Search results for: modified Jacobian matrix

Authors: Marcus Goh Tian Xi, Alicia Chua Si Wen, Eunice Gan Ghee Wu, Helen Bound, Lee Liang Ying, Albert Lee

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The Map of Dialogical Inquiry provides a conceptual look at the underlying nature of future-oriented skills. According to the Map, learning is learner-oriented, with conversational time shifted from teachers to learners, who play a strong role in deciding what and how they learn. For example, in courses operating on the principles of Dialogical Inquiry, learners were able to leave the classroom with a deeper understanding of the topic, broader exposure to differing perspectives, and stronger critical thinking capabilities, compared to traditional approaches to teaching. Despite its contributions to learning, the Map is grounded in a qualitative approach both in its development and its application for providing feedback to learners and educators. Studies hinge on openended responses by Map users, which can be time consuming and resource intensive. The present research is motivated by this gap in practicality by aiming to develop and validate a quantitative measure of the Map. In addition, a quantifiable measure may also strengthen applicability by making learning experiences trackable and comparable. The Map outlines eight learning aspects that learners should holistically engage. This research focuses on the Analysing aspect of learning. According to the Map, Analysing has four key components: liking or engaging in logic, using interpretative lenses, seeking patterns, and critiquing and deconstructing. Existing scales of constructs (e.g., critical thinking, rationality) related to these components were identified so that the current scale could adapt items from. Specifically, items were phrased beginning with an “I”, followed by an action phrase, to fulfil the purpose of assessing learners' engagement with Analysing either in general or in classroom contexts. Paralleling standard scale development procedure, the 26-item Analysing scale was administered to 330 participants alongside existing scales with varying levels of association to Analysing, to establish construct validity. Subsequently, the scale was refined and its dimensionality, reliability, and validity were determined. Confirmatory factor analysis (CFA) revealed if scale items loaded onto the four factors corresponding to the components of Analysing. To refine the scale, items were systematically removed via an iterative procedure, according to their factor loadings and results of likelihood ratio tests at each step. Eight items were removed this way. The Analysing scale is better conceptualised as unidimensional, rather than comprising the four components identified by the Map, for three reasons: 1) the covariance matrix of the model specified for the CFA was not positive definite, 2) correlations among the four factors were high, and 3) exploratory factor analyses did not yield an easily interpretable factor structure of Analysing. Regarding validity, since the Analysing scale had higher correlations with conceptually similar scales than conceptually distinct scales, with minor exceptions, construct validity was largely established. Overall, satisfactory reliability and validity of the scale suggest that the current procedure can result in a valid and easy-touse measure for each aspect of the Map.

Keywords: analytical thinking, dialogical inquiry, education, lifelong learning, pedagogy, scale development

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Authors: Nino Kupatadze, Mzevinar Bedinashvili, Tamar Memanishvili, Manana Gurielidze, David Tugushi, Ramaz Katsarava

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Bacteria easily colonize the surfaces of tissues, surgical devices (implants, orthopedics, catheters, etc.), and instruments causing surgical device related infections. Therefore, the battle against bacteria and the prevention of surgical devices from biofilm formation is one of the main challenges of biomedicine today. Our strategy to the solution of this problem consists in using antimicrobial polymeric coatings as effective “shields” to protect surfaces from bacteria’s colonization and biofilm formation. As one of the most promising approaches look be the use of antimicrobial bioerodible polymeric nanocomposites containing silver nanoparticles (AgNPs). We assume that the combination of an erodible polymer with a strong bactericide should put obstacles to bacteria to occupy the surface and to form biofilm. It has to be noted that this kind of nanocomposites are also promising as wound dressing materials to treat infected superficial wounds. Various synthetic and natural polymers were used for creating biocomposites containing AgNPs as both particles' stabilizers and matrices forming elastic films at surfaces. One of the most effective systems to fabricate AgNPs is an ethanol solution of polyvinylpyrrolidone(PVP) with dissolved AgNO3–ethanol serves as a AgNO3 reductant and PVP as AgNPs stabilizer (through the interaction of nanoparticles with nitrogen atom of the amide group). Though PVP is biocompatible and film-forming polymer, it is not a good candidate to design either "biofilm shield" or wound dressing material because of a high solubility in water – though the solubility of PVP provides the desirable release of AgNPs from the matrix, but the coating is easily washable away from the surfaces. More promising as matrices look water insoluble but bioerodible polymers that can provide the release of AgNPs and form long-lasting coatings at the surfaces. For creating bioerodible water-insoluble antimicrobial coatings containing AgNPs, we selected amino acid based biodegradable polymers(AABBPs)–poly(ester amide)s, poly(ester urea)s, their copolymers containing amide and related groups capable to stabilize AgNPs. Among a huge variety of AABBPs reported we selected the polymers soluble in ethanol. For preparing AgNPs containing nanocompositions AABBPs and AgNO3 were dissolved in ethanol and subjected to photochemical reduction using daylight-irradiation. The formation of AgNPs was observed visually by coloring the solutions in brownish-red. The obtained AgNPs were characterized by UV-spectroscopy, transmission electron microscopy(TEM), and dynamic light scattering(DLS). According to the UV and TEM data, the photochemical reduction resulted presumably in spherical AgNPs with rather high contribution of the particles below 10 nm that are known as responsible for the antimicrobial activity. DLS study showed that average size of nanoparticles formed after photo-reduction in ethanol solution ranged within 50 nm. The in vitro antimicrobial activity study of the new nanocomposite material is in progress now.

Keywords: nanocomposites, silver nanoparticles, polymer, biodegradable

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Authors: Galatee Levadoux, Trevor Benson, Chris Worrall

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With the rise of public awareness on climate change comes an increasing demand for renewable sources of energy. As a result, the wind power sector is striving to manufacture longer, more efficient and reliable wind turbine blades. Currently, one of the leading causes of blade failure in service is improper cure of the resin during manufacture. The infusion process creating the main part of the composite blade structure remains a critical step that is yet to be monitored in real time. This stage consists of a viscous resin being drawn into a mould under vacuum, then undergoing a curing reaction until solidification. Successful infusion assumes the resin fills all the voids and cures completely. Given that the electrical properties of the resin change significantly during its solidification, both the filling of the mould and the curing reaction are susceptible to be followed using dieletrometry. However, industrially available dielectrics sensors are currently too small to monitor the entire surface of a wind turbine blade. The aim of the present research project is to scale up the dielectric sensor technology and develop a device able to monitor the manufacturing process of large composite structures, assessing the conformity of the blade before it even comes out of the mould. An array of flat copper wires acting as electrodes are embedded in a polymer matrix fixed in an infusion mould. A multi-frequency analysis from 1 Hz to 10 kHz is performed during the filling of the mould with an epoxy resin and the hardening of the said resin. By following the variations of the complex admittance Y*, the filling of the mould and curing process are monitored. Results are compared to numerical simulations of the sensor in order to validate a virtual cure-monitoring system. The results obtained by drawing glycerol on top of the copper sensor displayed a linear relation between the wetted length of the sensor and the complex admittance measured. Drawing epoxy resin on top of the sensor and letting it cure at room temperature for 24 hours has provided characteristic curves obtained when conventional interdigitated sensor are used to follow the same reaction. The response from the developed sensor has shown the different stages of the polymerization of the resin, validating the geometry of the prototype. The model created and analysed using COMSOL has shown that the dielectric cure process can be simulated, so long as a sufficient time and temperature dependent material properties can be determined. The model can be used to help design larger sensors suitable for use with full-sized blades. The preliminary results obtained with the sensor prototype indicate that the infusion and curing process of an epoxy resin can be followed with the chosen configuration on a scale of several decimeters. Further work is to be devoted to studying the influence of the sensor geometry and the infusion parameters on the results obtained. Ultimately, the aim is to develop a larger scale sensor able to monitor the flow and cure of large composite panels industrially.

Keywords: composite manufacture, dieletrometry, epoxy, resin infusion, wind turbine blades

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Authors: Edvard P. G. Bruun

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One of the best ways of improving our understanding of reinforced concrete is through large-scale experimental testing. The gathered information is critical in making inferences about structural mechanics and deriving the mathematical models that are the basis for finite element analysis programs and design codes. An effective way of measuring the strains across a region of a specimen is by using a system of surface mounted Linear Variable Differential Transformers (LVDTs). While a single LVDT can only measure the linear strain in one direction, by combining several measurements at known angles a Mohr’s circle of strain can be derived for the whole region under investigation. This paper presents a method that can be used by researchers, which improves the accuracy and removes experimental bias in the calculation of the Mohr’s circle, using four rather than three independent strain measurements. Obtaining high quality strain data is essential, since knowing the angular deviation (shear strain) and the angle of principal strain in the region are important properties in characterizing the governing structural mechanics. For example, the Modified Compression Field Theory (MCFT) developed at the University of Toronto, is a rotating crack model that requires knowing the direction of the principal stress and strain, and then calculates the average secant stiffness in this direction. But since LVDTs can only measure average strains across a plane (i.e., between discrete points), localized cracking and spalling that typically occur in reinforced concrete, can lead to unrealistic results. To build in redundancy and improve the quality of the data gathered, the typical experimental setup for a large-scale shell specimen has four independent directions (X, Y, H, and V) that are instrumented. The question now becomes, which three should be used? The most common approach is to simply discard one of the measurements. The problem is that this can produce drastically different answers, depending on the three strain values that are chosen. To overcome this experimental bias, and to avoid simply discarding valuable data, a more rigorous approach would be to somehow make use of all four measurements. This paper presents the derivation of a method to draw what is effectively a Mohr’s circle of 'best-fit', which optimizes the circle by using all four independent strain values. The four-strain optimized Mohr’s circle approach has been utilized to process data from recent large-scale shell tests at the University of Toronto (Ruggiero, Proestos, and Bruun), where analysis of the test data has shown that the traditional three-strain method can lead to widely different results. This paper presents the derivation of the method and shows its application in the context of two reinforced concrete shells tested in pure torsion. In general, the constitutive models and relationships that characterize reinforced concrete are only as good as the experimental data that is gathered – ensuring that a rigorous and unbiased approach exists for calculating the Mohr’s circle of strain during an experiment, is of utmost importance to the structural research community.

Keywords: reinforced concrete, shell tests, Mohr’s circle, experimental research

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Authors: Alena Kulikova, Leonid Parmaksiz, Ekaterina Orel

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Social and emotional skills are considered by modern researchers as predictors of a person's success both in specific areas of activity and in the life of a person as a whole. The popularity of this scientific direction ensures the emergence of a large number of practices aimed at developing and evaluating socio-emotional skills. Assessment of social and emotional development is carried out at the national level, as well as at the level of individual regions and institutions. Despite the fact that many of the already existing social and emotional skills assessment tools are quite convenient and reliable, there are now more and more new technologies and task formats which improve the basic characteristics of the tools. Thus, the goal of the current study is to develop a tool for assessing social and emotional skills such as emotion recognition, emotion regulation, empathy and a culture of self-care. To develop a tool assessing social and emotional skills, Rasch-Gutman scenario-based approach was used. This approach has shown its reliability and merit for measuring various complex constructs: parental involvement; teacher practices that support cultural diversity and equity; willingness to participate in the life of the community after psychiatric rehabilitation; educational motivation and others. To assess emotion recognition, we used a situational judgment task based on OCC (Ortony, Clore, and Collins) emotions theory. The main advantage of these two approaches compare to classical Likert scales is that it reduces social desirability in answers. A field test to check the psychometric properties of the developed instrument was conducted. The instrument was developed for the presidential autonomous non-profit organization “Russia - Land of Opportunity” for nationwide soft skills assessment among higher education students. The sample for the field test consisted of 500 people, students aged from 18 to 25 (mean = 20; standard deviation 1.8), 71% female. 67% of students are only studying and are not currently working and 500 employed adults aged from 26 to 65 (mean = 42.5; SD 9), 57% female. Analysis of the psychometric characteristics of the scales was carried out using the methods of IRT (Item Response Theory). A one-parameter rating scale model RSM (Rating scale model) and Graded Response model (GRM) of the modern testing theory were applied. GRM is a polyatomic extension of the dichotomous two-parameter model of modern testing theory (2PL) based on the cumulative logit function for modeling the probability of a correct answer. The validity of the developed scales was assessed using correlation analysis and MTMM (multitrait-multimethod matrix). The developed instrument showed good psychometric quality and can be used by HR specialists or educational management. The detailed results of a psychometric study of the quality of the instrument, including the functioning of the tasks of each scale, will be presented. Also, the results of the validity study by MTMM analysis will be discussed.

Keywords: social and emotional skills, psychometrics, MTMM, IRT

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Authors: Chenyao Shen, Jie Shen

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The rating system provides an effective framework for assessing building environmental performance and integrating sustainable development into building and construction processes; as it can be used as a design tool by developing appropriate sustainable design strategies and determining performance measures to guide the sustainable design and decision-making processes. Healthcare buildings are resource (water, energy, etc.) intensive. To maintain high-cost operations and complex medical facilities, they require a great deal of hazardous and non-hazardous materials, stringent control of environmental parameters, and are responsible for producing polluting emission. Compared with other types of buildings, the impact of healthcare buildings on the full cycle of the environment is particularly large. With broad recognition among designers and operators that energy use can be reduced substantially, many countries have set up their own green rating systems for healthcare buildings. There are four main green healthcare building evaluation systems widely acknowledged in the world - Green Guide for Health Care (GGHC), which was jointly organized by the United States HCWH and CMPBS in 2003; BREEAM Healthcare, issued by the British Academy of Building Research (BRE) in 2008; the Green Star-Healthcare v1 tool, released by the Green Building Council of Australia (GBCA) in 2009; and LEED Healthcare 2009, released by the United States Green Building Council (USGBC) in 2011. In addition, the German Association of Sustainable Building (DGNB) has also been developing the German Sustainable Building Evaluation Criteria (DGNB HC). In China, more and more scholars and policy makers have recognized the importance of assessment of sustainable development, and have adapted some tools and frameworks. China’s first comprehensive assessment standard for green building (the GBTs) was issued in 2006 (lately updated in 2014), promoting sustainability in the built-environment and raise awareness of environmental issues among architects, engineers, contractors as well as the public. However, healthcare building was not involved in the evaluation system of GBTs because of its complex medical procedures, strict requirements of indoor/outdoor environment and energy consumption of various functional rooms. Learn from advanced experience of GGHC, BREEAM, and LEED HC above, China’s first assessment criteria for green hospital/healthcare buildings was finally released in December 2015. Combined with both quantitative and qualitative assessment criteria, the standard highlight the differences between healthcare and other public buildings in meeting the functional needs for medical facilities and special groups. This paper has focused on the assessment criteria framework for sustainable healthcare buildings, for which the comparison of different rating systems is rather essential. Descriptive analysis is conducted together with the cross-matrix analysis to reveal rich information on green assessment criteria in a coherent manner. The research intends to know whether the green elements for healthcare buildings in China are different from those conducted in other countries, and how to improve its assessment criteria framework.

Keywords: assessment criteria framework, green building design, healthcare building, building performance rating tool

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Authors: Zhao Gao, Eran Edirisinghe

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The production of an accurate sketch of a suspect based on a verbal description obtained from a witness is an essential task for most criminal investigations. The criminal investigation system employs specifically trained professional artists to manually draw a facial image of the suspect according to the descriptions of an eyewitness for subsequent identification. Within the advancement of Deep Learning, Recurrent Neural Networks (RNN) have shown great promise in Natural Language Processing (NLP) tasks. Additionally, Generative Adversarial Networks (GAN) have also proven to be very effective in image generation. In this study, a trained GAN conditioned on textual features such as keywords automatically encoded from a verbal description of a human face using an RNN is used to generate photo-realistic facial images for criminal investigations. The intention of the proposed system is to map corresponding features into text generated from verbal descriptions. With this, it becomes possible to generate many reasonably accurate alternatives to which the witness can use to hopefully identify a suspect from. This reduces subjectivity in decision making both by the eyewitness and the artist while giving an opportunity for the witness to evaluate and reconsider decisions. Furthermore, the proposed approach benefits law enforcement agencies by reducing the time taken to physically draw each potential sketch, thus increasing response times and mitigating potentially malicious human intervention. With publically available 'CelebFaces Attributes Dataset' (CelebA) and additionally providing verbal description as training data, the proposed architecture is able to effectively produce facial structures from given text. Word Embeddings are learnt by applying the RNN architecture in order to perform semantic parsing, the output of which is fed into the GAN for synthesizing photo-realistic images. Rather than the grid search method, a metaheuristic search based on genetic algorithms is applied to evolve the network with the intent of achieving optimal hyperparameters in a fraction the time of a typical brute force approach. With the exception of the ‘CelebA’ training database, further novel test cases are supplied to the network for evaluation. Witness reports detailing criminals from Interpol or other law enforcement agencies are sampled on the network. Using the descriptions provided, samples are generated and compared with the ground truth images of a criminal in order to calculate the similarities. Two factors are used for performance evaluation: The Structural Similarity Index (SSIM) and the Peak Signal-to-Noise Ratio (PSNR). A high percentile output from this performance matrix should attribute to demonstrating the accuracy, in hope of proving that the proposed approach can be an effective tool for law enforcement agencies. The proposed approach to criminal facial image generation has potential to increase the ratio of criminal cases that can be ultimately resolved using eyewitness information gathering.

Keywords: RNN, GAN, NLP, facial composition, criminal investigation

Procedia PDF Downloads 144

Authors: D. Ficai, A. Ficai, D. Gudovan, I. A. Gudovan, I. Ardelean, R. Trusca, E. Andronescu, V. Mitran, A. Cimpean

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In the last years, scientists struggled hardly to mimic bone structures to develop implants and biostructures which present higher biocompatibility and reduced rejection rate. One way to obtain this goal is to use similar materials as that of bone, namely collagen/hydroxyapatite composite materials. However, it is very important to tailor both compositions but also the microstructure of the bone that would ensure both the optimal osteointegartion and the mechanical properties required by the application. In this study, new collagen/hydroxyapatites composite materials doped with Cu, Li, Mn, Zn were successfully prepared. The synthesis method is described below: weight the Ca(OH)₂ mass, i.e., 7,3067g, and ZnCl₂ (0.134g), CuSO₄ (0.159g), LiCO₃ (0.133g), MnCl₂.4H₂O (0.1971g), and suspend in 100ml distilled water under magnetic stirring. The solution thus obtained is added a solution of NaH₂PO₄*H2O (8.247g dissolved in 50ml distilled water) under slow dropping of 1 ml/min followed by adjusting the pH to 9.5 with HCl and finally filter and wash until neutral pH. The as-obtained slurry was dried in the oven at 80°C and then calcined at 600°C in order to ensure a proper purification of the final product of organic phases, also inducing a proper sterilization of the mixture before insertion into the collagen matrix. The collagen/hydroxyapatite composite materials are tailored from morphological point of view to optimize their biocompatibility and bio-integration against mechanical properties whereas the addition of the dopants is aimed to improve the biological activity of the samples. The addition of transitional metals can improve the biocompatibility and especially the osteoblasts adhesion (Mn²⁺) or to induce slightly better osteoblast differentiation of the osteoblast, Zn²⁺ being a cofactor for many enzymes including those responsible for cell differentiation. If the amount is too high, the final material can become toxic and lose all of its biocompatibility. In order to achieve a good biocompatibility and not reach the cytotoxic effect, the amount of transitional metals added has to be maintained at low levels (0.5% molar). The amount of transitional metals entering into the elemental cell of HA will be verified using inductively-coupled plasma mass spectrometric system. This highly sensitive technique is necessary, because, at such low levels of transitional metals, the difference between biocompatible and cytotoxic is a very thin line, thus requiring proper and thorough investigation using a precise technique. In order to determine the structure and morphology of the obtained composite materials, IR spectroscopy, X-Ray diffraction (XRD), scanning electron microscopy (SEM), and Energy Dispersive X-Ray Spectrometry (EDS) were used. Acknowledgment: The present work was possible due to the EU-funding grant POSCCE-A2O2.2.1-2013-1, Project No. 638/12.03.2014, code SMIS-CSNR 48652. The financial contribution received from the national project “Biomimetic porous structures obtained by 3D printing developed for bone tissue engineering (BIOGRAFTPRINT), No. 127PED/2017 is also highly acknowledged.

Keywords: collagen, composite materials, hydroxyapatite, bone tissue engineering

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Authors: V. Giacometti, R. Mirabelli, V. Patera, D. Pinci, A. Sarti, A. Sciubba, G. Traini, M. Marafini

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The particle therapy (PT) is a very modern technique of non invasive radiotherapy mainly devoted to the treatment of tumours untreatable with surgery or conventional radiotherapy, because localised closely to organ at risk (OaR). Nowadays, PT is available in about 55 centres in the word and only the 20\% of them are able to treat with carbon ion beam. However, the efficiency of the ion-beam treatments is so impressive that many new centres are in construction. The interest in this powerful technology lies to the main characteristic of PT: the high irradiation precision and conformity of the dose released to the tumour with the simultaneous preservation of the adjacent healthy tissue. However, the beam interactions with the patient produce a large component of secondary particles whose additional dose has to be taken into account during the definition of the treatment planning. Despite, the largest fraction of the dose is released to the tumour volume, a non-negligible amount is deposed in other body regions, mainly due to the scattering and nuclear interactions of the neutrons within the patient body. One of the main concerns in PT treatments is the possible occurrence of secondary malignant neoplasm (SMN). While SMNs can be developed up to decades after the treatments, their incidence impacts directly life quality of the cancer survivors, in particular in pediatric patients. Dedicated Treatment Planning Systems (TPS) are used to predict the normal tissue toxicity including the risk of late complications induced by the additional dose released by secondary neutrons. However, no precise measurement of secondary neutrons flux is available, as well as their energy and angular distributions: an accurate characterization is needed in order to improve TPS and reduce safety margins. The project MONDO (MOnitor for Neutron Dose in hadrOntherapy) is devoted to the construction of a secondary neutron tracker tailored to the characterization of that secondary neutron component. The detector, based on the tracking of the recoil protons produced in double-elastic scattering interactions, is a matrix of thin scintillating fibres, arranged in layer x-y oriented. The final size of the object is 10 x 10 x 20 cm3 (squared 250µm scint. fibres, double cladding). The readout of the fibres is carried out with a dedicated SPAD Array Sensor (SBAM) realised in CMOS technology by FBK (Fondazione Bruno Kessler). The detector is under development as well as the SBAM sensor and it is expected to be fully constructed for the end of the year. MONDO will make data tacking campaigns at the TIFPA Proton Therapy Center of Trento, at the CNAO (Pavia) and at HIT (Heidelberg) with carbon ion in order to characterize the neutron component and predict the additional dose delivered on the patients with much more precision and to drastically reduce the actual safety margins. Preliminary measurements with charged particles beams and MonteCarlo FLUKA simulation will be presented.

Keywords: secondary neutrons, particle therapy, tracking detector, elastic scattering

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Authors: Andres Nieto-Leal, Victor N. Kaliakin, Tania P. Molina

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The nature of most engineering materials is quite complex. It is, therefore, difficult to devise a general mathematical model that will cover all possible ranges and types of excitation and behavior of a given material. As a result, the development of mathematical models is based upon simplifying assumptions regarding material behavior. Such simplifications result in some material idealization; for example, one of the simplest material idealization is to assume that the material behavior obeys the elasticity. However, soils are nonhomogeneous, anisotropic, path-dependent materials that exhibit nonlinear stress-strain relationships, changes in volume under shear, dilatancy, as well as time-, rate- and temperature-dependent behavior. Over the years, many constitutive models, possessing different levels of sophistication, have been developed to simulate the behavior geomaterials, particularly cohesive soils. Early in the development of constitutive models, it became evident that elastic or standard elastoplastic formulations, employing purely isotropic hardening and predicated in the existence of a yield surface surrounding a purely elastic domain, were incapable of realistically simulating the behavior of geomaterials. Accordingly, more sophisticated constitutive models have been developed; for example, the bounding surface elastoplasticity. The essence of the bounding surface concept is the hypothesis that plastic deformations can occur for stress states either within or on the bounding surface. Thus, unlike classical yield surface elastoplasticity, the plastic states are not restricted only to those lying on a surface. Elastoplastic bounding surface models have been improved; however, there is still need to improve their capabilities in simulating the response of anisotropically consolidated cohesive soils, especially the response in extension tests. Thus, in this work an improved constitutive model that can more accurately predict diverse stress-strain phenomena exhibited by cohesive soils was developed. Particularly, an improved rotational hardening rule that better simulate the response of cohesive soils in extension. The generalized definition of the bounding surface model provides a convenient and elegant framework for unifying various previous versions of the model for anisotropically consolidated cohesive soils. The Generalized Bounding Surface Model for cohesive soils is a fully three-dimensional, time-dependent model that accounts for both inherent and stress induced anisotropy employing a non-associative flow rule. The model numerical implementation in a computer code followed an adaptive multistep integration scheme in conjunction with local iteration and radial return. The one-step trapezoidal rule was used to get the stiffness matrix that defines the relationship between the stress increment and the strain increment. After testing the model in simulating the response of cohesive soils through extensive comparisons of model simulations to experimental data, it has been shown to give quite good simulations. The new model successfully simulates the response of different cohesive soils; for example, Cardiff Kaolin, Spestone Kaolin, and Lower Cromer Till. The simulated undrained stress paths, stress-strain response, and excess pore pressures are in very good agreement with the experimental values, especially in extension.

Keywords: bounding surface elastoplasticity, cohesive soils, constitutive model, modeling of geomaterials

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Authors: Marina Shakleina, Konstantin Shaklein, Stanislav Yakiro

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The digitalization of modern human life over the last decade has facilitated the acquisition, storage, and processing of data, which are used to detect changes in consumer preferences and to improve the internal efficiency of the production process. This emerging trend has attracted academic interest in the use of big data in research. The study focuses on modeling the social comfort of the Russian population for the period 2010-2021 using big data. Big data provides enormous opportunities for understanding human interactions at the scale of society with plenty of space and time dynamics. One of the most popular big data sources is Google Trends. The methodology for assessing social comfort using big data involves several steps: 1. 574 words were selected based on the Harvard IV-4 Dictionary adjusted to fit the reality of everyday Russian life. The set of keywords was further cleansed by excluding queries consisting of verbs and words with several lexical meanings. 2. Search queries were processed to ensure comparability of results: the transformation of data to a 10-point scale, elimination of popularity peaks, detrending, and deseasoning. The proposed methodology for keyword search and Google Trends processing was implemented in the form of a script in the Python programming language. 3. Block and summary integral indicators of social comfort were constructed using the first modified principal component resulting in weighting coefficients values of block components. According to the study, social comfort is described by 12 blocks: ‘health’, ‘education’, ‘social support’, ‘financial situation’, ‘employment’, ‘housing’, ‘ethical norms’, ‘security’, ‘political stability’, ‘leisure’, ‘environment’, ‘infrastructure’. According to the model, the summary integral indicator increased by 54% and was 4.631 points; the average annual rate was 3.6%, which is higher than the rate of economic growth by 2.7 p.p. The value of the indicator describing social comfort in Russia is determined by 26% by ‘social support’, 24% by ‘education’, 12% by ‘infrastructure’, 10% by ‘leisure’, and the remaining 28% by others. Among 25% of the most popular searches, 85% are of negative nature and are mainly related to the blocks ‘security’, ‘political stability’, ‘health’, for example, ‘crime rate’, ‘vulnerability’. Among the 25% most unpopular queries, 99% of the queries were positive and mostly related to the blocks ‘ethical norms’, ‘education’, ‘employment’, for example, ‘social package’, ‘recycling’. In conclusion, the introduction of the latent category ‘social comfort’ into the scientific vocabulary deepens the theory of the quality of life of the population in terms of the study of the involvement of an individual in the society and expanding the subjective aspect of the measurements of various indicators. Integral assessment of social comfort demonstrates the overall picture of the development of the phenomenon over time and space and quantitatively evaluates ongoing socio-economic policy. The application of big data in the assessment of latent categories gives stable results, which opens up possibilities for their practical implementation.

Keywords: big data, Google trends, integral indicator, social comfort

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Authors: Jyoti Sahu, Vinay A. Juvekar

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Electrolytes are often used to bring about salting-in and salting-out of organic molecules and polymers (e.g. polyethylene glycols/proteins) from the aqueous solutions. For quantification of these phenomena, a thermodynamic model which can accurately predict activity coefficient of electrolyte as a function of temperature is needed. The thermodynamics models available in the literature contain a large number of empirical parameters. These parameters are estimated using lower/upper critical solution temperature of the solution in the electrolyte/organic molecule at different temperatures. Since the number of parameters is large, inaccuracy can bethe creep in during their estimation, which can affect the reliability of prediction beyond the range in which these parameters are estimated. Cloud point of solution is related to its free energy through temperature and composition derivative. Hence, the Cloud point measurement can be used for accurate estimation of the temperature and composition dependence of parameters in the model for free energy. Hence, if we use a two pronged procedure in which we first use cloud point of solution to estimate some of the parameters of the thermodynamic model and determine the rest using osmotic coefficient data, we gain on two counts. First, since the parameters, estimated in each of the two steps, are fewer, we achieve higher accuracy of estimation. The second and more important gain is that the resulting model parameters are more sensitive to temperature. This is crucial when we wish to use the model outside temperatures window within which the parameter estimation is sought. The focus of the present work is to prove this proposition. We have used electrolyte (NaCl/Na2CO3)-water-organic molecule (Iso-propanol/ethanol) as the model system. The model of Robinson-Stokes-Glukauf is modified by incorporating the temperature dependent Flory-Huggins interaction parameters. The Helmholtz free energy expression contains, in addition to electrostatic and translational entropic contributions, three Flory-Huggins pairwise interaction contributions viz., and (w-water, p-polymer, s-salt). These parameters depend both on temperature and concentrations. The concentration dependence is expressed in the form of a quadratic expression involving the volume fractions of the interacting species. The temperature dependence is expressed in the form .To obtain the temperature-dependent interaction parameters for organic molecule-water and electrolyte-water systems, Critical solution temperature of electrolyte -water-organic molecules is measured using cloud point measuring apparatus The temperature and composition dependent interaction parameters for electrolyte-water-organic molecule are estimated through measurement of cloud point of solution. The model is used to estimate critical solution temperature (CST) of electrolyte water-organic molecules solution. We have experimentally determined the critical solution temperature of different compositions of electrolyte-water-organic molecule solution and compared the results with the estimates based on our model. The two sets of values show good agreement. On the other hand when only osmotic coefficients are used for estimation of the free energy model, CST predicted using the resulting model show poor agreement with the experiments. Thus, the importance of the CST data in the estimation of parameters of the thermodynamic model is confirmed through this work.

Keywords: concentrated electrolytes, Debye-Hückel theory, interaction parameters, Robinson-Stokes-Glueckauf model, Flory-Huggins model, critical solution temperature

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Authors: Benrithung Murry

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This paper highlights the biosocial determinants of health-seeking behavior in tribal population groups of northeast India, focusing on maternal and child health. The northeastern region of India is a conglomeration of several ethnic groups, most of which are scheduled as tribal groups. A total of 750 ever-married women in reproductive ages (15-49 years) were interviewed from three tribal groups of Nagaland, India using pre-tested and modified maternal health schedule. Data pertaining to reproductive performance of the mothers and their children health status were collected from 12 villages of Dimapur district, Nagaland, India. The sample for study comprises 212 Angami women, 267 Ao women, and 271 Sumi women, all of which belonging to tribal populations of Northeast India. Sex ratios of 15-49 years in these three populations are 1018.18, 1086.69, and 1106.92, respectively. 90% of the populations in the study are nuclear families, with about 10% of households falling below the poverty line as per the cutoffs for India. Female literacy level in these population groups is higher than the national average of 65.46%; however, about 30% of all married women are not engaged in any sort of earnings. Total fertility rates of these populations are alarming (Total Fertility Rate ≥ 6) and far from replacement fertility level, while infant mortality rates are found to be much lower than the national average of 34 per 1000. The perception and practice of maternal health in this region is unimpressive despite the availability of medical amenities. Only 3 % of mothers in the study have reported 4 times antenatal checkups during last two pregnancies. Other mothers have reported 1 to 3 times of antenatal checkups, but about 25% of them never visited a doctor during the entire pregnancy period. About 15% of mothers never took tetanus injection, while 40% of mothers never took iron folic supplements during pregnancy. Almost half of all women and their husbands do not use birth control measures even for the spacing of children, which has an immense impact on prenatal mortality mainly due to deliberate abortions: the percentage of prenatal mortality among Angami, Ao and Sumi populations is 44.88, 31.88 and 54.98, respectively per 1000 live births. The steep decline in fertility levels in most countries is a consequence of the increasing use of modern methods of contraception. However, among users of birth control measures in these populations, it is seen that most couples use it only after they have the desired number of children, thus its use having no substantial influence in reducing fertility. It is also seen that the majority of the children were only partially vaccinated. With many child deliveries being done at home, many newborns are not administered with polio at birth. Two-third of all children do not have complete basic immunization against polio, diphtheria, tetanus, pertussis, bacillus, and hepatitis besides others. Certain adherence to traditional beliefs and customs apart from the socio-economic factors is believed to have been operating in these populations, which determines their health-seeking behavior. While a more in-depth study combining biological, socio-cultural, economic, and genetic factors is suggested, there is an urgent need for intervention in these populations to combat with the poor maternal and child health status.

Keywords: case study, health behavior, mother and child, northeast india

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Authors: Muhammad Karim Ahmadzai

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Floods are natural phenomena and are an integral part of the water cycle. The majority of them are the result of climatic conditions, but are also affected by the geology and geomorphology of the area, topography and hydrology, the water permeability of the soil and the vegetation cover, as well as by all kinds of human activities and structures. However, from the moment that human lives are at risk and significant economic impact is recorded, this natural phenomenon becomes a natural disaster. Flood management is now a key issue at regional and local levels around the world, affecting human lives and activities. The majority of floods are unlikely to be fully predicted, but it is feasible to reduce their risks through appropriate management plans and constructions. The aim of this Case Study is to identify, and map areas of flood risk in the Khinch District of Panjshir Province, Afghanistan specifically in the area of Peshghore, causing numerous damages. The main purpose of this study is to evaluate the contribution of remote sensing technology and Geographic Information Systems (GIS) in assessing the susceptibility of this region to flood events. Panjsher is facing Seasonal floods and human interventions on streams caused floods. The beds of which have been trampled to build houses and hotels or have been converted into roads, are causing flooding after every heavy rainfall. The streams crossing settlements and areas with high touristic development have been intensively modified by humans, as the pressure for real estate development land is growing. In particular, several areas in Khinch are facing a high risk of extensive flood occurrence. This study concentrates on the construction of a flood susceptibility map, of the study area, by combining vulnerability elements, using the Analytical Hierarchy Process/ AHP. The Analytic Hierarchy Process, normally called AHP, is a powerful yet simple method for making decisions. It is commonly used for project prioritization and selection. AHP lets you capture your strategic goals as a set of weighted criteria that you then use to score projects. This method is used to provide weights for each criterion which Contributes to the Flood Event. After processing of a digital elevation model (DEM), important secondary data were extracted, such as the slope map, the flow direction and the flow accumulation. Together with additional thematic information (Landuse and Landcover, topographic wetness index, precipitation, Normalized Difference Vegetation Index, Elevation, River Density, Distance from River, Distance to Road, Slope), these led to the final Flood Risk Map. Finally, according to this map, the Priority Protection Areas and Villages and the structural and nonstructural measures were demonstrated to Minimize the Impacts of Floods on residential and Agricultural areas.

Keywords: flood hazard, flood risk map, flood mitigation measures, AHP analysis

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Authors: Deb Kumar Shah, M. Shaheer Akhtar, Ha Ryeon Lee, O-Bong Yang, Chong Yeal Kim

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The crystalline silicon (Si) solar cells are highly renowned photovoltaic technology and well-established as the commercial solar technology. Most of the solar panels are globally installed with the crystalline Si solar modules. At the present scenario, the major photovoltaic (PV) market is shared by c-Si solar cells, but the cost of c-Si panels are still very high as compared with the other PV technology. In order to reduce the cost of Si solar panels, few necessary steps such as low-cost Si manufacturing, cheap antireflection coating materials, inexpensive solar panel manufacturing are to be considered. It is known that the antireflection (AR) layer in c-Si solar cell is an important component to reduce Fresnel reflection for improving the overall conversion efficiency. Generally, Si wafer exhibits the 30% reflection because it normally poses the two major intrinsic drawbacks such as; the spectral mismatch loss and the high Fresnel reflection loss due to the high contrast of refractive indices between air and silicon wafer. In recent years, researchers and scientists are highly devoted to a lot of researches in the field of searching effective and low-cost AR materials. Silicon nitride (SiNx) is well-known AR materials in commercial c-Si solar cells due to its good deposition and interaction with passivated Si surfaces. However, the deposition of SiNx AR is usually performed by expensive plasma enhanced chemical vapor deposition (PECVD) process which could have several demerits like difficult handling and damaging the Si substrate by plasma when secondary electrons collide with the wafer surface for AR coating. It is very important to explore new, low cost and effective AR deposition process to cut the manufacturing cost of c-Si solar cells. One can also be realized that a nano-texturing process like the growth of nanowires, nanorods, nanopyramids, nanopillars, etc. on Si wafer can provide a low reflection on the surface of Si wafer based solar cells. The above nanostructures might be enhanced the antireflection property which provides the larger surface area and effective light trapping. In this work, we report on the development of crystalline Si solar cells without using the AR layer. The Silicon wafer was modified by growing nanowires like Si nanostructures using the wet controlled etching method and directly used for the fabrication of Si solar cell without AR. The nanostructures over Si wafer were optimized in terms of sizes, lengths, and densities by changing the etching conditions. Well-defined and aligned wires like structures were achieved when the etching time is 20 to 30 min. The prepared Si nanostructured displayed the minimum reflectance ~1.64% at 850 nm with the average reflectance of ~2.25% in the wavelength range from 400-1000 nm. The nanostructured Si wafer based solar cells achieved the comparable power conversion efficiency in comparison with c-Si solar cells with SiNx AR layer. From this study, it is confirmed that the reported method (controlled wet etching) is an easy, facile method for preparation of nanostructured like wires on Si wafer with low reflectance in the whole visible region, which has greater prospects in developing c-Si solar cells without AR layer at low cost.

Keywords: chemical etching, conversion efficiency, silicon nanostructures, silicon solar cells, surface modification

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Authors: Ayon Mukherjee

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Covariate-adjusted response-adaptive (CARA) designs use the available responses to skew the treatment allocation in a clinical trial in towards treatment found at an interim stage to be best for a given patient's covariate profile. Extensive research has been done on various aspects of CARA designs with the patient responses assumed to follow a parametric model. However, ranges of application for such designs are limited in real-life clinical trials where the responses infrequently fit a certain parametric form. On the other hand, robust estimates for the covariate-adjusted treatment effects are obtained from the parametric assumption. To balance these two requirements, designs are developed which are free from distributional assumptions about the survival responses, relying only on the assumption of proportional hazards for the two treatment arms. The proposed designs are developed by deriving two types of optimum allocation designs, and also by using a distribution function to link the past allocation, covariate and response histories to the present allocation. The optimal designs are based on biased coin procedures, with a bias towards the better treatment arm. These are the doubly-adaptive biased coin design (DBCD) and the efficient randomized adaptive design (ERADE). The treatment allocation proportions for these designs converge to the expected target values, which are functions of the Cox regression coefficients that are estimated sequentially. These expected target values are derived based on constrained optimization problems and are updated as information accrues with sequential arrival of patients. The design based on the link function is derived using the distribution function of a probit model whose parameters are adjusted based on the covariate profile of the incoming patient. To apply such designs, the treatment allocation probabilities are sequentially modified based on the treatment allocation history, response history, previous patients’ covariates and also the covariates of the incoming patient. Given these information, an expression is obtained for the conditional probability of a patient allocation to a treatment arm. Based on simulation studies, it is found that the ERADE is preferable to the DBCD when the main aim is to minimize the variance of the observed allocation proportion and to maximize the power of the Wald test for a treatment difference. However, the former procedure being discrete tends to be slower in converging towards the expected target allocation proportion. The link function based design achieves the highest skewness of patient allocation to the best treatment arm and thus ethically is the best design. Other comparative merits of the proposed designs have been highlighted and their preferred areas of application are discussed. It is concluded that the proposed CARA designs can be considered as suitable alternatives to the traditional balanced randomization designs in survival trials in terms of the power of the Wald test, provided that response data are available during the recruitment phase of the trial to enable adaptations to the designs. Moreover, the proposed designs enable more patients to get treated with the better treatment during the trial thus making the designs more ethically attractive to the patients. An existing clinical trial has been redesigned using these methods.

Keywords: censored response, Cox regression, efficiency, ethics, optimal allocation, power, variability

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Authors: Ife Elegbeleye, Nnditshedzeni Eric, Regina Maphanga, Femi Elegbeleye, Femi Agunbiade

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The global potential of other renewable energy sources such as wind, hydroelectric, bio-mass, and geothermal is estimated to be approximately 13 %, with hydroelectricity constituting a larger percentage. Sunlight provides by far the largest of all carbon-neutral energy sources. More energy from the sunlight strikes the Earth in one hour (4.3 × 1020 J) than all the energy consumed on the planet in a year (4.1 × 1020 J), hence, solar energy remains the most abundant clean, renewable energy resources for mankind. Photovoltaic (PV) devices such as silicon solar cells, dye sensitized solar cells are utilized for harnessing solar energy. Polyene-diphenylaniline organic molecules are important sets of molecules that has stirred many research interest as photosensitizers in TiO₂ semiconductor-based dye sensitized solar cells (DSSCs). The advantages of organic dye molecule over metal-based complexes are higher extinction coefficient, moderate cost, good environmental compatibility, and electrochemical properties. The polyene-diphenylaniline organic dyes with basic configuration of donor-π-acceptor are affordable, easy to synthesize and possess chemical structures that can easily be modified to optimize their photocatalytic and spectral properties. The enormous interest in polyene-diphenylaniline dyes as photosensitizers is due to their fascinating spectral properties which include visible light to near infra-red-light absorption. In this work, density functional theory approach via GPAW software, Avogadro and ASE were employed to study the effect of methoxy functionalized group on the spectral properties of polyene-diphenylaniline dyes and their photons absorbing characteristics in the visible region to near infrared region of the solar spectrum. Our results showed that the two-phenyl based complexes D5 and D7 exhibits maximum absorption peaks at 750 nm and 850 nm, while D9 and D11 with methoxy group shows maximum absorption peak at 800 nm and 900 nm respectively. The highest absorption wavelength is notable for D9 and D11 containing additional polyene and methoxy groups. Also, D9 and D11 chromophores with the methoxy group shows lower energy gap of 0.98 and 0.85 respectively than the corresponding D5 and D7 dyes complexes with energy gap of 1.32 and 1.08. The analysis of their electron injection kinetics ∆Ginject into the band gap of TiO₂ shows that D9 and D11 with the methoxy group has higher electron injection kinetics of -2.070 and -2.030 than the corresponding polyene-diphenylaniline complexes without the addition of polyene group with ∆Ginject values of -2.820 and -2.130 respectively. Our findings suggest that the addition of functionalized group as an extension of the organic complexes results in higher light harvesting efficiencies and bathochromic shift of the absorption spectra to higher wavelength which suggest higher current densities and open circuit voltage in DSSCs. The study suggests that the photocatalytic properties of organic chromophores/complexes with donor-π-acceptor configuration can be enhanced by the addition of functionalized groups.

Keywords: renewable energy resource, solar energy, dye sensitized solar cells, polyene-diphenylaniline organic chromophores

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Authors: G. Magalhães-Mota, C. Magro, S. Sério, E. Mateus, P. A. Ribeiro, A. B. Ribeiro, M. Raposo

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Triclosan [5-chloro-2-(2,4-dichlorophenoxy) phenol], belonging to the class of Pharmaceuticals and Personal Care Products (PPCPs), is a broad-spectrum antimicrobial agent and bactericide. Because of its antimicrobial efficacy, it is widely used in personal health and skin care products, such as soaps, detergents, hand cleansers, cosmetics, toothpastes, etc. However, it has been considered to disrupt the endocrine system, for instance, thyroid hormone homeostasis and possibly the reproductive system. Considering the widespread use of triclosan, it is expected that environmental and food safety problems regarding triclosan will increase dramatically. Triclosan has been found in river water samples in both North America and Europe and is likely widely distributed wherever triclosan-containing products are used. Although significant amounts are removed in sewage plants, considerable quantities remain in the sewage effluent, initiating widespread environmental contamination. Triclosan undergoes bioconversion to methyl-triclosan, which has been demonstrated to bio accumulate in fish. In addition, triclosan has been found in human urine samples from persons with no known industrial exposure and in significant amounts in samples of mother's milk, demonstrating its presence in humans. The action of sunlight in river water is known to turn triclosan into dioxin derivatives and raises the possibility of pharmacological dangers not envisioned when the compound was originally utilized. The aim of this work is to detect low concentrations of triclosan in an aqueous complex matrix through the use of a sensor array system, following the electronic tongue concept based on impedance spectroscopy. To achieve this goal, we selected the appropriate molecules to the sensor so that there is a high affinity for triclosan and whose sensitivity ensures the detection of concentrations of at least nano-molar. Thin films of organic molecules and oxides have been produced by the layer-by-layer (LbL) technique and sputtered onto glass solid supports already covered by gold interdigitated electrodes. By submerging the films in complex aqueous solutions with different concentrations of triclosan, resistance and capacitance values were obtained at different frequencies. The preliminary results showed that an array of interdigitated electrodes sensor coated or uncoated with different LbL and films, can be used to detect TCS traces in aqueous solutions in a wide range concentration, from 10⁻¹² to 10⁻⁶ M. The PCA method was applied to the measured data, in order to differentiate the solutions with different concentrations of TCS. Moreover, was also possible to trace a curve, the plot of the logarithm of resistance versus the logarithm of concentration, which allowed us to fit the plotted data points with a decreasing straight line with a slope of 0.022 ± 0.006 which corresponds to the best sensitivity of our sensor. To find the sensor resolution near of the smallest concentration (Cs) used, 1pM, the minimum measured value which can be measured with resolution is 0.006, so the ∆logC =0.006/0.022=0.273, and, therefore, C-Cs~0.9 pM. This leads to a sensor resolution of 0.9 pM for the smallest concentration used, 1pM. This attained detection limit is lower than the values obtained in the literature.

Keywords: triclosan, layer-by-layer, impedance spectroscopy, electronic tongue

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Authors: Syfur Rahman, Mohammad J. Khattak

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Every year a huge quantity of recycling concrete aggregate (RCA) is generated in the United States of America. Utilization of RCA can solve the storage problem, prevent environmental pollution, and reduce the construction cost. However, due to the overall low strength and durability characteristics of RCA, its usages are limited to a certain area like a landfill, low strength base material, replacement of a few percentages of virgin aggregates in Portland cement concrete, etc. This study focuses on the improvement of the strength and durability characteristics of RCA by introducing the concept of roller-compacted geopolymer concrete. In this research, developed roller-compacted geopolymer concrete (RCGPC) and roller-compacted cement concrete (RCC) mixtures containing 100% recycled concrete aggregate were evaluated and compared. Several selected RCGPC mixtures were investigated to find out the effect of mixture variables, including sodium hydroxide (NaOH) molar concentration, sodium silicate (Na₂SiO₃), to sodium hydroxide (NaOH) ratio on the strength, stiffness and durability characteristics of the developed RCGPC. Sodium hydroxide (NaOH) and sodium silicate (Na₂SiO₃) were mixed in different ratios to synthesize the alkali activator. American Concrete Pavement Association (ACPA) recommended RCC gradation was used with a maximum nominal aggregate size of 19 mm with a 4% fine particle passing 0.075 mm sieve. The mixtures were made using NaOH molar concentration of 8M and 10M along with, Na₂SiO₃ to NaOH ratio of 0 and 1 by mass and 15% class F fly ash. Optimum alkali content and moisture content were determined for each RCGPC and RCC mixtures, respectively, using modified proctor test. Compressive strength, semi-circular bending beam strength, and dynamic modulus test were conducted to evaluate the mechanistic characteristics of both mixtures. To determine the optimum curing conditions for RCGPC, effects of different curing temperature and curing duration on compressive strength were also studied. Sulphate attack and freeze-thaw tests were also carried out to assess the durability properties of the developed mixtures. X-ray diffraction (XRD) was used for morphology and microstructure analysis. From the optimum moisture content results, it was found that RCGPC has high alkali content, which was mainly due to the high absorption capacity of RCA. It was found that the mixtures with Na₂SiO₃ to NaOH ratio of 1 yielded about 60% higher compressive strength than the ratio of 0. Further, the mixtures using 10M NaOH concentrations and alkali ratio of 1 produced about 28 MPa of compressive strength, which was around 33% higher than 8M NaOH mixtures. Similar results were obtained for elastic and dynamic modulus of the mixtures. On the other hand, the semi-circular bending beam strength remained the same for both 8 and 10 molar NaOH geopolymer mixtures. Formation of new geopolymeric compounds and chemical bonds in the newly formed novel RCGPC mixtures were also discovered using XRD analysis. The results of mechanical and durability testing further revealed that RCGPC performed similarly to that of RCC mixtures. Based on the results of mechanical and durability testing, the developed RCGPC mixtures using 100% recycled concrete could be used as a cost-effective solution for the construction of pavement structures.

Keywords: roller compacted concrete, geopolymer concrete, recycled concrete aggregate, concrete pavement, fly ash

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Authors: Fabienne Samyn, Pauline Tranchard, Sophie Duquesne, Emilie Goncalves, Bruno Estebe, Serge Boubigot

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Stringent fire safety regulations are enforced in the aeronautical industry due to the consequences that potential fire event on an aircraft might imply. This is so much true that the fire issue is considered right from the design of the aircraft structure. Due to the incorporation of an increasing amount of polymer matrix composites in replacement of more conventional materials like metals, the nature of the fire risks is changing. The choice of materials used is consequently of prime importance as well as the evaluation of its resistance to fire. The fire testing is mostly done using the so-called certification tests according to standards such as the ISO2685:1998(E). The latter describes a protocol to evaluate the fire resistance of structures located in fire zone (ability to withstand fire for 5min). The test consists in exposing an at least 300x300mm² sample to an 1100°C propane flame with a calibrated heat flux of 116kW/m². This type of test is time-consuming, expensive and gives access to limited information in terms of fire behavior of the materials (pass or fail test). Consequently, it can barely be used for material development purposes. In this context, the laboratory UMET in collaboration with industrial partners has developed a horizontal and a vertical small-scale instrumented fire benches for the characterization of the fire behavior of composites. The benches using smaller samples (no more than 150x150mm²) enables to cut downs costs and hence to increase sampling throughput. However, the main added value of our benches is the instrumentation used to collect useful information to understand the behavior of the materials. Indeed, measurements of the sample backside temperature are performed using IR camera in both configurations. In addition, for the vertical set up, a complete characterization of the degradation process, can be achieved via mass loss measurements and quantification of the gasses released during the tests. These benches have been used to characterize and study the fire behavior of aeronautical carbon/epoxy composites. The horizontal set up has been used in particular to study the performances and durability of protective intumescent coating on 2mm thick 2D laminates. The efficiency of this approach has been validated, and the optimized coating thickness has been determined as well as the performances after aging. Reductions of the performances after aging were attributed to the migration of some of the coating additives. The vertical set up has enabled to investigate the degradation process of composites under fire. An isotropic and a unidirectional 4mm thick laminates have been characterized using the bench and post-fire analyses. The mass loss measurements and the gas phase analyses of both composites do not present significant differences unlike the temperature profiles in the thickness of the samples. The differences have been attributed to differences of thermal conductivity as well as delamination that is much more pronounced for the isotropic composite (observed on the IR-images). This has been confirmed by X-ray microtomography. The developed benches have proven to be valuable tools to develop fire safe composites.

Keywords: aeronautical carbon/epoxy composite, durability, intumescent coating, small-scale ‘ISO 2685 like’ fire resistance test, X-ray microtomography

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

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Authors: Ifeyinwa Victor-Uadiale, Georgina Pearson, Sophie Witter, D. Reidpath

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Introduction: Smoking, alcohol misuse, unhealthy diet, and physical inactivity are the primary drivers of noncommunicable diseases (NCD), including cardiovascular diseases, cancers, respiratory diseases, and diabetes, worldwide. Collectively, these diseases are the leading cause of all global deaths, most of which are premature, affecting people between 30 and 70 years. Empirical evidence suggests that these risk behaviors can be modified by community-based interventions (CBI). However, there is little insight into the mechanisms and contextual factors of successful community interventions that impact risk behaviours for chronic diseases. This study examined “Under what circumstances, for whom, and how, do community-based interventions modify smoking, alcohol use, unhealthy diet, and physical inactivity among adults”. Adopting the Capability (C), Opportunity (O), Motivation (M), Behavior (B) (COM-B) framework for behaviour change, it sought to: (1) identify the mechanisms through which CBIs could reduce tobacco use and alcohol consumption and increase physical activity and the consumption of healthy diets and (2) examine the contextual factors that trigger the impact of these mechanisms on these risk behaviours among adults. Methods: Pawson’s realist review method was used to examine the literature. Empirical evidence and theoretical understanding were combined to develop a realist program theory that explains how CBIs influence NCD risk behaviours. Documents published between 2002 and 2020 were systematically searched in five electronic databases (CINAHL, Cochrane Library, Medline, ProQuest Central, and PsycINFO). They were included if they reported on community-based interventions aimed at cardiovascular diseases, cancers, respiratory diseases, and diabetes in a global context; and had an outcome targeted at smoking, alcohol, physical activity, and diet. Findings: Twenty-nine scientific documents were retrieved and included in the review. Over half of them (n = 18; 62%) focused on three of the four risk behaviours investigated in this review. The review identified four mechanisms: capability, opportunity, motivation, and social support that are likely to change the dietary and physical activity behaviours in adults given certain contexts. There were weak explanations of how the identified mechanisms could likely change smoking and alcohol consumption habits. In addition, eight contextual factors that may affect how these mechanisms impact physical activity and dietary behaviours were identified: suitability to work and family obligations, risk status awareness, socioeconomic status, literacy level, perceived need, availability and access to resources, culture, and group format. Conclusion: The findings suggest that CBIs are likely to improve the physical activity and dietary habits of adults if the intervention function seeks to educate, incentivize, change the environment, and model the right behaviours. The review applies and advances theory, realist research, and the design and implementation of community-based interventions for NCD prevention.

Keywords: community-based interventions, noncommunicable disease, realist program theory, risk behaviors

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Authors: Cristina Opris, Bogdan Cojocaru, Madalina Tudorache, Simona M. Coman, Vasile I. Parvulescu, Camelia Bala, Bahir Duraki, Jeroen A. Van Bokhoven

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The tremendous achievements in the development of the society concretized by more sophisticated materials and systems are merely based on non-renewable resources. Consequently, after more than two centuries of intensive development, among others, we are faced with the decrease of the fossil fuel reserves, an increased impact of the greenhouse gases on the environment, and economic effects caused by the fluctuations in oil and mineral resource prices. The use of biomass may solve part of these problems, and recent analyses demonstrated that from the perspective of the reduction of the emissions of carbon dioxide, its valorization may bring important advantages conditioned by the usage of genetic modified fast growing trees or wastes, as primary sources. In this context, the abundance and complex structure of lignin may offer various possibilities of exploitation. However, its transformation in fuels or chemicals supposes a complex chemistry involving the cleavage of C-O and C-C bonds and altering of the functional groups. Chemistry offered various solutions in this sense. However, despite the intense work, there are still many drawbacks limiting the industrial application. Thus, the proposed technologies considered mainly homogeneous catalysts meaning expensive noble metals based systems that are hard to be recovered at the end of the reaction. Also, the reactions were carried out in organic solvents that are not acceptable today from the environmental point of view. To avoid these problems, the concept of this work was to investigate the synthesis of superparamagnetic core shell catalysts for the fragmentation of lignin directly in the aqueous phase. The magnetic nanoparticles were covered with a nanoshell of an oxide (niobia) with a double role: to protect the magnetic nanoparticles and to generate a proper (acidic) catalytic function and, on this composite, cobalt nanoparticles were deposed in order to catalyze the C-C bond splitting. With this purpose, we developed a protocol to prepare multifunctional and magnetic separable nano-composite Co@Nb2O5@Fe3O4 catalysts. We have also established an analytic protocol for the identification and quantification of the fragments resulted from lignin depolymerization in both liquid and solid phase. The fragmentation of various lignins occurred on the prepared materials in high yields and with very good selectivity in the desired fragments. The optimization of the catalyst composition indicated a cobalt loading of 4wt% as optimal. Working at 180 oC and 10 atm H2 this catalyst allowed a conversion of lignin up to 60% leading to a mixture containing over 96% in C20-C28 and C29-C37 fragments that were then completely fragmented to C12-C16 in a second stage. The investigated catalysts were completely recyclable, and no leaching of the elements included in the composition was determined by inductively coupled plasma optical emission spectrometry (ICP-OES).

Keywords: superparamagnetic core-shell catalysts, environmental production of fuels, renewable lignin, recyclable catalysts

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Authors: Omolola Ojetayo, Emmanuel Garuba, Obinna Ajunwa, Abiodun A. Onilude

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Introduction: Biofilm is a functional community of microorganisms that are associated with a surface or an interface. These adherent cells become embedded within an extracellular matrix composed of polymeric substances, i.e., biofilms refer to biological deposits consisting of both microbes and their extracellular products on biotic and abiotic surfaces. Despite their detrimental effects in medicine, biofilms as natural cell immobilization have found several applications in biotechnology, such as in the treatment of wastewater, bioremediation and biodegradation, desulfurization of gas, and conversion of agro-derived materials into alcohols and organic acids. The means of enhancing immobilized cells have been chemical-inductive, and this affects the medium composition and final product. Physical factors including electrical, magnetic, and electromagnetic flux have shown potential for enhancing biofilms depending on the bacterial species, nature, and intensity of emitted signals, the duration of exposure, and substratum used. However, the concept of cell immobilisation by electrical and magnetic induction is still underexplored. Methods: To assess the effects of physical factors on biofilm formation, six American typed culture collection (Acetobacter aceti ATCC15973, Pseudomonas aeruginosa ATCC9027, Serratia marcescens ATCC14756, Gluconobacter oxydans ATCC19357, Rhodobacter sphaeroides ATCC17023, and Bacillus subtilis ATCC6633) were used. Standard culture techniques for bacterial cells were adopted. Natural autoimmobilisation potentials of test bacteria were carried out by simple biofilms ring formation on tubes, while crystal violet binding assay techniques were adopted in the characterisation of biofilm quantity. Electroinduction of bacterial cells by direct current (DC) application in cell broth, static magnetic field exposure, and electromagnetic flux were carried out, and autoimmobilisation of cells in a biofilm pattern was determined on various substrata tested, including wood, glass, steel, polyvinylchloride (PVC) and polyethylene terephthalate. Biot Savart law was used in quantifying magnetic field intensity, and statistical analyses of data obtained were carried out using the analyses of variance (ANOVA) as well as other statistical tools. Results: Biofilm formation by the selected test bacteria was enhanced by the physical factors applied. Electromagnetic induction had the greatest effect on biofilm formation, with magnetic induction producing the least effect across all substrata used. Microbial cell-cell communication could be a possible means via which physical signals affected the cells in a polarisable manner. Conclusion: The enhancement of biofilm formation by bacteria using physical factors has shown that their inherent capability as a cell immobilization method can be further optimised for industrial applications. A possible relationship between the presence of voltage-dependent channels, mechanosensitive channels, and bacterial biofilms could shed more light on this phenomenon.

Keywords: bacteria, biofilm, cell immobilization, electromagnetic induction, substrata

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Authors: Hoda Manafian, Stephen Holland

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Problem statement: Rural areas in Iran are one of the most popular tourism destinations. Abyaneh Village is one of them with a long history behind it (more than 1500 years) which is a national heritage site and also is nominated as a world heritage site in UNESCO tentative list from 2007. There is a considerable foundation of religious-cultural heritage and also agricultural history and activities. However, this heritage site suffers from mass tourism which is beyond its social and physical carrying capacity, since the annual number of tourists exceed 500,000. While there are four adjacent villages around Abyaneh which can benefit from advantages of tourism. Local managers also can at the same time prorate the tourists’ flux of Abyaneh on those other villages especially in high-season. The other villages have some cultural and natural tourism attractions as well. Goal: The main goal of this study is to identify a feasible development strategy according to the current strengths, weaknesses, opportunities and threats of rural tourism in this area (Abyaneh Village and four adjacent villages). This development strategy can lead to sustainable management of these destinations. Method: To this end, we used SWOT analysis as a well-established tool for conducting a situational analysis to define a sustainable development strategy. The procedures included following steps: 1) Extracting variables of SWOT chart based on interviewing tourism experts (n=13), local elites (n=17) and personal observations of researcher. 2) Ranking the extracted variables from 1-5 by 13 tourism experts in Isfahan Cultural Heritage, Handcrafts and Tourism Organization (ICHTO). 3) Assigning weights to the ranked variables using Expert Choice Software and the method of Analytical Hierarchical Process (AHP). 4) Defining the Total Weighted Score (TWS) for each part of SWOT chart. 5) Identifying the strategic position according to the TWS 6) Selecting the best development strategy based on the defined position using the Strategic Position and Action Evaluation (SPACE) matrix. 7) Assessing the Probability of Strategic Success (PSS) for the preferred strategy using relevant formulas. 8) Defining two feasible alternatives for sustainable development. Results and recommendations: Cultural heritage attractions were first-ranked variable in strength chart and also lack of sufficient amenities for one-day tourists (catering, restrooms, parking, and accommodation) was firs-ranked weakness. The strategic position was in ST (Strength-Threat) quadrant which is a maxi-mini position. According this position we would suggest ‘Competitive Strategy’ as a development strategy which means relying on strengths in order to neutralization threats. The result of Probability of Strategic Success assessment which was 0.6 shows that this strategy could be successful. The preferred approach for competitive strategy could be rebranding the market of tourism in this area. Rebranding the market can be achieved by two main alternatives which are based on the current strengths and threats: 1) Defining a ‘Heritage Corridor’ from first adjacent village to Abyaneh as a final destination. 2) Focus on ‘educational tourism’ versus mass tourism and also green tourism by developing agritourism in that corridor.

Keywords: Abyaneh village, rural tourism, SWOT analysis, sustainable strategies

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Authors: G. M. Vlasceanu, H. Iovu, E. Vasile, M. Ionita

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Herein, the synthesis and characterization of chitosan-gelatin highly porous scaffold reinforced with graphene oxide, and hydroxyapatite (HAp), crosslinked with genipin was targeted. In tissue engineering, chitosan and gelatin are two of the most robust biopolymers with wide applicability due to intrinsic biocompatibility, biodegradability, low antigenicity properties, affordability, and ease of processing. HAp, per its exceptional activity in tuning cell-matrix interactions, is acknowledged for its capability of sustaining cellular proliferation by promoting bone-like native micro-media for cell adjustment. Genipin is regarded as a top class cross-linker, while graphene oxide (GO) is viewed as one of the most performant and versatile fillers. The composites with natural bone HAp/biopolymer ratio were obtained by cascading sonochemical treatments, followed by uncomplicated casting methods and by freeze-drying. Their structure was characterized by Fourier Transform Infrared Spectroscopy and X-ray Diffraction, while overall morphology was investigated by Scanning Electron Microscopy (SEM) and micro-Computer Tomography (µ-CT). Ensuing that, in vitro enzyme degradation was performed to detect the most promising compositions for the development of in vivo assays. Suitable GO dispersion was ascertained within the biopolymer mix as nanolayers specific signals lack in both FTIR and XRD spectra, and the specific spectral features of the polymers persisted with GO load enhancement. Overall, correlations between the GO induced material structuration, crystallinity variations, and chemical interaction of the compounds can be correlated with the physical features and bioactivity of each composite formulation. Moreover, the HAp distribution within follows an auspicious density gradient tuned for hybrid osseous/cartilage matter architectures, which were mirrored in the mice model tests. Hence, the synthesis route of a natural polymer blend/hydroxyapatite-graphene oxide composite material is anticipated to emerge as influential formulation in bone tissue engineering. Acknowledgement: This work was supported by the project 'Work-based learning systems using entrepreneurship grants for doctoral and post-doctoral students' (Sisteme de invatare bazate pe munca prin burse antreprenor pentru doctoranzi si postdoctoranzi) - SIMBA, SMIS code 124705 and by a grant of the National Authority for Scientific Research and Innovation, Operational Program Competitiveness Axis 1 - Section E, Program co-financed from European Regional Development Fund 'Investments for your future' under the project number 154/25.11.2016, P_37_221/2015. The nano-CT experiments were possible due to European Regional Development Fund through Competitiveness Operational Program 2014-2020, Priority axis 1, ID P_36_611, MySMIS code 107066, INOVABIOMED.

Keywords: biopolymer blend, ectopic osteoinduction, graphene oxide composite, hydroxyapatite

Procedia PDF Downloads 95

Authors: N. Schneider, M. Bruchhage, M. Hartweg, G. Mutungi, J. O Regan, S. Deoni

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Observational neuroimaging studies suggest differences between breast-fed and formula-fed infants in developmental myelination, a key brain process for learning and cognitive development. However, the possible effects of a nutrient formulation on myelin development in healthy term infants in an intervention study have not been investigated. Objective was, therefore, to investigate the efficacy of a nutrient formulation with higher levels of myelin-relevant nutrients as compared to a control formulation with lower levels of the same nutrients on brain myelination and cognitive development in the first 6 months of life. The study is an ongoing randomized, controlled, double-blind, two-center, parallel-group clinical trial with a nonrandomized, non-blinded arm of exclusively breastfed infants. The current findings result from a staged statistical analysis at 6 months; the recruitment and intervention period has been completed for all participants. Follow-up visits at 12, 18 and 24 months are still ongoing. N= 81 enrolled full term, neurotypical infants of both sexes were randomized into either the investigational (N= 42) or the control group (N= 39), and N= 108 children in the breast-fed arm served as a natural reference group. The effect of a blend of docosahexaenoic acid, arachidonic acid, iron, vitamin B12, folic acid as well as sphingomyelin from a uniquely proceed whey protein concentrate enriched in alpha-lactalbumin and phospholipids in an infant nutrition product matrix was investigated. The main outcomes for the staged statistical analyses at 6 months included brain myelination measures derived from MRI. Additional outcomes were brain volume, cognitive development and safety. The full analyses set at 6 months comprised N= 66 infants. Higher levels of myelin-relevant nutrients compared to lower levels resulted in significant differences in myelin structure, volume, and rate of myelination as early as 3 and 6 months of life. The cross-sectional change of means between groups for whole-brain myelin volume was 8.4% for investigational versus control formulation (3.5% versus the breastfeeding reference) group at 3 months and increased to 36.4% for investigational versus control formulation (14.1% versus breastfeeding reference) at 6 months. No statistically significant differences were detected for early cognition scores. Safety findings were largely similar across groups. This is the first pediatric nutritional neuroimaging study demonstrating the efficacy of a myelin nutrient blend on developmental myelination in well-nourished term infants. Myelination is a critical process in learning and development. The effects were demonstrated across the brain, particularly in temporal and parietal regions, known to be functionally involved in sensory, motor and language skills. These first results add to the field of nutritional neuroscience by demonstrating early life nutrition benefits for brain architecture which may be foundational for later cognitive and behavioral outcomes. ClinicalTrials.gov Identifier: NCT03111927 (Infant Nutrition and Brain Development - Full-Text View - ClinicalTrials.gov).

Keywords: brain development, infant nutrition, MRI, myelination

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Authors: Allison Herlene Du Plessis, Dalena (R.M.) Van Rooyen, Wilma Ten Ham-Baloyi, Sihaam Jardien-Baboo

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Introduction: Women die in pregnancy and childbirth for five main reasons—severe bleeding, infections, unsafe abortions, hypertensive disorders (pre-eclampsia and eclampsia), and medical complications including cardiac disease, diabetes, or HIV/AIDS complicated by pregnancy. In 2015, WHO classified sepsis as the third highest cause for maternal mortalities in the world. Chorioamnionitis is a clinical syndrome of intrauterine infection during any stage of the pregnancy and it refers to ascending bacteria from the vaginal canal up into the uterus, causing infection. While the incidence rates for chorioamnionitis are not well documented, complications related to chorioamnionitis are well documented and midwives still struggle to identify this condition in time due to its complex nature. Few diagnostic methods are available in public health services, due to escalated laboratory costs. Often the affordable biomarkers, such as C-reactive protein CRP, full blood count (FBC) and WBC, have low significance in diagnosing chorioamnionitis. A lack of screening impacts on effective and timeous management of chorioamnionitis, and early identification and management of risks could help to prevent neonatal complications and reduce the subsequent series of morbidities and healthcare costs of infants who are health foci of perinatal infections. Objective: This integrative literature review provides an overview of current best research evidence on the screening of women at risk for chorioamnionitis. Design: An integrative literature review was conducted using a systematic electronic literature search through EBSCOhost, Cochrane Online, Wiley Online, PubMed, Scopus and Google. Guidelines, research studies, and reports in English related to chorioamnionitis from 2008 up until 2020 were included in the study. Findings: After critical appraisal, 31 articles were included. More than one third (67%) of the literature included ranked on the three highest levels of evidence (Level I, II and III). Data extracted regarding screening for chorioamnionitis was synthesized into four themes, namely: screening by clinical signs and symptoms, screening by causative factors of chorioamnionitis, screening of obstetric history, and essential biomarkers to diagnose chorioamnionitis. Key conclusions: There are factors that can be used by midwives to identify women at risk for chorioamnionitis. However, there are a paucity of established sociological, epidemiological and behavioral factors to screen this population. Several biomarkers are available to diagnose chorioamnionitis. Increased Interleukin-6 in amniotic fluid is the better indicator and strongest predictor of histological chorioamnionitis, whereas the available rapid matrix-metalloproteinase-8 test requires further testing. Maternal white blood cells count (WBC) has shown poor selectivity and sensitivity, and C-reactive protein (CRP) thresholds varied among studies and are not ideal for conclusive diagnosis of subclinical chorioamnionitis. Implications for practice: Screening of women at risk for chorioamnionitis by health care providers providing care for pregnant women, including midwives, is important for diagnosis and management before complications arise, particularly in resource-constraint settings.

Keywords: chorioamnionitis, guidelines, best evidence, screening, diagnosis, pregnant women

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Authors: Pawel Martynowicz

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Vibrations are a crucial problem for slender structures such as towers, masts, chimneys, wind turbines, bridges, high buildings, etc., that is why most of them are equipped with vibration attenuation or fatigue reduction solutions. In this work, a slender structure (i.e., wind turbine tower-nacelle model) equipped with nonlinear, semiactive tuned vibration absorber(s) is analyzed. For this study purposes, magnetorheological (MR) dampers are used as semiactive actuators. Several optimal-based approaches to structural vibration attenuation are investigated against the standard ‘ground-hook’ law and passive tuned vibration absorber(s) implementations. The common approach to optimal control of nonlinear systems is offline computation of the optimal solution, however, so determined open loop control suffers from lack of robustness to uncertainties (e.g., unmodelled dynamics, perturbations of external forces or initial conditions), and thus perturbation control techniques are often used. However, proper linearization may be an issue for highly nonlinear systems with implicit relations between state, co-state, and control. The main contribution of the author is the development as well as numerical and experimental verification of the Pontriagin maximum-principle-based vibration control concepts that produce directly actuator control input (not the demanded force), thus force tracking algorithm that results in control inaccuracy is entirely omitted. These concepts, including one-step optimal control, quasi-optimal control, and optimal-based modified ‘ground-hook’ law, can be directly implemented in online and real-time feedback control for periodic (or semi-periodic) disturbances with invariant or time-varying parameters, as well as for non-periodic, transient or random disturbances, what is a limitation for some other known solutions. No offline calculation, excitations/disturbances assumption or vibration frequency determination is necessary, moreover, all of the nonlinear actuator (MR damper) force constraints, i.e., no active forces, lower and upper saturation limits, hysteresis-type dynamics, etc., are embedded in the control technique, thus the solution is optimal or suboptimal for the assumed actuator, respecting its limitations. Depending on the selected method variant, a moderate or decisive reduction in the computational load is possible compared to other methods of nonlinear optimal control, while assuring the quality and robustness of the vibration reduction system, as well as considering multi-pronged operational aspects, such as possible minimization of the amplitude of the deflection and acceleration of the vibrating structure, its potential and/or kinetic energy, required actuator force, control input (e.g. electric current in the MR damper coil) and/or stroke amplitude. The developed solutions are characterized by high vibration reduction efficiency – the obtained maximum values of the dynamic amplification factor are close to 2.0, while for the best of the passive systems, these values exceed 3.5.

Keywords: magnetorheological damper, nonlinear tuned vibration absorber, optimal control, real-time structural vibration attenuation, wind turbines

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Authors: Hsueh Ping Peng

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End-stage renal disease most commonly occurs in the elderly population. Elderly people are approaching the end of their lives, and when facing major life-threatening situations, apart from aggressive medical treatment, they can also choose treatment methods such as hospice care to improve their quality of life. The purpose of this study was to investigate factors associated with the awareness and willingness to sign hospice and palliative care consent forms in elderly with end-stage renal disease. This study used both quantitative, cross-sectional study designs. In the quantitative section, 110 elderly patients (aged 65 or above) with end-stage renal disease receiving conventional hemodialysis were recruited as study participants from a medical center in Taipei City. Data were collected using structured questionnaires. Study tools included basic demographic data, questionnaires on the awareness and perception of hospice and palliative care, etc. After collecting the data, data analysis was conducted using SPSS 20.0 statistical software, including descriptive statistics, chi-square test, logistic regression, and other inferential statistics. The results showed that the average age of participants was 71.6 years old, more males than females, average years of dialysis was 6.1 years and most subjects rated their self-perceived health status as fair. Results of the study are summarized as follows: Elderly people with end-stage renal disease did not have sufficient knowledge and awareness about hospice and palliative care. Influencing factors included level of education, marital status, years of dialysis and age, etc. Demographic factors influencing the signing of consent forms included gender, marital status, and age, which all showed significant impacts. Factors taken into consideration when signing consent forms included awareness of hospice care, understanding the relevant definitions of hospice care, and understanding that consent may be modified or cancelled at any time; it was predicted that people who knew more about ways to receive hospice care or more related definitions were more willing to sign the consent forms. In the qualitative study section, 10 participants who signed the consent form, five male, and 5 female, between the ages of 65-90, have completed the semi-structured interviews. Analysis of the interviews revealed six themes: (1) passing away peacefully, (2) autonomy on arrangements of life and death, (3) unwillingness to increase family and social burden, (4) friends and relatives’ experience influencing the decision to give consent, (5) sharing information to facilitate the giving of consent, (6) facing each day with ease, to reflect the experience and factors of consideration for elderly with end-stage renal disease when signing consent forms. The results of this study provides the awareness, thoughts and feelings of elderly with end-stage renal disease on signing consent forms, and serve as a future reference for the dialysis unit to enhance the promotion of hospice and palliative care and related caregiving measures, thereby improving the quality of life and care for elderly people with end-stage renal disease.

Keywords: end-stage renal disease, hemodialysis, hospice and palliative care, awareness, willingness

Procedia PDF Downloads 151