Search results for: fixed partial denture

Authors: Mariana Stuparu-Cretu, Doina-Carina Voinescu, Rodica-Mihaela Dinica, Daniela Borda, Camelia Vizireanu, Gabriela Iordachescu, Camelia Busila

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Obesity is involved in the etiology or acceleration of progression of important non-communicable diseases, such as: metabolic, cardiovascular, rheumatological, oncological and depression. It is a need to prevent the obesity occurrence, like a key link in disease management. From this point of view, the best approach is to early educate youngsters upon the need for a healthy nutrition lifestyle associated with constant physical activities. The objective of the study was to assess correlations between weight condition, physical activities and food preferences of students from South East Romania. Questionnaires were applied on high school students in Galati: 1006 girls and 880 boys, aged between 14 and 19 years (being approved by Local School Inspectorate and the Ethics Committee of the 'Dunarea de Jos' University of Galati). The collected answers have been statistically processed by using the multivariate regression method (PLS2) by Unscramble X program (Camo, Norway). Multiple variables such as age group, body mass index, nutritional habits and physical activities were separately analysed, depending on gender and general mathematical models were proposed to explain the obesity trend at an early age. The study results show that overweight and obesity are present in less than a fifth of the adolescents who were surveyed. With a very small variation and a strong correlation of over 86% for 99% of the cases, a general preference for sweet foods, nocturnal eating associated with computer work and a reduced period of physical activity is noticed for girls. In addition, the overweight girls consume sweet juices and alcohol, although a percentage of them also practice the gym. There is also a percentage of the normoponderal girls that consume high caloric foods which predispose this group to turn into overweight cases in time. Within the studied group, statistics for the boys show a positive correlation of almost 87% for over 96% of cases. They prefer high calories foods, fast food, and sweet juices, and perform medium physical activities. Both overweight and underweight boys are more sedentary. Over 15% of girls and over a quarter of boys consume alcohol. All these bad eating habits seem to increase with age, for both sexes. To conclude, obesity and overweight assessed in adolescents in S-E Romania reveal nonsignificant percentage differences between boys and girls. However, young people in this area of the country are sedentary in general; a significant percentage prefers sweets / sweet juices / fast-food and practice computer nourishing. The authors consider that at this age, it is very useful to adapt nutritional education by new methods of food processing and market supply. This would require an early understanding of the difference among foods and nutrients and the benefits of physical activities integrated into the healthy current lifestyle, as a measure for preventing and managing non-communicable chronic diseases related to nutritional errors and sedentarism. Acknowledgment— This study has been partial founded by the Francophone University Agency, Project Réseau régional dans le domaine de la santé, la nutrition et la sécurité alimentaire (SaIN), no.21899/ 06.09.2017.

Keywords: adolescents, body mass index, nutritional habits, obesity, physical activity

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Authors: Moroof, O. Oloruntola, Sunday Oladele, Daniel, O. Obasaju, Victor, O Ojekunle, Olateju, O. Bayewu, Ganiyu, O. Mosuro

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Integrated geophysical methods involving Vertical Electrical Sounding (VES) and 2D resistivity survey were deployed to gain an insight into the influence of the two varying rock types (mica-schist and granite gneiss) underlying the road alignment to the incessant highway failure along Ajaokuta-Anyigba, North-central Nigeria. The highway serves as a link-road for the single largest cement factory in Africa (Dangote Cement Factory) and two major ceramic industries to the capital (Abuja) via Lokoja. 2D Electrical Resistivity survey (Dipole-Dipole Array) and Vertical Electrical Sounding (VES) (Schlumberger array) were employed. Twenty-two (22) 2D profiles were occupied, twenty (20) conducted about 1 m away from the unstable section underlain by mica-schist with profile length each of approximately 100 m. Two (2) profiles were conducted about 1 m away from the stable section with a profile length of 100 m each due to barriers caused by the drainage system and outcropping granite gneiss at the flanks of the road. A spacing of 2 m was used for good image resolution of the near-surface. On each 2D profile, a range of 1-3 VES was conducted; thus, forty-eight (48) soundings were acquired. Partial curve matching and WinResist software were used to obtain the apparent and true resistivity values of the 1D survey, while DiprofWin software was used for processing the 2-D survey. Two exposed lithologic sections caused by abandoned river channels adjacent to two profiles as well as the knowledge of the geology of the area helped to constrain the VES and 2D processing and interpretation. Generally, the resistivity values obtained reflect the parent rock type, degree of weathering, moisture content and competency of the tested area. Resistivity values < 100; 100 – 950; 1000 – 2000 and > 2500 ohms-m were interpreted as clay, weathered layer, partly weathered layer and fresh basement respectively. The VES results and 2-D resistivity structures along the unstable segment showed similar lithologic characteristics and sequences dominated by clayey substratum for depths range of 0 – 42.2 m. The clayey substratum is a product of intensive weathering of the parent rock (mica-schist) and constitutes weak foundation soils, causing highway failure. This failure is further exacerbated by several heavy-duty trucks which ply the section round the clock due to proximity to two major ceramic industries in the state and lack of drainage system. The two profiles on the stable section show 2D structures that are remarkably different from those of the unstable section with very thin topsoils, higher resistivity weathered substratum (indicating the presence of coarse fragments from the parent rock) and shallow depth to the basement (1.0 – 7. 1 m). Also, the presence of drainage and lower volume of heavy-duty trucks are contributors to the pavement stability of this section of the highway. The resistivity surveys effectively delineated two contrasting soil profiles of the subbase/subgrade that reflect variation in the mineralogy of underlying parent rocks.

Keywords: clay, geophysical methods, pavement, resistivity

Procedia PDF Downloads 139

Authors: Azeem Tariq, Stephane De Tourdonnet, Lars Stoumann Jensen, Reiner Wassmann, Bjoern Ole Sander, Quynh Duong Vu, Trinh Van Mai, Andreas De Neergaard

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Rice growing area is increasing to meet the food demand of increasing population. Mostly, rice is growing on lowland, small landholder fields in most part of the world, which is one of the major sources of greenhouse gases (GHG) emissions from agriculture fields. The strategies such as, altering water and residues (carbon) management practices are assumed to be essential to mitigate the GHG emissions from flooded rice system. The actual implementation and potential of these measures on small farmer fields is still challenging. A field study was conducted on red river delta in Northern Vietnam to identify the potential challenges and barriers to the small rice farmers for implementation of climate smart rice practices. The objective of this study was to develop and access the feasibility of climate smart rice prototypes under actual farmer conditions. Field and scientific oriented framework was used to meet our objective. The methodological framework composed of six steps: i) identification of stakeholders and possible options, ii) assessment of barrios, drawbacks/advantages of new technologies, iii) prototype design, iv) assessment of mitigation potential of each prototype, v) scenario building and vi) scenario assessment. A farm survey was conducted to identify the existing farm practices and major constraints of small rice farmers. We proposed the two water (pre transplant+midseason drainage and early+midseason drainage) and one straw (full residue incorporation) management option keeping in views the farmers constraints and barriers for implementation. To test new typologies with existing prototypes (midseason drainage, partial residue incorporation) at farmer local conditions, a participatory field experiment was conducted for two consecutive rice seasons at farmer fields. Following the results of each season a workshop was conducted with stakeholders (farmers, village leaders, cooperatives, irrigation staff, extensionists, agricultural officers) at local and district level to get feedbacks on new tested prototypes and to develop possible scenarios for climate smart rice production practices. The farm analysis survey showed that non-availability of cheap labor and lacks of alternatives for straw management influence the small farmers to burn the residues in the fields except to use for composting or other purposes. Our field results revealed that application of early season drainage significantly mitigates (40-60%) the methane emissions from residue incorporation. Early season drainage was more efficient and easy to control under cooperate manage system than individually managed water system, and it leads to both economic (9-11% high rice yield, low cost of production, reduced nutrient loses) and environmental (mitigate methane emissions) benefits. The participatory field study allows the assessment of adaptation potential and possible benefits of climate smart practices on small farmer fields. If farmers have no other residue management option, full residue incorporation with early plus midseason drainage is adaptable and beneficial (both environmentally and economically) management option for small rice farmers.

Keywords: adaptation, climate smart agriculture, constrainsts, smallholders

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Authors: Simon Komesker, Achim Wagner, Martin Ruskowski

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In times of volatile markets with fluctuating demand and the uncertainty of global supply chains, flexible production systems are the key to an efficient implementation of a desired production program. In this publication, the authors present a holistic information concept taking into account various influencing factors for operating towards the global optimum. Therefore, a strategy for the implementation of multi-level planning for a flexible, reconfigurable production system with an alternative production concept in the automotive industry is developed. The main contribution of this work is a system structure mixing central and decentral planning and control evaluated in a simulation framework. The information system structure in current production systems in the automotive industry is rigidly hierarchically organized in monolithic systems. The production program is created rule-based with the premise of achieving uniform cycle time. This program then provides the information basis for execution in subsystems at the station and process execution level. In today's era of mixed-(car-)model factories, complex conditions and conflicts arise in achieving logistics, quality, and production goals. There is no provision for feedback loops of results from the process execution level (resources) and process supporting (quality and logistics) systems and reconsideration in the planning systems. To enable a robust production flow, the complexity of production system control is artificially reduced by the line structure and results, for example in material-intensive processes (buffers and safety stocks - two container principle also for different variants). The limited degrees of freedom of line production have produced the principle of progress figure control, which results in one-time sequencing, sequential order release, and relatively inflexible capacity control. As a result, modularly structured production systems such as modular production according to known approaches with more degrees of freedom are currently difficult to represent in terms of information technology. The remedy is an information concept that supports cross-system and cross-level information processing for centralized and decentralized decision-making. Through an architecture of hierarchically organized but decoupled subsystems, the paradigm of hybrid control is used, and a holonic manufacturing system is offered, which enables flexible information provisioning and processing support. In this way, the influences from quality, logistics, and production processes can be linked holistically with the advantages of mixed centralized and decentralized planning and control. Modular production systems also require modularly networked information systems with semi-autonomous optimization for a robust production flow. Dynamic prioritization of different key figures between subsystems should lead the production system to an overall optimum. The tasks and goals of quality, logistics, process, resource, and product areas in a cyber-physical production system are designed as an interconnected multi-agent-system. The result is an alternative system structure that executes centralized process planning and decentralized processing. An agent-based manufacturing control is used to enable different flexibility and reconfigurability states and manufacturing strategies in order to find optimal partial solutions of subsystems, that lead to a near global optimum for hybrid planning. This allows a robust near to plan execution with integrated quality control and intralogistics.

Keywords: holonic manufacturing system, modular production system, planning, and control, system structure

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Authors: Parag Katira, Frederika Rentzeperis, Zuzanna Nowicka, Giada Fiandaca, Thomas Veith, Jack Farinhas, Noemi Andor

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Resource limitations shape the outcome of competitions between genetically heterogeneous pre-malignant cells. One example of such heterogeneity is in the ploidy (DNA content) of pre-malignant cells. A whole-genome duplication (WGD) transforms a diploid cell into a tetraploid one and has been detected in 28-56% of human cancers. If a tetraploid subclone expands, it consistently does so early in tumor evolution, when cell density is still low, and competition for nutrients is comparatively weak – an observation confirmed for several tumor types. WGD+ cells need more resources to synthesize increasing amounts of DNA, RNA, and proteins. To quantify resource limitations and how they relate to ploidy, we performed a PAN cancer analysis of WGD, PET/CT, and MRI scans. Segmentation of >20 different organs from >900 PET/CT scans were performed with MOOSE. We observed a strong correlation between organ-wide population-average estimates of Oxygen and the average ploidy of cancers growing in the respective organ (Pearson R = 0.66; P= 0.001). In-vitro experiments using near-diploid and near-tetraploid lineages derived from a breast cancer cell line supported the hypothesis that DNA content influences Glucose- and Oxygen-dependent proliferation-, death- and migration rates. To model how subpopulations with variable DNA content compete in the resource-limited environment of the human brain, we developed a stochastic state-space model of the brain (S3MB). The model discretizes the brain into voxels, whereby the state of each voxel is defined by 8+ variables that are updated over time: stiffness, Oxygen, phosphate, glucose, vasculature, dead cells, migrating cells and proliferating cells of various DNA content, and treat conditions such as radiotherapy and chemotherapy. Well-established Fokker-Planck partial differential equations govern the distribution of resources and cells across voxels. We applied S3MB on sequencing and imaging data obtained from a primary GBM patient. We performed whole genome sequencing (WGS) of four surgical specimens collected during the 1ˢᵗ and 2ⁿᵈ surgeries of the GBM and used HATCHET to quantify its clonal composition and how it changes between the two surgeries. HATCHET identified two aneuploid subpopulations of ploidy 1.98 and 2.29, respectively. The low-ploidy clone was dominant at the time of the first surgery and became even more dominant upon recurrence. MRI images were available before and after each surgery and registered to MNI space. The S3MB domain was initiated from 4mm³ voxels of the MNI space. T1 post and T2 flair scan acquired after the 1ˢᵗ surgery informed tumor cell densities per voxel. Magnetic Resonance Elastography scans and PET/CT scans informed stiffness and Glucose access per voxel. We performed a parameter search to recapitulate the GBM’s tumor cell density and ploidy composition before the 2ⁿᵈ surgery. Results suggest that the high-ploidy subpopulation had a higher Glucose-dependent proliferation rate (0.70 vs. 0.49), but a lower Glucose-dependent death rate (0.47 vs. 1.42). These differences resulted in spatial differences in the distribution of the two subpopulations. Our results contribute to a better understanding of how genomics and microenvironments interact to shape cell fate decisions and could help pave the way to therapeutic strategies that mimic prognostically favorable environments.

Keywords: tumor evolution, intra-tumor heterogeneity, whole-genome doubling, mathematical modeling

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Authors: Wonil Nam, Xiang Ren, Inyoung Kim, Masoud Agah, Wei Zhou

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Despite its ultrasensitive detection capability, surface-enhanced Raman spectroscopy (SERS) faces challenges as a quantitative biochemical analysis tool due to the significant dependence of local field intensity in hotspots on nanoscale geometric variations of plasmonic nanostructures. Therefore, despite enormous progress in plasmonic nanoengineering of high-performance SERS devices, it is still challenging to quantitatively correlate the measured SERS signals with the actual molecule concentrations at hotspots. A significant effort has been devoted to developing SERS calibration methods by introducing internal standards. It has been achieved by placing Raman tags at plasmonic hotspots. Raman tags undergo similar SERS enhancement at the same hotspots, and ratiometric SERS signals for analytes of interest can be generated with reduced dependence on geometrical variations. However, using Raman tags still faces challenges for real-world applications, including spatial competition between the analyte and tags in hotspots, spectral interference, laser-induced degradation/desorption due to plasmon-enhanced photochemical/photothermal effects. We show that electronic Raman scattering (ERS) signals from metallic nanostructures at hotspots can serve as the internal calibration standard to enable quantitative SERS analysis and improve biostatistical analysis. We perform SERS with Au-SiO₂ multilayered metal-insulator-metal nano laminated plasmonic nanostructures. Since the ERS signal is proportional to the volume density of electron-hole occupation in hotspots, the ERS signals exponentially increase when the wavenumber is approaching the zero value. By a long-pass filter, generally used in backscattered SERS configurations, to chop the ERS background continuum, we can observe an ERS pseudo-peak, IERS. Both ERS and SERS processes experience the |E|⁴ local enhancements during the excitation and inelastic scattering transitions. We calibrated IMRS of 10 μM Rhodamine 6G in solution by IERS. The results show that ERS calibration generates a new analytical value, ISERS/IERS, insensitive to variations from different hotspots and thus can quantitatively reflect the molecular concentration information. Given the calibration capability of ERS signals, we performed label-free SERS analysis of living biological systems using four different breast normal and cancer cell lines cultured on nano-laminated SERS devices. 2D Raman mapping over 100 μm × 100 μm, containing several cells, was conducted. The SERS spectra were subsequently analyzed by multivariate analysis using partial least square discriminant analysis. Remarkably, after ERS calibration, MCF-10A and MCF-7 cells are further separated while the two triple-negative breast cancer cells (MDA-MB-231 and HCC-1806) are more overlapped, in good agreement with the well-known cancer categorization regarding the degree of malignancy. To assess the strength of ERS calibration, we further carried out a drug efficacy study using MDA-MB-231 and different concentrations of anti-cancer drug paclitaxel (PTX). After ERS calibration, we can more clearly segregate the control/low-dosage groups (0 and 1.5 nM), the middle-dosage group (5 nM), and the group treated with half-maximal inhibitory concentration (IC50, 15 nM). Therefore, we envision that ERS calibrated SERS can find crucial opportunities in label-free molecular profiling of complicated biological systems.

Keywords: cancer cell drug efficacy, plasmonics, surface-enhanced Raman spectroscopy (SERS), SERS calibration

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Authors: Lucille Alonso, Florent Renard

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The characterizations of urban heat island (UHI) and their interactions with climate change and urban climates are the main research and public health issue, due to the increasing urbanization of the population. These solutions require a better knowledge of the UHI and micro-climate in urban areas, by combining measurements and modelling. This study is part of this topic by evaluating microclimatic conditions in dense urban areas in the Lyon Metropolitan Area (France) using a combination of data traditionally used such as topography, but also from LiDAR (Light Detection And Ranging) data, Landsat 8 satellite observation and Sentinel and ground measurements by bike. These bicycle-dependent weather data collections are used to build the database of the variable to be modelled, the air temperature, over Lyon’s hyper-center. This study aims to model the air temperature, measured during 6 mobile campaigns in Lyon in clear weather, using multiple linear regressions based on 33 explanatory variables. They are of various categories such as meteorological parameters from remote sensing, topographic variables, vegetation indices, the presence of water, humidity, bare soil, buildings, radiation, urban morphology or proximity and density to various land uses (water surfaces, vegetation, bare soil, etc.). The acquisition sources are multiple and come from the Landsat 8 and Sentinel satellites, LiDAR points, and cartographic products downloaded from an open data platform in Greater Lyon. Regarding the presence of low, medium, and high vegetation, the presence of buildings and ground, several buffers close to these factors were tested (5, 10, 20, 25, 50, 100, 200 and 500m). The buffers with the best linear correlations with air temperature for ground are 5m around the measurement points, for low and medium vegetation, and for building 50m and for high vegetation is 100m. The explanatory model of the dependent variable is obtained by multiple linear regression of the remaining explanatory variables (Pearson correlation matrix with a |r| < 0.7 and VIF with < 5) by integrating a stepwise sorting algorithm. Moreover, holdout cross-validation is performed, due to its ability to detect over-fitting of multiple regression, although multiple regression provides internal validation and randomization (80% training, 20% testing). Multiple linear regression explained, on average, 72% of the variance for the study days, with an average RMSE of only 0.20°C. The impact on the model of surface temperature in the estimation of air temperature is the most important variable. Other variables are recurrent such as distance to subway stations, distance to water areas, NDVI, digital elevation model, sky view factor, average vegetation density, or building density. Changing urban morphology influences the city's thermal patterns. The thermal atmosphere in dense urban areas can only be analysed on a microscale to be able to consider the local impact of trees, streets, and buildings. There is currently no network of fixed weather stations sufficiently deployed in central Lyon and most major urban areas. Therefore, it is necessary to use mobile measurements, followed by modelling to characterize the city's multiple thermal environments.

Keywords: air temperature, LIDAR, multiple linear regression, surface temperature, urban heat island

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Authors: May Bazzi, Shafik Tokmaj, Younes Saberi, Mats Geijer, Tony Jurkiewicz, Patrik Sund, Anna Bjällmark

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Mobile radiography, employing portable X-ray equipment, has become a routine procedure within hospital settings, with chest X-rays in intensive care units standing out as the most prevalent mobile X-ray examinations. This approach is not limited to hospitals alone, as it extends its benefits to imaging patients in various settings, particularly those too frail to be transported, such as elderly care residents in nursing homes. Moreover, the utility of mobile X-ray isn't confined solely to traditional healthcare recipients; it has proven to be a valuable resource for vulnerable populations, including the homeless, drug users, asylum seekers, and patients with multiple co-morbidities. Mobile X-rays reduce patient stress, minimize costly hospitalizations, and offer cost-effective imaging. While studies confirm its reliability, further research is needed, especially regarding image quality. Recent advancements in lightweight equipment with enhanced battery and detector technology provide the potential for nearly handheld radiography. The main aim of this study was to evaluate a new lightweight mobile X-ray system with two different detectors and compare the image quality with a modern stationary system. Methods: A total of 74 images of the chest (chest anterior-posterior (AP) views and chest lateral views) and pelvic/hip region (AP pelvis views, hip AP views, and hip cross-table lateral views) were acquired on a whole-body phantom (Kyotokagaku, Japan), utilizing varying image parameters. These images were obtained using a stationary system - 18 images (Mediel, Sweden), a mobile X-ray system with a second-generation detector - 28 images (FDR D-EVO II; Fujifilm, Japan) and a mobile X-ray system with a third-generation detector - 28 images (FDR D-EVO III; Fujifilm, Japan). Image quality was assessed by visual grading analysis (VGA), which is a method to measure image quality by assessing the visibility and accurate reproduction of anatomical structures within the images. A total of 33 image criteria were used in the analysis. A panel of two experienced radiologists, two experienced radiographers, and two final-term radiographer students evaluated the image quality on a 5-grade ordinal scale using the software Viewdex 3.0 (Viewer for Digital Evaluation of X-ray images, Sweden). Data were analyzed using visual grading characteristics analysis. The dose was measured by the dose-area product (DAP) reported by the respective systems. Results: The mobile X-ray equipment (both detectors) showed significantly better image quality than the stationary equipment for the pelvis, hip AP and hip cross-table lateral images with AUCVGA-values ranging from 0.64-0.92, while chest images showed mixed results. The number of images rated as having sufficient quality for diagnostic use was significantly higher for mobile X-ray generation 2 and 3 compared with the stationary X-ray system. The DAP values were higher for the stationary compared to the mobile system. Conclusions: The new lightweight radiographic equipment had an image quality at least as good as a fixed system at a lower radiation dose. Future studies should focus on clinical images and consider radiographers' viewpoints for a comprehensive assessment.

Keywords: mobile x-ray, visual grading analysis, radiographer, radiation dose

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Authors: Stephanie J. Sedberry, William J. Gerace, Ian D. Beatty, Michael J. Kane

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Increasing the number of US university students who attain degrees in STEM and enter the STEM workforce is a national priority. Demographic groups vary in their rates of participation in STEM, and the US produces just 10% of the world’s science and engineering degrees (2014 figures). To address these gaps, we have developed and tested a practical, 30-minute, single-session classroom-based intervention to improve students’ self-efficacy and academic performance in University STEM courses. Self-efficacy is a psychosocial construct that strongly correlates with academic success. Self-efficacy is a construct that is internal and relates to the social, emotional, and psychological aspects of student motivation and performance. A compelling body of research demonstrates that university students’ self-efficacy beliefs are strongly related to their selection of STEM as a major, aspirations for STEM-related careers, and persistence in science. The development of an intervention to increase students’ self-efficacy is motivated by research showing that short, social-psychological interventions in education can lead to large gains in student achievement. Our intervention addresses STEM self-efficacy via two strong, but previously separate, lines of research into attitudinal/affect variables that influence student success. The first is ‘attributional retraining,’ in which students learn to attribute their successes and failures to internal rather than external factors. The second is ‘mindset’ about fixed vs. growable intelligence, in which students learn that the brain remains plastic throughout life and that they can, with conscious effort and attention to thinking skills and strategies, become smarter. Extant interventions for both of these constructs have significantly increased academic performance in the classroom. We developed a 34-item questionnaire (Likert scale) to measure STEM Self-efficacy, Perceived Academic Control, and Growth Mindset in a University STEM context, and validated it with exploratory factor analysis, Rasch analysis, and multi-trait multi-method comparison to coded interviews. Four iterations of our 42-week research protocol were conducted across two academic years (2017-2018) at three different Universities in North Carolina, USA (UNC-G, NC A&T SU, and NCSU) with varied student demographics. We utilized a quasi-experimental prospective multiple-group time series research design with both experimental and control groups, and we are employing linear modeling to estimate the impact of the intervention on Self-Efficacy,wth-Mindset, Perceived Academic Control, and final course grades (performance measure). Preliminary results indicate statistically significant effects of treatment vs. control on Self-Efficacy, Growth-Mindset, Perceived Academic Control. Analyses are ongoing and final results pending. This intervention may have the potential to increase student success in the STEM classroom—and ownership of that success—to continue in a STEM career. Additionally, we have learned a great deal about the complex components and dynamics of self-efficacy, their link to performance, and the ways they can be impacted to improve students’ academic performance.

Keywords: academic performance, affect variables, growth mindset, intervention, perceived academic control, psycho-social variables, self-efficacy, STEM, university classrooms

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Authors: Rui Pedro de Sousa Guimarães Ferreira, Carlos Alberto Maia Domínguez

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Despite the ambitions to achieve climate neutrality by 2050, to fulfill the Paris Agreement's goals, the building and construction sector remains one of the most resource-intensive and greenhouse gas-emitting industries in the world, accounting for 40% of worldwide CO ₂ emissions. Over the past few decades, globalization and population growth have led to an exponential rise in demand in the housing market and, by extension, in the building industry. Considering this housing crisis, it is obvious that we will not stop building in the near future. However, the transition, which has already started, is challenging and complex because it calls for the worldwide participation of numerous organizations in altering how building systems, which have been a part of our everyday existence for over a century, are used. Wood is one of the alternatives that is most frequently used nowadays (under responsible forestry conditions) because of its physical qualities and, most importantly, because it produces fewer carbon emissions during manufacturing than steel or concrete. Furthermore, as wood retains its capacity to store CO ₂ after application and throughout the life of the building, working as a natural carbon filter, it helps to reduce greenhouse gas emissions. After a century-long focus on other materials, in the last few decades, technological advancements have made it possible to innovate systems centered around the use of wood. However, there are still some questions that require further exploration. It is necessary to standardize production and manufacturing processes based on prefabrication and modularization principles to achieve greater precision and optimization of the solutions, decreasing building time, prices, and waste from raw materials. In addition, this approach will make it possible to develop new architectural solutions to solve the rigidity and irreversibility of buildings, two of the most important issues facing housing today. Most current models are still created as inflexible, fixed, monofunctional structures that discourage any kind of regeneration, based on matrices that sustain the conventional family's traditional model and are founded on rigid, impenetrable compartmentalization. Adaptability and flexibility in housing are, and always have been, necessities and key components of architecture. People today need to constantly adapt to their surroundings and themselves because of the fast-paced, disposable, and quickly obsolescent nature of modern items. Migrations on a global scale, different kinds of co-housing, or even personal changes are some of the new questions that buildings have to answer. Designing with the reversibility of construction systems and materials in mind not only allows for the concept of "looping" in construction, with environmental advantages that enable the development of a circular economy in the sector but also unleashes multiple social benefits. In this sense, it is imperative to develop prefabricated and modular construction systems able to address the formalization of a reversible proposition that adjusts to the scale of time and its multiple reformulations, many of which are unpredictable. We must allow buildings to change, grow, or shrink over their lifetime, respecting their nature and, finally, the nature of the people living in them. It´s the ability to anticipate the unexpected, adapt to social factors, and take account of demographic shifts in society to stabilize communities, the foundation of real innovative sustainability.

Keywords: modular, timber, flexibility, housing

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Authors: Joshua Kaufman, Felix Tan, Morgan Monroe, Ayman Abouraddy

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Textiles and clothing have been a staple of human existence for millennia, yet the basic structure and functionality of textile fibers and yarns has remained unchanged. While color and appearance are essential characteristics of a textile, an advancement in the fabrication of yarns that allows for user-controlled dynamic changes to the color or appearance of a garment has been lacking. Touch-activated and photosensitive pigments have been used in textiles, but these technologies are passive and cannot be controlled by the user. The technology described here allows the owner to control both when and in what pattern the fabric color-change takes place. In addition, the manufacturing process is compatible with mass-producing the user-controlled, color-changing yarns. The yarn fabrication utilizes a fiber spinning system that can produce either monofilament or multifilament yarns. For products requiring a more robust fabric (backpacks, purses, upholstery, etc.), larger-diameter monofilament yarns with a coarser weave are suitable. Such yarns are produced using a thread-coater attachment to encapsulate a 38-40 AWG metal wire inside a polymer sheath impregnated with thermochromic pigment. Conversely, products such as shirts and pants requiring yarns that are more flexible and soft against the skin comprise multifilament yarns of much smaller-diameter individual fibers. Embedding a metal wire in a multifilament fiber spinning process has not been realized to date. This research has required collaboration with Hills, Inc., to design a liquid metal-injection system to be combined with fiber spinning. The new system injects molten tin into each of 19 filaments being spun simultaneously into a single yarn. The resulting yarn contains 19 filaments, each with a tin core surrounded by a polymer sheath impregnated with thermochromic pigment. The color change we demonstrate is distinct from garments containing LEDs that emit light in various colors. The pigment itself changes its optical absorption spectrum to appear a different color. The thermochromic color-change is induced by a temperature change in the inner metal wire within each filament when current is applied from a small battery pack. The temperature necessary to induce the color change is near body temperature and not noticeable by touch. The prototypes already developed either use a simple push button to activate the battery pack or are wirelessly activated via a smart-phone app over Wi-Fi. The app allows the user to choose from different activation patterns of stripes that appear in the fabric continuously. The power requirements are mitigated by a large hysteresis in the activation temperature of the pigment and the temperature at which there is full color return. This was made possible by a collaboration with Chameleon International to develop a new, customized pigment. This technology enables a never-before seen capability: user-controlled, dynamic color and pattern change in large-area woven and sewn textiles and fabrics with wide-ranging applications from clothing and accessories to furniture and fixed-installation housing and business décor. The ability to activate through Wi-Fi opens up possibilities for the textiles to be part of the ‘Internet of Things.’ Furthermore, this technology is scalable to mass-production levels for wide-scale market adoption.

Keywords: activation, appearance, color, manufacturing

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Authors: Krzysztof Skiba, Zbigniew Czyz, Ksenia Siadkowska, Piotr Borowiec

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The article presents selected concepts of technologies that use intelligent materials in aircraft in order to improve their performance. Most of the research focuses on solutions that improve the performance of fixed wing aircraft due to related to their previously dominant market share. Recently, the development of the rotorcraft has been intensive, so there are not only helicopters but also gyroplanes and unmanned aerial vehicles using rotors and vertical take-off and landing. There are many different technologies to change a shape of the aircraft or its elements. Piezoelectric, deformable actuator systems can be applied in the system of an active control of vibration dampening in the aircraft tail structure. Wires made of shape memory alloys (SMA) could be used instead of hydraulic cylinders in the rear part of the aircraft flap. The aircraft made of intelligent materials (piezoelectrics and SMA) is one of the NASA projects which provide the possibility of changing a wing shape coefficient by 200%, a wing surface by 50%, and wing deflections by 20 degrees. Active surfaces made of shape memory alloys could be used to control swirls in the flowing stream. An intelligent control system for helicopter blades is a method for the active adaptation of blades to flight conditions and the reduction of vibrations caused by the rotor. Shape memory alloys are capable of recovering their pre-programmed shapes. They are divided into three groups: nickel-titanium-based, copper-based, and ferromagnetic. Due to the strongest shape memory effect and the best vibration damping ability, a Ni-Ti alloy is the most commercially important. The subject of this work was to prepare a conceptual design of a rotor blade with SMA actuators. The scope of work included 3D design of the supporting rotor blade, 3D design of beams enabling to change the geometry by changing the angle of rotation and FEM (Finite Element Method) analysis. The FEM analysis was performed using NX 12 software in the Pre/Post module, which includes extended finite element modeling tools and visualizations of the obtained results. Calculations are presented for two versions of the blade girders. For FEM analysis, three types of materials were used for comparison purposes (ABS, aluminium alloy 7057, steel C45). The analysis of internal stresses and extreme displacements of crossbars edges was carried out. The internal stresses in all materials were close to the yield point in the solution of girder no. 1. For girder no. 2 solution, the value of stresses decreased by about 45%. As a result of the displacement analysis, it was found that the best solution was the ABS girder no. 1. The displacement of about 0.5 mm was obtained, which resulted in turning the crossbars (upper and lower) by an angle equal to 3.59 degrees. This is the largest deviation of all the tests. The smallest deviation was obtained for beam no. 2 made of steel. The displacement value of the second girder solution was approximately 30% lower than the first solution. Acknowledgement: This work has been financed by the Polish National Centre for Research and Development under the LIDER program, Grant Agreement No. LIDER/45/0177/L-9/17/NCBR/2018.

Keywords: aircraft, helicopters, shape memory alloy, SMA, smart material, unmanned aerial vehicle, UAV

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Authors: Tamal Roy, Anuradha Bhat

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Cognitive abilities aid fishes in foraging, avoiding predators & locating mates. Factors like predation pressure & habitat complexity govern learning & memory in fishes. This study aims to compare spatial learning & memory across four natural populations of zebrafish. Zebrafish, a small cyprinid inhabits a diverse range of freshwater habitats & this makes it amenable to studies investigating role of native environment in spatial cognitive abilities. Four populations were collected across India from waterbodies with contrasting ecological conditions. Habitat complexity of the water-bodies was evaluated as a combination of channel substrate diversity and diversity of vegetation. Experiments were conducted on populations under controlled laboratory conditions. A square shaped spatial testing arena (maze) was constructed for testing the performance of adult zebrafish. The square tank consisted of an inner square shaped layer with the edges connected to the diagonal ends of the tank-walls by connections thereby forming four separate chambers. Each of the four chambers had a main door in the centre. Each chamber had three sections separated by two windows. A removable coloured window-pane (red, yellow, green or blue) identified each main door. A food reward associated with an artificial plant was always placed inside the left-hand section of the red-door chamber. The position of food-reward and plant within the red-door chamber was fixed. A test fish would have to explore the maze by taking turns and locate the food inside the right-side section of the red-door chamber. Fishes were sorted from each population stock and kept individually in separate containers for identification. At a time, a test fish was released into the arena and allowed 20 minutes to explore in order to find the food-reward. In this way, individual fishes were trained through the maze to locate the food reward for eight consecutive days. The position of red door, with the plant and the reward, was shuffled every day. Following training, an intermission of four days was given during which the fishes were not subjected to trials. Post-intermission, the fishes were re-tested on the 13th day following the same protocol for their ability to remember the learnt task. Exploratory tendencies and latency of individuals to explore on 1st day of training, performance time across trials, and number of mistakes made each day were recorded. Additionally, mechanism used by individuals to solve the maze each day was analyzed across populations. Fishes could be expected to use algorithm (sequence of turns) or associative cues in locating the food reward. Individuals of populations did not differ significantly in latencies and tendencies to explore. No relationship was found between exploration and learning across populations. High habitat-complexity populations had higher rates of learning & stronger memory while low habitat-complexity populations had lower rates of learning and much reduced abilities to remember. High habitat-complexity populations used associative cues more than algorithm for learning and remembering while low habitat-complexity populations used both equally. The study, therefore, helped understand the role of natural ecology in explaining variations in spatial learning abilities across populations.

Keywords: algorithm, associative cue, habitat complexity, population, spatial learning

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Authors: Zhenmin Tao, Jasper De Smet, Koen Laurijssen, Jeroen Stuyts, Sonja Sioncke

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Today, the quality of knowledge management (KM)become one of the underpinning factors in the success of an organization, as it determines the effectiveness of capitalizing the organization’s knowledge. Overall, KMin an organization consists of five aspects: (knowledge) creation, validation, presentation, distribution, and application. Among others, KM in research institutes is considered as the cornerstone as their activities cover all five aspects. Furthermore, KM in a research institute facilitates the steering committee to envision the future roadmap, identify knowledge gaps, and make decisions on future research directions. Likewise, KMis even more challenging in industrial research institutes. From a technical perspective, technology advancement in the past decades calls for combinations of breadth and depth in expertise that poses challenges in talent acquisition and, therefore, knowledge creation. From a regulatory perspective, the strict intellectual property protection from industry collaborators and/or the contractual agreements made by possible funding authoritiesform extra barriers to knowledge validation, presentation, and distribution. From a management perspective, seamless KM activities are only guaranteed by inter-disciplinary talents that combine technical background knowledge, management skills, and leadership, let alone international vision. From a financial perspective, the long feedback period of new knowledge, together with the massive upfront investment costs and low reusability of the fixed assets, lead to low RORC (return on research capital) that jeopardize KM practice. In this study, we aim to address the challenges, practices, and opportunitiesof KM in Flanders Make – a leading European research institute specialized in the manufacturing industry. In particular, the analyses encompass an internal KM project which involves functionalities ranging from management to technical domain experts. This wide range of functionalities provides comprehensive empirical evidence on the challenges and practices w.r.t.the abovementioned KMaspects. Then, we ground our analysis onto the critical dimensions ofKM–individuals, socio‐organizational processes, and technology. The analyses have three steps: First, we lay the foundation and define the environment of this study by briefing the KM roles played by different functionalities in Flanders Make. Second, we zoom in to the CoreLab MotionS where the KM project is located. In this step, given the technical domains covered by MotionS products, the challenges in KM will be addressed w.r.t. the five KM aspects and three critical dimensions. Third, by detailing the objectives, practices, results, and limitations of the MotionSKMproject, we justify the practices and opportunities derived in the execution ofKMw.r.t. the challenges addressed in the second step. The results of this study are twofold: First, a KM framework that consolidates past knowledge is developed. A library based on this framework can, therefore1) overlook past research output, 2) accelerate ongoing research activities, and 3) envision future research projects. Second, the challenges inKM on both individual (actions) level and socio-organizational level (e.g., interactions between individuals)are identified. By doing so, suggestions and guidelines will be provided in KM in the context of industrial research institute. To this end, the results in this study are reflected towards the findings in existing literature.

Keywords: technical knowledge management framework, industrial research institutes, individual knowledge management, socio-organizational knowledge management.

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Authors: Shuo Li, Yannick Coffinier, Chann Lagadec, Fabrizio Cleri, Katsuhiko Nishiguchi, Akira Fujiwara, Soo Hyeon Kim, Nicolas Clément

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The need for single cell detection and analysis techniques has increased in the past decades because of the heterogeneity of individual living cells, which increases the complexity of the pathogenesis of malignant tumors. In the search for early cancer detection, high-precision medicine and therapy, the technologies most used today for sensitive detection of target analytes and monitoring the variation of these species are mainly including two types. One is based on the identification of molecular differences at the single-cell level, such as flow cytometry, fluorescence-activated cell sorting, next generation proteomics, lipidomic studies, another is based on capturing or detecting single tumor cells from fresh or fixed primary tumors and metastatic tissues, and rare circulating tumors cells (CTCs) from blood or bone marrow, for example, dielectrophoresis technique, microfluidic based microposts chip, electrochemical (EC) approach. Compared to other methods, EC sensors have the merits of easy operation, high sensitivity, and portability. However, despite various demonstrations of low limits of detection (LOD), including aptamer sensors, arrayed EC sensors for detecting single-cell have not been demonstrated. In this work, a new technique based on 20-nm-thick nanopillars array to support cells and keep them at ideal recognition distance for redox-labeled aptamers grafted on the surface. The key advantages of this technology are not only to suppress the false positive signal arising from the pressure exerted by all (including non-target) cells pushing on the aptamers by downward force but also to stabilize the aptamer at the ideal hairpin configuration thanks to a confinement effect. With the first implementation of this technique, a LOD of 13 cells (with5.4 μL of cell suspension) was estimated. In further, the nanosupported cell technology using redox-labeled aptasensors has been pushed forward and fully integrated into a single-cell electrochemical aptasensor array. To reach this goal, the LOD has been reduced by more than one order of magnitude by suppressing parasitic capacitive electrochemical signals by minimizing the sensor area and localizing the cells. Statistical analysis at the single-cell level is demonstrated for the recognition of cancer cells. The future of this technology is discussed, and the potential for scaling over millions of electrodes, thus pushing further integration at sub-cellular level, is highlighted. Despite several demonstrations of electrochemical devices with LOD of 1 cell/mL, the implementation of single-cell bioelectrochemical sensor arrays has remained elusive due to their challenging implementation at a large scale. Here, the introduced nanopillar array technology combined with redox-labeled aptamers targeting epithelial cell adhesion molecule (EpCAM) is perfectly suited for such implementation. Combining nanopillar arrays with microwells determined for single cell trapping directly on the sensor surface, single target cells are successfully detected and analyzed. This first implementation of a single-cell electrochemical aptasensor array based on Brownian-fluctuating redox species opens new opportunities for large-scale implementation and statistical analysis of early cancer diagnosis and cancer therapy in clinical settings.

Keywords: bioelectrochemistry, aptasensors, single-cell, nanopillars

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Authors: Marielle Leijten, Catherine Meulemans, Sven De Maeyer, Luuk Van Waes

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For the diagnosis of Alzheimer's disease (AD), a large variety of neuropsychological tests are available. In some of these tests, linguistic processing - both oral and written - is an important factor. Language disturbances might serve as a strong indicator for an underlying neurodegenerative disorder like AD. However, the current diagnostic instruments for language assessment mainly focus on product measures, such as text length or number of errors, ignoring the importance of the process that leads to written or spoken language production. In this study, it is our aim to describe and test differences between cognitive and impaired elderly on the basis of a selection of writing process variables (inter- and intrapersonal characteristics). These process variables are mainly related to pause times, because the number, length, and location of pauses have proven to be an important indicator of the cognitive complexity of a process. Method: Participants that were enrolled in our research were chosen on the basis of a number of basic criteria necessary to collect reliable writing process data. Furthermore, we opted to match the thirteen cognitively impaired patients (8 MCI and 5 AD) with thirteen cognitively healthy elderly. At the start of the experiment, participants were each given a number of tests, such as the Mini-Mental State Examination test (MMSE), the Geriatric Depression Scale (GDS), the forward and backward digit span and the Edinburgh Handedness Inventory (EHI). Also, a questionnaire was used to collect socio-demographic information (age, gender, eduction) of the subjects as well as more details on their level of computer literacy. The tests and questionnaire were followed by two typing tasks and two picture description tasks. For the typing tasks participants had to copy (type) characters, words and sentences from a screen, whereas the picture description tasks each consisted of an image they had to describe in a few sentences. Both the typing and the picture description tasks were logged with Inputlog, a keystroke logging tool that allows us to log and time stamp keystroke activity to reconstruct and describe text production processes. The main rationale behind keystroke logging is that writing fluency and flow reveal traces of the underlying cognitive processes. This explains the analytical focus on pause (length, number, distribution, location, etc.) and revision (number, type, operation, embeddedness, location, etc.) characteristics. As in speech, pause times are seen as indexical of cognitive effort. Results. Preliminary analysis already showed some promising results concerning pause times before, within and after words. For all variables, mixed effects models were used that included participants as a random effect and MMSE scores, GDS scores and word categories (such as determiners and nouns) as a fixed effect. For pause times before and after words cognitively impaired patients paused longer than healthy elderly. These variables did not show an interaction effect between the group participants (cognitively impaired or healthy elderly) belonged to and word categories. However, pause times within words did show an interaction effect, which indicates pause times within certain word categories differ significantly between patients and healthy elderly.

Keywords: Alzheimer's disease, keystroke logging, matching, writing process

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Authors: Avdhesh K. Sharma

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Key, in the development of energy-efficient micro-scale heat exchanger devices, is to select large heat transfer surface to volume ratio without much expanse on re-circulated pumps. The increased interest in short heat exchanger (SHE) is due to accessibility of advanced technologies for manufacturing of micro-tubes in range of 1 micron m - 1 mm. Such SHE using micro-tubes are highly effective for high flux heat transfer technologies. Nanofluids, are used to enhance the thermal conductivity of re-circulated coolant and thus enhances heat transfer rate further. Higher viscosity associated with nanofluid expands more pumping power. Thus, there is a trade-off between heat transfer rate and pressure drop with geometry of micro-tubes. Herein, a novel design of short counter flow heat exchanger (SCFHE) using non-circular micro-tubes flooded with CuO-water nanofluid is conceptualized by varying the ratio of surface area to cross-sectional area of micro-tubes. A framework for comparative analysis of SCFHE using micro-tubes non-circular shape flooded by CuO-water nanofluid is presented. In SCFHE concept, micro-tubes having various geometrical shapes (viz., triangular, rectangular and trapezoidal) has been arranged row-wise to facilitate two aspects: (1) allowing easy flow distribution for cold and hot stream, and (2) maximizing the thermal interactions with neighboring channels. Adequate distribution of rows for cold and hot flow streams enables above two aspects. For comparative analysis, a specific volume or cross-section area is assigned to each elemental cell (which includes flow area and area corresponds to half wall thickness). A specific volume or cross-section area is assumed to be constant for each elemental cell (which includes flow area and half wall thickness area) and variation in surface area is allowed by selecting different geometry of micro-tubes in SCFHE. Effective thermal conductivity model for CuO-water nanofluid has been adopted, while the viscosity values for water based nanofluids are obtained empirically. Correlations for Nusselt number (Nu) and Poiseuille number (Po) for micro-tubes have been derived or adopted. Entrance effect is accounted for. Thermal and hydrodynamic performances of SCFHE are defined in terms of effectiveness and pressure drop or pumping power, respectively. For defining the overall performance index of SCFHE, two links are employed. First one relates heat transfer between the fluid streams q and pumping power PP as (=qj/PPj); while another link relates effectiveness eff and pressure drop dP as (=effj/dPj). For analysis, the inlet temperatures of hot and cold streams are varied in usual range of 20dC-65dC. Fully turbulent regime is seldom encountered in micro-tubes and transition of flow regime occurs much early (i.e., ~Re=1000). Thus, Re is fixed at 900, however, the uncertainty in Re due to addition of nanoparticles in base fluid is quantified by averaging of Re. Moreover, for minimizing error, volumetric concentration is limited to range 0% to ≤4% only. Such framework may be helpful in utilizing maximum peripheral surface area of SCFHE without any serious severity on pumping power and towards developing advanced short heat exchangers.

Keywords: CuO-water nanofluid, non-circular micro-tubes, performance index, short counter flow heat exchanger

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Authors: Gus Calderon, Richard McCreight, Tammy Schwartz

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Forensic analysis of community wildfire destruction in California has shown that reducing or removing flammable vegetation in proximity to buildings and structures is one of the most important wildfire defenses available to homeowners. State laws specify the requirements for homeowners to create and maintain defensible space around all structures. Unfortunately, this decades-long effort had limited success due to noncompliance and minimal enforcement. As a result, vulnerable communities continue to experience escalating human and economic costs along the wildland-urban interface (WUI). Quantifying vegetative fuels at both the community and parcel scale requires detailed imaging from an aircraft with remote sensing technology to reduce uncertainty. FireWatch has been delivering high spatial resolution (5” ground sample distance) wildfire hazard maps annually to the community of Rancho Santa Fe, CA, since 2019. FireWatch uses a multispectral imaging system mounted onboard an aircraft to create georeferenced orthomosaics and spectral vegetation index maps. Using proprietary algorithms, the vegetation type, condition, and proximity to structures are determined for 1,851 properties in the community. Secondary data processing combines object-based classification of vegetative fuels, assisted by machine learning, to prioritize mitigation strategies within the community. The remote sensing data for the 10 sq. mi. community is divided into parcels and sent to all homeowners in the form of defensible space maps and reports. Follow-up aerial surveys are performed annually using repeat station imaging of fixed GPS locations to address changes in defensible space, vegetation fuel cover, and condition over time. These maps and reports have increased wildfire awareness and mitigation efforts from 40% to over 85% among homeowners in Rancho Santa Fe. To assist homeowners fighting increasing insurance premiums and non-renewals, FireWatch has partnered with Black Swan Analytics, LLC, to leverage the multispectral imagery and increase homeowners’ understanding of wildfire risk drivers. For this study, a subsample of 100 parcels was selected to gain a comprehensive understanding of wildfire risk and the elements which can be mitigated. Geospatial data from FireWatch’s defensible space maps was combined with Black Swan’s patented approach using 39 other risk characteristics into a 4score Report. The 4score Report helps property owners understand risk sources and potential mitigation opportunities by assessing four categories of risk: Fuel sources, ignition sources, susceptibility to loss, and hazards to fire protection efforts (FISH). This study has shown that susceptibility to loss is the category residents and property owners must focus their efforts. The 4score Report also provides a tool to measure the impact of homeowner actions on risk levels over time. Resiliency is the only solution to breaking the cycle of community wildfire destruction and it starts with high-quality data and education.

Keywords: defensible space, geospatial data, multispectral imaging, Rancho Santa Fe, susceptibility to loss, wildfire risk.

Procedia PDF Downloads 76

Authors: Reyna Singh, David Lokhat, Milan Carsky

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The world crude oil demand is projected to rise to 108.5 million bbl/d by the year 2035. With reserves estimated at 869 billion tonnes worldwide, coal is an abundant resource. This work was aimed at producing a high value hydrocarbon liquid product from the Direct Coal Liquefaction (DCL) process at, comparatively, mild operating conditions. Via hydrogenation, the temperature-staged approach was investigated. In a two reactor lab-scale pilot plant facility, the objectives included maximising thermal dissolution of the coal in the presence of a hydrogen donor solvent in the first stage, subsequently promoting hydrogen saturation and hydrodesulphurization (HDS) performance in the second. The feed slurry consisted of high grade, pulverized bituminous coal on a moisture-free basis with a size fraction of < 100μm; and Tetralin mixed in 2:1 and 3:1 solvent/coal ratios. Magnetite (Fe3O4) at 0.25wt% of the dry coal feed was added for the catalysed runs. For both stages, hydrogen gas was used to maintain a system pressure of 100barg. In the first stage, temperatures of 250℃ and 300℃, reaction times of 30 and 60 minutes were investigated in an agitated batch reactor. The first stage liquid product was pumped into the second stage vertical reactor, which was designed to counter-currently contact the hydrogen rich gas stream and incoming liquid flow in the fixed catalyst bed. Two commercial hydrotreating catalysts; Cobalt-Molybdenum (CoMo) and Nickel-Molybdenum (NiMo); were compared in terms of their conversion, selectivity and HDS performance at temperatures 50℃ higher than the respective first stage tests. The catalysts were activated at 300°C with a hydrogen flowrate of approximately 10 ml/min prior to the testing. A gas-liquid separator at the outlet of the reactor ensured that the gas was exhausted to the online VARIOplus gas analyser. The liquid was collected and sampled for analysis using Gas Chromatography-Mass Spectrometry (GC-MS). Internal standard quantification methods for the sulphur content, the BTX (benzene, toluene, and xylene) and alkene quality; alkanes and polycyclic aromatic hydrocarbon (PAH) compounds in the liquid products were guided by ASTM standards of practice for hydrocarbon analysis. In the first stage, using a 2:1 solvent/coal ratio, an increased coal to liquid conversion was favoured by a lower operating temperature of 250℃, 60 minutes and a system catalysed by magnetite. Tetralin functioned effectively as the hydrogen donor solvent. A 3:1 ratio favoured increased concentrations of the long chain alkanes undecane and dodecane, unsaturated alkenes octene and nonene and PAH compounds such as indene. The second stage product distribution showed an increase in the BTX quality of the liquid product, branched chain alkanes and a reduction in the sulphur concentration. As an HDS performer and selectivity to the production of long and branched chain alkanes, NiMo performed better than CoMo. CoMo is selective to a higher concentration of cyclohexane. For 16 days on stream each, NiMo had a higher activity than CoMo. The potential to cover the demand for low–sulphur, crude diesel and solvents from the production of high value hydrocarbon liquid in the said process, is thus demonstrated.

Keywords: catalyst, coal, liquefaction, temperature-staged

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Authors: Festus Okotie

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Nigeria is the giant of Africa with great and diverse transport potentials yet to be fully tapped into and explored.it is the most populated nation in Africa with nearly 200 million people, the sixth largest oil producer overall and largest oil producer in Africa with proven oil and gas reserves of 37 billion barrels and 192 trillion cubic feet, over 300 square kilometers of arable land and significant deposits of largely untapped minerals. A world bank indicator which measures trading across border ranked Nigeria at 183 out of 185 countries in 2017 and although different governments in the past made efforts through different interventions such as 2007 ports reforms led by Ngozi Okonjo-Iweala, a former minister of Finance and world bank managing director also attempted to resolve some of the challenges such as infrastructure shortcomings, policy and regulatory inconsistencies, overlapping functions and duplicated roles among the different MDA’S. It is one of the fundamental structures smart nations and cities are using to improve the living conditions of its citizens and achieving sustainability. Examples of some of its benefits includes tracking high pedestrian areas, traffic patterns, railway stations, planning and scheduling bus times, it also enhances interoperability, creates alerts of transport situation and has swift capacity to share information among the different platforms and transport modes. It also offers a comprehensive approach to risk management, putting emergency procedures and response capabilities in place, identifying dangers, including vandalism or violence, fare evasion, and medical emergencies. The Nigerian transport system is urgently in need of modern infrastructures such as ITS. Smart city transport technology helps cities to function productively, while improving services for businesses and lives of is citizens. This technology has the ability to improve travel across traditional modes of transport, such as cars and buses, with immediate benefits for city dwellers and also helps in managing transport systems such as dangerous weather conditions, heavy traffic, and unsafe speeds which can result in accidents and loss of lives. Intelligent transportation systems help in traffic control such as permitting traffic lights to react to changing traffic patterns, instead of working on a fixed schedule in traffic. Intelligent transportation systems is very important in Nigeria’s transportation sector and so would require trained personnel to drive its efficiency to greater height because the purpose of introducing it is to add value and at the same time reduce motor vehicle miles and traffic congestion which is a major challenge around Tin can island and Apapa Port, a major transportation hub in Nigeria. The need for the federal government, state governments, houses of assembly to organise a national transportation workshop to begin the process of addressing the challenges in our nation’s transport sector is highly expedient and so bills that will facilitate the implementation of policies to promote intelligent transportation systems needs to be sponsored because of its potentials to create thousands of jobs for our citizens, provide farmers with better access to cities and a better living condition for Nigerians.

Keywords: intelligent, transport, system, Nigeria

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Authors: Jose Neri, Fabrice Canto, Alastair Magnaldo, Laurent Guillerme, Vincent Dugas

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A miniaturized and automated approach for the volumetric titration of free nitric acid in U(VI) solutions is presented. Free acidity measurement refers to the acidity quantification in solutions containing hydrolysable heavy metal ions such as U(VI), U(IV) or Pu(IV) without taking into account the acidity contribution from the hydrolysis of such metal ions. It is, in fact, an operation having an essential role for the control of the nuclear fuel recycling process. The main objective behind the technical optimization of the actual ‘beaker’ method was to reduce the amount of radioactive substance to be handled by the laboratory personnel, to ease the instrumentation adjustability within a glove-box environment and to allow a high-throughput analysis for conducting more cost-effective operations. The measurement technique is based on the concept of the Taylor-Aris dispersion in order to create inside of a 200 μm x 5cm circular cylindrical micro-channel a linear concentration gradient in less than a second. The proposed analytical methodology relies on the actinide complexation using pH 5.6 sodium oxalate solution and subsequent alkalimetric titration of nitric acid with sodium hydroxide. The titration process is followed with a CCD camera for fluorescence detection; the neutralization boundary can be visualized in a detection range of 500nm- 600nm thanks to the addition of a pH sensitive fluorophore. The operating principle of the developed device allows the active generation of linear concentration gradients using a single cylindrical micro channel. This feature simplifies the fabrication and ease of use of the micro device, as it does not need a complex micro channel network or passive mixers to generate the chemical gradient. Moreover, since the linear gradient is determined by the liquid reagents input pressure, its generation can be fully achieved in faster intervals than one second, being a more timely-efficient gradient generation process compared to other source-sink passive diffusion devices. The resulting linear gradient generator device was therefore adapted to perform for the first time, a volumetric titration on a chip where the amount of reagents used is fixed to the total volume of the micro channel, avoiding an important waste generation like in other flow-based titration techniques. The associated analytical method is automated and its linearity has been proven for the free acidity determination of U(VI) samples containing up to 0.5M of actinide ion and nitric acid in a concentration range of 0.5M to 3M. In addition to automation, the developed analytical methodology and technique greatly improves the standard off-line oxalate complexation and alkalimetric titration method by reducing a thousand fold the required sample volume, forty times the nuclear waste per analysis as well as the analysis time by eight-fold. The developed device represents, therefore, a great step towards an easy-to-handle nuclear-related application, which in the short term could be used to improve laboratory safety as much as to reduce the environmental impact of the radioanalytical chain.

Keywords: free acidity, lab-on-a-chip, linear concentration gradient, Taylor-Aris dispersion, volumetric titration

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Authors: Shuai Yuan, Minxia Shi, Xu Zhang, Jianzhi Yang, Kangqi Tian, Yuzheng Ma

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The precise measurement of muscle activities is essential for understanding the function of various body movements. This work aims to develop a muscle magnetic field signal detection system based on mathematical analysis. Medical research has underscored that early detection of muscle atrophy, coupled with lifestyle adjustments such as dietary control and increased exercise, can significantly enhance muscle-related diseases. Currently, surface electromyography (sEMG) is widely employed in research as an early predictor of muscle atrophy. Nonetheless, the primary limitation of using sEMG to forecast muscle strength is its inability to directly measure the signals generated by muscles. Challenges arise from potential skin-electrode contact issues due to perspiration, leading to inaccurate signals or even signal loss. Additionally, resistance and phase are significantly impacted by adipose layers. The recent emergence of optically pumped magnetometers introduces a fresh avenue for bio-magnetic field measurement techniques. These magnetometers possess high sensitivity and obviate the need for a cryogenic environment unlike superconducting quantum interference devices (SQUIDs). They detect muscle magnetic field signals in the range of tens to thousands of femtoteslas (fT). The utilization of magnetometers for capturing muscle magnetic field signals remains unaffected by issues of perspiration and adipose layers. Since their introduction, optically pumped atomic magnetometers have found extensive application in exploring the magnetic fields of organs such as cardiac and brain magnetism. The optimal operation of these magnetometers necessitates an environment with an ultra-weak magnetic field. To achieve such an environment, researchers usually utilize a combination of active magnetic compensation technology with passive magnetic shielding technology. Passive magnetic shielding technology uses a magnetic shielding device built with high permeability materials to attenuate the external magnetic field to a few nT. Compared with more layers, the coils that can generate a reverse magnetic field to precisely compensate for the residual magnetic fields are cheaper and more flexible. To attain even lower magnetic fields, compensation coils designed by Biot-Savart law are involved to generate a counteractive magnetic field to eliminate residual magnetic fields. By solving the magnetic field expression of discrete points in the target region, the parameters that determine the current density distribution on the plane can be obtained through the conventional target field method. The current density is obtained from the partial derivative of the stream function, which can be represented by the combination of trigonometric functions. Optimization algorithms in mathematics are introduced into coil design to obtain the optimal current density distribution. A one-dimensional linear regression analysis was performed on the collected data, obtaining a coefficient of determination R2 of 0.9349 with a p-value of 0. This statistical result indicates a stable relationship between the peak-to-peak value (PPV) of the muscle magnetic field signal and the magnitude of grip strength. This system is expected to be a widely used tool for healthcare professionals to gain deeper insights into the muscle health of their patients.

Keywords: muscle magnetic signal, magnetic shielding, compensation coils, trigonometric functions.

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Authors: Daniele Lerede, Gianvito Colucci, Matteo Nicoli, Laura Savoldi

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The European Green Deal is the first internationally agreed set of measures to contrast climate change and environmental degradation. Besides the main target of reducing emissions by at least 55% by 2030, it sets the target of accompanying European countries through an energy transition to make the European Union into a modern, resource-efficient, and competitive net-zero emissions economy by 2050, decoupling growth from the use of resources and ensuring a fair adaptation of all social categories to the transformation process. While the general purpose to allow the realization of the purposes of the Green Deal already dates back to 2019, strategies and policies keep being developed coping with recent circumstances and achievements. However, general long-term measures like the Circular Economy Action Plan, the proposals to shift from fossil natural gas to renewable and low-carbon gases, in particular biomethane and hydrogen, and to end the sale of gasoline and diesel cars by 2035, will all have significant effects on energy supply and demand evolution across the next decades. The interactions between energy supply and demand over long-term time frames are usually assessed via energy system models to derive useful insights for policymaking and to address technological choices and research and development. TEMOA-Europe is a newly developed energy system optimization model instance based on the minimization of the total cost of the system under analysis, adopting a technologically integrated, detailed, and explicit formulation and considering the evolution of the system in partial equilibrium in competitive markets with perfect foresight. TEMOA-Europe is developed on the TEMOA platform, an open-source modeling framework totally implemented in Python, therefore ensuring third-party verification even on large and complex models. TEMOA-Europe is based on a single-region representation of the European Union and EFTA countries on a time scale between 2005 and 2100, relying on a set of assumptions for socio-economic developments based on projections by the International Energy Outlook and a large technological dataset including 7 sectors: the upstream and power sectors for the production of all energy commodities and the end-use sectors, including industry, transport, residential, commercial and agriculture. TEMOA-Europe also includes an updated hydrogen module considering its production, storage, transportation, and utilization. Besides, it can rely on a wide set of innovative technologies, ranging from nuclear fusion and electricity plants equipped with CCS in the power sector to electrolysis-based steel production processes and steel in the industrial sector – with a techno-economic characterization based on public literature – to produce insightful energy scenarios and especially to cope with the very long analyzed time scale. The aim of this work is to examine in detail the scheme of measures and policies for the realization of the purposes of the Green Deal and to transform them into a set of constraints and new socio-economic development pathways. Based on them, TEMOA-Europe will be used to produce and comparatively analyze scenarios to assess the consequences of Green Deal-related measures on the future evolution of the energy mix over the whole energy system in an economic optimization environment.

Keywords: European Green Deal, energy system optimization modeling, scenario analysis, TEMOA-Europe

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Authors: Gousilin Leandra Rocha Da Silva, Stéfani T. A. Dantas, Bruna F. Rossi, Erika R. Bonsaglia, Ivana G. Castilho, Terue Sadatsune, Ary Fernandes Júnior, Vera l. M. Rall

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Kidney failure causes decreased diuresis and accumulation of nitrogenous substances in the body. To increase patient survival, hemodialysis is used as a partial substitute for renal function. However, contamination of the water used in this treatment, causing bacteremia in patients, is a worldwide concern. The Burkholderia cepacia complex (Bcc), a group of bacteria with more than 20 species, is frequently isolated from hemodialysis water samples and comprises opportunistic bacteria, affecting immunosuppressed patients, due to its wide variety of virulence factors, in addition to innate resistance to several antimicrobial agents, contributing to the permanence in the hospital environment and to the pathogenesis in the host. The objective of the present work was to characterize molecularly and phenotypically Bcc isolates collected from the water and dialysate of the Hemodialysis Unit and from the blood of patients at a Public Hospital in Botucatu, São Paulo, Brazil, between 2019 and 2021. We used 33 Bcc isolates, previously obtained from blood cultures from patients with bacteremia undergoing hemodialysis treatment (2019-2021) and 24 isolates obtained from water and dialysate samples in a Hemodialysis Unit (same period). The recA gene was sequenced to identify the specific species among the Bcc group. All isolates were tested for the presence of some genes that encode virulence factors such as cblA, esmR, zmpA and zmpB. Considering the epidemiology of the outbreak, the Bcc isolates were molecularly characterized by Multi Locus Sequence Type (MLST) and by pulsed-field gel electrophoresis (PFGE). The verification and quantification of biofilm in a polystyrene microplate were performed by submitting the isolates to different incubation temperatures (20°C, average water temperature and 35°C, optimal temperature for group growth). The antibiogram was performed with disc diffusion tests on agar, using discs impregnated with cefepime (30µg), ceftazidime (30µg), ciprofloxacin (5µg), gentamicin (10µg), imipenem (10µg), amikacin 30µg), sulfametazol/trimethoprim (23.75/1.25µg) and ampicillin/sulbactam (10/10µg). The presence of ZmpB was identified in all isolates, while ZmpA was observed in 96.5% of the isolates, while none of them presented the cblA and esmR genes. The antibiogram of the 33 human isolates indicated that all were resistant to gentamicin, colistin, ampicillin/sulbactam and imipenem. 16 (48.5%) isolates were resistant to amikacin and lower rates of resistance were observed for meropenem, ceftazidime, cefepime, ciprofloxacin and piperacycline/tazobactam (6.1%). All isolates were sensitive to sulfametazol/trimethoprim, levofloxacin and tigecycline. As for the water isolates, resistance was observed only to gentamicin (34.8%) and imipenem (17.4%). According to PFGE results, all isolates obtained from humans and water belonged to the same pulsotype (1), which was identified by recA sequencing as B. cepacia¸, belonging to sequence type ST-767. By observing a single pulse type over three years, one can observe the persistence of this isolate in the pipeline, contaminating patients undergoing hemodialysis, despite the routine disinfection of water with peracetic acid. This persistence is probably due to the production of biofilm, which protects bacteria from disinfectants and, making this scenario more critical, several isolates proved to be multidrug-resistant (resistance to at least three groups of antimicrobials), turning the patient care even more difficult.

Keywords: hemodialysis, burkholderia cepacia, PFGE, MLST, multi drug resistance

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Authors: Clorinda Hogan, Shaun Abbott, Mark Halaki, Marcela Torres Catiglioni, Goshi Yamauchi, Lachlan Mitchell, James Salter, Michael Romann, Stephen Cobley

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Introduction: Common annual age-group competition structures unintentionally introduce participation inequalities, performance (dis)advantages and selection biases due to the effect of maturational variation between youth swimmers. On this basis, there are implications for improving performance evaluation strategies. Therefore the aim was to: (1) To determine maturity timing distributions in female youth swimming; (2) quantify the relationship between maturation status and 100-m FC performance; (3) apply Maturational-based Corrective Adjustment Procedures (Mat-CAPs) for removal of maturational status performance influences. Methods: (1) Cross-sectional analysis of 663 female (10-15 years) swimmers who underwent assessment of anthropometrics (mass, height and sitting height) and estimations of maturity timing and offset. (2) 100-m front-crawl performance (seconds) was assessed at Australian regional, state, and national-level competitions between 2016-2020. To determine the relationship between maturation status and 100-m front-crawl performance, MO was plotted against 100-m FC performance time. The expected maturity status - performance relationship for females aged 10-15 years of age was obtained through a quadratic function (y = ax2 + bx + c) from unstandardized coefficients. The regression equation was subsequently used for Mat-CAPs. (3) Participants aged 10-13 years were categorised into maturity-offset categories. Maturity offset distributions for Raw (‘All’, ‘Top 50%’ & ‘Top 25%’) and Correctively Adjusted swim times were examined. Chi-square, Cramer’s V and ORs determined the occurrence of maturation biases for each age group and selection level. Results—: (1) Maturity timing distributions illustrated overrepresentation of ‘normative’ maturing swimmers (11.82 ± 0.40 years), with a descriptive shift toward the early maturing relative to the normative population. (2) A curvilinear relationship between maturity-offset and swim performance was identified (R2 = 0.53, P < 0.001) and subsequently utilised for Mat-CAPs. (3) Raw maturity offset categories identified partial maturation status skewing towards biologically older swimmers at 10/11 and 12 years, with effect magnitudes increasing in the ‘Top 50%’ and ‘25%’ of performance times. Following Mat-CAPs application, maturity offset biases were removed in similar age groups and selection levels. When adjusting performance times for maturity offset, Mat-CAPs was successful in mitigating against maturational biases until approximately 1-year post Peak Height Velocity. The overrepresentation of ‘normative’ maturing female swimmers contrasted with the substantial overrepresentation of ‘early’ maturing male swimmers found previously in 100-m front-crawl. These findings suggest early maturational timing is not advantageous in females, but findings associated with Aim 2, highlight how advanced maturational status remained beneficial to performance. Observed differences between female and male maturational biases may relate to the differential impact of physiological development during pubertal years. Females experience greater increases of fat mass and potentially differing changes in body shape which can negatively affect swim performance. Conclusions: Transient maturation status-based participation and performance advantages were apparent within a large sample of Australian female youth 100-m FC swimmers. By removing maturity status performance biases within female youth swimming, Mat-CAPs could help improve participation experiences and the accuracy of identifying genuinely skilled female youth swimmers.

Keywords: athlete development, long-term sport participation, performance evaluation, talent identification, youth competition

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Authors: Ariunaa Sampilvanjil, Javzandulam Enkhbat, Chimegsaikhan Sodnompil, Oyungerel Sodjamts, Khulan Batbayasgalan, Altantsetseg Battulga, Tumenbayar Bataa

Abstract:

Introduction: Prenatal stress has been linked to heightened allergy sensitivity in offspring. However, there is a notable absence of research on the mesovarium structure of offspring born from mothers subjected to cold stress during pregnancy. Understanding the impact of maternal cold stress on the mesovarium structure could provide valuable insights into reproductive health outcomes in offspring. Objective: This study aims to investigate structural changes in the mesovarium of offspring born from cold-stress affected rats. Material and Methods: 20 female Westar rats weighing around 200g were chosen and evenly divided into four containers; then 2-3 male rats were introduced to each container. The Papanicolaou method was used to estimate the spermatozoa and estrus period from vaginal swabs taken from female rats at 8:00 a.m. Female rats examined with presence of spermatozoa during the estrous phase of the estrous cycle are defined as pregnant. Pregnant rats are divided into experimental and control groups. The experimental group was stressed using the model of severe and chronic cold stress for 30 days. They were exposed to a cold stress for 3 hours each morning between 8:00 to 11:00 o’clock at a temperature of minus 15 degrees Celsius. The control group was kept under normal laboratory conditions. Newborn female rats from both experimental and control groups were selected. At 2 months of age, rats were euthanized by decapitation, and their mesovaria were collected. Tissues were fixed in 4% formalin, embedded in paraffin, and sectioned into 5μm thick slices. The sections were stained with H&E and digitized by digital microscope. Area of brown fat and inflammatory infiltrations were quantified using Image J software. The blood cortisol levels were measured using ELISA. Data are expressed as the mean ± standard error of the mean (SEM). The Mann-Whitney test was used to compare two groups. All analyses were performed using Prism (GraphPad Software). A p-value of < 0.05 was considered statistically significant. Result: Offspring born from stressed mothers exhibited significant physiological differences compared to the control group. Specifically: The body weight of offspring from stressed mothers was significantly lower than the control group (p=0.0002). Conversely, the cortisol level in offspring from stressed mothers was significantly higher (p=0.0446). Offspring born from stressed mothers showed a statistically significant increase in brown fat area compared to the control group (p=0.01). Additionally, offspring from stressed mothers had a significantly higher number of inflammatory infiltrates in their mesovarium compared to the control group (p<0.047). These results indicate the profound impact of maternal stress on offspring physiology, affecting body weight, stress hormone levels, metabolic characteristics, and inflammatory responses. Conclusion: Exposure to cold stress during pregnancy has significant repercussions on offspring physiology. Our findings demonstrate that cold stress exposure leads to increased blood cortisol levels, brown fat accumulation, and inflammatory cell infiltration in offspring. These results underscore the profound impact of maternal stress on offspring health and highlight the importance of mitigating environmental stressors during pregnancy to promote optimal offspring outcomes.

Keywords: brown fat, cold stress during pregnancy, inflammation, mesovarium

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Authors: Wenyu Guo, Malachy O’Rourke, Mark Bowkett, Michael Gilchrist

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Many devices for real-time monitoring of surface water have been developed in the past few years to provide early warning of pollutions and so to decrease the risk of environmental pollution efficiently. One of the most common methodologies used in the detection system is a colorimetric process, in which a container with fixed volume is filled with target ions and reagents to combine a colorimetric dye. The colorimetric ions can sensitively absorb a specific-wavelength radiation beam, and its absorbance rate is proportional to the concentration of the fully developed product, indicating the concentration of target nutrients in the pre-mixed water samples. In order to achieve precise and rapid detection effect, channels with dimensions in the order of micrometers, i.e., microfluidic systems have been developed and introduced into these diagnostics studies. Microfluidics technology largely reduces the surface to volume ratios and decrease the samples/reagents consumption significantly. However, species transport in such miniaturized channels is limited by the low Reynolds numbers in the regimes. Thus, the flow is extremely laminar state, and diffusion is the dominant mass transport process all over the regimes of the microfluidic channels. The objective of this present work has been to analyse the mixing effect and chemistry kinetics in a stop-flow microfluidic device measuring Nitride concentrations in fresh water samples. In order to improve the temporal resolution of the Nitride microfluidic sensor, we have used computational fluid dynamics to investigate the influence that the effectiveness of the mixing process between the sample and reagent within a microfluidic device exerts on the time to completion of the resulting chemical reaction. This computational approach has been complemented by physical experiments. The kinetics of the Griess reaction involving the conversion of sulphanilic acid to a diazonium salt by reaction with nitrite in acidic solution is set in the Laminar Finite-rate chemical reaction in the model. Initially, a methodology was developed to assess the degree of mixing of the sample and reagent within the device. This enabled different designs of the mixing channel to be compared, such as straight, square wave and serpentine geometries. Thereafter, the time to completion of the Griess reaction within a straight mixing channel device was modeled and the reaction time validated with experimental data. Further simulations have been done to compare the reaction time to effective mixing within straight, square wave and serpentine geometries. Results show that square wave channels can significantly improve the mixing effect and provides a low standard deviations of the concentrations of nitride and reagent, while for straight channel microfluidic patterns the corresponding values are 2-3 orders of magnitude greater, and consequently are less efficiently mixed. This has allowed us to design novel channel patterns of micro-mixers with more effective mixing that can be used to detect and monitor levels of nutrients present in water samples, in particular, Nitride. Future generations of water quality monitoring and diagnostic devices will easily exploit this technology.

Keywords: nitride detection, computational fluid dynamics, chemical kinetics, mixing effect

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Authors: Salvatore Luongo, Carlo Luongo

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This paper discusses the implementation solutions to reduce the computational load for the Traffic Situational Awareness with Alerts (TSAA) application, based on Automatic Dependent Surveillance-Broadcast (ADS-B) technology. In 2008, there were 23 total mid-air collisions involving general aviation fixed-wing aircraft, 6 of which were fatal leading to 21 fatalities. These collisions occurred during visual meteorological conditions, indicating the limitations of the see-and-avoid concept for mid-air collision avoidance as defined in the Federal Aviation Administration’s (FAA). The commercial aviation aircraft are already equipped with collision avoidance system called TCAS, which is based on classic transponder technology. This system dramatically reduced the number of mid-air collisions involving air transport aircraft. In general aviation, the same reduction in mid-air collisions has not occurred, so this reduction is the main objective of the TSAA application. The major difference between the original conflict detection application and the TSAA application is that the conflict detection is focused on preventing loss of separation in en-route environments. Instead TSAA is devoted to reducing the probability of mid-air collision in all phases of flight. The TSAA application increases the flight crew traffic situation awareness providing alerts of traffic that are detected in conflict with ownship in support of the see-and-avoid responsibility. The relevant effort has been spent in the design process and the code generation in order to maximize the efficiency and performances in terms of computational load and memory consumption reduction. The TSAA architecture is divided into two high-level systems: the “Threats database” and the “Conflict detector”. The first one receives the traffic data from ADS-B device and provides the memorization of the target’s data history. Conflict detector module estimates ownship and targets trajectories in order to perform the detection of possible future loss of separation between ownship and each target. Finally, the alerts are verified by additional conflict verification logic, in order to prevent possible undesirable behaviors of the alert flag. In order to reduce the computational load, a pre-check evaluation module is used. This pre-check is only a computational optimization, so the performances of the conflict detector system are not modified in terms of number of alerts detected. The pre-check module uses analytical trajectories propagation for both target and ownship. This allows major accuracy and avoids the step-by-step propagation, which requests major computational load. Furthermore, the pre-check permits to exclude the target that is certainly not a threat, using an analytical and efficient geometrical approach, in order to decrease the computational load for the following modules. This software improvement is not suggested by FAA documents, and so it is the main innovation of this work. The efficiency and efficacy of this enhancement are verified using fast-time and real-time simulations and by the execution on a real device in several FAA scenarios. The final implementation also permits the FAA software certification in compliance with DO-178B standard. The computational load reduction allows the installation of TSAA application also on devices with multiple applications and/or low capacity in terms of available memory and computational capabilities

Keywords: traffic situation awareness, general aviation, aircraft conflict detection, computational load reduction, implementation solutions, software certification

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Authors: Ririh Rahma Ratinghayu, Jayu Pramudya, Nur Aini Masruroh, Shi-Woei Lin

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This research studies pricing strategy in cooperative setting of hotel duopoly selling perishable product under fixed capacity constraint by using the perspective of managers. In hotel revenue management, competitor’s average room rate and occupancy rate should be taken into manager’s consideration in determining pricing strategy to generate optimum revenue. This information is not provided by business intelligence or available in competitor’s website. Thus, Information Sharing (IS) among players might result in improved performance of pricing strategy. IS is widely adopted in the logistics industry, but IS within hospitality industry has not been well-studied. This research put IS as one of cooperative game schemes, besides Mutual Price Setting (MPS) scheme. In off-peak season, hotel manager arranges pricing strategy to offer promotion package and various kinds of discounts up to 60% of full-price to attract customers. Competitor selling homogenous product will react the same, then triggers a price war. Price war which generates lower revenue may be avoided by creating collaboration in pricing strategy to optimize payoff for both players. In MPS cooperative game, players collaborate to set a room rate applied for both players. Cooperative game may avoid unfavorable players’ payoff caused by price war. Researches on horizontal cooperative game in logistics show better performance and payoff for the players, however, horizontal cooperative game in hotel revenue management has not been demonstrated. This paper aims to develop hotel revenue management models under duopoly cooperative schemes (IS & MPS), which are compared to models under non-cooperative scheme too. Each scheme has five models, Capacity Allocation Model; Demand Model; Revenue Model; Optimal Price Model; and Equilibrium Price Model. Capacity Allocation Model and Demand Model employs self-hotel and competitor’s full and discount price as predictors under non-linear relation. Optimal price is obtained by assuming revenue maximization motive. Equilibrium price is observed by interacting self-hotel’s and competitor’s optimal price under reaction equation. Equilibrium is analyzed using game theory approach. The sequence applies for three schemes. MPS Scheme differently aims to optimize total players’ payoff. The case study in which theoretical models are applied observes two hotels offering homogenous product in Indonesia during a year. The Capacity Allocation, Demand, and Revenue Models are built using multiple regression and statistically tested for validation. Case study data confirms that price behaves within demand model in a non-linear manner. IS Models can represent the actual demand and revenue data better than Non-IS Models. Furthermore, IS enables hotels to earn significantly higher revenue. Thus, duopoly hotel players in general, might have reasonable incentives to share information horizontally. During off-peak season, MPS Models are able to predict the optimal equal price for both hotels. However, Nash equilibrium may not always exist depending on actual payoff of adhering or betraying mutual agreement. To optimize performance, horizontal cooperative game may be chosen over non-cooperative game. Mathematical models can be used to detect collusion among business players. Empirical testing can be used as policy input for market regulator in preventing unethical business practices potentially harming society welfare.

Keywords: horizontal cooperative game theory, hotel revenue management, information sharing, mutual price setting

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Authors: Joel A. Gordon, Nazmiye Balta-Ozkan, Seyed Ali Nabavi

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Hydrogen-fueled technologies are rapidly advancing as a critical component of the low-carbon energy transition. In countries historically reliant on natural gas for home heating, such as the UK, hydrogen may prove fundamental for decarbonizing the residential sector, alongside other technologies such as heat pumps and district heat networks. While the UK government is set to take a long-term policy decision on the role of domestic hydrogen by 2026, there are considerable uncertainties regarding consumer preferences for ‘hydrogen homes’ (i.e., hydrogen-fueled appliances for space heating, hot water, and cooking. In comparison to other hydrogen energy technologies, such as road transport applications, to date, few studies have engaged with the social acceptance aspects of the domestic hydrogen transition, resulting in a stark knowledge deficit and pronounced risk to policymaking efforts. In response, this study aims to safeguard against undesirable policy measures by revealing the underlying relationships between the factors of domestic hydrogen acceptance and their respective dimensions: attitudinal, socio-political, community, market, and behavioral acceptance. The study employs an online survey (n=~2100) to gauge how different UK householders perceive the proposition of switching from natural gas to hydrogen-fueled appliances. In addition to accounting for housing characteristics (i.e., housing tenure, property type and number of occupants per dwelling) and several other socio-structural variables (e.g. age, gender, and location), the study explores the impacts of consumer heterogeneity on hydrogen acceptance by recruiting respondents from across five distinct groups: (1) fuel poor householders, (2) technology engaged householders, (3) environmentally engaged householders, (4) technology and environmentally engaged householders, and (5) a baseline group (n=~700) which filters out each of the smaller targeted groups (n=~350). This research design reflects the notion that supporting a socially fair and efficient transition to hydrogen will require parallel engagement with potential early adopters and demographic groups impacted by fuel poverty while also accounting strongly for public attitudes towards net zero. Employing a second-order multigroup confirmatory factor analysis (CFA) in Mplus, the proposed hydrogen acceptance model is tested to fit the data through a partial least squares (PLS) approach. In addition to testing differences between and within groups, the findings provide policymakers with critical insights regarding the significance of knowledge and awareness, safety perceptions, perceived community impacts, cost factors, and trust in key actors and stakeholders as potential explanatory factors of hydrogen acceptance. Preliminary results suggest that knowledge and awareness of hydrogen are positively associated with support for domestic hydrogen at the household, community, and national levels. However, with the exception of technology and/or environmentally engaged citizens, much of the population remains unfamiliar with hydrogen and somewhat skeptical of its application in homes. Knowledge and awareness present as critical to facilitating positive safety perceptions, alongside higher levels of trust and more favorable expectations for community benefits, appliance performance, and potential cost savings. Based on these preliminary findings, policymakers should be put on red alert about diffusing hydrogen into the public consciousness in alignment with energy security, fuel poverty, and net-zero agendas.

Keywords: hydrogen homes, social acceptance, consumer heterogeneity, heat decarbonization

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