Search results for: optimal site selection

Authors: Andreea Campu, Ilinica Muresan, Simona Cainap, Simion Astilean, Monica Focsan

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Acute myocardial infarction (AMI) is the most severe cardiovascular disease, which has threatened human lives for decades, thus a continuous interest is directed towards the detection of cardiac biomarkers such as cardiac troponin I (cTnI) in order to predict risk and, implicitly, fulfill the early diagnosis requirements in AMI settings. Microfluidics is a major technology involved in the development of efficient sensing devices with real-time fast responses and on-site applicability. Microfluidic devices have gathered a lot of attention recently due to their advantageous features such as high sensitivity and specificity, miniaturization and portability, ease-of-use, low-cost, facile fabrication, and reduced sample manipulation. The integration of gold nanoparticles into the structure of microfluidic sensors has led to the development of highly effective detection systems, considering the unique properties of the metallic nanostructures, specifically the Localized Surface Plasmon Resonance (LSPR), which makes them highly sensitive to their microenvironment. In this scientific context, herein, we propose the implementation of a novel detection device, which successfully combines the efficiency of gold bipyramids (AuBPs) as signal transducers and thermal generators with the sample-driven advantages of the microfluidic channels into a miniaturized, portable, low-cost, specific, and sensitive test for the dual LSPR-thermographic cTnI detection. Specifically, AuBPs with longitudinal LSPR response at 830 nm were chemically synthesized using the seed-mediated growth approach and characterized in terms of optical and morphological properties. Further, the colloidal AuBPs were deposited onto pre-treated silanized glass substrates thus, a uniform nanoparticle coverage of the substrate was obtained and confirmed by extinction measurements showing a 43 nm blue-shift of the LSPR response as a consequence of the refractive index change. The as-obtained plasmonic substrate was then integrated into a microfluidic “Y”-shaped polydimethylsiloxane (PDMS) channel, fabricated using a Laser Cutter system. Both plasmonic and microfluidic elements were plasma treated in order to achieve a permanent bond. The as-developed microfluidic plasmonic chip was further coupled to an automated syringe pump system. The proposed biosensing protocol implicates the successive injection inside the microfluidic channel as follows: p-aminothiophenol and glutaraldehyde, to achieve a covalent bond between the metallic surface and cTnI antibody, anti-cTnI, as a recognition element, and target cTnI biomarker. The successful functionalization and capture of cTnI was monitored by LSPR detection thus, after each step, a red-shift of the optical response was recorded. Furthermore, as an innovative detection technique, thermal determinations were made after each injection by exposing the microfluidic plasmonic chip to 785 nm laser excitation, considering that the AuBPs exhibit high light-to-heat conversion performances. By the analysis of the thermographic images, thermal curves were obtained, showing a decrease in the thermal efficiency after the anti-cTnI-cTnI reaction was realized. Thus, we developed a microfluidic plasmonic chip able to operate as both LSPR and thermal sensor for the detection of the cardiac troponin I biomarker, leading thus to the progress of diagnostic devices.

Keywords: gold nanobipyramids, microfluidic device, localized surface plasmon resonance detection, thermographic detection

Procedia PDF Downloads 108

Authors: George Charkoftakis, Panagiotis Liosatos, Nicolas-Alexander Tatlas, Dimitrios Goustouridis, Stelios M. Potirakis

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E-maintenance is a relatively new concept, generally referring to maintenance management by monitoring assets over the Internet. One of the key links in the chain of an e-maintenance system is data acquisition and transmission. Specifically for the case of a fleet of heavy-duty vehicles, where the main challenge is the diversity of the vehicles and vehicle-embedded self-diagnostic/reporting technologies, the design of the data acquisition and transmission unit is a demanding task. This clear if one takes into account that a heavy-vehicles fleet assortment may range from vehicles with only a limited number of analog sensors monitored by dashboard light indicators and gauges to vehicles with plethora of sensors monitored by a vehicle computer producing digital reporting. The present work proposes an adaptable internet of things (IoT) sensor node that is capable of addressing this challenge. The proposed sensor node architecture is based on the increasingly popular single-board computer – expansion boards approach. In the proposed solution, the expansion boards undertake the tasks of position identification by means of a global navigation satellite system (GNSS), cellular connectivity by means of 3G/long-term evolution (LTE) modem, connectivity to on-board diagnostics (OBD), and connectivity to analog and digital sensors by means of a novel design of expansion board. Specifically, the later provides eight analog plus three digital sensor channels, as well as one on-board temperature / relative humidity sensor. The specific device offers a number of adaptability features based on appropriate zero-ohm resistor placement and appropriate value selection for limited number of passive components. For example, although in the standard configuration four voltage analog channels with constant voltage sources for the power supply of the corresponding sensors are available, up to two of these voltage channels can be converted to provide power to the connected sensors by means of corresponding constant current source circuits, whereas all parameters of analog sensor power supply and matching circuits are fully configurable offering the advantage of covering a wide variety of industrial sensors. Note that a key feature of the proposed sensor node, ensuring the reliable operation of the connected sensors, is the appropriate supply of external power to the connected sensors and their proper matching to the IoT sensor node. In standard mode, the IoT sensor node communicates to the data center through 3G/LTE, transmitting all digital/digitized sensor data, IoT device identity, and position. Moreover, the proposed IoT sensor node offers WiFi connectivity to mobile devices (smartphones, tablets) equipped with an appropriate application for the manual registration of vehicle- and driver-specific information, and these data are also forwarded to the data center. All control and communication tasks of the IoT sensor node are performed by dedicated firmware. It is programmed with a high-level language (Python) on top of a modern operating system (Linux). Acknowledgment: This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship, and Innovation, under the call RESEARCH—CREATE—INNOVATE (project code: T1EDK- 01359, IntelligentLogger).

Keywords: IoT sensor nodes, e-maintenance, single-board computers, sensor expansion boards, on-board diagnostics

Procedia PDF Downloads 131

Authors: Scott M. Black, Craig Maclean, Pauline Hall Barrientos, Konstantinos Ritos, Asimina Kazakidi

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Aortic aneurysms and dissections are leading causes of death in cardiovascular disease. Both inevitably lead to hemodynamic instability without surgical intervention in the form of vascular stent-graft deployment. An accurate description of the aortic geometry and blood flow in patient-specific cases is vital for treatment planning and long-term success of such grafts, as they must generate physiological branch perfusion and in-stent hemodynamics. The aim of this study was to create patient-specific computational fluid dynamics (CFD) models through a multi-modality, multi-dimensional approach with boundary condition optimization to predict branch flow rates and in-stent hemodynamics in custom stent-graft configurations. Three-dimensional (3D) thoracoabdominal aortae were reconstructed from four-dimensional flow-magnetic resonance imaging (4D Flow-MRI) and computed tomography (CT) medical images. The former employed a novel approach to generate and enhance vessel lumen contrast via through-plane velocity at discrete, user defined cardiac time steps post-hoc. To produce patient-specific boundary conditions (BCs), the aortic geometry was reduced to a one-dimensional (1D) model. Thereafter, a zero-dimensional (0D) 3-Element Windkessel model (3EWM) was coupled to each terminal branch to represent the distal vasculature. In this coupled 0D-1D model, the 3EWM parameters were optimized to yield branch flow waveforms which are representative of the 4D Flow-MRI-derived in-vivo data. Thereafter, a 0D-3D CFD model was created, utilizing the optimized 3EWM BCs and a 4D Flow-MRI-obtained inlet velocity profile. A sensitivity analysis on the effects of stent-graft configuration and BC parameters was then undertaken using multiple stent-graft configurations and a range of distal vasculature conditions. 4D Flow-MRI granted unparalleled visualization of blood flow throughout the cardiac cycle in both the pre- and postsurgical states. Segmentation and reconstruction of healthy and stented regions from retrospective 4D Flow-MRI images also generated 3D models with geometries which were successfully validated against their CT-derived counterparts. 0D-1D coupling efficiently captured branch flow and pressure waveforms, while 0D-3D models also enabled 3D flow visualization and quantification of clinically relevant hemodynamic parameters for in-stent thrombosis and graft limb occlusion. It was apparent that changes in 3EWM BC parameters had a pronounced effect on perfusion distribution and near-wall hemodynamics. Results show that the 3EWM parameters could be iteratively changed to simulate a range of graft limb diameters and distal vasculature conditions for a given stent-graft to determine the optimal configuration prior to surgery. To conclude, this study outlined a methodology to aid in the prediction post-surgical branch perfusion and in-stent hemodynamics in patient specific cases for the implementation of custom stent-grafts.

Keywords: 4D flow-MRI, computational fluid dynamics, vascular stent-grafts, windkessel

Procedia PDF Downloads 153

Authors: Simon J. Wilde, David M. Herold, Michael J. Bryant

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Social media networks have become the hotbed for advertising activities, due mainly to their increasing consumer/user base, and secondly, owing to the ability of marketers to accurately measure ad exposure and consumer-based insights on such networks. More than half of the world’s population (4.8 billion) now uses social media (60%), with 150 million new users having come online within the last 12 months (to June 2022). As the use of social media networks by users grows, key business strategies used for interacting with these potential customers have matured, especially social media advertising. Unlike other traditional media outlets, social media advertising is highly interactive and digital channel-specific. Social media advertisements are clearly targetable, providing marketers with an extremely powerful marketing tool. Yet despite the measurable benefits afforded to businesses engaged in social media advertising, recent controversies (such as the relationship between Facebook and Cambridge Analytica in 2018) have only heightened the role trust and privacy play within these social media networks. The purpose of this exploratory paper is to investigate the extent to which social media users trust social media advertising. Understanding this relationship will fundamentally assist marketers in better understanding social media interactions and their implications for society. Using a web-based quantitative survey instrument, survey participants were recruited via a reputable online panel survey site. Respondents to the survey represented social media users from all states and territories within Australia. Completed responses were received from a total of 258 social media users. Survey respondents represented all core age demographic groupings, including Gen Z/Millennials (18-45 years = 60.5% of respondents) and Gen X/Boomers (46-66+ years = 39.5% of respondents). An adapted ADTRUST scale, using a 20 item 7-point Likert scale, measured trust in social media advertising. The ADTRUST scale has been shown to be a valid measure of trust in advertising within traditional different media, such as broadcast media and print media, and more recently, the Internet (as a broader platform). The adapted scale was validated through exploratory factor analysis (EFA), resulting in a three-factor solution. These three factors were named reliability, usefulness and affect, and the willingness to rely on. Factor scores (weighted measures) were then calculated for these factors. Factor scores are estimates of the scores survey participants would have received on each of the factors had they been measured directly, with the following results recorded (Reliability = 4.68/7; Usefulness and Affect = 4.53/7; and Willingness to Rely On = 3.94/7). Further statistical analysis (independent samples t-test) determined the difference in factor scores between the factors when age (Gen Z/Millennials vs. Gen X/Boomers) was utilised as the independent, categorical variable. The results showed the difference in mean scores across all three factors to be statistically significant (p<0.05) for these two core age groupings: Gen Z/Millennials Reliability = 4.90/7 vs Gen X/Boomers Reliability = 4.34/7; Gen Z/Millennials Usefulness and Affect = 4.85/7 vs Gen X/Boomers Usefulness and Affect = 4.05/7; and Gen Z/Millennials Willingness to Rely On = 4.53/7 vs Gen X/Boomers Willingness to Rely On = 3.03/7. The results clearly indicate that older social media users lack trust in the quality of information conveyed in social media ads, when compared to younger, more social media-savvy consumers. This is especially evident with respect to Factor 3 (Willingness to Rely On), whose underlying variables reflect one’s behavioural intent to act based on the information conveyed in advertising. These findings can be useful to marketers, advertisers, and brand managers in that the results highlight a critical need to design ‘authentic’ advertisements on social media sites to better connect with these older users, in an attempt to foster positive behavioural responses from within this large demographic group – whose engagement with social media sites continues to increase year on year.

Keywords: social media advertising, trust, older consumers, online

Procedia PDF Downloads 62

Authors: Elaine Yee Sing Wong, Jonine Jancey, Andy H. Lee, Anthony P. James

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Singapore has a rapidly aging population, where the majority of older women aged 50 years and above, are physically inactive and have unhealthy dietary habits, placing them at ‘high risk’ of non-communicable diseases. Given the multiplicity of less than optimal dietary habits and high levels of physical inactivity among Singaporean women, it is imperative to develop appropriate lifestyle interventions at recreational centres to enhance both their physical and nutritional knowledge, as well as provide them with the opportunity to develop skills to support behaviour change. To the best of our knowledge, this proposed study is the first physical activity and nutrition cluster randomised controlled trial conducted in Singapore for older women. Findings from this study may provide insights and recommendations for policy makers and key stakeholders to create new healthy living, recreational centres with supportive environments. This 6-month community-based cluster randomised controlled trial will involve the implementation and evaluation of physical activity and nutrition program for community dwelling Singaporean women, who currently attend recreational centres to promote social leisure activities in their local neighbourhood. The intervention will include dietary education and counselling sessions, physical activity classes, and telephone contact by certified fitness instructors and qualified nutritionists. Social Cognitive Theory with Motivational Interviewing will inform the development of strategies to support health behaviour change. Sixty recreational centres located in Singapore will be randomly selected from five major geographical districts and randomly allocated to the intervention (n=30) or control (n=30) cluster. A sample of 600 (intervention n=300; control n=300) women aged 50 years and above will then be recruited from these recreational centres. The control clusters will only undergo pre and post data collection and will not receive the intervention. It is hypothesised that by the end of the intervention, the intervention group participants (n = 300) compared to the control group (n = 300), will show significant improvements in the following variables: lipid profile, body mass index, physical activity and dietary behaviour, anthropometry, mental and physical health. Data collection will be examined and compared via the Statistical Package for the Social Science version 23. Descriptive and summary statistics will be used to quantify participants’ characteristics and outcome variables. Multi-variable mixed regression analyses will be used to confirm the effects of the proposed health intervention, taking into account the repeated measures and the clustering of the observations. The research protocol was approved by the Curtin University Human Research Ethics Committee (approval number: HRE2016-0366). The study has been registered with the Australian and New Zealand Clinical Trial Registry (12617001022358).

Keywords: community based, healthy aging, intervention, nutrition, older women, physical activity

Procedia PDF Downloads 152

Authors: David Oyewumi Oyekunle, David Preston, Florence Ibeh

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The paper provides an overview of the impacts of the human dimension in project management and team management on projects, which is increasingly affecting the performance of organizations. Recognizing its crucial significance, the research focuses on analyzing the psychological and interpersonal dynamics within project teams. This research is highly significant in the dynamic field of project management, as it addresses important gaps and offers vital insights that align with the constantly changing demands of the profession. A case study was conducted at the University of Salford to examine how human activity affects project management and performance. The study employed a mixed methodology to gain a deeper understanding of the real-world experiences of the subjects and project teams. Data analysis procedures to address the research objectives included the deductive approach, which involves testing a clear hypothesis or theory, as well as descriptive analysis and visualization. The survey comprised a sample size of 40 participants out of 110 project management professionals, including staff and final students in the Salford Business School, using a purposeful sampling method. To mitigate bias, the study ensured diversity in the sample by including both staff and final students. A smaller sample size allowed for more in-depth analysis and a focused exploration of the research objective. Conflicts, for example, are intricate occurrences shaped by a multitude of psychological stimuli and social interactions and may have either a deterrent perspective or a positive perspective on project performance and project management productivity. The study identified conflict elements, including culture, environment, personality, attitude, individual project knowledge, team relationships, leadership, and team dynamics among team members, as crucial human activities to minimize conflict. The findings are highly significant in the dynamic field of project management, as they address important gaps and offer vital insights that align with the constantly changing demands of the profession. It provided project professionals with valuable insights that can help them create a collaborative and high-performing project environment. Uncovering human influence on project performance, effective communication, optimal team synergy, and a keen understanding of project scope are necessary for the management of projects to attain exceptional performance and efficiency. For the research to achieve the aims of this study, it was acknowledged that the productive dynamics of teams and strong group cohesiveness are crucial for effectively managing conflicts in a beneficial and forward-thinking manner. Addressing the identified human influence will contribute to a more sustainable project management approach and offer opportunities for exploration and potential contributions to both academia and practical project management.

Keywords: human dimension, project management, team dynamics, conflict resolution

Procedia PDF Downloads 58

Authors: Mark R. Leipnik, Dahlia Durga, Linda Johnson-Bhola

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Kaieteur is the most iconic National Park in the rainforest-clad nation of Guyana in South America. However, the magnificent 226-meter-high waterfall at its center is virtually inaccessible by surface transportation, and the occasional charter flights to the small airstrip in the park are too expensive for many tourists and residents. Thus, the largest waterfall in all of Amazonia, where the Potaro River plunges over a single free drop twice as high as Victoria Falls, remains preserved in splendid isolation inside a 57,000-hectare National Park established by the British in 1929, in the deepest recesses of a remote jungle canyon. Kaieteur Falls are largely unseen firsthand, but images of the falls are depicted on the Guyanese twenty dollar note, in every Guyanese tourist promotion, and on many items in the national capital of Georgetown. Georgetown is only 223-241 kilometers away from the falls. The lack of a single mileage figure demonstrates there is no single overland route. Any journey, except by air, involves changes of vehicles, a ferry ride, and a boat ride up a jungle river. It also entails hiking for many hours to view the falls. Surface access from Georgetown (or any city) is thus a 3-5 day-long adventure; even in the dry season, during the two wet seasons, travel is a particularly sticky proposition. This journey was made overland by the paper's co-author Dahlia Durga. This paper focuses on potential ways to improve overland tourist access to Kaieteur National Park from Georgetown. This is primarily a GIS-based analysis, using multiple criteria to determine the least cost means of creating all-weather road access to the area near the base of the falls while minimizing distance and elevation changes. Critically, it also involves minimizing the number of new bridges required to be built while utilizing the one existing ferry crossings of a major river. Cost estimates are based on data from road and bridge construction engineers operating currently in the interior of Guyana. The paper contains original maps generated with ArcGIS of the potential routes for such an overland connection, including the one deemed optimal. Other factors, such as the impact on endangered species habitats and Indigenous populations, are considered. This proposed infrastructure development is taking place at a time when Guyana is undergoing the largest boom in its history due to revenues from offshore oil and gas development. Thus, better access to the most important tourist attraction in the country is likely to happen eventually in some manner. But the questions of the most environmentally sustainable and least costly alternatives for such access remain. This paper addresses those questions and others related to access to this magnificent natural treasure and the tradeoffs such access will have on the preservation of the currently pristine natural environment of Kaieteur Falls.

Keywords: nature tourism, GIS, Amazonia, national parks

Procedia PDF Downloads 128

Authors: Khachen Kongpakwattana, Nathorn Chaiyakunapruk

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Background: Decision-analytic models for Alzheimer’s disease (AD) have been advanced to discrete-event simulation (DES), in which individual-level modelling of disease progression across continuous severity spectra and incorporation of key parameters such as treatment persistence into the model become feasible. This study aimed to apply the DES to perform a cost-effectiveness analysis of treatment for AD in Thailand. Methods: A dataset of Thai patients with AD, representing unique demographic and clinical characteristics, was bootstrapped to generate a baseline cohort of patients. Each patient was cloned and assigned to donepezil, galantamine, rivastigmine, memantine or no treatment. Throughout the simulation period, the model randomly assigned each patient to discrete events including hospital visits, treatment discontinuation and death. Correlated changes in cognitive and behavioral status over time were developed using patient-level data. Treatment effects were obtained from the most recent network meta-analysis. Treatment persistence, mortality and predictive equations for functional status, costs (Thai baht (THB) in 2017) and quality-adjusted life year (QALY) were derived from country-specific real-world data. The time horizon was 10 years, with a discount rate of 3% per annum. Cost-effectiveness was evaluated based on the willingness-to-pay (WTP) threshold of 160,000 THB/QALY gained (4,994 US$/QALY gained) in Thailand. Results: Under a societal perspective, only was the prescription of donepezil to AD patients with all disease-severity levels found to be cost-effective. Compared to untreated patients, although the patients receiving donepezil incurred a discounted additional costs of 2,161 THB, they experienced a discounted gain in QALY of 0.021, resulting in an incremental cost-effectiveness ratio (ICER) of 138,524 THB/QALY (4,062 US$/QALY). Besides, providing early treatment with donepezil to mild AD patients further reduced the ICER to 61,652 THB/QALY (1,808 US$/QALY). However, the dominance of donepezil appeared to wane when delayed treatment was given to a subgroup of moderate and severe AD patients [ICER: 284,388 THB/QALY (8,340 US$/QALY)]. Introduction of a treatment stopping rule when the Mini-Mental State Exam (MMSE) score goes below 10 to a mild AD cohort did not deteriorate the cost-effectiveness of donepezil at the current treatment persistence level. On the other hand, none of the AD medications was cost-effective when being considered under a healthcare perspective. Conclusions: The DES greatly enhances real-world representativeness of decision-analytic models for AD. Under a societal perspective, treatment with donepezil improves patient’s quality of life and is considered cost-effective when used to treat AD patients with all disease-severity levels in Thailand. The optimal treatment benefits are observed when donepezil is prescribed since the early course of AD. With healthcare budget constraints in Thailand, the implementation of donepezil coverage may be most likely possible when being considered starting with mild AD patients, along with the stopping rule introduced.

Keywords: Alzheimer's disease, cost-effectiveness analysis, discrete event simulation, health technology assessment

Procedia PDF Downloads 104

Authors: Andreas Lind, Aitor Iriondo Pascual, Dan Hogberg, Lars Hanson

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Factory setup lifecycles are most often described and prepared in CAD environments; the preparation is based on experience and inputs from several cross-disciplinary processes. Early in the factory setup preparation, a so-called block layout is created. The intention is to describe a high-level view of the intended factory setup and to claim area reservations and allocations. Factory areas are then blocked, i.e., targeted to be used for specific intended resources and processes, later redefined with detailed factory setup layouts. Each detailed layout is based on the block layout and inputs from cross-disciplinary preparation processes, such as manufacturing sequence, productivity, workers’ workplace requirements, and resource setup preparation. However, this activity is often not carried out with all variables considered simultaneously, which might entail a risk of sub-optimizing the detailed layout based on manual decisions. Therefore, this work aims to realize a digital method for assembly manufacturing layout planning where productivity, area utilization, and ergonomics can be considered simultaneously in a cross-disciplinary manner. The purpose of the digital method is to support engineers in finding optimized designs of detailed layouts for assembly manufacturing factories, thereby facilitating better decisions regarding setups of future factories. Input datasets are company-specific descriptions of required dimensions for specific area reservations, such as defined dimensions of a worker’s workplace, material façades, aisles, and the sequence to realize the product assembly manufacturing process. To test and iteratively develop the digital method, a demonstrator has been developed with an adaptation of existing software that simulates and proposes optimized designs of detailed layouts. Since the method is to consider productivity, ergonomics, area utilization, and constraints from the automatically generated block layout, a multi-objective optimization approach is utilized. In the demonstrator, the input data are sent to the simulation software industrial path solutions (IPS). Based on the input and Lua scripts, the IPS software generates a block layout in compliance with the company’s defined dimensions of area reservations. Communication is then established between the IPS and the software EPP (Ergonomics in Productivity Platform), including intended resource descriptions, assembly manufacturing process, and manikin (digital human) resources. Using multi-objective optimization approaches, the EPP software then calculates layout proposals that are sent iteratively and simulated and rendered in IPS, following the rules and regulations defined in the block layout as well as productivity and ergonomics constraints and objectives. The software demonstrator is promising. The software can handle several parameters to optimize the detailed layout simultaneously and can put forward several proposals. It can optimize multiple parameters or weight the parameters to fine-tune the optimal result of the detailed layout. The intention of the demonstrator is to make the preparation between cross-disciplinary silos transparent and achieve a common preparation of the assembly manufacturing factory setup, thereby facilitating better decisions.

Keywords: factory setup, multi-objective, optimization, simulation

Procedia PDF Downloads 127

Authors: Maryam Fallahpoor, Biswajeet Pradhan

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

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

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Authors: K. Kamal

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Structural sandwich panels with core of Advanced Composites Laminates l Honeycombs / PU-foams are used in aerospace applications and are also fabricated for use now in some civil engineering applications. An all Advanced Composites Foot Over Bridge (FOB) system, designed and developed for pedestrian traffic is one such application earlier, may be cited as an example here. During development stage of this FoB, a profile of its decks was then spurred as a single corrugate sheet core sandwiched between two Glass Fibre Reinforced Plastics(GFRP) flat laminates. Once successfully fabricated and used, these decks did prove suitable also to form other structure on assembly, such as, erecting temporary shelters. Such corrugated sheet core profile sandwiched panels were then also tried using the construction materials but any conventional method of construction only posed certain difficulties in achieving the required core profile monolithically within the sandwiched slabs and hence it was then abended. Such monolithic construction was, however, subsequently eased out on demonstration by dispensing building materials mix through a suitably designed multi-dispenser system attached to a 3D Printer. This study conducted at lab level was thus reported earlier and it did include the fabrication of a 3D printer in-house first as ‘3DcMP’ as well as on its functional operation, some required sandwich core profiles also been 3D-printed out producing panels hardware. Once a number of these sandwich panels in single corrugated sheet core monolithically printed out, panels were subjected to load test in an experimental set up as also their structural behavior was studied analytically, and subsequently, these results were correlated as reported in the literature. In achieving the required more depths and also to exhibit further the stronger and creating sandwiched decks of better structural and mechanical behavior, further more complex core configuration such as stack corrugate sheets core with a flat mid plane was felt to be the better sandwiched core. Such profile remained as an outcome that turns out merely on stacking of two separately printed out monolithic units of single corrugated sheet core developed earlier as above and bonded them together initially, maintaining a different orientation. For any required sequential understanding of the structural behavior of any such complex profile core sandwiched decks with special emphasis to study of the effect in the variation of corrugation orientation in each distinct tire in this core, it obviously calls for an analytical study first. The rectangular,simply supported decks have therefore been considered for analysis adopting the ‘Advanced Composite Technology(ACT), some numerical results along with some fruitful findings were obtained and these are all presented here in this paper. From this numerical result, it has been observed that a mid flat layer which eventually get created monolethically itself, in addition to eliminating the bonding process in development, has been found to offer more effective bending resistance by such decks subjected to UDL over them. This is understood to have resulted here since the existence of a required shear resistance layer at the mid of the core in this profile, unlike other bending elements. As an addendum to all such efforts made as covered above and was published earlier, this unique stack corrugate sheet core profile sandwiched structural decks, monolithically construction with ease at the site itself, has been printed out from a 3D Printer. On employing 3DcMP and using some innovative building construction materials, holds the future promises of such research & development works since all those several aspects of a 3D printing in construction are now included such as reduction in the required construction time, offering cost effective solutions with freedom in design of any such complex shapes thus can widely now be realized by the modern construction industry.

Keywords: advance composite technology(ACT), corrugated laminates, 3DcMP, foot over bridge (FOB), sandwiched deck units

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Authors: Saule Mussabekova

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A number of chemical elements widely presented in the nature is seldom met in people and vice versa. This is a peculiarity of accumulation of elements in the body, and their selective use regardless of widely changed parameters of external environment. Microelemental identification of human hair and particularly dead body is a new step in the development of modern forensic medicine which needs reliable criteria while identifying the person. In the condition of technology-related pressing of large industrial cities for many years and specific for each region multiple-factor toxic effect from many industrial enterprises it’s important to assess actuality and the role of researches of human hair while assessing degree of deposition with specific pollution. Hair is highly sensitive biological indicator and allows to assess ecological situation, to perform regionalism of large territories of geological and chemical methods. Besides, monitoring of concentrations of chemical elements in the regions of Kazakhstan gives opportunity to use these data while performing forensic medical identification of dead bodies of unknown persons. Methods based on identification of chemical composition of hair with further computer processing allowed to compare received data with average values for the sex, age, and to reveal causally significant deviations. It gives an opportunity preliminary to suppose the region of residence of the person, having concentrated actions of policy for search of people who are unaccounted for. It also allows to perform purposeful legal actions for its further identification having created more optimal and strictly individual scheme of personal identity. Hair is the most suitable material for forensic researches as it has such advances as long term storage properties with no time limitations and specific equipment. Besides, quantitative analysis of micro elements is well correlated with level of pollution of the environment, reflects professional diseases and with pinpoint accuracy helps not only to diagnose region of temporary residence of the person but to establish regions of his migration as well. Peculiarities of elemental composition of human hair have been established regardless of age and sex of persons residing on definite territories of Kazakhstan. Data regarding average content of 29 chemical elements in hair of population in different regions of Kazakhstan have been systemized. Coefficients of concentration of studies elements in hair relative to average values around the region have been calculated for each region. Groups of regions with specific spectrum of elements have been emphasized; these elements are accumulated in hair in quantities exceeding average indexes. Our results have showed significant differences in concentrations of chemical elements for studies groups and showed that population of Kazakhstan is exposed to different toxic substances. It depends on emissions to atmosphere from industrial enterprises dominating in each separate region. Performed researches have showed that obtained elemental composition of human hair residing in different regions of Kazakhstan reflects technogenic spectrum of elements.

Keywords: analysis of elemental composition of hair, forensic medical research of hair, identification of unknown dead bodies, microelements

Procedia PDF Downloads 125

Authors: Pradipta Chandra, Titas Bhattacharjee, Bhaskar Bhowmick

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The foundation of economy in India is primarily based on agriculture while this is the most neglected in the rural setting. More significantly, household women take part in agriculture with higher involvement. However, because of lower education of women they have limited access towards financial decisions, land ownership and technology but they have vital role towards the individual family level. There are limited studies on the institution-wise training barriers with the focus of gender disparity. The main purpose of this paper is to find out the factors of institution-wise training (non-formal education) barriers in technology transfer with the focus of participation of rural women in agriculture. For this study primary and secondary data were collected in the line of qualitative and quantitative approach. Qualitative data were collected by several field visits in the adjacent areas of Seva-Bharati, Seva Bharati Krishi Vigyan Kendra through semi-structured questionnaires. In the next level detailed field surveys were conducted with close-ended questionnaires scored on the seven-point Likert scale. Sample size was considered as 162. During the data collection the focus was to include women although some biasness from the end of respondents and interviewer might exist due to dissimilarity in observation, views etc. In addition to that the heterogeneity of sample is not very high although female participation is more than fifty percent. Data were analyzed using Exploratory Factor Analysis (EFA) technique with the outcome of three significant factors of training barriers in technology adoption by farmers: (a) Failure of technology transfer training (TTT) comprehension interprets that the technology takers, i.e., farmers can’t understand the technology either language barrier or way of demonstration exhibited by the experts/ trainers. (b) Failure of TTT customization, articulates that the training for individual farmer, gender crop or season-wise is not tailored. (c) Failure of TTT generalization conveys that absence of common training methods for individual trainers for specific crops is more prominent at the community level. The central finding is that the technology transfer training method can’t fulfill the need of the farmers under an economically challenged area. The impact of such study is very high in the area of dry lateritic and resource crunch area of Jangalmahal under Paschim Medinipur district, West Bengal and areas with similar socio-economy. Towards the policy level decision this research may help in framing digital agriculture for implementation of the appropriate information technology for the farming community, effective and timely investment by the government with the selection of beneficiary, formation of farmers club/ farm science club etc. The most important research implication of this study lies upon the contribution towards the knowledge diffusion mechanism of the agricultural sector in India. Farmers may overcome the barriers to achieve higher productivity through adoption of modern farm practices. Corporates will be interested in agro-sector through investment under corporate social responsibility (CSR). The research will help in framing public or industry policy and land use pattern. Consequently, a huge mass of rural farm-women will be empowered and farmer community will be benefitted.

Keywords: dry lateritic zone, institutional barriers, technology transfer in India, farm-women participation

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Authors: Jo Mitchell, Daniel Johnson

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MindMax is a digital community and learning platform built to maximise the wellbeing and resilience of AFL Players and Australian men. The MindMax application engages men, via their existing connection with sport and video games, in a range of wellbeing ideas, stories and actions, because we believe fit minds, kick goals. MindMax is an AFL Players Association led project, supported by a Movember Foundation grant, to improve the mental health of Australian males aged between 16-35 years. The key engagement and delivery strategy for the project was digital technology, sport (AFL) and video games, underpinned by evidenced based wellbeing science. The project commenced April 2015, and the expected completion date is March 2017. This paper describes the conceptual model underpinning product development, including progress, key learnings and challenges, as well as the research agenda. Evaluation of the MindMax project is a multi-pronged approach of qualitative and quantitative methods, including participatory design workshops, online reference groups, longitudinal survey methods, a naturalistic efficacy trial and evaluation of the social and economic return on investment. MindMax is focused on the wellness pathway and maximising our mind's capacity for fitness by sharing and promoting evidence-based actions that support this. A range of these ideas (from ACT, mindfulness and positive psychology) are already being implemented in AFL programs and services, mostly in face-to-face formats, with strong engagement by players. Player's experience features strongly as part of the product content. Wellbeing science is a discipline of psychology that explores what helps individuals and communities to flourish in life. Rather than ask questions about illness and poor functioning, wellbeing scientists and practitioners ask questions about wellness and optimal functioning. While illness and wellness are related, they operate as separate constructs and as such can be influenced through different pathways. The essential idea was to take the evidence-based wellbeing science around building psychological fitness to the places and spaces that men already frequent, namely sport and video games. There are 800 current senior AFL players, 5000+ past players, and 11 million boys and men that are interested in the lives of AFL Players; what they think and do to be their best both on and off field. AFL Players are also keen video gamers – using games as one way to de-stress, connect and build wellbeing. There are 9.5 million active gamers in Australia with 93% of households having a device for playing games. Video games in MindMax will be used as an engagement and learning tool. Gamers (including AFL players) can also share their personal experience of how games help build their mental fitness. Currently available games (i.e., we are not in the game creation business) will also be used to motivate and connect MindMax participants. The MindMax model is built with replication by other sport codes (e.g., Cricket) in mind. It is intended to not only support our current crop of athletes but also the community that surrounds them, so they can maximise their capacity for health and wellbeing.

Keywords: Australian football league, digital application, positive psychology, wellbeing

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Authors: Alaa Fezai, Anuj Sharma, Wolfgang Mueller-Hirsch, André Zimmermann

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Viscoelastic materials have been widely used in the automotive industry over the last few decades with different functionalities. Besides their main application as a simple and efficient surface damping treatment, they may ensure optimal operating conditions for on-board electronics as thermal interface or sealing layers. The dynamic behavior of viscoelastic materials is generally dependent on many environmental factors, the most important being temperature and strain rate or frequency. Prior to the reliability analysis of systems including viscoelastic layers, it is, therefore, crucial to accurately predict the dynamic and lifetime behavior of these materials. This includes the identification of the dynamic material parameters under critical temperature and frequency conditions along with a precise damage localization and identification methodology. The goal of this work is twofold. The first part aims at applying an inverse viscoelastic material-characterization approach for a wide frequency range and under different temperature conditions. For this sake, dynamic measurements are carried on a single lap joint specimen using an electrodynamic shaker and an environmental chamber. The specimen consists of aluminum beams assembled to adapter plates through a viscoelastic adhesive layer. The experimental setup is reproduced in finite element (FE) simulations, and frequency response functions (FRF) are calculated. The parameters of both the generalized Maxwell model and the fractional derivatives model are identified through an optimization algorithm minimizing the difference between the simulated and the measured FRFs. The second goal of the current work is to guarantee an on-line detection of the damage, i.e., delamination in the viscoelastic bonding of the described specimen during frequency monitored end-of-life testing. For this purpose, an inverse technique, which determines the damage location and size based on the modal frequency shift and on the change of the mode shapes, is presented. This includes a preliminary FE model-based study correlating the delamination location and size to the change in the modal parameters and a subsequent experimental validation achieved through dynamic measurements of specimen with different, pre-generated crack scenarios and comparing it to the virgin specimen. The main advantage of the inverse characterization approach presented in the first part resides in the ability of adequately identifying the material damping and stiffness behavior of soft viscoelastic materials over a wide frequency range and under critical temperature conditions. Classic forward characterization techniques such as dynamic mechanical analysis are usually linked to limitations under critical temperature and frequency conditions due to the material behavior of soft viscoelastic materials. Furthermore, the inverse damage detection described in the second part guarantees an accurate prediction of not only the damage size but also its location using a simple test setup and outlines; therefore, the significance of inverse numerical-experimental approaches in predicting the dynamic behavior of soft bonding layers applied in automotive electronics.

Keywords: damage detection, dynamic characterization, inverse approaches, vibration testing, viscoelastic layers

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Authors: Federica Verna, Alessandra Pautasso, Maria Caramelli, Cristiana Maurella, Walter Mignone, Cristina Casalone

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Mosquito-Borne Diseases (MBDs) are dangerously increasing in prevalence, geographical distribution and severity, representing an emerging threat for both humans and animals. Interaction between multiple disciplines is needed for an effective early warning, surveillance and control of MBDs, according to the One Health concept. This work reports the integrated surveillance system enforced by IZSPLV in Piedmont, Liguria and Valle d’Aosta regions (Northwestern Italy) in order to control MDBs spread. Veterinary services and local human health authority are involved in an information network, to connect the surveillance of human clinical cases with entomological surveillance and veterinary monitoring in order to implement control measures in case of outbreak. A systematic entomological surveillance is carried out during the vector season using mosquitoes traps located in sites selected according to risk factors. Collected mosquitoes are counted, identified to species level by morphological standard classification keys and pooled by collection site, date and species with a maximum of 100 individuals. Pools are analyzed, after RNA extraction, by Real Time RT-PCR distinctive for West Nile Virus (WNV) Lineage 1 and Lineage 2, Real Time RT-PCR USUTU virus (USUV) and a traditional flavivirus End-point RT-PCR. Positive pools are sequenced and the related sequences employed to perform a basic local alignment search tool (BLAST) in the GenBank library. Positive samples are sent to the National Reference Centre for Animal Exotic Diseases (CESME, Teramo) for confirmation. With particular reference to WNV, after the confirmation, as provided by national legislation, control measures involving both local veterinary and human health services are activated: equine sera are randomly sampled within a 4 km radius from the positive collection sites and tested with ELISA kit and WNV NAT screening of blood donors is introduced. This surveillance network allowed to detect since 2011 USUV circulation in this area of Italy. WNV was detected in Piedmont and Liguria for the first time in 2014 in mosquitoes. During the 2015 vector season, we observed the expansion of its activity in Piedmont. The virus was detected in almost all Provinces both in mosquitoes (6 pools) and animals (19 equine sera, 4 birds). No blood bag tested resulted infected. The first neuroinvasive human case occurred too. Competent authorities should be aware of a potentially increased risk of MBDs activity during the 2016 vector season. This work shows that this surveillance network allowed to early detect the presence of MBDs in humans and animals, and provided useful information to public authorities, in order to apply control measures. Finally, an additional value of our diagnostic protocol is the ability to detect all viruses belonging to the Flaviviridae family, considering the emergence caused by other Flaviviruses in humans such as the recent Zika virus infection in South America. Italy has climatic and environmental features conducive to Zika virus transmission, the competent vector and many travellers from Brazil reported every year.

Keywords: integrated surveillance, mosquito borne disease, West Nile virus, Zika virus

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Authors: Sofia N. Gonçalves, Duarte M. S. Albuquerque, José C. F. Pereira

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The energy transition is spurred by structural changes in energy demand, supply, and prices. Microwave technology was first proposed as a faster alternative for cooking food. It was found that food heated instantly when interacting with high-frequency electromagnetic waves. The dielectric properties account for a material’s ability to absorb electromagnetic energy and dissipate this energy in the form of heat. Many energy-intense industries could benefit from electromagnetic heating since many of the raw materials are dielectric at high temperatures. Limestone sedimentary rock is a dielectric material intensively used in the cement industry to produce unslaked lime. A numerical 3D model was implemented in COMSOL Multiphysics to study the limestone continuous processing under microwave heating. The model solves the two-way coupling between the Energy equation and Maxwell’s equations as well as the coupling between heat transfer and chemical interfaces. Complementary, a controller was implemented to optimize the overall heating efficiency and control the numerical model stability. This was done by continuously matching the cavity impedance and predicting the required energy for the system, avoiding energy inefficiencies. This controller was developed in MATLAB and successfully fulfilled all these goals. The limestone load influence on thermal decomposition and overall process efficiency was the main object of this study. The procedure considered the Verification and Validation of the chemical kinetics model separately from the coupled model. The chemical model was found to correctly describe the chosen kinetic equation, and the coupled model successfully solved the equations describing the numerical model. The interaction between flow of material and electric field Poynting vector revealed to influence limestone decomposition, as a result from the low dielectric properties of limestone. The numerical model considered this effect and took advantage from this interaction. The model was demonstrated to be highly unstable when solving non-linear temperature distributions. Limestone has a dielectric loss response that increases with temperature and has low thermal conductivity. For this reason, limestone is prone to produce thermal runaway under electromagnetic heating, as well as numerical model instabilities. Five different scenarios were tested by considering a material fill ratio of 30%, 50%, 65%, 80%, and 100%. Simulating the tube rotation for mixing enhancement was proven to be beneficial and crucial for all loads considered. When uniform temperature distribution is accomplished, the electromagnetic field and material interaction is facilitated. The results pointed out the inefficient development of the electric field within the bed for 30% fill ratio. The thermal efficiency showed the propensity to stabilize around 90%for loads higher than 50%. The process accomplished a maximum microwave efficiency of 75% for the 80% fill ratio, sustaining that the tube has an optimal fill of material. Electric field peak detachment was observed for the case with 100% fill ratio, justifying the lower efficiencies compared to 80%. Microwave technology has been demonstrated to be an important ally for the decarbonization of the cement industry.

Keywords: CFD numerical simulations, efficiency optimization, electromagnetic heating, impedance matching, limestone continuous processing

Procedia PDF Downloads 147

Authors: Laurence Weinberg, Dominic Walpole, Dong-Kyu Lee, Michael D’Silva, Jian W. Chan, Lachlan F. Miles, Bradley Carp, Adam Wells, Tuck S. Ngun, Siven Seevanayagam, George Matalanis, Ziauddin Ansari, Rinaldo Bellomo, Michael Yii

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Background: There have been multiple recent advancements in the selection, optimization and management of cardiac surgical patients. However, there is limited data regarding the outcomes of nonagenarians undergoing cardiac surgery, despite this vulnerable cohort increasingly receiving these interventions. This study describes the patient characteristics, management and outcomes of a group of nonagenarians undergoing cardiac surgery in the context of contemporary peri-operative care. Methods: A retrospective observational study was conducted of patients 90 to 99 years of age (i.e., nonagenarians) who had undergone cardiac surgery requiring a classic median sternotomy (i.e., open-heart surgery). All operative indications were included. Patients who underwent minimally invasive surgery, transcatheter aortic valve implantation and thoracic aorta surgery were excluded. Data were collected from four hospitals in Victoria, Australia, over an 8-year period (January 2012 – December 2019). The primary objective was to assess six-month mortality in nonagenarians undergoing open-heart surgery and to evaluate the incidence and severity of postoperative complications using the Clavien-Dindo classification system. The secondary objective was to provide a detailed description of the characteristics and peri-operative management of this group. Results: A total of 12,358 adult patients underwent cardiac surgery at the study centers during the observation period, of whom 18 nonagenarians (0.15%) fulfilled the inclusion criteria. The median (IQR) [min-max] age was 91 years (90.0:91.8) [90-94] and 14 patients (78%) were men. Cardiovascular comorbidities, polypharmacy and frailty, were common. The median (IQR) predicted in-hospital mortality by EuroSCORE II was 6.1% (4.1-14.5). All patients were optimized preoperatively by a multidisciplinary team of surgeons, cardiologists, geriatricians and anesthetists. All index surgeries were performed on cardiopulmonary bypass. Isolated coronary artery bypass grafting (CABG) and CABG with aortic valve replacement were the most common surgeries being performed in four and five patients, respectively. Half the study group underwent surgery involving two or more major procedures (e.g. CABG and valve replacement). Surgery was undertaken emergently in 44% of patients. All patients except one experienced at least one postoperative complication. The most common complications were acute kidney injury (72%), new atrial fibrillation (44%) and delirium (39%). The highest Clavien-Dindo complication grade was IIIb occurring once each in three patients. Clavien-Dindo grade IIIa complications occurred in only one patient. The median (IQR) postoperative length of stay was 11.6 days (9.8:17.6). One patient was discharged home and all others to an inpatient rehabilitation facility. Three patients had an unplanned readmission within 30 days of discharge. All patients had follow-up to at least six months after surgery and mortality over this period was zero. The median (IQR) duration of follow-up was 11.3 months (6.0:26.4) and there were no cases of mortality observed within the available follow-up records. Conclusion: In this group of nonagenarians undergoing cardiac surgery, postoperative six-month mortality was zero. Complications were common but generally of low severity. These findings support carefully selected nonagenarian patients being offered cardiac surgery in the context of contemporary, multidisciplinary perioperative care. Further, studies are needed to assess longer-term mortality and functional and quality of life outcomes in this vulnerable surgical cohort.

Keywords: cardiac surgery, mortality, nonagenarians, postoperative complications

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Authors: Nursuhaili Najwa Masrol, Nur Hafizah Mohammed, Nur Nadhirah Rusyda Rosnan, Vijaya Subramaniam, Sim Choon Cheak

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Replanting in oil palm cultivation is vital to enable the introduction of planting materials and provides an opportunity to improve the road, drainage, terrace design, and planting density. Oil palm replanting is fundamentally necessary every 25 years. The adoption of the digital replanting blueprint is imperative as it can assist the Malaysia Oil Palm industry in addressing challenges such as labour shortages and limited expertise related to replanting tasks. Effective replanting planning should commence at least 6 months prior to the actual replanting process. Therefore, this study will help to plan and design the replanting blueprint with high-precision translation on the ground. With the advancement of geospatial technology, it is now feasible to engage in thoroughly researched planning, which can help maximize the potential yield. A blueprint designed before replanting is to enhance management’s ability to optimize the planting program, address manpower issues, or even increase productivity. In terrace planting blueprints, geographic tools have been utilized to design the roads, drainages, terraces, and planting points based on the ARM standards. These designs are mapped with location information and undergo statistical analysis. The geospatial approach is essential in precision agriculture and ensuring an accurate translation of design to the ground by implementing high-accuracy technologies. In this study, geospatial and remote sensing technologies played a vital role. LiDAR data was employed to determine the Digital Elevation Model (DEM), enabling the precise selection of terraces, while ortho imagery was used for validation purposes. Throughout the designing process, Geographical Information System (GIS) tools were extensively utilized. To assess the design’s reliability on the ground compared with the current conventional method, high-precision GPS instruments like EOS Arrow Gold and HIPER VR GNSS were used, with both offering accuracy levels between 0.3 cm and 0.5cm. Nearest Distance Analysis was generated to compare the design with actual planting on the ground. The analysis revealed that it could not be applied to the roads due to discrepancies between actual roads and the blueprint design, which resulted in minimal variance. In contrast, the terraces closely adhered to the GPS markings, with the most variance distance being less than 0.5 meters compared to actual terraces constructed. Considering the required slope degrees for terrace planting, which must be greater than 6 degrees, the study found that approximately 65% of the terracing was constructed at a 12-degree slope, while over 50% of the terracing was constructed at slopes exceeding the minimum degrees. Utilizing blueprint replanting promising strategies for optimizing land utilization in agriculture. This approach harnesses technology and meticulous planning to yield advantages, including increased efficiency, enhanced sustainability, and cost reduction. From this study, practical implementation of this technique can lead to tangible and significant improvements in agricultural sectors. In boosting further efficiencies, future initiatives will require more sophisticated techniques and the incorporation of precision GPS devices for upcoming blueprint replanting projects besides strategic progression aims to guarantee the precision of both blueprint design stages and its subsequent implementation on the field. Looking ahead, automating digital blueprints are necessary to reduce time, workforce, and costs in commercial production.

Keywords: replanting, geospatial, precision agriculture, blueprint

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Authors: Evelyn Castle, Adam Thompson

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Background: In 2013, the Kano State Primary Health Care Management Board redesigned its Routine immunization supply chain from diffused pull to direct delivery push. It addressed issues around stockouts and reduced time spent by health facility staff collecting, and reporting on vaccine usage. The health care board sought the help of a 3PL for twice-monthly deliveries from its cold store to 484 facilities across 44 local governments. eHA’s Health Delivery Systems group formed a 3PL to serve 326 of these new facilities in partnership with the State. We focused on designing and implementing a technology system throughout. Basic methodologies: GIS Mapping: - Planning the delivery of vaccines to hundreds of health facilities requires detailed route planning for delivery vehicles. Mapping the road networks across Kano and Bauchi with a custom routing tool provided information for the optimization of deliveries. Reducing the number of kilometers driven each round by 20%, - reducing cost and delivery time. Direct Delivery Information System: - Vaccine Direct Deliveries are facilitated through pre-round planning (driven by health facility database, extensive GIS, and inventory workflow rules), manager and driver control panel customizing delivery routines and reporting, progress dashboard, schedules/routes, packing lists, delivery reports, and driver data collection applications. Move: Last Mile Logistics Management System: - MOVE has improved vaccine supply information management to be timely, accurate and actionable. Provides stock management workflow support, alerts management for cold chain exceptions/stock outs, and on-device analytics for health and supply chain staff. Software was built to be offline-first with user-validated interface and experience. Deployed to hundreds of vaccine storage site the improved information tools helps facilitate the process of system redesign and change management. Findings: - Stock-outs reduced from 90% to 33% - Redesigned current health systems and managing vaccine supply for 68% of Kano’s wards. - Near real time reporting and data availability to track stock. - Paperwork burdens of health staff have been dramatically reduced. - Medicine available when the community needs it. - Consistent vaccination dates for children under one to prevent polio, yellow fever, tetanus. - Higher immunization rates = Lower infection rates. - Hundreds of millions of Naira worth of vaccines successfully transported. - Fortnightly service to 326 facilities in 326 wards across 30 Local Government areas. - 6,031 cumulative deliveries. - Over 3.44 million doses transported. - Minimum travel distance covered in a round of delivery is 2000 kms & maximum of 6297 kms. - 153,409 kms travelled by 6 drivers. - 500 facilities in 326 wards. - Data captured and synchronized for the first time. - Data driven decision making now possible. Conclusion: eHA’s Vaccine Direct delivery has met challenges in Kano and Bauchi State and provided a reliable delivery service of vaccinations that ensure t health facilities can run vaccination clinics for children under one. eHA uses innovative technology that delivers vaccines from Northern Nigerian zonal stores straight to healthcare facilities. Helped healthcare workers spend less time managing supplies and more time delivering care, and will be rolled out nationally across Nigeria.

Keywords: direct delivery information system, health delivery system, GIS mapping, Northern Nigeria, vaccines

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Authors: Amine Ganibardi, Cherif Arab Ali

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This paper addresses the data cleaning issue as a part of web usage data preprocessing within the scope of Web Usage Mining. Weblog data recorded by web servers within log files reflect usage activity, i.e., End-users’ clicks and underlying user-agents’ hits. As Web Usage Mining is interested in End-users’ behavior, user-agents’ hits are referred to as noise to be cleaned-off before mining. Filtering hits from clicks is not trivial for two reasons, i.e., a server records requests interlaced in sequential order regardless of their source or type, website resources may be set up as requestable interchangeably by end-users and user-agents. The current methods are content-centric based on filtering heuristics of relevant/irrelevant items in terms of some cleaning attributes, i.e., website’s resources filetype extensions, website’s resources pointed by hyperlinks/URIs, http methods, user-agents, etc. These methods need exhaustive extra-weblog data and prior knowledge on the relevant and/or irrelevant items to be assumed as clicks or hits within the filtering heuristics. Such methods are not appropriate for dynamic/responsive Web for three reasons, i.e., resources may be set up to as clickable by end-users regardless of their type, website’s resources are indexed by frame names without filetype extensions, web contents are generated and cancelled differently from an end-user to another. In order to overcome these constraints, a clustering-based cleaning method centered on the logging structure is proposed. This method focuses on the statistical properties of the logging structure at the requested and referring resources attributes levels. It is insensitive to logging content and does not need extra-weblog data. The used statistical property takes on the structure of the generated logging feature by webpage requests in terms of clicks and hits. Since a webpage consists of its single URI and several components, these feature results in a single click to multiple hits ratio in terms of the requested and referring resources. Thus, the clustering-based method is meant to identify two clusters based on the application of the appropriate distance to the frequency matrix of the requested and referring resources levels. As the ratio clicks to hits is single to multiple, the clicks’ cluster is the smallest one in requests number. Hierarchical Agglomerative Clustering based on a pairwise distance (Gower) and average linkage has been applied to four logfiles of dynamic/responsive websites whose click to hits ratio range from 1/2 to 1/15. The optimal clustering set on the basis of average linkage and maximum inter-cluster inertia results always in two clusters. The evaluation of the smallest cluster referred to as clicks cluster under the terms of confusion matrix indicators results in 97% of true positive rate. The content-centric cleaning methods, i.e., conventional and advanced cleaning, resulted in a lower rate 91%. Thus, the proposed clustering-based cleaning outperforms the content-centric methods within dynamic and responsive web design without the need of any extra-weblog. Such an improvement in cleaning quality is likely to refine dependent analysis.

Keywords: clustering approach, data cleaning, data preprocessing, weblog data, web usage data

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Authors: Milica Carević, Katarina Banjanac, Marija ĆOrović, Ana Milivojević, Nevena Prlainović, Aleksandar Marinković, Dejan Bezbradica

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Nowadays, considering the growing awareness of functional food beneficial effects on human health, due attention is dedicated to the research in the field of obtaining new prominent products exhibiting improved physiological and physicochemical characteristics. Therefore, different approaches to valuable bioactive compounds synthesis have been proposed. β-Galactosidase, for example, although mainly utilized as hydrolytic enzyme, proved to be a promising tool for these purposes. Namely, under the particular conditions, such as high lactose concentration, elevated temperatures and low water activities, reaction of galactose moiety transfer to free hydroxyl group of the alternative acceptor (e.g. different sugars, alcohols or aromatic compounds) can generate a wide range of potentially interesting products. Up to now, galacto-oligosaccharides and lactulose have attracted the most attention due to their inherent prebiotic properties. The goal of this study was to obtain a novel product sorbitol galactoside, using the similar reaction mechanism, namely transgalactosylation reaction catalyzed by β-galactosidase from Aspergillus oryzae. By using sugar alcohol (sorbitol) as alternative acceptor, a diverse mixture of potential prebiotics is produced, enabling its more favorable functional features. Nevertheless, an introduction of alternative acceptor into the reaction mixture contributed to the complexity of reaction scheme, since several potential reaction pathways were introduced. Therefore, the thorough optimization using response surface method (RSM), in order to get an insight into different parameter (lactose concentration, sorbitol to lactose molar ratio, enzyme concentration, NaCl concentration and reaction time) influences, as well as their mutual interactions on product yield and productivity, was performed. In view of product yield maximization, the obtained model predicted optimal lactose concentration 500 mM, the molar ratio of sobitol to lactose 9, enzyme concentration 0.76 mg/ml, concentration of NaCl 0.8M, and the reaction time 7h. From the aspect of productivity, the optimum substrate molar ratio was found to be 1, while the values for other factors coincide. In order to additionally, improve enzyme efficiency and enable its reuse and potential continual application, immobilization of β-galactosidase onto tailored silica nanoparticles was performed. These non-porous fumed silica nanoparticles (FNS)were chosen on the basis of their biocompatibility and non-toxicity, as well as their advantageous mechanical and hydrodinamical properties. However, in order to achieve better compatibility between enzymes and the carrier, modifications of the silica surface using amino functional organosilane (3-aminopropyltrimethoxysilane, APTMS) were made. Obtained support with amino functional groups (AFNS) enabled high enzyme loadings and, more importantly, extremely high expressed activities, approximately 230 mg proteins/g and 2100 IU/g, respectively. Moreover, this immobilized preparation showed high affinity towards sorbitol galactoside synthesis. Therefore, the findings of this study could provided a valuable contribution to the efficient production of physiologically active galactosides in immobilized enzyme reactors.

Keywords: β-galactosidase, immobilization, silica nanoparticles, transgalactosylation

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Authors: Joel Rookwood

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Sports mega events have become increasingly significant in sporting, political and economic terms, with analysis often focusing on issues including resource expenditure, development, legacy and sustainability. Transnational tournaments can inspire interest from a variety of demographics, and the operational management of such events can involve contributions from a range of personnel. In addition to television audiences events also attract attending spectators, and in football contexts the temporary migration of fans from potentially rival nations and teams can present event organising committees and security personnel with various challenges in relation to crowd management. The behaviour, interaction and control of supporters has previously led to incidents of disorder and hooliganism, with damage to property as well as injuries and deaths proving significant consequences. The Heysel tragedy at the 1985 European Cup final in Brussels is a notable example, where 39 fans died following crowd disorder and mismanagement. Football disasters and disorder, particularly in the context of international competition, have inspired responses from police, law makers, event organisers, clubs and associations, including stadium improvements, legislative developments and crowd management practice to improve the effectiveness of spectator safety. The growth and internationalisation of fandom and developments in event management and tourism have seen various responses to the evolving challenges associated with hosting large numbers of visiting spectators at mega events. In football contexts ‘fan parks’ are a notable example. Since the first widespread introduction in European football competitions at the 2006 World Cup finals in Germany, these facilities have become a staple element of such mega events. This qualitative, longitudinal, multi-continent research draws on extensive semi-structured interview and observation data. As a frame of reference, this work considers football events staged before and after the development of fan parks. Research was undertaken at four World Cup finals (Japan 2002, Germany 2006, South Africa 2010 and Brazil 2014), four European Championships (Portugal 2004, Switzerland/Austria 2008, Poland/Ukraine 2012 and France 2016), four other confederation tournaments (Ghana 2008, Qatar 2011, USA 2011 and Chile 2015), and four European club finals (Istanbul 2005, Athens 2007, Rome 2009 and Basle 2016). This work found that these parks are typically temporarily erected, specifically located zones where supporters congregate together irrespective of allegiances to watch matches on large screens, and partake in other forms of organised on-site entertainment. Such facilities can also allow organisers to control the behaviour, confine the movement and monitor the alcohol consumption of supporters. This represents a notable shift in policy from previous football tournaments, when the widely assumed causal link between alcohol and hooliganism which frequently shaped legislative and police responses to disorder, also dissuaded some authorities from permitting fans to consume alcohol in and around stadia. It also reflects changing attitudes towards modern football fans. The work also found that in certain contexts supporters have increasingly engaged with such provision which impacts fan behaviour, but that this is relative to factors including location, facilities, management and security.

Keywords: event, facility, fan, management, park

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Authors: Rachael Andrews, Viktoria McMillan, Shuaib Nasser, Christopher M. Roberts

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Background and objective: The National Review of Asthma Deaths (NRAD) found that asthma management and care was inadequate in 26% of cases reviewed. Major shortfalls identified were adherence to national guidelines and standards and, particularly, the organisation of care, including supervision and monitoring in primary care, with 70% of cases reviewed having at least one avoidable factor in this area. 5.4 million people in the UK are diagnosed with and actively treated for asthma, and approximately 60,000 are admitted to hospital with acute exacerbations each year. The majority of people with asthma receive management and treatment solely in primary care. This has therefore created concern that many people within the UK are receiving sub-optimal asthma care resulting in unnecessary morbidity and risk of adverse outcome. NRAD concluded that a national asthma audit programme should be established to measure and improve processes, organisation, and outcomes of asthma care. Objective: To develop a primary care dataset enabling extraction of information from GP practices in Wales and providing robust data by which results and lessons could be drawn and drive service development and improvement. Methods: A multidisciplinary group of experts, including general practitioners, primary care organisation representatives, and asthma patients was formed and used as a source of governance and guidance. A review of asthma literature, guidance, and standards took place and was used to identify areas of asthma care which, if improved, would lead to better patient outcomes. Modified Delphi methodology was used to gain consensus from the expert group on which of the areas identified were to be prioritised, and an asthma patient and carer focus group held to seek views and feedback on areas of asthma care that were important to them. Areas of asthma care identified by both groups were mapped to asthma guidelines and standards to inform and develop primary and secondary care datasets covering both adult and pediatric care. Dataset development consisted of expert review and a targeted consultation process in order to seek broad stakeholder views and feedback. Results: Areas of asthma care identified as requiring prioritisation by the National Asthma Audit were: (i) Prescribing, (ii) Asthma diagnosis (iii) Asthma Reviews (iv) Personalised Asthma Action Plans (PAAPs) (v) Primary care follow-up after discharge from hospital (vi) Methodologies and primary care queries were developed to cover each of the areas of poor and variable asthma care identified and the queries designed to extract information directly from electronic patients’ records. Conclusion: This paper describes the methodological approach followed to develop primary care datasets for a National Asthma Audit. It sets out the principles behind the establishment of a National Asthma Audit programme in response to a national asthma mortality review and describes the development activities undertaken. Key process elements included: (i) mapping identified areas of poor and variable asthma care to national guidelines and standards, (ii) early engagement of experts, including clinicians and patients in the process, and (iii) targeted consultation of the queries to provide further insight into measures that were collectable, reproducible and relevant.

Keywords: asthma, primary care, general practice, dataset development

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Authors: Vincent Schlageter, Maroua Mestiri, Florian Denzinger, Hugo Raetzo, Michel Demierre

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Precise landslide monitoring with differential global navigation satellite system (GNSS) is well known, but technical or economic reasons limit its application by geotechnical companies. This study demonstrates the reliability and the usefulness of Geomon (Infrasurvey Sàrl, Switzerland), a stand-alone and cost-effective rover network. The system permits deploying up to 15 rovers, plus one reference station for differential GNSS. A dedicated radio communication links all the modules to a base station, where an embedded computer automatically provides all the relative positions (L1 phase, open-source RTKLib software) and populates an Internet server. Each measure also contains information from an internal inclinometer, battery level, and position quality indices. Contrary to standard GNSS survey systems, which suffer from a limited number of beacons that must be placed in areas with good GSM signal, Geomon offers greater flexibility and permits a real overview of the whole landslide with good spatial resolution. Each module is powered with solar panels, ensuring autonomous long-term recordings. In this study, we have tested the system on several sites in the Swiss mountains, setting up to 7 rovers per site, for an 18 month-long survey. The aim was to assess the robustness and the accuracy of the system in different environmental conditions. In one case, we ran forced blind tests (vertical movements of a given amplitude) and compared various session parameters (duration from 10 to 90 minutes). Then the other cases were a survey of real landslides sites using fixed optimized parameters. Sub centimetric-accuracy with few outliers was obtained using the best parameters (session duration of 60 minutes, baseline 1 km or less), with the noise level on the horizontal component half that of the vertical one. The performance (percent of aborting solutions, outliers) was reduced with sessions shorter than 30 minutes. The environment also had a strong influence on the percent of aborting solutions (ambiguity search problem), due to multiple reflections or satellites obstructed by trees and mountains. The length of the baseline (distance reference-rover, single baseline processing) reduced the accuracy above 1 km but had no significant effect below this limit. In critical weather conditions, the system’s robustness was limited: snow, avalanche, and frost-covered some rovers, including the antenna and vertically oriented solar panels, leading to data interruption; and strong wind damaged a reference station. The possibility of changing the sessions’ parameters remotely was very useful. In conclusion, the rover network tested provided the foreseen sub-centimetric-accuracy while providing a dense spatial resolution landslide survey. The ease of implementation and the fully automatic long-term survey were timesaving. Performance strongly depends on surrounding conditions, but short pre-measures should allow moving a rover to a better final placement. The system offers a promising hazard mitigation technique. Improvements could include data post-processing for alerts and automatic modification of the duration and numbers of sessions based on battery level and rover displacement velocity.

Keywords: GNSS, GSM, landslide, long-term, network, solar, spatial resolution, sub-centimeter.

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Authors: Zdravko Trivic, John Chye Fung, Ruzica Bozovic-Stamenovic

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Within the context of rapidly ageing population in Singapore and the pressing demands on both caregivers and care providers, an integrated approach to ageing-friendly and ability-sensitive enabling environment becomes an imperative. This particularly applies to nursing home environments and their immediate surroundings, as they are becoming one of the main available options of long-term care for many senior adults who are unable to age at home. Yet, despite the considerable efforts to break the still predominant clinical approach to eldercare and to introduce more home-like design and person-centric care model, nursing homes keep being stigmatised and perceived as not so desirable environments to grow old in. The challenges are further emphasised by the associated physical, sensorial, psychological and cognitive declines that are the common consequences of ageing. Such declines have an immense impact on almost all aspects of older adults’ daily functioning, including problems with mobility and spatial orientation, difficulties in communication, withdrawal from social interaction, higher level of depression and decreased sense of independence and autonomy. However, typical nursing home designs tend to neglect the full capacities of balanced and carefully integrated multisensory stimuli as active component of care and ability building. This paper outlines part of a larger multi-disciplinary study of six nursing homes in Singapore, with overarching objectives to create new models of supportive nursing home environments that go beyond the clinical care model and encourage community integration with the nursing home settings. The paper focuses on the largely neglected aspects of sensorial comfort and multi-sensorial properties of nursing homes, including both indoor and immediate outdoor spaces (boundaries). The objective was to investigate the sensory rhythms and explore their role in nursing home users’ daily routine and therapeutic capacities. Socio-sensory rhythms were captured and analysed through a combination of on-site sensory recordings of “objective” quantitative sensory data (air temperature and humidity, sound level and luminance) using multi-function environment meter, perceived experienced data, spatial mapping, first-person observations of nursing home users’ activity patterns, and interviews. This was done in addition to employment of available assessment tools, such as Wisconsin Person Directed Care assessment tool, Dementia Quality of Life [DQoL] instrument, and Resident Environment Impact Scale [REIS], as these tools address the issues of sensorial experience insufficiently and selectively. Key findings indicate varied levels of sensory comfort, as well as diversity, intensity, and customisation of multi-sensory conditions within different nursing home spaces. Sensory stimulation is typically concentrated in communal living areas of the nursing homes or in the areas that often provide controlled or limited access, including specifically designed sensory rooms and outdoor green spaces (gardens and terraces). Opportunities for sensory stimulation are particularly limited for bed-bound senior residents and within more functional areas, such as corridors. This suggests that the capacities of nursing home designs to provide more diverse and better integrated pleasant sensory conditions as integrated “therapeutic devices” to build nursing home residents’ physical and mental abilities, encourage activity and improve wellbeing are far from exhausted.

Keywords: ageing-supportive environment, enabling design, multi-sensory assessment, nursing home environment

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Authors: Natia Jalagonia, Tinatin Kuchukhidze

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Polymer electrolytes (PE) play an important part in electrochemical devices such as batteries and fuel cells. To achieve optimal performance, the PE must maintain a high ionic conductivity and mechanical stability at both high and low relative humidity. The polymer electrolyte also needs to have excellent chemical stability for long and robustness. According to the prevailing theory, ionic conduction in polymer electrolytes is facilitated by the large-scale segmental motion of the polymer backbone, and primarily occurs in the amorphous regions of the polymer electrolyte. Crystallinity restricts polymer backbone segmental motion and significantly reduces conductivity. Consequently, polymer electrolytes with high conductivity at room temperature have been sought through polymers which have highly flexible backbones and have largely amorphous morphology. The interest in polymer electrolytes was increased also by potential applications of solid polymer electrolytes in high energy density solid state batteries, gas sensors and electrochromic windows. Conductivity of 10-3 S/cm is commonly regarded as a necessary minimum value for practical applications in batteries. At present, polyethylene oxide (PEO)-based systems are most thoroughly investigated, reaching room temperature conductivities of 10-7 S/cm in some cross-linked salt in polymer systems based on amorphous PEO-polypropylene oxide copolymers.. It is widely accepted that amorphous polymers with low glass transition temperatures Tg and a high segmental mobility are important prerequisites for high ionic conductivities. Another necessary condition for high ionic conductivity is a high salt solubility in the polymer, which is most often achieved by donors such as ether oxygen or imide groups on the main chain or on the side groups of the PE. It is well established also that lithium ion coordination takes place predominantly in the amorphous domain, and that the segmental mobility of the polymer is an important factor in determining the ionic mobility. Great attention was pointed to PEO-based amorphous electrolyte obtained by synthesis of comb-like polymers, by attaching short ethylene oxide unit sequences to an existing amorphous polymer backbone. The aim of presented work is to obtain of solid polymer electrolyte membranes using PMHS as a matrix. For this purpose the hydrosilylation reactions of α,ω-bis(trimethylsiloxy)methyl¬hydrosiloxane with allyl triethylene-glycol mo¬nomethyl ether and vinyltriethoxysilane at 1:28:7 ratio of initial com¬pounds in the presence of Karstedt’s catalyst, platinum hydrochloric acid (0.1 M solution in THF) and platinum on the carbon catalyst in 50% solution of anhydrous toluene have been studied. The synthesized olygomers are vitreous liquid products, which are well soluble in organic solvents with specific viscosity ηsp ≈ 0.05 - 0.06. The synthesized olygomers were analysed with FTIR, 1H, 13C, 29Si NMR spectroscopy. Synthesized polysiloxanes were investigated with wide-angle X-ray, gel-permeation chromatography, and DSC analyses. Via sol-gel processes of doped with lithium trifluoromethylsulfonate (triflate) or lithium bis¬(trifluoromethylsulfonyl)¬imide polymer systems solid polymer electrolyte membranes have been obtained. The dependence of ionic conductivity as a function of temperature and salt concentration was investigated and the activation energies of conductivity for all obtained compounds are calculated

Keywords: synthesis, PMHS, membrane, electrolyte

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Authors: Philipp Sommer, Amgad Agoub

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The construction sector significantly impacts global CO₂ emissions, particularly through the energy usage of residential buildings. To address this, various governments, including Germany's, are focusing on reducing emissions via sustainable refurbishment initiatives. This study examines the application of machine learning (ML) to estimate energy demands dynamically in residential buildings and enhance the potential for large-scale sustainable refurbishment. A major challenge in Germany is the lack of extensive publicly labeled datasets for energy performance, as energy performance certificates, which provide critical data on building-specific energy requirements and consumption, are not available for all buildings or require on-site inspections. Conversely, England and other countries in the European Union (EU) have rich public datasets, providing a viable alternative for analysis. This research adapts insights from these English datasets to the German context by developing a comprehensive data schema and calibration dataset capable of predicting building energy demand effectively. The study proposes a minimal feature set, determined through feature importance analysis, to optimize the ML model. Findings indicate that ML significantly improves the scalability and accuracy of energy demand forecasts, supporting more effective emissions reduction strategies in the construction industry. Integrating energy performance certificates into municipal heat planning in Germany highlights the transformative impact of data-driven approaches on environmental sustainability. The goal is to identify and utilize key features from open data sources that significantly influence energy demand, creating an efficient forecasting model. Using Extreme Gradient Boosting (XGB) and data from energy performance certificates, effective features such as building type, year of construction, living space, insulation level, and building materials were incorporated. These were supplemented by data derived from descriptions of roofs, walls, windows, and floors, integrated into three datasets. The emphasis was on features accessible via remote sensing, which, along with other correlated characteristics, greatly improved the model's accuracy. The model was further validated using SHapley Additive exPlanations (SHAP) values and aggregated feature importance, which quantified the effects of individual features on the predictions. The refined model using remote sensing data showed a coefficient of determination (R²) of 0.64 and a mean absolute error (MAE) of 4.12, indicating predictions based on efficiency class 1-100 (G-A) may deviate by 4.12 points. This R² increased to 0.84 with the inclusion of more samples, with wall type emerging as the most predictive feature. After optimizing and incorporating related features like estimated primary energy consumption, the R² score for the training and test set reached 0.94, demonstrating good generalization. The study concludes that ML models significantly improve prediction accuracy over traditional methods, illustrating the potential of ML in enhancing energy efficiency analysis and planning. This supports better decision-making for energy optimization and highlights the benefits of developing and refining data schemas using open data to bolster sustainability in the building sector. The study underscores the importance of supporting open data initiatives to collect similar features and support the creation of comparable models in Germany, enhancing the outlook for environmental sustainability.

Keywords: machine learning, remote sensing, residential building, energy performance certificates, data-driven, heat planning

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Authors: Mohamad Saab, Florent Real, Francois Virot, Laurent Cantrel, Valerie Vallet

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All spent nuclear fuel reprocessing plants use the PUREX process (Plutonium Uranium Refining by Extraction), which is a liquid-liquid extraction method. The organic extracting solvent is a mixture of tri-n-butyl phosphate (TBP) and hydrocarbon solvent such as hydrogenated tetra-propylene (TPH). By chemical complexation, uranium and plutonium (from spent fuel dissolved in nitric acid solution), are separated from fission products and minor actinides. During a normal extraction operation, uranium is extracted in the organic phase as the UO₂(NO₃)₂(TBP)₂ complex. The TBP solvent can form an explosive mixture called red oil when it comes in contact with nitric acid. The formation of this unstable organic phase originates from the reaction between TBP and its degradation products on the one hand, and nitric acid, its derivatives and heavy metal nitrate complexes on the other hand. The decomposition of the red oil can lead to violent explosive thermal runaway. These hazards are at the origin of several accidents such as the two in the United States in 1953 and 1975 (Savannah River) and, more recently, the one in Russia in 1993 (Tomsk). This raises the question of the exothermicity of reactions that involve TBP and all other degradation products, and calls for a better knowledge of the underlying chemical phenomena. A simulation tool (Alambic) is currently being developed at IRSN that integrates thermal and kinetic functions related to the deterioration of uranyl nitrates in organic and aqueous phases, but not of the n-butyl phosphate. To include them in the modeling scheme, there is an urgent need to obtain the thermodynamic and kinetic functions governing the deterioration processes in liquid phase. However, little is known about the thermodynamic properties, like standard enthalpies of formation, of the n-butyl phosphate molecules and of the UO₂(NO₃)₂(TBP)₂ UO₂(NO₃)₂(HDBP)(TBP) and UO₂(NO₃)₂(HDBP)₂ complexes. In this work, we propose to estimate the thermodynamic properties with Quantum Methods (QM). Thus, in the first part of our project, we focused on the mono, di, and tri-butyl complexes. Quantum chemical calculations have been performed to study several reactions leading to the formation of mono-(H₂MBP), di-(HDBP), and TBP in gas and liquid phases. In the gas phase, the optimal structures of all species were optimized using the B3LYP density functional. Triple-ζ def2-TZVP basis sets were used for all atoms. All geometries were optimized in the gas-phase, and the corresponding harmonic frequencies were used without scaling to compute the vibrational partition functions at 298.15 K and 0.1 Mpa. Accurate single point energies were calculated using the efficient localized LCCSD(T) method to the complete basis set limit. Whenever species in the liquid phase are considered, solvent effects are included with the COSMO-RS continuum model. The standard enthalpies of formation of TBP, HDBP, and H2MBP are finally predicted with an uncertainty of about 15 kJ mol⁻¹. In the second part of this project, we have investigated the fundamental properties of three organic species that mostly contribute to the thermal runaway: UO₂(NO₃)₂(TBP)₂, UO₂(NO₃)₂(HDBP)(TBP), and UO₂(NO₃)₂(HDBP)₂ using the same quantum chemical methods that were used for TBP and its derivatives in both the gas and the liquid phase. We will discuss the structures and thermodynamic properties of all these species.

Keywords: PUREX process, red oils, quantum chemical methods, hydrolysis

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Authors: David F. Nettleton, Elodie Bugnicourt, Christian Wasiak, Alejandro Rosales

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In this presentation, preliminary results are given for the modeling and calibration of two different industrial winding MIMO (Multiple Input Multiple Output) processes using machine learning techniques. In contrast to previous approaches which have typically used ‘black-box’ linear statistical methods together with a definition of the mechanical behavior of the process, we use non-linear machine learning algorithms together with a ‘white-box’ rule induction technique to create a supervised model of the fitting error between the expected and real force measures. The final objective is to build a precise model of the winding process in order to control de-tension of the material being wound in the first case, and the friction of the material passing through the die, in the second case. Case 1, Tension Control of a Winding Process. A plastic web is unwound from a first reel, goes over a traction reel and is rewound on a third reel. The objectives are: (i) to train a model to predict the web tension and (ii) calibration to find the input values which result in a given tension. Case 2, Friction Force Control of a Micro-Pullwinding Process. A core+resin passes through a first die, then two winding units wind an outer layer around the core, and a final pass through a second die. The objectives are: (i) to train a model to predict the friction on die2; (ii) calibration to find the input values which result in a given friction on die2. Different machine learning approaches are tested to build models, Kernel Ridge Regression, Support Vector Regression (with a Radial Basis Function Kernel) and MPART (Rule Induction with continuous value as output). As a previous step, the MPART rule induction algorithm was used to build an explicative model of the error (the difference between expected and real friction on die2). The modeling of the error behavior using explicative rules is used to help improve the overall process model. Once the models are built, the inputs are calibrated by generating Gaussian random numbers for each input (taking into account its mean and standard deviation) and comparing the output to a target (desired) output until a closest fit is found. The results of empirical testing show that a high precision is obtained for the trained models and for the calibration process. The learning step is the slowest part of the process (max. 5 minutes for this data), but this can be done offline just once. The calibration step is much faster and in under one minute obtained a precision error of less than 1x10-3 for both outputs. To summarize, in the present work two processes have been modeled and calibrated. A fast processing time and high precision has been achieved, which can be further improved by using heuristics to guide the Gaussian calibration. Error behavior has been modeled to help improve the overall process understanding. This has relevance for the quick optimal set up of many different industrial processes which use a pull-winding type process to manufacture fibre reinforced plastic parts. Acknowledgements to the Openmind project which is funded by Horizon 2020 European Union funding for Research & Innovation, Grant Agreement number 680820

Keywords: data model, machine learning, industrial winding, calibration

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