Search results for: optimize controller

Authors: Danny Hjeij, Karine Bilodeau, Caroline Arbour

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Background: Chemotherapy infusions often lead to a cluster of co-occurring and difficult-to-treat symptoms (nausea, tingling, etc.), which may negatively impact the treatment experience at the outpatient clinic. Although several complementary approaches have shown beneficial effects for chemotherapy-induced symptom management, they are not easily implementable during chemotherapy infusion. In response to this limitation, comfort talk (CT), a simple, fast conversational method inspired by the language principles of clinical hypnosis, is known to optimize the management of symptoms related to antineoplastic treatments. However, the perception of nurses who have had to integrate this practice into their care has never been documented. Study design: A qualitative descriptive study with iterative content analysis was conducted among oncology nurses working in a chemotherapy outpatient clinic who had previous experience with CT. Semi-structured interviews were conducted by phone, using a pre-tested interview guide and a sociodemographic survey to document their perception of CT. The conceptual framework. Results: A total of six nurses (4 women, 2 men) took part in the interviews (N=6). The average age of participants was 49 years (36-61 years). Participants had an average of 24 years of experience (10-38 years) as a nurse, including 14.5 years in oncology (5-32 years). Data saturation (i.e., redundancy of words) was observed around the fifth interview. A sixth interview was conducted as confirmation. Six themes emerged: two addressing contextual and organizational obstacles at the chemotherapy outpatient clinic, and three addressing the added value of CT for oncology nursing care. Specific themes included: 1) the outpatient oncology clinic, a saturated care setting, 2) the keystones that support the integration of CT into care, 3) added value for patients, 4) a positive and rewarding experience for nurses, 5) collateral benefits, and 6) CT an approach to consider during the COVID-19 pandemic. Conclusion: For the first time, this study describes nurses' perception of the integration of CT into the care surrounding the administration of chemotherapy at the outpatient oncology clinic. In summary, contextual and organizational difficulties, as well as the lack of training, are among the main obstacles that could hinder the integration of CT in oncology. Still, the experience was reported mostly as positive. Indeed, nurses saw HC as an added value to patient care and meeting their need for holistic care. HC also appears to be beneficial for patients on several levels (for pain management in particular). Results will be used to inform future knowledge transfer activities related to CT in oncology nursing.

Keywords: cancer, chemotherapy, comfort talk, oncology nursing role

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Authors: María Barbaño Acevedo Gómez, Elena Sonsoles Rodríguez López, Sofía Olivia Calvo Moreno, Ángel Basas García, Christophe RamíRez Parenteau

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Introduction: Urinary incontinence (UI) is defined as the involuntary leakage of urine. In persons who practice sport, its prevalence is 36.1% (95% CI 26.5% –46.8%) and varies as it seems to depend on the intensity of exercise, movements and impact on the ground. Such high impact sports are likely to generate higher intra-abdominal pressures and leading to pelvic floor muscle weakness. Although physical exercise reduces the risk of suffering from many diseases the mentality of an elite athlete is not to optimize their health, achieving their goals can put their health at risk. Furthermore, feeling or suffering from any discomfort during training seems to be normal within the elite sport demands. Objective: The main objective of the present study was to know the effects of UI in sports performance in athletes. Methods: This was an observational study conducted in 754 elite athletes. After collecting questions about pelvic floor, UI and sport-related data, participants completed the questionnaire International Consultation on Incontinence Questionnaire-UI Short- Form (ICIQ-SF) and ISI (index of incontinence severity). Results: 48.8% of the athletes declare having losses also in rest, preseason and / or competition (χ2 [3] = 3.64; p = 0.302), being the competition period (29.1%) the most frequent where suffer from urine leakage. Of the elite athletes surveyed, 33% had UI according ICIQ-SF (mean age 23.75 ± 7.74 years). Elite athletes with UI (5.31 ± 1.07 days) dedicate significantly more days per week to training [M = 0.28; 95% CI = 0.08-0.48; t (752) = 2.78; p = 0.005] than those without UI. Regarding frequency, 59.7% lose urine once a week, 25.6% lose urine more than 3 times a week, and 14.7% daily. Based on the amount, approximately 15% claim to lose a moderate and abundant. Athletes with the highest number of urine leaks during their training, the UI affects them more in their daily life (r = 0.259; p = 0.001), they present a greater number of losses in their day to day (r = 0.341; p <0.001 ) and greater severity of UI (r = 0.341; p <0.001). Conclusions: Athletes consider that UI affects them negatively in their daily routine, 30.9% affirm having a severity between moderate and severe in their daily routine, and 29.1% loss urine in competition period. An interesting fact is that more than half of the samples collected were elite athletes who compete at the highest level (Olympic Games, World and European Championship), the dedication to sport occupies a big piece in their life. The most frequent period where athletes suffers urine leakage is in competition and there are many emotions that athletes manage to get their best performance, if we add urine losses in that moments it is possible that their performance could be affected.

Keywords: athletes, performance, prevalence, sport, training, urinary incontinence

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Authors: Jafar S. Noori, Jan Romano-deGea, Maria Dimaki, John Mortensen, Winnie E. Svendsen

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Pesticides have been intensively used in agriculture to control weeds, insects, fungi, and pest. One of the most commonly used pesticides is glyphosate. Glyphosate has the ability to attach to the soil colloids and degraded by the soil microorganisms. As glyphosate led to the appearance of resistant species, the pesticide was used more intensively. As a consequence of the heavy use of glyphosate, residues of this compound are increasingly observed in food and water. Recent studies reported a direct link between glyphosate and chronic effects such as teratogenic, tumorigenic and hepatorenal effects although the exposure was below the lowest regulatory limit. Today, pesticides are detected in water by complicated and costly manual procedures conducted by highly skilled personnel. It can take up to several days to get an answer regarding the pesticide content in water. An alternative to this demanding procedure is offered by electrochemical measuring techniques. Electrochemistry is an emerging technology that has the potential of identifying and quantifying several compounds in few minutes. It is currently not possible to detect glyphosate directly in water samples, and intensive research is underway to enable direct selective and quantitative detection of glyphosate in water. This study focuses on developing and modifying a sensor chip that has the ability to selectively measure glyphosate and minimize the signal interference from other compounds. The sensor is a silicon-based chip that is fabricated in a cleanroom facility with dimensions of 10×20 mm. The chip is comprised of a three-electrode configuration. The deposited electrodes consist of a 20 nm layer chromium and 200 nm gold. The working electrode is 4 mm in diameter. The working electrodes are modified by creating molecularly imprinted polymers (MIP) using electrodeposition technique that allows the chip to selectively measure glyphosate at low concentrations. The modification included using gold nanoparticles with a diameter of 10 nm functionalized with 4-aminothiophenol. This configuration allows the nanoparticles to bind to the working electrode surface and create the template for the glyphosate. The chip was modified using electrodeposition technique. An initial potential for the identification of glyphosate was estimated to be around -0.2 V. The developed sensor was used on 6 different concentrations and it was able to detect glyphosate down to 0.5 mgL⁻¹. This value is below the accepted pesticide limit of 0.7 mgL⁻¹ set by the US regulation. The current focus is to optimize the functionalizing procedure in order to achieve glyphosate detection at the EU regulatory limit of 0.1 µgL⁻¹. To the best of our knowledge, this is the first attempt to modify miniaturized sensor electrodes with functionalized nanoparticles for glyphosate detection.

Keywords: pesticides, glyphosate, rapid, detection, modified, sensor

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Authors: Stefan Peters, Phillip Roetman

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The global loss of biodiversity is threatening the benefits nature provides to human populations and has become a more pressing issue than climate change and requires immediate attention. While there have been successful global agreements for environmental protection, such as the Montreal Protocol, these are rare, and we cannot rely on them solely. Thus, it is crucial to take national and local actions to support biodiversity. Australia is one of the 17 countries in the world with a high level of biodiversity, and its cities are vital habitats for endangered species, with more of them found in urban areas than in non-urban ones. However, the protection of biodiversity in metropolitan Adelaide has been inadequate, with over 130 species disappearing since European colonization in 1836. In this research project we conceptualized, developed and implemented a framework for wildlife Habitat Hotspots and Habitat Corridor modelling in an urban context using geographic data and GIS modelling and analysis. We used detailed topographic and other geographic data provided by a local council, including spatial and attributive properties of trees, parcels, water features, vegetated areas, roads, verges, traffic, and census data. Weighted factors considered in our raster-based Habitat Hotspot model include parcel size, parcel shape, population density, canopy cover, habitat quality and proximity to habitats and water features. Weighted factors considered in our raster-based Habitat Corridor model include habitat potential (resulting from the Habitat Hotspot model), verge size, road hierarchy, road widths, human density, and presence of remnant indigenous vegetation species. We developed a GIS model, using Python scripting and ArcGIS-Pro Model-Builder, to establish an automated reproducible and adjustable geoprocessing workflow, adaptable to any study area of interest. Our habitat hotspot and corridor modelling framework allow to determine and map existing habitat hotspots and wildlife habitat corridors. Our research had been applied to the study case of Burnside, a local council in Adelaide, Australia, which encompass an area of 30 km2. We applied end-user expertise-based category weightings to refine our models and optimize the use of our habitat map outputs towards informing local strategic decision-making.

Keywords: biodiversity, GIS modeling, habitat hotspot, wildlife corridor

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Authors: Hatice Akbıyık, Hülya Gökmen Özel, Nagehan Emiralioğlu, Elmas Ebru Güneş Yalçın, Deniz Doğru Ersöz, Hayriye Uğur Özçelik, Nural Kiper

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Background: Dietary recommendations in cystic fibrosis (CF) are based on the need to compensate for the increased energy needs of infection, the increased energy cost of breathing and the losses, incurred from malabsorption. Studies in CF indicate that dietary recommendations for CF patients can be difficult to achieve Aim: The aim of this study was to evaluate the energy and nutrient intakes and to compare in accordance with CF dietary guidelines in CF. Methods: One-hundred sixty patients with CF, aged between 2 to 20 years (mean±SD= 7.4±4.8 years) attending Hacettepe University, Faculty of Medicine, Department of Pediatric Pulmonary Diseases were included. Energy and nutrient intakes from foods and enteral products were calculated using a-24-hour dietary recall method with BEBIS 7.2 programme. Percentages of energy and nutrient intakes were compared in accordance with CF dietary guidelines. Patients or/and parents completed a questionnaire showing mealtime problems, usage of alternative therapies and type of nutrition. Statistical analyses were done using SPSS 16.0 programme. Results: It was obtained that 14.5% and 46.9% of the total energy intake were from proteins and carbohydrates, respectively. The actual contribution of total, saturated, monounsaturated and polyunsaturated fats to the total caloric intake was 37.5%, 14.3%, 14.9%, 9.9%, respectively. It was found that 87.7% of energy, 85% of protein 91.7% of carbohydrate, 81.1% of fat intakes were met, when compared CF recommended intakes of 120% RDA. Additionally 67%, 69.5%, 68.2% and 68.9% of the subjects did not achieve CF recommended intakes of 120% RDA for energy, protein, carbohydrate and fat, respectively. Patients with CF had low intakes for age for almost all vitamins and minerals, although supplementation was given. Especially most patients did not achieve the minimum recommended vitamin K intake of 120% RDA. The percentage meeting 120% RDA was 75.9% for vitamin K. It was shown that 41% of the patients had mealtime problems and they skipped the breakfast. Moreover 25.4% of the patients used alternative products outside the standard treatment (such as omega-3, ginger, turmeric, local honey). It was also showed that 60.8% of patients were using enteral products in addition to normal foods, the remaining patients were on only normal foods. Conclusion: The aims of improving nutritional status in children are to achieve normal weight gain and growth; optimize vitamin and mineral status; and slow the rate of clinical decline. In this study although enteral products were used in patients with CF, it was found that energy and nutrient requirements were unable to meet. Because dietary assessment is essential to identify the need for earlier nutritional intervention, in each visit patients need to be referred to CF specialist dietitian.

Keywords: cystic fibrosis, energy and nutrient intakes, mealtime problems, malabsorbtion

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Authors: S. Cheng, C. Catallo

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Introduction: Canada's healthcare and social services systems are failing high risk, vulnerable older adults. Care for vulnerable older Canadians (65 and older) is not optimal in Canada. It does not address the care needs of vulnerable, high risk adults using a holistic approach. Given the growing aging population, and the care needs for seniors with complex conditions is one of the highest in Canada's health care system, there is a sense of urgency to optimize care. Integration of health and social services is an emerging trend in Canada when compared to European countries. There is no common and universal understanding of healthcare and social services integration within the country. Consequently, a clear understanding and definition of integrated health and social services are absent in Canada. Objectives: A study was undertaken to develop a case definition for integrated health and social care initiatives that serve older adults, which was then tested against three Canadian integrated initiatives. Methodology: A limited literature review was undertaken to identify common characteristics of integrated health and social care initiatives that serve older adults, and comprised both scientific and grey literature, in order to develop a case definition. Three Canadian integrated initiatives that are located in the province of Ontario, were identified using an online search and a screening process. They were surveyed to determine if the literature-based integration definition applied to them. Results: The literature showed that there were 24 common healthcare and social services integration characteristics that could be categorized into ten themes: 1) patient-care approach; 2) program goals; 3) measurement; 4) service and care quality; 5) accountability and responsibility; 6) information sharing; 7) Decision-making and problem-solving; 8) culture; 9) leadership; and 10) staff and professional interaction. The three initiatives showed agreement on all the integration characteristics except for those characteristics associated with healthcare and social care professional interaction, collaborative leadership and shared culture. This disagreement may be due to several reasons, including the existing governance divide between the healthcare and social services sectors within the province of Ontario that has created a ripple effect in how professions in the two different sectors interact. In addition, the three initiatives may be at maturing levels of integration, which may explain disagreement on the characteristics associated with leadership and culture. Conclusions: The development of a case definition for healthcare and social services integration that incorporates common integration characteristics can act as a useful instrument in identifying integrated healthcare and social services, particularly given the emerging and evolutionary state of this phenomenon within Canada.

Keywords: Canada, case definition, healthcare and social services integration, integration, seniors health, services delivery

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Authors: Pukhrambam Helena Chanu, Janardan Yadav

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This study investigates the potential of various fungal isolates to solubilize zinc and counteract rice pathogens, with the aim of mitigating zinc deficiency and disease prevalence in rice farming. Soil samples from the rhizosphere were collected, and zinc-solubilizing fungi were isolated and purified. Molecular analysis identified Talaromyces sp, Talaromyces versatilis, Talaromyces pinophilus, and Aspergillus terreus as effective zinc solubilizers. Through qualitative and quantitative assessments, it was observed that solubilization efficiencies varied among the isolates over time, with Talaromyces versatilis displaying the highest capacity for solubilization. This variability in solubilization rates may be attributed to differences in fungal metabolic activity and their ability to produce organic acids that facilitate zinc release from insoluble sources in the soil. In inhibition assays against rice pathogens, the fungal isolates exhibited antagonistic properties, with Talaromyces versatilis demonstrating the most significant inhibition rates. This antagonistic activity may be linked to the production of secondary metabolites, such as antibiotics or lytic enzymes by fungi, which inhibit the growth of rice pathogens. The ability of Talaromyces versatilis to outperform other isolates in both zinc solubilization and pathogen inhibition highlights its potential as a multifunctional biocontrol agent in rice cultivation systems. These findings emphasize the potential of fungi as natural solutions for enhancing zinc uptake and managing diseases in rice cultivation. Utilizing indigenous zinc-solubilizing fungi offers a sustainable and environmentally friendly approach to addressing zinc deficiency in soils, reducing the need for chemical fertilizers. Moreover, harnessing the antagonistic activity of these fungi can contribute to integrated disease management strategies, minimizing reliance on synthetic pesticides and promoting ecological balance in agroecosystems. Additionally, the study included the evaluation of dipping time under different concentrations, viz.,10 ppm, 20 ppm, and 30 ppm of biosynthesized nano ZnO on rice seedlings. This investigation aimed to optimize the application of nano ZnO for efficient zinc uptake by rice plants while minimizing potential risks associated with excessive nanoparticle exposure. Evaluating the effects of varying concentrations and dipping durations provides valuable insights into the safe and effective utilization of nano ZnO as a micronutrient supplement in rice farming practices.

Keywords: biosynthesized nano ZnO, rice, root dipping, zinc solubilizing fungi.

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Authors: B. Mohammadi, A. Riazati, P. Soltan Sanjari, S. Azimbeik

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The ever-increasing development of civic demands on one hand; and the urban constrains for newly establish of infrastructures, on the other hand, perforce the engineering committees to apply non-conflicting methods in order to optimize the results. One of these optimized procedures to establish the main sewerage networks is the pipe jacking and micro-tunneling method. The raw information and researches are based on the experiments of the slurry micro-tunneling project of the Tehran main sewerage network that it has executed by the KAYSON co. The 4985 meters route of the mentioned project that is located nearby the Azadi square and the most vital arteries of Tehran is faced to 45% physical progress nowadays. The boring machine is made by the Herrenknecht and the diameter of the using concrete-polymer pipes are 1600 and 1800 millimeters. Placing and excavating several shafts on the ground and direct Tunnel boring between the axes of issued shafts is one of the requirements of the micro-tunneling. Considering the stream of the ground located shafts should care the hydraulic circumstances, civic conditions, site geography, traffic cautions and etc. The profile length has to convert to many shortened segment lines so the generated angle between the segments will be based in the manhole centers. Each segment line between two continues drive and receive the shaft, displays the jack location, driving angle and the path straight, thus, the diversity of issued angle causes the variety of jack positioning in the shaft. The jacking frame fixing conditions and it's associated dynamic load direction produces various patterns of Stress and Strain distribution and creating fatigues in the shaft wall and the soil surrounded the shaft. This pattern diversification makes the shaft wall transformed, unbalanced subsidence and alteration in the pipe jacking Stress Contour. This research is based on experiments of the Tehran's west sewerage plan and the numerical analysis the interaction of the soil around the shaft, shaft walls and the Jacking frame direction and finally, the suitable or unsuitable location of the pipe jacking shaft will be determined.

Keywords: underground structure, micro-tunneling, fatigue analysis, dynamic-soil–structure interaction, underground water, finite element analysis

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Authors: Tassadit Issaadi Hamitouche, Nicolas Gillard, Jean Petit, Valerie Lavaste, Celine Mayousse

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Water is a fundamental resource for the industry. It is taken from the environment either from municipal distribution networks or from various natural water sources such as the sea, ocean, rivers, aquifers, etc. Once used, water is discharged into the environment, reprocessed at the plant or treatment plants. These withdrawals and discharges have a direct impact on natural water resources. These impacts can apply to the quantity of water available, the quality of the water used, or to impacts that are more complex to measure and less direct, such as the health of the population downstream from the watercourse, for example. Based on the analysis of data (meteorological, river characteristics, physicochemical substances), we wish to predict water stress episodes and anticipate prefectoral decrees, which can impact the performance of plants and propose improvement solutions, help industrialists in their choice of location for a new plant, visualize possible interactions between companies to optimize exchanges and encourage the pooling of water treatment solutions, and set up circular economies around the issue of water. The development of a system for the collection, processing, and use of data related to water resources requires the functional constraints specific to the latter to be made explicit. Thus the system will have to be able to store a large amount of data from sensors (which is the main type of data in plants and their environment). In addition, manufacturers need to have 'near-real-time' processing of information in order to be able to make the best decisions (to be rapidly notified of an event that would have a significant impact on water resources). Finally, the visualization of data must be adapted to its temporal and geographical dimensions. In this study, we set up an infrastructure centered on the TICK application stack (for Telegraf, InfluxDB, Chronograf, and Kapacitor), which is a set of loosely coupled but tightly integrated open source projects designed to manage huge amounts of time-stamped information. The software architecture is coupled with the cross-industry standard process for data mining (CRISP-DM) data mining methodology. The robust architecture and the methodology used have demonstrated their effectiveness on the study case of learning the level of a river with a 7-day horizon. The management of water and the activities within the plants -which depend on this resource- should be considerably improved thanks, on the one hand, to the learning that allows the anticipation of periods of water stress, and on the other hand, to the information system that is able to warn decision-makers with alerts created from the formalization of prefectoral decrees.

Keywords: data mining, industry, machine Learning, shortage, water resources

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Authors: Ali H. Daraji, Jack M. Hale, Ye Jianqiao

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With the extensive use of high specific strength structures to optimise the loading capacity and material cost in aerospace and most engineering applications, much effort has been expended to develop intelligent structures for active vibration reduction and structural health monitoring. These structures are highly flexible, inherently low internal damping and associated with large vibration and long decay time. The modification of such structures by adding lightweight piezoelectric sensors and actuators at efficient locations integrated with an optimal control scheme is considered an effective solution for structural vibration monitoring and controlling. The size and location of sensor and actuator are important research topics to investigate their effects on the level of vibration detection and reduction and the amount of energy provided by a controller. Several methodologies have been presented to determine the optimal location of a limited number of sensors and actuators for small-scale structures. However, these studies have tackled this problem directly, measuring the fitness function based on eigenvalues and eigenvectors achieved with numerous combinations of sensor/actuator pair locations and converging on an optimal set using heuristic optimisation techniques such as the genetic algorithms. This is computationally expensive for small- and large-scale structures subject to optimise a number of s/a pairs to suppress multiple vibration modes. This paper proposes an efficient method to determine optimal locations for a limited number of sensor/actuator pairs for active vibration reduction of a flexible structure based on finite element method and Hamilton’s principle. The current work takes the simplified approach of modelling a structure with sensors at all locations, subjecting it to an external force to excite the various modes of interest and noting the locations of sensors giving the largest average percentage sensors effectiveness measured by dividing all sensor output voltage over the maximum for each mode. The methodology was implemented for a cantilever plate under external force excitation to find the optimal distribution of six sensor/actuator pairs to suppress the first six modes of vibration. It is shown that the results of the optimal sensor locations give good agreement with published optimal locations, but with very much reduced computational effort and higher effectiveness. Furthermore, it is shown that collocated sensor/actuator pairs placed in these locations give very effective active vibration reduction using optimal linear quadratic control scheme.

Keywords: optimisation, plate, sensor effectiveness, vibration control

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Authors: Pablo Chico De Guzman, Cesar Sanchez

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Microservices are a software development methodology in which applications are built by composing a set of independently deploy-able, small, modular services. Each service runs a unique process and it gets instantiated and deployed in one or more machines (we assume that different microservices are deployed into different machines). Microservices are becoming the de facto standard for developing distributed cloud applications due to their reduced release cycles. In principle, the responsibility of a microservice can be as simple as implementing a single function, which can lead to the following issues: - Resource fragmentation due to the virtual machine boundary. - Poor communication performance between microservices. Two composition techniques can be used to optimize resource fragmentation and communication performance: aggregation and embedding of microservices. Aggregation allows the deployment of a set of microservices on the same machine using a proxy server. Aggregation helps to reduce resource fragmentation, and is particularly useful when the aggregated services have a similar scalability behavior. Embedding deals with communication performance by deploying on the same virtual machine those microservices that require a communication channel (localhost bandwidth is reported to be about 40 times faster than cloud vendor local networks and it offers better reliability). Embedding can also reduce dependencies on load balancer services since the communication takes place on a single virtual machine. For example, assume that microservice A has two instances, a1 and a2, and it communicates with microservice B, which also has two instances, b1 and b2. One embedding can deploy a1 and b1 on machine m1, and a2 and b2 are deployed on a different machine m2. This deployment configuration allows each pair (a1-b1), (a2-b2) to communicate using the localhost interface without the need of a load balancer between microservices A and B. Aggregation and embedding techniques are complex since different microservices might have incompatible runtime dependencies which forbid them from being installed on the same machine. There is also a security concern since the attack surface between microservices can be larger. Luckily, container technology allows to run several processes on the same machine in an isolated manner, solving the incompatibility of running dependencies and the previous security concern, thus greatly simplifying aggregation/embedding implementations by just deploying a microservice container on the same machine as the aggregated/embedded microservice container. Therefore, a wide variety of deployment configurations can be described by combining aggregation and embedding to create an efficient and robust microservice architecture. This paper presents a formal method that receives a declarative definition of a microservice architecture and proposes different optimized deployment configurations by aggregating/embedding microservices. The first prototype is based on i2kit, a deployment tool also submitted to ICWS 2018. The proposed prototype optimizes the following parameters: network/system performance, resource usage, resource costs and failure tolerance.

Keywords: aggregation, deployment, embedding, resource allocation

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Authors: Jeh Patel, Chandrahas Paidi, Ahmed Hambaba

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Traditional methods for analyzing athlete movement often lack the detail and immediacy required for optimal training. This project aims to address this limitation by developing a Real-time human pose estimation system specifically designed to enhance athlete training across various sports. This system leverages the power of convolutional neural networks (CNNs) to provide a comprehensive and immediate analysis of an athlete’s movement patterns during training sessions. The core architecture utilizes dilated convolutions to capture crucial long-range dependencies within video frames. Combining this with the robust encoder-decoder architecture to further refine pose estimation accuracy. This capability is essential for precise joint localization across the diverse range of athletic poses encountered in different sports. Furthermore, by quantifying movement efficiency, power output, and range of motion, the system provides data-driven insights that can be used to optimize training programs. Pose estimation data analysis can also be used to develop personalized training plans that target specific weaknesses identified in an athlete’s movement patterns. To overcome the limitations posed by outdoor environments, the project employs strategies such as multi-camera configurations or depth sensing techniques. These approaches can enhance pose estimation accuracy in challenging lighting and occlusion scenarios, where pose estimation accuracy in challenging lighting and occlusion scenarios. A dataset is collected From the labs of Martin Luther King at San Jose State University. The system is evaluated through a series of tests that measure its efficiency and accuracy in real-world scenarios. Results indicate a high level of precision in recognizing different poses, substantiating the potential of this technology in practical applications. Challenges such as enhancing the system’s ability to operate in varied environmental conditions and further expanding the dataset for training were identified and discussed. Future work will refine the model’s adaptability and incorporate haptic feedback to enhance the interactivity and richness of the user experience. This project demonstrates the feasibility of an advanced pose detection model and lays the groundwork for future innovations in assistive enhancement technologies.

Keywords: computer vision, deep learning, human pose estimation, U-NET, CNN

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Authors: Abiodun Olayinka, Daniel Dzidzienyo, Pangirayi Tongoona, Samuel Offei, Edwige Gaby Nkouaya Mbanjo, Chiedozie Egesi, Ismail Yusuf Rabbi

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Cassava (Manihot esculenta Crantz) is a major source of starch for various industrial applications. However, the traditional cultivation and harvesting methods of cassava are labour-intensive and inefficient, limiting the supply of fresh cassava roots for industrial starch production. To achieve improved productivity and quality of fresh cassava roots through mechanized cultivation, cassava cultivars with compact plant architecture and moderate plant height are needed. Plant architecture-related traits, such as plant height, harvest index, stem diameter, branching angle, and lodging tolerance, are critical for crop productivity and suitability for mechanized cultivation. However, the genetics of cassava plant architecture remain poorly understood. This study aimed to identify the genetic bases of the relationships between plant architecture traits and productivity-related traits, particularly starch content. A panel of 453 clones developed at the International Institute of Tropical Agriculture, Nigeria, was genotyped and phenotyped for 18 plant architecture and productivity-related traits at four locations in Nigeria. A genome-wide association study (GWAS) was conducted using the phenotypic data from a panel of 453 clones and 61,238 high-quality Diversity Arrays Technology sequencing (DArTseq) derived Single Nucleotide Polymorphism (SNP) markers that are evenly distributed across the cassava genome. Five significant associations between ten SNPs and three plant architecture component traits were identified through GWAS. We found five SNPs on chromosomes 6 and 16 that were significantly associated with shoot weight, harvest index, and total yield through genome-wide association mapping. We also discovered an essential candidate gene that is co-located with peak SNPs linked to these traits in M. esculenta. A review of the cassava reference genome v7.1 revealed that the SNP on chromosome 6 is in proximity to Manes.06G101600.1, a gene that regulates endodermal differentiation and root development in plants. The findings of this study provide insights into the genetic basis of plant architecture and yield in cassava. Cassava breeders could leverage this knowledge to optimize plant architecture and yield in cassava through marker-assisted selection and targeted manipulation of the candidate gene.

Keywords: Manihot esculenta Crantz, plant architecture, DArtseq, SNP markers, genome-wide association study

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Authors: Pooria Norouzi, Nicholas Tsang, Adam van der Goes, Joseph Yu, Douglas Zheng, Sirine Maleej

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In this study, virtual meters will be designed and used for energy balance measurements of an air handling unit (AHU). The method aims to replace traditional physical sensors in heating, ventilation, and air conditioning (HVAC) systems with simulated virtual meters. Due to the inability to manage and monitor these systems, many HVAC systems have a high level of inefficiency and energy wastage. Virtual meters are implemented and applied in an actual HVAC system, and the result confirms the practicality of mathematical sensors for alternative energy measurement. While most residential buildings and offices are commonly not equipped with advanced sensors, adding, exploiting, and monitoring sensors and measurement devices in the existing systems can cost thousands of dollars. The first purpose of this study is to provide an energy consumption rate based on available sensors and without any physical energy meters. It proves the performance of virtual meters in HVAC systems as reliable measurement devices. To demonstrate this concept, mathematical models are created for AHU-07, located in building NE01 of the British Columbia Institute of Technology (BCIT) Burnaby campus. The models will be created and integrated with the system’s historical data and physical spot measurements. The actual measurements will be investigated to prove the models' accuracy. Based on preliminary analysis, the resulting mathematical models are successful in plotting energy consumption patterns, and it is concluded confidently that the results of the virtual meter will be close to the results that physical meters could achieve. In the second part of this study, the use of virtual meters is further assisted by artificial intelligence (AI) in the HVAC systems of building to improve energy management and efficiency. By the data mining approach, virtual meters’ data is recorded as historical data, and HVAC system energy consumption prediction is also implemented in order to harness great energy savings and manage the demand and supply chain effectively. Energy prediction can lead to energy-saving strategies and considerations that can open a window in predictive control in order to reach lower energy consumption. To solve these challenges, the energy prediction could optimize the HVAC system and automates energy consumption to capture savings. This study also investigates AI solutions possibility for autonomous HVAC efficiency that will allow quick and efficient response to energy consumption and cost spikes in the energy market.

Keywords: virtual meters, HVAC, artificial intelligence, energy consumption prediction

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Authors: Deanne McArthur, Melinda Wall, Claire Hanlon, Dana Agnolin, Krista Davis, Melanie Dennis, Elizabeth Glidden, Anne Marie Smith, Claudette Thomson

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Background and significance: Patients with eating disorders have traditionally been an underserviced population within the publicly-funded Canadian healthcare system. This situation was worsened by the COVID-19 pandemic and accompanying public health measures, such as “lockdowns” which led to increased isolation, changes in routine, and other disruptions. Illness severity and prevalence rose significantly with corresponding increases in patient suffering and poor outcomes. In Ontario, Canada, the provincial government responded by increasing funding for the treatment of eating disorders, including the launch of a new day program at an intermediate, regional health centre that already housed an outpatient treatment service. The funding was received in March 2022. The care team sought to optimize this opportunity by designing a program that would fit well within the resource-constrained context in Ontario. Methods: This case study will detail how the team consulted the literature and sought patient and family input to design a program that optimizes patient outcomes and supports for patients and families while they await treatment. Early steps include a review of the literature, expert consultation and patient and family focus groups. Interprofessional consensus was sought at each step with the team adopting a shared leadership and patient-centered approach. Methods will include interviews, observations and document reviews to detail a rich description of the process undertaken to design the program, including evaluation measures adopted. Interim findings pertaining to the early stages of the program-building process will be detailed as well as early lessons and ongoing evolution of the program and design process. Program implementation and outcome evaluation will continue throughout 2022 and early 2023 with further publication and presentation of study results expected in the summer of 2023. The aim of this study is to contribute to the body of knowledge pertaining to the design and implementation of eating disorder treatment services that combine outpatient and day treatment services in a resource-constrained context.

Keywords: eating disorders, day program, interprofessional, outpatient, adolescents, transitional aged youth

Procedia PDF Downloads 83

Authors: S. Jurado, E. Pazmino

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Determination of the medial axis of a porous media sample is a non-trivial problem of interest for several disciplines, e.g., hydrology, fluid dynamics, contaminant transport, filtration, oil extraction, etc. However, the computational tools available for researchers are limited and restricted. The primary aim of this work was to develop a series of algorithms to extract porosity, medial axis structure, and pore-throat size distributions from porous media domains. A complementary objective was to provide the algorithms as free computational software available to the academic community comprising researchers and students interested in 3D data processing. The burn algorithm was tested on porous media data obtained from High-Resolution X-Ray Microtomography (HRXMT) and idealized computer-generated domains. The real data and idealized domains were discretized in voxels domains of 550³ elements and binarized to denote solid and void regions to determine porosity. Subsequently, the algorithm identifies the layer of void voxels next to the solid boundaries. An iterative process removes or 'burns' void voxels in sequence of layer by layer until all the void space is characterized. Multiples strategies were tested to optimize the execution time and use of computer memory, i.e., segmentation of the overall domain in subdomains, vectorization of operations, and extraction of single burn layer data during the iterative process. The medial axis determination was conducted identifying regions where burnt layers collide. The final medial axis structure was refined to avoid concave-grain effects and utilized to determine the pore throat size distribution. A graphic user interface software was developed to encompass all these algorithms, including the generation of idealized porous media domains. The software allows input of HRXMT data to calculate porosity, medial axis, and pore-throat size distribution and provide output in tabular and graphical formats. Preliminary tests of the software developed during this study achieved medial axis, pore-throat size distribution and porosity determination of 100³, 320³ and 550³ voxel porous media domains in 2, 22, and 45 minutes, respectively in a personal computer (Intel i7 processor, 16Gb RAM). These results indicate that the software is a practical and accessible tool in postprocessing HRXMT data for the academic community.

Keywords: medial axis, pore-throat distribution, porosity, porous media

Procedia PDF Downloads 94

Authors: Liam Martin, Martha Watson

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Patients with learning disabilities (LD) are at increased risk of physical and mental illness due to health inequality. To address this, NICE recommends that people from the age of 14 with a learning disability should have an annual LD health check. This consultation should include a holistic review of the patient’s physical, mental and social health needs with a view of creating an action plan to support the patient’s care. The expected standard set by the Quality and Outcomes Framework (QOF) is that each general practice should review at least 75% of their LD patients annually. During COVID-19, there have been barriers to primary care, including health anxiety, the shift to online general practice and the increase in GP workloads. A surgery in North London wanted to assess whether they were falling short of the expected standard for LD patient annual reviews in order to optimize care post Covid-19. A baseline audit was completed to assess how many LD patients were receiving their annual reviews over the period of 29th September 2020 to 29th September 2021. This information was accessed using EMIS Web Health Care System (EMIS). Patients included were aged 14 and over as per QOF standards. Doctors were not notified of this audit taking place. Following the results of this audit, the creation of learning disability clinics was recommended. These clinics were recommended to be on the ground floor and should be a dedicated time for LD reviews. A re-audit was performed via the same process 6 months later in March 2022. At the time of the baseline audit, there were 71 patients aged 14 and over that were on the LD register. 54% of these LD patients were found to have documentation of an annual LD review within the last 12 months. None of the LD patients between the ages of 14-18 years old had received their annual review. The results were discussed with the practice, and dedicated clinics were set up to review their LD patients. A second pass of the audit was completed 6 months later. This showed an improvement, with 84% of the LD patients registered at the surgery now having a documented annual review within the last 12 months. 78% of the patients between the ages of 14-18 years old had now been reviewed. The baseline audit revealed that the practice was not meeting the expected standard for LD patient’s annual health checks as outlined by QOF, with the most neglected patients being between the ages of 14-18. Identification and awareness of this vulnerable cohort is important to ensure measures can be put into place to support their physical, mental and social wellbeing. Other practices could consider an audit of their annual LD health checks to make sure they are practicing within QOF standards, and if there is a shortfall, they could consider implementing similar actions as used here; dedicated clinics for LD patient reviews.

Keywords: COVID-19, learning disability, learning disability health review, quality and outcomes framework

Procedia PDF Downloads 62

Authors: Asma Omri, Noureddine Benothman, Sofiane Sayahi, Fethi Tlili, Hichem Besbes

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Cycling, a popular mode of transportation, can also be perilous due to cyclists' vulnerability to collisions with vehicles and obstacles. This paper presents an innovative cyclist safety system based on radar technology designed to offer real-time collision risk warnings to cyclists. The system incorporates a low-power radar sensor affixed to the bicycle and connected to a microcontroller. It leverages radar point cloud detections, a clustering algorithm, and a supervised classifier. These algorithms are optimized for efficiency to run on the TI’s AWR 1843 BOOST radar, utilizing a coarse classification approach distinguishing between cars, trucks, two-wheeled vehicles, and other objects. To enhance the performance of clustering techniques, we propose a 2-Level clustering approach. This approach builds on the state-of-the-art Density-based spatial clustering of applications with noise (DBSCAN). The objective is to first cluster objects based on their velocity, then refine the analysis by clustering based on position. The initial level identifies groups of objects with similar velocities and movement patterns. The subsequent level refines the analysis by considering the spatial distribution of these objects. The clusters obtained from the first level serve as input for the second level of clustering. Our proposed technique surpasses the classical DBSCAN algorithm in terms of geometrical metrics, including homogeneity, completeness, and V-score. Relevant cluster features are extracted and utilized to classify objects using an SVM classifier. Potential obstacles are identified based on their velocity and proximity to the cyclist. To optimize the system, we used the View of Delft dataset for hyperparameter selection and SVM classifier training. The system's performance was assessed using our collected dataset of radar point clouds synchronized with a camera on an Nvidia Jetson Nano board. The radar-based cyclist safety system is a practical solution that can be easily installed on any bicycle and connected to smartphones or other devices, offering real-time feedback and navigation assistance to cyclists. We conducted experiments to validate the system's feasibility, achieving an impressive 85% accuracy in the classification task. This system has the potential to significantly reduce the number of accidents involving cyclists and enhance their safety on the road.

Keywords: 2-level clustering, coarse classification, cyclist safety, warning system based on radar technology

Procedia PDF Downloads 54

Authors: M. Černe, I. Palčić, D. Anđelini, D. Cvitan, N. Major, M. Lukić, S. Goreta Ban, D. Ban, T. Rijavec, A. Lapanje

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Context: In the Mediterranean basin, large quantities of lignocellulosic by-products, such as olive pomace (OP), are generated during olive processing on an annual basis. Due to the phytotoxic nature of OP, composting is recommended for its stabilisation to produce the end-product safe for agricultural use. Research Aim: This study aims to evaluate the applicability of olive pomace compost (OPC) for use as a soil amendment by considering its physical and chemical characteristics and microbiological parameters. Methodology: The OPC samples were collected from the surface and depth layers of the compost pile after 8 months. The samples were analyzed for their C/N, pH, EC, total phenolic content, residual oils, and elemental content, as well as colloidal properties and microbial community structure. The specific analytical approaches used are detailed in the poster. Findings: The results showed that the pH of OPC ranged from 7.8 to 8.6, while the electrical conductivity was from 770 to 1608 mS/cm. The levels of nitrogen (N), phosphorus (P), and potassium (K) varied within the ranges of 1.5 to 27.2 g/kg d.w., 1.6 to 1.8 g/kg d.w., and 6.5 to 7.5 g/kg d.w., respectively. The contents of potentially toxic metals such as chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn) were below the EU limits for soil improvers. The microbial structure follows the changes of the gradient from the outer to the innermost layer with relatively low amounts of DNA. The gradient nature shows that it is needed to develop better strategies for composting surpassing the conventional approach. However, the low amounts of total phenols and oil residues indicated efficient biodegradation during composting. The carbon-to-nitrogen ratio (C/N) within the range of 13 to 16 suggested that OPC can be used as a soil amendment. Overall, the study suggests that composting can be a promising strategy for environmentally-friendly OP recycling. Theoretical Importance: This study contributes to the understanding of the use of OPC as a soil amendment and its potential benefits in resource recycling and reducing environmental burdens. It also highlights the need for improved composting strategies to optimize its process. Data Collection and Analysis Procedures: The OPC samples were taken from the compost pile and charasterised for selected chemical, physical and microbial parameters. The specific analytical procedures utilized are described in detail in the poster. Question Addressed: This study addresses the question of whether composting can be optimized to improve the biodegradation of OP. Conclusion: The study concludes that OPC has the potential to be used as a soil amendment due to its favorable physical and chemical characteristics, low levels of potentially toxic metals, and efficient biodegradation during composting. However, the results also suggest the need for improved composting strategies to improve the quality of OPC.

Keywords: olive pomace compost, waste valorisation, agricultural use, soil amendment

Procedia PDF Downloads 38

Authors: Amir Nazemi, Milad Ramezankhani, Marian Kӧrber, Abbas S. Milani

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The excellent strength to weight ratio of woven fabric composites, along with their high formability, is one of the primary design parameters defining their increased use in modern manufacturing processes, including those in aerospace and automotive. However, for emerging automated preform processes under the smart manufacturing paradigm, complex geometries of finished components continue to bring several challenges to the designers to cope with manufacturing defects on site. Wrinklinge. g. is a common defectoccurring during the forming process and handling of semi-finished textile composites. One of the main reasons for this defect is the weak bending stiffness of fibers in unconsolidated state, causing excessive relative motion between them. Further challenges are represented by the automated handling of large-area fiber blanks with specialized gripper systems. For fabric composites forming simulations, the finite element (FE)method is a longstanding tool usedfor prediction and mitigation of manufacturing defects. Such simulations are predominately meant, not only to predict the onset, growth, and shape of wrinkles but also to determine the best processing condition that can yield optimized positioning of the fibers upon forming (or robot handling in the automated processes case). However, the need for use of small-time steps via explicit FE codes, facing numerical instabilities, as well as large computational time, are among notable drawbacks of the current FEtools, hindering their extensive use as fast and yet efficient digital twins in industry. This paper presents a novel woven fabric simulation technique through the application of the material point method (MPM), which enables the use of much larger time steps, facing less numerical instabilities, hence the ability to run significantly faster and efficient simulationsfor fabric materials handling and forming processes. Therefore, this method has the ability to enhance the development of automated fiber handling and preform processes by calculating the physical interactions with the MPM fiber models and rigid tool components. This enables the designers to virtually develop, test, and optimize their processes based on either algorithmicor Machine Learning applications. As a preliminary case study, forming of a hemispherical plain weave is shown, and the results are compared to theFE simulations, as well as experiments.

Keywords: material point method, woven fabric composites, forming, material handling

Procedia PDF Downloads 156

Authors: Abiodun Olayinka, Daniel Dzidzienyo, Pangirayi Tongoona, Samuel Offei, Edwige Gaby Nkouaya Mbanjo, Chiedozie Egesi, Ismail Yusuf Rabbi

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Cassava (Manihot esculenta Crantz) is a major source of starch for various industrial applications. However, the traditional cultivation and harvesting methods of cassava are labour-intensive and inefficient, limiting the supply of fresh cassava roots for industrial starch production. To achieve improved productivity and quality of fresh cassava roots through mechanized cultivation, cassava cultivars with compact plant architecture and moderate plant height are needed. Plant architecture-related traits, such as plant height, harvest index, stem diameter, branching angle, and lodging tolerance, are critical for crop productivity and suitability for mechanized cultivation. However, the genetics of cassava plant architecture remain poorly understood. This study aimed to identify the genetic bases of the relationships between plant architecture traits and productivity-related traits, particularly starch content. A panel of 453 clones developed at the International Institute of Tropical Agriculture, Nigeria, was genotyped and phenotyped for 18 plant architecture and productivity-related traits at four locations in Nigeria. A genome-wide association study (GWAS) was conducted using the phenotypic data from a panel of 453 clones and 61,238 high-quality Diversity Arrays Technology sequencing (DArTseq) derived Single Nucleotide Polymorphism (SNP) markers that are evenly distributed across the cassava genome. Five significant associations between ten SNPs and three plant architecture component traits were identified through GWAS. We found five SNPs on chromosomes 6 and 16 that were significantly associated with shoot weight, harvest index, and total yield through genome-wide association mapping. We also discovered an essential candidate gene that is co-located with peak SNPs linked to these traits in M. esculenta. A review of the cassava reference genome v7.1 revealed that the SNP on chromosome 6 is in proximity to Manes.06G101600.1, a gene that regulates endodermal differentiation and root development in plants. The findings of this study provide insights into the genetic basis of plant architecture and yield in cassava. Cassava breeders could leverage this knowledge to optimize plant architecture and yield in cassava through marker-assisted selection and targeted manipulation of the candidate gene.

Keywords: manihot esculenta crantz, plant architecture, dartseq, snp markers, genome-wide association study

Procedia PDF Downloads 57

Authors: Pamela Del Rosario, Elisabetta Palumbo, Marzia Traverso

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The building sector plays an important role in addressing pressing environmental issues such as climate change and resource scarcity. The energy performance of buildings is considerably affected by the external envelope. In fact, a considerable proportion of the building energy demand is due to energy losses through the windows. Nevertheless, according to literature, to pay attention only to the contribution of windows to the building energy performance, i.e., their influence on energy use during building operation, could result in a partial evaluation. Hence, it is important to consider not only the building energy performance but also the environmental performance of windows, and this not only during the operational stage but along its complete life cycle. Life Cycle Assessment (LCA) according to ISO 14040:2006 and ISO 14044:2006+A1:2018 is one of the most adopted and robust methods to evaluate the environmental performance of products throughout their complete life cycle. This life-cycle based approach avoids the shift of environmental impacts of a life cycle stage to another, allowing to allocate them to the stage in which they originated and to adopt measures that optimize the environmental performance of the product. Moreover, the LCA method is widely implemented in the construction sector to assess whole buildings as well as construction products and materials. LCA is regulated by the European Standards EN 15978:2011, at the building level, and EN 15804:2012+A2:2019, at the level of construction products and materials. In this work, the environmental performance of wooden windows was assessed by implementing the LCA method and adopting primary data. More specifically, the emphasis is given to embedded and operational impacts. Furthermore, correlations are made between these environmental impacts and aspects such as type of wood and window transmittance. In the particular case of the operational impacts, special attention is set on the definition of suitable maintenance scenarios that consider the potential climate influence on the environmental impacts. For this purpose, a literature review was conducted, and expert consultation was carried out. The study underlined the variability of the embedded environmental impacts of wooden windows by considering different wood types and transmittance values. The results also highlighted the need to define appropriate maintenance scenarios for precise assessment results. It was found that both the service life and the window maintenance requirements in terms of treatment and its frequency are highly dependent not only on the wood type and its treatment during the manufacturing process but also on the weather conditions of the place where the window is installed. In particular, it became evident that maintenance-related environmental impacts were the highest for climate regions with the lowest temperatures and the greatest amount of precipitation.

Keywords: embedded impacts, environmental performance, life cycle assessment, LCA, maintenance stage, operational impacts, wooden windows

Procedia PDF Downloads 207

Authors: Bahar Salavati Vie Le Sage, Ismaïl Ben Hariz, Flavien Viguier, Sirine Noura Kahil, Audrey Jacquin, Maxime Convert

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The ballast layer plays a key role in railroad maintenance and the geometry of the track structure. Ballast also holds the track in place as the trains roll over it. Track ballast is packed between the sleepers and on the sides of railway tracks. An imbalance in ballast volume on the tracks can lead to safety issues as well as a quick degradation of the overall quality of the railway segment. If there is a lack of ballast in the track bed during the summer, there is a risk that the rails will expand and buckle slightly due to the high temperatures. Furthermore, the knowledge of the ballast quantities that will be excavated during renewal works is important for efficient ballast management. The volume of excavated ballast per meter of track can be calculated based on excavation depth, excavation width, volume of track skeleton (sleeper and rail) and sleeper spacing. Since 2012, SNCF has been collecting 3D points cloud data covering its entire railway network by using 3D laser scanning technology (LiDAR). This vast amount of data represents a modelization of the entire railway infrastructure, allowing to conduct various simulations for maintenance purposes. This paper aims to present an automated method for ballast volume estimation based on the processing of LiDAR data. The estimation of abnormal volumes in ballast on the tracks is performed by analyzing the cross-section of the track. Further, since the amount of ballast required varies depending on the track configuration, the knowledge of the ballast profile is required. Prior to track rehabilitation, excess ballast is often present in the ballast shoulders. Based on 3D laser scans, a Digital Terrain Model (DTM) was generated and automatic extraction of the ballast profiles from this data is carried out. The surplus in ballast is then estimated by performing a comparison between this ballast profile obtained empirically, and a geometric modelization of the theoretical ballast profile thresholds as dictated by maintenance standards. Ideally, this excess should be removed prior to renewal works and recycled to optimize the output of the ballast renewal machine. Based on these parameters, an application has been developed to allow the automatic measurement of ballast profiles. We evaluated the method on a 108 kilometers segment of railroad LiDAR scans, and the results show that the proposed algorithm detects ballast surplus that amounts to values close to the total quantities of spoil ballast excavated.

Keywords: ballast, railroad, LiDAR , cloud point, track ballast, 3D point

Procedia PDF Downloads 76

Authors: Luthfia A. Eka, Bertri M. Masita, G. Indah Lestari, Rizka. Ryanindya, Anindita D. Nur, Asih. Setiarini

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The preferred habit nowadays is to watch television or listen to the radio rather than reading a newspaper or magazine. The low interest in reading is the reason to the Indonesian government passed a regulation to foster interest in reading early in schoolchildren through literacy programs. Literacy programs are held for the first 10 - 15 minutes before classes begin and children are asked to read books other than textbooks such as storybooks or magazines. In addition, elementary school children have a tendency to buy less healthy snacks around the school and do not know the nutrition fact from the food purchased. Whereas snacks contribute greatly in the fulfillment of energy and nutrients of children every day. The purpose of this study was to increase reading interest as well as knowledge of nutrition and health for elementary school students. This study used quantitative method with experimental study design for four months with twice intervention per week and deepened by qualitative method in the form of interview. The participants were 130 students consisting of 3rd and 4th graders in selected elementary school in Depok City. The Interventions given using KUCERIA (Child Storybook) which were storybooks with pictures consisting of 12 series about nutrition and health given at school literacy hours. There were five questions given by using the crossword method to find out the students' understanding of the story content in each series. To maximize the understanding and absorption of information, two students were asked to retell the story in front of the class and one student to fill the crossword on the board for each series. In addition, interviews were conducted by asking questions about students' interest in reading books. Intervention involved not only students but also teachers and parents in order to optimize students' reading habits. Analysis showed > 80% of student could answer 3 of 5 questions correctly in each series, which showed they had an interest in what they read. Research data on nutrition and health knowledge were analyzed using Wilcoxon and Chi-Square Test to see the relationship. However, only 46% of students completed 12 series and the rest lost to follow up due to school schedule incompatibility with the program. The results showed that there was a significant increase of knowledge (p = 0.000) between before intervention with 66,53 score and after intervention with 81,47 score. Retention of knowledge was conducted one month after the last intervention was administered and the analysis result showed no significant decrease of knowledge (p = 0,000) from 79,17 score to 75,48 score. There is also no relationship between sex and class with knowledge. Hence, an increased interest in reading of elementary school students and nutritional knowledge interventions using KUCERIA was proved successful. These interventions may be replicated in other schools or learning communities.

Keywords: literation, reading interest, nutrition knowledge, school children

Procedia PDF Downloads 129

Authors: Peter. M. Kusen, Georg Wandrey, Christopher Probst, Dietrich Kohlheyer, Jochen Buchs, Jorg Pietruszkau

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Light as a stimulus provides the capability to develop regulation techniques for customizable gene expression. A great advantage is the extremely flexible and accurate dosing that can be performed in a non invasive and sterile manner even for high throughput technologies. Therefore, light regulation in a multiwell microbioreactor system was realized providing the opportunity to control gene expression with outstanding complexity. A light-regulated gene expression system in Saccharomyces cerevisiae was designed applying the strategy of caged compounds. These compounds are photo-labile protected and therefore biologically inactive regulator molecules which can be reactivated by irradiation with certain light conditions. The “caging” of a repressor molecule which is consumed after deprotection was essential to create a flexible expression system. Thereby, gene expression could be temporally repressed by irradiation and subsequent release of the active repressor molecule. Afterwards, the repressor molecule is consumed by the yeast cells leading to reactivation of gene expression. A yeast strain harboring a construct with the corresponding repressible promoter in combination with a fluorescent marker protein was applied in a Photo-BioLector platform which allows individual irradiation as well as online fluorescence and growth detection. This device was used to precisely control the repression duration by adjusting the amount of released repressor via different irradiation times. With the presented screening platform the regulation of complex expression procedures was achieved by combination of several repression/derepression intervals. In particular, a stepwise increase of temporally-constant expression levels was demonstrated which could be used to study concentration dependent effects on cell functions. Also linear expression rates with variable slopes could be shown representing a possible solution for challenging protein productions, whereby excessive production rates lead to misfolding or intoxication. Finally, the very flexible regulation enabled accurate control over the expression induction, although we used a repressible promoter. Summing up, the continuous online regulation of gene expression has the potential to synchronize gene expression levels to optimize metabolic flux, artificial enzyme cascades, growth rates for co cultivations and many other applications addicted to complex expression regulation. The developed light-regulated expression platform represents an innovative screening approach to find optimization potential for production processes.

Keywords: caged-compounds, gene expression regulation, optogenetics, photo-labile protecting group

Procedia PDF Downloads 299

Authors: Chinedu F. Anochie

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The presence of gangue particles in recovered metal concentrates has been a serious challenge to ore dressing engineers. Middlings lower the quality of concentrates, and in most cases, drastically affect the smelter terms, owing to exorbitant amounts paid by Mineral Processing industries as treatment charge. Models which encourage optimization of liberation operations have been utilized in most ore beneficiation industries to reduce the presence of locked particles in valuable concentrates. Moreover, methods such as incorporation of regrind mills, scavenger, rougher and cleaner cells, to the milling and flotation plants has been widely employed to tackle these concerns, and to optimize the grade–recovery relationship of metal concentrates. This work compared the crushing and grinding method of liberation, to the mine to mill route, by evaluating the proportion of middlings present in selectively processed complex Pb-Zn ore samples. To establish the effect of size reduction operations on the percentage of locked particles present in recovered concentrates, two similar samples of complex Pb- Zn ores were processed. Following blasting operation, the first ore sample was ground directly in a ball mill (Mine to Mill Route of Comminution), while the other sample was manually crushed, and subsequently ground in the ball mill (Crushing and Grinding Route of Comminution). The two samples were separately sieved in a mesh to obtain the desired representative particle sizes. An equal amount of each sample that would be processed in the flotation circuit was then obtained with the aid of a weighing balance. These weighed fine particles were simultaneously processed in the flotation circuit using the selective flotation technique. Sodium cyanide, Methyl isobutyl carbinol, Sodium ethyl xanthate, Copper sulphate, Sodium hydroxide, Lime and Isopropyl xanthate, were the reagents used to effect differential flotation of the two ore samples. Analysis and calculations showed that the degree of liberation obtained for the ore sample which went through the conventional crushing and grinding route of comminution, was higher than that of the directly milled run off mine (ROM) ore. Similarly, the proportion of middlings obtained from the separated galena (PbS) and sphalerite (ZnS) concentrates, were lower for the crushed and ground ore sample. A concise data which proved that the mine to mill method of size reduction is not the most ideal technique for the recovery of quality metal concentrates has been established.

Keywords: comminution, degree of liberation, middlings, mine to mill

Procedia PDF Downloads 115

Authors: Jason Gica, Yi-Hsieng Samuel Wu, Deng-Jye Yang, Yi-Chen Chen

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Mycotoxins, harmful secondary metabolites produced by certain fungi species, pose significant risks to animals and humans worldwide. Their stable properties lead to contamination during grain harvesting, transportation, and storage, as well as in processed food products. The prevalence of mycotoxin contamination has attracted significant attention due to its adverse impact on food safety and global trade. The secondary contamination pathway from animal products has been identified as an important route of exposure, posing health risks for livestock and humans consuming contaminated products. Pork, one of the highly consumed meat products in Taiwan according to the National Food Consumption Database, plays a critical role in the nation's diet and economy. Given its substantial consumption, pork processing products are a significant component of the food supply chain and a potential source of mycotoxin contamination. This study is paramount for formulating effective regulations and strategies to mitigate mycotoxin-related risks in the food supply chain. By establishing a reliable analytical method, this research contributes to safeguarding public health and enhancing the quality of pork processing products. The findings will serve as valuable guidance for policymakers, food industries, and consumers to ensure a safer food supply chain in the face of emerging mycotoxin challenges. An innovative and efficient analytical approach is proposed using Ultra-High Performance Liquid Chromatography coupled with Temperature Control Fluorescence Detector Light (UHPLC-TCFLD) to determine multiple mycotoxins in pork meat samples due to its exceptional capacity to detect multiple mycotoxins at the lowest levels of concentration, making it highly sensitive and reliable for comprehensive mycotoxin analysis. Additionally, its ability to simultaneously detect multiple mycotoxins in a single run significantly reduces the time and resources required for analysis, making it a cost-effective solution for monitoring mycotoxin contamination in pork processing products. The research aims to optimize the efficient mycotoxin QuEChERs extraction method and rigorously validate its accuracy and precision. The results will provide crucial insights into mycotoxin levels in pork processing products.

Keywords: multiple-mycotoxin analysis, pork processing products, QuEChERs, UHPLC-TCFLD, validation

Procedia PDF Downloads 34

Authors: Geyang Xia

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In many countries, governments have responded to the growing demand for educational resources through school district systems, and there is substantial evidence that school district systems have been effective in promoting inter-district and inter-school equity in educational resources. However, the scarcity of quality educational resources has brought about varying levels of education among different school districts, making it a common choice for many parents to buy a house in the school district where a quality school is located, and they are even willing to bear huge commuting costs for this purpose. Moreover, this is evidenced by the fact that parents of families in school districts with quality education resources have longer average commute lengths and longer average commute distances than parents in average school districts. This "unequal traveling" under the influence of the school district system is more common in school districts at the primary level of education. This further reinforces the differential hierarchy of educational resources and raises issues of inequitable educational public services, education-led residential segregation, and gentrification of school district housing. Against this background, this paper takes Nanjing, a famous educational city in China, as a case study and selects the school districts where the top 10 public elementary schools are located. The study first identifies the spatio-temporal behavioral trajectory dataset of these high-quality school district households by using spatial vector data, decrypted cell phone signaling data, and census data. Then, by constructing a "house-school-work (HSW)" commuting pattern of the population in the school district where the high-quality educational resources are located, and based on the classification of the HSW commuting pattern of the population, school districts with long employment hours were identified. Ultimately, the mechanisms and patterns inherent in this unequal commuting are analyzed in terms of six aspects, including the centrality of school district location, functional diversity, and accessibility. The results reveal that the "unequal commuting" of Nanjing's high-quality school districts under the influence of the school district system occurs mainly in the peripheral areas of the city, and the schools matched with these high-quality school districts are mostly branches of prestigious schools in the built-up areas of the city's core. At the same time, the centrality of school district location and the diversity of functions are the most important influencing factors of unequal commuting in high-quality school districts. Based on the research results, this paper proposes strategies to optimize the spatial layout of high-quality educational resources and corresponding transportation policy measures.

Keywords: school-district system, high quality school district, commuting pattern, unequal traveling

Procedia PDF Downloads 68

Authors: Bharatkumar Doshi

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Electro-Magnetic Pulse Welding (EMPW) is a solid state welding process carried out at almost room temperature, in which joining is enabled by high impact velocity deformation. In this process, high voltage capacitor’s stored energy is discharged in an EM coil resulting in a damped, sinusoidal current with an amplitude of several hundred kiloamperes. Due to these transient magnetic fields of few tens of Tesla near the coil is generated. As the conductive (tube) part is positioned in this area, an opposing eddy current is induced in this part. Consequently, high Lorentz forces act on the part, leading to acceleration away from the coil. In case of a tube, it gets compressed under forming velocities of more than 300 meters per second. After passing the joining gap it collides with the second metallic joining rod, leading to the formation of a jet under appropriate collision conditions. Due to the prevailing high pressure, metallurgical bonding takes place. A characteristic feature is the wavy interface resulting from the heavy plastic deformations. In the process, the formation of intermetallic compounds which might deteriorate the weld strength can be avoided, even for metals with dissimilar thermal properties. In order to optimize the process parameters like current, voltage, inductance, coil dimensions, workpiece dimensions, air gap, impact velocity, effective plastic strain, shear stress acting in the welding zone/impact zone etc. are very critical and important to establish. These process parameters could be determined by simulation using Finite Element Methods (FEM) in which electromagnetic –structural couple field analysis is performed. The feasibility of welding could thus be investigated by varying the parameters in the simulation using COMSOL. Simulation results shall be applied in performing the preliminary experiments of welding the different alloy steel tubes and/or alloy steel to other materials. The single turn coil (S.S.304) with field shaper (copper) has been designed and manufactured. The preliminary experiments are performed using existing EMPW facility available Institute for Plasma Research, Gandhinagar, India. The experiments are performed at 22kV charged into 64µF capacitor bank and the energy is discharged into single turn EM coil. Welding of axi-symetric components such as aluminum tube and rod has been proven experimentally using EMPW techniques. In this paper EM coil design, manufacturing, Electromagnetic-structural FEM simulation of Magnetic Pulse Welding and preliminary experiment results is reported.

Keywords: COMSOL, EMPW, FEM, Lorentz force

Procedia PDF Downloads 156

Authors: Domenico Panno, Antonino D’amico, Hamed Jafargholi

Abstract:

This paper presents an experimental analysis of the performance of a system for freezing fish products equipped with a modulating vapour injection scroll compressor operating with R448A refrigerant. Freezing is a critical process for the preservation of seafood products, as it influences quality, food safety, and environmental sustainability. The use of a modulating scroll compressor with vapour injection, associated with the R448A refrigerant, is proposed as a solution to optimize the performance of the system, reducing energy consumption and mitigating the environmental impact. The steam injection modulating scroll compressor represents an advanced technology that allows you to adjust the compressor capacity based on the actual cooling needs of the system. Vapour injection allows the optimization of the refrigeration cycle, reducing the evaporation temperature and improving the overall efficiency of the system. The use of R448A refrigerant, with a low global warming potential (GWP), is part of an environmental sustainability perspective, helping to reduce the climate impact of the system. The aim of this research was to evaluate the performance of the system through a series of experiments conducted on a pilot plant for the freezing of fish products. Several operational variables were monitored and recorded, including evaporation temperature, condensation temperature, energy consumption, and freezing time of seafood products. The results of the experimental analysis highlighted the benefits deriving from the use of the modulating vapour injection scroll compressor with the R448A refrigerant. In particular, a significant reduction in energy consumption was recorded compared to conventional systems. The modulating capacity of the compressor made it possible to adapt the cold production to variations in the thermal load, ensuring optimal operation of the system and reducing energy waste. Furthermore, the use of an electronic expansion valve highlighted greater precision in the control of the evaporation temperature, with minimal deviation from the desired set point. This helped ensure better quality of the final product, reducing the risk of damage due to temperature changes and ensuring uniform freezing of the fish products. The freezing time of seafood has been significantly reduced thanks to the configuration of the entire system, allowing for faster production and greater production capacity of the plant. In conclusion, the use of a modulating vapour injection scroll compressor operating with R448A refrigerant has proven effective in improving the performance of a system for freezing fish products. This technology offers an optimal balance between energy efficiency, temperature control, and environmental sustainability, making it an advantageous choice for food industries.

Keywords: freezing, scroll compressor, energy efficiency, vapour injection

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