Search results for: incomplete immunization

Authors: Azad Jarrahian, Ehsan Heidaryan

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Matrix acidizing treatments can yield impressive production increase if properly applied. In this study, carbonate samples taken from Ahwaz Oilfield have undergone static solubility, sludge, emulsion, and core flooding tests. In each test interaction of acid and rock is reported and at the end it has been shown that how initial permeability and type of acid affects the overall treatment efficiency.

Keywords: carbonate acidizing, organic acids, spending rate, acid penetration, incomplete spending.

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Authors: Amadou Wurry Jallow, Adama N. S. Bah, Karamo Bah, Shih-Ye Wang, Kuo-Chung Chu, Chien-Yeh Hsu

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Chronic kidney disease (CKD) is a major public health challenge with high prevalence, rising incidence, and serious adverse consequences. Developing effective risk prediction models is a cost-effective approach to predicting and preventing complications of chronic kidney disease (CKD). This study aimed to develop an accurate machine learning model that can dynamically identify individuals at risk of CKD using various kinds of diagnostic data, with or without laboratory data, at different follow-up points. Creatinine is a key component used to predict CKD. These models will enable affordable and effective screening for CKD even with incomplete patient data, such as the absence of creatinine testing. This retrospective cohort study included data on 19,429 adults provided by a private research institute and screening laboratory in Taiwan, gathered between 2001 and 2015. Univariate Cox proportional hazard regression analyses were performed to determine the variables with high prognostic values for predicting CKD. We then identified interacting variables and grouped them according to diagnostic data categories. Our models used three types of data gathered at three points in time: non-laboratory, laboratory, and metabolic indices data. Next, we used subgroups of variables within each category to train two machine learning models (Random Forest and XGBoost). Our machine learning models can dynamically discriminate individuals at risk for developing CKD. All the models performed well using all three kinds of data, with or without laboratory data. Using only non-laboratory-based data (such as age, sex, body mass index (BMI), and waist circumference), both models predict chronic kidney disease as accurately as models using laboratory and metabolic indices data. Our machine learning models have demonstrated the use of different categories of diagnostic data for CKD prediction, with or without laboratory data. The machine learning models are simple to use and flexible because they work even with incomplete data and can be applied in any clinical setting, including settings where laboratory data is difficult to obtain.

Keywords: chronic kidney disease, glomerular filtration rate, creatinine, novel metabolic indices, machine learning, risk prediction

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Authors: Peiran Ma

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This study explored the role of political polarization in an individual's decision of receiving the COVID-19 vaccine. A total of 15 participants participated in individual interviews and focus group discussions about the relationships among domestic political polarization, vaccine hesitancy, and behavioral responses to the COVID-19 pandemic. Political affiliation affected an individual’s decision on the COVID-19 vaccination, such that people who identified as Liberals and Democrats were more accepting of the vaccine. On the other hand, the level of influence declined over time (2020-2022) when the general conception of COVID-19 immunization shifted from political to personal. Results provided qualitative support to the previously identified positive relationship between divided political opinions and COVID-19 vaccine hesitancy and highlighted the decreasing trend in the power of political polarization in vaccination and the existence of other factors.

Keywords: COVID-19, vaccine hesitancy, political polarization, partisanship, ideology

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Authors: Tim Crocker-Buque, Sandra Mounier-Jack, Natasha Howard

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Background: Due to both the increasing scale and speed of urbanisation, urban areas in low and middle-income countries (LMICs) host increasingly large populations of under-immunized children, with the additional associated risks of rapid disease transmission in high-density living environments. Multiple interdependent factors are associated with these coverage disparities in urban areas and most evidence comes from relatively few countries, e.g., predominantly India, Kenya, Nigeria, and some from Pakistan, Iran, and Brazil. This study aimed to identify, describe, and assess the main tools used to measure or improve coverage of immunisation services in poor urban areas. Methods: Authors used a qualitative review design, including academic and non-academic literature, to identify tools used to improve coverage of public health interventions in urban areas. Authors selected and extracted sources that provided good examples of specific tools, or categories of tools, used in a context relevant to urban immunization. Diagnostic (e.g., for data collection, analysis, and insight generation) and programme tools (e.g., for investigating or improving ongoing programmes) and interventions (e.g., multi-component or stand-alone with evidence) were selected for inclusion to provide a range of type and availability of relevant tools. These were then prioritised using a decision-analysis framework and a tool selection guide for programme managers developed. Results: Authors reviewed tools used in urban immunisation contexts and tools designed for (i) non-immunization and/or non-health interventions in urban areas, and (ii) immunisation in rural contexts that had relevance for urban areas (e.g., Reaching every District/Child/ Zone). Many approaches combined several tools and methods, which authors categorised as diagnostic, programme, and intervention. The most common diagnostic tools were cross-sectional surveys, key informant interviews, focus group discussions, secondary analysis of routine data, and geographical mapping of outcomes, resources, and services. Programme tools involved multiple stages of data collection, analysis, insight generation, and intervention planning and included guidance documents from WHO (World Health Organisation), UNICEF (United Nations Children's Fund), USAID (United States Agency for International Development), and governments, and articles reporting on diagnostics, interventions, and/or evaluations to improve urban immunisation. Interventions involved service improvement, education, reminder/recall, incentives, outreach, mass-media, or were multi-component. The main gaps in existing tools were an assessment of macro/policy-level factors, exploration of effective immunization communication channels, and measuring in/out-migration. The proposed framework uses a problem tree approach to suggest tools to address five common challenges (i.e. identifying populations, understanding communities, issues with service access and use, improving services, improving coverage) based on context and available data. Conclusion: This study identified many tools relevant to evaluating urban LMIC immunisation programmes, including significant crossover between tools. This was encouraging in terms of supporting the identification of common areas, but problematic as data volumes, instructions, and activities could overwhelm managers and tools are not always suitably applied to suitable contexts. Further research is needed on how best to combine tools and methods to suit local contexts. Authors’ initial framework can be tested and developed further.

Keywords: health equity, immunisation, low and middle-income countries, poverty, urban health

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Authors: El Mahdi Barrah, Said Safi, Abdessamad Malaoui

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In this paper, we present an algorithm for reconstruction from incomplete 2D scans for tifinagh characters. This algorithm is based on using correlation between the lost block and its neighbors. This system proposed contains three main parts: pre-processing, features extraction and recognition. In the first step, we construct a database of tifinagh characters. In the second step, we will apply “shape analysis algorithm”. In classification part, we will use Neural Network. The simulation results demonstrate that the proposed method give good results.

Keywords: Tifinagh character recognition, neural networks, local cost computation, ANN

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Authors: Jularat Chumnaul

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In forensic science, corpses from various homicides are different; there are both complete and incomplete, depending on causes of death or forms of homicide. For example, some corpses are cut into pieces, some are camouflaged by dumping into the river, some are buried, some are burned to destroy the evidence, and others. If the corpses are incomplete, it can lead to the difficulty of personally identifying because some tissues and bones are destroyed. To specify gender of the corpses from skeletal remains, the most precise method is DNA identification. However, this method is costly and takes longer so that other identification techniques are used instead. The first technique that is widely used is considering the features of bones. In general, an evidence from the corpses such as some pieces of bones, especially the skull and pelvis can be used to identify their gender. To use this technique, forensic scientists are required observation skills in order to classify the difference between male and female bones. Although this technique is uncomplicated, saving time and cost, and the forensic scientists can fairly accurately determine gender by using this technique (apparently an accuracy rate of 90% or more), the crucial disadvantage is there are only some positions of skeleton that can be used to specify gender such as supraorbital ridge, nuchal crest, temporal lobe, mandible, and chin. Therefore, the skeletal remains that will be used have to be complete. The other technique that is widely used for gender specifying in forensic science and archeology is skeletal measurements. The advantage of this method is it can be used in several positions in one piece of bones, and it can be used even if the bones are not complete. In this study, the classification and cluster analysis are applied to this technique, including the Kth Nearest Neighbor Classification, Classification Tree, Ward Linkage Cluster, K-mean Cluster, and Two Step Cluster. The data contains 507 particular individuals and 9 skeletal measurements (diameter measurements), and the performance of five methods are investigated by considering the apparent error rate (APER). The results from this study indicate that the Two Step Cluster and Kth Nearest Neighbor method seem to be suitable to specify gender from human skeletal remains because both yield small apparent error rate of 0.20% and 4.14%, respectively. On the other hand, the Classification Tree, Ward Linkage Cluster, and K-mean Cluster method are not appropriate since they yield large apparent error rate of 10.65%, 10.65%, and 16.37%, respectively. However, there are other ways to evaluate the performance of classification such as an estimate of the error rate using the holdout procedure or misclassification costs, and the difference methods can make the different conclusions.

Keywords: skeletal measurements, classification, cluster, apparent error rate

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Authors: Felipe Villegas-Velasquez, Harold Pantoja-Villota, Sergio Holguin-Cardona, Alejandro Osorio-Botero, Brayan Candamil-Arango

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Colombian electricity comes mainly from hydric resources, affected by environmental variations such as the El Niño phenomenon. That is why incorporating other types of resources is necessary to provide electricity constantly. This research seeks to fill the wind speed and global solar irradiance dataset for two years with the highest amount of information. A further result is the characterization of the data by region that led to infer which errors occurred and offered the incomplete dataset.

Keywords: energy, wind speed, global solar irradiance, Colombia, imputation

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Authors: Halkiopoulos Constantinos, Koutsopoulou Ioanna, Gkintoni Evgenia, Antonopoulou Hera

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Immunization appears to be an essential part of health care service in times of pandemics such as covid-19 and aims not only to protect the health of the population but also the health and sustainability of the economies of the countries affected. It is reported that more than 3.44 billion doses have been administered so far, which accounts for 45 doses for 100 people. Vaccination programs in various countries have been promoted and accepted by people differently and therefore they proceeded in different ways and speed; most countries directing them towards people with vulnerable chronic or recent health statuses. Large scale restriction measures or lockdown, personal protection measures such as masks and gloves and a decrease in leisure and sports activities were also implemented around the world as part of the protection health strategies against the covid-19 pandemic. This research aims to present an analysis based on variations on people’s attitudes towards vaccination based on demographic, social and epidemiological characteristics, and health status on the one hand and perception of health, health satisfaction, pain, and quality of life on the other hand. 1500 Greek e-consumers participated in the research, mainly through social media who took part in an online-based survey voluntarily. The questionnaires included demographic, social and medical characteristics of the participants, and questions asking people’s willingness to be vaccinated and their opinion on whether there should be a vaccine against covid-19. Other stressor factors were also reported in the questionnaires and participants’ loss of someone close due to covid-19, or staying at home quarantine due to being infected from covid-19. WHOQUOL-BREF and GLOBAL PSYCHOTRAUMA SCREEN- GPS were used with kind permission from WHO and from the International Society for Traumatic Stress Studies in this study. Attitudes towards vaccination varied significantly related to aging, level of education, health status and consumer behavior. Health professionals’ attitudes also varied in relation to age, level of education, profession, health status and consumer needs. Vaccines have been the most common technological aid of human civilization so far in the fight against viruses. The results of this study can be used for health managers and digital marketers of pharmaceutical companies and also other staff involved in vaccination programs and for designing health policy immunization strategies during pandemics in order to achieve positive attitudes towards vaccination and larger populations being vaccinated in shorter periods of time after the break out of pandemic. Health staff needs to be trained, aided and supervised to go through with vaccination programs and to be protected through vaccination programs themselves. Feedback in each country’s vaccination program, short backs, deficiencies and delays should be addressed and worked out.

Keywords: consumer behavior, cognitive models, vaccination policy, pandemic, Covid-19, Greece

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Authors: Belhouchet Selma, Ben Amar Anis

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We examine the impact of COVID-19 transmission, containment measures, and vaccination growth on daily stock market returns for the G7 countries (Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States) from January 22, 2020, to August 31, 2021, more than a year and a half after COVID-19. For this objective, we use panel pooled ordinary least squares regressions. Our findings indicate that the spread of the pandemic has a negative impact on the daily performance of the world's seven main stock markets. Government measures to improve stock market returns are no longer successful. Furthermore, our findings demonstrate that immunization efforts in G7 nations do not increase stock market performance in these countries. A variety of robustness tests back up our conclusions. Our findings have far-reaching implications for investors, governments, and regulators not only in the G7 countries but also in all developed countries and all countries globally.

Keywords: COVID-19, G7 stock market, containment measures, vaccination

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Authors: Hazem M. Al-Mofleh

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In this paper, a new four-parameter univariate continuous distribution called the Normal-Generalized Hyperbolic Secant Distribution (NGHS) is defined and studied. Some general and structural distributional properties are investigated and discussed, including: central and non-central n-th moments and incomplete moments, quantile and generating functions, hazard function, Rényi and Shannon entropies, shapes: skewed right, skewed left, and symmetric, modality regions: unimodal and bimodal, maximum likelihood (MLE) estimators for the parameters. Finally, two real data sets are used to demonstrate empirically its flexibility and prove the strength of the new distribution.

Keywords: bimodality, estimation, hazard function, moments, Shannon’s entropy

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Authors: H. M. Nanjundaswamy, S. K. Nath, S. Ray

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TiO₂ particles have been added in molten aluminium to result in aluminium based cast Al/Al₃Ti-Al₂O₃ composite, which has been added then to molten magnesium to synthesize magnesium based cast Mg-Al/Al₃Ti-Al₂O₃ composite. The nominal compositions in terms of Mg, Al, and TiO₂ contents in the magnesium based composites are Mg-9Al-0.6TiO₂, Mg-9Al-0.8TiO₂, Mg-9Al-1.0TiO₂ and Mg-9Al-1.2TiO₂ designated respectively as MA6T, MA8T, MA10T and MA12T. The microstructure of the cast magnesium based composite shows grayish rods of intermetallics Al₃Ti, inherited from aluminium based composite but these rods, on hot forging, breaks into smaller lengths decreasing the average aspect ratio (length to diameter) from 7.5 to 3.0. There are also cavities in between the broken segments of rods. β-phase in cast microstructure, Mg₁₇Al₁₂, dissolves during heating prior to forging and re-precipitates as relatively finer particles on cooling. The amount of β-phase also decreases on forging as segregation is removed. In both the cast and forged composite, the Brinell hardness increases rapidly with increasing addition of TiO₂ but the hardness is higher in forged composites by about 80 BHN. With addition of higher level of TiO₂ in magnesium based cast composite, yield strength decreases progressively but there is marginal increase in yield strength over that of the cast Mg-9 wt. pct. Al, designated as MA alloy. But the ultimate tensile strength (UTS) in the cast composites decreases with the increasing particle content indicating possibly an early initiation of crack in the brittle inter-dendritic region and their easy propagation through the interfaces of the particles. In forged composites, there is a significant improvement in both yield strength and UTS with increasing TiO₂ addition and also, over those observed in their cast counterpart, but at higher addition it decreases. It may also be noted that as in forged MA alloy, incomplete recovery of forging strain increases the strength of the matrix in the composites and the ductility decreases both in the forged alloy and the composites. Initiation fracture toughness, J_IC, decreases drastically in cast composites compared to that in MA alloy due to the presence of intermetallic Al₃Ti and Al₂O₃ particles in the composite. There is drastic reduction of J_IC on forging both in the alloy and the composites, possibly due to incomplete recovery of forging strain in both as well as breaking of Al₃Ti rods and the voids between the broken segments of Al₃Ti rods in composites. The ratio of tearing modulus to elastic modulus in cast composites show higher ratio, which increases with the increasing TiO₂ addition. The ratio decreases comparatively more on forging of cast MA alloy than those in forged composites.

Keywords: composite, fracture toughness, forging, tensile properties

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Authors: Mohammad Tahir Yousafzai, Rubina Qasim

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We assessed Hepatitis B vaccination and its determinants among health care workers (HCW) in Northwest Pakistan. HCWs from both public and private clinics were interviewed about hepatitis B vaccination, socio-demographic, hepatitis B virus transmission modes, disease threat and benefits of vaccination. Logistic regression was performed. Hepatitis B vaccination was 40% (Qualified Physicians: 86% and non-qualified Dispensers:16%). Being Qualified Physician (Adj. OR 26.6; 95%CI 9.3-73.2), Non-qualified Physician (Adj.OR 1.9; 95%CI 0.8-4.6), qualified Dispensers (Adj. OR 3.6; 95%CI 1.3-9.5) compared to non-qualified Dispensers, working in public clinics (Adj. OR 2.5; 95%CI 1.1-5.7) compared to private, perceived disease threat after exposure to blood and body fluids (Adj. OR 1.1; 95%CI 1.1-1.2) and perceived benefits of vaccination (Adj. OR 1.1; 95%CI 1.1-1.2) were significant predictors of hepatitis B vaccination. Improved perception of disease threat and benefits of vaccination and qualification of HCWs are associated with hepatitis B vaccination.

Keywords: Hepatitis B vaccine, immunization, healthcare workers, primary health

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Authors: Syed Ali Taqi, Muhammad Ismail

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A comparative study of estimators of population means in two phase sampling in the presence of non-response when Unknown population means of the auxiliary variable(s) and incomplete information of study variable y as well as of auxiliary variable(s) is made. Three real data sets of University students, hospital and unemployment are used for comparison of all the available techniques in two phase sampling in the presence of non-response with the newly generalized ratio estimators.

Keywords: two-phase sampling, ratio estimator, product estimator, generalized estimators

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Authors: Ana Staneva, Vessela Stoimenova

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A parametric estimation of the MBP with Power Series offspring distribution family is considered in this paper. The MLE for the parameters is obtained in the case when the observable data are incomplete and consist only with the generation sizes of the family tree of MBP. The parameter estimation is calculated by using the Monte Carlo EM algorithm. The estimation for the posterior distribution and for the offspring distribution parameters are calculated by using the Bayesian approach and the Gibbs sampler. The article proposes various examples with bivariate branching processes together with computational results, simulation and an implementation using R.

Keywords: Bayesian, branching processes, EM algorithm, Gibbs sampler, Monte Carlo methods, statistical estimation

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Authors: Jasman Tuyon, Zamri Ahmad

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Behavioral asset pricing research has been gaining momentum since in 1990s. However, it is still incomplete and has been criticized for some philosophical, theoretical and model specification limitations. Due to these drawbacks, investors’ behaviors as a source of risk in behavioral asset pricing modeling still remains disputable. This paper aims to address these issues with an alternative perspective based on behavioral finance paradigm. Specifically, this paper proposes a theoretical linkages of both fundamental and behavioral risks on stock prices formation and an extension of the multifactor stock pricing model by combining multi-factor fundamentals and behavioral risks factors.

Keywords: behavioral finance, multifactor asset pricing, behavioral risks, fundamental risks

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Authors: Mohammed A. Zidan, Alaa Sagheer, Nasser Metwally

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Real-time learning is an important goal that most of artificial intelligence researches try to achieve it. There are a lot of problems and applications which require low cost learning such as learn a robot to be able to classify and recognize patterns in real time and real-time recall. In this contribution, we suggest a model of quantum competitive learning based on a series of quantum gates and additional operator. The proposed model enables to recognize any incomplete patterns, where we can increase the probability of recognizing the pattern at the expense of the undesired ones. Moreover, these undesired ones could be utilized as new patterns for the system. The proposed model is much better compared with classical approaches and more powerful than the current quantum competitive learning approaches.

Keywords: competitive learning, quantum gates, quantum gates, winner-take-all

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Authors: S. Woźniak, J. Rybka, T. Paszkowski, P. Milart

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A 30-year-old patient, who was pregnant for her second 9 weeks, was admitted to the hospital due to a suspected incomplete miscarriage. A fetal egg was found in the uterine cavity near the mouth of the fallopian tube. The patient was qualified for dilatation and curettage. The histopathological examination revealed fragments of the trophoblast. Two months later, the patient was re-admitted to the hospital due to vaginal bleeding and elevated levels of beta-hCG. Additional tests were performed. An intramural pregnancy was suspected. The patient was qualified for embolization of the uterine arteries and then treatment with methotrexate. Three weeks later, during a routine gynecological examination, a detached tumor 4 cm in diameter was found in the vagina. The material was sent for histopathological examination, which showed the presence of trophoblastic cells.

Keywords: ectopic pregnancy, intramural pregnancy, uterine artery embolization, methotrexate

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Authors: Alexis Aldo Mendoza Villarroel, Ademir Clemente Villena Zevallos, Cristian Jose Lopez Del Alamo

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With the advancement of technology it is now possible to scan entire objects and obtain their digital representation by using point clouds or polygon meshes. However, some objects may be broken or have missing parts; thus, several methods focused on this problem have been proposed based on Geometric Deep Learning, such as GCNN, ACNN, PointNet, among others. In this article an approach from a different paradigm is proposed, using metric data structures to index global descriptors in the spectral domain and allow the recovery of a set of similar models in polynomial time; to later use the Iterative Close Point algorithm and recover the parts of the incomplete model using the geometry and topology of the model with less Hausdorff distance.

Keywords: 3D reconstruction method, point cloud completion, shape completion, similarity search

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Authors: Ronald Croce, Timothy Quinn, John Miller

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Incomplete activation, or activation failure, of motor units during maximal voluntary contractions is often referred to as muscle inhibition (MI), and is defined as the inability of the central nervous system to maximally drive a muscle during a voluntary contraction. The purpose of the present study was to assess the interrelationship amongst peak torque (PT), muscle inhibition (MI; incomplete activation of motor units), and voluntary muscle activation (VMA) of the quadriceps’ muscle group as a function of knee angle and muscle length during maximal voluntary isometric contractions (MVICs). Nine young adult males (mean + standard deviation: age: 21.58 + 1.30 years; height: 180.07 + 4.99 cm; weight: 89.07 + 7.55 kg) performed MVICs in random order with the knee at 15, 55, and 95° flexion. MI was assessed using the interpolated twitch technique and was estimated by the amount of additional knee extensor PT evoked by the superimposed twitch during MVICs. Voluntary muscle activation was estimated by root mean square amplitude electromyography (EMGrms) and mechanomyography (MMGrms) of agonist (vastus medialis [VM], vastus lateralis [VL], and rectus femoris [RF]) and antagonist (biceps femoris ([BF]) muscles during MVICs. Data were analyzed using separate repeated measures analysis of variance. Results revealed a strong dependency of quadriceps’ PT (p < 0.001), MI (p < 0.001) and MA (p < 0.01) on knee joint position: PT was smallest at the most shortened muscle position (15°) and greatest at mid-position (55°); MI and MA were smallest at the most shortened muscle position (15°) and greatest at the most lengthened position (95°), with the RF showing the greatest change in MA. It is hypothesized that the ability to more fully activate the quadriceps at short compared to longer muscle lengths (96% contracted at 15°; 91% at 55°; 90% at 95°) might partly compensate for the unfavorable force-length mechanics at the more extended position and consequent declines in VMA (decreases in EMGrms and MMGrms muscle amplitude during MVICs) and force production (PT = 111-Nm at 15°, 217-NM at 55°, 199-Nm at 95°). Biceps femoris EMG and MMG data showed no statistical differences (p = 0.11 and 0.12, respectively) at joint angles tested, although there were greater values at the extended position. Increased BF muscle amplitude at this position could be a mechanism by which anterior shear and tibial rotation induced by high quadriceps’ activity are countered. Measuring and understanding the degree to which one sees MI and VMA in the QF muscle has particular clinical relevance because different knee-joint disorders, such ligament injuries or osteoarthritis, increase levels of MI observed and markedly reduced the capability of full VMA.

Keywords: electromyography, interpolated twitch technique, mechanomyography, muscle activation, muscle inhibition

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Authors: Gopinath Rathod, Vinod Puranik

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Sustainability is regarded as a key concept for survival in the competitive scenario. Industrial risk and diversification of risk type’s increases with industrial developments. In the context of sustainable manufacturing, the evaluation of risk is difficult because of the incomplete information and multiple indicators. Fuzzy Multiple Attribute Decision Method (FMADM) has been used with a three level hierarchical decision making model to evaluate aggregate risk for sustainable manufacturing projects. A case study has been presented to reflect the risk characteristics in sustainable manufacturing projects.

Keywords: sustainable manufacturing, decision making, aggregate risk, fuzzy logic, fuzzy multiple attribute decision method

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Authors: Maik Kschischo, Dominik Kahl, Philipp Wendland, Andreas Weber

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Understanding and modelling of real-world complex dynamic systems in biology, engineering and other fields is often made difficult by incomplete knowledge about the interactions between systems states and by unknown disturbances to the system. In fact, most real-world dynamic networks are open systems receiving unknown inputs from their environment. To understand a system and to estimate the state dynamics, these inputs need to be reconstructed from output measurements. Reconstructing the input of a dynamic system from its measured outputs is an ill-posed problem if only a limited number of states is directly measurable. A first requirement for solving this problem is the invertibility of the input-output map. In our work, we exploit the fact that invertibility of a dynamic system is a structural property, which depends only on the network topology. Therefore, it is possible to check for invertibility using a structural invertibility algorithm which counts the number of node disjoint paths linking inputs and outputs. The algorithm is efficient enough, even for large networks up to a million nodes. To understand structural features influencing the invertibility of a complex dynamic network, we analyze synthetic and real networks using the structural invertibility algorithm. We find that invertibility largely depends on the degree distribution and that dense random networks are easier to invert than sparse inhomogeneous networks. We show that real networks are often very difficult to invert unless the sensor nodes are carefully chosen. To overcome this problem, we present a sensor node placement algorithm to achieve invertibility with a minimum set of measured states. This greedy algorithm is very fast and also guaranteed to find an optimal sensor node-set if it exists. Our results provide a practical approach to experimental design for open, dynamic systems. Since invertibility is a necessary condition for unknown input observers and data assimilation filters to work, it can be used as a preprocessing step to check, whether these input reconstruction algorithms can be successful. If not, we can suggest additional measurements providing sufficient information for input reconstruction. Invertibility is also important for systems design and model building. Dynamic models are always incomplete, and synthetic systems act in an environment, where they receive inputs or even attack signals from their exterior. Being able to monitor these inputs is an important design requirement, which can be achieved by our algorithms for invertibility analysis and sensor node placement.

Keywords: data-driven dynamic systems, inversion of dynamic systems, observability, experimental design, sensor node placement

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Authors: Sergey Podluzhnyy

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One of the most important tasks of investment and pension fund management is building decision support system which helps to make right decision on corporate bond portfolio formation. Today there are several basic methods of bond portfolio management. They are duration management, immunization and convexity management. Identified methods have serious disadvantage: they do not take into account credit risk or insolvency risk of issuer. So, identified methods can be applied only for management and evaluation of high-quality sovereign bonds. Applying article proposes mathematical model for building an optimal in case of risk and yield corporate bond portfolio. Proposed model takes into account the default probability in formula of assessment of bonds which results to more correct evaluation of bonds prices. Moreover, applied model provides tools for visualization of the efficient frontier of corporate bonds portfolio taking into account the exposure to credit risk, which will increase the quality of the investment decisions of portfolio managers.

Keywords: corporate bond portfolio, default probability, effective boundary, portfolio optimization task

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Authors: Ahmed Abdallatif

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Background: Patients with malignant germ cell tumors have age distribution in two peaks, with the first one during infancy and the second after the onset of puberty. Gonadal germ cell tumors are the most common malignant ovarian tumor in females aged below twenty years. Sacrococcygeal and retroperitoneal abdominal tumors usually presents in a large size before the onset of symptoms. Methods: Patients with pediatric germ cell tumors presenting to Children’s Cancer Hospital Egypt and National Cancer Institute Egypt from January 2008 to June 2011 Patients underwent stratification according to risk into low, intermediate and high risk groups according to children oncology group classification. Objectives: Assessment of the clinicopathologic features of all cases of pediatric germ cell tumors and classification of malignant cases according to their stage, and the primary site to low, intermediate and high risk patients. Evaluation of surgical management in each group of patients focusing on surgical approach, the extent of surgical resection according to each site, ability to achieve complete surgical resection and perioperative complications. Finally, determination of the three years overall and disease-free survival in different groups and the relation to different prognostic factors including the extent of surgical resection. Results: Out of 131 cases surgically explored only 26 cases had re exploration with 8 cases explored for residual disease 9 cases for remote recurrence or metastatic disease and the other 9 cases for other complications. Patients with low risk kept under follow up after surgery, out of those of low risk group (48 patients) only 8 patients (16.5%) shifted to intermediate risk. There were 20 patients (14.6%) diagnosed as intermediate risk received 3 cycles of compressed (Cisplatin, Etoposide and Bleomycin) and all high risk group patients 69patients (50.4%) received chemotherapy. Stage of disease was strongly and significantly related to overall survival with a poorer survival in late stages (stage IV) as compared to earlier stages. Conclusion: Overall survival rate at 3 three years was (76.7% ± 5.4, 3) years EFS was (77.8 % ±4.0), however 3 years DFS was much better (89.8 ± 3.4) in whole study group with ovarian tumors had significantly higher Overall survival (90% ± 5.1). Event Free Survival analysis showed that Male gender was 3 times likely to have bad events than females. Patients who underwent incomplete resection were 4 times more than patients with complete resection to have bad events. Disease free survival analysis showed that Patients who underwent incomplete surgery were 18.8 times liable for recurrence compared to those who underwent complete surgery, and patients who were exposed to re-excision were 21 times more prone to recurrence compared to other patients.

Keywords: extragonadal, germ cell tumors, gonadal, pediatric

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Authors: A. Danbaba

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Several experiments are conducted at different environments such as locations or periods (seasons) with identical treatments to each experiment purposely to study the interaction between the treatments and environments or between the treatments and periods (seasons). The commonly used designs of experiments for this purpose are randomized block design, Latin square design, balanced incomplete block design, Youden design, and one or more factor designs. The interest is to carry out a combined analysis of the data from these multi-environment experiments, instead of analyzing each experiment separately. This paper proposed combined analysis of experiments conducted via Sudoku square design of odd order with same experimental treatments.

Keywords: combined analysis, sudoku design, common treatment, multi-environment experiments

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Authors: Ali Mohammadi

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The construction of Embankment dams is considered one of the most challenging construction projects, for which several main reasons can be mentioned. Excavation and embankment must be done in a large area, and its design is based on preliminary studies, but at the time of construction, it is possible that excavation does not match with the stability or slope of the rock, or the design is incomplete, and corrections should be made in order to be able to carry out excavation and embankment. Also, the progress of the work depends on the main factors, the lack of each of which can slow down the construction of the dams, and lead to an increase in costs, and control of excavations and embankments and calculations of their volumes are done in this collection. In the following, we will investigate three Embankment dams in Iran that faced these challenges and how they overcame these challenges. KHODA AFARIN on the Aras River between the two countries of IRAN and AZARBAIJAN, SIAH BISHEH PUMPED STORAGE on CHALUS River and GOTVAND on KARUN River are among the most important dams built in Iran.

Keywords: section, data transfer, tunnel, free station

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Authors: M. Pieńko, A. Robak, E. Błazik-Borowa, J. Szer

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This paper presents the results of analysis of 100 full-scale scaffolding structures in terms of compliance with legal acts and safety of use. In 2016 and 2017, authors examined scaffolds in Poland located at buildings which were at construction or renovation stage. The basic elements affecting the safety of scaffolding use such as anchors, supports, platforms, guardrails and toe-boards have been taken into account. All of these elements were checked in each of considered scaffolding. Based on the analyzed scaffoldings, the most common errors concerning assembly process and use of scaffolding were collected. Legal acts on the scaffoldings are not always clear, and this causes many issues. In practice, people realize how dangerous the use of incomplete scaffolds is only when the accident occurs. Despite the fact that the scaffolding should ensure the safety of its users, most accidents on construction sites are caused by fall from a height.

Keywords: façade scaffolds, load capacity, practice, safety of people

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Authors: Luigi Pintacuda

Abstract:

What characterize the phenomenology of Bucharest is that all operations of modernization have never been completed, creating a city made up of fragments. Understood this fragmented nature, the traces and fractures, the acceptance of their scars must represent the basis for the design of development for Bucharest. From this insight comes a new analysis of this city: a city of two million inhabitants that does not need a project on an urban scale (as all other major projects for the city have failed), but, starting from the study of all these interstitial spaces of public property, it must find its own strategy, a strategy on a large-scale that reflects on the sites on an architectural one. It is a city composed by fragments, not waste, but places for the project: ‘waiting spaces’ for a possible continuation of the process of genesis of a city which is often incomplete.

Keywords: public spaces, traces fractures, urban design, urban development

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Authors: Jihen Bennaceur, Wissem Zouaghi, Ali Mabrouk

Abstract:

The major aim of cyber threat intelligence (CTI) is to provide sophisticated knowledge about cybersecurity threats to ensure internal and external safeguards against modern cyberattacks. Inaccurate, incomplete, outdated, and invaluable threat intelligence is the main problem. Therefore, data analysis based on AI algorithms is one of the emergent solutions to overcome the threat of information-sharing issues. In this paper, we propose a supervised machine learning-based algorithm to improve threat information sharing by providing a sophisticated classification of cyber threats and data. Extensive simulations investigate the accuracy, precision, recall, f1-score, and support overall to validate the designed algorithm and to compare it with several supervised machine learning algorithms.

Keywords: threat information sharing, supervised learning, data classification, performance evaluation

Procedia PDF Downloads 142

Authors: Ranjeeta Kumari, Makesh M, Gayatri Tripathi, K V Rajendran, Megha Bedekar

Abstract:

A comparative study on DNA immunization with recombinant glyceraldehyde-3-phosphate dehydrogenase (GAPDH) construct of Edwardsiella tarda (pGPD group) and a bicistronic construct expressing GAPDH plus IFN-γ of Labeo rohita as adjuvant (pGPD+IFN group) was undertaken in Labeo rohita along with the control animals. Successful co-expression of two genes that is GAPDH and IFN-γ was confirmed in SSN-1 cells line by RT-qPCR and western blot. The protective immune response of host to DNA vaccine construct was determined by RPS and specific antibody production. Fishes immunized with plasmids via intramuscular injection (I/M) exhibited a considerable relative percentage survivability of 66.66% in pGPD+IFN immunized group and 53.34% in pGPD immunized group after challenge with E. tarda. Antibody response was also significantly high in pGPD+IFN group at all time points under study. This was analysed by competitive ELISA, using anti GAPDH monoclonal antibodies. The experiment revealed that the GAPDH gene of E. tarda is one of the ideal candidates for generating protective immune response in L. rohita. Further addition of Interferon gamma to DNA vaccine construct can enhance the immune response in host.

Keywords: DNA vaccine, Edwardsiella tarda, Labeo rohita, zoonosis, immune response

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Authors: Giselda Cristina Ferreira, Carlos Alberto Kamienski, Ana Lígia Scott

Abstract:

The COVID-19 pandemic has enhanced the anti-vaccination movement in Brazil, supported by unscientific theories and false news and the possibility of wide communication through social networks such as Twitter, Facebook, and YouTube. The World Health Organization (WHO) classified the large volume of information on the subject against COVID-19 as an Infodemic. In this paper, we present a protocol to identify polarizing users (called polarizers) and study the profiles of Brazilian polarizers on Twitter (renamed to X some weeks ago). We analyzed polarizing interactions on Twitter (in Portuguese) to identify the main polarizers and how the conflicts they caused influenced the COVID-19 vaccination rate throughout the pandemic. This protocol uses data from this social network, graph theory, Java, and R-studio scripts to model and analyze the data. The information about the vaccination rate was obtained in a public database for the government called OpenDataSus. The results present the profiles of Twitter’s Polarizer (political position, gender, professional activity, immunization opinions). We observed that social and political events influenced the participation of these different profiles in conflicts and the vaccination rate.

Keywords: Twitter, polarization, vaccine, Brazil

Procedia PDF Downloads 73