosystems and of food insecurity identified by researchers and recognized by international agencies like the UN and FAO has enhanced the feminist discourse into the food sovereignty movement, considering the historical inequalities that place women farmers in subaltern positions inside the families and rural communities. The current tendency in many rural areas of more women taking responsibility for food production and still facing the lack of access to natural resources meets particular aspects in Latin America due to the global economic logic which places the Global South in the position of raw material supplier for the industrialized North, combined with regional characteristics. In this context, Latin American countries play the role of commodities exporters in the international labor division, including among exported items grains, soybean paste, and ores, to the expense of local food chains which provide domestic quality food supply under more sustainable practices. The connections between gender inequalities and global territorial inequalities related to the access and control of food and natural resources are pointed out by feminist political ecology - FPE - authors, and are linked in this article to the potentialities and limitations of women farmers to reproduce diversified agroecosystems in the tropical environments. The work brings the importance of local practices held by women farmers which are crucial to maintaining sustainable agricultural systems and their results on seeds, soil, biodiversity and water conservation. This work presents an analysis of documents, releases, videos and other publicized experiences launched by some peasants’ organizations in Latin America which evidence the different technical and political answers that meet food sovereignty from peasants’ groups that are attributed to women farmers. They are associated with articles presenting the empirical analysis of women farmers' practices in Latin America. The combination drove to discuss the benefits of peasants' conceptions about food systems and their connections with local realities and the gender issues linked to the food sovereignty conceptualization. Conclusion meets that reality on the field cannot reach food sovereignty's ideal homogeneously and that agricultural sustainable practices are dependent on rights' achievement and social inequalities' eradication.

Keywords: food sovereignty, gender, diversified agricultural systems, access to natural resources

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Authors: Zuhal Kurt, Meral Kurt, Bilge T. Bal, Kemal Ozkan

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Shade matching and reproduction is the most important element of success in prosthetic dentistry. Until recently, shade matching procedure was implemented by dentists visual perception with the help of shade guides. Since many factors influence visual perception; tooth shade matching using visual devices (shade guides) is highly subjective and inconsistent. Subjective nature of this process has lead to the development of instrumental devices. Nowadays, colorimeters, spectrophotometers, spectroradiometers and digital image analysing systems are used for instrumental shade selection. Instrumental devices have advantages that readings are quantifiable, can obtain more rapidly and simply, objectively and precisely. However, these devices have noticeable drawbacks. For example, translucent structure and irregular surfaces of teeth lead to defects on measurement with these devices. Also between the results acquired by devices with different measurement principles may make inconsistencies. So, its obligatory to search for new methods for dental shade matching process. A computer-aided system device; digital camera has developed rapidly upon today. Currently, advances in image processing and computing have resulted in the extensive use of digital cameras for color imaging. This procedure has a much cheaper process than the use of traditional contact-type color measurement devices. Digital cameras can be taken by the place of contact-type instruments for shade selection and overcome their disadvantages. Images taken from teeth show morphology and color texture of teeth. In last decades, a new method was recommended to compare the color of shade tabs taken by a digital camera using color features. This method showed that visual and computer-aided shade matching systems should be used as concatenated. Recently using methods of feature extraction techniques are based on shape description and not used color information. However, color is mostly experienced as an essential property in depicting and extracting features from objects in the world around us. When local feature descriptors with color information are extended by concatenating color descriptor with the shape descriptor, that descriptor will be effective on visual object recognition and classification task. Therefore, the color descriptor is to be used in combination with a shape descriptor it does not need to contain any spatial information, which leads us to use local histograms. This local color histogram method is remain reliable under variation of photometric changes, geometrical changes and variation of image quality. So, coloring local feature extraction methods are used to extract features, and also the Scale Invariant Feature Transform (SIFT) descriptor used to for shape description in the proposed method. After the combination of these descriptors, the state-of-art descriptor named by Color-SIFT will be used in this study. Finally, the image feature vectors obtained from quantization algorithm are fed to classifiers such as Nearest Neighbor (KNN), Naive Bayes or Support Vector Machines (SVM) to determine label(s) of the visual object category or matching. In this study, SVM are used as classifiers for color determination and shade matching. Finally, experimental results of this method will be compared with other recent studies. It is concluded from the study that the proposed method is remarkable development on computer aided tooth shade determination system.

Keywords: classifiers, color determination, computer-aided system, tooth shade matching, feature extraction

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Authors: Dalila Chaid, Bennameur Fedilli, Mohammed Amine Bellelou

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The study focuses on the experience of lower-limb amputees, who face both physical and psychological challenges due to their disability. Chronic neuropathic pain and various types of limb pain are common in these patients. They often require orthopaedic interventions for issues such as dressings, infection, ulceration, and bone-related problems. Research Aim: The aim of this study is to determine the most suitable anaesthetic technique for lower-limb amputees, which can provide them with the greatest comfort and prolonged analgesia. The study also aims to demonstrate the effectiveness and cost-effectiveness of ultrasound-guided local regional anaesthesia (LRA) in this patient population. Methodology: The study is an observational analytical study conducted over a period of eight years, from 2010 to 2018. It includes a total of 955 cases of revisions performed on lower limb stumps. The parameters analyzed in this study include the effectiveness of the block and the use of sedation, the duration of the block, the post-operative visual analog scale (VAS) scores, and patient comfort. Findings: The study findings highlight the benefits of ultrasound-guided LRA in providing comfort by optimizing post-operative analgesia, which can contribute to psychological and bodily repair in lower-limb amputees. Additionally, the study emphasizes the use of alpha2 agonist adjuvants with sedative and analgesic properties, long-acting local anaesthetics, and larger volumes for better outcomes. Theoretical Importance: This study contributes to the existing knowledge by emphasizing the importance of choosing an appropriate anaesthetic technique for lower-limb amputees. It highlights the potential of ultrasound-guided LRA and the use of specific adjuvants and local anaesthetics in improving post-operative analgesia and overall patient outcomes. Data Collection and Analysis Procedures: Data for this study were collected through the analysis of medical records and relevant documentation related to the 955 cases included in the study. The effectiveness of the anaesthetic technique, duration of the block, post-operative pain scores, and patient comfort were analyzed using statistical methods. Question Addressed: The study addresses the question of which anaesthetic technique would be most suitable for lower-limb amputees to provide them with optimal comfort and prolonged analgesia. Conclusion: The study concludes that ultrasound-guided LRA, along with the use of alpha2 agonist adjuvants, long-acting local anaesthetics, and larger volumes, can be an effective approach in providing comfort and improving post-operative analgesia for lower-limb amputees. This technique can potentially contribute to the psychological and bodily repair of these patients. The findings of this study have implications for clinical practice in the management of lower-limb amputees, highlighting the importance of personalized anaesthetic approaches for better outcomes.

Keywords: neuropathic pain, ultrasound-guided peripheral nerve block, DN4 quiz, EMG

Procedia PDF Downloads 78

Authors: Shanlong Lu, Jiming Jin, Xiaochun Wang

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The Tibetan Plateau has the largest number of inland lakes with the highest elevation on the planet. These massive and large lakes are mostly in natural state and are less affected by human activities. Their shrinking or expansion can truly reflect regional climate and environmental changes and are sensitive indicators of global climate change. However, due to the sparsely populated nature of the plateau and the poor natural conditions, it is difficult to effectively obtain the change data of the lake, which has affected people's understanding of the temporal and spatial processes of lake water changes and their influencing factors. By using the MODIS (Moderate Resolution Imaging Spectroradiometer) MOD09Q1 surface reflectance images as basic data, this study produced the 8-day lake water surface data set of the Tibetan Plateau from 2000 to 2012 at 250 m spatial resolution, with a lake water surface extraction method of combined with lake water surface boundary buffer analyzing and lake by lake segmentation threshold determining. Then based on the dataset, the lake water surface variations and their influencing factors were analyzed, by using 4 typical natural geographical zones of Eastern Qinghai and Qilian, Southern Qinghai, Qiangtang, and Southern Tibet, and the watersheds of the top 10 lakes of Qinghai, Siling Co, Namco, Zhari NamCo, Tangra Yumco, Ngoring, UlanUla, Yamdrok Tso, Har and Gyaring as the analysis units. The accuracy analysis indicate that compared with water surface data of the 134 sample lakes extracted from the 30 m Landsat TM (Thematic Mapper ) images, the average overall accuracy of the lake water surface data set is 91.81% with average commission and omission error of 3.26% and 5.38%; the results also show strong linear (R2=0.9991) correlation with the global MODIS water mask dataset with overall accuracy of 86.30%; and the lake area difference between the Second National Lake Survey and this study is only 4.74%, respectively. This study provides reliable dataset for the lake change research of the plateau in the recent decade. The change trends and influencing factors analysis indicate that the total water surface area of lakes in the plateau showed overall increases, but only lakes with areas larger than 10 km2 had statistically significant increases. Furthermore, lakes with area larger than 100 km2 experienced an abrupt change in 2005. In addition, the annual average precipitation of Southern Tibet and Southern Qinghai experienced significant increasing and decreasing trends, and corresponding abrupt changes in 2004 and 2006, respectively. The annual average temperature of Southern Tibet and Qiangtang showed a significant increasing trend with an abrupt change in 2004. The major reason for the lake water surface variation in Eastern Qinghai and Qilian, Southern Qinghai and Southern Tibet is the changes of precipitation, and that for Qiangtang is the temperature variations.

Keywords: lake water surface variation, MODIS MOD09Q1, remote sensing, Tibetan Plateau

Procedia PDF Downloads 231

Authors: Evgenia Iakovleva, Juha Koivisto, Pasi Karppinen, J. Inkinen, Mikko Alava

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Preventing the spread of infectious diseases throughout the worldwide is one of the most important tasks of modern health care. Infectious diseases not only account for one fifth of the deaths in the world, but also cause many pathological complications for the human health. Touch surfaces pose an important vector for the spread of infections by varying microorganisms, including antimicrobial resistant organisms. Further, antimicrobial resistance is reply of bacteria to the overused or inappropriate used of antibiotics everywhere. The biggest challenges in bacterial detection by existing methods are non-direct determination, long time of analysis, the sample preparation, use of chemicals and expensive equipment, and availability of qualified specialists. Therefore, a high-performance, rapid, real-time detection is demanded in rapid practical bacterial detection and to control the epidemiological hazard. Among the known methods for determining bacteria on the surfaces, Hyperspectral methods can be used as direct and rapid methods for microorganism detection on different kind of surfaces based on fluorescence without sampling, sample preparation and chemicals. The aim of this study was to assess the relevance of such systems to remote sensing of surfaces for microorganisms detection to prevent a global spread of infectious diseases. Bacillus subtilis and Escherichia coli with different concentrations (from 0 to 10x8 cell/100µL) were detected with hyperspectral camera using different filters as visible visualization of bacteria and background spots on the steel plate. A method of internal standards was applied for monitoring the correctness of the analysis results. Distances from sample to hyperspectral camera and light source are 25 cm and 40 cm, respectively. Each sample is optically imaged from the surface by hyperspectral imaging system, utilizing a JAI CM-140GE-UV camera. Light source is BeamZ FLATPAR DMX Tri-light, 3W tri-colour LEDs (red, blue and green). Light colors are changed through DMX USB Pro interface. The developed system was calibrated following a standard procedure of setting exposure and focused for light with λ=525 nm. The filter is ThorLabs KuriousTM hyperspectral filter controller with wavelengths from 420 to 720 nm. All data collection, pro-processing and multivariate analysis was performed using LabVIEW and Python software. The studied human eye visible and invisible bacterial stains clustered apart from a reference steel material by clustering analysis using different light sources and filter wavelengths. The calculation of random and systematic errors of the analysis results proved the applicability of the method in real conditions. Validation experiments have been carried out with photometry and ATP swab-test. The lower detection limit of developed method is several orders of magnitude lower than for both validation methods. All parameters of the experiments were the same, except for the light. Hyperspectral imaging method allows to separate not only bacteria and surfaces, but also different types of bacteria, such as Gram-negative Escherichia coli and Gram-positive Bacillus subtilis. Developed method allows skipping the sample preparation and the use of chemicals, unlike all other microbiological methods. The time of analysis with novel hyperspectral system is a few seconds, which is innovative in the field of microbiological tests.

Keywords: Escherichia coli, Bacillus subtilis, hyperspectral imaging, microorganisms detection

Procedia PDF Downloads 223

Authors: Qian Chen, Lin Xu, Ping Ju, Zhuoran Li, Yiping Yu, Yuqing Jin

Abstract:

The operation of power grid is becoming more and more complex and difficult due to its rapid development towards high voltage, long distance, and large capacity. For instance, many large-scale wind farms have connected to power grid, where their fluctuation and randomness is very likely to affect the stability and safety of the grid. Fortunately, many new-type equipments based on power electronics have been applied to power grid, such as UPFC (Unified Power Flow Controller), TCSC (Thyristor Controlled Series Compensation), STATCOM (Static Synchronous Compensator) and so on, which can help to deal with the problem above. Compared with traditional equipment such as generator, new-type controllable devices, represented by the FACTS (Flexible AC Transmission System), have more accurate control ability and respond faster. But they are too expensive to use widely. Therefore, on the basis of the comparison and analysis of the controlling characteristics between traditional control equipment and new-type controllable equipment in both time and space scale, a coordinated optimizing control method within mutil-time-space frame is proposed in this paper to bring both kinds of advantages into play, which can better both control ability and economical efficiency. Firstly, the coordination of different space sizes of grid is studied focused on the fluctuation caused by large-scale wind farms connected to power grid. With generator, FSC (Fixed Series Compensation) and TCSC, the coordination method on two-layer regional power grid vs. its sub grid is studied in detail. The coordination control model is built, the corresponding scheme is promoted, and the conclusion is verified by simulation. By analysis, interface power flow can be controlled by generator and the specific line power flow between two-layer regions can be adjusted by FSC and TCSC. The smaller the interface power flow adjusted by generator, the bigger the control margin of TCSC, instead, the total consumption of generator is much higher. Secondly, the coordination of different time sizes is studied to further the amount of the total consumption of generator and the control margin of TCSC, where the minimum control cost can be acquired. The coordination method on two-layer ultra short-term correction vs. AGC (Automatic Generation Control) is studied with generator, FSC and TCSC. The optimal control model is founded, genetic algorithm is selected to solve the problem, and the conclusion is verified by simulation. Finally, the aforementioned method within multi-time-space scale is analyzed with practical cases, and simulated on PSASP (Power System Analysis Software Package) platform. The correctness and effectiveness are verified by the simulation result. Moreover, this coordinated optimizing control method can contribute to the decrease of control cost and will provide reference to the following studies in this field.

Keywords: FACTS, multi-space-time frame, optimal control, TCSC

Procedia PDF Downloads 267

Authors: Giulia Bonaldo, Alberto Vaccheri, Ottavio D'Annibali, Domenico Motola

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The Human Papilloma Virus (HPV) was shown to be the cause of different types of carcinomas, first of all of the cervical intraepithelial neoplasia. Since the early 80s to today, thanks first to the preventive screening campaigns (pap-test) and following to the introduction of HPV vaccines on the market; the number of new cases of cervical cancer has decreased significantly. The HPV vaccines currently approved are three: Cervarix® (HPV2 - virus type: 16 and 18), Gardasil® (HPV4 - 6, 11, 16, 18) and Gardasil 9® (HPV9 - 6, 11, 16, 18, 31, 33, 45, 52, 58), which all protect against the two high-risk HPVs (6, 11) that are mainly involved in cervical cancers. Despite the remarkable effectiveness of these vaccines has been demonstrated, in the recent years, there have been many complaints about their risk-benefit profile due to Adverse Events Following Immunization (AEFI). The purpose of this study is to provide a support about the ongoing discussion on the safety profile of HPV vaccines based on real life data deriving from spontaneous reports of suspected AEFIs collected in the Vaccine Adverse Events Reporting System (VAERS). VAERS is a freely-available national vaccine safety surveillance database of AEFI, co-administered by the Centers for Disease Control and Prevention (CDC) and Food and Drug Administration (FDA). We collected all the reports between January 2007 to December 2017 related to the HPV vaccines with a brand name (HPV2, HPV4, HPV9) or without (HPVX). A disproportionality analysis using Reporting Odds Ratio (ROR) with 95% confidence interval and p value ≤ 0.05 was performed. Over the 10-year period, 54889 reports of AEFI related to HPV vaccines reported in VAERS, corresponding to 224863 vaccine-event pairs, were retrieved. The highest number of reports was related to Gardasil (n = 42244), followed by Gardasil 9 (7212) and Cervarix (3904). The brand name of the HPV vaccine was not reported in 1529 cases. The two events more frequently reported and statistically significant for each vaccine were: dizziness (n = 5053) ROR = 1.28 (CI95% 1.24 – 1.31) and syncope (4808) ROR = 1.21 (1.17 – 1.25) for Gardasil. For Gardasil 9, injection site pain (305) ROR = 1.40 (1.25 – 1.57) and injection site erythema (297) ROR = 1.88 (1.67 – 2.10) and for Cervarix, headache (672) ROR = 1.14 (1.06 – 1.23) and loss of consciousness (528) ROR = 1.71 (1.57 – 1.87). In total, we collected 406 reports of death and 2461 cases of permanent disability in the ten-year period. The events consisting of incorrect vaccine storage or incorrect administration were not considered. The AEFI analysis showed that the most frequently reported events are non-serious and listed in the corresponding SmPCs. In addition to these, potential safety signals arose regarding less frequent and severe AEFIs that would deserve further investigation. This already happened with the referral of the European Medicines Agency (EMA) for the adverse events POTS (Postural Orthostatic Tachycardia Syndrome) and CRPS (Complex Regional Pain Syndrome) associated with anti-papillomavirus vaccines.

Keywords: adverse drug reactions, pharmacovigilance, safety, vaccines

Procedia PDF Downloads 163