Search results for: negative data

Authors: Sonia Boscenco, Zihan Wang, Euclides José de Mendoça Filho, João Paulo Hoppe, Irina Pokhvisneva, Geoffrey B.C. Hall, Michael J. Meaney, Patricia Pelufo Silveira

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Entropy can be described as a measure of the number of states of a system, and when used in the context of physiological time-based signals, it serves as a measure of complexity. In functional connectivity data, entropy can account for the moment-to-moment variability that is neglected in traditional functional magnetic resonance imaging (fMRI) analyses. While brain fMRI resting state entropy has been associated with some pathological conditions like schizophrenia, no investigations have explored the association between brain entropy measures and individual differences in child behavior in healthy children. We describe a novel exploratory approach to evaluate brain fMRI resting state data in two child cohorts, and MAVAN (N=54, 4.5 years, 48% males) and GUSTO (N = 206, 4.5 years, 48% males) and its associations to child behavior, that can be used in future research in the context of child exposures and long-term health. Following rs-fMRI data pre-processing and Shannon entropy calculation across 32 network regions of interest to acquire 496 unique functional connections, partial correlation coefficient analysis adjusted for sex was performed to identify associations between entropy data and Strengths and Difficulties questionnaire in MAVAN and Child Behavior Checklist domains in GUSTO. Significance was set at p < 0.01, and we found eight significant associations in GUSTO. Negative associations were found between two frontoparietal regions and cerebellar posterior and oppositional defiant problems, (r = -0.212, p = 0.006) and (r = -0.200, p = 0.009). Positive associations were identified between somatic complaints and four default mode connections: salience insula (r = 0.202, p < 0.01), dorsal attention intraparietal sulcus (r = 0.231, p = 0.003), language inferior frontal gyrus (r = 0.207, p = 0.008) and language posterior superior temporal gyrus (r = 0.210, p = 0.008). Positive associations were also found between insula and frontoparietal connection and attention deficit / hyperactivity problems (r = 0.200, p < 0.01), and insula – default mode connection and pervasive developmental problems (r = 0.210, p = 0.007). In MAVAN, ten significant associations were identified. Two positive associations were found = with prosocial scores: the salience prefrontal cortex and dorsal attention connection (r = 0.474, p = 0.005) and the salience supramarginal gyrus and dorsal attention intraparietal sulcus (r = 0.447, p = 0.008). The insula and prefrontal connection were negatively associated with peer problems (r = -0.437, p < 0.01). Conduct problems were negatively associated with six separate connections, the left salience insula and right salience insula (r = -0.449, p = 0.008), left salience insula and right salience supramarginal gyrus (r = -0.512, p = 0.002), the default mode and visual network (r = -0.444, p = 0.009), dorsal attention and language network (r = -0.490, p = 0.003), and default mode and posterior parietal cortex (r = -0.546, p = 0.001). Entropy measures of resting state functional connectivity can be used to identify individual differences in brain function that are correlated with variation in behavioral problems in healthy children. Further studies applying this marker into the context of environmental exposures are warranted.

Keywords: child behaviour, functional connectivity, imaging, Shannon entropy

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Authors: Mikel Niño, Roberto V. Zicari, Todor Ivanov, Kim Hee, Naveed Mushtaq, Marten Rosselli, Concha Sánchez-Ocaña, Karsten Tolle, José Miguel Blanco, Arantza Illarramendi, Jörg Besier, Harry Underwood

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One of the application fields for data analysis techniques and technologies gaining momentum is the area of social good or “common good”, covering cases related to humanitarian crises, global health care, or ecology and environmental issues, among others. The promotion of data-driven projects in this field aims at increasing the efficacy and efficiency of social initiatives, improving the way these actions help humanity in general and people in need in particular. This application field, however, poses its own barriers and challenges when developing data-driven projects, lagging behind in comparison with other scenarios. These challenges derive from aspects such as the scope and scale of the social issue to solve, cultural and political barriers, the skills of main stakeholders and the technological resources available, the motivation to be engaged in such projects, or the ethical and legal issues related to sensitive data. This paper analyzes the application of data projects in the field of social good, reviewing its current state and noteworthy initiatives, and presenting a framework covering the key aspects to analyze in such projects. The goal is to provide guidelines to understand the main challenges and opportunities for this type of data project, as well as identifying the main differential issues compared to “classical” data projects in general. A case study is presented on the initial steps and stakeholder analysis of a data project for the inclusion of refugees in the city of Frankfurt, Germany, in order to empirically confront the framework with a real example.

Keywords: data-driven projects, humanitarian operations, personal and sensitive data, social good, stakeholders analysis

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Authors: Nia McRae, Robert Wright, Ghalib Bello

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Introduction: Postpartum depression is a prevalent mood disorder that is detrimental to the mental and physical health of mothers and their newborns. Lead (Pb) is a toxic metal that is associated with hormonal imbalance and mental impairments. The hormone changes that accompany pregnancy and childbirth may be exacerbated by Pb and increase new mothers’ susceptibility to postpartum depression. To the best of the author’s knowledge, this is the only study that investigates the association between prenatal Pb exposure and postpartum depression. Identifying risk factors can contribute to improved prevention and treatment strategies for postpartum depression. Methods: Data was derived from the Programming Research in Obesity, Growth, Environment and Social Stress (PROGRESS) study which is an ongoing longitudinal birth cohort. Postpartum depression was identified by a score of 13 or above on the 10-Item Edinburg Postnatal Depression Scale (EPDS) 6-months and 12-months postpartum. Pb was measured in the blood (BPb) in the second and third trimester and in the tibia and patella 1-month postpartum. Quantile regression models were used to assess the relationship between BPb and postpartum depression. Results: BPb in the second trimester was negatively associated with the 80th percentile of depression 6-months postpartum (β: -0.26; 95% CI: -0.51, -0.01). No significant association was found between BPb in the third trimester and depression 6-months postpartum. BPb in the third trimester exhibited an inverse relationship with the 60th percentile (β: -0.23; 95% CI: -0.41, -0.06), 70th percentile (β: -0.31; 95% CI: -0.52, -0.10), and 90th percentile of depression 12-months postpartum (β: -0.36; 95% CI: -0.69, -0.03). There was no significant association between BPb in the second trimester and depression 12-months postpartum. Bone Pb concentrations were not significantly associated with postpartum depression. Conclusion: The negative association between BPb and postpartum depression may support research which demonstrates lead is a nontherapeutic stimulant. Further research is needed to verify these results and identify effect modifiers.

Keywords: depression, lead, postpartum, prenatal

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Authors: B. Y. Danjuma, A. Archibong-Eso, Aliyu M. Aliyu, H. Yeung

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In this experimental investigation, a new data for slugging frequency for high viscosity oil-gas flow are reported. Scale experiments were carried out using a mixture of air and mineral oil as the liquid phase in a 17 m long horizontal pipe with 0.0762 ID. The data set was acquired using two high-speed Gamma Densitometers at a data acquisition frequency of 250 Hz over a time interval of 30 seconds. For the range of flow conditions investigated, increase in liquid oil viscosity was observed to strongly influence the slug frequency. A comparison of the present data with prediction models available in the literature revealed huge discrepancies. A new correlation incorporating the effect of viscosity on slug frequency has been proposed for the horizontal flow, which represents the main contribution of this work.

Keywords: gamma densitometer, flow pattern, pressure gradient, slug frequency

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Authors: Tolga Hayit, Ucman Ergun, Ugur Fidan

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Being healthy is undoubtedly an indispensable necessity for human life. With technological improvements, in the literature, various health monitoring and imaging systems have been developed to satisfy your health needs. In this context, the work of monitoring and recording the data of individual health monitoring data via wireless technology is also being part of these studies. Nowadays, mobile devices which are located in almost every house and which become indispensable of our life and have wireless technology infrastructure have an important place of making follow-up health everywhere and every time because these devices were using in the health monitoring systems. In this study, Arduino an open-source microcontroller card was used in which a sample sugar measuring device was connected in series. In this way, the glucose data (glucose ratio, time) obtained with the glucometer is transferred to the mobile device based on the Android operating system with the Bluetooth technology channel. A mobile application was developed using the Apache Cordova framework for listing data, presenting graphically and reading data over Arduino. Apache Cordova, HTML, Javascript and CSS are used in coding section. The data received from the glucometer is stored in the local database of the mobile device. It is intended that people can transfer their measurements to their mobile device by using wireless technology and access the graphical representations of their data. In this context, the aim of the study is to be able to perform health monitoring by using different wireless technologies in mobile devices that can respond to different wireless technologies at present. Thus, that will contribute the other works done in this area.

Keywords: Arduino, Bluetooth, glucose measurement, mobile health monitoring

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Authors: Natalia Kalinowska

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The adoption of the General Data Protection Regulation, (GDPR) finished the four-year work of the European Commission in this area in the European Union. Considering far-reaching changes, which will be applied by GDPR, the European legislator envisaged two-year transitional period. Member states and companies have to prepare for a new regulation until 25 of May 2018. The idea, which becomes a new look at an attitude to data protection in the European Union is risk-based approach. So far, as a result of implementation of Directive 95/46/WE, in many European countries (including Poland) there have been adopted very particular regulations, specifying technical and organisational security measures e.g. Polish implementing rules indicate even how long password should be. According to the new approach from May 2018, controllers and processors will be obliged to apply security measures adequate to level of risk associated with specific data processing. The risk in GDPR should be interpreted as the likelihood of a breach of the rights and freedoms of the data subject. According to Recital 76, the likelihood and severity of the risk to the rights and freedoms of the data subject should be determined by reference to the nature, scope, context and purposes of the processing. GDPR does not indicate security measures which should be applied – in recitals there are only examples such as anonymization or encryption. It depends on a controller’s decision what type of security measures controller considered as sufficient and he will be responsible if these measures are not sufficient or if his identification of risk level is incorrect. Data protection regulation indicates few levels of risk. Recital 76 indicates risk and high risk, but some lawyers think, that there is one more category – low risk/now risk. Low risk/now risk data processing is a situation when it is unlikely to result in a risk to the rights and freedoms of natural persons. GDPR mentions types of data processing when a controller does not have to evaluate level of risk because it has been classified as „high risk” processing e.g. processing on a large scale of special categories of data, processing with using new technologies. The methodology will include analysis of legal regulations e.g. GDPR, the Polish Act on the Protection of personal data. Moreover: ICO Guidelines and articles concerning risk based approach in GDPR. The main conclusion is that an appropriate risk assessment is a key to keeping data safe and avoiding financial penalties. On the one hand, this approach seems to be more equitable, not only for controllers or processors but also for data subjects, but on the other hand, it increases controllers’ uncertainties in the assessment which could have a direct impact on incorrect data protection and potential responsibility for infringement of regulation.

Keywords: general data protection regulation, personal data protection, privacy protection, risk based approach

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Authors: Kamel Barka, Lyamine Guezouli, Assem Rezki

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In this article, we propose a protocol called DataGA-DRF (a protocol for Data collection using a Genetic Algorithm through Dynamic Reference Points) that collects data from Heterogeneous wireless sensor networks. This protocol is based on DGA (Destination selection according to Genetic Algorithm) to control the movement of the UAV (Unmanned aerial vehicle) between dynamic reference points that virtually represent the sensor node deployment. The dynamics of these points ensure an even distribution of energy consumption among the sensors and also improve network performance. To determine the best points, DataGA-DRF uses a classification algorithm such as K-Means.

Keywords: heterogeneous wireless networks, unmanned aerial vehicles, reference point, collect data, genetic algorithm

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Authors: Fuad Ali Mohammed Al-Yarimi

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Many algorithms have been proposed to provide privacy preserving in data mining. These protocols are based on two main approaches named as: the perturbation approach and the Cryptographic approach. The first one is based on perturbation of the valuable information while the second one uses cryptographic techniques. The perturbation approach is much more efficient with reduced accuracy while the cryptographic approach can provide solutions with perfect accuracy. However, the cryptographic approach is a much slower method and requires considerable computation and communication overhead. In this paper, a new scalable protocol is proposed which combines the advantages of the perturbation and distortion along with cryptographic approach to perform privacy preserving in distributed frequent itemset mining on horizontally distributed data. Both the privacy and performance characteristics of the proposed protocol are studied empirically.

Keywords: anonymity data, data mining, distributed frequent itemset mining, gaussian perturbation, perturbation approach, privacy preserving data mining

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Authors: Shubham Bhonde, Nekzad Doctor, Shashwat Gawande

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For the use and the import of Keys and ID Transmitter as well as Body Control Modules with radio transmission in a lot of countries, homologation is required. Final deliverables in homologation of the product are certificates. In considering the world of homologation, there are approximately 200 certificates per product, with most of the certificates in local languages. It is challenging to manually investigate each certificate and extract relevant data from the certificate, such as expiry date, approval date, etc. It is most important to get accurate data from the certificate as inaccuracy may lead to missing re-homologation of certificates that will result in an incompliance situation. There is a scope of automation in reading the certificate data in the field of homologation. We are using deep learning as a tool for automation. We have first trained a model using machine learning by providing all country's basic data. We have trained this model only once. We trained the model by feeding pdf and jpg files using the ETL process. Eventually, that trained model will give more accurate results later. As an outcome, we will get the expiry date and approval date of the certificate with a single click. This will eventually help to implement automation features on a broader level in the database where certificates are stored. This automation will help to minimize human error to almost negligible.

Keywords: homologation, re-homologation, data science, deep learning, machine learning, ETL (extract transform loading)

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Authors: Kanchan Mondal, Dasharath Koulage, Dattatray Manerikar, Asmita Ghate

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This paper presents an additive reliability model using warranty data and Finite Element Analysis (FEA) data. Warranty data for any product gives insight to its underlying issues. This is often used by Reliability Engineers to build prediction model to forecast failure rate of parts. But there is one major limitation in using warranty data for prediction. Warranty periods constitute only a small fraction of total lifetime of a product, most of the time it covers only the infant mortality and useful life zone of a bathtub curve. Predicting with warranty data alone in these cases is not generally provide results with desired accuracy. Failure rate of a mechanical part is driven by random issues initially and wear-out or usage related issues at later stages of the lifetime. For better predictability of failure rate, one need to explore the failure rate behavior at wear out zone of a bathtub curve. Due to cost and time constraints, it is not always possible to test samples till failure, but FEA-Fatigue analysis can provide the failure rate behavior of a part much beyond warranty period in a quicker time and at lesser cost. In this work, the authors proposed an Additive Weibull Model, which make use of both warranty and FEA fatigue analysis data for predicting failure rates. It involves modeling of two data sets of a part, one with existing warranty claims and other with fatigue life data. Hazard rate base Weibull estimation has been used for the modeling the warranty data whereas S-N curved based Weibull parameter estimation is used for FEA data. Two separate Weibull models’ parameters are estimated and combined to form the proposed Additive Weibull Model for prediction.

Keywords: bathtub curve, fatigue, FEA, reliability, warranty, Weibull

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Authors: Barry D. Kyle, Jessica Boyd, Robin Pickersgill, Nicole Squires, Cynthia Balion

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Background-Aim: Fentanyl is a highly-potent synthetic μ-opioid receptor agonist used for exceptional pain management. Its main metabolite, norfentanyl, is typically present in urine at significantly high concentrations (i.e. ~20%) representing an effective targeting molecule for immunoassay detection. Here, we evaluated the NCS^TM One Step Fentanyl Test Device© and the BTNX Rapid Response^TM Single Drug Test Strip© point of care (POC) test strips targeting norfentanyl (20 ng/ml) and fentanyl (100 ng/ml) molecules for potential risperidone interference. Methods: POC tests calibrated against norfentanyl (20 ng/ml) used [immunochromatographic] lateral flow devices to provide qualitative results within five minutes of urine sample contact. Results were recorded as negative if lines appeared in the test and control regions according to manufacturer’s instructions. Positive results were recorded if no line appeared in the test region (i.e., control line only visible). Pooled patient urine (n=20), that screened negative for drugs of abuse (using NCS One Step Multi-Line Screen) and fentanyl (using BTNX Rapid Response Strip) was used for spiking studies. Urine was spiked with risperidone alone and with combinations of fentanyl, norfentanyl and/or risperidone to evaluate cross-reactivity in each test device. Results: A positive screen result was obtained when 8,000 ng/mL of risperidone was spiked into drug free urine using the NCS test device. Positive screen results were also obtained in spiked urine samples containing fentanyl and norfentanyl combinations below the cut-off concentrations when 4000 ng/mL risperidone was present using the NCS testing device. There were no screen positive test results using the BTNX test strip with up to 8,000 ng/mL alone or in combination with concentrations of fentanyl and norfentanyl below the cut-off. Both devices screened positive when either fentanyl or norfentanyl exceeded the cut-off threshold in the absence and presence of risperidone. Conclusion: We report that urine samples containing risperidone may give a false positive result using the NCS One Step Fentanyl Test Device.

Keywords: fentanyl, interferences, point of care test, Risperidone

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Authors: Marianne Lumacang, Jessarine Dultra, Joana Fenol

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Filipinos are known to be conservative, sex or pornography is not discussed openly in the Philippines, topic of sex, when raised, will most likely elicit snickers, jokes, and blushes in most Filipino or expressions of disgust. However, a lot of Filipinos are still engaging into this kind of activity for some reasons. The study aims to determine young adult’s point of view about cyber pornography viewing, as well as their reasons for engagement, and its effects on them and their relationship with their partner. Interpretative Phenomenological Analysis was used to explore how young adults make sense of cyber pornography viewing. The study focused on Filipino young adults who are in a romantic or married relationship, engage in cyber pornography viewing, and currently residing in Cavite, Philippines. A total of four young adult couples, four females and four males participated in the study as research participants. Data gathered from a total of four young adult couples resulted to a total of nine superordinate themes focusing on (1) exploring young adult couple’s rationales for cyber pornography viewing, (2) experiences of positive effects in engaging to cyber pornography viewing, (3) experiences of negative effects in engaging to cyber pornography viewing, (4) experience of infidelity, (5) experience of necessity, (6) females perception about cyber pornography viewing towards self, (7) males perception about cyber pornography viewing towards self, (8) males perception about cyber pornography viewing towards romantic partner, and (9) males perception about cyber pornography viewing towards others.

Keywords: cyberpornography, Filipino, interpretative phenomenological analysis, making sense of cyberpornography, young adult

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Authors: Farzaneh Mohammadi Jouzdani, Vahid Javidroozi, Monica Mateo Garcia, Hanifa Shah

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The emergence of developing smart net-zero cities in recent years has attracted significant attention and interest from worldwide communities and scholars as a potential solution to the critical requirement for urban sustainability. This research-in-progress paper aims to investigate the development of smart net-zero cities to propose a digital transformation roadmap for smart net-zero cities with a primary focus on data. Employing systems thinking as an underpinning theory, the study advocates for the necessity of utilising a holistic strategy for understanding the complex interdependencies and interrelationships that characterise urban systems. The proposed methodology will involve an in-depth investigation of current data-driven approaches in the smart net-zero city. This is followed by utilising predictive analysis methods to evaluate the holistic impact of the approaches on moving toward a Smart net-zero city. It is expected to achieve systemic intervention followed by a data-focused and systemic digital transformation roadmap for smart net-zero, contributing to a more holistic understanding of urban sustainability.

Keywords: smart city, net-zero city, digital transformation, systems thinking, data integration, data-driven approach

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Authors: Brittany Joi B. Kirsch

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Textbooks carry a crucial role in imparting ideologies that stimulate inclusivity and social diversity. In the Philippines, a law on inclusive education (IE) for differently-abled learners has recently been signed in order to ensure their rights to quality and IE are protected and upheld (Republic Act No. 11650, 2022). With the presence of ableism in textbooks, the promotion of IE may be challenged. A considerable amount of research has been done on disability representation and ableism in foreign countries; however, none, to the extent of the researcher’s knowledge, has been conducted on ableist ideologies in primary education English language textbooks in the Philippines. Hence, this paper aims to investigate the negotiation of ableist ideologies in primary education English language textbooks in the Philippines. Utilizing Fairclough’s (1995) three-dimensional model of critical discourse analysis (CDA) as the framework, six prescribed primary education English language textbooks from different grade levels were analyzed to examine instances of ableism in the texts. To further support the analysis of the study, supplemental data were gathered from the accounts of six public elementary school English language teachers. Findings reveal that the textbooks contain ableist ideologies with a limited representation of differently-abled people; by disclosing them as (1) invisible, (2) equipped with negative abilities, and (3) plagued with delicate health. By identifying ableist ideologies in textbooks, educational institutions and publishers may benefit in assessing and reforming instructional materials to resolve the presence of such ideologies, thereby abiding by the country’s law on IE and strengthening its overall implementation.

Keywords: textbooks, ideologies, inclusive education, critical discourse analysis, ableism

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Authors: A. Myrzabekova, D. Nurmukhamed, K. Nurumov, A. Zhulbarissova

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It is widely believed that stress can affect teachers’ intention to change the workplace. While existing research primarily focuses on the intrinsic sources of stress stemming from the school climate, the current attempt analyzes educational policies as one of the determinants of teacher’s intention to leave schools. In this respect, Kazakhstan presents a unique case since the country endorsed several educational policies which directly impacted teaching and administrative practices within schools. Using Teaching and Learning International Survey 2018 (TALIS) data with the country specific questionnaire, we construct a statistical measure of stress caused by the implementation of educational policies and test its impact on teacher’s intention to leave through the logistic regression. In addition, we control for sociodemographic, professional, and students related covariates while considering the intrinsic dimension of stress stemming from the school climate. Overall, our results suggest that stress caused by the educational policies has a statistically significant positive effect on teachers’ intentions to transfer between schools. Both policy makers and educational scholars could find these results beneficial. For the former careful planning and addressing the negative effects of the educational policies is critical for the sustainability of the educational process. For the latter, accounting for exogenous sources of stress can lead to a more complete understanding of why teachers decide to change their schools.

Keywords: educational policies, Kazakhstani teachers, logistic regression factor analysis, sustainability education TALIS, teacher turnover intention, work stress

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Authors: Sheillah Hlamalani Mboweni, Lufuno Makhado

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Background: The increasing number of people who tested HIV positive and who demand antiretroviral therapy (ART) prompted the National Department of Health to adopt WHO recommendations of task shifting where Professional Nurses(PNs) initiate ART rather than doctors in the hospital. This resulted in the decentralization of services to primary health care(PHC), generating a need to capacitate PNs on NIMART. After years of training, the impact of NIMART was assessed where it was established that even though there was an increased number who accessed ART, the quality of care is of serious concern. The study aims to answer the following question: What are the challenges influencing NIMART implementation in primary health care. Objectives: This study explores challenges influencing NIMART training and implementation and makes recommendations to improve patient and HIV program outcomes. Methods: A qualitative explorative program evaluation research design. The study was conducted in the rural districts of North West province. Purposive sampling was used to sample PNs trained on NIMART. FGDs were used to collect data with 6-9 participants and data was analysed using ATLAS ti. Results: Five FGDs, n=28 PNs and three program managers were interviewed. The study results revealed two themes: inadequacy in NIMART training and the health care system challenges. Conclusion: The deficiency in NIMART training and health care system challenges is a public health concern as it compromises the quality of HIV management resulting in poor patients’ outcomes and retard the goal of ending the HIV epidemic. These should be dealt with decisively by all stakeholders. Recommendations: The national department of health should improve NIMART training and HIV management: standardization of NIMART training curriculum through the involvement of all relevant stakeholders skilled facilitators, the introduction of pre-service NIMART training in institutions of higher learning, support of PNs by district and program managers, plan on how to deal with the shortage of staff, negative attitude to ensure compliance to guidelines. There is a need to develop a conceptual framework that provides guidance and strengthens NIMART implementation in PHC facilities.

Keywords: antiretroviral therapy, nurse initiated management of retroviral therapy, primary health care, professional nurses

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Authors: Mohamad Ammar Ayass, Natalya Griko, Victor Pashkov, Wanying Cao, Kevin Zhu, Jin Zhang, Lina Abi Mosleh

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Respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent for coronavirus disease 2019 (COVID-19). Early evidence pointed at the angiotensin-converting enzyme 2 (ACE-2) expressed on the epithelial cells of the lung as the main entry point of SARS-CoV-2 into the cells. The viral entry is mediated by the binding of the Receptor Binding Domain (RBD) of the spike protein that is expressed on the surface of the virus to the ACE-2 receptor. As the number of SARS-CoV-2 variants continues to increase, mutations arising in the RBD of SARS-CoV-2 may lead to the ineffectiveness of RBD targeted neutralizing antibodies. To address this limitation, the objective of this study is to develop a combination of aptamers that target different regions of the RBD, preventing the binding of the spike protein to ACE-2 receptor and subsequent viral entry and replication. A safe and innovative biomedical tool was developed to inhibit viral infection and reduce the harms of COVID-19. In the present study, DNA aptamers were developed against a recombinant trimer S protein using the Systematic Evolution of Ligands by Exponential enrichment (SELEX). Negative selection was introduced at round number 7 to select for aptamers that bind specifically to the RBD domain. A series of 9 aptamers (ADI2010, ADI2011, ADI201L, ADI203L, ADI205L, ADIR68, ADIR74, ADIR80, ADIR83) were selected and characterized with high binding affinity and specificity to the RBD of the spike protein. Aptamers (ADI25, ADI2009, ADI203L) were able to bind and pull down endogenous spike protein expressed on the surface of SARS-CoV-2 virus in COVID-19 positive patient samples and determined by liquid chromatography- tandem mass spectrometry analysis (LC-MS/MS). LC-MS/MS data confirmed that aptamers can bind to the RBD of the spike protein. Furthermore, results indicated that the combination of the 9 best aptamers inhibited the binding of the purified trimer spike protein to the ACE-2 receptor found on the surface of Vero E6 cells. In the same experiment, the combined aptamers displayed a better neutralizing effect than antibodies. The data suggests that the selected aptamers could be used in therapy to neutralize the effect of the SARS-CoV-2 virus by inhibiting the interaction between the RBD and ACE-2 receptor, preventing viral entry into target cells and therefore blocking viral replication.

Keywords: aptamer, ACE-2 receptor, binding inhibitor, COVID-19, spike protein, SARS-CoV-2, treatment

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Authors: Graciela Soares Marcelli, Elison Eduardo Jardim Bierhals, Luciane Teresa Salvi, Claudineia Brazil, Rafael Haag

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The sun is a source of renewable energy, and its use as both a source of heat and light is one of the most promising energy alternatives for the future. To measure the thermal or photovoltaic systems a solar irradiation database is necessary. Brazil still has a reduced number of meteorological stations that provide frequency tests, as an alternative to the radio data platform, with reanalysis systems, quite significant. ERA-Interim is a global fire reanalysis by the European Center for Medium-Range Weather Forecasts (ECMWF). The data assimilation system used for the production of ERA-Interim is based on a 2006 version of the IFS (Cy31r2). The system includes a 4-dimensional variable analysis (4D-Var) with a 12-hour analysis window. The spatial resolution of the dataset is approximately 80 km at 60 vertical levels from the surface to 0.1 hPa. This work aims to make a comparative analysis between the ERA-Interim data and the data observed in the Solarimmetric Atlas of the State of Rio Grande do Sul, to verify its applicability in the absence of an observed data network. The analysis of the results obtained for a study region as an alternative to the energy potential of a given region.

Keywords: energy potential, reanalyses, renewable energy, solar radiation

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Authors: Vasantha Gouri Prathapagiri

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Innovations in ICT sector facilitate qualitative life style for citizens across the globe. Countries that facilitate usage of new techniques in ICT, i.e., big data analytics find it easier to fulfil the needs of their citizens. Big data is characterised by its volume, variety, and speed. Analytics involves its processing in a cost effective way in order to draw conclusion for their useful application. Big data also involves into the field of machine learning, artificial intelligence all leading to accuracy in data presentation useful for public policy making. Hence using data analytics in public policy making is a proper way to march towards all round development of any country. The data driven insights can help the government to take important strategic decisions with regard to socio-economic development of her country. Developed nations like UK and USA are already far ahead on the path of digitization with the support of Big Data analytics. India is a huge country and is currently on the path of massive digitization being realised through Digital India Mission. Internet connection per household is on the rise every year. This transforms into a massive data set that has the potential to improvise the public services delivery system into an effective service mechanism for Indian citizens. In fact, when compared to developed nations, this capacity is being underutilized in India. This is particularly true for administrative system in rural areas. The present paper focuses on the need for big data analytics adaptation in Indian rural administration and its contribution towards development of the country on a faster pace. Results of the research focussed on the need for increasing awareness and serious capacity building of the government personnel working for rural development with regard to big data analytics and its utility for development of the country. Multiple public policies are framed and implemented for rural development yet the results are not as effective as they should be. Big data has a major role to play in this context as can assist in improving both policy making and implementation aiming at all round development of the country.

Keywords: Digital India Mission, public service delivery system, public policy, Indian administration

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Authors: Zhala Ahmad, Zainab Lazim, Haider Hamzah

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Bacterial resistance is a pressing global health issue, with multidrug-resistant (MDR), extensively drug-resistant (XDR), and pandrug-resistant (PDR) strains to pose a serious threat. In this context, researchers are investigating effective, safe, and affordable metabolites to combat these pathogens. This study focuses on gum essential oil (GEO) extracted from Pistacia atlantica and its activity and the mechanism of action against XDR Gram-negative Acinetobacter baumannii. GEO was extracted by hydrodistillation and analyzed using GC-MS. Eleven A. baumannii isolates were collected from the ward environment of Burn and Plastic Surgery Hospital in Al Sulaymaniyah City, Iraq. They were identified using the VITEK 2 system, 16S rRNA gene, and confirmed with the blaₒₓₐ₋₅₁ gene; A. baumannii ATCC 19606 was used as a reference strain. The isolates were identified as resistant to twelve different antibiotics spanning six distinct antibiotic classes while showing susceptibility to tetracycline and trimethoprim. Over 40 chemical constituents were detected in the gum's essential oils, with α-pinene being the most abundant. GEO was found to inhibit the growth of A. baumannii isolates; the minimum inhibitory concentration (MIC) of GEO was 2.5 µl/ml. GEO induced protein leakage, phosphate, and potassium ion efflux, distorted cell morphology, and cell death in the tested bacteria. GEO exhibited bacterial clearance and anti-adhesion activity using Band-Aids. This study's findings suggest that GEO could be used as a potential alternative treatment for infectious diseases caused by XRD pathogens, shedding further light on the importance of GEO in biomedical applications. Future studies must focus on generating clinically feasible sources of GEO for testing in small animal models before proceeding to human trials, ensuring safe and effective translation from the laboratory to the clinic.

Keywords: antibiotic resistance, Acinetobacter baumannii, essential oils, Pistacia atlantica, alpha-pinene

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Authors: Mythri G., Manjunath ML, Girish Babu M., Shireen Swaliha Quadri

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Background: The increase in diabetes among the elderly is of concern because in addition to the wide range of traditional diabetes complications, evidence has been growing that diabetes is associated with increased risk of cognitive decline. Aims and Objectives: To find out if there is any association between blood sugar levels and short-term and working memory status in patients of type 2 diabetes. Materials and Methods: The study was carried out in 200 individuals aged between 40-65 years consisting of 100 diagnosed cases of Type 2 Diabetes Mellitus and 100 non-diabetics from OPD of Mc Gann Hospital, Shivamogga. Rye’s Auditory Verbal Learning Test, Verbal Fluency Test and Visual Reproduction Test, Working Digit Span Test and Validation Span Test were used to assess short-term and working memory. Fasting and Post Prandial blood sugar levels were estimated. Statistical analysis was done using SPSS 21. Results: Memory test scores of type 2 diabetics were significantly reduced (p < 0.001) when compared to the memory scores of age and gender matched non-diabetics. Fasting blood sugar levels were found to have a negative correlation with memory scores for all 5 tests: AVLT (r=-0.837), VFT (r=-0.888), VRT(r=-0.787), WDST (r=-0.795) and VST (r=-0.943). Post- Prandial blood sugar levels were found to have a negative correlation with memory scores for all 5 tests: AVLT (r=-0.922), VFT (r=-0.848), VRT(r=-0.707),WDST (r=-0.729) and VST (r=-0.880) Memory scores in all 5 tests were found to be negatively correlated with the FBS and PPBS levels in diabetic patients (p < 0.001). Conclusion: The decreased memory status in diabetic patients may be due to many factors like hyperglycemia, vascular disease, insulin resistance, amyloid deposition and also some of the factor combine to produce additive effects like, type of diabetes, co-morbidities, age of onset, duration of the disease and type of therapy. These observed effects of blood sugar levels of diabetics on memory status are of potential clinical importance because even mild cognitive impairment could interfere with todays’ activities.

Keywords: diabetes, cognition, diabetes, HRV, respiratory medicine

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Authors: K. Sanjayani, C. Saraswathy, S. Sreenivasan, S. Sudhahar, D. Suganya, K. S. Neelukumari, N. Vijayarangan

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Double Base Number System (DBNS) is an imminent system of representing a number using two bases namely 2 and 3, which has its application in Elliptic Curve Cryptography (ECC) and Digital Signature Algorithm (DSA).The previous binary method representation included only base 2. DBNS uses an approximation algorithm namely, Greedy Algorithm. By using this algorithm, the number of digits required to represent a larger number is less when compared to the standard binary method that uses base 2 algorithms. Hence, the computational speed is increased and time being reduced. The standard binary method uses binary digits 0 and 1 to represent a number whereas the DBNS method uses binary digit 1 alone to represent any number (canonical form). The greedy algorithm uses two ways to represent the number, one is by using only the positive summands and the other is by using both positive and negative summands. In this paper, arithmetic operations are used for elliptic curve cryptography. Elliptic curve discrete logarithm problem is the foundation for most of the day to day elliptic curve cryptography. This appears to be a momentous hard slog compared to digital logarithm problem. In elliptic curve digital signature algorithm, the key generation requires 160 bit of data by usage of standard binary representation. Whereas, the number of bits required generating the key can be reduced with the help of double base number representation. In this paper, a new technique is proposed to generate key during encryption and extraction of key in decryption.

Keywords: cryptography, double base number system, elliptic curve cryptography, elliptic curve digital signature algorithm

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Authors: Theresa Steiner, Markus Pajones, Christian Haider

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Traffic is being induced by companies due to their economic behavior. Basically, two different types of traffic occur at company sites: freight traffic and commuting traffic. Due to the fact that these traffic types are connected to each other in different kinds, an integrated approach to manage them is useful. Mobility management is a proved method for companies, to handle the traffic processes caused by their business activities. According to recent trend analysis in Austria, the freight traffic as well as the individual traffic, as part of the commuting traffic, will continue to increase. More traffic jams, as well as negative environmental impacts, are expected impacts for the future. Mobility management is a tool to control the traffic behavior with the scope to reduce emissions and other negative effects which are caused by traffic. Until now, mobility management is mainly used for optimizing commuting traffic without taking the freight logistics processes into consideration. However, the method of mobility management can be used to improve the freight traffic area of a company as well. The focus of this paper will be particularly laid on analyzing to what extent companies are already using mobility management to influence not only the commuting traffic they produce but also their processes of freight logistics. A further objective is to acquire knowledge about the motivating factors which persuade companies to introduce and apply mobility management. Additionally, advantages and disadvantages of this tool will be defined as well as limitations and factors of success, with a special focus on freight logistics, will be depicted. The first step of this paper is to conduct a literature review on the issue of mobility management with a special focus on freight logistics processes. To compare the theoretical findings with the practice, interviews, following a structured interview guidline, with mobility managers of different companies in Upper Austria will be undertaken. A qualitative analysis of these surveys will in a first step show the motivation behind using mobility management to improve traffic processes and how far this approach is already being used to especially influence the freight traffic of the companies. An evaluation to what extent the method of mobility management is already being approached at Upper Austrian companies to regulate freight logistics processes will be one outcome of this publication. Furthermore, the results of the theoretical and practical analysis will reveal not only the possibilities but also the limitations of using mobility management to influence the processes of freight logistics.

Keywords: freight logistics processes, freight traffic, mobility management, passenger traffic

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Authors: Umego Chukwudi T., Ntui Valentine O., Uyoh Edak A.

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Phosphorus (P) deficiency has been identified as a major hindrance to rice production the world over. Eleven (11) rice genotypes predominantly used by local farmers in Nigeria were studied for their responses to P deficient conditions. The characterization was based on morpho-physiologic parameters. The genotypes were screened using a hydroponic system in a modified Hoagland’s solution. Morphological and physiologic parameters, including Plant height (PH), number of tillers per plant, shoot dry weight (SDW), shoot phosphate concentration (SPC), and chlorophyll content, were recorded after exposure to three levels of phosphate concentration (0µM, 400 µM, and 800 µM). The data obtained were subjected to analysis of variance (ANOVA), and the means were separated using least significance difference tests. The results obtained showed that P starvation caused a significant (p≤0.05) reduction in PH, SDW, and tillering and also triggered a significant (p≤0.05) increase in root length among the genotypes. The Pearsons correlation coefficient was used to estimate the relationships among studied parameters, and a significant negative correlation was observed between plant height and root length. FARO63 was identified as a highly tolerant genotype to P deficiency with a low (0.24) SPC and higher (4.81) phosphate utilization efficiency (PUE). This study has identified FARO63 as a true tolerant genotype to Phosphate deficiency, which will be useful in breeding for phosphate deficiency tolerance in rice and thus combating food insecurity.

Keywords: phosphate deficiency, rice genotypes, hydroponic system, food security

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Authors: Ahmed Rashad Harb Riad Ismail

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The purpose of this research is to study the potential of Dynamic Pricing if deployed by mobile operators and analyse its effects from both operators and consumers side. Furthermore, to conclude, throughout the research study, the recommended conditions for successful Dynamic Pricing deployment, recommended factors identifying the type of markets where Dynamic Pricing can be effective, and proposal for a Dynamic Pricing stakeholders’ framework were presented. Currently, the mobile telecommunications industry is witnessing a dramatic growth rate in the data consumption, being fostered mainly by higher data speed technology as the 4G LTE and by the smart devices penetration rates. However, operators’ revenue from data services lags behind and is decupled from this data consumption growth. Pricing strategy is a key factor affecting this ecosystem. Since the introduction of the 4G LTE technology will increase the pace of data growth in multiples, consequently, if pricing strategies remain constant, then the revenue and usage gap will grow wider, risking the sustainability of the ecosystem. Therefore, this research study is focused on Dynamic Pricing for 4G LTE data services, researching the drivers, benefits and challenges of 4G LTE Dynamic Pricing and the feasibility of its deployment in practice from different perspectives including operators, regulators, consumers, and telecommunications equipment manufacturers point of views.

Keywords: LTE, dynamic pricing, EPC, research

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Authors: S. Adjiri-Bailiche, S. M. Boudia, H. Daaou, S. Hadouche, A. Benzaoui

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In this work the study of changes in the wind speed depending on the altitude is calculated and described by the model of the neural networks, the use of measured data, the speed and direction of wind, temperature and the humidity at 10 m are used as input data and as data targets at 50m above sea level. Comparing predict wind speeds and extrapolated at 50 m above sea level is performed. The results show that the prediction by the method of artificial neural networks is very accurate.

Keywords: MATLAB, neural network, power low, vertical extrapolation, wind energy, wind speed

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Authors: Ahmad Badawi Saluy, Novawiguna Kemalasari

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This study aims to examine, analyze and explain the impacts of compensation, career development and employee engagement to employee’s performance partially and simultaneously (Case Study at PT Bank XYZ). The research design used is quantitative descriptive research causality involving 30 respondents. Sources of data are from primary and secondary data, primary data obtained from questionnaires distribution and secondary data obtained from journals and books. Data analysis used model test using smart application PLS 3 that consists of test outer model and inner model. The results showed that compensation, career development and employee engagement partially have a positive impact on employee performance, while they have a positive and significant impact on employee performance simultaneously. The independent variable has the greatest impact is the employee engagement.

Keywords: compensation, career development, employee engagement, employee performance

Procedia PDF Downloads 147

Authors: C. Miranda, R. Soares, S. Cunha, L. Ferreira, G. Igrejas, P. Poeta

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Different animal species, including ornamental animals, are reported as potential reservoirs of antibiotic resistance genes. Consequently, these resistances can be disseminated in the environment and transferred to humans. Moreover, multidrug-resistant bacteria reduce the efficacy of antibiotics, as the case of vancomycin-resistant enterococci. Enterococcus faecalis and E. faecium are described as the main nosocomial pathogens. In this line, the aim of this study was to characterize resistance and virulence genes of enterococci species isolated from samples of food supplied to ornamental animals during 2020. The 29 enterococci isolates (10 E. faecalis and 19 E. faecium) were tested for the presence of the resistance genes for the following antibiotics: erythromicyn (ermA, ermB and ermC), tetracycline (tetL, tetM, tetK and tetO), quinupristin/dalfopristin (vatD and vatE), gentamicin (aac(6’)-aph(2’’)-Ia), chloramphenicol (catA), streptomycin (ant(6)-Ia) and vancomycin (vanA and vanB). The same isolates were also tested for 10 virulence factors genes (esp, ace, gelE, agg, fsr, cpd, cylA, cylB, cylM and cylLL). The resistance and virulence genes were performed by PCR, using specific primers and conditions. Negative and positive controls were used in all PCR assays. The most prevalent resistance genes detected in both enterococci species were ermB (n=15, 52%), ermC (n=7, 24%), tetK (n=8, 28%) and vatE (n=4, 14%). Resistance genes for vancomycin were found in ten (34%) E. faecalis and ten (34%) E. faecium isolates. Only E. faecium isolates showed the presence of ermA (n=2, 7%), tetL (n=13, 45%) and ant(6)-Ia gene (n=4, 14%). A total of nine (31%) enterococci isolates were classified as multidrug-resistant bacteria (3 E. faecalis and 6 E. faecium). In three E. faecalis and one E. faecium were not detected resistance genes. The virulence genes detected in both species were agg (n=6, 21%) and cylLL (n=11, 38%). In general, each isolate showed only one of these virulence genes. Five E. faecalis and eleven E. faecium isolates were negative for all analyzed virulence genes. These preliminary results showed the presence of multidrug-resistant enterococci in food supplied to ornamental animals, in particular vancomycin-resistant enterococci. This genotypic characterization reinforces the relevance to public health in the control of antibiotic-resistant bacteria.

Keywords: antibiotic resistance, enterococci, feed, ornamental animals

Procedia PDF Downloads 193

Authors: Thomas L. McCullough, John D. Hague, Marylesa M. Howard, Matthew K. Kiser, Michael A. Mazur, Lance K. McLean, Johanna L. Turk

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Radiological search and mapping depends on the successful recognition of anomalies in large data sets which contain varied and dynamic backgrounds. We present a new algorithmic approach for real-time anomaly detection which is resistant to common detector imperfections, avoids the limitations of a source template library and provides immediate, and easily interpretable, user feedback. This algorithm is based on a continuous wavelet transform for variance reduction and evaluates the deviation between a foreground measurement and a local background expectation using methods from linear algebra. We also present a technique for recognizing and visualizing spectrally similar clusters of data. This technique uses Laplacian Eigenmap Manifold Learning to perform dimensional reduction which preserves the geometric "closeness" of the data while maintaining sensitivity to outlying data. We illustrate the utility of both techniques on real-world data sets.

Keywords: radiological search, radiological mapping, radioactivity, radiation protection

Procedia PDF Downloads 688

Authors: Rhaed Khiati, Muhammad Hanif

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In the past decade, smart healthcare systems have been on an ascendant drift, especially with the evolution of hospitals and their increasing reliance on bioinformatics and software specializing in healthcare. Doctors have become reliant on technology more than ever, something that in the past would have been looked down upon, as technology has become imperative in reducing overall costs and improving the quality of patient care. With patient-doctor interactions becoming more necessary and more complicated than ever, systems must be developed while taking into account costs, patient comfort, and patient data, among other things. In this work, we proposed a smart hospital bed, which mixes the complexity and big data usage of traditional healthcare systems with the comfort found in soft beds while taking certain concerns like data confidentiality, security, and maintaining SLA agreements, etc. into account. This research work potentially provides users, namely patients and doctors, with a seamless interaction with to their respective nurses, as well as faster access to up-to-date personal data, including prescriptions and severity of the condition in contrast to the previous research in the area where there is lack of consideration of such provisions.

Keywords: big data, smart healthcare, distributed systems, bioinformatics

Procedia PDF Downloads 194