Search results for: quality properties

Authors: Rose Mini Agoes Salim, Shahnaz Safitri

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The aim of this study is to test the effectiveness of teaching kindness in preschool children by using several techniques. Kindness is a physical act or emotional support aimed to build or maintain relationships with others. Kindness is known to be essential in the development of moral reasoning to distinguish between the good and bad things. In this study, kindness is operationalized as several acts including helping friends, comforting sad friends, inviting friends to play, protecting others, sharing, saying hello, saying thank you, encouraging others, and apologizing. It is mentioned that kindness is crucial to be developed in preschool children because this is the time the children begin to interact with their social environment through play. Furthermore, preschool children's cognitive development makes them begin to represent the world with words, which then allows them to interact with others. On the other hand, preschool children egocentric thinking makes them still need to learn to consider another person's perspective. In relation to social interaction, preschool children need to be stimulated and assisted by adult to be able to pay attention to other and act with kindness toward them. On teaching kindness to children, the quality of interaction between children and their significant others is the key factor. It is known that preschool children learn about kindness by imitating adults on their two way interaction. Specifically, this study examines two types of teaching techniques that can be done by parents as a way to teach kindness, namely the picture-storybook reading and hand-puppet storytelling. These techniques were examined because both activities are easy to do and both also provide a model of behavior for the child based on the character in the story. To specifically examine those techniques effectiveness in teaching kindness, two studies were conducted. Study I involves 31 children aged 5-6 years old with picture-storybook reading technique, where the intervention is done by reading 8 picture books for 8 days. In study II, hand-puppet storytelling technique is examined to 32 children aged 3-5 years old. The treatments effectiveness are measured using an instrument in the form of nine colored cards that describe the behavior of kindness. Data analysis using Wilcoxon Signed-rank test shows a significant difference on the average score of kindness (p < 0.05) before and after the intervention has been held. For daily observation, a ‘kindness tree’ and observation sheets are used which are filled out by the teacher. Two weeks after interventions, an improvement on all kindness behaviors measured is intact. The same result is also gained from both ‘kindness tree’ and observational sheets.

Keywords: kindness, moral teaching, storytelling, hand puppet

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Authors: Arianna Nativio, Zoran Kapelan, Jan Peter van der Hoek

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Bio-composite materials are becoming increasingly popular in various applications, such as the automotive industry. Usually, bio-composite materials are made from natural resources recovered from plants, now, a new type of bio-composite material has begun to be produced in the Netherlands. This material is made from resources recovered from drinking water treatments (calcite), wastewater treatment (cellulose), and material from surface water management (aquatic plants). Surface water, raw drinking water, and wastewater can be contaminated with pathogens and chemical compounds. Therefore, it would be valuable to develop a framework to assess, monitor, and control the potential risks. Indeed, the goal is to define the major risks in terms of human health, quality of materials, and environment associated with the production and application of these new materials. This study describes the general risk assessment framework, starting with a qualitative risk assessment. The qualitative risk analysis was carried out by using the HAZOP methodology for the hazard identification phase. The HAZOP methodology is logical and structured and able to identify the hazards in the first stage of the design when hazards and associated risks are not well known. The identified hazards were analyzed to define the potential associated risks, and then these were evaluated by using the qualitative Event Tree Analysis. ETA is a logical methodology used to define the consequences for a specific hazardous incidents, evaluating the failure modes of safety barriers and dangerous intermediate events that lead to the final scenario (risk). This paper shows the effectiveness of combining of HAZOP and qualitative ETA methodologies for hazard identification and risk mapping. Then, key risks were identified, and a quantitative framework was developed based on the type of risks identified, such as QMRA and QCRA. These two models were applied to assess human health risks due to the presence of pathogens and chemical compounds such as heavy metals into the bio-composite materials. Thus, due to these contaminations, the bio-composite product, during its application, might release toxic substances into the environment leading to a negative environmental impact. Therefore, leaching tests are going to be planned to simulate the application of these materials into the environment and evaluate the potential leaching of inorganic substances, assessing environmental risk.

Keywords: bio-composite, risk assessment, water reuse, resource recovery

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Authors: Rio Hirakawa, Christian Gundlach, Sven Hartwig

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In recent years, the use of aluminium has further expanded and is expected to replace steel in the future as vehicles become lighter and more recyclable in order to reduce greenhouse gas (GHG) emissions and improve fuel economy. In line with this, structures and components are becoming increasingly multi-material, with different materials, including aluminium, being used in combination to improve mechanical utility and performance. A common method of assembling dissimilar materials is mechanical fastening, but it has several drawbacks, such as increased manufacturing processes and the influence of substrate-specific mechanical properties. Adhesive bonding and fusion bonding are methods that overcome the above disadvantages. In these two joining methods, surface pre-treatment of the substrate is always necessary to ensure the strength and durability of the joint. Previous studies have shown that laser surface treatment improves the strength and durability of the joint. Yan et al. showed that laser surface treatment of aluminium alloys changes α-Al2O3 in the oxide layer to γ-Al2O3. As γ-Al2O3 has a large specific surface area, is very porous and chemically active, laser-treated aluminium surfaces are expected to undergo physico-chemical changes over time and adsorb moisture and organic substances from the air or storage atmosphere. The impurities accumulated on the laser-treated surface may be released at the adhesive and bonding interface by the heat input to the bonding system during the joining phase, affecting the strength and durability of the joint. However, only a few studies have discussed the effect of such storage periods on laser-treated surfaces. This paper, therefore, investigates the ageing of laser-treated aluminium alloy surfaces through thermal analysis, electrochemical analysis and microstructural observations.AlMg3 of 0.5 mm and 1.5 mm thickness was cut using a water-jet cutting machine, cleaned and degreased with isopropanol and surface pre-treated with a pulsed fibre laser at 1060 nm wavelength, 70 W maximum power and 55 kHz repetition frequency. The aluminium surface was then analysed using SEM, thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR) and cyclic voltammetry (CV) after storage in air for various periods ranging from one day to several months TGA and FTIR analysed impurities adsorbed on the aluminium surface, while CV revealed changes in the true electrochemically active surface area. SEM also revealed visual changes on the treated surface. In summary, the changes in the laser-treated aluminium surface with storage time were investigated, and the final results were used to determine the appropriate storage period.

Keywords: laser surface treatment, pre-treatment, adhesion, bonding, corrosion, durability, dissimilar material interface, automotive, aluminium alloys

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Authors: Geliashvili T. M., Tyulyandina A. S., Valiev A. K., Kononets P. V., Kharatishvili T. K., Salkov A. G., Pronin A. I., Gadzhieva E. H., Parnas A. V., Ilyakov V. S.

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Aim/Introduction: Metastasis (Mts) to the sternum, while extremely rare in differentiated thyroid cancer (DTC) (1), requires a personalized, multidisciplinary treatment approach. In aggressively growing Mts to the sternum, which rapidly become unresectable, a comprehensive therapeutic and diagnostic approach is particularly important. Materials and methods: We present a clinical case of solitary Mts to the sternum as first manifestation of a papillary thyroid microcarcinoma in a 55-year-old man. Results: 18F-FDG PET/CT after thyroidectomy confirmed the solitary Mts to the sternum with extremely high FDG uptake (SUVmax=71,1), which predicted its radioiodine-refractory (RIR). Due to close attachment to the mediastinum and rapid growth, Mts was considered unresectable. During the next three months, the patient received targeted therapy with the tyrosine kinase inhibitor (TKI) Lenvatinib 24 mg per day. 1st course of radioiodine therapy (RIT) 6 GBq was also performed, the results of which confirmed the RIR of the tumor process. As a result of systemic therapy (targeted therapy combined with RIT and suppressive hormone therapy with L-thyroxine), there was a significant biochemical response (decrease of serum thyroglobulin level from 50,000 ng/ml to 550 ng/ml) and a partial response with decrease of tumor size (from 80x69x123 mm to 65x50x112 mm) and decrease of FDG accumulation (SUVmax from 71.1 to 63). All of this made possible to perform surgical treatment of Mts - sternal extirpation with its replacement by an individual titanium implant. At the control examination, the stimulated thyroglobulin level was only 134 ng/ml, and PET/CT revealed postoperative areas of 18F-FDG metabolism in the removed sternal Mts. Also, 18F-FDG PET/CT in the early (metabolic) stage revealed two new bone Mts (in the area of L3 SUVmax=17,32 and right iliac bone SUVmax=13,73), which, as well as the removed sternal Mts, appeared to be RIRs at the 2nd course of RIT 6 GBq. Subsequently, on 02.2022, external beam radiation therapy (EBRT) was performed on the newly identified oligometastatic bone foci. At present, the patient is under dynamic monitoring and in the process of suppressive hormone therapy with L-thyroxine. Conclusion: Thus, only due to the early prescription of targeted TKI therapy was it possible to perform surgical resection of Mts to the sternum, thereby improve the patient's quality of life and preserve the possibility of radical treatment in case of oligometastatic disease progression.

Keywords: differentiated thyroid cancer, metastasis to the sternum, radioiodine therapy, radioiodine-refractory cancer, targeted therapy, lenvatinib

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Authors: Rajat Dhawan, Hitendra K. Malik

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Electronegative plasmas comprising electrons, positive ions, and negative ions are advantageous for their expanding applications in industries. In plasma cleaning, plasma etching, and plasma deposition process, electronegative plasmas are preferred because of relatively less potential developed on the surface of the material under investigation. Also, the presence of negative ions avoid the irregularity in etching shapes and also enhance the material working during the fabrication process. The interaction of metallic conducting surface with plasma becomes mandatory to understand these applications. A metallic conducting probe immersed in a plasma results in the formation of a thin layer of charged species around the probe called as a sheath. The density of the ions embedded on the surface of the material and the sheath thickness are the important parameters for the surface-plasma interaction. Sheath thickness will give rise to the information of affected plasma region due to conducting surface/probe. The knowledge of the density of ions in the sheath region is advantageous in plasma nitriding, and their temperature is equally important as it strongly influences the thickness of the modified layer during surface plasma interaction. In the present work, we considered a negatively biased metallic probe immersed in a warm electronegative plasma. For this system, we adopted the continuity equation and momentum transfer equation for both the positive and negative ions, whereas electrons are described by Boltzmann distribution. Finally, we use the Poisson’s equation. Here, we assumed the spherical geometry for small probe radius. Poisson’s equation reveals the behaviour of potential surrounding a conducting metallic probe along with the use of the continuity and momentum transfer equations, with the help of proper boundary conditions. In turn, it gives rise to the information about the density profile of charged species and most importantly the thickness of the sheath. By keeping in mind, the well-known Bohm-Sheath criterion, all calculations are done. We found that positive ion density decreases with an increase in positive ion temperature, whereas it increases with the higher temperature of the negative ions. Positive ion density decreases as we move away from the center of the probe and is found to show a discontinuity at a particular distance from the center of the probe. The distance where discontinuity occurs is designated as sheath edge, i.e., the point where sheath ends. These results are beneficial for industrial applications, as the density of ions embedded on material surface is strongly affected by the temperature of plasma species. It has a drastic influence on the surface properties, i.e., the hardness, corrosion resistance, etc. of the materials.

Keywords: electronegative plasmas, plasma surface interaction positive ion density, sheath thickness

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Authors: G. Ghamrawi, Y. Abunnasr, M. Fawaz, S. Yazigi

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Coastal cities are constantly exposed to environmental degradation and economic regression fueled by rapid and uncontrolled urban growth as well as continuous resource depletion. This is the case of the City of Mina in Tripoli (Lebanon), where lack of awareness to preserve social, ecological, and historical assets, coupled with the increasing development pressures, are threatening the socioeconomic status of the city residents, the quality of life and accessibility to the coast. To address these challenges, a holistic coastal urban design and planning approach was developed to analyze the environmental, political, legal, and socioeconomic context of the city. This approach aims to investigate the potential of balancing urban development with the protection and enhancement of cultural, ecological, and environmental assets under an integrated coastal zone management approach (ICZM). The analysis of Mina's different sectors adopted several tools that include direct field observation, interviews with stakeholders, analysis of available data, historical maps, and previously proposed projects. The findings from the analysis were mapped and graphically represented, allowing the recognition of character zones that become the design intervention units. Consequently, the thesis proposes an urban, city-scale intervention that identifies 6 different character zones (the historical fishing port, Abdul Wahab island, the abandoned Port Said, Hammam el Makloub, the sand beach, and the new developable area) and proposes context-specific design interventions that capitalize on the main characteristics of each zone. Moreover, the intervention builds on the institutional framework of ICZM as well as other studies previously conducted for the coast and adopts nature-based solutions with hybrid systems for providing better environmental design solutions for developing the coast. This enables the realization of an all-inclusive, well-connected shoreline with easy and free access towards the sea; a developed shoreline with an active local economy, and an improved urban environment.

Keywords: blue green infrastructure, coastal cities, hybrid solutions, integrated coastal zone management, sustainable development, urban planning

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Authors: Wanwadee Neamsakul

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VARK learning style is an effective method of learning that could enhance all skills of the students like visual (V), auditory (A), read/write (R), and kinesthetic (K). This learning style benefits the students in terms of professional competencies, critical thinking and lifelong learning which are the desirable characteristics of the nursing students. This study aimed to develop a model of teaching and learning clinical practicum at postpartum ward for nursing students by using VARK learning styles, and evaluate the nursing students’ opinions about the developmental model. A methodology used for this study was research and development (R&D). The model was developed by focus group discussion with five obstetric nursing instructors who have experiences teaching Maternal Newborn and Midwifery I subject. The activities related to practices in the postpartum (PP) ward including all skills of VARK were assigned into the matrix table. The researcher asked the experts to supervise the model and adjusted the model following the supervision. Subsequently, it was brought to be tried out with the nursing students who practiced on the PP ward. Thirty third year nursing students from one of the northern Nursing Colleges, Academic year 2015 were purposive sampling. The opinions about the satisfaction of the model were collected using a questionnaire which was tested for its validity and reliability. Data were analyzed using descriptive statistics. The developed model composed of 27 activities. Seven activities were developed as enhancement of visual skills for the nursing students (25.93%), five activities as auditory skills (18.52%), six activities as read and write skills (22.22%), and nine activities as kinesthetic skills (33.33%). Overall opinions about the model were reported at the highest level of average satisfaction (mean=4.63, S.D=0.45). In the aspects of visual skill (mean=4.80, S.D=0.45) was reported at the highest level of average satisfaction followed by auditory skill (mean=4.62, S.D=0.43), read and write skill (mean=4.57, S.D=0.46), and kinesthetic skill (mean=4.53, S.D=0.45) which were reported at the highest level of average satisfaction, respectively. The nursing students reported that the model could help them employ all of their skills during practicing and taking care of the postpartum women and newborn babies. They could establish self-confidence while providing care and felt proud of themselves by the benefits of the model. It can be said that using VARK learning style to develop the model could enhance both nursing students’ competencies and positive attitude towards the nursing profession. Consequently, they could provide quality care for postpartum women and newborn babies effectively in the long run.

Keywords: model, nursing students, postpartum ward, teaching and learning clinical practicum

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Authors: Jamila Fakchich, Mostafa Jamila Lazaar Elachouri, Lakhder Fakchich, Fatna Ouali, Abd Errazzak Belkacem

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Diabetes is a chronic metabolic disease that has a significant impact on the health, quality of life, and life expectancy of patients as well as the health care system. By its nature diabetes, is a multisystem disease with wide-ranging complication that span nearly all region of the body. This epidemic problem, however, is not unique to the industrialized society, but has also hardly struck the developing countries. In Morocco, as developing country, there is an epidemic rise in diabetes, with ensuing concern about the management and control of this disease; it began a chronic burdensome disease of largely middle-aged and elderly people, with a long course and serious complications often resulting in high death-rate, the treatment of diabetes spent vast amount of resources including medicines, diets, physical training. Treatment of this disease is considered problematic due to the lack of effective and safe drugs capable of inducing sustained clinical, biochemical, and histological cure. In Moroccan society, the phytoremedies are some times the only affordable sources of healthcare, particularly for the people in remote areas. In this paper, we present a synthesis work obtained from the ethnobotanical data reported in different specialized journals. A Synthesis of four published ethnobotanical studies that have been carried out in different region of Morocco by different team seekers during the period from 1997 to 2015. Medicinal plants inventoried by different seekers in four Moroccan’s areas have been regrouped and codified, then, Factorial Analysis (FA) and Principal Components Analysis (PCA) are used to analyse the aggregated data from the four studies and plants are classified according to their frequency of use by population. Our work deals with an attempt to gather information on some traditional uses of medicinal plants from different regions of Morocco, also, it was designed to give a set of medicinal plants commonly used by Moroccan people in the treatment of diabetes; In this paper, we intended to provide a basic knowledge about plant species used by Moroccan society for treatment of diabetes. One of the most interesting aspects of this type of works is to assess the relative cultural importance of medicinal plants for specific illnesses and exploring its usefulness in the context of diabetes.

Keywords: Morocco, medicinal plants, ethnobotanical, diabetes, phytoremedies

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Authors: Valentina Marutyan

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Healthcare data mining is a rapidly developing field at the intersection of technology and medicine that has the potential to change our understanding and approach to providing healthcare. Healthcare and data mining is the process of examining huge amounts of data to extract useful information that can be applied in order to improve patient care, treatment effectiveness, and overall healthcare delivery. This field looks for patterns, trends, and correlations in a variety of healthcare datasets, such as electronic health records (EHRs), medical imaging, patient demographics, and treatment histories. To accomplish this, it uses advanced analytical approaches. Predictive analysis using historical patient data is a major area of interest in healthcare data mining. This enables doctors to get involved early to prevent problems or improve results for patients. It also assists in early disease detection and customized treatment planning for every person. Doctors can customize a patient's care by looking at their medical history, genetic profile, current and previous therapies. In this way, treatments can be more effective and have fewer negative consequences. Moreover, helping patients, it improves the efficiency of hospitals. It helps them determine the number of beds or doctors they require in regard to the number of patients they expect. In this project are used models like logistic regression, random forests, and neural networks for predicting diseases and analyzing medical images. Patients were helped by algorithms such as k-means, and connections between treatments and patient responses were identified by association rule mining. Time series techniques helped in resource management by predicting patient admissions. These methods improved healthcare decision-making and personalized treatment. Also, healthcare data mining must deal with difficulties such as bad data quality, privacy challenges, managing large and complicated datasets, ensuring the reliability of models, managing biases, limited data sharing, and regulatory compliance. Finally, secret code of data mining in healthcare helps medical professionals and hospitals make better decisions, treat patients more efficiently, and work more efficiently. It ultimately comes down to using data to improve treatment, make better choices, and simplify hospital operations for all patients.

Keywords: data mining, healthcare, big data, large amounts of data

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Authors: M. Khorshed Alam, H. Takaba

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The catalytic properties of metal usually change by intermixturing with another metal in polymer electrolyte fuel cells. Pt-Ru alloy is one of the much-talked used alloy to enhance the CO oxidation. In this work, we have investigated the CO coverage on the Pt2Ru3 nanoparticle with different atomic conformation of Pt and Ru using a combination of material informatics with computational chemistry. Density functional theory (DFT) calculations used to describe the adsorption strength of CO and H with different conformation of Pt Ru ratio in the Pt2Ru3 slab surface. Then through the Monte Carlo (MC) simulations we examined the segregation behaviour of Pt as a function of surface atom ratio, subsurface atom ratio, particle size of the Pt2Ru3 nanoparticle. We have constructed a regression equation so as to reproduce the results of DFT only from the structural descriptors. Descriptors were selected for the regression equation; xa-b indicates the number of bonds between targeted atom a and neighboring atom b in the same layer (a,b = Pt or Ru). Terms of xa-H2 and xa-CO represent the number of atoms a binding H2 and CO molecules, respectively. xa-S is the number of atom a on the surface. xa-b- is the number of bonds between atom a and neighboring atom b located outside the layer. The surface segregation in the alloying nanoparticles is influenced by their component elements, composition, crystal lattice, shape, size, nature of the adsorbents and its pressure, temperature etc. Simulations were performed on different size (2.0 nm, 3.0 nm) of nanoparticle that were mixing of Pt and Ru atoms in different conformation considering of temperature range 333K. In addition to the Pt2Ru3 alloy we also considered pure Pt and Ru nanoparticle to make comparison of surface coverage by adsorbates (H2, CO). Hence, we assumed the pure and Pt-Ru alloy nanoparticles have an fcc crystal structures as well as a cubo-octahedron shape, which is bounded by (111) and (100) facets. Simulations were performed up to 50 million MC steps. From the results of MC, in the presence of gases (H2, CO), the surfaces are occupied by the gas molecules. In the equilibrium structure the coverage of H and CO as a function of the nature of surface atoms. In the initial structure, the Pt/Ru ratios on the surfaces for different cluster sizes were in range of 0.50 - 0.95. MC simulation was employed when the partial pressure of H2 (PH2) and CO (PCO) were 70 kPa and 100-500 ppm, respectively. The Pt/Ru ratios decrease as the increase in the CO concentration, without little exception only for small nanoparticle. The adsorption strength of CO on the Ru site is higher than the Pt site that would be one of the reason for decreasing the Pt/Ru ratio on the surface. Therefore, our study identifies that controlling the nanoparticle size, composition, conformation of alloying atoms, concentration and chemical potential of adsorbates have impact on the steadiness of nanoparticle alloys which ultimately and also overall catalytic performance during the operations.

Keywords: anode catalysts, fuel cells, material informatics, Monte Carlo

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Authors: Amritee Bora, B. S. Mipun

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Land degradation is often used to describe the land environmental phenomena that reduce land’s original productivity both qualitatively and quantitatively. The study of land degradation vulnerability primarily deals with “Environmentally Sensitive Areas” (ESA) and the amount of topsoil loss due to erosion. In many studies, it is observed that the assessment of the existing status of land degradation is used to represent the vulnerability. Moreover, it is also noticed that in most studies, the primary emphasis of land degradation vulnerability is to assess its sensitivity to soil erosion only. However, the concept of land degradation vulnerability can have different objectives depending upon the perspective of the study. It shows the extent to which changes in land use land cover can imprint their effect on the land. In other words, it represents the susceptibility of a piece of land to degrade its productive quality permanently or in the long run. It is also important to mention that the vulnerability of land degradation is not a single factor outcome. It is a probability assessment to evaluate the status of land degradation and needs to consider both biophysical and human induce parameters. To avoid the complexity of the previous models in this regard, the present study has emphasized on to generate a simplified model to assess the land degradation vulnerability in terms of its current human population pressure, land use practices, and existing biophysical conditions. It is a “Mixed-Method” termed as the land degradation vulnerability index (LDVi). It was originally inspired by the MEDALUS model (Mediterranean Desertification and Land Use), 1999, and Farazadeh’s 2007 revised version of it. It has followed the guidelines of Space Application Center, Ahmedabad / Indian Space Research Organization for land degradation vulnerability. The model integrates the climatic index (Ci), vegetation index (Vi), erosion index (Ei), land utilization index (Li), population pressure index (Pi), and cover management index (CMi) by giving equal weightage to each parameter. The final result shows that the very high vulnerable zone primarily indicates three (3) prominent circumstances; land under continuous population pressure, high concentration of human settlement, and high amount of topsoil loss due to surface runoff within the study sites. As all the parameters of the model are amalgamated with equal weightage further with the help of regression analysis, the LDVi model also provides a strong grasp of each parameter and how far they are competent to trigger the land degradation process.

Keywords: population pressure, land utilization, soil erosion, land degradation vulnerability

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Authors: Aspasia Koutsokosta, Stefanos Katsavounis

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This paper reviews the model-based qualitative and quantitative Operations Management research in the context of Construction Supply Chain Management (CSCM). Construction industry has been traditionally blamed for low productivity, cost and time overruns, waste, high fragmentation and adversarial relationships. The construction industry has been slower than other industries to employ the Supply Chain Management (SCM) concept and develop models that support the decision-making and planning. However the last decade there is a distinct shift from a project-based to a supply-based approach of construction management. CSCM comes up as a new promising management tool of construction operations and improves the performance of construction projects in terms of cost, time and quality. Modeling the Construction Supply Chain (CSC) offers the means to reap the benefits of SCM, make informed decisions and gain competitive advantage. Different modeling approaches and methodologies have been applied in the multi-disciplinary and heterogeneous research field of CSCM. The literature review reveals that a considerable percentage of CSC modeling accommodates conceptual or process models which discuss general management frameworks and do not relate to acknowledged soft OR methods. We particularly focus on the model-based quantitative research and categorize the CSCM models depending on their scope, mathematical formulation, structure, objectives, solution approach, software used and decision level. Although over the last few years there has been clearly an increase of research papers on quantitative CSC models, we identify that the relevant literature is very fragmented with limited applications of simulation, mathematical programming and simulation-based optimization. Most applications are project-specific or study only parts of the supply system. Thus, some complex interdependencies within construction are neglected and the implementation of the integrated supply chain management is hindered. We conclude this paper by giving future research directions and emphasizing the need to develop robust mathematical optimization models for the CSC. We stress that CSC modeling needs a multi-dimensional, system-wide and long-term perspective. Finally, prior applications of SCM to other industries have to be taken into account in order to model CSCs, but not without the consequential reform of generic concepts to match the unique characteristics of the construction industry.

Keywords: construction supply chain management, modeling, operations research, optimization, simulation

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Authors: Zahra Jandaghian, Mehdi Ghobadi, Michal Bartko, Alex Hayes, Marianne Armstrong, Alexandra Thompson, Michael Lacasse

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The Intergovernmental Panel on Climate Change (IPCC) report stated the urgent need to cut greenhouse gas emissions to avoid the adverse impacts of climatic changes. The United Nations has forecasted that nearly 70 percent of people will live in urban areas by 2050 resulting in a doubling of the global building stock. Given that buildings are currently recognised as emitting 40 percent of global carbon emissions, there is thus an urgent incentive to decarbonize existing buildings and to build net-zero carbon buildings. To attain net zero carbon emissions in communities in the future requires action in two directions: I) reduction of emissions; and II) removal of on-going emissions from the atmosphere once de-carbonization measures have been implemented. Nature-based solutions (NBS) have a significant role to play in achieving net zero carbon communities, spanning both emission reductions and removal of on-going emissions. NBS for the decarbonisation of buildings can be achieved by using green roofs and green walls – increasing vertical and horizontal vegetation on the building envelopes – and using nature-based materials that either emit less heat to the atmosphere thus decreasing photochemical reaction rates, or store substantial amount of carbon during the whole building service life within their structure. The NBS approach can also mitigate urban flooding and overheating, improve urban climate and air quality, and provide better living conditions for the urban population. For existing buildings, de-carbonization mostly requires retrofitting existing envelopes efficiently to use NBS techniques whereas for future construction, de-carbonization involves designing new buildings with low carbon materials as well as having the integrity and system capacity to effectively employ NBS. This paper presents the opportunities and challenges in respect to the de-carbonization of buildings using NBS for both building retrofits and new construction. This review documents the effectiveness of NBS to de-carbonize Canadian buildings, identifies the missing links to implement these techniques in cold climatic conditions, and determine a road map and immediate approaches to mitigate the adverse impacts of climate change such as urban heat islanding. Recommendations are drafted for possible inclusion in the Canadian building and energy codes.

Keywords: decarbonization, nature-based solutions, GHG emissions, greenery enhancement, buildings

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Authors: Nyashadzashe Chiraga, Anthony Walker, Glen Bright

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The manufacturing industry is currently experiencing a paradigm shift into the Fourth Industrial Revolution in which customers are increasingly at the epicentre of production. The high degree of production customization and personalization requires a flexible manufacturing system that will rapidly respond to the dynamic and volatile changes driven by the market. They are a gap in technology that allows for the optimal flow of information and optimal manufacturing operations on the shop floor regardless of the rapid changes in the fixture and part demands. Information is the reduction of uncertainty; it gives meaning and context on the state of each cell. The amount of information needed to describe cellular manufacturing systems is investigated by two measures: the structural entropy and the operational entropy. Structural entropy is the expected amount of information needed to describe scheduled states of a manufacturing system. While operational entropy is the amount of information that describes the scheduled states of a manufacturing system, which occur during the actual manufacturing operation. Using Anylogic simulator a typical manufacturing job shop was set-up with a cellular manufacturing configuration. The cellular make-up of the configuration included; a Material handling cell, 3D Printer cell, Assembly cell, manufacturing cell and Quality control cell. The factory shop provides manufactured parts to a number of clients, and there are substantial variations in the part configurations, new part designs are continually being introduced to the system. Based on the normal expected production schedule, the schedule adherence was calculated from the structural entropy and operation entropy of varying the amounts of information communicated in simulated runs. The structural entropy denotes a system that is in control; the necessary real-time information is readily available to the decision maker at any point in time. For contractive analysis, different out of control scenarios were run, in which changes in the manufacturing environment were not effectively communicated resulting in deviations in the original predetermined schedule. The operational entropy was calculated from the actual operations. From the results obtained in the empirical study, it was seen that increasing, the efficiency of a factory communication system increases the degree of adherence of a job to the expected schedule. The performance of downstream production flow fed from the parallel upstream flow of information on the factory state was increased.

Keywords: information entropy, communication in manufacturing, mass customisation, scheduling

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Authors: Kurt Maxwell Kusterer, Sylvain Mignot, Annick Vignes

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To our best knowledge YouTube is the largest video hosting platform in the world. A high number of creators, viewers, subscribers and commentators act in this specific eco-system which generates huge sums of money. Views, subscribers, and comments help to increase the popularity of content creators. The most popular creators are sponsored by brands and participate in marketing campaigns. For a few of them, this becomes a financially rewarding profession. This is made possible through the YouTube Partner Program, which shares revenue among creators based on their popularity. We believe that the role of comments in increasing the popularity is to be emphasized. In what follows, YouTube is considered as a bilateral network between the videos and the commentators. Analyzing a detailed data set focused on French YouTubers, we consider each comment as a link between a commentator and a video. Our research question asks what are the predominant features of a video which give it the highest probability to be commented on. Following on from this question, how can we use these features to predict the action of the agent in commenting one video instead of another, considering the characteristics of the commentators, videos, topics, channels, and recommendations. We expect to see that the videos of more popular channels generate higher viewer engagement and thus are more frequently commented. The interest lies in discovering features which have not classically been considered as markers for popularity on the platform. A quick view of our data set shows that 96% of the commentators comment only once on a certain video. Thus, we study a non-weighted bipartite network between commentators and videos built on the sub-sample of 96% of unique comments. A link exists between two nodes when a commentator makes a comment on a video. We run an Exponential Random Graph Model (ERGM) approach to evaluate which characteristics influence the probability of commenting a video. The creation of a link will be explained in terms of common video features, such as duration, quality, number of likes, number of views, etc. Our data is relevant for the period of 2020-2021 and focuses on the French YouTube environment. From this set of 391 588 videos, we extract the channels which can be monetized according to YouTube regulations (channels with at least 1000 subscribers and more than 4000 hours of viewing time during the last twelve months).In the end, we have a data set of 128 462 videos which consist of 4093 channels. Based on these videos, we have a data set of 1 032 771 unique commentators, with a mean of 2 comments per a commentator, a minimum of 1 comment each, and a maximum of 584 comments.

Keywords: YouTube, social networks, economics, consumer behaviour

Procedia PDF Downloads 65

Authors: Bulcha Belay Etana, Benny Malengier, Debelo Oljira, Janarthanan Krishnamoorthy, Lieva Vanlangenhove

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Electromyography (EMG) is a technique used to measure the electrical activity of muscles. EMG can be used to assess muscle function in a variety of settings, including clinical, research, and sports medicine. The aim of this study was to develop a wearable textile sensor for EMG monitoring. The sensor was designed to be soft, stretchable, and washable, making it suitable for long-term use. The sensor was fabricated using a conductive thread material that was embroidered onto a fabric substrate. The sensor was then connected to a microcontroller unit (MCU) and a Wi-Fi-enabled module. The MCU was programmed to acquire the EMG signal and transmit it wirelessly to the Wi-Fi-enabled module. The Wi-Fi-enabled module then sent the signal to a server, where it could be accessed by a computer or smartphone. The sensor was able to successfully acquire and transmit EMG signals from a variety of muscles. The signal quality was comparable to that of commercial EMG sensors. The development of this sensor has the potential to improve the way EMG is used in a variety of settings. The sensor is soft, stretchable, and washable, making it suitable for long-term use. This makes it ideal for use in clinical settings, where patients may need to wear the sensor for extended periods of time. The sensor is also small and lightweight, making it ideal for use in sports medicine and research settings. The data for this study was collected from a group of healthy volunteers. The volunteers were asked to perform a series of muscle contractions while the EMG signal was recorded. The data was then analyzed to assess the performance of the sensor. The EMG signals were analyzed using a variety of methods, including time-domain analysis and frequency-domain analysis. The time-domain analysis was used to extract features such as the root mean square (RMS) and average rectified value (ARV). The frequency-domain analysis was used to extract features such as the power spectrum. The question addressed by this study was whether a wearable textile sensor could be developed that is soft, stretchable, and washable and that can successfully acquire and transmit EMG signals. The results of this study demonstrate that a wearable textile sensor can be developed that meets the requirements of being soft, stretchable, washable, and capable of acquiring and transmitting EMG signals. This sensor has the potential to improve the way EMG is used in a variety of settings.

Keywords: EMG, electrode position, smart wearable, textile sensor, IoT, IoT-integrated textile sensor

Procedia PDF Downloads 72

Authors: Ramin Hosseinnezhad, Iurii Vozniak, Andrzej Galeski

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Shear-induced crystallization, originated from orientation of chains along the flow direction, is an inevitable part of most polymer processing technologies. It plays a dominant role in determining the final product properties and is affected by many factors such as shear rate, cooling rate, total strain, etc. Investigation of the shear-induced crystallization process become of great importance for preparation of nanocomposite, which requires crystallization of nanofibrous sheared inclusions at higher temperatures. Thus, the effects of shear time, shear rate, and also thermal condition of cooling on crystallization of two aliphatic-aromatic copolyesters have been investigated. This was performed using Linkam optical shearing system (CSS450) for both Ecoflex® F Blend C1200 produced by BASF and synthesized copolyester of butylene terephthalate and a mixture of butylene esters: adipate, succinate, and glutarate, (PBASGT), containing 60% of aromatic comonomer. Crystallization kinetics of these biodegradable copolyesters was studied at two different conditions of shearing. First, sample with a thickness of 60µm was heated to 60˚C above its melting point and subsequently subjected to different shear rates (100–800 sec-1) while cooling with specific rates. Second, the same type of sample was cooled down when shearing at constant temperature was finished. The intensity of transmitted depolarized light, recorded by a camera attached to the optical microscope, was used as a measure to follow the crystallization. Temperature dependencies of conversion degree of samples during cooling were collected and used to determine the half-temperature (Th), at which 50% conversion degree was reached. Shearing ecoflex films for 45 seconds with a shear rate of 100 sec-1 resulted in significant increase of Th from 56˚C to 70˚C. Moreover, the temperature range for the transition of molten samples to crystallized state decreased from 42˚C to 20˚C. Comparatively low shift of 10˚C in Th towards higher temperature was observed for PBASGT films at shear rate of 600 sec-1 for 45 seconds. However, insufficient melt flow strength and non-laminar flow due to Taylor vortices was a hindrance to reach more elevated Th at very high shear rates (600–800 sec-1). The shift in Th was smaller for the samples sheared at a constant temperature and subsequently cooled down. This may be attributed to the longer time gap between cessation of shearing and the onset of crystallization. The longer this time gap, the more possibility for crystal nucleus to re-melt at temperatures above Tm and for polymer chains to recoil and relax. It is found that the crystallization temperature, crystallization induction time and spherulite growth of aliphatic-aromatic copolyesters are dramatically influenced by both the cooling rate and the shear imposed during the process.

Keywords: induced crystallization, shear rate, aliphatic-aromatic copolyester, ecoflex

Procedia PDF Downloads 445

Authors: Rajasekhar Reddy Poonuru, Anusha Parnem

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Purpose: To formulate proliposome powder of agomelatine, an antipsychotic drug, and to evaluate physicochemical, in vitro characters and effect of surface charge on ex vivo intestinal permeation. Methods: Film deposition technique was employed to develop proliposomal powders of agomelatin with varying molar ratios of lipid Hydro Soy PC L-α-phosphatidylcholine (HSPC) and cholesterol with fixed sum of drug. With the aim to derive free flowing and stable proliposome powder, fluid retention potential of various carriers was examined. Liposome formation and number of vesicles formed for per mm3 up on hydration, vesicle size, and entrapment efficiency was assessed to deduce an optimized formulation. Sodium cholate added to optimized formulation to induce surface charge on formed vesicles. Solid-state characterization (FTIR, DSC, and XRD) was performed with the intention to assess native crystalline and chemical behavior of drug. The in vitro dissolution test of optimized formulation along with pure drug was evaluated to estimate dissolution efficiency (DE) and relative dissolution rate (RDR). Effective permeability co-efficient (Peff(rat)) in rat and enhancement ratio (ER) of drug from formulation and pure drug dispersion were calculated from ex vivo permeation studies in rat ileum. Results: Proliposomal powder formulated with equimolar ratio of HSPC and cholesterol ensued in higher no. of vesicles (3.95) with 90% drug entrapment up on hydration. Neusilin UFL2 was elected as carrier because of its high fluid retention potential (4.5) and good flow properties. Proliposome powder exhibited augmentation in DE (60.3 ±3.34) and RDR (21.2±01.02) of agomelation over pure drug. Solid state characterization studies demonstrated the transformation of native crystalline form of drug to amorphous and/or molecular state, which was in correlation with results obtained from in vitro dissolution test. The elevated Peff(rat) of 46.5×10-4 cm/sec and ER of 2.65 of drug from charge induced proliposome formulation with respect to pure drug dispersion was assessed from ex vivo intestinal permeation studies executed in ileum of wistar rats. Conclusion: Improved physicochemical characters and ex vivo intestinal permeation of drug from charge induced proliposome powder with Neusilin UFL2 unravels the potentiality of this system in enhancing oral delivery of agomelatin.

Keywords: agomelatin, proliposome, sodium cholate, neusilin

Procedia PDF Downloads 130

Authors: Jean Paul Muambangu Milambo, Peter Nyasulu, John Akudugu, Leonidas Ndayisaba, Joyce Tsoka-Gwegweni, Lebwaze Massamba Bienvenu, Mitshindo Mwambangu Chiro

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In 2018, non-communicable diseases (NCDs) were responsible for 48% of deaths in the Democratic Republic of Congo (DRC), with cancer contributing to 5% of these deaths. There is a notable absence of cancer registries, capacity-building activities, budgets, and treatment roadmaps in the DRC. Current cancer estimates are primarily based on mathematical modeling with limited data from neighboring countries. This study aimed to assess cancer subtype prevalence in Kinshasa hospitals and compare these findings with WHO model estimates. Methods: A retrospective observational study was conducted from 2018 to 2020 at HJ Hospitals in Kinshasa. Data were collected using American Cancer Society (ACS) questionnaires and physician logs. Descriptive analysis was performed using STATA version 16 to estimate cancer burden and provide evidence-based recommendations. Results: The results from the chart review at HJ Hospitals in Kinshasa (2018-2020) indicate that out of 6,852 samples, approximately 11.16% were diagnosed with cancer. The distribution of cancer subtypes in this cohort was as follows: breast cancer (33.6%), prostate cancer (21.8%), colorectal cancer (9.6%), lymphoma (4.6%), and cervical cancer (4.4%). These figures are based on histopathological confirmation at the facility and may not fully represent the broader population due to potential selection biases related to geographic and financial accessibility to the hospital. In contrast, the World Health Organization (WHO) model estimates for cancer prevalence in the DRC show different proportions. According to WHO data, the distribution of cancer types is as follows: cervical cancer (15.9%), prostate cancer (15.3%), breast cancer (14.9%), liver cancer (6.8%), colorectal cancer (5.9%), and other cancers (41.2%) (WHO, 2020). Conclusion: The data indicate a rising cancer prevalence in DRC but highlight significant gaps in clinical, biomedical, and genetic cancer data. The establishment of a population-based cancer registry (PBCR) and a defined cancer management pathway is crucial. The current estimates are limited due to data scarcity and inconsistencies in clinical practices. There is an urgent need for multidisciplinary cancer management, integration of palliative care, and improvement in care quality based on evidence-based measures.

Keywords: cancer, risk factors, DRC, gene-environment interactions, survivors

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Authors: Mrinalini Ranjan, Sudheesh Chethil

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Epilepsy is a common neurological disorder characterised by the recurrence of seizures. Electroencephalogram (EEG) signals are complex biomedical signals which exhibit nonlinear and nonstationary behavior. We use two methods 1) Detrended Fluctuation Analysis (DFA) and 2) Recurrence Plots (RP) to capture this complex behavior of EEG signals. DFA considers fluctuation from local linear trends. Scale invariance of these signals is well captured in the multifractal characterisation using detrended fluctuation analysis (DFA). Analysis of long-range correlations is vital for understanding the dynamics of EEG signals. Correlation properties in the EEG signal are quantified by the calculation of a scaling exponent. We report the existence of two scaling behaviours in the epileptic EEG signals which quantify short and long-range correlations. To illustrate this, we perform DFA on extant ictal (seizure) and interictal (seizure free) datasets of different patients in different channels. We compute the short term and long scaling exponents and report a decrease in short range scaling exponent during seizure as compared to pre-seizure and a subsequent increase during post-seizure period, while the long-term scaling exponent shows an increase during seizure activity. Our calculation of long-term scaling exponent yields a value between 0.5 and 1, thus pointing to power law behaviour of long-range temporal correlations (LRTC). We perform this analysis for multiple channels and report similar behaviour. We find an increase in the long-term scaling exponent during seizure in all channels, which we attribute to an increase in persistent LRTC during seizure. The magnitude of the scaling exponent and its distribution in different channels can help in better identification of areas in brain most affected during seizure activity. The nature of epileptic seizures varies from patient-to-patient. To illustrate this, we report an increase in long-term scaling exponent for some patients which is also complemented by the recurrence plots (RP). RP is a graph that shows the time index of recurrence of a dynamical state. We perform Recurrence Quantitative analysis (RQA) and calculate RQA parameters like diagonal length, entropy, recurrence, determinism, etc. for ictal and interictal datasets. We find that the RQA parameters increase during seizure activity, indicating a transition. We observe that RQA parameters are higher during seizure period as compared to post seizure values, whereas for some patients post seizure values exceeded those during seizure. We attribute this to varying nature of seizure in different patients indicating a different route or mechanism during the transition. Our results can help in better understanding of the characterisation of epileptic EEG signals from a nonlinear analysis.

Keywords: detrended fluctuation, epilepsy, long range correlations, recurrence plots

Procedia PDF Downloads 172

Authors: Chetra Mang, Ahmadali Tahmasebimoradi, Xavier Lorang

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Lattice structures are widely used in various applications, especially in aeronautic, aerospace, and medical applications because of their high performance properties. Thanks to advancement of the additive manufacturing technology, the lattice structures can be manufactured by different methods such as laser beam melting technology. However, the presence of geometric defects in the lattice structures is inevitable due to the manufacturing process. The geometric defects may have high impact on the mechanical strength of the structures. This work analyzes the correlation between the manufacturing parameters and the mechanical strengths of the lattice structures. To do that, two types of the lattice structures; body-centered cubic with z-struts (BCCZ) structures made of Inconel718, and body-centered cubic (BCC) structures made of Scalmalloy, are manufactured by laser melting beam machine using Taguchi design of experiment. Each structure is placed on the substrate with a specific position and orientation regarding the roller direction of deposed metal powder. The position and orientation are considered as the manufacturing parameters. The geometric defects of each beam in the lattice are characterized and used to build the geometric model in order to perform simulations. Then, the mechanical strengths are defined by the homogeneous response as Young's modulus and yield strength. The distribution of mechanical strengths is observed as a function of manufacturing parameters. The mechanical response of the BCCZ structure is stretch-dominated, i.e., the mechanical strengths are directly dependent on the strengths of the vertical beams. As the geometric defects of vertical beams are slightly changed based on their position/orientation on the manufacturing substrate, the mechanical strengths are less dispersed. The manufacturing parameters are less influenced on the mechanical strengths of the structure BCCZ. The mechanical response of the BCC structure is bending-dominated. The geometric defects of inclined beam are highly dispersed within a structure and also based on their position/orientation on the manufacturing substrate. For different position/orientation on the substrate, the mechanical responses are highly dispersed as well. This shows that the mechanical strengths are directly impacted by manufacturing parameters. In addition, this work is carried out to study the uncertainty propagation of the geometric defects on the mechanical strength of the BCC lattice structure made of Scalmalloy. To do that, we observe the distribution of mechanical strengths of the lattice according to the distribution of the geometric defects. A probability density law is determined based on a statistical hypothesis corresponding to the geometric defects of the inclined beams. The samples of inclined beams are then randomly drawn from the density law to build the lattice structure samples. The lattice samples are then used for simulation to characterize the mechanical strengths. The results reveal that the distribution of mechanical strengths of the structures with the same manufacturing parameters is less dispersed than one of the structures with different manufacturing parameters. Nevertheless, the dispersion of mechanical strengths due to the structures with the same manufacturing parameters are unneglectable.

Keywords: geometric defects, lattice structure, mechanical strength, uncertainty propagation

Procedia PDF Downloads 121

Authors: Haseen Siddiqui, Sanjay M. Mahajani

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Various important reactions in chemical and metallurgical industries fall in the category of gas-solid reactions. These reactions can be categorized as catalytic and non-catalytic gas-solid reactions. In gas-solid reaction systems, heat and mass transfer limitations put an appreciable influence on the rate of the reaction. The consequences can be unavoidable for overlooking such effects while collecting the reaction rate data for the design of the reactor. Pyrolysis reaction comes in this category that involves the production of gases due to the interaction of heat and solid substance. Pyrolysis is also an important step in the gasification process and therefore, the gasification reactivity majorly influenced by the pyrolysis process that produces the char, as a feed for the gasification process. Therefore, in the present study, a non-isothermal transient 1-D model is developed for a single biomass pellet to investigate the effect of heat and mass transfer limitations on the rate of pyrolysis reaction. The obtained set of partial differential equations are firstly discretized using the concept of ‘method of lines’ to obtain a set of ordinary differential equation with respect to time. These equations are solved, then, using MATLAB ode solver ode15s. The model is capable of incorporating structural changes, porosity variation, variation in various thermal properties and various pellet shapes. The model is used to analyze the effectiveness factor for different values of Lewis number and heat of reaction (G factor). Lewis number includes the effect of thermal conductivity of the solid pellet. Higher the Lewis number, the higher will be the thermal conductivity of the solid. The effectiveness factor was found to be decreasing with decreasing Lewis number due to the fact that smaller Lewis numbers retard the rate of heat transfer inside the pellet owing to a lower rate of pyrolysis reaction. G factor includes the effect of the heat of reaction. Since the pyrolysis reaction is endothermic in nature, the G factor takes negative values. The more the negative value higher will be endothermic nature of the pyrolysis reaction. The effectiveness factor was found to be decreasing with more negative values of the G factor. This behavior can be attributed to the fact that more negative value of G factor would result in more energy consumption by the reaction owing to a larger temperature gradient inside the pellet. Further, the analytical expressions are also derived for gas and solid concentrations and effectiveness factor for two limiting cases of the general model developed. The two limiting cases of the model are categorized as the homogeneous model and unreacted shrinking core model.

Keywords: effectiveness factor, G-factor, homogeneous model, lewis number, non-catalytic, shrinking core model

Procedia PDF Downloads 130

Authors: Kenza Benali

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Over the past decade, a number of remarkable projects in urban brownfield reconversion emerged across Canada, including the reconversion of former military bases owned by the Canada Lands Company (CLC) into sustainable communities. However, unlike other developments, the regeneration project of the former Canadian Forces Base Rockcliffe in Ottawa – which was announced as one of the most ambitious Smart growth projects in Canada – faced serious obstacles in terms of social acceptance by the local community, particularly urban minorities composed of Francophones, Indigenous and vulnerable groups who live near or on the Base. This turn of events led to the project being postponed and even reconsidered. Through an analysis of its press coverage, this research aims to understand the causes of this urban conflict which lasted for nearly ten years. The findings reveal that the conflict is not limited to the “standard” issues common to most conflicts related to urban mega-projects in the world – e.g., proximity issues (threads to the quality of the surrounding neighbourhoods; noise, traffic, pollution, New-build gentrification) often associated with NIMBY phenomena. In this case, the local actors questioned the purpose of the project (for whom and for what types of uses is it conceived?), its local implementation (to what extent are the local history and existing environment taken into account?), and the degree of implication of the local population in the decision-making process (with whom is the project built?). Moreover, the interests of the local actors have “jumped scales” and transcend the micro-territorial level of their daily life to take on a national and even international dimension. They defined an alternative view of how this project, considered strategic by his location in the nation’s capital, should be a reference as well as an international showcase of Canadian ambition and achievement in terms of urban sustainability. This vision promoted, actually, a territorial and national identity approach - in which some cultural values are highly significant (respect of social justice, inclusivity, ethnical diversity, cultural heritage, etc.)- as a counterweight to planners’ vision which is criticized as a normative/ universalist logic that ignore the territorial peculiarities.

Keywords: smart growth, brownfield reconversion, sustainable neighborhoods, Canada Lands Company, Canadian Forces Base Rockcliffe, urban conflicts

Procedia PDF Downloads 379

Authors: Jesus Salmeron, Carmen De Vega, Maria Soledad Vicente, Mireia Olabarria, Olaia Martinez

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Dysphagia or difficulty in swallowing affects mostly elder people: 56-78% of the institutionalized and 44% of the hospitalized. Liquid food thickening is a necessary measure in this situation because it reduces the risk of penetration-aspiration. Until now, and as proposed by the American Dietetic Association in 2002, possible consistencies have been categorized in three groups attending to their viscosity: nectar (50-350 mPa•s), honey (350-1750 mPa•s) and pudding (>1750 mPa•s). The adequate viscosity level should be identified for every patient, according to her/his impairment. Nevertheless, a systematic review on dysphagia diet performed recently indicated that there is no evidence to suggest that there is any transition of clinical relevance between the three levels proposed. It was also stated that other physical properties of the bolus (slipperiness, density or cohesiveness, among others) could influence swallowing in affected patients and could contribute to the amount of remaining residue. Texture parameters need to be evaluated as possible alternative to viscosity. The aim of this study was to evaluate the instrumental extrusion-compression test as a possible tool to characterize changes along time in water thickened with various products and in the three theoretical consistencies. Six commercial thickeners were used: NM® (NM), Multi-thick® (M), Nutilis Powder® (Nut), Resource® (R), Thick&Easy® (TE) and Vegenat® (V). All of them with a modified starch base. Only one of them, Nut, also had a 6,4% of gum (guar, tara and xanthan). They were prepared as indicated in the instructions of each product and dispensing the correspondent amount for nectar, honey and pudding consistencies in 300 mL of tap water at 18ºC-20ºC. The mixture was stirred for about 30 s. Once it was homogeneously spread, it was dispensed in 30 mL plastic glasses; always to the same height. Each of these glasses was used as a measuring point. Viscosity was measured using a rotational viscometer (ST-2001, Selecta, Barcelona). Extrusion-compression test was performed using a TA.XT2i texture analyzer (Stable Micro Systems, UK) with a 25 mm diameter cylindrical probe (SMSP/25). Penetration distance was set at 10 mm and a speed of 3 mm/s. Measurements were made at 1, 5, 10, 20, 30, 40, 50 and 60 minutes from the moment samples were mixed. From the force (g)–time (s) curves obtained in the instrumental assays, maximum force peak (F) was chosen a reference parameter. Viscosity (mPa•s) and F (g) showed to be highly correlated and had similar development along time, following time-dependent quadratic models. It was possible to predict viscosity using F as an independent variable, as they were linearly correlated. In conclusion, compression-extrusion test could be an alternative and a useful tool to assess physical characteristics of thickened liquids.

Keywords: compression-extrusion test, dysphagia, texture analyzer, thickener

Procedia PDF Downloads 363

Authors: Paula Andrea Segura Delgado, Martha Helena Ramírez-Bahena

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Research on how the brain learns has a transcendental application in the educational context. It is crucial for teacher training to understand the nature of brain changes and their direct influence on learning processes. This communication is based on a literature review focused on neuroscience, neuroeducation, and the impact of digital technology on the human brain. Information was gathered from both English and Spanish language sources, using online journals, books and reports. The general objective was to analyze the role of neuroscience knowledge in enriching our understanding of the learning process. In fact, the authors have focused on the impact of digital technology on the human brain as well as its influence in the field of education..Neuroscience knowledge can contribute significantly to improving the training of educators and therefore educational practices. Education as an instrument of change and school as an agent of socialization, it is necessary to understand what it aims to transform: the human brain. Understanding the functioning of the human brain has important repercussions on education: this elucidates cognitive skills, psychological processes and elements that influence the learning process (memory, executive functions, emotions and the circadian cycle); helps identify psychological and neurological deficits that can impede learning processes (dyslexia, autism, hyperactivity); It allows creating environments that promote brain development and contribute to the advancement of brain capabilities in alignment with the stages of neurobiological development. The digital age presents diverse opportunities to every social environment. The frequent use of digital technology (DT) has had a significant and abrupt impact on both the cognitive abilities and physico-chemical properties of the brain, significantly influencing educational processes. Hence, educational community, with the insights from advances in neuroscience, aspire to identify the positive and negative effects of digital technology on the human brain. This knowledge helps ensure the alignment of teacher training and practices with these findings. The knowledge of neuroscience enables teachers to develop teaching methods that are aligned with the way the brain works. For example, neuroscience research has shown that digital technology is having a significant impact on the human brain (addition, anxiety, high levels of dopamine, circadian cycle disorder, decrease in attention, memory, concentration, problems with their social relationships). Therefore, it is important to understand the nature of these changes, their impact on the learning process, and how educators should effectively adapt their approaches based on these brain's changes.

Keywords: digital technology, learn process, neuroscience knowledge, neuroeducation, training proffesors

Procedia PDF Downloads 57

Authors: Wang Yang

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Shenzhen is a modern city of China's reform and opening-up policy, the development of urban morphology has been established on the administration of the Chinese government. This city`s planning paradigm is primarily affected by the spatial structure and human behavior. The subjective urban agglomeration center is divided into several groups and centers. In comparisons of this effect, the city development law has better to be neglected. With the continuous development of the internet, extensive data technology has been introduced in China. Data mining and data analysis has become important tools in municipal research. Data mining has been utilized to improve data cleaning such as receiving business data, traffic data and population data. Prior to data mining, government data were collected by traditional means, then were analyzed using city-relationship research, delaying the timeliness of urban development, especially for the contemporary city. Data update speed is very fast and based on the Internet. The city's point of interest (POI) in the excavation serves as data source affecting the city design, while satellite remote sensing is used as a reference object, city analysis is conducted in both directions, the administrative paradigm of government is broken and urban research is restored. Therefore, the use of data mining in urban analysis is very important. The satellite remote sensing data of the Shenzhen city in July 2018 were measured by the satellite Modis sensor and can be utilized to perform land surface temperature inversion, and analyze city heat island distribution of Shenzhen. This article acquired and classified the data from Shenzhen by using Data crawler technology. Data of Shenzhen heat island and interest points were simulated and analyzed in the GIS platform to discover the main features of functional equivalent distribution influence. Shenzhen is located in the east-west area of China. The city’s main streets are also determined according to the direction of city development. Therefore, it is determined that the functional area of the city is also distributed in the east-west direction. The urban heat island can express the heat map according to the functional urban area. Regional POI has correspondence. The research result clearly explains that the distribution of the urban heat island and the distribution of urban POIs are one-to-one correspondence. Urban heat island is primarily influenced by the properties of the underlying surface, avoiding the impact of urban climate. Using urban POIs as analysis object, the distribution of municipal POIs and population aggregation are closely connected, so that the distribution of the population corresponded with the distribution of the urban heat island.

Keywords: POI, satellite remote sensing, the population distribution, urban heat island thermal map

Procedia PDF Downloads 101

Authors: Aloke Bapli, Debabrata Seth

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Graphene oxide (GO) is the two-dimensional (2D) nanoscale allotrope of carbon having several physiochemical properties such as high mechanical strength, high surface area, strong thermal and electrical conductivity makes it an important candidate in various modern applications such as drug delivery, supercapacitors, sensors etc. GO has been used in the photothermal treatment of cancers and Alzheimer’s disease etc. The main idea to choose GO in our work is that it is a surface active molecule, it has a large number of hydrophilic functional groups such as carboxylic acid, hydroxyl, epoxide on its surface and in basal plane. So it can easily interact with organic fluorophores through hydrogen bonding or any other kind of interaction and easily modulate the photophysics of the probe molecules. We have used different spectroscopic techniques for our work. The Ground-state absorption spectra and steady-state fluorescence emission spectra were measured by using UV-Vis spectrophotometer from Shimadzu (model-UV-2550) and spectrofluorometer from Horiba Jobin Yvon (model-Fluoromax 4P) respectively. All the fluorescence lifetime and anisotropy decays were collected by using time-correlated single photon counting (TCSPC) setup from Edinburgh instrument (model: LifeSpec-II, U.K.). Herein, we described the photophysics of a hydrophilic molecule 7-(n,n׀-diethylamino) coumarin-3-carboxylic acid (7-DCCA) in the reverse micelles containing GO. It was observed that photophysics of dye is modulated in the presence of GO compared to photophysics of dye in the absence of GO inside the reverse micelles. Here we have reported the solvent relaxation and rotational relaxation time in GO containing reverse micelle and compare our work with normal reverse micelle system by using 7-DCCA molecule. Normal reverse micelle means reverse micelle in the absence of GO. The absorption maxima of 7-DCCA were blue shifted and emission maxima were red shifted in GO containing reverse micelle compared to normal reverse micelle. The rotational relaxation time in GO containing reverse micelle is always faster compare to normal reverse micelle. Solvent relaxation time, at lower w₀ values, is always slower in GO containing reverse micelle compare to normal reverse micelle and at higher w₀ solvent relaxation time of GO containing reverse micelle becomes almost equal to normal reverse micelle. Here emission maximum of 7-DCCA exhibit bathochromic shift in GO containing reverse micelles compared to that in normal reverse micelles because in presence of GO the polarity of the system increases, as polarity increases the emission maxima was red shifted an average decay time of GO containing reverse micelle is less than that of the normal reverse micelle. In GO containing reverse micelle quantum yield, decay time, rotational relaxation time, solvent relaxation time at λₑₓ=375 nm is always higher than λₑₓ=405 nm, shows the excitation wavelength dependent photophysics of 7-DCCA in GO containing reverse micelles.

Keywords: photophysics, reverse micelle, rotational relaxation, solvent relaxation

Procedia PDF Downloads 153

Authors: M. H. Arslan, U. K. Sahin, H. Acikgoz-Tufan, I. Gocek, I. Erdem

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Various exterior factors have perpetual effects on textile materials during wear, use and laundering in everyday life. In accordance with their frequency of use, textile materials are required to be laundered at certain intervals. The medium in which the laundering process takes place have inevitable detrimental physical and chemical effects on textile materials caused by the unique parameters of the process inherently existing. Connatural structures of various textile materials result in many different physical, chemical and mechanical characteristics. Because of their specific structures, these materials have different behaviors against several exterior factors. By modeling the behavior of commercial and test textiles as group-wise against laundering process, it is possible to disclose the relation in between these two groups of materials, which will lead to better understanding of their behaviors in terms of similarities and differences against the washing parameters of the laundering. Thus, the goal of the current research is to examine the behavior of two groups of textile materials as commercial textiles and as test textiles towards the main washing machine parameters during laundering process such as temperature, load quantity, mechanical action and level of water amount by concentrating on shrinkage, pilling, sewing defects, collar abrasion, the other defects other than sewing, whitening and overall properties of textiles. In this study, cotton fabrics were preferred as commercial textiles due to the fact that garments made of cotton are the most demanded products in the market by the textile consumers in daily life. Full factorial experimental set-up was used to design the experimental procedure. All profiles always including all of the commercial and the test textiles were laundered for 20 cycles by commercial home laundering machine to investigate the effects of the chosen parameters. For the laundering process, a modified version of ‘‘IEC 60456 Test Method’’ was utilized. The amount of detergent was altered as 0.5% gram per liter depending on varying load quantity levels. Datacolor 650®, EMPA Photographic Standards for Pilling Test and visual examination were utilized to test and characterize the textiles. Furthermore, in the current study the relation in between commercial and test textiles in terms of their performance was deeply investigated by the help of statistical analysis performed by MINITAB® package program modeling their behavior against the parameters of the laundering process. In the experimental work, the behaviors of both groups of textiles towards washing machine parameters were visually and quantitatively assessed in dry state.

Keywords: behavior against washing machine parameters, performance evaluation of textiles, statistical analysis, commercial and test textiles

Procedia PDF Downloads 357

Authors: Tuna Şahsuvaroğlu

Abstract:

The concept of disability is a concept that has been the subject of many studies in national and international literature with its social, sociological, political, anthropological, economic and social dimensions as well as with individual and social consequences. A disabled person is defined as a person who has difficulties in adapting to social life and meeting daily needs due to loss of physical, mental, spiritual, sensory and social abilities to various degrees, either from birth or for any reason later, and they are in need of protection, care, rehabilitation, counseling and support services. The industrial revolution and the rapid industrialization it brought with it led to an increase in the rate of disabilities resulting from work accidents, in addition to congenital disabilities. This increase has resulted in disabled people included in the employment policies of nations as a disadvantaged group. Although the participation of disabled individuals in the workforce is of great importance in terms of both increasing their quality of life and their integration with society and although disabled individuals are willing to participate in the workforce, they encounter with many problems. One of these problems is the negative attitudes and prejudices that develop in society towards the employment of disabled individuals. One of the most powerful ways to turn these negative attitudes and prejudices into positive ones is education. Education is a way of guiding societies and transferring existing social characteristics to future generations. This can be maintained thanks to teachers, who are one of the most dynamic parts of society and act as the locomotive of education driven by the need to give direction and transfer and basically to help and teach. For this reason, there is a strong relationship between the teaching profession and the attitudes formed in society towards the employment of disabled individuals, as they can influence each other. Therefore, the purpose of this study is to examine teacher candidates' attitudes towards the employment of disabled individuals in terms of various variables. The participants of the study consist of 665 teacher candidates studying at various departments at Marmara University Faculty of Education in the 2022-2023 academic year. The descriptive survey model of the general survey model was used in this study as it intends to determine the attitudes of teacher candidates towards the employment of disabled individuals in terms of different variables. The Attitude Scale Towards Employment of Disabled People was used to collect data. The data were analyzed according to the variables of age, gender, marital status, the department, and whether there is a disabled relative in the family, and the findings were discussed in the context of further research.

Keywords: teacher candidates, disabled, attitudes towards the employment of disabled people, attitude scale towards the employment of disabled people

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Authors: Danish Laidin, Peter Gostomski, Aaron Marshall, Carlo Carere

Abstract:

Groundwater contamination of nitrate (NO3-) is becoming more prevalent in regions of intensive and extensive agricultural activities. Household nitrate removal involves using ion exchange membranes and reverse osmosis (RO) systems, whereas industrial nitrate removal may use organic carbon substrates (e.g. methanol) for heterotrophic microbial denitrification. However, these approaches both require high capital investment and operating costs. In this study, denitrification was demonstrated using bio-electrochemical systems (BESs) inoculated from sediments and microbial enrichment cultures. The BES reactors were operated continuously as microbial electrolytic cells (MECs) with a poised potential of -0.7V and -1.1V vs Ag/AgCl. Three parallel MECs were inoculated using hydrogen-driven denitrifying enrichments, stream sediments, and biofilm harvested from a denitrifying biotrickling filter, respectively. These reactors were continuously operated for over a year as various operating conditions were investigated to determine the optimal conditions for electroactive denitrification. The mass loading rate of nitrate was varied between 10 – 70 mg NO3-/d, and the maximum observed nitrate removal rate was 22 mg NO3- /(cm2∙d) with a current of 2.1 mA. For volumetric load experiments, the dilution rate of 1 mM NO3- feed was varied between 0.01 – 0.1 hr-1 to achieve a nitrate loading rate similar to the mass loading rate experiments. Under these conditions, the maximum rate of denitrification observed was 15.8 mg NO3- /(cm2∙d) with a current of 1.7mA. Hydrogen (H2) was supplied intermittently to investigate the hydrogenotrophic potential of the denitrifying biofilm electrodes. H2 supplementation at 0.1 mL/min resulted in an increase of nitrate removal from 0.3 mg NO3- /(cm2∙d) to 3.4 mg NO3- /(cm2∙d) in the hydrogenotrophically subcultured reactor but had no impact on the reactors which exhibited direct electron transfer properties. Results from this study depict the denitrification performance of the immobilized biofilm electrodes, either by direct electron transfer or hydrogen-driven denitrification, and the contribution of the planktonic cells present in the growth medium. Other results will include the microbial community analysis via 16s rDNA amplicon sequencing, varying the effect of poising cathodic potential from 0.7V to 1.3V vs Ag/AgCl, investigating the potential of using in-situ electrochemically produced hydrogen for autotrophic denitrification and adjusting the conductivity of the feed solution to mimic groundwater conditions. These findings highlight the overall performance of sediment inoculated MECs in removing nitrate and will be used for the future development of sustainable solutions for the treatment of nitrate polluted groundwater.

Keywords: bio-electrochemical systems, groundwater, electroactive denitrification, microbial electrolytic cell

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