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Authors: Suzanne Giasson, Alberto Guerron

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Stimuli-responsive polymer coatings can be used as functional elements in nanotechnologies, such as valves in microfluidic devices, as membranes in biomedical engineering, as substrates for the culture of biological tissues or in developing nanomaterials for targeted therapies in different diseases. However, such coatings usually suffer from major shortcomings, such as a lack of selectivity and poor environmental stability. The study will present multi-responsive hierarchical and hybrid polymer-based coatings aiming to overcome some of these limitations. Hierarchical polymer coatings, consisting of two-dimensional arrays of thermo-responsive cationic PNIPAM-based microgels and surface-functionalized with non-responsive or pH-responsive polymers, were covalently grafted to substrates to tune the surface chemistry and the elasticity of the surface independently using different stimuli. The characteristic dimensions (i.e., layer thickness) and surface properties (i.e., adhesion, friction) of the microgel coatings were assessed using the Surface Forces Apparatus. The ability to independently control the swelling and surface properties using temperature and pH as triggers were investigated for microgels in aqueous suspension and microgels immobilized on substrates. Polymer chain grafting did not impede the ability of cationic PNIPAM microgels to undergo a volume phase transition above the VPTT, either in suspension or immobilized on a substrate. Due to the presence of amino groups throughout the entirety of the microgel polymer network, the swelling behavior was also pH dependent. However, the thermo-responsive swelling was more significant than the pH-triggered one. The microgels functionalized with PEG exhibited the most promising behavior. Indeed, the thermo-triggered swelling of microgel-co-PEG did not give rise to changes in the microgel surface properties (i.e., surface potential and adhesion) within a wide range of pH values. It was possible for the immobilized microgel-co-PEG to undergo a volume transition (swelling/shrinking) with no change in adhesion, suggesting that the surface of the thermal-responsive microgels remains rather hydrophilic above the VPTT. This work confirms the possibility of tuning the swelling behavior of microgels without changing the adhesive properties. Responsive surfaces whose swelling properties can be reversibly and externally altered over space and time regardless of the surface chemistry are very innovative and will enable revolutionary advances in technologies, particularly in biomedical surface engineering and microfluidics, where advanced assembly of functional components is increasingly required.

Keywords: responsive materials, polymers, surfaces, cell culture

Procedia PDF Downloads 53

Authors: Rodrigo Calili, Anna Carolina Sermarini, João Henrique Azevedo, Vanessa Cardoso de Albuquerque, Felipe Gonçalves, Gilberto Jannuzzi

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The diffusion of Distributed Energy Resources (DER) has caused structural changes in the relationship between consumers and electrical systems. The Photovoltaic Distributed Generation (PVDG), in particular, is an essential strategy for achieving the 2030 Agenda goals, especially SDG 7 and SDG 13. However, it is observed that most projects involving this technology in Brazil are restricted to the wealthiest classes of society, not yet reaching the low-income population, aligned with theories of energy justice. Considering the research for energy equality, one of the policies adopted by governments is the social electricity tariff (SET), which provides discounts on energy tariffs/bills. However, just granting this benefit may not be effective, and it is possible to merge it with DER technologies, such as the PVDG. Thus, this work aims to evaluate the economic viability of the policy to replace the social electricity tariff (the current policy aimed at the low-income population in Brazil) by PVDG projects. To this end, a proprietary methodology was developed that included: mapping the stakeholders, identifying critical variables, simulating policy options, and carrying out an analysis in the Brazilian context. The simulation answered two key questions: in which municipalities low-income consumers would have lower bills with PVDG compared to SET; which consumers in a given city would have increased subsidies, which are now provided for solar energy in Brazil and for the social tariff. An economic model was created for verifying the feasibility of the proposed policy in each municipality in the country, considering geographic issues (tariff of a particular distribution utility, radiation from a specific location, etc.). To validate these results, four sensitivity analyzes were performed: variation of the simultaneity factor between generation and consumption, variation of the tariff readjustment rate, zeroing CAPEX, and exemption from state tax. The behind-the-meter modality of generation proved to be more promising than the construction of a shared plant. However, although the behind-the-meter modality presents better results than the shared plant, there is a greater complexity in adopting this modality due to issues related to the infrastructure of the most vulnerable communities (e.g., precarious electrical networks, need to reinforce roofs). Considering the shared power plant modality, many opportunities are still envisaged since the risk of investing in such a policy can be mitigated. Furthermore, this modality can be an alternative due to the mitigation of the risk of default, as it allows greater control of users and facilitates the process of operation and maintenance. Finally, it was also found, that in some regions of Brazil, the continuity of the SET presents more economic benefits than its replacement by PVDG. However, the proposed policy offers many opportunities. For future works, the model may include other parameters, such as cost with low-income populations’ engagement, and business risk. In addition, other renewable sources of distributed generation can be studied for this purpose.

Keywords: low income, subsidy policy, distributed energy resources, energy justice

Procedia PDF Downloads 91

Authors: Christian Skowronski, Andrew Shanholtzer, Brent Yelton, Muayad Almahariq, Daniel J. Krauss

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Prostate cancer has the third highest incidence rate and is the second leading cause of cancer death for men in the United States. Of the diagnostic tools available for intermediate-risk prostate cancer, magnetic resonance imaging (MRI) provides superior soft tissue delineation serving as a valuable tool for both diagnosis and treatment planning. Currently, there is minimal data regarding the practical utility of MRI for evaluation of intermediate-risk prostate cancer. As such, the National Comprehensive Cancer Network’s guidelines indicate MRI as optional in intermediate-risk prostate cancer evaluation. This project aims to elucidate whether MRI affects radiation treatment decisions for intermediate-risk prostate cancer. This was a retrospective study evaluating 210 patients with intermediate-risk prostate cancer, treated with definitive radiotherapy at our institution between 2019-2020. NCCN risk stratification criteria were used to define intermediate-risk prostate cancer. Patients were divided into two groups: those with pretreatment prostate MRI, and those without pretreatment prostate MRI. We compared the use of external beam radiotherapy, brachytherapy alone, brachytherapy boost, and androgen depravation therapy between the two groups. Inverse probability of treatment weighting was used to match the two groups for age, comorbidity index, American Urologic Association symptoms index, pretreatment PSA, grade group, and percent core involvement on prostate biopsy. Wilcoxon Rank Sum and Chi-squared tests were used to compare continuous and categorical variables. Of the patients who met the study’s eligibility criteria, 133 had a prostate MRI and 77 did not. Following propensity matching, there were no differences between baseline characteristics between the two groups. There were no statistically significant differences in treatments pursued between the two groups: 42% vs 47% were treated with brachytherapy alone, 40% vs 42% were treated with external beam radiotherapy alone, 18% vs 12% were treated with external beam radiotherapy with a brachytherapy boost, and 24% vs 17% received androgen deprivation therapy in the non-MRI and MRI groups, respectively. This analysis suggests that pretreatment MRI does not significantly impact radiation therapy or androgen deprivation therapy decisions in patients with intermediate-risk prostate cancer. Obtaining a pretreatment prostate MRI should be used judiciously and pursued only to answer a specific question, for which the answer is likely to impact treatment decision. Further follow up is needed to correlate MRI findings with their impacts on specific oncologic outcomes.

Keywords: magnetic resonance imaging, prostate cancer, definitive radiotherapy, gleason score 7

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Authors: M. Grandcolas, N. Rival, H. Bu, S. Jahren, R. Schmid, H. Johnsen

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The concept of an autonomic self-healing material, where initiation of repair is integrated to the material, is now being considered for engineering applications and is a hot topic in the literature. Among several concepts/techniques, two are most interesting: i) Capsules: Integration of microcapsules in or at the surface of coatings or fibre-like structures has recently gained much attention. Upon damage-induced cracking, the microcapsules are broken by the propagating crack fronts resulting in a release of an active chemical (healing agent) by capillary action, subsequently repairing and avoiding further crack growth. ii) Self-healing polymers: Interestingly, the introduction of dynamic covalent bonds into polymer networks has also recently been used as a powerful approach towards the design of various intrinsically self-healing polymer systems. The idea behind this is to reconnect the chemical crosslinks which are broken when a material fractures, restoring the integrity of the material and thereby prolonging its lifetime. We propose here to integrate both self-healing concepts (capsules, self-healing polymers) in electrospun fibres and coatings. Different capsule preparation approaches have been investigated in SINTEF. The most advanced method to produce capsules is based on emulsification to create a water-in-oil emulsion before polymerisation. The healing agent is a polyurethane-based dispersion that was encapsulated in shell materials consisting of urea-benzaldehyde resins. Results showed the successful preparation of microcapsules and release of the agent when capsules break. Since capsules are produced in water-in-oil systems we mainly investigated organic solvent based coatings while a major challenge resides in the incorporation of capsules into water-based coatings. We also focused on developing more robust microcapsules to prevent premature rupture of the capsules. The capsules have been characterized in terms of size, and encapsulation and release might be visualized by incorporating fluorescent dyes and examine the capsules by microscopy techniques. Alternatively, electrospinning is an innovative technique that has attracted enormous attention due to unique properties of the produced nano-to-micro fibers, ease of fabrication and functionalization, and versatility in controlling parameters. Especially roll-to-roll electrospinning is a unique method which has been used in industry to produce nanofibers continuously. Electrospun nanofibers can usually reach a diameter down to 100 nm, depending on the polymer used, which is of interest for the concept with self-healing polymer systems. In this work, we proved the feasibility of fabrication of POSS-based (POSS: polyhedral oligomeric silsesquioxanes, tradename FunzioNano™) nanofibers via electrospinning. Two different formulations based on aqueous or organic solvents have shown nanofibres with a diameter between 200 – 450nm with low defects. The addition of FunzioNano™ in the polymer blend also showed enhanced properties in term of wettability, promising for e.g. membrane technology. The self-healing polymer systems developed are here POSS-based materials synthesized to develop dynamic soft brushes.

Keywords: capsules, coatings, electrospinning, fibers

Procedia PDF Downloads 241

Authors: Hannah Evangeline Sangeetha

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Ageing is an inevitable change in the life span of an individual. India’s old age population has increased from 19 million in 1947 to 100 million in the 21st century. The United Nations World Population ageing reports that the grey population has immensely increased from 9.2% in 1990 to 11.7 % in 2013, and it’s expected to triple by the year 2050 growing from 737 million to over 2 billion persons 60 years of age and older. Ageing is a period of physical, mental and social decline which brings a host of challenges to the individual and the family. Hence it requires attention at the micro, mezzo and the macro levels of the society. The concepts of healthy and successful aging are being used to help people to change their negative attitude towards aging. This perspective is important to make people realize their potentialities to bring about a change in the minds of senior citizens as well as the society. The objective of this study was to understand the level of active ageing among the rural elderly women and its impact on the quality of life. 330 elderly women from 12 villages of Sriperumbudur associated with the Mobile medical care of Help age India were interviewed using census method. The study revealed the following findings; most respondents in this study were young old between the age group of 60 to 75 years. All the three major religious groups were represented, 85.5percent were Hindus. Majority of the respondents 73.3percent had no education. It was interesting to know that majority of the respondents were self reliant (83.94 percent) and 82.73 percent of them very independent and took care of them by themselves (activities of daily living) without any support from their families. 76.9 percent of the senior women worked based on their competencies, 75.5 percent of them were involved in plenty of activities everyday including their occupation and household chores, which enabled them to be physically active. The chi square values that there is a significant association between the overall active ageing score, religion &number of members in the family. The other demographic variables like age, occupation, income marital status, age at marriage, number of children in the family and Socio –Economic Status were not significantly associated with the overall active aging score. The p-value 0.032 showed Social network and being self-reliant are significantly associated. The study surprisingly shows that most women enjoyed freedom and Independence in their family which is a positive indicator of active ageing.

Keywords: active ageing, quality of life, independence, self reliance

Procedia PDF Downloads 133

Authors: Ei Ei Hlaing, Narissara Lailerd, Sittiruk Roytrakul, Pichapat Piamrojanaphat

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Type 2 diabetes is one of the most common metabolic diseases all over the world. The pathogenesis of type 2 diabetes is not the only dysfunction of pancreatic beta cells but also insulin resistance in muscle, liver and adipose tissue. High levels of circulating free fatty acids, an increased lipid content of muscle cells, impaired insulin-mediated glucose uptake and diminished mitochondrial functioning are pathophysiological hallmarks of diabetic skeletal muscles. Purple rice (Oryza sativa L. indica) has been shown to have antidiabetic effects. However, the underlying mechanism(s) of antidiabetic activity of purple rice is still unraveled. In this research, to explore in-depth cellular mechanism(s), proteomic profile of purple rice supplemented type 2 diabetic rats’ skeletal muscle were analyzed contract with non-supplemented rats. Diabetic rats were induced high-fat diet combined with streptozotocin injection. By using one- dimensional gel electrophoresis (1-DE) and LC-MS/MS quantitative proteomic method, we analyzed proteomic profiles in skeletal muscle of normal rats, normal rats with purple rice supplementation, type 2 diabetic rats, and type 2 diabetic rats with purple rice supplementation. Total 2676 polypeptide expressions were identified. Among them, 24 peptides were only expressed in type 2 diabetic rats, and 24 peptides were unique peptides in type 2 diabetic rats with purple rice supplementation. Acetyl CoA carboxylase 1 (ACACA) found as unique protein in type 2 diabetic rats which is the major enzyme in lipid synthesis and metabolism. Interestingly, DNA damage response protein, heterogeneous nuclear ribonucleoprotein K [Mus musculus] (Hnrnpk), was upregulated in type 2 diabetic rats’ skeletal muscle. Meanwhile, unique proteins of type 2 diabetic rats with purple rice supplementation (bone morphogenetic 7 protein preproprotein, BMP7; and forkhead box protein NX4, Foxn4) involved with muscle cells growth through the regulation of TGF-β/Smad signaling network. Moreover, BMP7 may effect on insulin signaling through the downstream signaling of protein kinase B (Akt) which acts in protein synthesis, glucose uptake, and glycogen synthesis. In conclusion, our study supports that type 2 diabetes impairs muscular lipid metabolism. In addition, purple rice might recover the muscle cells growth and insulin signaling.

Keywords: proteomics, purple rice bran, skeletal muscle, type 2 diabetic rats

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Authors: Martina Santobuono, Wing Sze Chan, Elettra D'Amico, Henriette Selck

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Chemicals in modern society are fundamental in many different aspects of daily human life. We use a wide range of substances, including polychlorinated compounds, pesticides, plasticizers, and pharmaceuticals, to name a few. These compounds are excessively produced, and this has led to their introduction to the environment and food resources. Municipal and industrial effluents, landfills, and agricultural runoffs are a few examples of sources of chemical pollution. Many of these compounds, such as pharmaceuticals, have been proven to mimic or alter the performance of the hormone system, thus disrupting its normal function and altering the behavior and reproductive capability of non-target organisms. Antidepressants are pharmaceuticals commonly detected in the environment, usually in the range of ng L⁻¹ and µg L⁻¹. Since they are designed to have a biological effect at low concentrations, they might pose a risk to the native species, especially if exposure lasts for long periods. Hydrophobic antidepressants, like the selective serotonin reuptake inhibitor (SSRI) Sertraline, can sorb to the particles in the water column and eventually accumulate in the sediment compartment. Thus, deposit-feeding organisms may be at particular risk of exposure. The polychaete Capitella teleta is widespread in estuarine organically enriched sediments, being a key deposit-feeder involved in geochemistry processes happening in sediments. Since antidepressants are neurotoxic chemicals and endocrine disruptors, the aim of this work was to test if sediment-associated Sertraline impacts burrowing- and feeding behavior as well as reproduction capability in Capitella teleta in a chronic exposure set-up, which could better mimic what happens in the environment. 7 days old juveniles were selected and exposed to different concentrations of Sertraline for an entire generation until the mature stage was reached. This work was able to show that some concentrations of Sertraline altered growth and the time of first reproduction in Capitella teleta juveniles, potentially disrupting the population’s capability of survival. Acknowledgments: This Ph.D. position is part of the CHRONIC project “Chronic exposure scenarios driving environmental risks of Chemicals”, which is an Innovative Training Network (ITN) funded by the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Actions (MSCA).

Keywords: antidepressants, Capitella teleta, chronic exposure, endocrine disruption, sublethal endpoints, neurotoxicity

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Authors: Wenhao Li, Shijun Guo

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Carbon fibre reinforced composites are progressively replacing metal structures in modern civil aircraft. This is because composite materials have large potential of weight saving compared with metal. However, the achievement to date of weight saving in composite structure is far less than the theoretical potential due to many uncertainties in structural integrity and safety concern. Unlike the conventional metallic structure, composite components are bonded together along the joints where structural integrity is a major concern. To ensure the safety, metal fasteners are used to reinforce the composite bonded joints. One of the solutions for a significant weight saving of composite structure is to develop an effective technology of on-board Structural Health Monitoring (SHM) System. By monitoring the real-life stress status of composite structures during service, the safety margin set in the structure design can be reduced with confidence. It provides a means of safeguard to minimize the need for programmed inspections and allow for maintenance to be need-driven, rather than usage-driven. The aim of this paper is to develop smart composite joint. The key technology is a multifunctional thermoplastic composite fastener (MTCF). The MTCF will replace some of the existing metallic fasteners in the most concerned locations distributed over the aircraft composite structures to reinforce the joints and form an on-board SHM network system. Each of the MTCFs will work as a unit of the AU and AE technology. The proposed MTCF technology has been patented and developed by Prof. Guo in Cranfield University, UK in the past a few years. The manufactured MTCF has been successfully employed in the composite SLJ (Single-Lap Joint). In terms of the structure integrity, the hybrid SLJ reinforced by MTCF achieves 19.1% improvement in the ultimate failure strength in comparison to the bonded SLJ. By increasing the diameter or rearranging the lay-up sequence of MTCF, the hybrid SLJ reinforced by MTCF is able to achieve the equivalent ultimate strength as that reinforced by titanium fastener. The predicted ultimate strength in simulation is in good agreement with the test results. In terms of the structural health monitoring, a signal from the MTCF was measured well before the load of mechanical failure. This signal provides a warning of initial crack in the joint which could not be detected by the strain gauge until the final failure.

Keywords: composite single-lap joint, crack propagation, multifunctional composite fastener, structural health monitoring

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Authors: Hatem Abou-Senna, Essam Radwan

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With increasing traffic and limited resources, accommodating left-turning traffic has been a challenge for traffic engineers as they seek balance between intersection capacity and safety; these are two conflicting goals in the operation of a signalized intersection that are mitigated through signal phasing techniques. Hence, to increase the left-turn capacity and reduce the delay at the intersections, the Florida Department of Transportation (FDOT) moves forward with a vision of optimizing intersection control using innovative intersection designs through the Transportation Systems Management & Operations (TSM&O) program. These alternative designs successfully eliminate the left-turn phase, which otherwise reduces the conventional intersection’s (CI) efficiency considerably, and divide the intersection into smaller networks that would operate in a one-way fashion. This study focused on the Crossover Displaced Left-turn intersections (XDL), also known as Continuous Flow Intersections (CFI). The XDL concept is best suited for intersections with moderate to high overall traffic volumes, especially those with very high or unbalanced left turn volumes. There is little guidance on determining whether partial XDL intersections are adequate to mitigate the overall intersection condition or full XDL is always required. The primary objective of this paper was to evaluate the overall intersection performance in the case of different partial XDL designs compared to a full XDL. The XDL alternative was investigated for 4 different scenarios; partial XDL on the east-west approaches, partial XDL on the north-south approaches, partial XDL on the north and east approaches and full XDL on all 4 approaches. Also, the impact of increasing volume on the intersection performance was considered by modeling the unbalanced volumes with 10% increment resulting in 5 different traffic scenarios. The study intersection, located in Orlando Florida, is experiencing recurring congestion in the PM peak hour and is operating near capacity with volume to a capacity ratio closer to 1.00 due to the presence of two heavy conflicting movements; southbound and westbound. The results showed that a partial EN XDL alternative proved to be effective and compared favorably to a full XDL alternative followed by the partial EW XDL alternative. The analysis also showed that Full, EW and EN XDL alternatives outperformed the NS XDL and the CI alternatives with respect to the throughput, delay and queue lengths. Significant throughput improvements were remarkable at the higher volume level with percent increase in capacity of 25%. The percent reduction in delay for the critical movements in the XDL scenarios compared to the CI scenario ranged from 30-45%. Similarly, queue lengths showed percent reduction in the XDL scenarios ranging from 25-40%. The analysis revealed how partial XDL design can improve the overall intersection performance at various demands, reduce the costs associated with full XDL and proved to outperform the conventional intersection. However, partial XDL serving low volumes or only one of the critical movements while other critical movements are operating near or above capacity do not provide significant benefits when compared to the conventional intersection.

Keywords: continuous flow intersections, crossover displaced left-turn, microscopic traffic simulation, transportation system management and operations, VISSIM simulation model

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Authors: Sara Rejeb, Catherine Duveau, Tabea Rebafka

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To monitor the production process of turbofan aircraft engines, multiple measurements of various geometrical parameters are systematically recorded on manufactured parts. Engine parts are subject to extremely high standards as they can impact the performance of the engine. Therefore, it is essential to analyze these databases to better understand the influence of the different parameters on the engine's performance. Self-organizing maps are unsupervised neural networks which achieve two tasks simultaneously: they visualize high-dimensional data by projection onto a 2-dimensional map and provide clustering of the data. This technique has become very popular for data exploration since it provides easily interpretable results and a meaningful global view of the data. As such, self-organizing maps are usually applied to aircraft engine condition monitoring. As databases in this field are huge and complex, they naturally contain multiple missing entries for various reasons. The classical Kohonen algorithm to compute self-organizing maps is conceived for complete data only. A naive approach to deal with partially observed data consists in deleting items or variables with missing entries. However, this requires a sufficient number of complete individuals to be fairly representative of the population; otherwise, deletion leads to a considerable loss of information. Moreover, deletion can also induce bias in the analysis results. Alternatively, one can first apply a common imputation method to create a complete dataset and then apply the Kohonen algorithm. However, the choice of the imputation method may have a strong impact on the resulting self-organizing map. Our approach is to address simultaneously the two problems of computing a self-organizing map and imputing missing values, as these tasks are not independent. In this work, we propose an extension of self-organizing maps for partially observed data, referred to as missSOM. First, we introduce a criterion to be optimized, that aims at defining simultaneously the best self-organizing map and the best imputations for the missing entries. As such, missSOM is also an imputation method for missing values. To minimize the criterion, we propose an iterative algorithm that alternates the learning of a self-organizing map and the imputation of missing values. Moreover, we develop an accelerated version of the algorithm by entwining the iterations of the Kohonen algorithm with the updates of the imputed values. This method is efficiently implemented in R and will soon be released on CRAN. Compared to the standard Kohonen algorithm, it does not come with any additional cost in terms of computing time. Numerical experiments illustrate that missSOM performs well in terms of both clustering and imputation compared to the state of the art. In particular, it turns out that missSOM is robust to the missingness mechanism, which is in contrast to many imputation methods that are appropriate for only a single mechanism. This is an important property of missSOM as, in practice, the missingness mechanism is often unknown. An application to measurements on one type of part is also provided and shows the practical interest of missSOM.

Keywords: imputation method of missing data, partially observed data, robustness to missingness mechanism, self-organizing maps

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Authors: Christine Y. Yeh, Brian D. Piening, Sarah M. Totten, Kimberly Kukurba, Wenyu Zhou, Kevin P. F. Contrepois, Gucci J. Gu, Sharon Pitteri, Michael Snyder

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Three million deaths worldwide are attributed to obesity. However, the biomolecular mechanisms that describe the link between adiposity and subsequent disease states are poorly understood. Insulin resistance characterizes approximately half of obese individuals and is a major cause of obesity-mediated diseases such as Type II diabetes, hypertension and other cardiovascular diseases. This study makes use of longitudinal quantitative and high-throughput multi-omics (genomics, epigenomics, transcriptomics, glycoproteomics etc.) methodologies on blood samples to develop multigenic and multi-analyte signatures associated with weight gain and insulin resistance. Participants of this study underwent a 30-day period of weight gain via excessive caloric intake followed by a 60-day period of restricted dieting and return to baseline weight. Blood samples were taken at three different time points per patient: baseline, peak-weight and post weight loss. Patients were characterized as either insulin resistant (IR) or insulin sensitive (IS) before having their samples processed via longitudinal multi-omic technologies. This comparative study revealed a wealth of biomolecular changes associated with weight gain after using methods in machine learning, clustering, network analysis etc. Pathways of interest included those involved in lipid remodeling, acute inflammatory response and glucose metabolism. Some of these biomolecules returned to baseline levels as the patient returned to normal weight whilst some remained elevated. IR patients exhibited key differences in inflammatory response regulation in comparison to IS patients at all time points. These signatures suggest differential metabolism and inflammatory pathways between IR and IS patients. Biomolecular differences associated with weight gain and insulin resistance were identified on various levels: in gene expression, epigenetic change, transcriptional regulation and glycosylation. This study was not only able to contribute to new biology that could be of use in preventing or predicting obesity-mediated diseases, but also matured novel biomedical informatics technologies to produce and process data on many comprehensive omics levels.

Keywords: insulin resistance, multi-omics, next generation sequencing, proteogenomics, type ii diabetes

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Authors: Muhammad Umer Mehmood, Muhammad Luqman, Muhammad Yaseen, Imtiaz Hussain

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Climate change is an arduous fact, which could not be unheeded easily. It is a phenomenon which has brought a collection of challenges for the mankind. Scientists have found many of its negative impacts on the life of human being and the resources on which the life of humanity is dependent. There are many issues which are associated with the factor of prime importance in this study, 'climate change'. Whenever changes happen in nature, they strike the whole globe. Effects of these changes vary from region to region. Climate of every region of this globe is different from the other. Even within a state, country or the province has different climatic conditions. So it is mandatory that the response in that specific region and the coping strategy of this specific region should be according to the prevailing risk. In the present study, the objective was to assess the coping strategies and vulnerability of small landholders. So that a professional suggestion could be made to cope with the vulnerability factor of small farmers. The cross-sectional research design was used with the intervention of quantitative approach. The study was conducted in the Khanewal district, of Punjab, Pakistan. 120 small farmers were interviewed after randomized sampling from the population of respective area. All respondents were above the age of 15 years. A questionnaire was developed after keen observation of facts in the respective area. Content and face validity of the instrument was assessed with SPSS and experts in the field. Data were analyzed through SPSS using descriptive statistics. From the sample of 120, 81.67% of the respondents claimed that the environment is getting warmer and not fit for their present agricultural practices. 84.17% of the sample expressed serious concern that they are disturbed due to change in rainfall pattern and vulnerability towards the climatic effects. On the other hand, they expressed that they are not good at tackling the effects of climate change. Adaptation of coping strategies like change in cropping pattern, use of resistant varieties, varieties with minimum water requirement, intercropping and tree planting was low by more than half of the sample. From the sample 63.33% small farmers said that the coping strategies they adopt are not effective enough. The present study showed that subsistence farming, lack of marketing and overall infrastructure, lack of access to social security networks, limited access to agriculture extension services, inappropriate access to agrometeorological system, unawareness and access to scientific development and low crop yield are the prominent factors which are responsible for the vulnerability of small farmers. A comprehensive study should be conducted at national level so that a national policy could be formulated to cope with the dilemma in future with relevance to climate change. Mainstreaming and collaboration among the researchers and academicians could prove beneficiary in this regard the interest of national leaders’ does matter. Proper policies to avoid the vulnerability factors should be the top priority. The world is taking up this issue with full responsibility as should we, keeping in view the local situation.

Keywords: adaptation, coping strategies, climate change, Pakistan, small farmers, vulnerability

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Authors: Areej Al-Hamad, Yasin Yasin, Kateryna Metersky

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This mixed-method systematic review and meta-analysis provide an encompassing understanding of the barriers, facilitators, and predictors of refugee women's employment and economic inclusion. The study sheds light on the complex interplay of sociocultural, personal, political, and environmental factors influencing these outcomes, underlining the urgent need for a multifaceted, tailored approach to devising strategies, policies, and interventions aimed at boosting refugee women's economic empowerment. Our findings suggest that sociocultural factors, including gender norms, societal attitudes, language proficiency, and social networks, profoundly shape refugee women's access to and participation in the labor market. Personal factors such as age, educational attainment, health status, skills, and previous work experience also play significant roles. Political factors like immigration policies, regulations, and rights to work, alongside environmental factors like labor market conditions, availability of employment opportunities, and access to resources and support services, further contribute to the complex dynamics influencing refugee women's economic inclusion. The significant variability observed in the impacts of these factors across different contexts underscores the necessity of adopting population and region-specific strategies. A one-size-fits-all approach may prove to be ineffective due to the diversity and unique circumstances of refugee women across different geographical, cultural, and political contexts. The study's findings have profound implications for policy-making, practice, education, and research. The insights garnered a call for coordinated efforts across these domains to bolster refugee women's economic participation. In policy-making, the findings necessitate a reassessment of current immigration and labor market policies to ensure they adequately support refugee women's employment and economic integration. In practice, they highlight the need for comprehensive, tailored employment services and interventions that address the specific barriers and leverage the facilitators identified. In education, they underline the importance of language and skills training programs that cater to the unique needs and circumstances of refugee women. Lastly, in research, they emphasize the need for ongoing investigations into the multifaceted factors influencing refugee women's employment experiences, allowing for continuous refinement of our understanding and interventions. Through this comprehensive exploration, the study contributes to ongoing efforts aimed at creating more inclusive, equitable societies. By continually refining our understanding of the complex factors influencing refugee women's employment experiences, we can pave the way toward enhanced economic empowerment for this vulnerable population.

Keywords: refugee women, employment barriers, systematic review, employment facilitators

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Authors: M. Walmsley, S. Elmatarri, S. Mannion

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Introduction: Self-inflicted injury is a recognised cause of major trauma in adults and is an independent indicator of a reduced functional outcome compared to non-intentional major trauma. There is little literature available on the inpatient mental health (MH) management of this vulnerable group. A retrospective review was conducted of inpatient MH management of major trauma patients admitted to a UK regional Major Trauma Centre (MTC). Their outcomes were compared to all major trauma patients. This group of patients required multiple MH interventions whilst on the Major Trauma Ward (MTW) and a had worse functional outcome compared to non-intentional trauma. Method: The national TARN (Trauma Audit and Research Network) database was used to identify patients admitted to a regional MTC over a 2-year period from June 2018 to July 2020. Patients with an ISS (Injury Severity Score) of greater than 15 with a mechanism of either self-harm or high-risk behavior were included for further analysis. Inpatient medical notes were reviewed for MH interventions on the MTW. Further outcomes, including mortality, length of stay (LOS) and Glasgow Outcome Score (GOS) were compared with all major trauma patients for the same time period. Results: A total of 60 patients were identified in the time period and of those, 27 spent time on the MTW. A total of 23 (85%) had a prior MH diagnosis, with 11 (41%) under the care of secondary MH services. Adequate inpatient records for review were available for 24 patients. During their inpatient stay, 8 (33%) were reviewed on the ward by the inpatient MH team. There were 10 interventions required for 6 (25%) patients on the MTW including, sections under the Mental Health Act, transfer to specialist MH facility, pharmacological sedation and security being called to the MTW. When compared to all major trauma patients, those admitted due to self-harm or high-risk behavior had a statistically significantly higher ISS (31.43 vs 24.22, p=0.0001) and LOS (23.51d vs 16.06d, p=0.002). Functional outcomes using the GOS were reduced in this group of patients, GOS 5 (low disability) (51.66% vs. 61.01%) and they additionally had a higher level of mortality, GOS 1 (15.00% vs 11.67%). Discussion: Intentional self-harm is a recognised cause of major trauma in adults and this patient group sustains more severe injuries, requiring a longer hospital stay with worse outcomes compared to all major trauma patients. Inpatient MH interventions are required for a significant proportion of these patients and therefore, there needs to be a close relationship with MH services. There is limited available evidence for how this patient group is best managed as an inpatient to aid their recovery and further work is needed on how outcomes in this vulnerable group can be improved.

Keywords: adult major trauma, attempted suicide, self-inflicted major trauma, inpatient management

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Authors: Jolanta Jonak, Sylvia Tolczyk

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Educational systems are tasked with preparing students for future success in academic or work environments. Schools strive to achieve this goal, but often it is challenging as conventional teaching approaches are often ineffective in increasingly diverse educational systems. In today’s ever-increasing global society, educational systems become increasingly diverse in terms of cultural and linguistic differences, learning preferences and styles, ability and disability. Through increased understanding of disabilities and improved identification processes, students having some form of disabilities tend to be identified earlier than in the past, meaning that more students with identified disabilities are being supported in our classrooms. Also, a large majority of students with disabilities are educated in general education environments. Due to cognitive makeup and life experiences, students have varying learning styles and preferences impacting how they receive and express what they are learning. Many students come from bi or multilingual households and with varying proficiencies in the English language, further impacting their learning. All these factors need to be seriously considered when developing learning opportunities for student's. Educators try to adjust their teaching practices as they discover that conventional methods are often ineffective in reaching each student’s potential. Many teachers do not have the necessary educational background or training to know how to teach students whose learning needs are more unique and may vary from the norm. This is further complicated by the fact that many classrooms lack consistent access to interventionists/coaches that are adequately trained in evidence-based approaches to meet the needs of all students, regardless of what their academic needs may be. One evidence-based way for providing successful education for all students is by incorporating cognitive approaches and strategies that tap into affective, recognition, and strategic networks in the student's brain. This can be done through Differentiated Instruction (DI). Differentiated Instruction is increasingly recognized model that is established on the basic principles of Universal Design for Learning. This form of support ensures that regardless of the students’ learning preferences and cognitive learning profiles, they have opportunities to learn through approaches that are suitable to their needs. This approach improves the educational outcomes of students with special needs and it benefits other students as it accommodates learning styles as well as the scope of unique learning needs that are evident in the typical classroom setting. Differentiated Instruction also is recognized as an evidence-based best practice in education and is highly effective when it is implemented within the tiered system of the Response to Intervention (RTI) model. Recognition of DI becomes more common; however, there is still limited understanding of the effective implementation and use of strategies that can create unique learning environments for each student within the same setting. Through employing knowledge of a variety of instructional strategies, general and special education teachers can facilitate optimal learning for all students, with and without a disability. A desired byproduct of DI is that it can eliminate inaccurate perceptions about the students’ learning abilities, unnecessary referrals for special education evaluations, and inaccurate decisions about the presence of a disability.

Keywords: differentiated instruction, universal design for learning, special education, diversity

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Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

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Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

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Authors: Mustafa Metin Donma, Orkide Donma

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Obesity is a disease with an ever-increasing prevalence throughout the world. The metabolic network associated with obesity is very complicated. In metabolic syndrome (MetS), it becomes even more difficult to understand. Within this context, hormones, cytokines, and many others participate in this complex matrix. The collaboration among all of these parameters is a matter of great wonder. Cortisol, as a stress hormone, is closely associated with obesity. Thyroid hormones are involved in the regulation of energy as well as glucose metabolism with all of its associates. Fetuin A is known for years; however, the involvement of this parameter in obesity discussions is rather new. Recently, it has been defined as one of the new generation markers of obesity. In this study, the aim was to introduce complex interactions among all to be able to make clear comparisons, at least for a part of this complicated matter. Morbid obese (MO) children participated in the study. Two groups with 46 MO children and 43 with MetS were constituted. All children included in the study were above 99th age- and sex-adjusted body mass index (BMI) percentiles according to World Health Organization criteria. Forty-three morbid obese children in the second group had also MetS components. Informed consent forms were filled by the parents of the participants. The institutional ethics committee has given approval for the study protocol. Data as well as the findings of the study were evaluated from a statistical point of view. Two groups were matched for their age and gender compositions. Significantly higher body mass index (BMI), waist circumference, thyrotropin, and insulin values were observed in the MetS group. Triiodothyronine concentrations did not differ between the groups. Elevated levels for thyroxin, cortisol, and fetuin-A were detected in the MetS group compared to the first group (p > 0.05). In MO MetS- group, cortisol was correlated with thyroxin and fetuin-A (p < 0.05). In the MO MetS+ group, none of these correlations were present. Instead, a correlation between cortisol and thyrotropin was found (p < 0.05). In conclusion, findings have shown that cortisol was the key player in severely obese children. The association of this hormone with the participants of thyroid hormone metabolism was quite important. The lack of association with fetuin A in the morbid obese MetS+ group has suggested the possible interference of MetS components in the behavior of this new generation obesity marker. The most remarkable finding of the study was the unique correlation between cortisol and thyrotropin in the morbid obese MetS+ group, suggesting that thyrotropin may serve as a target along with cortisol in the morbid obese MetS+ group. This association may deserve specific attention during the development of remedies against MetS in the pediatric population.

Keywords: children, cortisol, fetuin A, morbid obesity, thyrotropin

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Authors: Gabriela R. Silveira, Claudia S. Rocha, Lais S. Vitti, Jeane L. Borges, Helen B. Durgante

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Emerging adulthood occurs after adolescence in a period that maybe be marked by experimentation, identity reconfigurations, labor life demands, and insertion in the work environment, which tends to generate stress and emotional instability. Health promotion programs for the development of strengths and virtues, based on Positive Psychology, for emerging adults are sparse in Brazil. The aim of this study was to evaluate the preliminary effects of an online multi-component Positive Psychology program for the health promotion of emerging adults based on Cognitive Behavioural Therapy and Positive Psychology. The program included six online (synchronous) weekly group sessions of approximately two hours each and homework (asynchronous) activities. The themes worked were Values and self-care/Prudence, Optimism, Empathy, Gratitude, Forgiveness, and Meaning of life and work. This study presents data from a longitudinal, pre-experimental design with pre (T1) and post-test (T2) evaluation in the intervention group. 47 individuals aged between 19-30 years old participated, mean age of 24.53 years (SD=3.13), 37 females (78.7%). 42 (89.4%) self-defined as heterosexual, four (8.5%) as homosexual, and one (2.5%) as bisexual. 33 (70.2%) had incomplete higher education, four (8.5%) completed higher education, and seven (14.9%) had a graduate level of education. 27 participants worked (57.4%), out of which 25 were health workers (53.2%). 14 (29.8%) were caregivers, 27 (57.4%) had a spiritual belief, 36 (76.6%) had access to leisure, and 38 (80.9%) had perceived social support. The instruments used were a sociodemographic questionnaire, the 10-item Perceived Stress Scale, and the 12-item General Health Questionnaire. The program was advertised on social networks and interested participants filled out the Consent Form and the evaluation protocol at T1 and T2 via Google Docs form. The main research was approved (CEP n.1,899,368; 4,143,219; CAAE: 61997516.5.0000.5334) and complied with sanitary and Ethics criteria in research with human beings. Wilcoxon statistics revealed significant improvements in indicators of perceived stress between T1 (X=22.21, SD=6.79) and T2 (X=15.10, SD=5.82); (Z=-4.353; p=0.001) as well as depression and anxiety symptoms (T1:X=26.72, SD=8.84; T2: X=19.23, SD=4.68); (Z=-3.945, p=0.001) of the emerging adults after their participation in the programme. The programme has an innovative character not only for presenting an online Positive Psychology approach but also for being based on an intervention developed, evaluated, and manualized in Brazil. By focusing on emerging adults, this study contributes to advancing research on a relatively new field in developmental studies. As a limitation, this is a pre-experimental and pilot study, requiring an increase in sample size for greater statistical robustness, also qualitative data analysis is crucial for methodological complementarity. The importance of investing efforts to accompany this age group and provide advances in longitudinal research in the area of health promotion and disease prevention is highlighted.

Keywords: emerging adults, disease prevention, health promotion, online program

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Authors: Stamatis Zoras, Vasilis Evagelopoulos, Theodoros Staurakas

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The association between elevated air pollution levels and extreme climate conditions (temperature, particulate matter, ozone levels, etc.) and mental consequences has been, recently, the focus of significant number of studies. It varies depending on the time of the year it occurs either during the hot period or cold periods but, specifically, when extreme air pollution and weather events are observed, e.g. air pollution episodes and persistent heatwaves. It also varies spatially due to different effects of air quality and climate extremes to human health when considering metropolitan or rural areas. An air pollutant concentration and a climate extreme are taking a different form of impact if the focus area is countryside or in the urban environment. In the built environment the climate extreme effects are driven through the formed microclimate which must be studied more efficiently. Variables such as biological, age groups etc may be implicated by different environmental factors such as increased air pollution/noise levels and overheating of buildings in comparison to rural areas. Gridded air quality and climate variables derived from the land surface observations network of West Macedonia in Greece will be analysed against mortality data in a spatial format in the region of West Macedonia. Artificial intelligence (AI) tools will be used for data correction and prediction of health deterioration with climatic conditions and air pollution at local scale. This would reveal the built environment implications against the countryside. The air pollution and climatic data have been collected from meteorological stations and span the period from 2000 to 2009. These will be projected against the mortality rates data in daily, monthly, seasonal and annual grids. The grids will be operated as AI-based warning models for decision makers in order to map the health conditions in rural and urban areas to ensure improved awareness of the healthcare system by taken into account the predicted changing climate conditions. Gridded data of climate conditions, air quality levels against mortality rates will be presented by AI-analysed gridded indicators of the implicated variables. An Al-based gridded warning platform at local scales is then developed for future system awareness platform for regional level.

Keywords: air quality, artificial inteligence, climatic conditions, mortality

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Authors: Aleksandra Jonas, Aleksandra Gronowska, Maciej Ścigacz, Szymon Jadczak

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Exact Data is a smart tool which helps with meaningful marketing content creation. It helps marketers achieve this by analyzing the text of an advertisement before and after its publication on social media sites like Facebook or Instagram. In our research we focus on four areas of natural language processing (NLP): grammar correction, sentiment analysis, irony detection and advertisement interpretation. Our research has identified a considerable lack of NLP tools for the Polish language, which specifically aid online marketers. In light of this, our research team has set out to create a robust and versatile NLP tool for the Polish language. The primary objective of our research is to develop a tool that can perform a range of language processing tasks in this language, such as sentiment analysis, text classification, text correction and text interpretation. Our team has been working diligently to create a tool that is accurate, reliable, and adaptable to the specific linguistic features of Polish, and that can provide valuable insights for a wide range of marketers needs. In addition to the Polish language version, we are also developing an English version of the tool, which will enable us to expand the reach and impact of our research to a wider audience. Another area of focus in our research involves tackling the challenge of the limited availability of linguistically diverse corpora for non-English languages, which presents a significant barrier in the development of NLP applications. One approach we have been pursuing is the translation of existing English corpora, which would enable us to use the wealth of linguistic resources available in English for other languages. Furthermore, we are looking into other methods, such as gathering language samples from social media platforms. By analyzing the language used in social media posts, we can collect a wide range of data that reflects the unique linguistic characteristics of specific regions and communities, which can then be used to enhance the accuracy and performance of NLP algorithms for non-English languages. In doing so, we hope to broaden the scope and capabilities of NLP applications. Our research focuses on several key NLP techniques including sentiment analysis, text classification, text interpretation and text correction. To ensure that we can achieve the best possible performance for these techniques, we are evaluating and comparing different approaches and strategies for implementing them. We are exploring a range of different methods, including transformers and convolutional neural networks (CNNs), to determine which ones are most effective for different types of NLP tasks. By analyzing the strengths and weaknesses of each approach, we can identify the most effective techniques for specific use cases, and further enhance the performance of our tool. Our research aims to create a tool, which can provide a comprehensive analysis of advertising effectiveness, allowing marketers to identify areas for improvement and optimize their advertising strategies. The results of this study suggest that a smart tool for advertisement analysis can provide valuable insights for businesses seeking to create effective advertising campaigns.

Keywords: NLP, AI, IT, language, marketing, analysis

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Authors: Jožef Ritonja, Bojan Grčar, Boštjan Polajžer

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In recent years, electricity trade between neighboring countries has become increasingly intense. Increasing power transmission over long distances has resulted in an increase in the oscillations of the transmitted power. The damping of the oscillations can be carried out with the reconfiguration of the network or the replacement of generators, but such solution is not economically reasonable. The only cost-effective solution to improve the damping of power oscillations is to use power system stabilizers. Power system stabilizer represents a part of synchronous generator control system. It utilizes semiconductor’s excitation system connected to the rotor field excitation winding to increase the damping of the power system. The majority of the synchronous generators are equipped with the conventional power system stabilizers with fixed parameters. The control structure of the conventional power system stabilizers and the tuning procedure are based on the linear control theory. Conventional power system stabilizers are simple to realize, but they show non-sufficient damping improvement in the entire operating conditions. This is the reason that advanced control theories are used for development of better power system stabilizers. In this paper, the adaptive control theory for power system stabilizers design and synthesis is studied. The presented work is focused on the use of model reference adaptive control approach. Control signal, which assures that the controlled plant output will follow the reference model output, is generated by the adaptive algorithm. Adaptive gains are obtained as a combination of the "proportional" term and with the σ-term extended "integral" term. The σ-term is introduced to avoid divergence of the integral gains. The necessary condition for asymptotic tracking is derived by means of hyperstability theory. The benefits of the proposed model reference adaptive power system stabilizer were evaluated as objectively as possible by means of a theoretical analysis, numerical simulations and laboratory realizations. Damping of the synchronous generator oscillations in the entire operating range was investigated. Obtained results show the improved damping in the entire operating area and the increase of the power system stability. The results of the presented work will help by the development of the model reference power system stabilizer which should be able to replace the conventional stabilizers in power systems.

Keywords: power system, stability, oscillations, power system stabilizer, model reference adaptive control

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Authors: Jessica Gu, Yu Chen

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Knowledge Management (KM) is undoubtable crucial to organizational value creation, learning, and adaptation. Although the rapidly growing KM domain has been fueled with full-fledged methodologies and technologies, studies on KM evolution that bridge the organizational performance and adaptation to the organizational environment are still rarely attempted. In particular, creation (or generation) and diffusion (or share/exchange) of knowledge are of the organizational primary concerns on the problem-solving perspective, however, the optimized distribution of knowledge creation and diffusion endeavors are still unknown to knowledge workers. This research proposed an agent-based model of knowledge creation and diffusion in an organization, aiming at elucidating how the intertwining knowledge flows at microscopic level lead to optimized organizational performance at macroscopic level through evolution, and exploring what exogenous interventions by the policy maker and endogenous adjustments of the knowledge workers can better cope with different environmental conditions. With the developed model, a series of simulation experiments are conducted. Both long-term steady-state and time-dependent developmental results on organizational performance, network and structure, social interaction and learning among individuals, knowledge audit and stocktaking, and the likelihood of choosing knowledge creation and diffusion by the knowledge workers are obtained. One of the interesting findings reveals a non-monotonic phenomenon on organizational performance under turbulent environment while a monotonic phenomenon on organizational performance under a stable environment. Hence, whether the environmental condition is turbulence or stable, the most suitable exogenous KM policy and endogenous knowledge creation and diffusion choice adjustments can be identified for achieving the optimized organizational performance. Additional influential variables are further discussed and future work directions are finally elaborated. The proposed agent-based model generates evidence on how knowledge worker strategically allocates efforts on knowledge creation and diffusion, how the bottom-up interactions among individuals lead to emerged structure and optimized performance, and how environmental conditions bring in challenges to the organization system. Meanwhile, it serves as a roadmap and offers great macro and long-term insights to policy makers without interrupting the real organizational operation, sacrificing huge overhead cost, or introducing undesired panic to employees.

Keywords: knowledge creation, knowledge diffusion, agent-based modeling, organizational performance, decision making evolution

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Authors: Rui Fonseca-Pinto, Emanuel Silva, Rui Rijo, Ricardo Martinho, Bruno Carreira

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The sedentary lifestyle is associated to the development of chronic noncommunicable diseases (obesity, hypertension, Diabetes Mellitus Type 2) and the World Health Organization, given the evidence that physical activity is determinant for individual and collective health, defined the Physical Activity Level (PAL) as a vital signal. Strategies for increasing the practice of physical activity in all age groups have emerged from the various social organizations (municipalities, universities, health organizations, companies, social groups) by increasingly developing innovative strategies to promote motivation strategies and conditions to the practice of physical activity. The adaptation of cities to the new paradigms of sustainable mobility has provided the adaptation of urban training circles and mobilized citizens to combat sedentarism. This adaptation has accompanied the technological evolution and makes possible the use of mobile technology to monitor outdoor training programs and also, through the network connection (IoT), use the training data to make personalized recommendations. This work presents a physical activity counseling platform to be used in the physical maintenance circuits of urban centers, the MOVIDA.polis. The platform consists of a back office for the management of circuits and training stations, and for a mobile application for monitoring the user performance during workouts. Using a QRcode, each training station is recognized by the App and based on the individual performance records (effort perception, heart rate variation) artificial intelligence algorithms are used to make a new personalized recommendation. The results presented in this work were obtained during the proof of concept phase, which was carried out in the PolisLeiria training circuit in the city of Leiria (Portugal). It was possible to verify the increase in adherence to the practice of physical activity, as well as to decrease the interval between training days. Moreover, the AI-based recommendation acts as a partner in the training and an additional challenging factor. The platform is ready to be used by other municipalities in order to reduce the levels of sedentarism and approach the weekly goal of 150 minutes of moderate physical activity. Acknowledgments: This work was supported by Fundação para a Ciência e Tecnologia FCT- Portugal and CENTRO2020 under the scope of MOVIDA project: 02/SAICT/2016 – 23878.

Keywords: physical activity, mHealth, urban training circuits, health promotion

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Authors: Zainab Algharibi, Julie McAdam, Catherine Fagan

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The purpose of this paper is to shed light on how Omani children in the first grade experience their needs during their transition to primary school. Theoretically, the paper was built on two perspectives: Dewey's concept of continuity of experience and the boundary objects introduced by Vygotsky (CHAT). The methodology of the study is based on the crucial role of children’s agency which is a very important activity as an educational tool to enhance the child’s participation in the learning process and develop their ability to face various issues in their life. Thus, the data were obtained from 45 children in grade one from 4 different primary schools using drawing and visual narrative activities, in addition to researcher observations during the start of the first weeks of the academic year for the first grade. As the study dealt with children, all of the necessary ethical laws were followed. This paper is considered original since it seeks to deal with the issue of children's transition from kindergarten to primary school in Oman, if not in the Arab region. Therefore, it is expected to fill an important gap in this field and present a proposal that will be a door for researchers to enter this research field later. The analysis of drawing and visual narrative was performed according to the social semiotics approach in two phases. The first is to read out the surface message “denotation,” while the second is to go in-depth via the symbolism obtained from children while they talked and drew letters and signs. This stage is known as “signified”; a video was recorded of each child talking about their drawing and expressing themself. Then, the data were organised and classified according to a cross-data network. Regarding the researcher observation analyses, the collected data were analysed according to the model was developed for the "grounded theory". It is based on comparing the recent data collected from observations with data previously encoded by other methods in which children were drawing alongside the visual narrative in the current study, in order to identify the similarities and differences, and also to clarify the meaning of the accessed categories and to identify sub-categories of them with a description of possible links between them. This is a kind of triangulation in data collection. The study came up with a set of findings, the most vital being that the children's greatest interest goes to their social and psychological needs, such as friends, their teacher, and playing. Also, their biggest fears are a new place, a new teacher, and not having friends, while they showed less concern for their need for educational knowledge and skills.

Keywords: children’s academic needs, children’s social needs, transition, primary school

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Authors: Fazli Rahim Shinwari, Ulrich Dittmer

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Like many megacities around the world, Kabul is facing severe problems due to the rising frequency of urban flooding. Since 2001, Kabul is experiencing rapid population growth because of the repatriation of refugees and internal migration. Due to unplanned development, green areas inside city and hilly areas within and around the city are converted into new housing towns that had increased runoff. Trenches along the roadside comprise the unplanned drainage network of the city that drains the combined sewer flow. In rainy season overflow occurs, and after streets become dry, the dust particles contaminate the air which is a major cause of air pollution in Kabul city. In this study, a stormwater management model is introduced as a basis for a systematic approach to urban drainage planning in Kabul. For this purpose, Kabul city is delineated into 8 watersheds with the help of one-meter resolution LIDAR DEM. Storm, water management model, is developed for Wazirabad catchment by using available data and literature values. Due to lack of long term metrological data, the model is only run for hourly rainfall data of a rain event that occurred in April 2016. The rain event from 1st to 3rd April with maximum intensity of 3mm/hr caused huge flooding in Wazirabad Catchment of Kabul City. Model-estimated flooding at some points of the catchment as an actual measurement of flooding was not possible; results were compared with information obtained from local people, Kabul Municipality and Capital Region Independent Development Authority. The model helped to identify areas where flooding occurred because of less capacity of drainage system and areas where the main reason for flooding is due to blockage in the drainage canals. The model was used for further analysis to find a sustainable solution to the problem. The option to construct new canals was analyzed, and two new canals were proposed that will reduce the flooding frequency in Wazirabad catchment of Kabul city. By developing the methodology to develop a stormwater management model from digital data and information, the study had fulfilled the primary objective, and similar methodology can be used for other catchments of Kabul city to prepare an emergency and long-term plan for drainage system of Kabul city.

Keywords: urban hydrology, storm water management, modeling, SWMM, GEO-SWMM, GIS, identification of flood vulnerable areas, urban flooding analysis, sustainable urban drainage

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Authors: Tatsuya Kasuga, Hidehisa Shimada, Kimio Oguchi

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Recent rapid progress in ICT (Information and Communication Technology) has advanced the penetration of sensor networks (SNs) and their attractive applications. Agriculture is one of the fields well able to benefit from ICT. Plant factories control several parameters related to plant growth in closed areas such as air temperature, humidity, water, culture medium concentration, and artificial lighting by using computers and AI (Artificial Intelligence) is being researched in order to obtain stable and safe production of vegetables and medicinal plants all year anywhere, and attain self-sufficiency in food. By providing isolation from the natural environment, a plant factory can achieve higher productivity and safe products. However, the biggest issue with plant factories is the return on investment. Profits are tenuous because of the large initial investments and running costs, i.e. electric power, incurred. At present, LED (Light Emitting Diode) lights are being adopted because they are more energy-efficient and encourage photosynthesis better than the fluorescent lamps used in the past. However, further cost reduction is essential. This paper introduces experiments that reveal which color of LED lighting best enhances the growth of cultured radish sprouts. Radish sprouts were cultivated in the experimental environment formed by a hydroponics kit with three cultivation shelves (28 samples per shelf) each with an artificial lighting rack. Seven LED arrays of different color (white, blue, yellow green, green, yellow, orange, and red) were compared with a fluorescent lamp as the control. Lighting duration was set to 12 hours a day. Normal water with no fertilizer was circulated. Seven days after germination, the length, weight and area of leaf of each sample were measured. Electrical power consumption for all lighting arrangements was also measured. Results and discussions: As to average sample length, no clear difference was observed in terms of color. As regards weight, orange LED was less effective and the difference was significant (p < 0.05). As to leaf area, blue, yellow and orange LEDs were significantly less effective. However, all LEDs offered higher productivity per W consumed than the fluorescent lamp. Of the LEDs, the blue LED array attained the best results in terms of length, weight and area of leaf per W consumed. Conclusion and future works: An experiment on radish sprout cultivation under 7 different color LED arrays showed no clear difference in terms of sample size. However, if electrical power consumption is considered, LEDs offered about twice the growth rate of the fluorescent lamp. Among them, blue LEDs showed the best performance. Further cost reduction e.g. low power lighting remains a big issue for actual system deployment. An automatic plant monitoring system with sensors is another study target.

Keywords: electric power consumption, LED color, LED lighting, plant factory

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Authors: Chia-Wen Wang, Patou Masika Musumari, Teeranee Techasrivichien, S. Pilar Suguimoto, Chang-Chuan Chan, Masako Ono-Kihara, Masahiro Kihara

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Background: In recent years, a particular form of bullying, referred to as 'cyberbullying' has emerged along with the rapid expansion of the Internet, social network services (SNSs) and smart phones. Many Asian countries, including Taiwan, are faced with both the cyberbullying and the traditional form of bullying. This study aims to explore Taiwanese adolescents’ experiences, perceptions and opinions regarding cyberbullying and traditional bullying through the perspective of victim, perpetrator, or witness. Method: This is a qualitative study using face-to-face in-depth interviews guided by a semi-structured questionnaire among high school students -aged 16 to 18 years- in Taipei, Taiwan. The participants were recruited through convenience sampling from five high schools between June and November 2016. Interviews were digitally recorded, transcribed, and analyzed using the thematic analysis approach. Results: Forty-eight participants were recruited, of which, 14 (29.2%) reported had ever experienced bullying. Specifically, 7 participants (14.6%) reported had ever been victims of cyberbullying, 1 (2%) had been victims of traditional bullying, and 6 (12.5%) had been victims of both cyber and traditional bullying. The majority (70.8%) reported had ever witnessed acts of bullying; however, none of the participants recognized had ever been a perpetrator of bullying. Cyberbullying mostly happens on social media (Facebook and Instagram) or LINE instant messaging application, and included upload and sharing of degrading pictures and videos of victims, as well as gossip and mean messages by the perpetrators. The anonymous and public nature of social media groups in schools made it easier to perpetrate bullying. The victim of traditional bullying reported being the target of verbal attack because of his physical appearance. Regardless of the type of bullying, victims reported feeling bad, angry, or depressed as a result of being bullied. Witnesses of both cyber- and traditional bullying cited physical appearance (e.g. having the big/flat bust or big butt, or overweight or obese) and disability as the most reasons of being a bullying victim. Conclusion: Both cyberbullying and traditional bullying had negative emotional and psychological impacts on victims. This study warrants further research to assess the extent of this phenomenon and understand the characteristics of perpetrators, victims, and witnesses to inform the design of tailored interventions using appropriate channels of dissemination.

Keywords: cyberbullying, traditional bullying, social media, adolescents

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Authors: Gu Sihao

Abstract:

The coordinated development of "ecology-production-life" in cities has been highly concerned by the country, and the transformation development and sustainable development of resource-based cities have become a hot research topic at present. As an important part of China's resource-based cities, coal resource-based cities have the characteristics of large number and wide distribution. However, due to the adjustment of national energy structure and the gradual exhaustion of urban coal resources, the development vitality of coal resource-based cities is gradually reduced. In many studies, the deterioration of ecological environment in coal resource-based cities has become the main problem restricting their urban transformation and sustainable development due to the "emphasis on economy and neglect of ecology". Since the 18th National Congress of the Communist Party of China (CPC), the Central Government has been deepening territorial space planning and development. On the premise of optimizing territorial space development pattern, it has completed the demarcation of ecological protection red lines, carried out ecological zoning and ecosystem evaluation, which have become an important basis and scientific guarantee for ecological modernization and ecological civilization construction. Grasp the regional multiple ecosystem services is the precondition of the ecosystem management, and the relationship between the multiple ecosystem services study, ecosystem services cluster can identify the interactions between multiple ecosystem services, and on the basis of the characteristics of the clusters on regional ecological function zoning, to better Social-Ecological system management. Based on this cognition, this study optimizes the spatial function zoning of Gujiao, a coal resource-based city, in order to provide a new theoretical basis for its sustainable development. This study is based on the detailed analysis of characteristics and utilization of Gujiao city land space, using SOFM neural networks to identify local ecosystem service clusters, according to the cluster scope and function of ecological function zoning of space partition balance and coordination between different ecosystem services strength, establish a relationship between clusters and land use, and adjust the functions of territorial space within each zone. Then, according to the characteristics of coal resources city and national spatial function zoning characteristics, as the driving factors of land change, by cellular automata simulation program, such as simulation under different restoration strategy situation of urban future development trend, and provides relevant theories and technical methods for the "third-line" demarcations of Gujiao's territorial space planning, optimizes territorial space functions, and puts forward targeted strategies for the promotion of regional ecosystem services, providing theoretical support for the improvement of human well-being and sustainable development of resource-based cities.

Keywords: coal resource-based city, territorial spatial planning, ecosystem service cluster, gmop model, geosos-FLUS model, functional zoning optimization and upgrading

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Authors: Francesco Saverio Angiò

Abstract:

The Islamic State of Iraq and the Levant / Syria (ISIL/S), Al-Qaeda in the Islamic Maghreb (AQIM) and People Committed to the Propagation of the Prophet's Teachings and Jihad, also known as ‘Boko Haram’ (BH), have fought successfully against Syria and Iraq, Mali, Nigeria’s government, respectively. According to Napoleoni, the ‘shell-state’ concept can explain the economic dimension and the financing model of the ISIL insurgency. However, she argues that AQIM and BH did not properly plan their financial model. Consequently, her idea would not be suitable to these groups. Nevertheless, AQIM and BH’s economic performances and their (short) territorialisation suggest that their financing models respond to a well-defined strategy, which they were able to adapt to new circumstances. Therefore, Napoleoni’s idea of ‘shell-state’ can be applied to the three jihadist armed groups. In the last five years, together with other similar entities, ISIL/S, AQIM and BH have been fighting against governments with insurgent tactics and terrorism acts, conquering and ruling a quasi-state; a physical space they presented as legitimate territorial entity, thanks to a puritan version of the Islamic law. In these territories, they have exploited the traditional local economic networks. In addition, they have contributed to the development of legal and illegal transnational business activities. They have also established a justice system and created an administrative structure to supply services. Napoleoni’s ‘shell-state’ can describe the evolution of ISIL/S, AQIM and BH, which has switched from an insurgency to a proto or a quasi-state entity, enjoying a significant share of power over territories and populations. Napoleoni first developed and applied the ‘Shell-state’ concept to describe the nature of groups such as the Palestine Liberation Organisation (PLO), before using it to explain the expansion of ISIL. However, her original conceptualisation emphasises on the economic dimension of the rise of the insurgency, focusing on the ‘business’ model and the insurgents’ financing management skills, which permits them to turn into an organisation. However, the idea of groups which use, coordinate and grab some territorial economic activities (at the same time, encouraging new criminal ones), can also be applied to administrative, social, infrastructural, legal and military levels of their insurgency, since they contribute to transform the insurgency to the same extent the economic dimension does. In addition, according to Napoleoni’s view, the ‘shell-state’ prism is valid to understand the ISIL/S phenomenon, because the group has carefully planned their financial steps. Napoleoni affirmed that ISIL/S carries out activities in order to promote their conversion from a group relying on external sponsors to an entity that can penetrate and condition local economies. On the contrary, ‘shell-state’ could not be applied to AQIM or BH, which are acting more like smugglers. Nevertheless, despite its failure to control territories, as ISIL has been able to do, AQIM and BH have responded strategically to their economic circumstances and have defined specific dynamics to ensure a flow of stable funds. Therefore, Napoleoni’s theory is applicable.

Keywords: shell-state, jihadist insurgency, proto or quasi-state entity economic planning, strategic financing

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Authors: Hamsasew Hankebo Lemago, Dóra Hessz, Zoltán Erdélyi, Imre Miklós Szilágyi

Abstract:

Metal oxide inverse opals are a unique class of photocatalysts with a hierarchical structure that mimics the natural opal gemstone. They are composed of a network of interconnected pores, which provides a large surface area and efficient pathways for the transport of light and reactants. Atomic layer deposition (ALD) is a versatile technique for the synthesis of high-precision metal oxide thin films, including inverse opals. ALD allows for precise control over the thickness, composition, and morphology of the synthesized films, making it an ideal technique for the fabrication of photocatalysts with tailored properties. In this study, we report the synthesis of TiO2, ZnO, and Al2O3 inverse opal photocatalysts using thermal or plasma-enhanced ALD. The synthesized photocatalysts were characterized using a variety of techniques, including scanning electron microscopy (SEM)-energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), Raman spectroscopy, photoluminescence (PL), ellipsometry, and UV-visible spectroscopy. The results showed that the ALD-synthesized metal oxide inverse opals had a highly ordered structure and a tunable pore size. The PL spectroscopy results showed low recombination rates of photogenerated electron-hole pairs, while the ellipsometry and UV-visible spectroscopy results showed tunable optical properties and band gap energies. The photocatalytic activity of the samples was evaluated by the degradation of methylene blue under visible light irradiation. The results showed that the ALD-synthesized metal oxide inverse opals exhibited high photocatalytic activity, even under visible light irradiation. The composites photocatalysts showed even higher activity than the individual metal oxide inverse opals. The enhanced photocatalytic activity of the composites can be attributed to the synergistic effect between the different metal oxides. For example, Al2O3 can act as a charge carrier scavenger, which can reduce the recombination of photogenerated electron-hole pairs. The ALD-synthesized metal oxide inverse opals and their composites are promising photocatalysts for a variety of applications, such as wastewater treatment, air purification, and energy production. For example, they can be used to remove organic pollutants from wastewater, decompose harmful gases in the air, and produce hydrogen fuel from water.

Keywords: ALD, metal oxide inverse opals, composites, photocatalysis

Procedia PDF Downloads 58