Search results for: hybrid memory

Authors: Kennedy Zinn, Chris Anderson

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Chronic Covid syndrome (CCS) is a condition in which individuals who test positive for Covid-19 experience persistent symptoms after recovering from the virus. CCS affects every organ system, including the central nervous system. Neurological “long-haul” symptoms last from a few weeks to several months and include brain fog, chronic fatigue, dyspnea, mood dysregulation, and headaches. Data suggest that 10-30% of individuals testing positive for Covid-19 develop CCS. Current literature indicates a decreased quality of life in persistent symptoms. CCS is a pervasive and pernicious COVID-19 sequelae. More research is needed to understand risk factors, impact, and possible interventions. Research frequently cites cytokine storming as noteworthy etiology in CCS. Cytokine storming is a malfunctional immune response and facilitates multidimensional interconnected physiological responses. The most prominent responses include abnormal blood flow, hypoxia/hypoxemia, inflammation, and endothelial damage. Neurological impairments and pathogenesis in CCS parallel that of traumatic brain injury (TBI). Both exhibit impairments in memory, cognition, mood, sustained attention, and chronic fatigue. Evidence suggests abnormal blood flow, inflammation, and hypoxemia as shared causal factors. Cytokine storming is also typical in mTBI. The shared characteristics in symptoms and etiology suggest potential parallel routes of investigation that allow for better understanding of CCS. Research on the effect of altitude in mTBI varies. Literature finds decreased rates of concussions at higher altitudes. Other studies suggest that at a higher altitude, pre-existing mTBI symptoms are exacerbated. This may mean that in CCS, the geographical location where individuals live and the location where individuals experienced acute Covid-19 symptoms may influence the severity and risk of developing CCS. It also suggests that clinics which treat mTBI patients could also provide benefits for those with CCS. This study aims to examine the relationships between altitude and CCS as a risk factor and investigate the longevity and severity of symptoms in different altitudes. Existing patient data from a concussion clinic using fMRI scans and self-reported symptoms will be used for approximately 30 individuals with CCS symptoms. The association between acclimated altitude and CCS severity will be analyzed. Patients will be classified into low, medium, and high altitude groups and compared for differences on fMRI severity scores and self-reported measures. It is anticipated that individuals living in lower altitudes are at higher risk of developing more severe neuropsychological symptoms in CCS. It is also anticipated that a treatment approach for mTBI will also be beneficial to those with CCS.

Keywords: altitude, chronic covid syndrome, concussion, covid brain, EPIC treatment, fMRI, traumatic brain injury

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Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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Authors: Lesley Northrop, Justin DeGrazia, Jessica Greenwood

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ASPIRA Labs now offers an en-suit and ready-to-implement technology transfer solution to enable labs and hospitals that lack the resources to build it themselves to offer in-house genetic testing. This unique platform employs a patented Molecular Inversion Probe (MIP) technology that combines the specificity of a hybrid capture protocol with the ease of an amplicon-based protocol and utilizes an advanced bioinformatics analysis pipeline based on machine learning. To demonstrate its efficacy, two independent genetic tests were validated on this technology transfer platform: expanded carrier screening (ECS) and hereditary cancer testing (HC). The analytical performance of ECS and HC was validated separately in a blinded manner for calling three different types of variants: SNVs, short indels (typically, <50 bp), and large indels/CNVs defined as multi-exonic del/dup events. The reference set was constructed using samples from Coriell Institute, an external clinical genetic testing laboratory, Maine Molecular Quality Controls Inc. (MMQCI), SeraCare and GIAB Consortium. Overall, the analytical performance showed a sensitivity and specificity of >99.4% for both ECS and HC in detecting SNVs. For indels, both tests reported specificity of 100%, and ECS demonstrated a sensitivity of 100%, whereas HC exhibited a sensitivity of 96.5%. The bioinformatics pipeline also correctly called all reference CNV events resulting in a sensitivity of 100% for both tests. No additional calls were made in the HC panel, leading to a perfect performance (specificity and F-measure of 100%). In the carrier panel, however, three additional positive calls were made outside the reference set. Two of these calls were confirmed using an orthogonal method and were re-classified as true positives leaving only one false positive. The pipeline also correctly identified all challenging carrier statuses, such as positive cases for spinal muscular atrophy and alpha-thalassemia, resulting in 100% sensitivity. After confirmation of additional positive calls via long-range PCR and MLPA, specificity for such cases was estimated at 99%. These performance metrics demonstrate that this tech-transfer solution can be confidently internalized by clinical labs and hospitals to offer mainstream ECS and HC as part of their test catalog, substantially increasing access to quality germline genetic testing for labs of all sizes and resources levels.

Keywords: clinical genetics, genetic testing, molecular genetics, technology transfer

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Authors: Hiromi Kawasaki, Satoko Yamasaki, Mika Iwasa, Tomoko Iki, Akiko Takaki

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In basic nursing, the conditions necessary for maintaining human health -temperature, humidity, illumination, distance from others, noise, moisture, meals, and excretion- were explained. Nursing students often think of these conditions in the context of a hospital room. In order to make students think of these conditions in terms of an environment necessary for maintaining health and preventing illness for residents, in the third year of community health nursing, students learned how to assess and improve the environment -particularly via the case of shelters in the event of a disaster. The importance of environmental management has increased in 2020 as a preventive measure against COVID-19 infection. We verified the effect of the lessons, which was decided to be conducted through distance learning. Sixty third-year nursing college students consented to participate in this study. Environmental standard knowledge for conducting environmental assessment was examined before and after class, and the percentage of correct answers was compared. The χ² test was used for the test, with a 5% significance level employed. Measures were evaluated via a report submitted by the students after class. Student descriptions were analyzed both qualitatively and descriptively with respect to expected health problems and suggestions for improvement. Students have already learned about the environment in terms of basic nursing in their second year. The correct answers for external environmental values concerning interpersonal distance, illumination, noise, and room temperature (p < 0.001) increased significantly after taking the class. Humidity was registered 83.3% before class and 93.3% after class (p = 0.077). Regarding the body, the percentage of students who answered correctly was 70% or more, both before and after the class. The students’ reports included overcrowding, high humidity/high temperature, and the number of toilets as health hazards. Health disorders to be prevented were heat stroke, infectious diseases, and economy class syndrome; improvement methods were recommended for hyperventilation, stretching, hydration, and waiting at home. After the public health nursing class, the students were able to not only propose environmental management of a hospital room but also had an understanding of the environment in terms of the lives of individuals, environmental assessment, and solutions to health problems. The response rate for basic items learned in the second year was already high before and after class, and interpersonal distance and ventilation were described by students. Students were able to use what they learned in basic nursing about the standards of the human mind and body. In the external environment, the memory of specific numerical values was ambiguous. The environment of the hospital room is controlled, and interest in numerical values may decrease. Nursing staff needs to maintain and improve human health as well as hospital rooms. With COVID-19, it was thought that students would continue to not only consider this point in reference to hospital rooms but also in regard to places where people gather. Even in distance learning, students were able to learn the important issues and lessons.

Keywords: environmental assessment, evacuation center, nursing education, nursing students

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Authors: Shivani, Seema Sharma, Shveta Singh, Akriti Chandra

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Business activities contribute to various environmental issues such as deforestation, waste generation, and pollution. Therefore, integration of environmental concerns within manufacturing operations is vital for the long-term survival of businesses. In this context, green entrepreneurial orientation (GEO) is recognized as a firm-level internal strategy to mitigate ecological damage through initiating green business practices. However, despite the surge in research on GEO in recent years, ambiguity remains on the genesis of GEO and the mechanism through which GEO impacts various organizational outcomes. This prompts an examination of the ongoing scholarly discourse about GEO and its domain knowledge structure within the entrepreneurship literature using bibliometric analysis and the Theories, Contexts, Characteristics, and Methodologies (TCCM) framework. The authors analyzed a dataset comprising 73 scientific documents sourced from the Scopus and Web of Science database from 2005 to 2024 to provide insights into the publication trends, prominent journals, authors, articles, countries' collaboration, and keyword analysis in GEO research. The findings indicate that the number of relevant papers and citations has increased consistently, with authors from China being the main contributors. The articles are mainly published in Business Strategy and the Environment and Sustainability. Dynamic capability view is the dominant framework applied in the GEO domain, with large manufacturing firms and SMEs constituting the majority of the sample. Further, various antecedents of GEO have been identified at an organizational level to which managers can focus their attention. The studies have used various contextual factors to explain when GEO translates into superior organizational outcomes. The Method analysis reveals that PLS-SEM is the commonly used approach for analyzing the primary data collected through surveys. Moreover, the content analysis indicates four emerging research frontiers identified as unidimensional vs. multidimensional perspectives of GEO, typologies of green innovation, environmental management in the hospitality industry, and tech-savvy sustainability in the agriculture sector. This study is one of the earliest to apply quantitative methods to synthesize the extant literature on GEO. This research holds relevance for management practice due to the escalating levels of carbon emissions, energy consumption, and waste discharges observed in recent years, resulting in increased apprehension about climate change.

Keywords: green entrepreneurship, sustainability, SLR, TCCM

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Authors: Chien-Ho Lin, Ho-Ching Yang, Barbara Knowlton, Shin-Leh Huang, Ming-Chang Chiang

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Practicing motor tasks arranged in an interleaved order (interleaved practice, or IP) generally leads to better learning than practicing tasks in a repetitive order (repetitive practice, or RP), an example of how desirable difficulty during practice benefits learning. Greater difficulty during practice, e.g. IP, is associated with greater brain activity measured by higher blood-oxygen-level dependent (BOLD) signal in functional magnetic resonance imaging (fMRI) in the sensorimotor areas of the brain. In this study resting-state fMRI was applied to investigate whether increase in resting-state brain connectivity immediately after practice predicts the benefit of desirable difficulty to motor learning. 26 healthy adults (11M/15F, age = 23.3±1.3 years) practiced two sets of three sequences arranged in a repetitive or an interleaved order over 2 days, followed by a retention test on Day 5 to evaluate learning. On each practice day, fMRI data were acquired in a resting state after practice. The resting-state fMRI data was decomposed using a group-level spatial independent component analysis (ICA), yielding 9 independent components (IC) matched to the precuneus network, primary visual networks (two ICs, denoted by I and II respectively), sensorimotor networks (two ICs, denoted by I and II respectively), the right and the left frontoparietal networks, occipito-temporal network, and the frontal network. A weighted resting-state functional connectivity (wRSFC) was then defined to incorporate information from within- and between-network brain connectivity. The within-network functional connectivity between a voxel and an IC was gauged by a z-score derived from the Fisher transformation of the IC map. The between-network connectivity was derived from the cross-correlation of time courses across all possible pairs of ICs, leading to a symmetric nc x nc matrix of cross-correlation coefficients, denoted by C = (pᵢⱼ). Here pᵢⱼ is the extremum of cross-correlation between ICs i and j; nc = 9 is the number of ICs. This component-wise cross-correlation matrix C was then projected to the voxel space, with the weights for each voxel set to the z-score that represents the above within-network functional connectivity. The wRSFC map incorporates the global characteristics of brain networks measured by the between-network connectivity, and the spatial information contained in the IC maps measured by the within-network connectivity. Pearson correlation analysis revealed that greater IP-minus-RP difference in wRSFC was positively correlated with the RP-minus-IP difference in the response time on Day 5, particularly in brain regions crucial for motor learning, such as the right dorsolateral prefrontal cortex (DLPFC), and the right premotor and supplementary motor cortices. This indicates that enhanced resting brain connectivity during the early phase of memory consolidation is associated with enhanced learning following interleaved practice, and as such wRSFC could be applied as a biomarker that measures the beneficial effects of desirable difficulty on motor sequence learning.

Keywords: desirable difficulty, functional magnetic resonance imaging, independent component analysis, resting-state networks

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Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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Authors: Katharina Kargel, Frederic Vobbe

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Sexual online grooming is generally defined as digital interactions for the purpose of sexual exploitation of children or minors, i.e. as a process for preparing and framing sexual child abuse. Due to its conceptual history, sexual online grooming is often associated with perpetrators who are previously unknown to those affected. While the strategies of perpetrators and the perception of those affected are increasingly being investigated, the instrumentalisation of digital media has not yet been researched much. Therefore, the present paper aims at contributing to this research gap by examining in what kind of ways perpetrators instrumentalise digital media. Our analyses draw on 46 case documentations and 18 interviews with those affected. The cases and the partly narrative interviews were collected by ten cooperating specialist centers working on sexualized violence in childhood and youth. For this purpose, we designed a documentation grid allowing for a detailed case reconstruction i.e. including information on the violence, digital media use and those affected. By using Reflexive Grounded Theory, our analyses emphasize a) the subjective benchmark of professional practitioners as well as those affected and b) the interpretative implications resulting from our researchers’ subjective and emotional interaction with the data material. It should first be noted that sexualized online grooming can result in both online and offline sexualized violence as well as hybrid forms. Furthermore, the perpetrators either come from the immediate social environment of those affected or are unknown to them. The perpetrator-victim relationship plays a more important role with regard to the question of the instrumentalisation of digital media than the question of the space (on vs. off) in which the primary violence is committed. Perpetrators unknown to those affected instrumentalise digital media primarily to establish a sexualized system of norms, which is usually embedded in a supposed love relationship. In some cases, after an initial exchange of sexualized images or video recordings, a latent play on the position of power takes place. In the course of the grooming process, perpetrators from the immediate social environment increasingly instrumentalise digital media to establish an explicit relationship of power and dependence, which is directly determined by coercion, threats and blackmail. The knowledge of possible vulnerabilities is strategically used in the course of maintaining contact. The above explanations lead to the conclusion that the motive for the crime plays an essential role in the question of the instrumentalisation of digital media. It is therefore not surprising that it is mostly the near-field perpetrators without commercial motives who initiate a spiral of violence and stress by digitally distributing sexualized (violent) images and video recordings within the reference system of those affected.

Keywords: sexualized violence, children and youth, grooming, offender strategies, digital media

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Authors: Takoua Soltani, Imen Soltani, Taoufik Aguili

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The communications' and radar systems' demands give rise to new developments in the domain of active integrated antennas (AIA) and arrays. The main advantages of AIA arrays are the simplicity of fabrication, low cost of manufacturing, and the combination between free space power and the scanner without a phase shifter. The integrated active antenna modeling is the coupling between the electromagnetic model and the transport model that will be affected in the high frequencies. Global modeling of active circuits is important for simulating EM coupling, interaction between active devices and the EM waves, and the effects of EM radiation on active and passive components. The current review focuses on the modeling of the active element which is a MESFET transistor immersed in a rectangular waveguide. The proposed EM analysis is based on the Method of Moments combined with the Generalised Equivalent Circuit method (MOM-GEC). The Method of Moments which is the most common and powerful software as numerical techniques have been used in resolving the electromagnetic problems. In the class of numerical techniques, MOM is the dominant technique in solving of Maxwell and Transport’s integral equations for an active integrated antenna. In this situation, the equivalent circuit is introduced to the development of an integral method formulation based on the transposition of field problems in a Generalised equivalent circuit that is simpler to treat. The method of Generalised Equivalent Circuit (MGEC) was suggested in order to represent integral equations circuits that describe the unknown electromagnetic boundary conditions. The equivalent circuit presents a true electric image of the studied structures for describing the discontinuity and its environment. The aim of our developed method is to investigate the antenna parameters such as the input impedance and the current density distribution and the electric field distribution. In this work, we propose a global EM modeling of the MESFET AsGa transistor using an integral method. We will begin by describing the modeling structure that allows defining an equivalent EM scheme translating the electromagnetic equations considered. Secondly, the projection of these equations on common-type test functions leads to a linear matrix equation where the unknown variable represents the amplitudes of the current density. Solving this equation resulted in providing the input impedance, the distribution of the current density and the electric field distribution. From electromagnetic calculations, we were able to present the convergence of input impedance for different test function number as a function of the guide mode numbers. This paper presents a pilot study to find the answer to map out the variation of the existing current evaluated by the MOM-GEC. The essential improvement of our method is reducing computing time and memory requirements in order to provide a sufficient global model of the MESFET transistor.

Keywords: active integrated antenna, current density, input impedance, MESFET transistor, MOM-GEC method

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Authors: Neoclis Hadjigeorgiou, Spyridon Angelopoulos, Evangelos V. Hristoforou, Paul P. Sotiriadis

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The increasing demand for accurate and reliable magnetic measurements over the past decades has paved the way for the development of different types of magnetic sensing systems as well as of more advanced measurement techniques. Anisotropic Magneto Resistance (AMR) sensors have emerged as a promising solution for applications requiring high resolution, providing an ideal balance between performance and cost. However, certain issues of AMR sensors such as non-linear response and measurement noise are rarely discussed in the relevant literature. In this work, an analog closed loop compensation system is proposed, developed and tested as a means to eliminate the non-linearity of AMR response, reduce the 1/f noise and enhance the sensitivity of magnetic sensor. Additional performance aspects, such as cross-axis and hysteresis effects are also examined. This system was analyzed using an analytical model and a P-Spice model, considering both the sensor itself as well as the accompanying electronic circuitry. In addition, a commercial closed loop architecture Flux-Gate sensor (calibrated and certified), has been used for comparison purposes. Three different experimental setups have been constructed for the purposes of this work, each one utilized for DC magnetic field measurements, AC magnetic field measurements and Noise density measurements respectively. The DC magnetic field measurements have been conducted in laboratory environment employing a cubic Helmholtz coil setup in order to calibrate and characterize the system under consideration. A high-accuracy DC power supply has been used for providing the operating current to the Helmholtz coils. The results were recorded by a multichannel voltmeter The AC magnetic field measurements have been conducted in laboratory environment employing a cubic Helmholtz coil setup in order to examine the effective bandwidth not only of the proposed system but also for the Flux-Gate sensor. A voltage controlled current source driven by a function generator has been utilized for the Helmholtz coil excitation. The result was observed by the oscilloscope. The third experimental apparatus incorporated an AC magnetic shielding construction composed of several layers of electric steel that had been demagnetized prior to the experimental process. Each sensor was placed alone and the response was captured by the oscilloscope. The preliminary experimental results indicate that closed loop AMR response presented a maximum deviation of 0.36% with respect to the ideal linear response, while the corresponding values for the open loop AMR system and the Fluxgate sensor reached 2% and 0.01% respectively. Moreover, the noise density of the proposed close loop AMR sensor system remained almost as low as the noise density of the AMR sensor itself, yet considerably higher than that of the Flux-Gate sensor. All relevant numerical data are presented in the paper.

Keywords: AMR sensor, chopper, closed loop, electronic noise, magnetic noise, memory effects, flux-gate sensor, linearity improvement, sensitivity improvement

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Authors: Weiliang Gong, Lissa Gomes, Lucile Raymond, Hui Xu, Werner Lutze, Ian L. Pegg

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Alkali-activated materials, particularly geopolymers, have attracted much interest in academia. Commercial applications are on the rise, as well. Geopolymers are produced typically by a reaction of one or two aluminosilicates with an alkaline solution at room temperature. Fly ash is an important aluminosilicate source. However, using low-Ca fly ash, the byproduct of burning hard or black coal reacts and sets slowly at room temperature. The development of mechanical durability, e.g., compressive strength, is slow as well. The use of fly ashes with relatively high contents ( > 6%) of unburned carbon, i.e., high loss on ignition (LOI), is particularly disadvantageous as well. This paper will show to what extent these impediments can be mitigated by mixing the fly ash with one or two more aluminosilicate sources. The fly ash used here is generated at the Orlando power plant (Florida, USA). It is low in Ca ( < 1.5% CaO) and has a high LOI of > 6%. The additional aluminosilicate sources are metakaolin and blast furnace slag. Binary fly ash-metakaolin and ternary fly ash-metakaolin-slag geopolymers were prepared. Properties of geopolymer pastes before and after setting have been measured. Fresh mixtures of aluminosilicates with an alkaline solution were studied by Vicat needle penetration, rheology, and isothermal calorimetry up to initial setting and beyond. The hardened geopolymers were investigated by SEM/EDS and the compressive strength was measured. Initial setting (fluid to solid transition) was indicated by a rapid increase in yield stress and plastic viscosity. The rheological times of setting were always smaller than the Vicat times of setting. Both times of setting decreased with increasing replacement of fly ash with blast furnace slag in a ternary fly ash-metakaolin-slag geopolymer system. As expected, setting with only Orlando fly ash was the slowest. Replacing 20% fly ash with metakaolin shortened the set time. Replacing increasing fractions of fly ash in the binary system by blast furnace slag (up to 30%) shortened the time of setting even further. The 28-day compressive strength increased drastically from < 20 MPa to 90 MPa. The most interesting finding relates to the calorimetric measurements. The use of two or three aluminosilicates generated significantly more heat (20 to 65%) than the calculated from the weighted sum of the individual aluminosilicates. This synergetic heat contributes or may be responsible for most of the increase of compressive strength of our binary and ternary geopolymers. The synergetic heat effect may be also related to increased incorporation of calcium in sodium aluminosilicate hydrate to form a hybrid (N,C)A-S-H) gel. The time of setting will be correlated with heat release and maximum heat flow.

Keywords: alkali-activated materials, binary and ternary geopolymers, blends of fly ash, metakaolin and blast furnace slag, rheology, synergetic heats

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Authors: Linette van der Merwe

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It is known that visual artists, performing artists, and literary artists have inspired each other since time immemorial. The enduring, symbiotic relationship between the various art genres is evident where words, colours, lines, and sounds act as metaphors, a physical separation of the transcendental reality of art. Simonides of Keos (c. 556-468 BC) confirmed this, stating that a poem is a talking picture, or, in a more modern expression, a picture is worth a thousand words. It can be seen as an ancient relationship, originating from the epigram (tombstone or artefact inscriptions), the carmen figuratum (figure poem), and the ekphrasis (a description in the form of a poem of a work of art). Visual artists, including Michelangelo, Leonardo da Vinci, and Goethe, wrote poems and songs. Goya, Degas, and Picasso are famous for their works of art and for trying their hands at poetry. Afrikaans writers whose fine art is often published together with their writing, as in the case of Andries Bezuidenhout, Breyten Breytenbach, Sheila Cussons, Hennie Meyer, Carina Stander, and Johan van Wyk, among others, are not a strange phenomenon either. Imitating one art form into another art form is a form of translation, transposition, contemplation, and discovery of artistic impressions, showing parallel interpretations rather than physical comparison. It is especially about the harmony that exists between the different art genres, i.e., a poem that describes a painting or a visual text that portrays a poem that becomes a translation, interpretation, and rediscovery of the verbal text, or rather, from the word text to the image text. Poetry-film, as a form of such a translation of the word text into an image text, can be considered a hybrid, transdisciplinary art form that connects poetry and film. Poetry-film is regarded as an intertwined entity of word, sound, and visual image. It is an attempt to transpose and transform a poem into a new artwork that makes the poem more accessible to people who are not necessarily open to the written word and will, in effect, attract a larger audience to a genre that usually has a limited market. Poetry-film is considered a creative expression of an inverted ekphrastic inspiration, a visual description, interpretation, and expression of a poem. Research also emphasises that animated poetry-film is not widely regarded as a genre of anything and is thus severely under-theorized. This paper will focus on Afrikaans animated poetry-films as a multimodal transposition of a poem text to an animated poetry film, with specific reference to animated poetry-films in Filmverse I (2014) and Filmverse II (2016).

Keywords: poetry film, animated poetry film, poetic metaphor, conceptual metaphor, monomodal metaphor, multimodal metaphor, semiotic metaphor, multimodality, metaphor analysis, target domain, source domain

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Authors: Maria Ulfa, Nur Awaliyah Putri

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Madurese is known as Malayo-Sumbawan Austronesian language which is used by Madurese people in Madura Island, Indonesia. However, there was a massive migration of Madurese people due to Dutch colonization. The Madurese people were brought by force for cultivation system to the eastern salient north coast or called as Tapal Kuda that spread in region covers the regencies of Probolinggo, Lumajang, Jember, Situbondo, Bondowoso, and Banyuwangi, the eastern part of the Pasuruan Regency, as well as the city of Probolinggo. The city of Probolinggo has unique characteristic regarding the ethnic and language variation. Several ethnics can be found in this city, such as Madurese, Javanese, Tengger, Arabic, Mandhalungan, Osing, and Chinese. Hence, the hybrid culture happens in Probolinggo, they called the culture as Pendhalungan which is the combination of culture among Madurese and Javanese. Among those ethnics, Madurese is the strongest ethnic that still maintains their identity, such as their ethnic language. The massive growth of Madurese in Probolinggo city, East Java is interesting to be analyzed. The object of this study is to discover language ideology and literacy of Madurese to maintain their ethnic language in Probolinggo city, East Java. The researchers used the theory of language maintenance practice based on three types of practices social language, social literacy, and peripheral ritualized practices. The approach of this study was qualitative research with ethnography method. In order to collect the data, researchers used observation and interview techniques. The amount of informants were 20 families which consist of mother, father and children in 5 sub-districts in Probolinggo city and they were interviewed regarding language ideology and literacy of Madurese. In supporting the data, researchers employed the Madurese speakers outside family scope like in school, office, and market. The result of the study revealed that Madurese has been preserved heritably to young generations by ethnics of Madura in Probolinggo city. Primarily the language is being taught in the earlier age of their children as L1 and used as ethnic identity. The parents teach them with simple sentences that grammatically correct. This language literacy is applied to maintain ethnic language as their ethnicity marker since they inhabit in Javanese ethnic area. In fact, it is not the only ideology of Madurese ethnic but also the influence of economic situation like in trading communication. The usage of Madurese in the trading scope is very beneficial since people can bargain the goods cheaper and easier because most of the traders are from Madurese ethnic. In this situation, linguistic phenomena such as code mixing and code switching between Madurese and Javanese are emerged as the trading communication. From the result, it can be concluded that solidarity exists among Madurese people in many scopes.

Keywords: language literacy, language maintenance, Madurese, Probolinggo City

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Authors: Francesca Schiavello

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This work aims to create a hybrid algorithm, combining Quantum Approximate Optimization Algorithm (QAOA) with an Evolutionary Algorithm (EA) in the place of traditional gradient based optimization processes. QAOA’s were first introduced in 2014, where, at the time, their algorithm performed better than the traditional best known classical algorithm for Max-cut graphs. Whilst classical algorithms have improved since then and have returned to being faster and more efficient, this was a huge milestone for quantum computing, and their work is often used as a benchmarking tool and a foundational tool to explore variants of QAOA’s. This, alongside with other famous algorithms like Grover’s or Shor’s, highlights to the world the potential that quantum computing holds. It also presents the reality of a real quantum advantage where, if the hardware continues to improve, this could constitute a revolutionary era. Given that the hardware is not there yet, many scientists are working on the software side of things in the hopes of future progress. Some of the major limitations holding back quantum computing are the quality of qubits and the noisy interference they generate in creating solutions, the barren plateaus that effectively hinder the optimization search in the latent space, and the availability of number of qubits limiting the scale of the problem that can be solved. These three issues are intertwined and are part of the motivation for using EAs in this work. Firstly, EAs are not based on gradient or linear optimization methods for the search in the latent space, and because of their freedom from gradients, they should suffer less from barren plateaus. Secondly, given that this algorithm performs a search in the solution space through a population of solutions, it can also be parallelized to speed up the search and optimization problem. The evaluation of the cost function, like in many other algorithms, is notoriously slow, and the ability to parallelize it can drastically improve the competitiveness of QAOA’s with respect to purely classical algorithms. Thirdly, because of the nature and structure of EA’s, solutions can be carried forward in time, making them more robust to noise and uncertainty. Preliminary results show that the EA algorithm attached to QAOA can perform on par with the traditional QAOA with a Cobyla optimizer, which is a linear based method, and in some instances, it can even create a better Max-Cut. Whilst the final objective of the work is to create an algorithm that can consistently beat the original QAOA, or its variants, due to either speedups or quality of the solution, this initial result is promising and show the potential of EAs in this field. Further tests need to be performed on an array of different graphs with the parallelization aspect of the work commencing in October 2023 and tests on real hardware scheduled for early 2024.

Keywords: evolutionary algorithm, max cut, parallel simulation, quantum optimization

Procedia PDF Downloads 60

Authors: Bei Shan Lin, Chun Mei Lu, Ya Ping Chen, Li Chen Lu

Abstract:

This study explores the ethical issues concerning the use of physical restraint in geriatric care. Physical restraint use in a medical care setting is seen as a controversial form of treatment that has occurred over decades. There is no doubt that people nowadays are living longer than previous generations. The ageing process is inevitable. Common disease such as impaired comprehension, memory loss, and trouble expressing one’s self contribute to the difficulty that these older patients have in adapting to medical institution. For these reasons, physical restraint is often used in reducing the risk of falling, managing wandering behaviour, preventing agitation, and promoting patient compliance in geriatric care. It can mean that physical restraints are considered as a common practice that is used in the care of older patients. It is most commonly used for three specific purposes, including procedural restraint, restraint to prevent falls, and behavioural restraints. Although there have been well documented instances of morbidity and mortality recognised as being potential risks associated with physical restraint use, it continues to be permitted and used in healthcare, often in the name of safety. However, there is insufficient evidence supporting the effectiveness of physical restraint use reducing injuries from falls and controlling challenging behaviour in geriatric care settings. There is barely any empirical evidence of either a scientific basis or clinical trials have evaluated the improvement in patient safety following physical restraint. In difficult clinical situations, guidelines and practical suggestions for Healthcare professionals to comply requirements can help those making appropriate decisions and to facilitate better judgement regarding physical restraint use. The following recommendations are given for physical restraint use in long-term care settings: an interdisciplinary team approach to assess, evaluate, and treat underlying diseases to determine if treatment can ease issues precipitating physical restraint use; a clearly stated purpose of treatment plan should be made after weighing up the risk of physical restraint use against the risk of without physical restraint use; a care plan for physical restraint has to include individualised treatment planning, informed consent, identification and remedial action to avoid negative consequences, regular assessment and modification, reduction and removal of risks; patients and their families must have the opportunity to consider and give voluntary informed consent prior to physical restraint utilisation; patients, family members, and Healthcare professionals should be educated on use and adverse consequences of physical restraints in order to make raise awareness of potential risks and to take appropriate steps to prevent unnecessary harm; after physical restraint removal, Healthcare professionals should discuss with patients and family members about their experience, feelings, and any anxieties regarding the treatment. Physical restraint should always be considered a last resort as deprive patient’s freedom, control, and individuality. Healthcare professionals should emphasise on providing individualized care, interdisciplinary decision-making process, and creative and collaborative alternatives to promote older patient’s rights, dignity and overall well-being as much as possible.

Keywords: ethics healthcare, geriatric care, healthcare, physical restraint

Procedia PDF Downloads 133

Authors: Eric Pla Erra, Mariana Jimenez Martinez

Abstract:

While aggregated loads at a community level tend to be easier to predict, individual household load forecasting present more challenges with higher volatility and uncertainty. Furthermore, the drastic changes that our behavior patterns have suffered due to the COVID-19 pandemic have modified our daily electrical consumption curves and, therefore, further complicated the forecasting methods used to predict short-term electric load. Load forecasting is vital for the smooth and optimized planning and operation of our electric grids, but it also plays a crucial role for individual domestic consumers that rely on a HEMS (Home Energy Management Systems) to optimize their energy usage through self-generation, storage, or smart appliances management. An accurate forecasting leads to higher energy savings and overall energy efficiency of the household when paired with a proper HEMS. In order to study how COVID-19 has affected the accuracy of forecasting methods, an evaluation of the performance of a state-of-the-art LGBM (Light Gradient Boosting Model) will be conducted during the transition between pre-pandemic and lockdowns periods, considering day-ahead electric load forecasting. LGBM improves the capabilities of standard Decision Tree models in both speed and reduction of memory consumption, but it still offers a high accuracy. Even though LGBM has complex non-linear modelling capabilities, it has proven to be a competitive method under challenging forecasting scenarios such as short series, heterogeneous series, or data patterns with minimal prior knowledge. An adaptation of the LGBM model – called “resilient LGBM” – will be also tested, incorporating a concept drift detection technique for time series analysis, with the purpose to evaluate its capabilities to improve the model’s accuracy during extreme events such as COVID-19 lockdowns. The results for the LGBM and resilient LGBM will be compared using standard RMSE (Root Mean Squared Error) as the main performance metric. The models’ performance will be evaluated over a set of real households’ hourly electricity consumption data measured before and during the COVID-19 pandemic. All households are located in the city of Barcelona, Spain, and present different consumption profiles. This study is carried out under the ComMit-20 project, financed by AGAUR (Agència de Gestiód’AjutsUniversitaris), which aims to determine the short and long-term impacts of the COVID-19 pandemic on building energy consumption, incrementing the resilience of electrical systems through the use of tools such as HEMS and artificial intelligence.

Keywords: concept drift, forecasting, home energy management system (HEMS), light gradient boosting model (LGBM)

Procedia PDF Downloads 105

Authors: Piret Pernik

Abstract:

Based on strategic, operational, and technical analysis of the ongoing armed conflict in Ukraine, this paper will examine the opportunities and risks of using small commercial drones (dual-use unmanned aerial vehicles, UAV) for military purposes. The paper discusses the opportunities and risks in the information domain, encompassing both cyber and electromagnetic interference and attacks. The paper will draw conclusions on a possible strategic impact to the battlefield outcomes in the modern armed conflicts by the widespread use of dual-use UAVs. This article will contribute to filling the gap in the literature by examining based on empirical data cyberattacks and electromagnetic interference. Today, more than one hundred states and non-state actors possess UAVs ranging from low cost commodity models, widely are dual-use, available and affordable to anyone, to high-cost combat UAVs (UCAV) with lethal kinetic strike capabilities, which can be enhanced with Artificial Intelligence (AI) and Machine Learning (ML). Dual-use UAVs have been used by various actors for intelligence, reconnaissance, surveillance, situational awareness, geolocation, and kinetic targeting. Thus they function as force multipliers enabling kinetic and electronic warfare attacks and provide comparative and asymmetric operational and tactical advances. Some go as far as argue that automated (or semi-automated) systems can change the character of warfare, while others observe that the use of small drones has not changed the balance of power or battlefield outcomes. UAVs give considerable opportunities for commanders, for example, because they can be operated without GPS navigation, makes them less vulnerable and dependent on satellite communications. They can and have been used to conduct cyberattacks, electromagnetic interference, and kinetic attacks. However, they are highly vulnerable to those attacks themselves. So far, strategic studies, literature, and expert commentary have overlooked cybersecurity and electronic interference dimension of the use of dual use UAVs. The studies that link technical analysis of opportunities and risks with strategic battlefield outcomes is missing. It is expected that dual use commercial UAV proliferation in armed and hybrid conflicts will continue and accelerate in the future. Therefore, it is important to understand specific opportunities and risks related to the crowdsourced use of dual-use UAVs, which can have kinetic effects. Technical countermeasures to protect UAVs differ depending on a type of UAV (small, midsize, large, stealth combat), and this paper will offer a unique analysis of small UAVs both from the view of opportunities and risks for commanders and other actors in armed conflict.

Keywords: dual-use technology, cyber attacks, electromagnetic warfare, case studies of cyberattacks in armed conflicts

Procedia PDF Downloads 102

Authors: S. Mehrab Amiri, Nasser Talebbeydokhti

Abstract:

Modeling sediment transport processes by means of numerical approach often poses severe challenges. In this way, a number of techniques have been suggested to solve flow and sediment equations in decoupled, semi-coupled or fully coupled forms. Furthermore, in order to capture flow discontinuities, a number of techniques, like artificial viscosity and shock fitting, have been proposed for solving these equations which are mostly required careful calibration processes. In this research, a numerical scheme for solving shallow water and Exner equations in fully coupled form is presented. First-Order Centered scheme is applied for producing required numerical fluxes and the reconstruction process is carried out toward using Monotonic Upstream Scheme for Conservation Laws to achieve a high order scheme.  In order to satisfy C-property of the scheme in presence of bed topography, Surface Gradient Method is proposed. Combining the presented scheme with fourth order Runge-Kutta algorithm for time integration yields a competent numerical scheme. In addition, to handle non-prismatic channels problems, Cartesian Cut Cell Method is employed. A trained Multi-Layer Perceptron Artificial Neural Network which is of Feed Forward Back Propagation (FFBP) type estimates sediment flow discharge in the model rather than usual empirical formulas. Hydrodynamic part of the model is tested for showing its capability in simulation of flow discontinuities, transcritical flows, wetting/drying conditions and non-prismatic channel flows. In this end, dam-break flow onto a locally non-prismatic converging-diverging channel with initially dry bed conditions is modeled. The morphodynamic part of the model is verified simulating dam break on a dry movable bed and bed level variations in an alluvial junction. The results show that the model is capable in capturing the flow discontinuities, solving wetting/drying problems even in non-prismatic channels and presenting proper results for movable bed situations. It can also be deducted that applying Artificial Neural Network, instead of common empirical formulas for estimating sediment flow discharge, leads to more accurate results.

Keywords: artificial neural network, morphodynamic model, sediment continuity equation, shallow water equations

Procedia PDF Downloads 187

Authors: Kristina Pflug, Markus Busch

Abstract:

Being able to predict polymer properties and processing behavior based on the applied operating reaction conditions in one of the key challenges in modern polymer reaction engineering. Especially, for cost-intensive processes such as the high-pressure polymerization of low-density polyethylene (LDPE) with high safety-requirements, the need for simulation-based process optimization and product design is high. A multi-scale modelling approach was set-up and validated via a series of high-pressure mini-plant autoclave reactor experiments. The approach starts with the numerical modelling of the complex reaction network of the LDPE polymerization taking into consideration the actual reaction conditions. While this gives average product properties, the complex polymeric microstructure including random short- and long-chain branching is calculated via a hybrid Monte Carlo-approach. Finally, the processing behavior of LDPE -its melt flow behavior- is determined in dependence of the previously determined polymeric microstructure using the branch on branch algorithm for randomly branched polymer systems. All three steps of the multi-scale modelling approach can be independently validated against analytical data. A triple-detector GPC containing an IR, viscosimetry and multi-angle light scattering detector is applied. It serves to determine molecular weight distributions as well as chain-length dependent short- and long-chain branching frequencies. 13C-NMR measurements give average branching frequencies, and rheological measurements in shear and extension serve to characterize the polymeric flow behavior. The accordance of experimental and modelled results was found to be extraordinary, especially taking into consideration that the applied multi-scale modelling approach does not contain parameter fitting of the data. This validates the suggested approach and proves its universality at the same time. In the next step, the modelling approach can be applied to other reactor types, such as tubular reactors or industrial scale. Moreover, sensitivity analysis for systematically varying process conditions is easily feasible. The developed multi-scale modelling approach finally gives the opportunity to predict and design LDPE processing behavior simply based on process conditions such as feed streams and inlet temperatures and pressures.

Keywords: low-density polyethylene, multi-scale modelling, polymer properties, reaction engineering, rheology

Procedia PDF Downloads 124

Authors: Fereydoon Bondarian, Samira Shaygan

Abstract:

Today, many nutritionists recommend the consumption of plants, fruits, and vegetables to provide the antioxidants needed by the body because the use of plant antioxidants usually causes fewer side effects and better treatment. Natural antioxidants increase the power of plasma antioxidants and reduce the incidence of some diseases, such as cancer. Bad lifestyles and environmental factors play an important role in increasing the incidence of cancer. In this study, different extracts of white teas taken from two types of tea available in Iran (clone 100 and Chinese hybrid) due to the presence of a hydroxyl functional group in their structure to inhibit free radicals and anticancer properties, using 3 aqueous, methanolic and aqueous-methanolic methods were used. The total polyphenolic content was calculated using the Folin-Ciocalcu method, and the percentage of inhibition and trapping of free radicals in each of the extracts was calculated using the DPPH method. With the help of high-performance liquid chromatography, a small amount of each catechin in the tea samples was obtained. Clone 100 white tea was found to be the best sample of tea in terms of all the examined attributes (total polyphenol content, antioxidant properties, and individual amount of each catechin). The results showed that aqueous and aqueous-methanolic extracts of Clone 100 white tea have the highest total polyphenol content with 27.59±0.08 and 36.67±0.54 (equivalent gallic acid per gram dry weight of leaves), respectively. Due to having the highest level of different groups of catechin compounds, these extracts have the highest property of inhibiting and trapping free radicals with 66.61±0.27 and 71.74±0.27% (mg/l) of the extracted sample against ascorbic acid). Using the MTT test, the inhibitory effect of clone 100 white tea extract in inhibiting the growth of HCT-116 colon cancer cells was investigated and the best time and concentration treatments were 500, 150 and 1000 micrograms in 8, 16 and 24 hours, respectively. To investigate gene expression changes, selected genes, including tumorigenic genes, proto-oncogenes, tumor suppressors, and genes involved in apoptosis, were selected and analyzed using the real-time PCR method and in the presence of concentrations obtained for white tea. White tea extract at a concentration of 1000 μg/ml 3 times 16, 8, and 24 hours showed the highest growth inhibition in cancer cells with 53.27, 55.8, and 86.06%. The concentration of 1000 μg/ml aqueous extract of white tea under 24-hour treatment increased the expression of tumor suppressor genes compared to the normal sample.

Keywords: catechin, gene expression, suppressor genes, colon cell line

Procedia PDF Downloads 58

Authors: Sven Borén, Henrik Ny

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Ambitions within the EU for moving towards sustainable transport include major emission reductions for fossil fuel road vehicles, especially for buses, trucks, and cars. The electric driveline seems to be an attractive solution for such development. This study first applied the Framework for Strategic Sustainable Development to compare sustainability effects of today’s fossil fuel vehicles with electric vehicles that have batteries or hydrogen fuel cells. The study then addressed a scenario were electric vehicles might be in majority in Europe by 2050. The methodology called Strategic Lifecycle Assessment was first used, were each life cycle phase was assessed for violations against sustainability principles. This indicates where further analysis could be done in order to quantify the magnitude of each violation, and later to create alternative strategies and actions that lead towards sustainability. A Life Cycle Assessment of combustion engine cars, plug-in hybrid cars, battery electric cars and hydrogen fuel cell cars was then conducted to compare and quantify environmental impacts. The authors found major violations of sustainability principles like use of fossil fuels, which contribute to the increase of emission related impacts such as climate change, acidification, eutrophication, ozone depletion, and particulate matters. Other violations were found, such as use of scarce materials for batteries and fuel cells, and also for most life cycle phases for all vehicles when using fossil fuel vehicles for mining, production and transport. Still, the studied current battery and hydrogen fuel cell cars have less severe violations than fossil fuel cars. The life cycle assessment revealed that fossil fuel cars have overall considerably higher environmental impacts compared to electric cars as long as the latter are powered by renewable electricity. By 2050, there will likely be even more sustainable alternatives than the studied electric vehicles when the EU electricity mix mainly should stem from renewable sources, batteries should be recycled, fuel cells should be a mature technology for use in vehicles (containing no scarce materials), and electric drivelines should have replaced combustion engines in other sectors. An uncertainty for fuel cells in 2050 is whether the production of hydrogen will have had time to switch to renewable resources. If so, that would contribute even more to a sustainable development. Except for being adopted in the GreenCharge roadmap, the authors suggest that the results can contribute to planning in the upcoming decades for a sustainable increase of EVs in Europe, and potentially serve as an inspiration for other smaller or larger regions. Further studies could map the environmental effects in LCA further, and include other road vehicles to get a more precise perception of how much they could affect sustainable development.

Keywords: strategic, electric vehicles, sustainability, LCA

Procedia PDF Downloads 386

Authors: Jigar N. Shah, Hiral J. Shah, Praful D. Bharadia

Abstract:

The major challenge faced by formulation scientists in transdermal drug delivery system is to overcome the inherent barriers related to skin permeation. The stratum corneum layer of the skin is working as the rate limiting step in transdermal transport and reduce drug permeation through skin. Many approaches have been used to enhance the penetration of drugs through this layer of the skin. The purpose of this study is to investigate the development and evaluation of a combined approach of drug carriers and iontophoresis as a vehicle to improve skin permeation of an analgesic drug. Iontophoresis is a non-invasive technique for transporting charged molecules into and through tissues by a mild electric field. It has been shown to effectively deliver a variety of drugs across the skin to the underlying tissue. In addition to the enhanced continuous transport, iontophoresis allows dose titration by adjusting the electric field, which makes personalized dosing feasible. Drug carrier could modify the physicochemical properties of the encapsulated molecule and offer a means to facilitate the percutaneous delivery of difficult-to-uptake substances. Recently, there are some reports about using liposomes, microemulsions and polymeric nanoparticles as vehicles for iontophoretic drug delivery. Niosomes, the nonionic surfactant-based vesicles that are essentially similar in properties to liposomes have been proposed as an alternative to liposomes. Niosomes are more stable and free from other shortcoming of liposomes. Recently, the transdermal delivery of certain drugs using niosomes has been envisaged and niosomes have proved to be superior transdermal nanocarriers. Proniosomes overcome some of the physical stability related problems of niosomes. The proniosomal structure was liquid crystalline-compact niosomes hybrid which could be converted into niosomes upon hydration. The combined use of drug carriers and iontophoresis could offer many additional benefits. The system was evaluated for Encapsulation Efficiency, vesicle size, zeta potential, Transmission Electron Microscopy (TEM), DSC, in-vitro release, ex-vivo permeation across skin and rate of hydration. The use of proniosomal gel as a vehicle for the transdermal iontophoretic delivery was evaluated in-vitro. The characteristics of the applied electric current, such as density, type, frequency, and on/off interval ratio were observed. The study confirms the synergistic effect of proniosomes and iontophoresis in improving the transdermal permeation profile of selected analgesic drug. It is concluded that proniosomal gel can be used as a vehicle for transdermal iontophoretic drug delivery under suitable electric conditions.

Keywords: iontophoresis, niosomes, permeation enhancement, transdermal delivery

Procedia PDF Downloads 379

Authors: W. Kritsarikan, T. Patcharawit, T. Yingnakorn, S. Khumkoa

Abstract:

Neodymium-iron-boron (NdFeB) magnets classified as high-power magnets are widely used in various applications such as electrical and medical devices and account for 13.5 % of the permanent magnet’s market. Since its typical composition of 29 - 32 % Nd, 64.2 – 68.5 % Fe and 1 – 1.2 % B contains a significant amount of rare earth metals and will be subjected to shortages in the future. Domestic NdFeB magnet waste recycling should therefore be developed in order to reduce social, environmental impacts toward a circular economy. Most research works focus on recycling the magnet wastes, both from the manufacturing process and end of life. Each type of wastes has different characteristics and compositions. As a result, these directly affect recycling efficiency as well as the types and purity of the recyclable products. This research, therefore, focused on the recycling of manufacturing NdFeB magnet waste obtained from the sintering stage of magnet production and the waste contained 23.6% Nd, 60.3% Fe and 0.261% B in order to recover high purity neodymium oxide (Nd₂O₃) using hybrid metallurgical process via oxidative roasting and selective leaching techniques. The sintered NdFeB waste was first ground to under 70 mesh prior to oxidative roasting at 550 - 800 °C to enable selective leaching of neodymium in the subsequent leaching step using H₂SO₄ at 2.5 M over 24 h. The leachate was then subjected to drying and roasting at 700 – 800 °C prior to precipitation by oxalic acid and calcination to obtain neodymium oxide as the recycling product. According to XRD analyses, it was found that increasing oxidative roasting temperature led to an increasing amount of hematite (Fe₂O₃) as the main composition with a smaller amount of magnetite (Fe₃O₄) found. Peaks of neodymium oxide (Nd₂O₃) were also observed in a lesser amount. Furthermore, neodymium iron oxide (NdFeO₃) was present and its XRD peaks were pronounced at higher oxidative roasting temperatures. When proceeded to acid leaching and drying, iron sulfate and neodymium sulfate were mainly obtained. After the roasting step prior to water leaching, iron sulfate was converted to form hematite as the main compound, while neodymium sulfate remained in the ingredient. However, a small amount of magnetite was still detected by XRD. The higher roasting temperature at 800 °C resulted in a greater Fe₂O₃ to Nd₂(SO₄)₃ ratio, indicating a more effective roasting temperature. Iron oxides were subsequently water leached and filtered out while the solution contained mainly neodymium sulfate. Therefore, low oxidative roasting temperature not exceeding 600 °C followed by acid leaching and roasting at 800 °C gave the optimum condition for further steps of precipitation and calcination to finally achieve neodymium oxide.

Keywords: NdFeB magnet waste, oxidative roasting, recycling, selective leaching

Procedia PDF Downloads 182

Authors: Sulalit Bandyopadhyay, Muhammad Awais Ashfaq Alvi, Anuvansh Sharma, Wilhelm R. Glomm

Abstract:

Release of drugs from nanogels and nanogel-based systems can occur under the influence of external stimuli like temperature, pH, magnetic fields and so on. pNIPAm-AAc nanogels respond to the combined action of both temperature and pH, the former being mostly determined by hydrophilic-to-hydrophobic transitions above the volume phase transition temperature (VPTT), while the latter is controlled by the degree of protonation of the carboxylic acid groups. These nanogels based systems are promising candidates in the field of drug delivery. Combining nanogels with magneto-plasmonic nanoparticles (NPs) introduce imaging and targeting modalities along with stimuli-response in one hybrid system, thereby incorporating multifunctionality. Fe@Au core-shell NPs possess optical signature in the visible spectrum owing to localized surface plasmon resonance (LSPR) of the Au shell, and superparamagnetic properties stemming from the Fe core. Although there exist several synthesis methods to control the size and physico-chemical properties of pNIPAm-AAc nanogels, yet, there is no comprehensive study that highlights the dependence of incorporation of one or more layers of NPs to these nanogels. In addition, effective determination of volume phase transition temperature (VPTT) of the nanogels is a challenge which complicates their uses in biological applications. Here, we have modified the swelling-collapse properties of pNIPAm-AAc nanogels, by combining with Fe@Au NPs using different solution based methods. The hydrophilic-hydrophobic transition of the nanogels above the VPTT has been confirmed to be reversible. Further, an analytical method has been developed to deduce the average VPTT which is found to be 37.3°C for the nanogels and 39.3°C for nanogel coated Fe@Au NPs. An opposite swelling –collapse behaviour is observed for the latter where the Fe@Au NPs act as bridge molecules pulling together the gelling units. Thereafter, Cyt C, a model protein drug and L-Dopa, a drug used in the clinical treatment of Parkinson’s disease were loaded separately into the nanogels and nanogel coated Fe@Au NPs, using a modified breathing-in mechanism. This gave high loading and encapsulation efficiencies (L Dopa: ~9% and 70µg/mg of nanogels, Cyt C: ~30% and 10µg/mg of nanogels respectively for both the drugs. The release kinetics of L-Dopa, monitored using UV-vis spectrophotometry was observed to be rather slow (over several hours) with highest release happening under a combination of high temperature (above VPTT) and acidic conditions. However, the release of L-Dopa from nanogel coated Fe@Au NPs was the fastest, accounting for release of almost 87% of the initially loaded drug in ~30 hours. The chemical structure of the drug, drug incorporation method, location of the drug and presence of Fe@Au NPs largely alter the drug release mechanism and the kinetics of these nanogels and Fe@Au NPs coated with nanogels.

Keywords: controlled release, nanogels, volume phase transition temperature, l-dopa

Procedia PDF Downloads 331

Authors: Rima Alfaraj, Abeer Alarawi, Murtadha AlTammar

Abstract:

The global energy landscape heavily relies on the oil and gas industry, which faces the critical challenge of reducing its carbon footprint. To address this issue, the integration of advanced materials like aerogels has emerged as a promising solution to enhance sustainability and environmental performance within the industry. This study thoroughly examines the application of aerogel-based technologies in the oil and gas sector, focusing particularly on their role in carbon capture and storage (CCS) initiatives. Aerogels, known for their exceptional properties, such as high surface area, low density, and customizable pore structure, have garnered attention for their potential in various CCS strategies. The review delves into various fabrication techniques utilized in producing aerogel materials, including sol-gel, supercritical drying, and freeze-drying methods, to assess their suitability for specific industry applications. Beyond fabrication, the practicality of aerogel materials in critical areas such as flow assurance, enhanced oil recovery, and thermal insulation is explored. The analysis spans a wide range of applications, from potential use in pipelines and equipment to subsea installations, offering valuable insights into the real-world implementation of aerogels in the oil and gas sector. The paper also investigates the adsorption and storage capabilities of aerogel-based sorbents, showcasing their effectiveness in capturing and storing carbon dioxide (CO₂) molecules. Optimization of pore size distribution and surface chemistry is examined to enhance the affinity and selectivity of aerogels towards CO₂, thereby improving the efficiency and capacity of CCS systems. Additionally, the study explores the potential of aerogel-based membranes for separating and purifying CO₂ from oil and gas streams, emphasizing their role in the carbon capture and utilization (CCU) value chain in the industry. Emerging trends and future perspectives in integrating aerogel-based technologies within the oil and gas sector are also discussed, including the development of hybrid aerogel composites and advanced functional components to further enhance material performance and versatility. By synthesizing the latest advancements and future directions in aerogel used for CCS applications in the oil and gas industry, this review offers a comprehensive understanding of how these innovative materials can aid in transitioning towards a more sustainable and environmentally conscious energy landscape. The insights provided can assist in strategic decision-making, drive technology development, and foster collaborations among academia, industry, and policymakers to promote the widespread adoption of aerogel-based solutions in the oil and gas sector.

Keywords: CCS, porous, carbon capture, oil and gas, sustainability

Procedia PDF Downloads 41

Authors: Woranittha Kritsarikan

Abstract:

Neodymium-iron-boron (NdFeB) magnets classified as high-power magnets are widely used in various applications such as electrical and medical devices and account for 13.5 % of the permanent magnet’s market. Since its typical composition of 29 - 32 % Nd, 64.2 – 68.5 % Fe and 1 – 1.2 % B contains a significant amount of rare earth metals and will be subjected to shortages in the future. Domestic NdFeB magnet waste recycling should therefore be developed in order to reduce social, environmental impacts toward the circular economy. Most research works focus on recycling the magnet wastes, both from the manufacturing process and end of life. Each type of wastes has different characteristics and compositions. As a result, these directly affect recycling efficiency as well as the types and purity of the recyclable products. This research, therefore, focused on the recycling of manufacturing NdFeB magnet waste obtained from the sintering stage of magnet production and the waste contained 23.6% Nd, 60.3% Fe and 0.261% B in order to recover high purity neodymium oxide (Nd₂O₃) using hybrid metallurgical process via oxidative roasting and selective leaching techniques. The sintered NdFeB waste was first ground to under 70 mesh prior to oxidative roasting at 550 - 800 ᵒC to enable selective leaching of neodymium in the subsequent leaching step using H₂SO₄ at 2.5 M over 24 hours. The leachate was then subjected to drying and roasting at 700 – 800 ᵒC prior to precipitation by oxalic acid and calcination to obtain neodymium oxide as the recycling product. According to XRD analyses, it was found that increasing oxidative roasting temperature led to the increasing amount of hematite (Fe₂O₃) as the main composition with a smaller amount of magnetite (Fe3O4) found. Peaks of neodymium oxide (Nd₂O₃) were also observed in a lesser amount. Furthermore, neodymium iron oxide (NdFeO₃) was present and its XRD peaks were pronounced at higher oxidative roasting temperature. When proceeded to acid leaching and drying, iron sulfate and neodymium sulfate were mainly obtained. After the roasting step prior to water leaching, iron sulfate was converted to form hematite as the main compound, while neodymium sulfate remained in the ingredient. However, a small amount of magnetite was still detected by XRD. The higher roasting temperature at 800 ᵒC resulted in a greater Fe2O3 to Nd2(SO4)3 ratio, indicating a more effective roasting temperature. Iron oxides were subsequently water leached and filtered out while the solution contained mainly neodymium sulfate. Therefore, low oxidative roasting temperature not exceeding 600 ᵒC followed by acid leaching and roasting at 800 ᵒC gave the optimum condition for further steps of precipitation and calcination to finally achieve neodymium oxide.

Keywords: NdFeB magnet waste, oxidative roasting, recycling, selective leaching

Procedia PDF Downloads 177

Authors: Mathula Thangarajh

Abstract:

Duchenne muscular dystrophy (DMD) is a severe form of X-linked muscular dystrophy caused by mutations in the dystrophin gene resulting in progressive skeletal muscle weakness. Boys with DMD also have significant cognitive disabilities. The intelligence quotient of boys with DMD, compared to peers, is approximately one standard deviation below average. Detailed neuropsychological testing has demonstrated that boys with DMD have a global developmental impairment, with verbal memory and visuospatial skills most significantly affected. Furthermore, the total brain volume and gray matter volume are lower in children with DMD compared to age-matched controls. These results are suggestive of a significant structural and functional compromise to the developing brain as a result of absent dystrophin protein expression. There is also some genetic evidence to suggest that mutations in the 3’ end of the DMD gene are associated with more severe neurocognitive problems. Our working hypothesis is that (i) boys with DMD do not make gains in neurodevelopmental skills compared to typically developing children and (ii) women carriers of DMD mutations may have subclinical cognitive deficits. We also hypothesize that there may be an intergenerational vulnerability of cognition, with boys of DMD-carrier mothers being more affected cognitively than boys of non-DMD-carrier mothers. The objectives of this study are: 1. Assess the neurodevelopment in boys with DMD at 4-time points and perform baseline neuroradiological assessment, 2. Assess cognition in biological mothers of DMD participants at baseline, 3. Assess possible correlation between DMD mutation and cognitive measures. This study also explores functional brain abnormalities in people with DMD by exploring how regional and global connectivity of the brain underlies executive function deficits in DMD. Such research can contribute to a better holistic understanding of the cognition alterations due to DMD and could potentially allow clinicians to create better-tailored treatment plans for the DMD population. There are four study visits for each participant (baseline, 2-4 weeks, 1 year, 18 months). At each visit, the participant completes the NIH Toolbox Cognition Battery, a validated psychometric measure that is recommended by NIH Common Data Elements for use in DMD. Visits 1, 3, and 4 also involve the administration of the BRIEF-2, ABAS-3, PROMIS/NeuroQoL, PedsQL Neuromuscular module 3.0, Draw a Clock Test, and an optional fMRI scan with the N-back matching task. We expect to enroll 52 children with DMD, 52 mothers of children with DMD, and 30 healthy control boys. This study began in 2020 during the height of the COVID-19 pandemic. Due to this, there were subsequent delays in recruitment because of travel restrictions. However, we have persevered and continued to recruit new participants for the study. We partnered with the Muscular Dystrophy Association (MDA) and helped advertise the study to interested families. Since then, we have had families from across the country contact us about their interest in the study. We plan to continue to enroll a diverse population of DMD participants to contribute toward a better understanding of Duchenne Muscular Dystrophy.

Keywords: neurology, Duchenne muscular dystrophy, muscular dystrophy, cognition, neurodevelopment, x-linked disorder, DMD, DMD gene

Procedia PDF Downloads 99

Authors: Igor Pejic

Abstract:

The main focus of this research will be on analyzing correlative links between terrorism as an asymmetrical threat and the consequences it leaves on conventional security forces. The methodology behind the research will include qualitative research methods focusing on comparative analysis of books, scientific papers, documents and other sources, in order to deduce, explore and formulate the results of the research. With the coming of the 21^st century and the rising multi-polar, new world threats quickly emerged. The realistic approach in international relations deems that relations among nations are in a constant state of anarchy since there are no definitive rules and the distribution of power varies widely. International relations are further characterized by egoistic and self-orientated human nature, anarchy or absence of a higher government, security and lack of morality. The asymmetry of power is also reflected on countries' security capabilities and its abilities to project power. With the coming of the new millennia and the rising multi-polar world order, the asymmetry of power can be also added as an important trait of the global society which consequently brought new threats. Among various others, terrorism is probably the most well-known, well-based and well-spread asymmetric threat. In today's global political arena, terrorism is used by state and non-state actors to fulfill their political agendas. Terrorism is used as an all-inclusive tool for regime change, subversion or a revolution. Although the nature of terrorist groups is somewhat inconsistent, terrorism as a security and social phenomenon has a one constant which is reflected in its political dimension. The state's security apparatus, which was embodied in the form of conventional armed forces, is now becoming fragile, unable to tackle new threats and to a certain extent outdated. Conventional security forces were designed to defend or engage an exterior threat which is more or less symmetric and visible. On the other hand, terrorism as an asymmetrical threat is a part of hybrid, special or asymmetric warfare in which specialized units, institutions or facilities represent the primary pillars of security. In today's global society, terrorism is probably the most acute problem which can paralyze entire countries and their political systems. This problem, however, cannot be engaged on an open field of battle, but rather it requires a different approach in which conventional armed forces cannot be used traditionally and their role must be adjusted. The research will try to shed light on the phenomena of modern day terrorism and to prove its correlation with the state conventional armed forces. States are obliged to adjust their security apparatus to the new realism of global society and terrorism as an asymmetrical threat which is a side-product of the unbalanced world.

Keywords: asymmetrical warfare, conventional forces, security, terrorism

Procedia PDF Downloads 262

Authors: Nasim Hashemi, Abbas Sheikhtaheri

Abstract:

Telemedicine is the use of telecommunication and information technologies to provide health care services that would often not be consistently available in distant rural communities to people at these remote areas. Teleophthalmology is a branch of telemedicine that delivers eye care through digital medical equipment and telecommunications technology. Thus, teleophthalmology can overcome geographical barriers and improve quality, access, and affordability of eye health care services. Since teleophthalmology has been widespread applied in recent years, the aim of this study was to determine the different applications of teleophthalmology in the world. To this end, three bibliographic databases (Medline, ScienceDirect, Scopus) were comprehensively searched with these keywords: eye care, eye health care, primary eye care, diagnosis, detection, and screening of different eye diseases in conjunction with telemedicine, telehealth, teleophthalmology, e-services, and information technology. All types of papers were included in the study with no time restriction. We conducted the search strategies until 2015. Finally 70 articles were surveyed. We classified the results based on the’type of eye problems covered’ and ‘the type of telemedicine services’. Based on the review, from the ‘perspective of health care levels’, there are three level for eye health care as primary, secondary and tertiary eye care. From the ‘perspective of eye care services’, the main application of teleophthalmology in primary eye care was related to the diagnosis of different eye diseases such as diabetic retinopathy, macular edema, strabismus and aged related macular degeneration. The main application of teleophthalmology in secondary and tertiary eye care was related to the screening of eye problems i.e. diabetic retinopathy, astigmatism, glaucoma screening. Teleconsultation between health care providers and ophthalmologists and also education and training sessions for patients were other types of teleophthalmology in world. Real time, store–forward and hybrid methods were the main forms of the communication from the perspective of ‘teleophthalmology mode’ which is used based on IT infrastructure between sending and receiving centers. In aspect of specialists, early detection of serious aged-related ophthalmic disease in population, screening of eye disease processes, consultation in an emergency cases and comprehensive eye examination were the most important benefits of teleophthalmology. Cost-effectiveness of teleophthalmology projects resulted from reducing transportation and accommodation cost, access to affordable eye care services and receiving specialist opinions were also the main advantages of teleophthalmology for patients. Teleophthalmology brings valuable secondary and tertiary care to remote areas. So, applying teleophthalmology for detection, treatment and screening purposes and expanding its use in new applications such as eye surgery will be a key tool to promote public health and integrating eye care to primary health care.

Keywords: applications, telehealth, telemedicine, teleophthalmology

Procedia PDF Downloads 374

Authors: Lorenzo Petrucci

Abstract:

This paper is intended to give insight into the potential use of small-scale off-grid trigeneration systems powered by biogas generated in a dairy farm. The off-grid plant object of analysis comprises a dual-fuel Genset as well as electrical and thermal storage equipment and an adsorption machine. The loads are the different apparatus used in the dairy farm, a household where the workers live and a small electric vehicle whose batteries can also be used as a power source in case of emergency. The insertion in the plant of an adsorption machine is mainly justified by the abundance of thermal energy and the simultaneous high cooling demand associated with the milk-chilling process. In the evaluated operational scenario, our research highlights the importance of prioritizing specific small loads which cannot sustain an interrupted supply of power over time. As a consequence, a photovoltaic and thermal panel is included in the plant and is tasked with providing energy independently of potentially disruptive events such as engine malfunctioning or scarce and unstable supplies of fuels. To efficiently manage the plant an energy dispatch strategy is created in order to control the flow of energy between the power sources and the thermal and electric storages. In this article we elaborate on models of the equipment and from these models, we extract parameters useful to build load-dependent profiles of the prime movers and storage efficiencies. We show that under reasonable assumptions the analysis provides a sensible estimate of the generated energy. The simulations indicate that a Diesel Generator sized to a value 25% higher than the total electrical peak demand operates 65% of the time below the minimum acceptable load threshold. To circumvent such a critical operating mode, dump loads are added through the activation and deactivation of small resistors. In this way, the excess of electric energy generated can be transformed into useful heat. The combination of PVT and electrical storage to support the prioritized load in an emergency scenario is evaluated in two different days of the year having the lowest and highest irradiation values, respectively. The results show that the renewable energy component of the plant can successfully sustain the prioritized loads and only during a day with very low irradiation levels it also needs the support of the EVs’ battery. Finally, we show that the adsorption machine can reduce the ice builder and the air conditioning energy consumption by 40%.

Keywords: hybrid power plants, mathematical modeling, off-grid plants, renewable energy, trigeneration

Procedia PDF Downloads 175