Search results for: photovoltaic integrated shading device

Authors: Vijaya Dixit Aasheesh Dixit

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Shipbuilding industry operates in Engineer Procure Construct (EPC) context. Product mix of a shipyard comprises of various types of ships like bulk carriers, tankers, barges, coast guard vessels, sub-marines etc. Each order is unique based on the type of ship and customized requirements, which are engineered into the product right from design stage. Thus, to execute every new project, a shipyard needs to upgrade its production expertise. As a result, over the long run, holistic learning occurs across different types of projects which contributes to the knowledge base of the shipyard. Simultaneously, in the short term, during execution of a project comprising of multiple sister ships, repetition of similar tasks leads to learning at activity level. This research aims to capture above learnings of a shipyard and incorporate learning curve effect in project scheduling and materials procurement to improve project performance. Extant literature provides support for the existence of such learnings in an organization. In shipbuilding, there are sequences of similar activities which are expected to exhibit learning curve behavior. For example, the nearly identical structural sub-blocks which are successively fabricated, erected, and outfitted with piping and electrical systems. Learning curve representation can model not only a decrease in mean completion time of an activity, but also a decrease in uncertainty of activity duration. Sister ships have similar material requirements. The same supplier base supplies materials for all the sister ships within a project. On one hand, this provides an opportunity to reduce transportation cost by batching the order quantities of multiple ships. On the other hand, it increases the inventory holding cost at shipyard and the risk of obsolescence. Further, due to learning curve effect the production scheduled of each consequent ship gets compressed. Thus, the material requirement schedule of every next ship differs from its previous ship. As more and more ships get constructed, compressed production schedules increase the possibility of batching the orders of sister ships. This work aims at integrating materials management with project scheduling of long duration projects for manufacturing of multiple sister ships. It incorporates the learning curve effect on progressively compressing material requirement schedules and addresses the above trade-off of transportation cost and inventory holding and shortage costs while satisfying budget constraints of various stages of the project. The activity durations and lead time of items are not crisp and are available in the form of probabilistic distribution. A Stochastic Mixed Integer Programming (SMIP) model is formulated which is solved using evolutionary algorithm. Its output provides ordering dates of items and degree of order batching for all types of items. Sensitivity analysis determines the threshold number of sister ships required in a project to leverage the advantage of learning curve effect in materials management decisions. This analysis will help materials managers to gain insights about the scenarios: when and to what degree is it beneficial to treat a multiple ship project as an integrated one by batching the order quantities and when and to what degree to practice distinctive procurement for individual ship.

Keywords: learning curve, materials management, shipbuilding, sister ships

Procedia PDF Downloads 502

Authors: Tugba G. Isin Ozkan, Yoshiharu Fujii

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One of the most important constrains that decrease the crop yields are weeds. Increased amount and number of chemical herbicides are being utilized every day to control weeds. Chemical herbicides which cause environmental effects, and limitations on implementation of them have led to the nonchemical alternatives in the management of weeds. It is needed increasingly the application of allelopathy as a nonherbicidal innovation to control weed populations in integrated weed management. It is not only because of public concern about herbicide use, but also increased agricultural costs and herbicide resistance weeds. Allelopathy is defined as a common biological phenomenon, direct or indirect interaction which one plant or organism produces biochemicals influence the physiological processes of another neighboring plant or organism. Biochemicals involved in allelopathy are called allelochemicals that influence beneficially or detrimentally the growth, survival, development, and reproduction of other plant or organisms. All plant parts could have allelochemicals which are secondary plant metabolites. Allelochemicals are released to environment, influence the germination and seedling growth of neighbors' weeds; that is the way how allelopathy is applied for weed control. Crop cultivars have significantly different ability for inhibiting the growth of certain weeds. So, a high commercial value crop Corylus avellana L. and its byproducts were chosen to introduce for their allelopathic potential in this research. Edible nut of Corylus avellana L., commonly known as hazelnut is commercially valuable crop with byproducts; skin, hard shell, green leafy cover, and tree leaf. Research on allelopathic potential of a plant by using the sandwich bioassay method and investigation growth inhibitory activity is the first step to develop new and environmentally friendly alternatives for weed control. Thus, the objective of this research is to determine allelopathic potential of C. avellana L. and its byproducts by using sandwich method and to determine effective concentrations (EC) of their extracts for inducing half-maximum elongation inhibition on radicle of test plant, EC50. The sandwich method is reliable and fast bioassay, very useful for allelopathic screening under laboratory conditions. In experiments, lettuce (Lactuca sativa L.) seeds will be test plant, because of its high sensitivity to inhibition by allelochemicals and reliability for germination. In sandwich method, the radicle lengths of dry material treated lettuce seeds and control lettuce seeds will be measured and inhibition of radicle elongation will be determined. Lettuce seeds will also be treated by the methanol extracts of dry hazelnut parts to calculate EC₅₀ values, which are required to induce half-maximal inhibition of growth, as mg dry weight equivalent mL-1. Inhibitory activity of extracts against lettuce seedling elongation will be evaluated, like in sandwich method, by comparing the radicle lengths of treated seeds with that of control seeds and EC₅₀ values will be determined. Research samples are dry parts of Turkish hazelnut, C. avellana L. The results would suggest the opportunity for allelopathic potential of C. avellana L. with its byproducts in plant-plant interaction, might be utilized for further researches, could be beneficial in finding bioactive chemicals from natural products and developing of natural herbicides.

Keywords: allelopathy, Corylus avellana L., EC50, Lactuca sativa L., sandwich method, Turkish hazelnut

Procedia PDF Downloads 175

Authors: Monica Arnaudo, Monika Topel, Bjorn Laumert

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Within the Swedish context, the current trend of relatively low electricity prices promotes the electrification of the energy infrastructure. The residential heating sector takes part in this transition by proposing a switch from a centralized district heating system towards a distributed heat pumps-based setting. When it comes to urban environments, two issues arise. The first, seen from an electricity-sector perspective, is related to the fact that existing networks are limited with regards to their installed capacities. Additional electric loads, such as heat pumps, can cause severe overloads on crucial network elements. The second, seen from a heating-sector perspective, has to do with the fact that the indoor comfort conditions can become difficult to handle when the operation of the heat pumps is limited by a risk of overloading on the distribution grid. Furthermore, the uncertainty of the electricity market prices in the future introduces an additional variable. This study aims at assessing the extent to which distributed heat pumps can penetrate an existing heat energy network while respecting the technical limitations of the electricity grid and the thermal comfort levels in the buildings. In order to account for the multi-disciplinary nature of this research question, a cosimulation modeling approach was adopted. In this way, each energy technology is modeled in its customized simulation environment. As part of the cosimulation methodology: a steady-state power flow analysis in pandapower was used for modeling the electrical distribution grid, a thermal balance model of a reference building was implemented in EnergyPlus to account for space heating and a fluid-cycle model of a heat pump was implemented in JModelica to account for the actual heating technology. With the models set in place, different scenarios based on forecasted electricity market prices were developed both for present and future conditions of Hammarby Sjöstad, a neighborhood located in the south-east of Stockholm (Sweden). For each scenario, the technical and the comfort conditions were assessed. Additionally, the average cost of heat generation was estimated in terms of levelized cost of heat. This indicator enables a techno-economic comparison study among the different scenarios. In order to evaluate the levelized cost of heat, a yearly performance simulation of the energy infrastructure was implemented. The scenarios related to the current electricity prices show that distributed heat pumps can replace the district heating system by covering up to 30% of the heating demand. By lowering of 2°C, the minimum accepted indoor temperature of the apartments, this level of penetration can increase up to 40%. Within the future scenarios, if the electricity prices will increase, as most likely expected within the next decade, the penetration of distributed heat pumps can be limited to 15%. In terms of levelized cost of heat, a residential heat pump technology becomes competitive only within a scenario of decreasing electricity prices. In this case, a district heating system is characterized by an average cost of heat generation 7% higher compared to a distributed heat pumps option.

Keywords: cosimulation, distributed heat pumps, district heating, electrical distribution grid, integrated energy systems

Procedia PDF Downloads 150

Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

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We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: autonomous surveillance, Bayesian reasoning, decision support, interventions, patterns of life, predictive analytics, predictive insights

Procedia PDF Downloads 115

Authors: Caspar Goeke, Holger Finger, Dorena Diekamp, Peter König

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Online-based research has recently gained increasing attention from various fields of research in the cognitive sciences. Technological advances in the form of online crowdsourcing (Amazon Mechanical Turk), open data repositories (Open Science Framework), and online analysis (Ipython notebook) offer rich possibilities to improve, validate, and speed up research. However, until today there is no cross-platform integration of these subsystems. Furthermore, implementation of online studies still suffers from the complex implementation (server infrastructure, database programming, security considerations etc.). Here we propose and test a new JavaScript framework that enables researchers to conduct any kind of behavioral research in the browser without the need to program a single line of code. In particular our framework offers the possibility to manipulate and combine the experimental stimuli via a graphical editor, directly in the browser. Moreover, we included an action-event system that can be used to handle user interactions, interactively change stimuli properties or store participants’ responses. Besides traditional recordings such as reaction time, mouse and keyboard presses, the tool offers webcam based eye and face-tracking. On top of these features our framework also takes care about the participant recruitment, via crowdsourcing platforms such as Amazon Mechanical Turk. Furthermore, the build in functionality of google translate will ensure automatic text translations of the experimental content. Thereby, thousands of participants from different cultures and nationalities can be recruited literally within hours. Finally, the recorded data can be visualized and cleaned online, and then exported into the desired formats (csv, xls, sav, mat) for statistical analysis. Alternatively, the data can also be analyzed online within our framework using the integrated Ipython notebook. The framework was designed such that studies can be used interchangeably between researchers. This will support not only the idea of open data repositories but also constitutes the possibility to share and reuse the experimental designs and analyses such that the validity of the paradigms will be improved. Particularly, sharing and integrating the experimental designs and analysis will lead to an increased consistency of experimental paradigms. To demonstrate the functionality of the framework we present the results of a pilot study in the field of spatial navigation that was conducted using the framework. Specifically, we recruited over 2000 subjects with various cultural backgrounds and consequently analyzed performance difference in dependence on the factors culture, gender and age. Overall, our results demonstrate a strong influence of cultural factors in spatial cognition. Such an influence has not yet been reported before and would not have been possible to show without the massive amount of data collected via our framework. In fact, these findings shed new lights on cultural differences in spatial navigation. As a consequence we conclude that our new framework constitutes a wide range of advantages for online research and a methodological innovation, by which new insights can be revealed on the basis of massive data collection.

Keywords: cultural differences, crowdsourcing, JavaScript framework, methodological innovation, online data collection, online study, spatial cognition

Procedia PDF Downloads 257

Authors: Yana Snegireva

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Carbonate reservoirs are known for their heterogeneity, resulting from various geological processes such as diagenesis and fracturing. These complexities may cause great challenges in understanding fluid flow behavior and predicting the production performance of naturally fractured reservoirs. The investigation of carbonate reservoirs is crucial, as many petroleum reservoirs are naturally fractured, which can be difficult due to the complexity of their fracture networks. This can lead to geological uncertainties, which are important for global petroleum reserves. The problem outlines the key challenges in carbonate reservoir modeling, including the accurate representation of fractures and their connectivity, as well as capturing the impact of fractures on fluid flow and production. Traditional reservoir modeling techniques often oversimplify fracture networks, leading to inaccurate predictions. Therefore, there is a need for a modern approach that can capture the complexities of carbonate reservoirs and provide reliable predictions for effective reservoir management and production optimization. The modern approach to carbonate reservoir modeling involves the utilization of the hybrid fracture modeling approach, including the discrete fracture network (DFN) method and implicit fracture network, which offer enhanced accuracy and reliability in characterizing complex fracture systems within these reservoirs. This study focuses on the application of the hybrid method in the Nepsko-Botuobinskaya anticline of the Eastern Siberia field, aiming to prove the appropriateness of this method in these geological conditions. The DFN method is adopted to model the fracture network within the carbonate reservoir. This method considers fractures as discrete entities, capturing their geometry, orientation, and connectivity. But the method has significant disadvantages since the number of fractures in the field can be very high. Due to limitations in the amount of main memory, it is very difficult to represent these fractures explicitly. By integrating data from image logs (formation micro imager), core data, and fracture density logs, a discrete fracture network (DFN) model can be constructed to represent fracture characteristics for hydraulically relevant fractures. The results obtained from the DFN modeling approaches provide valuable insights into the East Siberia field's carbonate reservoir behavior. The DFN model accurately captures the fracture system, allowing for a better understanding of fluid flow pathways, connectivity, and potential production zones. The analysis of simulation results enables the identification of zones of increased fracturing and optimization opportunities for reservoir development with the potential application of enhanced oil recovery techniques, which were considered in further simulations on the dual porosity and dual permeability models. This approach considers fractures as separate, interconnected flow paths within the reservoir matrix, allowing for the characterization of dual-porosity media. The case study of the East Siberia field demonstrates the effectiveness of the hybrid model method in accurately representing fracture systems and predicting reservoir behavior. The findings from this study contribute to improved reservoir management and production optimization in carbonate reservoirs with the use of enhanced and improved oil recovery methods.

Keywords: carbonate reservoir, discrete fracture network, fracture modeling, dual porosity, enhanced oil recovery, implicit fracture model, hybrid fracture model

Procedia PDF Downloads 75

Authors: Pomozova Kseniia, Gorlachev Gennadiy, Chernyaev Aleksandr, Golanov Andrey

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In clinical practice, and especially in stereotactic radiosurgery planning, the significance of diffusion-weighted imaging (DWI) is growing. This makes the existence of software capable of quickly processing and reliably visualizing diffusion data, as well as equipped with tools for their analysis in terms of different tasks. We are developing the «MRDiffusionImaging» software on the standard C++ language. The subject part has been moved to separate class libraries and can be used on various platforms. The user interface is Windows WPF (Windows Presentation Foundation), which is a technology for managing Windows applications with access to all components of the .NET 5 or .NET Framework platform ecosystem. One of the important features is the use of a declarative markup language, XAML (eXtensible Application Markup Language), with which you can conveniently create, initialize and set properties of objects with hierarchical relationships. Graphics are generated using the DirectX environment. The MRDiffusionImaging software package has been implemented for processing diffusion magnetic resonance imaging (dMRI), which allows loading and viewing images sorted by series. An algorithm for "masking" dMRI series based on T2-weighted images was developed using a deformable surface model to exclude tissues that are not related to the area of interest from the analysis. An algorithm of distortion correction using deformable image registration based on autocorrelation of local structure has been developed. Maximum voxel dimension was 1,03 ± 0,12 mm. In an elementary brain's volume, the diffusion tensor is geometrically interpreted using an ellipsoid, which is an isosurface of the probability density of a molecule's diffusion. For the first time, non-parametric intensity distributions, neighborhood correlations, and inhomogeneities are combined in one segmentation of white matter (WM), grey matter (GM), and cerebrospinal fluid (CSF) algorithm. A tool for calculating the coefficient of average diffusion and fractional anisotropy has been created, on the basis of which it is possible to build quantitative maps for solving various clinical problems. Functionality has been created that allows clustering and segmenting images to individualize the clinical volume of radiation treatment and further assess the response (Median Dice Score = 0.963 ± 0,137). White matter tracts of the brain were visualized using two algorithms: deterministic (fiber assignment by continuous tracking) and probabilistic using the Hough transform. The proposed algorithms test candidate curves in the voxel, assigning to each one a score computed from the diffusion data, and then selects the curves with the highest scores as the potential anatomical connections. White matter fibers were visualized using a Hough transform tractography algorithm. In the context of functional radiosurgery, it is possible to reduce the irradiation volume of the internal capsule receiving 12 Gy from 0,402 cc to 0,254 cc. The «MRDiffusionImaging» will improve the efficiency and accuracy of diagnostics and stereotactic radiotherapy of intracranial pathology. We develop software with integrated, intuitive support for processing, analysis, and inclusion in the process of radiotherapy planning and evaluating its results.

Keywords: diffusion-weighted imaging, medical imaging, stereotactic radiosurgery, tractography

Procedia PDF Downloads 85

Authors: Sagar Saroha, Sawan S. Sinha, Sunil Lakshmipathy

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Reynolds averaged Navier-Stokes (RANS) model is the popular computational tool for prediction of turbulent flows. Being computationally less expensive as compared to direct numerical simulation (DNS), RANS has received wide acceptance in industry and research community as well. However, for high Reynolds number flows, the traditional RANS approach based on the Boussinesq hypothesis is incapacitated to capture all the essential flow characteristics, and thus, its performance is restricted in high Reynolds number flows of practical interest. RANS performance turns out to be inadequate in regimes like flow over curved surfaces, flows with rapid changes in the mean strain rate, duct flows involving secondary streamlines and three-dimensional separated flows. In the recent decade, partially averaged Navier-Stokes (PANS) methodology has gained acceptability among seamless bridging methods of turbulence- placed between DNS and RANS. PANS methodology, being a scale resolving bridging method, is inherently more suitable than RANS for simulating turbulent flows. The superior ability of PANS method has been demonstrated for some cases like swirling flows, high-speed mixing environment, and high Reynolds number turbulent flows. In our work, we intend to evaluate PANS in case of separated turbulent flows past bluff bodies -which is of broad aerodynamic research and industrial application. PANS equations, being derived from base RANS, continue to inherit the inadequacies from the parent RANS model based on linear eddy-viscosity model (LEVM) closure. To enhance PANS’ capabilities for simulating separated flows, the shortcomings of the LEVM closure need to be addressed. Inabilities of the LEVMs have inspired the development of non-linear eddy viscosity models (NLEVM). To explore the potential improvement in PANS performance, in our study we evaluate the PANS behavior in conjugation with NLEVM. Our work can be categorized into three significant steps: (i) Extraction of PANS version of NLEVM from RANS model, (ii) testing the model in the homogeneous turbulence environment and (iii) application and evaluation of the model in the canonical case of separated non-homogeneous flow field (flow past prismatic bodies and bodies of revolution at high Reynolds number). PANS version of NLEVM shall be derived and implemented in OpenFOAM -an open source solver. Homogeneous flows evaluation will comprise the study of the influence of the PANS’ filter-width control parameter on the turbulent stresses; the homogeneous analysis performed over typical velocity fields and asymptotic analysis of Reynolds stress tensor. Non-homogeneous flow case will include the study of mean integrated quantities and various instantaneous flow field features including wake structures. Performance of PANS + NLEVM shall be compared against the LEVM based PANS and LEVM based RANS. This assessment will contribute to significant improvement of the predictive ability of the computational fluid dynamics (CFD) tools in massively separated turbulent flows past bluff bodies.

Keywords: bridging methods of turbulence, high Re-CFD, non-linear PANS, separated turbulent flows

Procedia PDF Downloads 145

Authors: Mei Xuan Tan, Gim-Yang Maggie Pee, Mei Chee Tan

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Academic performance, in the form of scoring high grades in enrolled subjects, is not the only significant trait in achieving success. Engineering graduates with experience in working on hands-on projects in a team setting are highly sought after in industry upon graduation. Such projects are typically real world problems that require the integration and application of knowledge and skills from several disciplines. In a traditional university setting, subjects are taught in a silo manner with no cross participation from other departments or disciplines. This may lead to knowledge compartmentalization and students are unable to understand and connect the relevance and applicability of the subject. University instructors thus see this integration across disciplines as a challenging task as they aim to better prepare students in understanding and solving problems for work or future studies. To improve students’ academic performance and to cultivate various skills such as critical thinking, there has been a gradual uptake in the use of an active learning approach in introductory science and engineering courses, where lecturing is traditionally the main mode of instruction. This study aims to discuss the implementation and experience of a hands-on, interdisciplinary project that involves all the four core subjects taught during the term at the Singapore University of Technology Design (SUTD). At SUTD, an interdisciplinary design activity, named 2D, is integrated into the curriculum to help students reinforce the concepts learnt. A student enrolled in SUTD experiences his or her first 2D in Term 1. This activity. which spans over one week in Week 10 of Term 1, highlights the application of chemistry, physics, mathematics, humanities, arts and social sciences (HASS) in designing an engineering product solution. The activity theme for Term 1 2D revolved around “work and play”. Students, in teams of 4 or 5, used a scaled-down model of a chemical launcher to launch a projectile across the room. It involved the use of a small chemical combustion reaction between ethanol (a highly volatile fuel) and oxygen. This reaction generated a sudden and large increase in gas pressure built up in a closed chamber, resulting in rapid gas expansion and ejection of the projectile out of the launcher. Students discussed and explored the meaning of play in their lives in HASS class while the engineering aspects of a combustion system to launch an object using underlying principles of energy conversion and projectile motion were revisited during the chemistry and physics classes, respectively. Numerical solutions on the distance travelled by the projectile launched by the chemical launcher, taking into account drag forces, was developed during the mathematics classes. At the end of the activity, students developed skills in report writing, data collection and analysis. Specific to this 2D activity, students gained an understanding and appreciation on the application and interdisciplinary nature of science, engineering and HASS. More importantly, students were exposed to design and problem solving, where human interaction and discussion are important yet challenging in a team setting.

Keywords: active learning, collaborative learning, first year undergraduate, interdisciplinary, STEAM

Procedia PDF Downloads 122

Authors: Tristance Kee

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With an unprecedented increase in elderly population around the world, the severe lack of quality housing and health-and-safety provisions to serve this cohort cannot be ignored any longer. Many elderly citizens, especially singletons, live in unsafe housing conditions with poorly executed planning and design. Some suffer from deteriorating mobility, sight and general alertness and their sub-standard living conditions further hinder their daily existence. This research explains how concepts such as Universal Design and Co-Design operate in a high density city such as Hong Kong, China where innovative design can become an alternative solution where government and the private sector fail to provide quality elderly friendly facilities to promote a sustainable urban development. Unlike other elderly research which focuses more on housing policies, nursing care and theories, this research takes a more progressive approach by providing an in-depth impact assessment on how innovative design can be practical solutions for creating a more sustainable built environment. The research objectives are to: 1) explain the relationship between innovative design for elderly and a healthier and sustainable environment; 2) evaluate the impact of human ergonomics with the use of universal design; and 3) explain how innovation can enhance the sustainability of a city in improving citizen’s sight, sound, walkability and safety within the ageing population. The research adopts both qualitative and quantitative methodologies to examine ways to improve elderly population’s relationship to our built environment. In particular, the research utilizes collected data from questionnaire survey and focus group discussions to obtain inputs from various stakeholders, including designers, operators and managers related to public housing, community facilities and overall urban development. In addition to feedbacks from end-users and stakeholders, a thorough analysis on existing elderly housing facilities and Universal Design provisions are examined to evaluate their adequacy. To echo the theme of this conference on Innovation and Sustainable Development, this research examines the effectiveness of innovative design in a risk-benefit factor assessment. To test the hypothesis that innovation can cater for a sustainable development, the research evaluated the health improvement of a sample size of 150 elderly in a period of eight months. Their health performances, including mobility, speech and memory are monitored and recorded on a regular basis to assess if the use of innovation does trigger impact on improving health and home safety for an elderly cohort. This study was supported by district community centers under the auspices of Home Affairs Bureau to provide respondents for questionnaire survey, a standardized evaluation mechanism, and professional health care staff for evaluating the performance impact. The research findings will be integrated to formulate design solutions such as innovative home products to improve elderly daily experience and safety with a particular focus on the enhancement on sight, sound and mobility safety. Some policy recommendations and architectural planning recommendations related to Universal Design will also be incorporated into the research output for future planning of elderly housing and amenity provisions.

Keywords: elderly population, innovative design, sustainable built environment, universal design

Procedia PDF Downloads 228

Authors: Diego Giuseppe Romano, Gianvito Apuleo, Jiri Duda

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Mobility is one of the most important societal needs for amusement, business activities and health. Thus, transport needs are continuously increasing, with the consequent traffic congestion and pollution increase. Aeronautic effort aims at smarter infrastructures use and in introducing greener concepts. A possible solution to address the abovementioned topics is the development of Small Air Transport (SAT) system, able to guarantee operability from today underused airfields in an affordable and green way, helping meanwhile travel time reduction, too. In the framework of Horizon2020, EU (European Union) has funded the Clean Sky 2 SAT TA (Transverse Activity) initiative to address market innovations able to reduce SAT operational cost and environmental impact, ensuring good levels of operational safety. Nowadays, most of the key technologies to improve passenger comfort and to reduce community noise, DOC (Direct Operating Costs) and pilot workload for SAT have reached an intermediate level of maturity TRL (Technology Readiness Level) 3/4. Thus, the key technologies must be developed, validated and integrated on dedicated ground and flying aircraft demonstrators to reach higher TRL levels (5/6). Particularly, SAT TA focuses on the integration at aircraft level of the following technologies [1]: 1)    Low-cost composite wing box and engine nacelle using OoA (Out of Autoclave) technology, LRI (Liquid Resin Infusion) and advance automation process. 2) Innovative high lift devices, allowing aircraft operations from short airfields (< 800 m). 3) Affordable small aircraft manufacturing of metallic fuselage using FSW (Friction Stir Welding) and LMD (Laser Metal Deposition). 4)       Affordable fly-by-wire architecture for small aircraft (CS23 certification rules). 5) More electric systems replacing pneumatic and hydraulic systems (high voltage EPGDS -Electrical Power Generation and Distribution System-, hybrid de-ice system, landing gear and brakes). 6) Advanced avionics for small aircraft, reducing pilot workload. 7) Advanced cabin comfort with new interiors materials and more comfortable seats. 8) New generation of turboprop engine with reduced fuel consumption, emissions, noise and maintenance costs for 19 seats aircraft. (9) Alternative diesel engine for 9 seats commuter aircraft. To address abovementioned market innovations, two different platforms have been designed: Reference and Green aircraft. Reference aircraft is a virtual aircraft designed considering 2014 technologies with an existing engine assuring requested take-off power; Green aircraft is designed integrating the technologies addressed in Clean Sky 2. Preliminary integration of the proposed technologies shows an encouraging reduction of emissions and operational costs of small: about 20% CO₂ reduction, about 24% NO_x reduction, about 10 db (A) noise reduction at measurement point and about 25% DOC reduction. Detailed description of the performed studies, analyses and validations for each technology as well as the expected benefit at aircraft level are reported in the present paper.

Keywords: affordable, European, green, mobility, technologies development, travel time reduction

Procedia PDF Downloads 99

Authors: Wesley Preßler, Lucie Schmidt

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Digital transformation is playing an increasingly important role in the development of smart residential quarters. In order to accompany and steer this process and ultimately make the success of the transformation efforts measurable, it is helpful to use an appropriate maturity model. However, conventional maturity models for digital transformation focus primarily on the evaluation of processes and neglect the information and power imbalances between the stakeholders, which affects the validity of the results. The Multi-Generation Smart Community (mGeSCo) research project is developing an interdisciplinary maturity model that integrates the dimensions of digital literacy, interpretive patterns, and technology acceptance to address this gap. As part of the mGeSCo project, the technological development of selected dimensions in the Smart Quarter Jena-Lobeda (Germany) is being investigated. A specific maturity model, based on Cohen's Smart Cities Wheel, evaluates the central dimensions Working, Living, Housing and Caring. To improve the reliability and relevance of the maturity assessment, the factors Digital Literacy, Interpretive Patterns and Technology Acceptance are integrated into the developed model. The digital literacy dimension examines stakeholders' skills in using digital technologies, which influence their perception and assessment of technological maturity. Digital literacy is measured by means of surveys, interviews, and participant observation, using the European Commission's Digital Literacy Framework (DigComp) as a basis. Interpretations of digital technologies provide information about how individuals perceive technologies and ascribe meaning to them. However, these are not mere assessments, prejudices, or stereotyped perceptions but collective patterns, rules, attributions of meaning and the cultural repertoire that leads to these opinions and attitudes. Understanding these interpretations helps in assessing the overarching readiness of stakeholders to digitally transform a/their neighborhood. This involves examining people's attitudes, beliefs, and values about technology adoption, as well as their perceptions of the benefits and risks associated with digital tools. These insights provide important data for a holistic view and inform the steps needed to prepare individuals in the neighborhood for a digital transformation. Technology acceptance is another crucial factor for successful digital transformation to examine the willingness of individuals to adopt and use new technologies. Surveys or questionnaires based on Davis' Technology Acceptance Model can be used to complement interpretive patterns to measure neighborhood acceptance of digital technologies. Integrating the dimensions of digital literacy, interpretive patterns and technology acceptance enables the development of a roadmap with clear prerequisites for initiating a digital transformation process in the neighborhood. During the process, maturity is measured at different points in time and compared with changes in the aforementioned dimensions to ensure sustainable transformation. Participation, co-creation, and co-production are essential concepts for a successful and inclusive digital transformation in the neighborhood context. This interdisciplinary maturity model helps to improve the assessment and monitoring of sustainable digital transformation processes in smart residential quarters. It enables a more comprehensive recording of the factors that influence the success of such processes and supports the development of targeted measures to promote digital transformation in the neighborhood context.

Keywords: digital transformation, interdisciplinary, maturity model, neighborhood

Procedia PDF Downloads 77

Authors: Laurie Dempsey

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Relationships are considered to be beneficial for emotional wellbeing, happiness and physical health. However, they are also complicated: individuals engage in a multitude of complex and volatile relationships during their lifetime, where the change to or ending of these dynamics can be deeply disruptive. As the internet is further integrated into everyday life and relationships are increasingly mediated, Media Studies’ and Sociology’s research interests intersect and converge. This study longitudinally explores how relationship change over time corresponds with the developing UK technological landscape between 2005-2018. Since the early 2000s, the use of computer-mediated communication (CMC) in the UK has dramatically reshaped interaction. Its use has compelled individuals to renegotiate how they consider their relationships: some argue it has allowed for vast networks to be accumulated and strengthened; others contend that it has eradicated the core values and norms associated with communication, damaging relationships. This research collaborated with UK media regulator Ofcom, utilising the longitudinal dataset from their Adult Media Lives study to explore how relationships and CMC use developed over time. This is a unique qualitative dataset covering 2005-2018, where the same 18 participants partook in annual in-home filmed depth interviews. The interviews’ raw video footage was examined year-on-year to consider how the same people changed their reported behaviour and outlooks towards their relationships, and how this coincided with CMC featuring more prominently in their everyday lives. Each interview was transcribed, thematically analysed and coded using NVivo 11 software. This study allowed for a comprehensive exploration into these individuals’ changing relationships over time, as participants grew older, experienced marriages or divorces, conceived and raised children, or lost loved ones. It found that as technology developed between 2005-2018, everyday CMC use was increasingly normalised and incorporated into relationship maintenance. It played a crucial role in altering relationship dynamics, even factoring in the breakdown of several ties. Three key relationships were identified as being shaped by CMC use: parent-child; extended family; and friendships. Over the years there were substantial instances of relationship conflict: for parents renegotiating their dynamic with their child as they tried to both restrict and encourage their child’s technology use; for estranged family members ‘forced’ together in the online sphere; and for friendships compelled to publicly display their relationship on social media, for fear of social exclusion. However, it was also evident that CMC acted as a crucial lifeline for these participants, providing opportunities to strengthen and maintain their bonds via previously unachievable means, both over time and distance. A longitudinal study of this length and nature utilising the same participants does not currently exist, thus provides crucial insight into how and why relationship dynamics alter over time. This unique and topical piece of research draws together Sociology and Media Studies, illustrating how the UK’s changing technological landscape can reshape one of the most basic human compulsions. This collaboration with Ofcom allows for insight that can be utilised in both academia and policymaking alike, making this research relevant and impactful across a range of academic fields and industries.

Keywords: computer mediated communication, longitudinal research, personal relationships, qualitative data

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Authors: Shana Malio-Satele, Lemalu Silao Vaisola Sefo

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Introductory Statement: South Seas Healthcare is Ōtara’s largest Pacific health provider in South Auckland, New Zealand. Our vision is excellent health and well-being for Pacific people and all communities through strong Pacific values. During the DELTA and Omicron outbreak of COVID-19, our Pacific people, indigenous Māori, and the community of South Auckland were disproportionately affected and faced significant hardship with existing inequities magnified. This study highlights the community-based learnings of harnessing community-based strengths such as indigenous resilience, family-informed experiences and stories that provide critical insights that inform health reform changes that will be sustainable and equitable for all indigenous populations. This study is based on critical learnings acquired during COVID-19 that challenge the deficit narrative common in healthcare about indigenous populations. This study shares case studies of marginalised groups and religious groups and the successful application of indigenous cultural strengths, such as collectivism, positive protective factors, and using trusted relationships to create meaningful change in the way healthcare is delivered. The significance of this study highlights the critical conditions needed to adopt a community-informed way of creating integrated healthcare that works and the role that the community can play in being part of the solution. Methodologies: Key methodologies utilised are indigenous and Pacific-informed. To achieve critical learnings from the community, Pacific research methodologies, heavily informed by the Polynesian practice, were applied. Specifically, this includes; Teu Le Va (Understanding the importance of trusted relationships as a way of creating positive health solutions); The Fonofale Methodology (A way of understanding how health incorporates culture, family, the physical, spiritual, mental and other dimensions of health, as well as time, context and environment; The Fonua Methodology – Understanding the overall wellbeing and health of communities, families and individuals and their holistic needs and environmental factors and the Talanoa methodology (Researching through conversation, where understanding the individual and community is through understanding their history and future through stories). Major Findings: Key findings in the study included: 1. The collectivist approach in the community is a strengths-based response specific to populations, which highlights the importance of trusted relationships and cultural values to achieve meaningful outcomes. 2. The development of a “village model” which identified critical components to achieving health reform change; system navigation, a sense of service that was culturally responsive, critical leadership roles, culturally appropriate support, and the ability to influence the system enablers to support an alternative way of working. Concluding Statement: There is a strong connection between community-based strengths being implemented into healthcare strategies and reforms and the sustainable success of indigenous populations and marginalised communities accessing services that are cohesive, equitably resourced, accessible and meaningful for families. This study highlights the successful community-informed approaches and practices used during the COVID-19 response in New Zealand that are now being implemented in the current health reform.

Keywords: indigenous voice, community voice, health reform, New Zealand

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Authors: Namiiro Shirat Umar

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The science of animals and veterinary medicine is a multidisciplinary field dedicated to understanding, managing, and enhancing the health and welfare of animals. This field encompasses a broad spectrum of disciplines, including animal physiology, genetics, nutrition, behavior, and pathology, as well as preventive and therapeutic veterinary care. Veterinary science focuses on diagnosing, treating, and preventing diseases in animals, ensuring their health and well-being. It involves the study of various animal species, from companion animals and livestock to wildlife and exotic species. Through advanced diagnostic techniques, medical treatments, and surgical procedures, veterinarians address a wide range of health issues, from infectious diseases and injuries to chronic conditions and reproductive health. Animal science complements veterinary medicine by providing a deeper understanding of animal biology and behavior, which is essential for effective health management. It includes research on animal breeding, nutrition, and husbandry practices aimed at improving animal productivity and welfare. Incorporating modern technologies and methodologies, such as genomics, bioinformatics, and precision farming, the science of animals and veterinary medicine continually evolves to address emerging challenges. This integrated approach ensures the development of sustainable practices, enhances animal welfare and contributes to public health by monitoring zoonotic diseases and ensuring the safety of animal products. Animal nutrition is a cornerstone of animal and veterinary science, focusing on the dietary needs of animals to promote health, growth, reproduction, and overall well-being. Proper nutrition ensures that animals receive essential nutrients, including macronutrients (carbohydrates, proteins, fats) and micronutrients (vitamins, minerals), tailored to their specific species, life stages, and physiological conditions. By emphasizing a balanced diet, animal nutrition serves as a preventive measure against diseases and enhances recovery from illnesses, reducing the need for pharmaceutical interventions. It addresses key health issues such as metabolic disorders, reproductive inefficiencies, and immune system deficiencies. Moreover, optimized nutrition improves the quality of animal products like meat, milk, and eggs and enhances the sustainability of animal farming by improving feed efficiency and reducing environmental waste. The integration of animal nutrition into veterinary practice necessitates a collaborative approach involving veterinarians, animal nutritionists, and farmers. Advances in nutritional science, such as precision feeding and the use of nutraceuticals, provide innovative solutions to traditional veterinary challenges. Overall, the focus on animal nutrition as a primary aspect of veterinary care leads to more holistic, sustainable, and effective animal health management practices, promoting the welfare and productivity of animals in various settings. This abstract is a trifold in nature as it traverses how education can put more emphasis on animal nutrition as an alternative for improving animal health as an important issue espoused under the discipline of animal and veterinary science; therefore, brief aspects of this paper and they are as follows; animal nutrition, veterinary science and animals.

Keywords: animal nutrition as a way to enhance growth, animal science as a study, veterinary science dealing with health of the animals, animals healthcare dealing with proper sanitation

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Authors: Hari K. Adhikari, Keshab Sharma, K. C. Apil

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The Gorkha Nepal earthquake of moment magnitude (Mw) 7.8 hit the central region of Nepal on April 25, 2015; with the epicenter about 77 km northwest of Kathmandu Valley. This paper aims to explore challenges of reconstruction in the rural earthquake-stricken areas of Nepal. The Gorkha earthquake on April 25, 2015, has significantly affected the livelihood of people and overall economy in Nepal, causing severe damage and destruction in central Nepal including nation’s capital. A larger part of the earthquake affected area is difficult to access with rugged terrain and scattered settlements, which posed unique challenges and efforts on a massive scale reconstruction and rehabilitation. 800 thousand buildings were affected leaving 8 million people homeless. Challenge of reconstruction of optimum 800 thousand houses is arduous for Nepal in the background of its turmoil political scenario and weak governance. With significant actors involved in the reconstruction process, no appreciable relief has reached to the ground, which is reflected over the frustration of affected people. The 2015 Gorkha earthquake is one of most devastating disasters in the modern history of Nepal. Best of our knowledge, there is no comprehensive study on reconstruction after disasters in modern Nepal, which integrates the necessary information to deal with challenges and opportunities of reconstructions. The study was conducted using qualitative content analysis method. Thirty engineers and ten social mobilizes working for reconstruction and more than hundreds local social workers, local party leaders, and earthquake victims were selected arbitrarily. Information was collected through semi-structured interviews and open-ended questions, focus group discussions, and field notes, with no previous assumption. Author also reviewed literature and document reviews covering academic and practitioner studies on challenges of reconstruction after earthquake in developing countries such as 2001 Gujarat earthquake, 2005 Kashmir earthquake, 2003 Bam earthquake and 2010 Haiti earthquake; which have very similar building typologies, economic, political, geographical, and geological conditions with Nepal. Secondary data was collected from reports, action plans, and reflection papers of governmental entities, non-governmental organizations, private sector businesses, and the online news. This study concludes that inaccessibility, absence of local government, weak governance, weak infrastructures, lack of preparedness, knowledge gap and manpower shortage, etc. are the key challenges of the reconstruction after 2015 earthquake in Nepal. After scrutinizing different challenges and issues, study counsels that good governance, integrated information, addressing technical issues, public participation along with short term and long term strategies to tackle with technical issues are some crucial factors for timely and quality reconstruction in context of Nepal. Sample collected for this study is relatively small sample size and may not be fully representative of the stakeholders involved in reconstruction. However, the key findings of this study are ones that need to be recognized by academics, governments, and implementation agencies, and considered in the implementation of post-disaster reconstruction program in developing countries.

Keywords: Gorkha earthquake, reconstruction, challenges, policy

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Authors: Malla Vijayeta, Y. Vijaya Kumar, N. Ramakrishna Raju, K. Satyanarayana

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Global AEC (architecture, engineering, and construction) industry has been coined as one of the most resistive domains in embracing technology. Although this digital era has been inundated with software tools like CAD, STADD, CANDY, Microsoft Project, Primavera etc. the key stakeholders have been working in siloes and processes remain fragmented. Unlike the yesteryears’ simpler project delivery methods, the current projects are of fast-track, complex, risky, multidisciplinary, stakeholder’s influential, statutorily regulative etc. pose extensive bottlenecks in preventing timely completion of projects. At this juncture, a paradigm shift surfaced in construction industry, and Building Information Modeling, aka BIM, has been a panacea to bolster the multidisciplinary teams’ cooperative and collaborative work leading to productive, sustainable and leaner project outcome. Building information modeling has been integrative, stakeholder engaging and centralized approach in providing a common platform of communication. A common misconception that BIM can be used for building/high rise projects in Indian Construction Industry, while this paper discusses of the implementation of BIM processes/methodologies in water and waste water industry. It elucidates about BIM 4D planning and constructability reviews of a Sewage Treatment Plant in India. Conventional construction planning and logistics management involves a blend of experience coupled with imagination. Even though the excerpts or judgments or lessons learnt gained from veterans might be predictive and helpful, but the uncertainty factor persists. This paper shall delve about the case study of real time implementation of BIM 4D planning protocols for one of the Sewage Treatment Plant of Dravyavati River Rejuvenation Project in India and develops a Time Liner to identify logistics planning and clash detection. With this BIM processes, we shall find that there will be significant reduction of duplication of tasks and reworks. Also another benefit achieved will be better visualization and workarounds during conception stage and enables for early involvement of the stakeholders in the Project Life cycle of Sewage Treatment Plant construction. Moreover, we have also taken an opinion poll of the benefits accrued utilizing BIM processes versus traditional paper based communication like 2D and 3D CAD tools. Thus this paper concludes with BIM framework for Sewage Treatment Plant construction which will achieve optimal construction co-ordination advantages like 4D construction sequencing, interference checking, clash detection checking and resolutions by primary engagement of all key stakeholders thereby identifying potential risks and subsequent creation of risk response strategies. However, certain hiccups like hesitancy in adoption of BIM technology by naïve users and availability of proficient BIM trainers in India poses a phenomenal impediment. Hence the nurture of BIM processes from conception, construction and till commissioning, operation and maintenance along with deconstruction of a project’s life cycle is highly essential for Indian Construction Industry in this digital era.

Keywords: integrated BIM workflow, 4D planning with BIM, building information modeling, clash detection and visualization, constructability reviews, project life cycle

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Authors: Nurlan Smagulov, Aiman Konkabayeva, Akerke Sadykova, Arailym Serik

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Introduction. Adverse environmental factors do not immediately lead to pathological changes in the body. They can exert the growth of pre-pathology characterized by shifts in physiological, biochemical, immunological and other indicators of the body state. These disorders are unstable, reversible and indicative of body reactions. There is an opportunity to objectively judge the internal structure of the adaptive body reactions at the level of individual organs and systems. In order to obtain a stable response of the body to the chronic effects of unfavorable environmental factors of low intensity (compared to production environment factors), a time called the «lag time» is needed. The obtained results without considering this factor distort reality and, for the most part, cannot be a reliable statement of the main conclusions in any work. A technique is needed to reduce methodological errors and combine mathematical logic using statistical methods and a medical point of view, which ultimately will affect the obtained results and avoid a false correlation. Objective. Development of a methodology for assessing and predicting the environmental factors impact on the population health considering the «lag time.» Methods. Research objects: environmental and population morbidity indicators. The database on the environmental state was compiled from the monthly newsletters of Kazhydromet. Data on population morbidity were obtained from regional statistical yearbooks. When processing static data, a time interval (lag) was determined for each «argument-function» pair. That is the required interval, after which the harmful factor effect (argument) will fully manifest itself in the indicators of the organism's state (function). The lag value was determined by cross-correlation functions of arguments (environmental indicators) with functions (morbidity). Correlation coefficients (r) and their reliability (t), Fisher's criterion (F) and the influence share (R2) of the main factor (argument) per indicator (function) were calculated as a percentage. Results. The ecological situation of an industrially developed region has an impact on health indicators, but it has some nuances. Fundamentally opposite results were obtained in the mathematical data processing, considering the «lag time». Namely, an expressed correlation was revealed after two databases (ecology-morbidity) shifted. For example, the lag period was 4 years for dust concentration, general morbidity, and 3 years – for childhood morbidity. These periods accounted for the maximum values of the correlation coefficients and the largest percentage of the influencing factor. Similar results were observed in relation to the concentration of soot, dioxide, etc. The comprehensive statistical processing using multiple correlation-regression variance analysis confirms the correctness of the above statement. This method provided the integrated approach to predicting the degree of pollution of the main environmental components to identify the most dangerous combinations of concentrations of leading negative environmental factors. Conclusion. The method of assessing the «environment-public health» system (considering the «lag time») is qualitatively different from the traditional (without considering the «lag time»). The results significantly differ and are more amenable to a logical explanation of the obtained dependencies. The method allows presenting the quantitative and qualitative dependence in a different way within the «environment-public health» system.

Keywords: ecology, morbidity, population, lag time

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Authors: Liudmyla Vesper

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The problems of modern education are large-scale and diverse. The aspirations of parents, teachers, and experts converge - everyone interested in growing up a generation of whole, well-educated persons. Both the family and society are expected in the future generation to be self-sufficient, desirable in the labor market, and capable of lifelong learning. Today's children have a powerful potential that is difficult to realize in the conditions of traditional school approaches. Focusing on STEM education in practice often ends with the simple use of computers and gadgets during class. "Science", "technology", "engineering" and "mathematics" are difficult to combine within school and university curricula, which have not changed much during the last 10 years. Solving the problems of modern education largely depends on teachers - innovators, teachers - practitioners who develop and implement effective educational methods and programs. Teachers who propose innovative pedagogical practices that allow students to master large-scale knowledge and apply it to the practical plane. Effective education considers the creation of stable neural structures during the learning process, which allow to preserve and increase knowledge throughout life. The author proposed a method of integrated lessons – cases based on the maths patterns for forming a holistic perception of the world. This method and program are scientifically substantiated and have more than 15 years of practical application experience in school and student classrooms. The first results of the practical application of the author's methodology and curriculum were announced at the International Conference "Teaching and Learning Strategies to Promote Elementary School Success", 2006, April 22-23, Yerevan, Armenia, IREX-administered 2004-2006 Multiple Component Education Project. This program is based on the concept of interdisciplinary connections and its implementation in the process of continuous learning. This allows students to save and increase knowledge throughout life according to a single pattern. The pattern principle stores information on different subjects according to one scheme (pattern), using long-term memory. This is how neural structures are created. The author also admits that a similar method can be successfully applied to the training of artificial intelligence neural networks. However, this assumption requires further research and verification. The educational method and program proposed by the author meet the modern requirements for education, which involves mastering various areas of knowledge, starting from an early age. This approach makes it possible to involve the child's cognitive potential as much as possible and direct it to the preservation and development of individual talents. According to the methodology, at the early stages of learning students understand the connection between school subjects (so-called "sciences" and "humanities") and in real life, apply the knowledge gained in practice. This approach allows students to realize their natural creative abilities and talents, which makes it easier to navigate professional choices and find their place in life.

Keywords: science education, maths education, AI, neuroplasticity, innovative education problem, creativity development, modern education problem

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Authors: Olayeye Olubunmi Shola

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Amidst increasing global environmental concerns, sustainable urban planning has emerged as a vital strategy in counteracting the negative impacts of urbanization on the environment. However, the emphasis on sustainability often disregards crucial elements of fairness and equal participation within urban settings. This abstract presents a comprehensive overview of the challenges, objectives, significance, and methodologies for addressing social inequalities in the development of eco-cities, with a specific focus on Abuja, Nigeria. Sustainable urban planning, particularly in the context of developing eco-cities, aims to construct cities prioritizing environmental sustainability and resilience. Nonetheless, a significant gap exists in addressing the enduring social disparities within these initiatives. Equitable distribution of resources, access to services, and social inclusivity are essential components that must be integrated into urban planning frameworks for cities that are genuinely sustainable and habitable. Abuja, the capital city of Nigeria, provides a distinctive case for examining the intersection of sustainability and social justice in urban planning. Despite the urban development, Abuja grapples with challenges such as socio-economic disparities, unequal access to essential services, and inadequate housing among its residents. Recognizing and redressing these disparities within the framework of eco-city development is critical for nurturing an inclusive and sustainable urban environment. The primary aim of this study is to scrutinize and pinpoint the social discrepancies within Abuja's initiatives for eco-city development. Specific objectives include: Evaluating the current socio-economic landscape of Abuja to identify disparities in resource, service, and infrastructure access. Comprehending the existing sustainable urban planning initiatives and their influence on social fairness. Suggesting strategies and recommendations to improve fairness and inclusivity within Abuja's plans for eco-city development. This research holds substantial importance for urban planning practices and policy formulation, not only in Abuja but also on a global scale. By highlighting the crucial role of social equity and inclusivity in the development of eco-cities, this study aims to provide insights that can steer more comprehensive, people-centered urban planning practices. Addressing social disparities within sustainability initiatives is crucial for achieving genuinely sustainable and fair urban spaces. The study will employ qualitative and quantitative methodologies. Data collection will involve surveys, interviews, and observations to capture the diverse experiences and perspectives of various social groups within Abuja. Furthermore, quantitative data on infrastructure, service access, and socio-economic indicators will be collated from government reports, academic sources, and non-governmental organizations. Analytical tools such as Geographic Information Systems (GIS) will be utilized to map and visualize spatial disparities in resource allocation and service access. Comparative analyses and case studies of successful interventions in other cities will be conducted to derive applicable strategies for Abuja's context. In conclusion, this study aims to contribute to the discourse on sustainable urban planning by advocating for equity and inclusivity in the development of eco-cities. By centering on Abuja as a case study, it aims to provide practical insights and solutions for the creation of more fair and sustainable urban environments.

Keywords: fairness, sustainability, geographical information system, equity

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Authors: Adedayo B. Adegbaju, Carel B. Schoeman, Ilse M. Schoeman

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The unique urban contexts that emanated from the apartheid history of South Africa informed the transport landscape of the City of Johannesburg. Apartheid‘s divisive spatial planning and land use management policies promoted sprawling and separated workers from job opportunities. This was further exacerbated by poor funding of public transport and road designs that encouraged the use of private cars. However, the democratization of the country in 1994 and the hosting of the 2010 FIFA World Cup provided a new impetus to the city’s public transport-oriented urban planning inputs. At the same time, the state’s new approach to policy formulations that entails the provision of public transport as one of the tools to end years of marginalization and inequalities soon began to largely reflect in planning decisions of other spheres of government. The Rea Vaya BRT and the Gautrain were respectively implemented by the municipal and provincial governments to demonstrate strong political will and commitment to the new policy direction. While the Gautrain was implemented to facilitate elite movement within Gauteng and to crowd investments and economic growths around station nodes, the BRT was provided for previously marginalized public transport users to provide a sustainable alternative to the dominant minibus taxi. The aim of this research is to evaluate the spatial impacts of the Gautrain and Rea Vaya BRT on the City of Johannesburg and to inform future outcomes by determining the existing potentials. By using the case study approach with a focus on the BRT and fast rail in a metropolitan context, the triangulation research method, which combines various data collection methods, was used to determine the research outcomes. The use of interviews, questionnaires, field observation, and databases such as REX, Quantec, StatsSA, GCRO observatory, national and provincial household travel surveys, and the quality of life surveys provided the basis for data collection. The research concludes that the Gautrain has demonstrated that viable alternatives to the private car can be provided, with its satisfactory feedbacks from users; while some of its station nodes (Sandton, Rosebank) have shown promises of transit-oriented development, one of the project‘s key objectives. The other stations have been unable to stimulate growth due to reasons like non-implementation of their urban design frameworks and lack of public sector investment required to attract private investors. The Rea Vaya BRT continues to be expanded in spite of both its inability to induce modal change and its low ridership figures. The research identifies factors like the low peak to base ratio, pricing, and the city‘s disjointed urban fabric as some of the reasons for its below-average performance. By drawing from the highlights and limitations, the study recommends that public transport provision should be institutionally integrated across and within spheres of government. Similarly, harmonization of the funding structure, better understanding of users’ needs, and travel patterns, underlined with continuity of policy direction and objectives, will equally promote optimal outcomes.

Keywords: bus rapid transit, Gautrain, Rea Vaya, sustainable transport, spatial and transport planning, transit oriented development

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Authors: Rouzbeh Jafari, Joe Nava

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This study includes learnings from an engineering practice normally performed on large scale biohydrogen processes. If properly scale-up is done, biohydrogen can be a reliable pathway for biowaste valorization. Most of the studies on biohydrogen process development have used model feedstock to investigate process key performance indicators (KPIs). This study does not intend to compare different technologies with model feedstock. However, it reports economic drivers and technical challenges which help in developing a road map for expanding biohydrogen economy deployment in Canada. BBA is a consulting firm responsible for the design of hydrogen production projects. Through executing these projects, activity has been performed to identify, register and mitigate technical drawbacks of large-scale hydrogen production. Those learnings, in this study, have been applied to the biohydrogen process. Through data collected by a comprehensive literature review, a base case has been considered as a reference, and several case studies have been performed. Critical parameters of the process were identified and through common engineering practice (process design, simulation, cost estimate, and life cycle assessment) impact of these parameters on the commercialization risk matrix and class 5 cost estimations were reported. The process considered in this study is food waste and woody biomass dark fermentation. To propose a reliable road map to develop a sustainable biohydrogen production process impact of critical parameters was studied on the end-to-end process. These parameters were 1) feedstock composition, 2) feedstock pre-treatment, 3) unit operation selection, and 4) multi-product concept. A couple of emerging technologies also were assessed such as photo-fermentation, integrated dark fermentation, and using ultrasound and microwave to break-down feedstock`s complex matrix and increase overall hydrogen yield. To properly report the impact of each parameter KPIs were identified as 1) Hydrogen yield, 2) energy consumption, 3) secondary waste generated, 4) CO2 footprint, 5) Product profile, 6) $/kg-H2 and 5) environmental impact. The feedstock is the main parameter defining the economic viability of biohydrogen production. Through parametric studies, it was found that biohydrogen production favors feedstock with higher carbohydrates. The feedstock composition was varied, by increasing one critical element (such as carbohydrate) and monitoring KPIs evolution. Different cases were studied with diverse feedstock, such as energy crops, wastewater slug, and lignocellulosic waste. The base case process was applied to have reference KPIs values and modifications such as pretreatment and feedstock mix-and-match were implemented to investigate KPIs changes. The complexity of the feedstock is the main bottleneck in the successful commercial deployment of the biohydrogen process as a reliable pathway for waste valorization. Hydrogen yield, reaction kinetics, and performance of key unit operations highly impacted as feedstock composition fluctuates during the lifetime of the process or from one case to another. In this case, concept of multi-product becomes more reliable. In this concept, the process is not designed to produce only one target product such as biohydrogen but will have two or multiple products (biohydrogen and biomethane or biochemicals). This new approach is being investigated by the BBA team and the results will be shared in another scientific contribution.

Keywords: biohydrogen, process scale-up, economic evaluation, commercialization uncertainties, hydrogen economy

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Authors: Manuel de Pazos-Liano, Manuel Cifuentes-Antonio, Juan Fisac-Gozalo, Sara Perales-Momparler, Carlos Martinez-Montero

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The first-ever game in the Wanda Metropolitano Stadium, the new home of the Club Atletico de Madrid, was played on September 16, 2017, thanks to the work of a multidisciplinary team that made it possible to combine urban development with sustainability goals. The new football ground sits on a 1.2 km² land owned by the city of Madrid. Its construction has dramatically increased the sealed area of the site (transforming the runoff coefficient from 0.35 to 0.9), and the surrounding sewer network has no capacity for that extra flow. As an alternative to enlarge the existing 2.5 m diameter pipes, it was decided to detain runoff on site by means of an integrated and durable infrastructure that would not blow up the construction cost nor represent a burden on the municipality’s maintenance tasks. Instead of the more conventional option of building a large concrete detention tank, the decision was taken on the use of pervious pavement on the 3013 car parking spaces for sub-surface water storage, a solution aligned with the city water ordinance and the Madrid + Natural project. Making the idea a reality, in only five months and during the summer season (which forced to pour the porous concrete only overnight), was a challenge never faced before in Spain, that required of innovation both at the material as well as the machinery side. The process consisted on: a) defining the characteristics required for the porous concrete (compressive strength of 15 N/mm2 and 20% voids); b) testing of different porous concrete dosages at the construction company laboratory; c) stablishing the cross section in order to provide structural strength and sufficient water detention capacity (20 cm porous concrete over a 5 cm 5/10 gravel, that sits on a 50 cm coarse 40/50 aggregate sub-base separated by a virgin fiber polypropylene geotextile fabric); d) hydraulic computer modelling (using the Full Hydrograph Method based on the Wallingford Procedure) to estimate design peak flows decrease (an average of 69% at the three car parking lots); e) use of a variety of machinery for the application of the porous concrete to achieve both structural strength and permeable surface (including an inverse rotating rolling imported from USA, and the so-called CMI, a sliding concrete paver used in the construction of motorways with rigid pavements); f) full-scale pilots and final construction testing by an accredited laboratory (pavement compressive strength average value of 15 N/mm2 and 0,0032 m/s permeability). The continuous testing and innovating construction process explained in detail within this article, allowed for a growing performance with time, finally proving the use of the CMI valid also for large porous car park applications. All this process resulted in a successful story that converts the Wanda Metropolitano Stadium into a great demonstration site that will help the application of the Spanish Royal Decree 638/2016 (it also counts with rainwater harvesting for grass irrigation).

Keywords: construction machinery, permeable carpark, porous concrete, SUDS, sustainable develpoment

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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: Artem Kim, Clara Savary, Christele Dubourg, Wilfrid Carre, Houda Hamdi-Roze, Valerie Dupé, Sylvie Odent, Marie De Tayrac, Veronique David

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Holoprosencephaly (HPE) is a rare congenital brain malformation resulting from the incomplete separation of the two cerebral hemispheres. It is characterized by a wide phenotypic spectrum and a high degree of locus heterogeneity. Genetic defects in 16 genes have already been implicated in HPE, but account for only 30% of cases, suggesting that a large part of genetic factors remains to be discovered. HPE has been recently redefined as a complex multigenic disorder, requiring the joint effect of multiple mutational events in genes belonging to one or several developmental pathways. The onset of HPE may result from accumulation of the effects of multiple rare variants in functionally-related genes, each conferring a moderate increase in the risk of HPE onset. In order to decipher the genetic basis of HPE, unconventional patterns of inheritance involving multiple genetic factors need to be considered. The primary objective of this study was to uncover possible disease causing combinations of multiple rare variants underlying HPE by performing trio-based Whole Exome Sequencing (WES) of familial cases where no molecular diagnosis could be established. 39 families were selected with no fully-penetrant causal mutation in known HPE gene, no chromosomic aberrations/copy number variants and without any implication of environmental factors. As the main challenge was to identify disease-related variants among a large number of nonpathogenic polymorphisms detected by WES classical scheme, a novel variant prioritization approach was established. It combined WES filtering with complementary gene-level approaches: transcriptome-driven (RNA-Seq data) and clinically-driven (public clinical data) strategies. Briefly, a filtering approach was performed to select variants compatible with disease segregation, population frequency and pathogenicity prediction to identify an exhaustive list of rare deleterious variants. The exome search space was then reduced by restricting the analysis to candidate genes identified by either transcriptome-driven strategy (genes sharing highly similar expression patterns with known HPE genes during cerebral development) or clinically-driven strategy (genes associated to phenotypes of interest overlapping with HPE). Deeper analyses of candidate variants were then performed on a family-by-family basis. These included the exploration of clinical information, expression studies, variant characteristics, recurrence of mutated genes and available biological knowledge. A novel bioinformatics pipeline was designed. Applied to the 39 families, this final integrated workflow identified an average of 11 candidate variants per family. Most of candidate variants were inherited from asymptomatic parents suggesting a multigenic inheritance pattern requiring the association of multiple mutational events. The manual analysis highlighted 5 new strong HPE candidate genes showing recurrences in distinct families. Functional validations of these genes are foreseen.

Keywords: complex genetic disorder, holoprosencephaly, multiple rare variants, whole exome sequencing

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

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

Keywords: bioelectrochemistry, aptasensors, single-cell, nanopillars

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Authors: Sabina Auhunas

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These days in Ukraine, Open Science dramatically develops for the sake of scientists of all branches, providing an opportunity to take a more close look on the studies by foreign scientists, as well as to deliver their own scientific data to national and international journals. However, when it comes to the generalization of data on science activities by Ukrainian scientists, these data are often integrated into E-systems that operate inconsistent and barely related information sources. In order to resolve these issues, developed countries productively use E-systems, designed to store and manage research data, such as Current Research Information Systems that enable combining uncompiled data obtained from different sources. An algorithm for selecting SARS-CoV-2 research articles was designed, by means of which we collected the set of papers published by Ukrainian scientists and uploaded by August 1, 2020. Resulting metadata (document type, open access status, citation count, h-index, most cited documents, international research funding, author counts, the bibliographic relationship of journals) were taken from Scopus and Web of Science databases. The study also considered the info from COVID-19/SARS-CoV-2-related documents published from December 2019 to September 2020, directly from documents published by authors depending on territorial affiliation to Ukraine. These databases are enabled to get the necessary information for bibliometric analysis and necessary details: copyright, which may not be available in other databases (e.g., Science Direct). Search criteria and results for each online database were considered according to the WHO classification of the virus and the disease caused by this virus and represented (Table 1). First, we identified 89 research papers that provided us with the final data set after consolidation and removing duplication; however, only 56 papers were used for the analysis. The total number of documents by results from the WoS database came out at 21641 documents (48 affiliated to Ukraine among them) in the Scopus database came out at 32478 documents (41 affiliated to Ukraine among them). According to the publication activity of Ukrainian scientists, the following areas prevailed: Education, educational research (9 documents, 20.58%); Social Sciences, interdisciplinary (6 documents, 11.76%) and Economics (4 documents, 8.82%). The highest publication activity by institution types was reported in the Ministry of Education and Science of Ukraine (its percent of published scientific papers equals 36% or 7 documents), Danylo Halytsky Lviv National Medical University goes next (5 documents, 15%) and P. L. Shupyk National Medical Academy of Postgraduate Education (4 documents, 12%). Basically, research activities by Ukrainian scientists were funded by 5 entities: Belgian Development Cooperation, the National Institutes of Health (NIH, U.S.), The United States Department of Health & Human Services, grant from the Whitney and Betty MacMillan Center for International and Area Studies at Yale, a grant from the Yale Women Faculty Forum. Based on the results of the analysis, we obtained a set of published articles and preprints to be assessed on the variety of features in upcoming studies, including citation count, most cited documents, a bibliographic relationship of journals, reference linking. Further research on the development of the national scientific E-database continues using brand new analytical methods.

Keywords: content analysis, COVID-19, scientometrics, text mining

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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: James Brown, Stella Kortekaas, Ian Finnie, George Zhang, Christine Devine, Neil Healy

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The use of GIS as an analysis tool for engineering decision making is now best practice in the offshore industry. GIS enables multidisciplinary data integration, analysis and visualisation which allows the presentation of large and intricate datasets in a simple map-interface accessible to all project stakeholders. Presenting integrated geoscience and geotechnical data in GIS enables decision makers to be well-informed. This paper is a successful case study of how GIS spatial analysis techniques were applied to help select the most favourable pipeline route. Routing a pipeline through any natural environment has numerous obstacles, whether they be topographical, geological, engineering or financial. Where the pipeline is subjected to external hydrostatic water pressure and is carrying pressurised hydrocarbons, the requirement to safely route the pipeline through hazardous terrain becomes absolutely paramount. This study illustrates how the application of modern, GIS-based pipeline routing techniques enabled the identification of a single most-favourable pipeline route crossing of a challenging seabed terrain. Conventional approaches to pipeline route determination focus on manual avoidance of primary constraints whilst endeavouring to minimise route length. Such an approach is qualitative, subjective and is liable to bias towards the discipline and expertise that is involved in the routing process. For very short routes traversing benign seabed topography in shallow water this approach may be sufficient, but for deepwater geohazardous sites, the need for an automated, multi-criteria, and quantitative approach is essential. This study combined multiple routing constraints using modern least-cost-routing algorithms deployed in GIS, hitherto unachievable with conventional approaches. The least-cost-routing procedure begins with the assignment of geocost across the study area. Geocost is defined as a numerical penalty score representing hazard posed by each routing constraint (e.g. slope angle, rugosity, vulnerability to debris flows) to the pipeline. All geocosted routing constraints are combined to generate a composite geocost map that is used to compute the least geocost route between two defined terminals. The analyses were applied to select the most favourable pipeline route for a potential gas development in deep water. The study area is geologically complex with a series of incised, potentially active, canyons carved into a steep escarpment, with evidence of extensive debris flows. A similar debris flow in the future could cause significant damage to a poorly-placed pipeline. Protruding inter-canyon spurs offer lower-gradient options for ascending an escarpment but the vulnerability of periodic failure of these spurs is not well understood. Close collaboration between geoscientists, pipeline engineers, geotechnical engineers and of course the gas export pipeline operator guided the analyses and assignment of geocosts. Shorter route length, less severe slope angles, and geohazard avoidance were the primary drivers in identifying the most favourable route.

Keywords: geocost, geohazard, pipeline route determination, pipeline route optimisation, spatial analysis

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Authors: Desireina Delancy, Tannice Hall, Eric Garraway, Dwight Robinson

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Aphis gossypii, as a pest, directly damages its host plant by extracting phloem sap (sucking) and indirectly damages it by the transmission of viruses, ultimately affecting the yield of the host. Due to its polyphagous nature, this species affects a wide range of host plants, some of which may serve as a reservoir for colonisation of important crops. In Jamaica, there have been outbreaks of viral plant pathogens that were transmitted by Aphis gossypii. Three such examples are Citrus tristeza virus, the Watermelon mosaic virus, and Papaya ringspot virus. Aphis gossypii also heavily colonized economically significant host plants, including pepper, eggplant, watermelon, cucumber, and hibiscus. To facilitate integrated pest management, it is imperative to understand the biology of the aphid and its host preference. Preliminary work in Jamaica has indicated differences in biology and host preference, as well as host variety within the species. However, specific details of fecundity, colony growth, host preference, distribution, and insecticide resistance of Aphis gossypii were unknown to the best of our knowledge. The aim was to investigate the following in relation to Aphis gossypii: influence of the host plant on colonization, life span, fecundity, population size, and morphology; the impact of host transfer on fecundity and population size as a measure of host preference and host transfer success and susceptibility to four commonly used insecticides. Fecundity and colony size were documented daily from aphids acclimatized on Capsicum chinense Jacquin 1776, Cucumis sativus Linnaeus 1630, Gossypium hirsutum Linnaeus 1751 and Abelmoschus esculentus (L.) Moench 1794 for three generations. The same measures were used after third instar aphids were transferred among the hosts as a measure of suitability and success. Mortality, and fecundity of survivors, were determined after aphids were exposed to varying concentrations of Actara®, Diazinon™, Karate Zeon®, and Pegasus®. Host preference results indicated that, over a 24-day period, Aphis gossypii reached its largest colony size on G. hirsutum (x̄ 381.80), with January – February being the most fecund period. Host transfer experiments were all significantly different, with the most significant occurring between transfers from C. chinense to C. sativus (p < 0.05). Colony sizes were found to increase significantly every 5 days, which has implications for regimes implemented to monitor and evaluate plots. Insecticides ranked on lethality are Karate Zeon®> Actara®> Pegasus® > Diazinon™. The highest LC50 values were obtained for aphids on G. hirsutum and C. chinense was with Pegasus® and for those on C. sativus with Diazinon™. Survivors of insecticide treatments had colony sizes on average that were 98 % less than untreated aphids. Cotton was preferred both in the field and in the glasshouse. It is on cotton the aphids settled first, had the highest fecundity, and the lowest mortality. Cotton can serve as reservoir for (re)populating other cotton or different host species based on migration due to overcrowding, heavy showers, high wind, or ant attendance. Host transfer success between all three hosts is highly probable within an intercropping system. Survivors of insecticide treatments can successfully repopulate host plants.

Keywords: Aphis gossypii, host-plant preference, colonization sequence, host transfers, insecticide susceptibility

Procedia PDF Downloads 95