Search results for: discrete phase modeling

Authors: Berna Çalışkan

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The integrated water management is a colloborative approach to planning that brings together institutions that influence all elements of the water cycle, waterways, watershed characteristics, wetlands, ponds, lakes, floodplain areas, stream channel structure. It encourages collaboration where it will be beneficial and links between water planning and other planning processes that contribute to improving sustainable urban development and liveability. Hydraulic considerations can influence the selection of a highway corridor and the alternate routes within the corridor. widening a roadway, replacing a culvert, or repairing a bridge. Because of this, the type and amount of data needed for planning studies can vary widely depending on such elements as environmental considerations, class of the proposed highway, state of land use development, and individual site conditions. The extraction of drainage networks provide helpful preliminary drainage data from the digital elevation model (DEM). A case study was carried out using the Arc Hydro extension within ArcGIS in the study area. It provides the means for processing and presenting spatially-referenced Stream Model. Study area’s flow routing, stream levels, segmentation, drainage point processing can be obtained using DEM as the 'Input surface raster'. These processes integrate the fields of hydrologic, engineering research, and environmental modeling in a multi-disciplinary program designed to provide decision makers with a science-based understanding, and innovative tools for, the development of interdisciplinary and multi-level approach. This research helps to manage transport project planning and construction phases to analyze the surficial water flow, high-level streams, wetland sites for development of transportation infrastructure planning, implementing, maintenance, monitoring and long-term evaluations to better face the challenges and solutions associated with effective management and enhancement to deal with Low, Medium, High levels of impact. Transport projects are frequently perceived as critical to the ‘success’ of major urban, metropolitan, regional and/or national development because of their potential to affect significant socio-economic and territorial change. In this context, sustaining and development of economic and social activities depend on having sufficient Water Resources Management. The results of our research provides a workflow to build a stream network how can classify suitability map according to stream levels. Transportation projects establish, develop, incorporate and deliver effectively by selecting best location for reducing construction maintenance costs, cost-effective solutions for drainage, landslide, flood control. According to model findings, field study should be done for filling gaps and checking for errors. In future researches, this study can be extended for determining and preventing possible damage of Sensitive Areas and Vulnerable Zones supported with field investigations.

Keywords: water resources management, hydro tool, water protection, transportation

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Authors: Swati Gautam, Salman Akhtar, S. P. Jaiswar, Amita Jain

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Background: FGTB is now a major global health problem mostly in developing countries including India. In humans, Mycobacterium Tuberculosis (M.tb) is a causating agent of infection. High index of suspicion is required for early diagnosis due to asymptomatic presentation of FGTB disease. In macrophages Toll Like Receptor-2 (TLR-2) is one which mediated host’s immune response to M.tb. The expression of TLR-2 on macrophages is important to determine the fate of innate immune responses to M.tb. TLR-2 have two work. First its high expression on macrophages worsen the outer of infection and another side, it maintains M.tb to its dormant stage avoids activation of M.tb from latent phase. Single Nucleotide Polymorphism (SNP) of TLR-2 gene plays an important role in susceptibility to TB among different populations and subsequently, in the development of infertility. Methodology: This Case-Control study was done in the Department of Obs and Gynae and Department of Microbiology at King George’s Medical University, U.P, Lucknow, India. Total 300 subjects (150 Cases and 150 Controls) were enrolled in the study. All subjects were enrolled only after fulfilling the given inclusion and exclusion criteria. Inclusion criteria: Age 20-35 years, menstrual-irregularities, positive on Acid-Fast Bacilli (AFB), TB-PCR, (LJ/MGIT) culture in Endometrial Aspiration (EA). Exclusion criteria: Koch’s active, on ATT, PCOS, and Endometriosis fibroid women, positive on Gonococal and Chlamydia. Blood samples were collected in EDTA tubes from cases and healthy control women (HCW) and genomic DNA extraction was carried out by salting-out method. Genotyping of TLR2 genetic variants (Arg753Gln and Arg677Trp) were performed by using single amplification refractory mutation system (ARMS) PCR technique. PCR products were analyzed by electrophoresis on 1.2% agarose gel and visualized by gel-doc. Statistical analysis of the data was performed using the SPSS 16.3 software and computing odds ratio (OR) with 95% CI. Linkage Disequiliribium (LD) analysis was done by SNP stats online software. Results: In TLR-2 (Arg753Gln) polymorphism significant risk of FGTB observed with GG homozygous mutant genotype (OR=13, CI=0.71-237.7, p=0.05), AG heterozygous mutant genotype (OR=13.7, CI=0.76-248.06, p=0.03) however, G allele (OR=1.09, CI=0.78-1.52, p=0.67) individually was not associated with FGTB. In TLR-2 (Arg677Trp) polymorphism a significant risk of FGTB observed with TT homozygous mutant genotype (OR= 0.020, CI=0.001-0.341, p < 0.001), CT heterozygous mutant genotype (OR=0.53, CI=0.33-0.86, p=0.014) and T allele (OR=0.463, CI=0.32-0.66, p < 0.001). TT mutant genotype was only found in FGTB cases and frequency of CT heterozygous more in control group as compared to FGTB group. So, CT genotype worked as protective mutation for FGTB susceptibility group. In haplotype analysis of TLR-2 genetic variants, four possible combinations, i.e. (G-T, A-C, G-C, and A-T) were obtained. The frequency of haplotype A-C was significantly higher in FGTB cases (0.32). Control group did not show A-C haplotype and only found in FGTB cases. Conclusion: In conclusion, study showed a significant association with both genetic variants of TLR-2 of FGTB disease. Moreover, the presence of specific associated genotype/alleles suggest the possibility of disease severity and clinical approach aimed to prevent extensive damage by disease and also helpful for early detection of disease.

Keywords: ARMS, EDTA, FGTB, TLR

Procedia PDF Downloads 284

Authors: André Python

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To this day, terrorism persists as a worldwide threat, exemplified by the recent deadly attacks in January 2015 in Paris and the ongoing massacres perpetrated by ISIS in Iraq and Syria. In response to this threat, states deploy various counterterrorism measures, the cost of which could be reduced through effective preventive measures. In order to increase the efficiency of preventive measures, policy-makers may benefit from accurate predictive models that are able to capture the complex spatial dynamics of terrorism occurring at a local scale. Despite empirical research carried out at country-level that has confirmed theories explaining the diffusion processes of terrorism across space and time, scholars have failed to assess diffusion’s theories on a local scale. Moreover, since scholars have not made the most of recent statistical modelling approaches, they have been unable to build up predictive models accurate in both space and time. In an effort to address these shortcomings, this research suggests a novel approach to systematically assess the theories of terrorism’s diffusion on a local scale and provide a predictive model of the local spatial dynamics of terrorism worldwide. With a focus on the lethal terrorist events that occurred after 9/11, this paper addresses the following question: why and how does lethal terrorism diffuse in space and time? Based on geolocalised data on worldwide terrorist attacks and covariates gathered from 2002 to 2013, a binomial spatio-temporal point process is used to model the probability of terrorist attacks on a sphere (the world), the surface of which is discretised in the form of Delaunay triangles and refined in areas of specific interest. Within a Bayesian framework, the model is fitted through an integrated nested Laplace approximation - a recent fitting approach that computes fast and accurate estimates of posterior marginals. Hence, for each location in the world, the model provides a probability of encountering a lethal terrorist attack and measures of volatility, which inform on the model’s predictability. Diffusion processes are visualised through interactive maps that highlight space-time variations in the probability and volatility of encountering a lethal attack from 2002 to 2013. Based on the previous twelve years of observation, the location and lethality of terrorist events in 2014 are statistically accurately predicted. Throughout the global scope of this research, local diffusion processes such as escalation and relocation are systematically examined: the former process describes an expansion from high concentration areas of lethal terrorist events (hotspots) to neighbouring areas, while the latter is characterised by changes in the location of hotspots. By controlling for the effect of geographical, economical and demographic variables, the results of the model suggest that the diffusion processes of lethal terrorism are jointly driven by contagious and non-contagious factors that operate on a local scale – as predicted by theories of diffusion. Moreover, by providing a quantitative measure of predictability, the model prevents policy-makers from making decisions based on highly uncertain predictions. Ultimately, this research may provide important complementary tools to enhance the efficiency of policies that aim to prevent and combat terrorism.

Keywords: diffusion process, terrorism, spatial dynamics, spatio-temporal modeling

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Authors: Choy Sonny Yip Hong

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This abstract presents an exploration into the creation of a sustainable bio-polymer compound for additive manufacturing, specifically 3D printing, with a focus on eggshells and polylactide (PLA) polymer. The project initially conducted experiments using a variety of food by-products to create bio-polymers, and promising results were obtained when combining eggshells with PLA polymer. The research journey involved precise measurements, drying of PLA to remove moisture, and the utilization of a filament-making machine to produce 3D printable filaments. The project began with exploratory research and experiments, testing various combinations of food by-products to create bio-polymers. After careful evaluation, it was discovered that eggshells and PLA polymer produced promising results. The initial mixing of the two materials involved heating them just above the melting point. To make the compound 3D printable, the research focused on finding the optimal formulation and production process. The process started with precise measurements of the PLA and eggshell materials. The PLA was placed in a heating oven to remove any absorbed moisture. Handmade testing samples were created to guide the planning for 3D-printed versions. The scrap PLA was recycled and ground into a powdered state. The drying process involved gradual moisture evaporation, which required several hours. The PLA and eggshell materials were then placed into the hopper of a filament-making machine. The machine's four heating elements controlled the temperature of the melted compound mixture, allowing for optimal filament production with accurate and consistent thickness. The filament-making machine extruded the compound, producing filament that could be wound on a wheel. During the testing phase, trials were conducted with different percentages of eggshell in the PLA mixture, including a high percentage (20%). However, poor extrusion results were observed for high eggshell percentage mixtures. Samples were created, and continuous improvement and optimization were pursued to achieve filaments with good performance. To test the 3D printability of the DIY filament, a 3D printer was utilized, set to print the DIY filament smoothly and consistently. Samples were printed and mechanically tested using a universal testing machine to determine their mechanical properties. This testing process allowed for the evaluation of the filament's performance and suitability for additive manufacturing applications. In conclusion, the project explores the creation of a sustainable bio-polymer compound using eggshells and PLA polymer for 3D printing. The research journey involved precise measurements, drying of PLA, and the utilization of a filament-making machine to produce 3D printable filaments. Continuous improvement and optimization were pursued to achieve filaments with good performance. The project's findings contribute to the advancement of additive manufacturing, offering opportunities for design innovation, carbon footprint reduction, supply chain optimization, and collaborative potential. The utilization of eggshell PLA polymer in additive manufacturing has the potential to revolutionize the manufacturing industry, providing a sustainable alternative and enabling the production of intricate and customized products.

Keywords: additive manufacturing, 3D printing, eggshell PLA polymer, design innovation, carbon footprint reduction, supply chain optimization, collaborative potential

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Authors: Gabriella Zarlenga, Martha L. Hall

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Introduction: Premature infants are at risk for neurodevelopmental deficits and hospital readmissions, which can increase the financial burden on the health care system and families. Kangaroo care (skin-to-skin contact) is a practice that can improve preterm infant health outcomes. Preterm infants can acquire adequate body temperature, heartbeat, and breathing regulation through lying directly on the mother’s abdomen and in between her breasts. Due to some infant’s condition, kangaroo care is not a feasible intervention. The purpose of this proof-of-concept research project is to create a device which simulates skin-to-skin contact for pre-term infants not eligible for kangaroo care, with the aim of promoting baby’s health outcomes, reducing the incidence of serious neonatal and early childhood illnesses, and/or improving cognitive, social and emotional aspects of development. Methods: The study design is a proof-of-concept based on a three-phase approach; (1) observational study and data analysis of the standard of care for 2 groups of pre-term infants, (2) design and concept development of a novel device for pre-term infants not currently eligible for standard kangaroo care, and (3) prototyping, laboratory testing, and evaluation of the novel device in comparison to current assessment parameters of kangaroo care. A single center study will be conducted in an area hospital offering Level III neonatal intensive care. Eligible participants include newborns born premature (28-30 weeks of age) admitted to the NICU. The study design includes 2 groups: a control group receiving standard kangaroo care and an experimental group not eligible for kangaroo care. Based on behavioral analysis of observational video data collected in the NICU, the device will be created to simulate mother’s body using electrical components in a thermoplastic polymer housing covered in silicone. It will be designed with a microprocessor that controls simulated respiration, heartbeat, and body temperature of the 'simulated caregiver' by using a pneumatic lung, vibration sensors (heartbeat), pressure sensors (weight/position), and resistive film to measure temperature. A slight contour of the simulator surface may be integrated to help position the infant correctly. Control and monitoring of the skin-to-skin contact simulator would be performed locally by an integrated touchscreen. The unit would have built-in Wi-Fi connectivity as well as an optional Bluetooth connection in which the respiration and heart rate could be synced with a parent or caregiver. A camera would be integrated, allowing a video stream of the infant in the simulator to be streamed to a monitoring location. Findings: Expected outcomes are stabilization of respiratory and cardiac rates, thermoregulation of those infants not eligible for skin to skin contact with their mothers, and real time mother Bluetooth to the device to mimic the experience in the womb. Results of this study will benefit clinical practice by creating a new standard of care for premature neonates in the NICU that are deprived of skin to skin contact due to various health restrictions.

Keywords: kangaroo care, wearable technology, pre-term infants, medical design

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Authors: M. Velana, G. Rinkenauer

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Nowadays, nurses are facing unprecedented amounts of pressure due to the ongoing global health demands. Work-related stress can cause a high physical and psychological workload, which can lead, in turn, to burnout. On the physiological level, stress triggers an initial activation of the sympathetic nervous and adrenomedullary systems resulting in increases in cardiac activity. Furthermore, activation of the hypothalamus-pituitary-adrenal axis provokes endocrine and immune changes leading to the release of cortisol and cytokines in an effort to re-establish body balance. Based on the current state of the literature, it has been identified that resilience and mindfulness exercises among nurses can effectively decrease stress and improve mood. However, it is still unknown what relaxation techniques would be suitable for and to what extent would be effective to decrease psychophysiological arousal deriving from either a physiological or a psychological stressor. Moreover, although cardiac activity and cortisol are promising candidates to examine the effectiveness of relaxation to reduce stress, it still remains to shed light on the role of cytokines in this process so as to thoroughly understand the body’s response to stress and to relaxation. Therefore, the main aim of the present study is to develop a comprehensive experimental paradigm and assess different relaxation techniques, namely progressive muscle relaxation and a mindfulness exercise originating from cognitive therapy by means of biofeedback, under highly controlled laboratory conditions. An experimental between-subject design will be employed, where 120 participants will be randomized either to a physiological or a psychological stress-related experiment. Particularly, the cold pressor test refers to a procedure in which the participants have to immerse their non-dominant hands into ice water (2-3 °C) for 3 min. The participants are requested to keep their hands in the water throughout the whole duration. However, they can immediately terminate the test in case it would be barely tolerable. A pre-test anticipation phase and a post-stress period of 3 min, respectively, are planned. The Trier Social Stress Test will be employed to induce psychological stress. During this laboratory stressor, the participants are instructed to give a 5-min speech in front of a committee of communication specialists. Before the main task, there is a 10-min anticipation period. Subsequently, participants are requested to perform an unexpected arithmetic task. After stress exposure, the participants will perform one of the relaxation exercises (treatment condition) or watch a neutral video (control condition). Electrocardiography, salivary samples, and self-report will be collected at different time points. The preliminary results deriving from the pilot study showed that the aforementioned paradigm could effectively induce stress reactions and that relaxation might decrease the impact of stress exposure. It is of utmost importance to assess how the human body responds under different stressors and relaxation exercises so that an evidence-based intervention could be transferred in a clinical setting to improve nurses’ general health. Based on suggestive future laboratory findings, the research group plans to conduct a pilot-level randomized study to decrease stress and promote well-being among nurses who work in the stress-riddled environment of a hospital located in Northern Germany.

Keywords: nurses, psychophysiology, relaxation, stress

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Authors: Ciaran Friel, Jerry Suls, Patrick Robles, Frank Vicari, Joan Duer-Hefele, Karina W. Davidson

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Physical activity guidelines focus on increasing moderate intensity activity for older adults, but adherence to recommendations remains low. This is despite the fact that scientific evidence supports that any increase in physical activity is positively correlated with health benefits. Behavior change techniques (BCTs) have demonstrated effectiveness in reducing sedentary behavior and promoting physical activity. This pilot study uses a Personalized Trials (N-of-1) design to evaluate the efficacy of using four BCTs to promote an increase in low-intensity physical activity (2,000 steps of walking per day) in adults aged 45-75 years old. The 4 BCTs tested were goal setting, action planning, feedback, and self-monitoring. BCTs were tested in random order and delivered by text message prompts requiring participant response. The study recruited health system employees in the target age range, without mobility restrictions and demonstrating interest in increasing their daily activity by a minimum of 2,000 steps per day for a minimum of five days per week. Participants were sent a Fitbit Charge 4 fitness tracker with an established study account and password. Participants were recommended to wear the Fitbit device 24/7, but were required to wear it for a minimum of ten hours per day. Baseline physical activity was measured by the Fitbit for two weeks. Participants then engaged with a clinical research coordinator to review comprehension of the text message content and required actions for each of the BCTs to be tested. Participants then selected a consistent daily time in which they would receive their text message prompt. In the 8 week intervention phase of the study, participants received each of the four BCTs, in random order, for a two week period. Text message prompts were delivered daily at a time selected by the participant. All prompts required an interactive response from participants and may have included recording their detailed plan for walking or daily step goal (action planning, goal setting). Additionally, participants may have been directed to a study dashboard to view their step counts or compare themselves with peers (self-monitoring, feedback). At the end of each two week testing interval, participants were asked to complete the Self-Efficacy for Walking Scale (SEW_Dur), a validated measure that assesses the participant’s confidence in walking incremental distances and a survey measuring their satisfaction with the individual BCT that they tested. At the end of their trial, participants received a personalized summary of their step data in response to each individual BCT. Analysis will examine the novel individual-level heterogeneity of treatment effect made possible by N-of-1 design, and pool results across participants to efficiently estimate the overall efficacy of the selected behavioral change techniques in increasing low-intensity walking by 2,000 steps, 5 days per week. Self-efficacy will be explored as the likely mechanism of action prompting behavior change. This study will inform the providers and demonstrate the feasibility of N-of-1 study design to effectively promote physical activity as a component of healthy aging.

Keywords: aging, exercise, habit, walking

Procedia PDF Downloads 117

Authors: Ariunaa.S., Javzandulam E., Chimegsaikhan S., Altantsetseg B., Oyungerel S., Bat-Erdene T., Naranbaatar S., Otgonbayar B., Suvdaa N., Tumenbayar B.

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

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

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Authors: Narottam Puri, Bishnu Panigrahi, Narayan Pendse

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Background: Clinical Outcomes are the globally agreed upon, evidence-based measurable changes in health or quality of life resulting from the patient care. Reporting of outcomes and its continuous monitoring provides an opportunity for both assessing and improving the quality of patient care. In 2012, International Consortium Of HealthCare Outcome Measurement (ICHOM) was founded which has defined global Standard Sets for measuring the outcome of various treatments. Method: Monitoring of Clinical Outcomes was identified as a pillar of Fortis’ core value of Patient Centricity. The project was started as an in-house developed Clinical Outcomes Reporting Portal by the Fortis Medical IT team. Standard sets of Outcome measurement developed by ICHOM were used. A pilot was run at Fortis Escorts Heart Institute from Aug’13 – Dec’13.Starting Jan’14, it was implemented across 11 hospitals of the group. The scope was hospital-wide and major clinical specialties: Cardiac Sciences, Orthopedics & Joint Replacement were covered. The internally developed portal had its limitations of report generation and also capturing of Patient related outcomes was restricted. A year later, the company provisioned for an ICHOM Certified Software product which could provide a platform for data capturing and reporting to ensure compliance with all ICHOM requirements. Post a year of the launch of the software; Fortis Healthcare has become the 1st Healthcare Provider in Asia to publish Clinical Outcomes data for the Coronary Artery Disease Standard Set comprising of Coronary Artery Bypass Graft and Percutaneous Coronary Interventions) in the public domain. (Jan 2016). Results: This project has helped in firmly establishing a culture of monitoring and reporting Clinical Outcomes across Fortis Hospitals. Given the diverse nature of the healthcare delivery model at Fortis Network, which comprises of hospitals of varying size and specialty-mix and practically covering the entire span of the country, standardization of data collection and reporting methodology is a huge achievement in itself. 95% case reporting was achieved with more than 90% data completion at the end of Phase 1 (March 2016). Post implementation the group now has one year of data from its own hospitals. This has helped identify the gaps and plan towards ways to bridge them and also establish internal benchmarks for continual improvement. Besides the value created for the group includes: 1. Entire Fortis community has been sensitized on the importance of Clinical Outcomes monitoring for patient centric care. Initial skepticism and cynicism has been countered by effective stakeholder engagement and automation of processes. 2. Measuring quality is the first step in improving quality. Data analysis has helped compare clinical results with best-in-class hospitals and identify improvement opportunities. 3. Clinical fraternity is extremely pleased to be part of this initiative and has taken ownership of the project. Conclusion: Fortis Healthcare is the pioneer in the monitoring of Clinical Outcomes. Implementation of ICHOM standards has helped Fortis Clinical Excellence Program in improving patient engagement and strengthening its commitment to its core value of Patient Centricity. Validation and certification of the Clinical Outcomes data by an ICHOM Certified Supplier adds confidence to its claim of being leaders in this space.

Keywords: clinical outcomes, healthcare delivery, patient centricity, ICHOM

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Authors: Esmael Makarian, Ayub Elyasi, Fatemeh Saberi, Olusegun Stanley Tomomewo

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Rock mechanical investigation is one of the most crucial activities in underground operations, especially in surveys related to hydrocarbon exploration and production, geothermal reservoirs, energy storage, mining, and geotechnics. There is a wide range of traditional methods for driving, collecting, and analyzing rock mechanics data. However, these approaches may not be suitable or work perfectly in some situations, such as fractured zones. Cutting-edge technologies have been provided to solve and optimize the mentioned issues. Internet of Things (IoT), Edge, and Cloud Computing technologies (ECt & CCt, respectively) are among the most widely used and new artificial intelligence methods employed for geomechanical studies. IoT devices act as sensors and cameras for real-time monitoring and mechanical-geological data collection of rocks, such as temperature, movement, pressure, or stress levels. Structural integrity, especially for cap rocks within hydrocarbon systems, and rock mass behavior assessment, to further activities such as enhanced oil recovery (EOR) and underground gas storage (UGS), or to improve safety risk management (SRM) and potential hazards identification (P.H.I), are other benefits from IoT technologies. EC techniques can process, aggregate, and analyze data immediately collected by IoT on a real-time scale, providing detailed insights into the behavior of rocks in various situations (e.g., stress, temperature, and pressure), establishing patterns quickly, and detecting trends. Therefore, this state-of-the-art and useful technology can adopt autonomous systems in rock mechanical surveys, such as drilling and production (in hydrocarbon wells) or excavation (in mining and geotechnics industries). Besides, ECt allows all rock-related operations to be controlled remotely and enables operators to apply changes or make adjustments. It must be mentioned that this feature is very important in environmental goals. More often than not, rock mechanical studies consist of different data, such as laboratory tests, field operations, and indirect information like seismic or well-logging data. CCt provides a useful platform for storing and managing a great deal of volume and different information, which can be very useful in fractured zones. Additionally, CCt supplies powerful tools for predicting, modeling, and simulating rock mechanical information, especially in fractured zones within vast areas. Also, it is a suitable source for sharing extensive information on rock mechanics, such as the direction and size of fractures in a large oil field or mine. The comprehensive review findings demonstrate that digital transformation through integrated IoT, Edge, and Cloud solutions is revolutionizing traditional rock mechanical investigation. These advanced technologies have empowered real-time monitoring, predictive analysis, and data-driven decision-making, culminating in noteworthy enhancements in safety, efficiency, and sustainability. Therefore, by employing IoT, CCt, and ECt, underground operations have experienced a significant boost, allowing for timely and informed actions using real-time data insights. The successful implementation of IoT, CCt, and ECt has led to optimized and safer operations, optimized processes, and environmentally conscious approaches in underground geological endeavors.

Keywords: rock mechanical studies, internet of things, edge computing, cloud computing, underground surveys, geological operations

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Authors: Athina Puype, Lorenzo Malerba, Nico De Wispelaere, Roumen Petrov, Jilt Sietsma

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Reduced activation ferritic/martensitic (RAFM) steels like EUROFER97 are primary candidate structural materials for first wall application in the future demonstration (DEMO) fusion reactor. Existing steels of this type obtain their functional properties by a two-stage heat treatment, which consists of an annealing stage at 980°C for thirty minutes followed by quenching and an additional tempering stage at 750°C for two hours. This thermal quench and temper (Q&T) treatment creates a microstructure of tempered martensite with, as main precipitates, M23C6 carbides, with M = Fe, Cr and carbonitrides of MX type, e.g. TaC and VN. The resulting microstructure determines the mechanical properties of the steel. The ductility is largely determined by the tempered martensite matrix, while the resistance to mechanical degradation, determined by the spatial and size distribution of precipitates and the martensite crystals, plays a key role in the high temperature properties of the steel. Unfortunately, the high temperature response of EUROFER97 is currently insufficient for long term use in fusion reactors, due to instability of the matrix phase and coarsening of the precipitates at prolonged high temperature exposure. The objective of this study is to induce grain refinement by appropriate modifications of the processing route in order to increase the high temperature strength of a lab-cast EUROFER RAFM steel grade. The goal of the work is to obtain improved mechanical behavior at elevated temperatures with respect to conventionally heat treated EUROFER97. A dilatometric study was conducted to study the effect of the annealing temperature on the mechanical properties after a Q&T treatment. The microstructural features were investigated with scanning electron microscopy (SEM), electron back-scattered diffraction (EBSD) and transmission electron microscopy (TEM). Additionally, hardness measurements, tensile tests at elevated temperatures and Charpy V-notch impact testing of KLST-type MCVN specimens were performed to study the mechanical properties of the furnace-heated lab-cast EUROFER RAFM steel grade. A significant prior austenite grain (PAG) refinement was obtained by lowering the annealing temperature of the conventionally used Q&T treatment for EUROFER97. The reduction of the PAG results in finer martensitic constituents upon quenching, which offers more nucleation sites for carbide and carbonitride formation upon tempering. The ductile-to-brittle transition temperature (DBTT) was found to decrease with decreasing martensitic block size. Additionally, an increased resistance against high temperature degradation was accomplished in the fine grained martensitic materials with smallest precipitates obtained by tailoring the annealing temperature of the Q&T treatment. It is concluded that the microstructural refinement has a pronounced effect on the DBTT without significant loss of strength and ductility. Further investigation into the optimization of the processing route is recommended to improve the mechanical behavior of RAFM steels at elevated temperatures.

Keywords: ductile-to-brittle transition temperature (DBTT), EUROFER, reduced activation ferritic/martensitic (RAFM) steels, thermal treatments

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Authors: Neil Singla, Derek Muse, Karen DiDonato, Pamela Palmer

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Introduction: Pain is the most common reason people visit emergency rooms. Studies indicate however, that Emergency Department (ED) physicians often do not provide adequate analgesia to their patients as a result of gender and age bias, opiophobia and insufficient knowledge of and formal training in acute pain management. Novel classes of analgesics have recently been introduced, but many patients suffer from acute pain in settings where the availability of intravenous (IV) access may be limited, so there remains a clinical need for rapid-acting, potent analgesics that do not require an invasive route of delivery. A sublingual sufentanil tablet (SST), dispensed using a single-dose applicator, is in development for treatment of moderate-to-severe acute pain in a medically-supervised setting. Objective: The primary objective of this study was to demonstrate the repeat-dose efficacy, safety and tolerability of sufentanil 20 mcg and 30 mcg sublingual tablets compared to placebo for the management of acute pain as determined by the time-weighted sum of pain intensity differences (SPID) to baseline over the 12-hour study period (SPID12). Key secondary efficacy variables included SPID over the first hour (SPID1), Total pain relief over the 12-hour study period (TOTPAR12), time to perceived pain relief (PR) and time to meaningful PR. Safety variables consisted of adverse events (AE), vital signs, oxygen saturation and early termination. Methods: In this Phase 2, double-blind, dose-finding study, an equal number of male and female patients were randomly assigned in a 2:2:1 ratio to SST 20 mcg, SS 30 mcg or placebo, respectively, following bunionectomy. Study drug was dosed as needed, but not more frequently than hourly. Rescue medication was available as needed. The primary endpoint was the Summed Pain Intensity Difference to baseline over 12h (SPIDI2). Safety was assessed by continuous oxygen saturation monitoring and adverse event reporting. Results: 101 patients (51 Male/50 Female) were randomized, 100 received study treatment (intent-to-treat [ITT] population), and 91 completed the study. Reasons for early discontinuation were lack of efficacy (6), adverse events (2) and drug-dosing error (1). Mean age was 42.5 years. For the ITT population, SST 30 mcg was superior to placebo (p=0.003) for the SPID12. SPID12 scores in the active groups were superior for both male (ANOVA overall p-value =0.038) and female (ANOVA overall p-value=0.005) patients. Statistically significant differences in favour of sublingual sufentanil were also observed between the SST 30mcg and placebo group for SPID1(p<0.001), TOTPAR12(p=0.002), time to perceived PR (p=0.023) and time to meaningful PR (p=0.010). Nausea, vomiting and somnolence were more frequent in the sufentanil groups but there were no significant differences between treatment arms for the proportion of patients who prematurely terminated due to AE or inadequate analgesia. Conclusions: Sufentanil tablets dispensed sublingually using a single-dose applicator is in development for treatment of patients with moderate-to-severe acute pain in a medically-supervised setting where immediate IV access is limited. When administered sublingually, sufentanil’s pharmacokinetic profile and non-invasive delivery makes it a useful alternative to IM or IV dosing.

Keywords: acute pain, pain management, sublingual, sufentanil

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Authors: Mazaher Yarmohamadi-Vasel, Ali Reza Modarresi-Alama, Sahar Shabzendedara

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Purpose/Objectives: The first purpose was synthesize Poly(N-(sulfophenyl)aniline) nanoflowers (PSANFLs) and Poly(N-(sulfophenyl)aniline) nanofibers/titanium dioxide nanoparticles ((PSANFs/TiO2NPs) by a solid-state mechano-chemical reaction and template-free method and use them in hybrid solar cell. Also, our second aim was to increase the solubility and the processability of conjugated nanomaterials in water through polar functionalized materials. poly[N-(4-sulfophenyl)aniline] is easily soluble in water because of the presence of polar groups of sulfonic acid in the polymer chain. Materials/Methods: Iron (III) chloride hexahydrate (FeCl3∙6H2O) were bought from Merck Millipore Company. Titanium oxide nanoparticles (TiO2, <20 nm, anatase) and Sodium diphenylamine-4-sulfonate (99%) were bought from Sigma-Aldrich Company. Titanium dioxide nanoparticles paste (PST-20T) was prepared from Sharifsolar Co. Conductive glasses coated with indium tin oxide (ITO) were bought from Xinyan Technology Co (China). For the first time we used the solid-state mechano-chemical reaction and template-free method to synthesize Poly(N-(sulfophenyl)aniline) nanoflowers. Moreover, for the first time we used the same technique to synthesize nanocomposite of Poly(N-(sulfophenyl)aniline) nanofibers and titanium dioxide nanoparticles (PSANFs/TiO2NPs) also for the first time this nanocomposite was synthesized. Examining the results of electrochemical calculations energy gap obtained by CV curves and UV–vis spectra demonstrate that PSANFs/TiO2NPs nanocomposite is a p-n type material that can be used in photovoltaic cells. Doctor blade method was used to creat films for three kinds of hybrid solar cells in terms of different patterns like ITO│TiO2NPs│Semiconductor sample│Al. In the following, hybrid photovoltaic cells in bilayer and bulk heterojunction structures were fabricated as ITO│TiO2NPs│PSANFLs│Al and ITO│TiO2NPs│PSANFs /TiO2NPs│Al, respectively. Fourier-transform infrared spectra, field emission scanning electron microscopy (FE-SEM), ultraviolet-visible spectra, cyclic voltammetry (CV) and electrical conductivity were the analysis that used to characterize the synthesized samples. Results and Conclusions: FE-SEM images clearly demonstrate that the morphology of the synthesized samples are nanostructured (nanoflowers and nanofibers). Electrochemical calculations of band gap from CV curves demonstrated that the forbidden band gap of the PSANFLs and PSANFs/TiO2NPs nanocomposite are 2.95 and 2.23 eV, respectively. I–V characteristics of hybrid solar cells and their power conversion efficiency (PCE) under 100 mWcm−2 irradiation (AM 1.5 global conditions) were measured that The PCE of the samples were 0.30 and 0.62%, respectively. At the end, all the results of solar cell analysis were discussed. To sum up, PSANFLs and PSANFLs/TiO2NPs were successfully synthesized by an affordable and straightforward mechanochemical reaction in solid-state under the green condition. The solubility and processability of the synthesized compounds have been improved compared to the previous work. We successfully fabricated hybrid photovoltaic cells of synthesized semiconductor nanostructured polymers and TiO2NPs as different architectures. We believe that the synthesized compounds can open inventive pathways for the development of other Poly(N-(sulfophenyl)aniline based hybrid materials (nanocomposites) proper for preparing new generation solar cells.

Keywords: mechanochemical synthesis, PSANFLs, PSANFs/TiO2NPs, solar cell

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Authors: Samira Hamiditehrani

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Automated vehicles (AVs) are emerging technologies that could potentially offer a wide range of opportunities and challenges for the transportation sector. The advent of AV technology has also resulted in new business models in shared mobility services where many ride hailing and car sharing companies are developing on-demand AVs including shared automated vehicles (SAVs) and pooled automated vehicles (Pooled AVs). SAVs and Pooled AVs could provide alternative shared mobility services which encourage sustainable transport systems, mitigate traffic congestion, and reduce automobile dependency. However, the success of on-demand AVs in addressing major transportation policy issues depends on whether and how the public adopts them as regular travel modes. To identify conditions under which individuals may adopt on-demand AVs, previous studies have applied human behavior and technology acceptance theories, where Theory of Planned Behavior (TPB) has been validated and is among the most tested in on-demand AV research. In this respect, this study has three objectives: (a) to propose and validate a theoretical model for behavioral intention to use SAVs and Pooled AVs by extending the original TPB model; (b) to identify the characteristics of early adopters of SAVs, who prefer to have a shorter and private ride, versus prospective users of Pooled AVs, who choose more affordable but longer and shared trips; and (c) to investigate Canadians’ intentions to adopt on-demand AVs for regular trips. Toward this end, this study uses data from an online survey (n = 3,622) of workers or adult students (18 to 75 years old) conducted in October and November 2021 for six major Canadian metropolitan areas: Toronto, Vancouver, Ottawa, Montreal, Calgary, and Hamilton. To accomplish the goals of this study, a base bivariate ordered probit model, in which both SAV and Pooled AV adoptions are estimated as ordered dependent variables, alongside a full structural equation modeling (SEM) system are estimated. The findings of this study indicate that affective motivations such as attitude towards AV technology, perceived privacy, and subjective norms, matter more than sociodemographic and travel behavior characteristic in adopting on-demand AVs. Also, the results of second objective provide evidence that although there are a few affective motivations, such as subjective norms and having ample knowledge, that are common between early adopters of SAVs and PooledAVs, many examined motivations differ among SAV and Pooled AV adoption factors. In other words, motivations influencing intention to use on-demand AVs differ among the service types. Likewise, depending on the types of on-demand AVs, the sociodemographic characteristics of early adopters differ significantly. In general, findings paint a complex picture with respect to the application of constructs from common technology adoption models to the study of on-demand AVs. Findings from the final objective suggest that policymakers, planners, the vehicle and technology industries, and the public at large should moderate their expectations that on-demand AVs may suddenly transform the entire transportation sector. Instead, this study suggests that SAVs and Pooled AVs (when they entire the Canadian market) are likely to be adopted as supplementary mobility tools rather than substitutions for current travel modes

Keywords: automated vehicles, Canadian perception, theory of planned behavior, on-demand AVs

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Authors: John E. Boberg, Steven J. Bourgeois

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The decline in student engagement and motivation through the middle years is well documented and clearly associated with a decline in mathematics achievement that persists through high school. To combat this trend and, very often, to meet high-stakes accountability standards, a growing number of parents, teachers, and schools have implemented various methods to incentivize learning. However, according to Self-Determination Theory, forms of incentivized learning such as public praise, tangible rewards, or threats of punishment tend to undermine intrinsic motivation and learning. By focusing on external forms of motivation that thwart autonomy in children, adults also potentially threaten relatedness measures such as trust and emotional engagement. Furthermore, these controlling motivational techniques tend to promote shallow forms of cognitive engagement at the expense of more effective deep processing strategies. Therefore, any short-term gains in apparent engagement or test scores are overshadowed by long-term diminished motivation, resulting in inauthentic approaches to learning and lower achievement. The current study focuses on the relationships between student trust, engagement, and motivation during these crucial years as students transition from elementary to middle school. In order to test the effects of controlled motivational techniques on achievement in mathematics, this quantitative study was conducted on a convenience sample of 22 elementary and middle schools from a single public charter school district in the south-central United States. The study employed multi-source data from students (N = 1,054), parents (N = 7,166), and teachers (N = 356), along with student achievement data and contextual campus variables. Cross-sectional questionnaires were used to measure the students’ self-regulated learning, emotional and cognitive engagement, and trust in teachers. Parents responded to a single item on incentivizing the academic performance of their child, and teachers responded to a series of questions about their acceptance of various incentive strategies. Structural equation modeling (SEM) was used to evaluate model fit and analyze the direct and indirect effects of the predictor variables on achievement. Although a student’s trust in teacher positively predicted both emotional and cognitive engagement, none of these three predictors accounted for any variance in achievement in mathematics. The parents’ use of incentives, on the other hand, predicted a student’s perception of his or her controlled motivation, and these two variables had significant negative effects on achievement. While controlled motivation had the greatest effects on achievement, parental incentives demonstrated both direct and indirect effects on achievement through the students’ self-reported controlled motivation. Comparing upper elementary student data with middle-school student data revealed that controlling forms of motivation may be taking their toll on student trust and engagement over time. While parental incentives positively predicted both cognitive and emotional engagement in the younger sub-group, such forms of controlling motivation negatively predicted both trust in teachers and emotional engagement in the middle-school sub-group. These findings support the claims, posited by Self-Determination Theory, about the dangers of incentivizing learning. Short-term gains belie the underlying damage to motivational processes that lead to decreased intrinsic motivation and achievement. Such practices also appear to thwart basic human needs such as relatedness.

Keywords: controlled motivation, student engagement, incentivized learning, mathematics achievement, self-determination theory, student trust

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Authors: Catherine Vasnetsov, Victor Vasnetsov

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Context: Thermo-responsive polymers are materials that undergo significant changes in their physical properties in response to temperature changes. These polymers have gained significant attention in research due to their potential applications in various industries and medicine. However, the molecular mechanisms underlying their behavior are not well understood, particularly in relation to cosolvency, which is crucial for practical applications. Research Aim: This study aimed to theoretically investigate the phenomenon of cosolvency in long-chain polymers using the Flory-Huggins statistical-mechanical framework. The main objective was to understand the interactions between the polymer, solvent, and cosolvent under different conditions. Methodology: The research employed a combination of Monte Carlo computer simulations and advanced machine-learning methods. The Flory-Huggins mean field theory was used as the basis for the simulations. Spinodal graphs and ternary plots were utilized to develop an initial computer model for predicting polymer behavior. Molecular dynamic simulations were conducted to mimic real-life polymer systems. Machine learning techniques were incorporated to enhance the accuracy and reliability of the simulations. Findings: The simulations revealed that the addition of very low or very high volumes of cosolvent molecules resulted in smaller radii of gyration for the polymer, indicating poor miscibility. However, intermediate volume fractions of cosolvent led to higher radii of gyration, suggesting improved miscibility. These findings provide a possible microscopic explanation for the cosolvency phenomenon in polymer systems. Theoretical Importance: This research contributes to a better understanding of the behavior of thermo-responsive polymers and the role of cosolvency. The findings provide insights into the molecular mechanisms underlying cosolvency and offer specific predictions for future experimental investigations. The study also presents a more rigorous analysis of the Flory-Huggins free energy theory in the context of polymer systems. Data Collection and Analysis Procedures: The data for this study was collected through Monte Carlo computer simulations and molecular dynamic simulations. The interactions between the polymer, solvent, and cosolvent were analyzed using the Flory-Huggins mean field theory. Machine learning techniques were employed to enhance the accuracy of the simulations. The collected data was then analyzed to determine the impact of cosolvent volume fractions on the radii of gyration of the polymer. Question Addressed: The research addressed the question of how cosolvency affects the behavior of long-chain polymers. Specifically, the study aimed to investigate the interactions between the polymer, solvent, and cosolvent under different volume fractions and understand the resulting changes in the radii of gyration. Conclusion: In conclusion, this study utilized theoretical modeling and computer simulations to investigate the phenomenon of cosolvency in long-chain polymers. The findings suggest that moderate cosolvent volume fractions can lead to improved miscibility, as indicated by higher radii of gyration. These insights contribute to a better understanding of the molecular mechanisms underlying cosolvency in polymer systems and provide predictions for future experimental studies. The research also enhances the theoretical analysis of the Flory-Huggins free energy theory.

Keywords: molecular modelling, flory-huggins, cosolvency, stimuli-responsive polymers

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Authors: S. Candamano, A. Iorfida, L. Pagnotta, F. Crea

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Basalt fabric reinforced cementitious composites (FRCM) have attracted great attention because they result in being effective in structural strengthening and eco-efficient. In this study, authors investigate their mechanical behavior when an alkali-activated binder, with tuned properties and containing high amounts of industrial by-products, such as ground granulated blast furnace slag, is used. Reinforcement is made up of a balanced, coated bidirectional fabric made out of basalt fibres and stainless steel micro-wire, with a mesh size of 8x8 mm and an equivalent design thickness equal to 0.064 mm. Mortars mixes have been prepared by maintaining constant the water/(reactive powders) and sand/(reactive powders) ratios at 0.53 and 2.7 respectively. Tensile tests were carried out on composite specimens of nominal dimensions equal to 500 mm x 50 mm x 10 mm, with 6 embedded rovings in the loading direction. Direct shear tests (DST), aimed to the stress-transfer mechanism and failure modes of basalt-FRCM composites, were carried out on brickwork substrate using an externally bonded basalt-FRCM composite strip 10 mm thick, 50 mm wide and a bonded length of 300 mm. Mortars exhibit, after 28 days of curing, a compressive strength of 32 MPa and a flexural strength of 5.5 MPa. Main hydration product is a poorly crystalline CASH gel. The constitutive behavior of the composite has been identified by means of direct tensile tests, with response curves showing a tri-linear behavior. The first linear phase represents the uncracked (I) stage, the second (II) is identified by crack development and the third (III) corresponds to cracked stage, completely developed up to failure. All specimens exhibit a crack pattern throughout the gauge length and failure occurred as a result of sequential tensile failure of the fibre bundles, after reaching the ultimate tensile strength. The behavior is mainly governed by cracks development (II) and widening (III) up to failure. The main average values related to the stages are σI= 173 MPa and εI= 0.026% that are the stress and strain of the transition point between stages I and II, corresponding to the first mortar cracking; σu = 456 MPa and εu= 2.20% that are the ultimate tensile strength and strain, respectively. The tensile modulus of elasticity in stage III is EIII= 41 GPa. All single-lap shear test specimens failed due to composite debonding. It occurred at the internal fabric-to-matrix interface, and it was the result of fracture of the matrix between the fibre bundles. For all specimens, transversal cracks were visible on the external surface of the composite and involved only the external matrix layer. This cracking appears when the interfacial shear stresses increase and slippage of the fabric at the internal matrix layer interface occurs. Since the external matrix layer is bonded to the reinforcement fabric, it translates with the slipped fabric. Average peak load around 945 N, peak stress around 308 MPa, and global slip around 6 mm were measured. The preliminary test results allow affirming that Alkali Activated Binders can be considered a potentially valid alternative to traditional mortars in designing FRCM composites.

Keywords: alkali activated binders, basalt-FRCM composites, direct shear tests, structural strengthening

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Authors: Saif Al Ghafri, Thomas Hughes, Armand Karimi, Kumarini Seneviratne, Jordan Oakley, Michael Johns, Eric F. May

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Knowledge of the thermophysical properties of complex mixtures at extreme conditions of pressure and temperature have always been essential to the Liquefied Natural Gas (LNG) industry’s evolution because of the tremendous technical challenges present at all stages in the supply chain from production to liquefaction to transport. Each stage is designed using predictions of the mixture’s properties, such as density, viscosity, surface tension, heat capacity and phase behaviour as a function of temperature, pressure, and composition. Unfortunately, currently available models lead to equipment over-designs of 15% or more. To achieve better designs that work more effectively and/or over a wider range of conditions, new fundamental property data are essential, both to resolve discrepancies in our current predictive capabilities and to extend them to the higher-pressure conditions characteristic of many new gas fields. Furthermore, innovative experimental techniques are required to measure different thermophysical properties at high pressures and over a wide range of temperatures, including near the mixture’s critical points where gas and liquid become indistinguishable and most existing predictive fluid property models used breakdown. In this work, we present a wide range of experimental measurements made for different binary and ternary mixtures relevant to LNG processing, with a particular focus on viscosity, surface tension, heat capacity, bubble-points and density. For this purpose, customized and specialized apparatus were designed and validated over the temperature range (200 to 423) K at pressures to 35 MPa. The mixtures studied were (CH4 + C3H8), (CH4 + C3H8 + CO2) and (CH4 + C3H8 + C7H16); in the last of these the heptane contents was up to 10 mol %. Viscosity was measured using a vibrating wire apparatus, while mixture densities were obtained by means of a high-pressure magnetic-suspension densimeter and an isochoric cell apparatus; the latter was also used to determine bubble-points. Surface tensions were measured using the capillary rise method in a visual cell, which also enabled the location of the mixture critical point to be determined from observations of critical opalescence. Mixture heat capacities were measured using a customised high-pressure differential scanning calorimeter (DSC). The combined standard relative uncertainties were less than 0.3% for density, 2% for viscosity, 3% for heat capacity and 3 % for surface tension. The extensive experimental data gathered in this work were compared with a variety of different advanced engineering models frequently used for predicting thermophysical properties of mixtures relevant to LNG processing. In many cases the discrepancies between the predictions of different engineering models for these mixtures was large, and the high quality data allowed erroneous but often widely-used models to be identified. The data enable the development of new or improved models, to be implemented in process simulation software, so that the fluid properties needed for equipment and process design can be predicted reliably. This in turn will enable reduced capital and operational expenditure by the LNG industry. The current work also aided the community of scientists working to advance theoretical descriptions of fluid properties by allowing to identify deficiencies in theoretical descriptions and calculations.

Keywords: LNG, thermophysical, viscosity, density, surface tension, heat capacity, bubble points, models

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Authors: Sylvie Michel, Sylvie Gerbaix, Marc Bidan

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Artificial intelligence (AI) can be held accountable for its detrimental impacts. This question gains heightened relevance given AI's pervasive reach across various domains, magnifying its power and potential. The expanding influence of AI raises fundamental ethical inquiries, primarily centering on biases, responsibility, and transparency. This encompasses discriminatory biases arising from algorithmic criteria or data, accidents attributed to autonomous vehicles or other systems, and the imperative of transparent decision-making. This article aims to stimulate reflection on AI accountability, denoting the necessity to elucidate the effects it generates. Accountability comprises two integral aspects: adherence to legal and ethical standards and the imperative to elucidate the underlying operational rationale. The objective is to initiate a reflection on the obstacles to this "accountability," facing the challenges of the complexity of artificial intelligence's system and its effects. Then, this article proposes to mobilize Edgar Morin's complex thought to encompass and face the challenges of this complexity. The first contribution is to point out the challenges posed by the complexity of A.I., with fractional accountability between a myriad of human and non-human actors, such as software and equipment, which ultimately contribute to the decisions taken and are multiplied in the case of AI. Accountability faces three challenges resulting from the complexity of the ethical issues combined with the complexity of AI. The challenge of the non-neutrality of algorithmic systems as fully ethically non-neutral actors is put forward by a revealing ethics approach that calls for assigning responsibilities to these systems. The challenge of the dilution of responsibility is induced by the multiplicity and distancing between the actors. Thus, a dilution of responsibility is induced by a split in decision-making between developers, who feel they fulfill their duty by strictly respecting the requests they receive, and management, which does not consider itself responsible for technology-related flaws. Accountability is confronted with the challenge of transparency of complex and scalable algorithmic systems, non-human actors self-learning via big data. A second contribution involves leveraging E. Morin's principles, providing a framework to grasp the multifaceted ethical dilemmas and subsequently paving the way for establishing accountability in AI. When addressing the ethical challenge of biases, the "hologrammatic" principle underscores the imperative of acknowledging the non-ethical neutrality of algorithmic systems inherently imbued with the values and biases of their creators and society. The "dialogic" principle advocates for the responsible consideration of ethical dilemmas, encouraging the integration of complementary and contradictory elements in solutions from the very inception of the design phase. Aligning with the principle of organizing recursiveness, akin to the "transparency" of the system, it promotes a systemic analysis to account for the induced effects and guides the incorporation of modifications into the system to rectify deviations and reintroduce modifications into the system to rectify its drifts. In conclusion, this contribution serves as an inception for contemplating the accountability of "artificial intelligence" systems despite the evident ethical implications and potential deviations. Edgar Morin's principles, providing a lens to contemplate this complexity, offer valuable perspectives to address these challenges concerning accountability.

Keywords: accountability, artificial intelligence, complexity, ethics, explainability, transparency, Edgar Morin

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Authors: Tobias Huwer, Thomas Bobek, Gunter Spöcker

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Driving forces for enhancements in production are trends like digitalization and individualized production. Currently, such developments are restricted to assembly parts. Thus, complex freeform surfaces are not addressed in this context. The need for efficient use of resources and near-net-shape production will require individualized production of complex shaped workpieces. Due to variations between nominal model and actual geometry, this can lead to changes in operations in Computer-aided process planning (CAPP) to make CAPP manageable for an adaptive serial production. In this context, 3D CAD data can be a key to realizing that objective. Along with developments in the geometrical adaptation, a preceding inspection method based on CAD data is required to support the process planner by finding objective criteria to make decisions about the adaptive manufacturability of workpieces. Nowadays, this kind of decisions is depending on the experience-based knowledge of humans (e.g. process planners) and results in subjective decisions – leading to a variability of workpiece quality and potential failure in production. In this paper, we present an automatic part inspection method, based on design and measurement data, which evaluates actual geometries of single workpiece preforms. The aim is to automatically determine the suitability of the current shape for further machining, and to provide a basis for an objective decision about subsequent adaptive manufacturability. The proposed method is realized by a workflow-based approach, keeping in mind the requirements of industrial applications. Workflows are a well-known design method of standardized processes. Especially in applications like aerospace industry standardization and certification of processes are an important aspect. Function blocks, providing a standardized, event-driven abstraction to algorithms and data exchange, will be used for modeling and execution of inspection workflows. Each analysis step of the inspection, such as positioning of measurement data or checking of geometrical criteria, will be carried out by function blocks. One advantage of this approach is its flexibility to design workflows and to adapt algorithms specific to the application domain. In general, within the specified tolerance range it will be checked if a geometrical adaption is possible. The development of particular function blocks is predicated on workpiece specific information e.g. design data. Furthermore, for different product lifecycle phases, appropriate logics and decision criteria have to be considered. For example, tolerances for geometric deviations are different in type and size for new-part production compared to repair processes. In addition to function blocks, appropriate referencing systems are important. They need to support exact determination of position and orientation of the actual geometries to provide a basis for precise analysis. The presented approach provides an inspection methodology for adaptive and part-individual process chains. The analysis of each workpiece results in an inspection protocol and an objective decision about further manufacturability. A representative application domain is the product lifecycle of turbine blades containing a new-part production and a maintenance process. In both cases, a geometrical adaptation is required to calculate individual production data. In contrast to existing approaches, the proposed initial inspection method provides information to decide between different potential adaptive machining processes.

Keywords: adaptive, CAx, function blocks, turbomachinery

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Authors: Hakimeh Masoudigavgani

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Since manufacturing firms deplete non-renewable resources and pollute air, soil, and water in greatly unsustainable manner, industrial activities or production of products are considered to be a key contributor to adverse environmental impacts. Hence, management strategies and approaches that involve an effective supply chain decision process in a manufacturing sector could be extremely significant to the application of environmental initiatives. Green manufacturing (GM) is one of these strategies which minimises negative effects on the environment through reducing greenhouse gas emissions, waste, and the consumption of energy and natural resources. This paper aims to explore what greening methods and mechanisms could be applied in the manufacturing supply chain and what are the outcomes of adopting these methods in terms of abating environmental burdens? The study is an interpretive research with an exploratory approach, using thematic analysis by coding text, breaking down and grouping the content of collected literature into various themes and categories. It is found that green supply chain could be attained through execution of some pre-production strategies including green building, eco-design, and green procurement as well as a number of in-production and post-production strategies involving green manufacturing and green logistics. To achieve an effective GM, the pre-production strategies are suggested to be employed. This paper defines GM as (1) the analysis of the ecological impacts generated by practices, products, production processes, and operational functions, and (2) the implementation of greening methods to reduce damaging influences of them on the natural environment. Analysis means assessing, monitoring, and auditing of practices in order to measure and pinpoint their harmful impacts. Moreover, greening methods involved within GM (arranged in order from the least to the most level of environmental compliance and techniques) consist of: •product stewardship (e.g. less use of toxic, non-renewable, and hazardous materials in the manufacture of the product; and stewardship of the environmental problems with regard to the product in all production, use, and end-of-life stages); •process stewardship (e.g. controlling carbon emission, energy and resources usage, transportation method, and disposal; reengineering polluting processes; recycling waste materials generated in production); •lean and clean production practices (e.g. elimination of waste, materials replacement, materials reduction, resource-efficient consumption, energy-efficient usage, emission reduction, managerial assessment, waste re-use); •use of eco-industrial parks (e.g. a shared warehouse, shared logistics management system, energy co-generation plant, effluent treatment). However, the focus of this paper is only on methods related to the in-production phase and needs further research on both pre-production and post-production environmental innovations. The outlined methods in this investigation may possibly be taken into account by policy/decision makers. Additionally, the proposed future research direction and identified gaps can be filled by scholars and researchers. The paper compares and contrasts a variety of viewpoints and enhances the body of knowledge by building a definition for GM through synthesising literature and categorising the strategic concept of greening methods, drivers, barriers, and successful implementing tactics.

Keywords: green manufacturing (GM), product stewardship, process stewardship, clean production, eco-industrial parks (EIPs)

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Authors: Karlee J. Hall, Mark Laylor, Jessy Varghese, Paula Polastri, Karen Van Ooteghem, William McIlroy

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Balance training is a common part of physiotherapy treatment and often involves a set of proprioceptive exercises which the patient carries out in the clinic and as part of their exercise program. Understanding all contributing factors to altered balance is of utmost importance to the clinical success of treatment of balance dysfunctions. A critical role for the autonomic nervous system (ANS) in the control of balance reactions has been proposed previously, with evidence for potential involvement being inferred from the observation of phasic galvanic skin responses (GSR) evoked by external balance perturbations. The current study explored whether the coupling between ANS reactivity and balance reactions would be observed during spontaneously occurring instability while standing, including standard positions typical of physiotherapy balance assessments. It was hypothesized that time-varying changes in GSR (ANS reactivity) would be associated with time-varying changes in the mediolateral center of pressure (ML-COP) (somatomotor reactivity). Nine individuals (5 females, 4 males, aged 19-37 years) were recruited. To induce varying balance demands during standing, the study compared ML-COP and GSR data across different task conditions varying the availability of vision and width of the base of support. Subjects completed 3, 30-second trials for each of the following stance conditions: standard, narrow, and tandem eyes closed, tandem eyes open, tandem eyes open with dome to shield visual input, and restricted peripheral visual field. ANS activity was evaluated by measures of GSR recorded from Ag-AgCl electrodes on the middle phalanges of digits 2 and 4 on the left hand; balance measures include ML-COP excursion frequency and amplitude recorded from two force plates embedded in the floor underneath each foot. Subjects were instructed to stand as still as possible with arms crossed in front of their chest. When comparing mean task differences across subjects, there was an expected increase in postural sway from tasks with a wide stance and no sensory restrictions (least challenging) to those with a narrow stance and no vision (most challenging). The correlation analysis revealed a significant positive relationship between ML-COP variability and GSR variability when comparing across tasks (r=0.94, df=5, p < 0.05). In addition, correlations coincided within each subject and revealed a significant positive correlation in 7 participants (r= 0.47, 0.57, 0.62, 0.62, 0.81, 0.64, 0.69 respectively, df=19, p < 0.05) and no significant relationship in 2 participants (r=0.36, 0.29 respectively, df=19, p > 0.05). The current study revealed a significant relationship between ML-COP and GSR during balance tasks, revealing the ANS reactivity associated with naturally occurring instability when standing still, which is proportional to the degree of instability. Understanding the link between ANS activity and control of COP is an important step forward in the enhancement of assessment of contributing factors to poor balance and treatment of balance dysfunctions. The next steps will explore the temporal association between the time-varying changes in COP and GSR to establish if the ANS reactivity phase leads or lags the evoked motor reactions, as well as exploration of potential biomarkers for use in screening of ANS activity as a contributing factor to altered balance control clinically.

Keywords: autonomic nervous system, balance control, center of pressure, somatic nervous system

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Authors: Deon Bezuidenhout

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Pre-seeding with autologous endothelial cells improves the long-term patency of synthetic vascular grafts levels obtained with autografts, but is limited to a single centre due to resource, time and other constraints. Spontaneous in vivo endothelialization would obviate the need for pre-seeding, but has been shown to be absent in man due to limited transanastomotic and fallout healing, and the lack of transmural ingrowth due to insufficient porosity. Two types of graft scaffolds with increased interconnected porosity for improved tissue ingrowth and healing are thus proposed and described. Foam-type polyurethane (PU) scaffolds with small, medium and large, interconnected pores were made by phase inversion and spherical porogen extraction, with and without additional surface modification with covalently attached heparin and subsequent loading with and delivery of growth factors. Fibrillar scaffolds were made either by standard electrospinning using degradable PU (Degrapol®), or by dual electrospinning using non-degradable PU. The latter process involves sacrificial fibres that are co-spun with structural fibres and subsequently removed to increased porosity and pore size. Degrapol samples were subjected to in vitro degradation, and all scaffold types were evaluated in vivo for tissue ingrowth and vascularization using rat subcutaneous model. The foam scaffolds were additionally evaluated in a circulatory (rat infrarenal aortic interposition) model that allows for the grafts to be anastomotically and/or ablumenally isolated to discern and determine endothelialization mode. Foam-type grafts with large (150 µm) pores showed improved subcutaneous healing in terms of vascularization and inflammatory response over smaller pore sizes (60 and 90µm), and vascularization of the large porosity scaffolds was significantly increased by more than 70% by heparin modification alone, and by 150% to 400% when combined with growth factors. In the circulatory model, extensive transmural endothelialization (95±10% at 12 w) was achieved. Fallout healing was shown to be sporadic and limited in groups that were ablumenally isolated to prevent transmural ingrowth (16±30% wrapped vs. 80±20% control; p<0.002). Heparinization and GF delivery improved both mural vascularization and lumenal endothelialization. Degrapol electrospun scaffolds showed decrease in molecular mass and corresponding tensile strength over the first 2 weeks, but very little decrease in mass over the 4w test period. Studies on the effect of tissue ingrowth with and without concomitant degradation of the scaffolds, are being used to develop material models for the finite element modelling. In the case of the dual-spun scaffolds, the PU fibre fraction could be controlled shown to vary linearly with porosity (P = −0.18FF +93.5, r2=0.91), which in turn showed inverse linear correlation with tensile strength and elastic modulus (r2 > 0.96). Calculated compliance and burst pressures of the scaffolds increased with fibre fraction, and compliances matching the human popliteal artery (5-10 %/100 mmHg), and high burst pressures (> 2000 mmHg) could be achieved. Increasing porosity (76 to 82 and 90%) resulted in increased tissue ingrowth from 33±7 to 77±20 and 98±1% after 28d. Transmural endothelialization of highly porous foamed grafts is achievable in a circulatory model, and the enhancement of porosity and tissue ingrowth may hold the key the development of spontaneously endothelializing electrospun grafts.

Keywords: electrospinning, endothelialization, porosity, scaffold, vascular graft

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Authors: Ankit Khurana

Abstract:

The sufficient heat storage capacity or ability to dissipate heat is the most decisive parameter to have an effective and efficient functioning of Friction-based Brake Disc systems. The primary aim of the research was to analyse the effect of multiple coatings on lightweight disk rotors surface which not only alleviates the mass of vehicle & also, augments heat transfer. This research is projected to aid the automobile fraternity with an enunciated view over the thermal aspects in a braking system. The results of the project indicate that with the advent of modern coating technologies a brake system’s thermal curtailments can be removed and together with forced convection, heat transfer processes can see a drastic improvement leading to increased lifetime of the brake rotor. Other advantages of modifying the surface of a lightweight rotor substrate will be to reduce the overall weight of the vehicle, decrease the risk of thermal brake failure (brake fade and fluid vaporization), longer component life, as well as lower noise and vibration characteristics. A mathematical model was constructed in MATLAB which encompassing the various thermal characteristics of the proposed coatings and substrate materials required to approximate the heat flux values in a free and forced convection environment; resembling to a real-time braking phenomenon which could easily be modelled into a full cum scaled version of the alloy brake rotor part in ABAQUS. The finite element of a brake rotor was modelled in a constrained environment such that the nodal temperature between the contact surfaces of the coatings and substrate (Wrought Aluminum alloy) resemble an amalgamated solid brake rotor element. The initial results obtained were for a Plasma Electrolytic Oxidized (PEO) substrate wherein the Aluminum alloy gets a hard ceramic oxide layer grown on its transitional phase. The rotor was modelled and then evaluated in real-time for a constant ‘g’ braking event (based upon the mathematical heat flux input and convective surroundings), which reflected the necessity to deposit a conducting coat (sacrificial) above the PEO layer in order to inhibit thermal degradation of the barrier coating prematurely. Taguchi study was then used to bring out certain critical factors which may influence the maximum operating temperature of a multi-coated brake disc by simulating brake tests: a) an Alpine descent lasting 50 seconds; b) an Autobahn stop lasting 3.53 seconds; c) a Six–high speed repeated stop in accordance to FMVSS 135 lasting 46.25 seconds. Thermal Barrier coating thickness and Vane heat transfer coefficient were the two most influential factors and owing to their design and manufacturing constraints a final optimized model was obtained which survived the 6-high speed stop test as per the FMVSS -135 specifications. The simulation data highlighted the merits for preferring Wrought Aluminum alloy 7068 over Grey Cast Iron and Aluminum Metal Matrix Composite in coherence with the multiple coating depositions.

Keywords: lightweight brakes, surface modification, simulated braking, PEO, aluminum

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Authors: João Coutinho-Rodrigues, Nuno Sousa, Luís Alçada-Almeida

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Transportation infrastructure systems are fundamental in modern society and economy. However, they need modernizing, maintaining, and reinforcing interventions which require large investments. In many countries, accumulated intervention delays arise from aging and intense use, being magnified by financial constraints of the past. The decision problem of managing the renewal of large backlogs is common to several types of important transportation infrastructures (e.g., railways, roads). This problem requires considering financial aspects as well as operational constraints under a multidimensional framework. The present research introduces a linear programming multiobjective model for managing railway infrastructure asset renewal. The model aims at minimizing three objectives: (i) yearly investment peak, by evenly spreading investment throughout multiple years; (ii) total cost, which includes extra maintenance costs incurred from renewal backlogs; (iii) priority delays related to work start postponements on the higher priority railway sections. Operational constraints ensure that passenger and freight services are not excessively delayed from having railway line sections under intervention. Achieving a balanced annual investment plan, without compromising the total financial effort or excessively postponing the execution of the priority works, was the motivation for pursuing the research which is now presented. The methodology, inspired by a real case study and tested with real data, reflects aspects of the practice of an infrastructure management company and is generalizable to different types of infrastructure (e.g., railways, highways). It was conceived for treating renewal interventions in infrastructure assets, which is a railway network may be rails, ballasts, sleepers, etc.; while a section is under intervention, trains must run at reduced speed, causing delays in services. The model cannot, therefore, allow for an accumulation of works on the same line, which may cause excessively large delays. Similarly, the lines do not all have the same socio-economic importance or service intensity, making it is necessary to prioritize the sections to be renewed. The model takes these issues into account, and its output is an optimized works schedule for the renewal project translatable in Gantt charts The infrastructure management company provided all the data for the first test case study and validated the parameterization. This case consists of several sections to be renewed, over 5 years and belonging to 17 lines. A large instance was also generated, reflecting a problem of a size similar to the USA railway network (considered the largest one in the world), so it is not expected that considerably larger problems appear in real life; an average of 25 years backlog and ten years of project horizon was considered. Despite the very large increase in the number of decision variables (200 times as large), the computational time cost did not increase very significantly. It is thus expectable that just about any real-life problem can be treated in a modern computer, regardless of size. The trade-off analysis shows that if the decision maker allows some increase in max yearly investment (i.e., degradation of objective ii), solutions improve considerably in the remaining two objectives.

Keywords: transport infrastructure, asset renewal, railway maintenance, multiobjective modeling

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Authors: Rachid Essamoud, Abdelkrim Afenzar, Ahmed Belqadi

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During the Early Mesozoic, the northwestern part of the African continent was affected by initial fracturing associated with the early stages of the opening of the Central Atlantic (Atlantic Rift). During this rifting phase, the Moroccan Meseta experienced an extensive tectonic regime. This extension favored the formation of a set of rift-type basins, including the Mohammedia-Benslimane-ElGara-Berrechid basin. Thus, it is essential to know the nature of the deposits in this basin and their evolution over time as well as their relationship with the basaltic effusion of the Central Atlantic Magmatic Province (CAMP). These deposits are subdivided into two large series: The Lower clay-salt series attributed to the Triassic and the Upper clay-salt series attributed to the Liassic. The two series are separated by the Upper Triassic-Lower Liassic basaltic complex. The detailed sedimentological analysis made it possible to characterize four mega-sequences, fifteen types of facies and eight architectural elements and facies associations in the Triassic series. A progressive decrease observed in paleo-slope over time led to the evolution of the paleoenvironment from a proximal system of alluvial fans to a braided fluvial style, then to an anastomosed system. These environments eventually evolved into an alluvial plain associated with a coastal plain where playa lakes, mudflats and lagoons had developed. The pure and massive halitic facies at the top of the series probably indicate an evolution of the depositional environment towards a shallow subtidal environment. The presence of these evaporites indicates a climate that favored their precipitation, in this case, a fairly hot and humid climate. The sedimentological analysis of the supra-basaltic part shows that during the Lower Liassic, the paleopente after basaltic effusion remained weak with distal environments. The faciological analysis revealed the presence of four major sandstone, silty, clayey and evaporitic lithofacies organized in two mega-sequences: the sedimentation of the first rock-salt mega-sequence took place in a brine depression system free, followed by saline mudflats under continental influences. The upper clay mega-sequence displays facies documenting sea level fluctuations from the final transgression of the Tethys or the opening Atlantic. Saliferous sedimentation is therefore favored from the Upper Triassic, but experienced a sudden rupture by the emission of basaltic flows which are interstratified in the azoic salt clays of very shallow seas. This basaltic emission which belongs to the CAMP would come from a fissural volcanism probably carried out through transfer faults located in the NW and SE of the basin. Their emplacement is probably subaquatic to subaerial. From a chronological and paleogeographic point of view, this main volcanism, dated between the Upper Triassic and the Lower Liassic (180-200 MA), is linked to the fragmentation of Pangea and managed by a progressive expansion triggered in the West in close relation with the initial phases of Central Atlantic rifting and seems to coincide with the major mass extinction at the Triassic-Jurassic boundary.

Keywords: Basalt, CAMP, Liassic, sedimentology, Triassic, Morocco

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Authors: George Kyriakopoulos, Photini Pazartzis, Anthi Koskina, Crystalie Bourcha

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The need for securing safe access to and return from outer space, as well as ensuring the viability of outer space operations, maintains vivid the debate over the promotion of organization of space traffic through a Space Traffic Management System (STM). The proliferation of outer space activities in recent years as well as the dynamic emergence of the private sector has gradually resulted in a diverse universe of actors operating in outer space. The said developments created an increased adverse impact on outer space sustainability as the case of the growing number of space debris clearly demonstrates. The above landscape sustains considerable threats to outer space environment and its operators that need to be addressed by a combination of scientific-technological measures and regulatory interventions. In this context, recourse to recent technological advancements and, in particular, to Artificial Intelligence (AI) and machine learning systems, could achieve exponential results in promoting space traffic management with respect to collision avoidance as well as launch and re-entry procedures/phases. New technologies can support the prospects of a successful space traffic management system at an international scale by enabling, inter alia, timely, accurate and analytical processing of large data sets and rapid decision-making, more precise space debris identification and tracking and overall minimization of collision risks and reduction of operational costs. What is more, a significant part of space activities (i.e. launch and/or re-entry phase) takes place in airspace rather than in outer space, hence the overall discussion also involves the highly developed, both technically and legally, international (and national) Air Traffic Management System (ATM). Nonetheless, from a regulatory perspective, the use of AI for the purposes of space traffic management puts forward implications that merit particular attention. Key issues in this regard include the delimitation of AI-based activities as space activities, the designation of the applicable legal regime (international space or air law, national law), the assessment of the nature and extent of international legal obligations regarding space traffic coordination, as well as the appropriate liability regime applicable to AI-based technologies when operating for space traffic coordination, taking into particular consideration the dense regulatory developments at EU level. In addition, the prospects of institutionalizing international cooperation and promoting an international governance system, together with the challenges of establishment of a comprehensive international STM regime are revisited in the light of intervention of AI technologies. This paper aims at examining regulatory implications advanced by the use of AI technology in the context of space traffic management operations and its key correlating concepts (SSA, space debris mitigation) drawing in particular on international and regional considerations in the field of STM (e.g. UNCOPUOS, International Academy of Astronautics, European Space Agency, among other actors), the promising advancements of the EU approach to AI regulation and, last but not least, national approaches regarding the use of AI in the context of space traffic management, in toto. Acknowledgment: The present work was co-funded by the European Union and Greek national funds through the Operational Program "Human Resources Development, Education and Lifelong Learning " (NSRF 2014-2020), under the call "Supporting Researchers with an Emphasis on Young Researchers – Cycle B" (MIS: 5048145).

Keywords: artificial intelligence, space traffic management, space situational awareness, space debris

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Authors: Gabrielle Robertson, Matthew Downs, Joseph Dagher

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Iron deposition in the brain has been linked with a host of neurological disorders such as Alzheimer’s, Parkinson’s, and Multiple Sclerosis. While some treatment options exist, there are no objective measurement tools that allow for the monitoring of iron levels in the brain in vivo. An emerging Magnetic Resonance Imaging (MRI) method has been recently proposed to deduce iron concentration through quantitative measurement of magnetic susceptibility. This is a multi-step process that involves repeated modeling of physical processes via approximate numerical solutions. For example, the last two steps of this Quantitative Susceptibility Mapping (QSM) method involve I) mapping magnetic field into magnetic susceptibility and II) mapping magnetic susceptibility into iron concentration. Process I involves solving an ill-posed inverse problem by using regularization via injection of prior belief. The end result from Process II highly depends on the model used to describe the molecular content of each voxel (type of iron, water fraction, etc.) Due to these factors, the accuracy and repeatability of QSM have been an active area of research in the MRI and medical imaging community. This work aims to estimate iron concentration in the brain via a single step. A synthetic numerical model of the human head was created by automatically and manually segmenting the human head on a high-resolution grid (640x640x640, 0.4mm³) yielding detailed structures such as microvasculature and subcortical regions as well as bone, soft tissue, Cerebral Spinal Fluid, sinuses, arteries, and eyes. Each segmented region was then assigned tissue properties such as relaxation rates, proton density, electromagnetic tissue properties and iron concentration. These tissue property values were randomly selected from a Probability Distribution Function derived from a thorough literature review. In addition to having unique tissue property values, different synthetic head realizations also possess unique structural geometry created by morphing the boundary regions of different areas within normal physical constraints. This model of the human brain is then used to create synthetic MRI measurements. This is repeated thousands of times, for different head shapes, volume, tissue properties and noise realizations. Collectively, this constitutes a training-set that is similar to in vivo data, but larger than datasets available from clinical measurements. This 3D convolutional U-Net neural network architecture was used to train data-driven Deep Learning models to solve for iron concentrations from raw MRI measurements. The performance was then tested on both synthetic data not used in training as well as real in vivo data. Results showed that the model trained on synthetic MRI measurements is able to directly learn iron concentrations in areas of interest more effectively than other existing QSM reconstruction methods. For comparison, models trained on random geometric shapes (as proposed in the Deep QSM method) are less effective than models trained on realistic synthetic head models. Such an accurate method for the quantitative measurement of iron deposits in the brain would be of important value in clinical studies aiming to understand the role of iron in neurological disease.

Keywords: magnetic resonance imaging, MRI, iron deposition, machine learning, quantitative susceptibility mapping

Procedia PDF Downloads 114

Authors: Chenyi Ma

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Background: The second costliest hurricane in U.S. history, Sandy landed in southern New Jersey on October 29, 2012, and struck the entire state with high winds and torrential rains. The disaster killed more than 100 people, left more than 8.5 million households without power, and damaged or destroyed more than 200,000 homes across the state. Immediately after the disaster, public policy support was provided in nine coastal counties that constituted 98% of the major and severely damaged housing units in NJ overall. The programs include Individuals and Households Assistance Program, Small Business Loan Program, National Flood Insurance Program, and the Federal Emergency Management Administration (FEMA) Public Assistance Grant Program. In the most severely affected counties, additional funding was provided through Community Development Block Grant: Reconstruction, Rehabilitation, Elevation, and Mitigation Program, and Homeowner Resettlement Program. How these policies individually and as a whole impacted housing recovery across communities with different socioeconomic and demographic profiles has not yet been studied, particularly in relation to damage levels. The concept of community social vulnerability has been widely used to explain many aspects of natural disasters. Nevertheless, how communities are vulnerable has been less fully examined. Community resilience has been conceptualized as a protective factor against negative impacts from disasters, however, how community resilience buffers the effects of vulnerability is not yet known. Because housing recovery is a dynamic social and economic process that varies according to context, this study examined the path from community vulnerability and resilience to housing recovery looking at both community characteristics and policy interventions. Sample/Methods: This retrospective longitudinal case study compared a literature-identified set of pre-disaster community characteristics, the effects of multiple public policy programs, and a set of time-variant community resilience indicators to changes in housing stock (operationally defined by percent of building permits to total occupied housing units/households) between 2010 and 2014, two years before and after Hurricane Sandy. The sample consisted of 51 municipalities in the nine counties in which between 4% and 58% of housing units suffered either major or severe damage. Structural equation modeling (SEM) was used to determine the path from vulnerability to the housing recovery, via multiple public programs, separately and as a whole, and via the community resilience indicators. The spatial analytical tool ArcGIS 10.2 was used to show the spatial relations between housing recovery patterns and community vulnerability and resilience. Findings: Holding damage levels constant, communities with higher proportions of Hispanic households had significantly lower levels of housing recovery while communities with households with an adult >age 65 had significantly higher levels of the housing recovery. The contrast was partly due to the different levels of total public support the two types of the community received. Further, while the public policy programs individually mediated the negative associations between African American and female-headed households and housing recovery, communities with larger proportions of African American, female-headed and Hispanic households were “vulnerable” to lower levels of housing recovery because they lacked sufficient public program support. Even so, higher employment rates and incomes buffered vulnerability to lower housing recovery. Because housing is the "wobbly pillar" of the welfare state, the housing needs of these particular groups should be more fully addressed by disaster policy.

Keywords: community social vulnerability, community resilience, hurricane, public policy

Procedia PDF Downloads 357

Authors: Mohammadreza Kashizadeh, Mohammadamin Hashemi

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Solymorph, a kinetic building facade designed for optimal energy capture and architectural expression, is explored in this paper. The system integrates photovoltaic panels with soft robotic actuators for precise solar tracking, resulting in enhanced electricity generation compared to static facades. Driven by the growing interest in dynamic building envelopes, the exploration of novel facade systems is necessitated. Increased energy generation and regulation of energy flow within buildings are potential benefits offered by integrating photovoltaic (PV) panels as kinetic elements. However, incorporating these technologies into mainstream architecture presents challenges due to the complexity of coordinating multiple systems. To address this, Solymorph leverages soft robotic actuators, known for their compliance, resilience, and ease of integration. Additionally, the project investigates the potential for employing Large Language Models (LLMs) to streamline the design process. The research methodology involved design development, material selection, component fabrication, and system assembly. Grasshopper (GH) was employed within the digital design environment for parametric modeling and scripting logic, and an LLM was experimented with to generate Python code for the creation of a random surface with user-defined parameters. Various techniques, including casting, 3D printing, and laser cutting, were utilized to fabricate the physical components. Finally, a modular assembly approach was adopted to facilitate installation and maintenance. A case study focusing on the application of Solymorph to an existing library building at Politecnico di Milano is presented. The facade system is divided into sub-frames to optimize solar exposure while maintaining a visually appealing aesthetic. Preliminary structural analyses were conducted using Karamba3D to assess deflection behavior and axial loads within the cable net structure. Additionally, Finite Element (FE) simulations were performed in Abaqus to evaluate the mechanical response of the soft robotic actuators under pneumatic pressure. To validate the design, a physical prototype was created using a mold adapted for a 3D printer's limitations. Casting Silicone Rubber Sil 15 was used for its flexibility and durability. The 3D-printed mold components were assembled, filled with the silicone mixture, and cured. After demolding, nodes and cables were 3D-printed and connected to form the structure, demonstrating the feasibility of the design. Solymorph demonstrates the potential of soft robotics and Artificial Intelligence (AI) for advancements in sustainable building design and construction. The project successfully integrates these technologies to create a dynamic facade system that optimizes energy generation and architectural expression. While limitations exist, Solymorph paves the way for future advancements in energy-efficient facade design. Continued research efforts will focus on cost reduction, improved system performance, and broader applicability.

Keywords: artificial intelligence, energy efficiency, kinetic photovoltaics, pneumatic control, soft robotics, sustainable building

Procedia PDF Downloads 36