Search results for: mode prediction

Authors: Ke Wang, Zhu Wang

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Coordinating and promoting urban and rural development has been a new round of institutional change in Zhejiang province since 2004. And this plan was fully implemented, which showed that the isolation between the urban and rural areas had gradually diminished. Little by little, an infiltration interface that is dynamic, flexible and interactive is formed, and this morphological structure starts to appear on the landscape form in the surrounding villages. In order to study the specific function and formation of the structure in the context of industrial revolution, Bimen village located on the interface between Anji Township, Huzhou and Yuhang District, Hangzhou is taken as the case. Anji township is in the cross area between Yangtze River delta economic circle and innovation center in Hangzhou. Awarded with ‘Chinese beautiful village’, Bimen has witnessed the growing process of infiltration in ecology, economy, technology and culture on the interface. Within the opportunity, Bimen village presents internal reformation to adapt to the energy exchange with urban areas. In the research, the reformation is to adjust the industrial structure, to upgrade the local special bamboo crafts, to release space for activities, and to establish infrastructures on the interface. The characteristic of an interface is elasticity achieved by introducing an Internet platform using ‘O2O’ agriculture method to connect cities and farmlands. There is a platform of this kind in Bimen named ‘Xiao Mei’. ‘Xiao’ in Chinese means small, ‘Mei’ means beautiful, which indicates the method to refine the landscape form. It turns out that the new agriculture mode will strengthen the interface by orienting the Third Party Platform upon the old dynamic basis and will bring new vitality for economy development in Bimen village. The research concludes opportunities and challenges generated by the evolution of the infiltration interface. It also proposes strategies for how to organically adapt to the urbanization process. Finally it demonstrates what will happen by increasing flexibility in the landscape forms of suburbs in the Bimen village.

Keywords: Bimen village, infiltration interface, flexibility, suburban landscape form

Procedia PDF Downloads 378

Authors: Jayanth Abishek Subramanian, Ramin Dabirian, Ilias Gavrielatos, Ram Mohan, Ovadia Shoham

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Downcomers are important conduits for multiphase flow transfer from offshore platforms to the seabed. Uncertainty in the predictions of the pressure drop of multiphase flow between platforms is often dominated by the uncertainty associated with the prediction of holdup and pressure drop in the downcomer. The objectives of this study are to conduct experimental and theoretical scale-up study of the downcomer. A 4-in. diameter vertical test section was designed and constructed to study two-phase flow in downcomer. The facility is equipped with baffles for flow area restriction, enabling interchangeable annular slot openings between 30% and 61.7%. Also, state-of-the-art instrumentation, the capacitance Wire-Mesh Sensor (WMS) was utilized to acquire the experimental data. A total of 76 experimental data points were acquired, including falling film under 30% and 61.7% annular slot opening for air-water and air-Conosol C200 oil cases as well as gas carry-under for 30% and 61.7% opening utilizing air-Conosol C200 oil. For all experiments, the parameters such as falling film thickness and velocity, entrained liquid holdup in the core, gas void fraction profiles at the cross-sectional area of the liquid column, the void fraction and the gas carry under were measured. The experimental results indicated that the film thickness and film velocity increase as the flow area reduces. Also, the increase in film velocity increases the gas entrainment process. Furthermore, the results confirmed that the increase of gas entrainment for the same liquid flow rate leads to an increase in the gas carry-under. A power comparison method was developed to enable evaluation of the Lopez (2011) model, which was created for full bore downcomer, with the novel scale-up experiment data acquired from the downcomer with the restricted area for flow. Comparison between the experimental data and the model predictions shows a maximum absolute average discrepancy of 22.9% and 21.8% for the falling film thickness and velocity, respectively; and a maximum absolute average discrepancy of 22.2% for fraction of gas carried with the liquid (oil).

Keywords: two phase flow, falling film, downcomer, wire-mesh sensor

Procedia PDF Downloads 166

Authors: Fonteyne Lot

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SIMON (Study capacities and Interest Monitor is a freely accessible online self-assessment tool that allows secondary education pupils to evaluate their interests and capacities in order to choose a post-secondary major that maximally suits their potential. The tool consists of two broad domains that correspond with two general questions pupils ask: 'What study fields interest me?' and 'Am I capable to succeed in this field of study?'. The first question is addressed by a RIASEC-type interest inventory that links personal interests to post-secondary majors. Pupils are provided with a personal profile and an overview of majors with their degree of congruence. The output is dynamic: respondents can manipulate their score and they can compare their results to the profile of all fields of study. That way they are stimulated to explore the broad range of majors. To answer whether pupils are capable of succeeding in a preferred major, a battery of tests is provided. This battery comprises a range of factors that are predictive of academic success. Traditional predictors such as (educational) background and cognitive variables (mathematical and verbal skills) are included. Moreover, non-cognitive predictors of academic success (such as 'motivation', 'test anxiety', 'academic self-efficacy' and 'study skills') are assessed. These non-cognitive factors are generally not included in admission decisions although research shows they are incrementally predictive of success and are less discriminating. These tests inform pupils on potential causes of success and failure. More important, pupils receive their personal chances of success per major. These differential probabilities are validated through the underlying research on academic success of students. For example, the research has shown that we can identify 22 % of the failing students in psychology and educational sciences. In this group, our prediction is 95% accurate. SIMON leads more students to a suitable major which in turn alleviates student success and retention. Apart from these benefits, the instrument grants insight into risk factors of academic failure. It also supports and fosters the development of evidence-based remedial interventions and therefore gives way to a more efficient use of means.

Keywords: academic success, online self-assessment, student retention, vocational choice

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Authors: Mehrdad Shafiei Dizaji, Hoda Azari

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The research explores the pioneering integration of Physics-Informed Neural Networks (PINNs) into the domain of Ground-Penetrating Radar (GPR) data prediction, akin to advancements in medical imaging for tracking tumor progression in the human body. This research presents a detailed development framework for a specialized PINN model proficient at interpreting and forecasting GPR data, much like how medical imaging models predict tumor behavior. By harnessing the synergy between deep learning algorithms and the physical laws governing subsurface structures—or, in medical terms, human tissues—the model effectively embeds the physics of electromagnetic wave propagation into its architecture. This ensures that predictions not only align with fundamental physical principles but also mirror the precision needed in medical diagnostics for detecting and monitoring tumors. The suggested deep learning structure comprises three components: a CNN, a spatial feature channel attention (SFCA) mechanism, and ConvLSTM, along with temporal feature frame attention (TFFA) modules. The attention mechanism computes channel attention and temporal attention weights using self-adaptation, thereby fine-tuning the visual and temporal feature responses to extract the most pertinent and significant visual and temporal features. By integrating physics directly into the neural network, our model has shown enhanced accuracy in forecasting GPR data. This improvement is vital for conducting effective assessments of bridge deck conditions and other evaluations related to civil infrastructure. The use of Physics-Informed Neural Networks (PINNs) has demonstrated the potential to transform the field of Non-Destructive Evaluation (NDE) by enhancing the precision of infrastructure deterioration predictions. Moreover, it offers a deeper insight into the fundamental mechanisms of deterioration, viewed through the prism of physics-based models.

Keywords: physics-informed neural networks, deep learning, ground-penetrating radar (GPR), NDE, ConvLSTM, physics, data driven

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Authors: D. Avila

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The tourism industry is a phenomenon that has become a growing presence in international socio-economic dynamics, which in most cases exceeds the control parameters in the various environmental regulations and sustainability of existing resources. Because of this, the effects on the natural environment at the regional and national levels represent a challenge, for which a number of strategies are necessary to minimize the environmental impact generated by the occupation of the territory. The hotel tourist building and sustainable development in the coastal zone, have an important impact on the environment and on the physical and psychological health of the inhabitants. Environmental quality associated with the comfort of humans to the sustainable development of natural resources; applied to the hotel architecture this concept involves the incorporation of new demands on all of the constructive process of a building, changing customs of developers and users. The methodology developed provides an initial analysis to determine and rank the different tourist buildings, with the above it will be feasible to establish methods of study and environmental impact assessment. Finally, it is necessary to establish an overview regarding the best way to implement tourism development on the coast, containing guidelines to improve and protect the natural environment. This paper analyzes the parameters and strategies to reduce environmental impacts derived from deployments tourism on the coast, through a series of recommendations towards sustainability, in the context of the Bahia de Banderas, Puerto Vallarta, Jalisco. The environmental impact caused by the implementation of tourism development, perceived in a coastal environment, forcing a series of processes, ranging from the identification of impacts, prediction and evaluation of them. For this purpose are described below, different techniques and valuation procedures: Identification of impacts. Methods for the identification of damage caused to the environment pursue general purpose to obtain a group of negative indicators that are subsequently used in the study of environmental impact. There are several systematic methods to identify the impacts caused by human activities. In the present work, develops a procedure based and adapted from the Ministry of works public urban reference in studies of environmental impacts, the representative methods are: list of contrast, arrays, and networks, method of transparencies and superposition of maps.

Keywords: environmental impact, physical health, sustainability, tourist building

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Authors: Caglayan Hizal, Kutay Yuceturk, Ertugrul Turker Uzun, Hasan Ceylan, Engin Aktas, Gursoy Turan

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Monitoring concepts for structural systems have been investigated by researchers for decades since such tools are quite convenient to determine intervention planning of structures. Despite the considerable development in this regard, the efficient use of monitoring data in reliability assessment, and prediction models are still in need of improvement in their efficiency. More specifically, reliability-based seismic risk assessment of engineering structures may play a crucial role in the post-earthquake decision-making process for the structures. After an earthquake, professionals could identify heavily damaged structures based on visual observations. Among these, it is hard to identify the ones with minimum signs of damages, even if they would experience considerable structural degradation. Besides, visual observations are open to human interpretations, which make the decision process controversial, and thus, less reliable. In this context, when a continuous monitoring system has been previously installed on the corresponding structure, this decision process might be completed rapidly and with higher confidence by means of the observed data. At this stage, the Structural Health Monitoring (SHM) procedure has an important role since it can make it possible to estimate the system reliability based on a recursively updated mathematical model. Therefore, integrating an SHM procedure into the reliability assessment process comes forward as an important challenge due to the arising uncertainties for the updated model in case of the environmental, material and earthquake induced changes. In this context, this study presents a case study on SHM-integrated reliability assessment of the continuously monitored progressively damaged systems. The objective of this study is to get instant feedback on the current state of the structure after an extreme event, such as earthquakes, by involving the observed data rather than the visual inspections. Thus, the decision-making process after such an event can be carried out on a rational basis. In the near future, this can give wing to the design of self-reported structures which can warn about its current situation after an extreme event.

Keywords: condition assessment, vibration-based SHM, reliability analysis, seismic risk assessment

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Authors: Alka Jakhar, Harmanpreet Kaur Sandhu, Samaresh Das

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The Terahertz (THz) technology-based devices are heightening at an alarming rate on account of the wide range of applications in imaging, security, communication, and spectroscopic field. The various available room operational THz detectors, including Golay cell, pyroelectric detector, field-effect transistors, and photoconductive antennas, have some limitations such as narrow-band response, slow response speed, transit time limits, and complex fabrication process. There is an urgent demand to explore new materials and device structures to accomplish efficient THz detection systems. Recently, TMDs including topological semimetals and topological insulators such as PtSe₂, MoTe₂, WSe₂, and PtTe₂ provide novel feasibility for photonic and optical devices. The peculiar properties of these materials, such as Dirac cone, fermions presence, nonlinear optical response, high conductivity, and ambient stability, make them worthy for the development of the THz devices. Here, the platinum telluride (PtTe₂) based devices have been demonstrated for THz detection in the frequency range of 0.1-1 THz. The PtTe₂ is synthesized by direct selenization of the sputtered platinum film on the high-resistivity silicon substrate by using the chemical vapor deposition (CVD) method. The Raman spectra, XRD, and XPS spectra confirm the formation of the thin PtTe₂ film. The PtTe₂ channel length is 5µm and it is connected with a bow-tie antenna for strong THz electric field confinement in the channel. The characterization of the devices has been carried out in a wide frequency range from 0.1-1 THz. The induced THz photocurrent is measured by using lock-in-amplifier after preamplifier. The maximum responsivity is achieved up to 1 A/W under self-biased mode. Further, this responsivity has been increased by applying biasing voltage. This photo response corresponds to low energy THz photons is mainly due to the photo galvanic effect in PtTe₂. The DC current is induced along the PtTe₂ channel, which is directly proportional to the amplitude of the incident THz electric field. Thus, these new topological semimetal materials provide new pathways for sensitive detection and sensing applications in the THz domain.

Keywords: terahertz, detector, responsivity, topological-semimetals

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Authors: Amiya Kumar Pati, Spandan Sahu, Kishanjit Kumar Khatua

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River is our main source of water which is a form of open channel flow and the flow in the open channel provides with many complex phenomena of sciences that needs to be tackled such as the critical flow conditions, boundary shear stress, and depth-averaged velocity. The development of society, more or less solely depends upon the flow of rivers. The rivers are major sources of many sediments and specific ingredients which are much essential for human beings. A river flow consisting of small and shallow channels sometimes divide and recombine numerous times because of the slow water flow or the built up sediments. The pattern formed during this process resembles the strands of a braid. Braided streams form where the sediment load is so heavy that some of the sediments are deposited as shifting islands. Braided rivers often exist near the mountainous regions and typically carry coarse-grained and heterogeneous sediments down a fairly steep gradient. In this paper, the apparent shear stress formulae were suitably modified, and the Energy Concept Method (ECM) was applied for the prediction of discharges at the junction of a two-flow braided compound channel. The Energy Concept Method has not been applied for estimating the discharges in the braided channels. The energy loss in the channels is analyzed based on mechanical analysis. The cross-section of channel is divided into two sub-areas, namely the main-channel below the bank-full level and region above the bank-full level for estimating the total discharge. The experimental data are compared with a wide range of theoretical data available in the published literature to verify this model. The accuracy of this approach is also compared with Divided Channel Method (DCM). From error analysis of this method, it is observed that the relative error is less for the data-sets having smooth floodplains when compared to rough floodplains. Comparisons with other models indicate that the present method has reasonable accuracy for engineering purposes.

Keywords: critical flow, energy concept, open channel flow, sediment, two-flow braided compound channel

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Authors: F. Pires, V. Geraldo, O. N. Oliveira Jr., M. Raposo

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Catechins are powerful antioxidants which have attractive properties useful for tumor therapy. Considering their antioxidant activity, these molecules can act as a scavenger of the reactive oxygen species (ROS), alleviating the damage of cell membrane induced by oxidative stress. The complexity and dynamic nature of the cell membrane compromise the analysis of the biophysical interactions between drug and cell membrane and restricts the transport or uptake of the drug by intracellular targets. To avoid the cell membrane complexity, we used biomimetic systems as liposomes and Langmuir monolayers to study the interaction between catechin and membranes at the molecular level. Liposomes were formed after the dispersion of anionic 1,2-dipalmitoyl-sn-glycero-3-[phospho-rac-(1-glycerol)(sodium salt) (DPPG) phospholipids in an aqueous solution, which mimic the arrangement of lipids in natural cell membranes and allows the entrapment of catechins. Langmuir monolayers were formed after dropping amphiphilic molecules, DPPG phospholipids, dissolved in an organic solvent onto the water surface. In this work, we mixed epigallocatechin-3-gallate (EGCG) with DPPG liposomes and exposed them to ultra-violet radiation in order to evaluate the antioxidant potential of these molecules against oxidative stress induced by radiation. The presence of EGCG in the mixture decreased the rate of lipid peroxidation, proving that EGCG protects membranes through the quenching of the reactive oxygen species. Considering the high amount of hydroxyl groups (OH groups) on structure of EGCG, a possible mechanism to these molecules interact with membrane is through hydrogen bonding. We also investigated the effect of EGCG at various concentrations on DPPG Langmuir monolayers. The surface pressure isotherms and infrared reflection-absorption spectroscopy (PM-IRRAS) results corroborate with absorbance results preformed on liposome-model, showing that EGCG interacts with polar heads of the monolayers. This study elucidates the physiological action of EGCG which can be incorporated in lipid membrane. These results are also relevant for the improvement of the current protocols used to incorporate catechins in drug delivery systems.

Keywords: catechins, lipid membrane, anticancer agent, molecular interactions

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Authors: Zahra Hamidi

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Promoting cycling, as an affordable environmentally friendly mode of transport to replace private car use has been central to sustainable transport policies. Cycling is faster than walking and combined with public transport has the potential to extend the opportunities that people can access. In other words, cycling, besides direct positive health impacts, can improve people mobility and ultimately their quality of life. Transport literature well supports the close relationship between mobility, quality of life, and, well being. At the same time inequity in the distribution of access and mobility has been associated with the key aspects of injustice and social exclusion. The pattern of social exclusion and inequality in access are also often related to population characteristics such as age, gender, income, health, and ethnic background. Therefore, while investing in transport infrastructure it is important to consider the equity of provided access for different population groups. This paper proposes a method to evaluate the equity of cycling in a city from Rawls egalitarian perspective. Since this perspective is concerned with the difference between individuals and social groups, this method combines accessibility measures and Theil index of inequality that allows capturing the inequalities ‘within’ and ‘between’ groups. The paper specifically focuses on two population characteristics as gender and ethnic background. Following Rawls equity principles, this paper measures accessibility by bikes to a selection of urban activities that can be linked to the concept of the social primary goods. Moreover, as growing number of cities around the world have launched bike-sharing systems (BSS) this paper incorporates both private and public bikes networks in the estimation of accessibility levels. Additionally, the typology of bike lanes (separated from or shared with roads), the presence of a bike sharing system in the network, as well as bike facilities (e.g. parking racks) have been included in the developed accessibility measures. Application of this proposed method to a real case study, the city of Malmö, Sweden, shows its effectiveness and efficiency. Although the accessibility levels were estimated only based on gender and ethnic background characteristics of the population, the author suggests that the analysis can be applied to other contexts and further developed using other properties, such as age, income, or health.

Keywords: accessibility, cycling, equity, gender

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Authors: Mahtab Makaremi Masouleh, Günter Wozniak

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This research is part of an interdisciplinary project, promoting the design of a light temporary installable textile defence system against flood. In case river water levels increase abruptly especially in winter time, one can expect massive extra load on a textile protective structure in term of impact as a result of floating debris and even tree trunks. Estimation of this impulsive force on such structures is of a great importance, as it can ensure the reliability of the design in critical cases. This fact provides the motivation for the numerical analysis of a fluid structure interaction application, comprising flexible slender shaped and free-surface water flow, where an accelerated heavy flotsam tends to approach the membrane. In this context, the analysis on both the behavior of the flexible membrane and its interaction with moving flotsam is conducted by finite elements based solvers of the explicit solver and implicit Abacus solver available as products of SIMULIA software. On the other hand, a study on how free surface water flow behaves in response to moving structures, has been investigated using the finite volume solver of Star CCM+ from Siemens PLM Software. An automatic communication tool (CSE, SIMULIA Co-Simulation Engine) and the implementation of an effective partitioned strategy in form of an implicit coupling algorithm makes it possible for partitioned domains to be interconnected powerfully. The applied procedure ensures stability and convergence in the solution of these complicated issues, albeit with high computational cost; however, the other complexity of this study stems from mesh criterion in the fluid domain, where the two structures approach each other. This contribution presents the approaches for the establishment of a convergent numerical solution and compares the results with experimental findings.

Keywords: co-simulation, flexible thin structure, fluid-structure interaction, implicit coupling algorithm, moving flotsam

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Authors: Anu Chandran, Reena Esther Rani

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Background of the Study: Dotted with multiple Unique Destination Prepositions (UDPs), Tamil Nadu is an established tourism brand as regards leisure, MICE, culture, and ecological flavors. Albeit, the enchanting destination possesses distinctive attributes and resources yet to be tapped for better competitive advantage. Being a destination that allures an incredible variety of migratory birds, Tamil Nadu is deemed to be an ornithologist’s paradise. This study primarily explores the prospects of developing Kaliveli, recognized as a bird sanctuary in the Tindivanam forest division of the Villupuram district in the State. Kaliveli is an ideal nesting site for migratory birds and is currently apt for a prospective analysis of regenerative tourism. Objectives of the study: This research lays an accent on avian tourism as part and parcel of sustainable tourism ventures. The impacts of projects like the Ornithological Conservation Centre on tourists have been gauged in the present paper. It maps the futuristic proactive propositions linked to regenerative tourism on the site. How far technological innovations can do a world of good in Kaliveli through Artificial Intelligence, Smart Tourism, and similar latest coinages to entice real eco-tourists, have been conceptualized. The experiential dimensions of resource stewardship as regards facilitating tourists’ relish the offerings in a sustainable manner is at the crux of this work. Methodology: Modeled as a case study, this work tries to deliberate on the impact of existing projects attributed to avian fauna in Kalveli. Conducted in the qualitative research design mode, the case study method was adopted for the processing and presentation of study results drawn by applying thematic content analysis based on the data collected from the field. Result and discussion: One of the key findings relates to the kind of nature trails that can be a regenerative dynamic for eco-friendly tourism in Kaliveli. Field visits have been conducted to assess the niche tourism aspects which could be incorporated with the regenerative tourism model to be framed as part of the study.

Keywords: regenerative tourism, Kaliveli bird sanctuary, sustainable development, resource Stewardship, Ornithology, Avian Fauna

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Authors: Ashraf Nawaz Khan, R. Alagirusamy, Apurba Das, Puneet Mahajan

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The thermoplastic-based fibre composites are acquiring a market sector of conventional as well as thermoset composites. However, replacing the thermoset with a thermoplastic composite has never been an easy task. The inherent high viscosity of thermoplastic resin reveals poor interface properties. In this work, a homo-polymer towpreg is produced through an electrostatic powder spray coating methodology. The produced flexible towpreg offers a low melt-flow distance during the consolidation of the laminate. The reduced melt-flow distance demonstrates a homogeneous fibre/matrix distribution (and low void content) on consolidation. The composite laminate has been fabricated with two manufacturing techniques such as conventional film stack (FS) and powder-coated (PC) technique. This helps in understanding the distinct response of produced laminates on applying load since the laminates produced through the two techniques are comprised of the same constituent fibre and matrix (constant fibre volume fraction). The changed behaviour is observed mainly due to the different fibre/matrix configurations within the laminate. The interface adhesion influences the load transfer between the fibre and matrix. Therefore, it influences the elastic, plastic, and failure patterns of the laminates. Moreover, the effect of preform geometries (plain weave and satin weave structure) are also studied for corresponding composite laminates in terms of various mechanical properties. The fracture analysis is carried out to study the effect of resin at the interlacement points through micro-CT analysis. The PC laminate reveals a considerably small matrix-rich and deficient zone in comparison to the FS laminate. The different load tensile, shear, fracture toughness, and drop weight impact test) is applied to the laminates, and corresponding damage behaviour is analysed in the successive stage of failure. The PC composite has shown superior mechanical properties in comparison to the FS composite. The damage that occurs in the laminate is captured through the SEM analysis to identify the prominent mode of failure, such as matrix cracking, fibre breakage, delamination, debonding, and other phenomena.

Keywords: composite, damage, fibre, manufacturing

Procedia PDF Downloads 137

Authors: Oxana Lukoshus

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The methods of corpus linguistics, a well-established field of research, are being increasingly applied in cognitive linguistics. Corpora data are especially useful for different quantitative studies of grammatical and other aspects of language. The main objective of this paper is to demonstrate how present-day corpora can be applied in semantic studies in general and in semantic studies of adjectives in particular. Polysemantic adjectives have been the subject of numerous studies. But most of them have been carried out on dictionaries. Undoubtedly, dictionaries are viewed as one of the basic data sources, but only at the initial steps of a research. The author usually starts with the analysis of the lexicographic data after which s/he comes up with a hypothesis. In the research conducted three polysemantic synonyms true, loyal, faithful have been analyzed in terms of differences and similarities in their semantic structure. A corpus-based approach in the study of the above-mentioned adjectives involves the following. After the analysis of the dictionary data there was the reference to the following corpora to study the distributional patterns of the words under study – the British National Corpus (BNC) and the Corpus of Contemporary American English (COCA). These corpora are continually updated and contain thousands of examples of the words under research which make them a useful and convenient data source. For the purpose of this study there were no special needs regarding genre, mode or time of the texts included in the corpora. Out of the range of possibilities offered by corpus-analysis software (e.g. word lists, statistics of word frequencies, etc.), the most useful tool for the semantic analysis was the extracting a list of co-occurrence for the given search words. Searching by lemmas, e.g. true, true to, and grouping the results by lemmas have proved to be the most efficient corpora feature for the adjectives under the study. Following the search process, the corpora provided a list of co-occurrences, which were then to be analyzed and classified. Not every co-occurrence was relevant for the analysis. For example, the phrases like An enormous sense of responsibility to protect the minds and hearts of the faithful from incursions by the state was perceived to be the basic duty of the church leaders or ‘True,’ said Phoebe, ‘but I'd probably get to be a Union Official immediately were left out as in the first example the faithful is a substantivized adjective and in the second example true is used alone with no other parts of speech. The subsequent analysis of the corpora data gave the grounds for the distribution groups of the adjectives under the study which were then investigated with the help of a semantic experiment. To sum it up, the corpora-based approach has proved to be a powerful, reliable and convenient tool to get the data for the further semantic study.

Keywords: corpora, corpus-based approach, polysemantic adjectives, semantic studies

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Authors: Linyao Qiu, Zhiqiang Du

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As the rapid development of urbanization, economic developments, and steady population growth in China, the widespread devastation, economic damages, and loss of human lives caused by numerous forms of natural disasters are becoming increasingly serious every year. Disaster management requires available and effective cooperation of different roles and organizations in whole process including mitigation, preparedness, response and recovery. Due to the imbalance of regional development in China, the disaster management capabilities of national and provincial disaster reduction centers are uneven. When an undeveloped area suffers from disaster, neither local reduction department could get first-hand information like high-resolution remote sensing images from satellites and aircrafts independently, nor sharing mechanism is provided for the department to access to data resources deployed in other place directly. Most existing disaster management systems operate in a typical passive data-centric mode and work for single department, where resources cannot be fully shared. The impediment blocks local department and group from quick emergency response and decision-making. In this paper, we introduce a collaborative platform for distributed disaster reduction. To address the issues of imbalance of sharing data sources and technology in the process of disaster reduction, we propose a multi-role oriented collaboration business mechanism, which is capable of scheduling and allocating for optimum utilization of multiple resources, to link various roles for collaborative reduction business in different place. The platform fully considers the difference of equipment conditions in different provinces and provide several service modes to satisfy technology need in disaster reduction. An integrated collaboration system based on focusing services mechanism is designed and implemented for resource scheduling, functional integration, data processing, task management, collaborative mapping, and visualization. Actual applications illustrate that the platform can well support data sharing and business collaboration between national and provincial department. It could significantly improve the capability of disaster reduction in China.

Keywords: business collaboration, data sharing, distributed disaster reduction, focusing service

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Authors: Su Chul Han, Seungwoo Park

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As the increasing incidence of cancer, the technology and modality of radiotherapy have advanced and the importance of preclinical model is increasing in the cancer research. Furthermore, the small animal dosimetry is an essential part of the evaluation of the relationship between the absorbed dose in preclinical small animal and biological effect in preclinical study. In this study, we carried out realistic modeling of the preclinical small animal phantom possible to verify irradiated dose using commercial software. The small animal phantom was modeling from 4D Digital Mouse whole body phantom. To manipulate Moby phantom in commercial software (Mimics, Materialise, Leuven, Belgium), we converted Moby phantom to DICOM image file of CT by Matlab and two- dimensional of CT images were converted to the three-dimensional image and it is possible to segment and crop CT image in Sagittal, Coronal and axial view). The CT images of small animals were modeling following process. Based on the profile line value, the thresholding was carried out to make a mask that was connection of all the regions of the equal threshold range. Using thresholding method, we segmented into three part (bone, body (tissue). lung), to separate neighboring pixels between lung and body (tissue), we used region growing function of Mimics software. We acquired 3D object by 3D calculation in the segmented images. The generated 3D object was smoothing by remeshing operation and smoothing operation factor was 0.4, iteration value was 5. The edge mode was selected to perform triangle reduction. The parameters were that tolerance (0.1mm), edge angle (15 degrees) and the number of iteration (5). The image processing 3D object file was converted to an STL file to output with 3D printer. We modified 3D small animal file using 3- Matic research (Materialise, Leuven, Belgium) to make space for radiation dosimetry chips. We acquired 3D object of realistic small animal phantom. The width of small animal phantom was 2.631 cm, thickness was 2.361 cm, and length was 10.817. Mimics software supported efficiency about 3D object generation and usability of conversion to STL file for user. The development of small preclinical animal phantom would increase reliability of verification of absorbed dose in small animal for preclinical study.

Keywords: mimics, preclinical small animal, segmentation, 3D printer

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Authors: Haoyu Zhao, Qianshu Ma, Min Xie, Yunqi Huang, Yunjia Liu, Huan Song, Hongsheng Gui, Mingli Li, Qiang Wang

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Rationale: Bipolar disorder (BD) and major depressive disorder (MDD), as severe chronic illnesses that restrict patients’ psychosocial functioning and reduce their quality of life, are both categorized into mood disorders. Emerging evidence has suggested that the reliability of self-rated health (SRH) was wellvalidated and that the risk of various health outcomes, including mortality and health care costs, could be predicted by SRH. Compared with other lengthy multi-item patient-reported outcomes (PRO) measures, SRH was proven to have a comparable predictive ability to predict mortality and healthcare utilization. However, to our knowledge, no study has been conducted to assess the association between SRH and hospitalization among people with mental disorders. Therefore, our study aims to determine the association between SRH and subsequent all-cause hospitalizations in patients with BD and MDD. Methods: We conducted a prospective cohort study on people with BD or MDD in the UK from 2006 to 2010 using UK Biobank touchscreen questionnaire data and linked administrative health databases. The association between SRH and 2-year all-cause hospitalizations was assessed using proportional hazard regression after adjustment for sociodemographics, lifestyle behaviors, previous hospitalization use, the Elixhauser comorbidity index, and environmental factors. Results: A total of 29,966 participants were identified, experiencing 10,279 hospitalization events. Among the cohort, the average age was 55.88 (SD 8.01) years, 64.02% were female, and 3,029 (10.11%), 15,972 (53.30%), 8,313 (27.74%), and 2,652 (8.85%) reported excellent, good, fair, and poor SRH, respectively. Among patients reporting poor SRH, 54.19% had a hospitalization event within 2 years compared with 22.65% for those having excellent SRH. In the adjusted analysis, patients with good, fair, and poor SRH had 1.31 (95% CI 1.21-1.42), 1.82 (95% CI 1.68-1.98), and 2.45 (95% CI 2.22, 2.70) higher hazards of hospitalization, respectively, than those with excellent SRH. Conclusion: SRH was independently associated with subsequent all-cause hospitalizations in patients with BD or MDD. This large study facilitates rapid interpretation of SRH values and underscores the need for proactive SRH screening in this population, which might inform resource allocation and enhance high-risk population detection.

Keywords: severe mental illnesses, hospitalization, risk prediction, patient-reported outcomes

Procedia PDF Downloads 160

Authors: A. Chowdhury, P. Egodawatta, J. M. McGree, A. Goonetilleke

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Hydrologic models are increasingly used as tools to predict stormwater quantity and quality from urban catchments. However, due to a range of practical issues, most models produce gross errors in simulating complex hydraulic and hydrologic systems. Difficulty in finding a robust approach for model calibration is one of the main issues. Though automatic calibration techniques are available, they are rarely used in common commercial hydraulic and hydrologic modelling software e.g. MIKE URBAN. This is partly due to the need for a large number of parameters and large datasets in the calibration process. To overcome this practical issue, a framework for automatic calibration of a hydrologic model was developed in R platform and presented in this paper. The model was developed based on the time-area conceptualization. Four calibration parameters, including initial loss, reduction factor, time of concentration and time-lag were considered as the primary set of parameters. Using these parameters, automatic calibration was performed using Approximate Bayesian Computation (ABC). ABC is a simulation-based technique for performing Bayesian inference when the likelihood is intractable or computationally expensive to compute. To test the performance and usefulness, the technique was used to simulate three small catchments in Gold Coast. For comparison, simulation outcomes from the same three catchments using commercial modelling software, MIKE URBAN were used. The graphical comparison shows strong agreement of MIKE URBAN result within the upper and lower 95% credible intervals of posterior predictions as obtained via ABC. Statistical validation for posterior predictions of runoff result using coefficient of determination (CD), root mean square error (RMSE) and maximum error (ME) was found reasonable for three study catchments. The main benefit of using ABC over MIKE URBAN is that ABC provides a posterior distribution for runoff flow prediction, and therefore associated uncertainty in predictions can be obtained. In contrast, MIKE URBAN just provides a point estimate. Based on the results of the analysis, it appears as though ABC the developed framework performs well for automatic calibration.

Keywords: automatic calibration framework, approximate bayesian computation, hydrologic and hydraulic modelling, MIKE URBAN software, R platform

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Authors: H. Jung, N. Kim, B. Kang, J. Choe

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History matching is a crucial procedure for predicting reservoir performances and making future decisions. However, it is difficult due to uncertainties of initial reservoir models. Therefore, it is important to have reliable initial models for successful history matching of highly heterogeneous reservoirs such as channel reservoirs. In this paper, we proposed a novel scheme for regenerating geological models using support vector machine (SVM) and principal component analysis (PCA). First, we perform PCA for figuring out main geological characteristics of models. Through the procedure, permeability values of each model are transformed to new parameters by principal components, which have eigenvalues of large magnitude. Secondly, the parameters are projected into two-dimensional plane by multi-dimensional scaling (MDS) based on Euclidean distances. Finally, we train an SVM classifier using 20% models which show the most similar or dissimilar well oil production rates (WOPR) with the true values (10% for each). Then, the other 80% models are classified by trained SVM. We select models on side of low WOPR errors. One hundred channel reservoir models are initially generated by single normal equation simulation. By repeating the classification process, we can select models which have similar geological trend with the true reservoir model. The average field of the selected models is utilized as a probability map for regeneration. Newly generated models can preserve correct channel features and exclude wrong geological properties maintaining suitable uncertainty ranges. History matching with the initial models cannot provide trustworthy results. It fails to find out correct geological features of the true model. However, history matching with the regenerated ensemble offers reliable characterization results by figuring out proper channel trend. Furthermore, it gives dependable prediction of future performances with reduced uncertainties. We propose a novel classification scheme which integrates PCA, MDS, and SVM for regenerating reservoir models. The scheme can easily sort out reliable models which have similar channel trend with the reference in lowered dimension space.

Keywords: history matching, principal component analysis, reservoir modelling, support vector machine

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Authors: Syed A. Bukhari, Ankur Goswmai, Dale Hume, Thomas Thundat

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Here we demonstrate mechanical detection of photo-induced Insulator to metal transition (MIT) in ultra-thin vanadium dioxide (VO₂) micro strings by using < 100 µW of optical power. Highly focused laser beam heated the string locally resulting in through plane and along axial heat diffusion. Localized temperature increase can cause temperature rise > 60 ºC. The heated region of VO₂ can transform from insulating (monoclinic) to conducting (rutile) phase leading to lattice compressions and stiffness increase in the resonator. The mechanical frequency of the resonator can be tuned by changing optical power and wavelength. The first mode resonance frequency was tuned in three different ways. A decrease in frequency below a critical optical power, a large increase between 50-120 µW followed by a large decrease in frequency for optical powers greater than 120 µW. The dynamic mechanical response was studied as a function of incident optical power and gas pressure. The resonance frequency and amplitude of vibration were found to be decreased with increasing laser power from 25-38 µW and increased by1-2 % when the laser power was further increased to 52 µW. The transition in films was induced and detected by a single pump and probe source and by employing external optical sources of different wavelengths. This trend in dynamic parameters of the strings can be co-related with reversible Insulator to metal transition in VO₂ films which creates change in density of the material and hence the overall stiffness of the strings leading to changes in string dynamics. The increase in frequency at a particular optical power manifests a transition to a more ordered metallic phase which tensile stress onto the string. The decrease in frequency at higher optical powers can be correlated with poor phonon thermal conductivity of VO₂ in conducting phase. Poor thermal conductivity of VO₂ can force in-plane penetration of heat causing the underneath SiN supporting VO₂ which can result as a decrease in resonance frequency. This noninvasive, non-contact laser-based excitation and detection of Insulator to metal transition using micro strings resonators at room temperature and with laser power in few µWs is important for low power electronics, and optical switching applications.

Keywords: thermal conductivity, vanadium dioxide, MEMS, frequency tuning

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Authors: Bantie Getnet Yirsaw, Muluken Chanie Agimas, Gebrie Getu Alemu, Tigabu Kidie Tesfie, Nebiyu Mekonnen Derseh, Habtamu Wagnew Abuhay, Meron Asmamaw Alemayehu, Getaneh Awoke Yismaw

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Introduction: Hepatitis B virus (HBV) is one of the major public health problems globally and needs an urgent response. It is one of the most responsible causes of mortality among the five hepatitis viruses, and it affects almost every class of individuals. Thus, the main objective of this study was to determine the pooled prevalence and its determinants among pregnant women in East Africa. Methods: We searched studies using PubMed, Scopus, Embase, ScienceDirect, Google Scholar, and grey literature that were published between January 01/2020 to January 30/2024. The studies were assessed using the Newcastle Ottawa Scale (NOS) quality assessment scale. The random-effect (DerSimonian) model was used to determine the pooled prevalence and associated factors of HBV among pregnant women. Heterogeneity was assessed by I² statistic, sub-group analysis, and sensitivity analysis. Publication bias was assessed by the Egger test, and the analysis was done using STATA version 17. Result: A total of 45 studies with 35639 pregnant women were included in this systematic review and meta-analysis. The overall pooled prevalence of HBV among pregnant women in East Africa was 6.0% (95% CI: 6.0%−7.0%, I² = 89.7%). The highest prevalence of 8% ((95% CI: 6%, 10%), I² = 91.08%) was seen in 2021, and the lowest prevalence of 5% ((95% CI: 4%, 6%) I² = 52.52%) was observed in 2022. A pooled meta-analysis showed that history of surgical procedure (OR = 2.14 (95% CI: 1.27, 3.61)), having multiple sexual partners (OR = 3.87 (95% CI: 2.52, 5.95), history of body tattooing (OR = 2.55 (95% CI: 1.62, 4.01)), history of tooth extraction (OR = 2.09 (95% CI: 1.29, 3.39)), abortion history(OR = 2.20(95% CI: 1.38, 3.50)), history of sharing sharp material (OR = 1.88 (95% CI: 1.07, 3.31)), blood transfusion (OR = 2.41 (95% CI: 1.62, 3.57)), family history of HBV (OR = 4.87 (95% CI: 2.95, 8.05)) and history needle injury (OR = 2.62 (95% CI: 1.20, 5.72)) were significant risk factors associated with HBV infection among pregnant women. Conclusions: The pooled prevalence of HBV infection among pregnant women in East Africa was at an intermediate level and different across countries, ranging from 1.5% to 22.2%. The result of this pooled prevalence was an indication of the need for screening, prevention, and control of HBV infection among pregnant women in the region. Therefore, early identification of risk factors, awareness creation of the mode of transmission of HBV, and implementation of preventive measures are essential in reducing the burden of HBV infection among pregnant women.

Keywords: hepatitis B virus, prevalence, determinants, pregnant women, meta-analysis, East Africa

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Authors: Umar Hayatu Sidik

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Application of liquid base petroleum fuel (petrol and diesel) for transportation fuel causes emissions of greenhouse gases (GHGs), while natural gas (NG) reduces the emissions of greenhouse gases (GHGs). At present, compression and liquefaction are the most matured technology used for transportation system. For transportation use, compression requires high pressure (200–300 bar) while liquefaction is impractical. A relatively low pressure of 30-40 bar is achievable by adsorbed natural gas (ANG) to store nearly compressed natural gas (CNG). In this study, adsorbents for high-pressure adsorption of methane (CH4) was prepared from coconut shells and polyetheretherketone (PEEK) using potassium hydroxide (KOH) and microwave-assisted activation. Design expert software version 7.1.6 was used for optimization and prediction of preparation conditions of the adsorbents for CH₄ adsorption. Effects of microwave power, activation time and quantity of PEEK on the adsorbents performance toward CH₄ adsorption was investigated. The adsorbents were characterized by Fourier transform infrared spectroscopy (FTIR), thermogravimetric (TG) and derivative thermogravimetric (DTG) and scanning electron microscopy (SEM). The ideal CH4 adsorption capacities of adsorbents were determined using volumetric method at pressures of 5, 17, and 35 bar at an ambient temperature and 5 oC respectively. Isotherm and kinetics models were used to validate the experimental results. The optimum preparation conditions were found to be 15 wt% amount of PEEK, 3 minutes activation time and 300 W microwave power. The highest CH4 uptake of 9.7045 mmol CH4 adsorbed/g adsorbent was recorded by M33P15 (300 W of microwave power, 3 min activation time and 15 wt% amount of PEEK) among the sorbents at an ambient temperature and 35 bar. The CH4 equilibrium data is well correlated with Sips, Toth, Freundlich and Langmuir. Isotherms revealed that the Sips isotherm has the best fit, while the kinetics studies revealed that the pseudo-second-order kinetic model best describes the adsorption process. In all scenarios studied, a decrease in temperature led to an increase in adsorption of both gases. The adsorbent (M33P15) maintained its stability even after seven adsorption/desorption cycles. The findings revealed the potential of coconut shell-PEEK as CH₄ adsorbents.

Keywords: adsorption, desorption, activated carbon, coconut shells, polyetheretherketone

Procedia PDF Downloads 67

Authors: Khairy M. A. Zoheir, Nehma A. Ali, Ahmed M. Darwish, Mohamed S. Kishta, Ahmed A. Abd-Rabou, Mohamed A. Abdelhafez, Karima F. Mahrous

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The study comprehensively investigated the multifaceted therapeutic properties of the IQGAP1shRNA plasmid, encompassing its hepatoprotective, immunomodulatory, and anticancer activities. The study employed a Prednisolone-induced immunosuppressed rat model to assess the hepatoprotective and immunomodulatory effects of IQGAP1shRNA plasmid. Using this model, IQGAP1shRNA plasmid was found to modulate haematopoiesis, improving RBC, platelet, and WBC counts, underscoring its potential in hematopoietic homeostasis. Organ atrophy, a hallmark of immunosuppression in spleen, heart, liver, ovaries, and kidneys, was reversed with IQGAP1shRNA plasmid treatment, reinforcing its hepatotrophic and organotropic capabilities. Elevated hepatic biomarkers (ALT, AST, ALP, LPO) indicative of hepatocellular injury and oxidative stress were reduced with GST, highlighting its hepatoprotective and antioxidative effects. IQGAP1shRNA plasmid also restored depleted antioxidants (GSH and SOD), emphasizing its potent antioxidative and free radical scavenging capabilities. Molecular insights into immune dysregulation revealed downregulation of IQGAP1, IQGAP3 interleukin-2 (IL-2), and interleukin-4 (IL-4) mRNA expression in the liver of immunosuppressed rats. IL-2 and IL-4 play pivotal roles in immune regulation, T-cell activation, and B-cell differentiation. Notably, treatment with IQGAP1shRNA plasmid exhibited a significant upregulation of IL-2 and IL-4 mRNA expression, thereby accentuating its immunomodulatory potential in orchestrating immune homeostasis. Additionally, immune dysregulation was associated with increased levels of TNF-α. However, treatment with IQGAP1shRNA plasmid effectively decreased the levels of TNF-α, further underscoring its role in modulating inflammatory responses and restoring immune balance in immunosuppressed rats. Additionally, pharmacokinetics, bioavailability, drug-likeness, and toxicity risk assessment prediction suggest its potential as a pharmacologically favourable agent with no serious adverse effects. In conclusion, this study confirms the therapeutic potential of the IQGAP1shRNA plasmid, showcasing its effectiveness against hepatotoxicity, oxidative stress, immunosuppression, and its notable anticancer activity.

Keywords: IQGAP1, shRNA, cancer, liver, rat

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Authors: Vinda B. Manurung, Laila Warkhaida, David Hutabarat, Sentanu Wisnuwardhana, Christovik Simatupang, Dhani Sanjaya, Ashadi, Redha B. Putra, Kiki Yustendi

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The geothermal drilling environment presents many obstacles that have limited the use of directional drilling and logging-while-drilling (LWD) technologies, such as borehole washout, mud losses, severe vibration, and high temperature. The case study presented in this paper demonstrates a practice to enhance data logging in geothermal drilling by deploying advanced telemetry and LWD technologies. This operation is aiming continuous improvement in geothermal drilling operations. The case study covers a 12.25-in. hole section of well XX-05 in Pad XX of the Sorik Marapi Geothermal Field. LWD string consists of electromagnetic (EM) telemetry, pressure while drilling (PWD), vibration (DDSr), and acoustic calliper (ACAL). Through this tool configuration, the operator acquired drilling mechanics and caliper logs in real-time and recorded mode, enabling effective monitoring of wellbore stability. Throughout the real-time acquisition, EM-PPM telemetry had provided a three times faster data rate to the surface unit. With the integration of Caliper data and Drilling mechanics data (vibration and ECD -equivalent circulating density), the borehole conditions were more visible to the directional driller, allowing for better control of drilling parameters to minimize vibration and achieve optimum hole cleaning in washed-out or tight formation sequences. After reaching well TD, the recorded data from the caliper sensor indicated an average of 8.6% washout for the entire 12.25-in. interval. Washout intervals were compared with loss occurrence, showing potential for the caliper to be used as an indirect indicator of fractured intervals and validating fault trend prognosis. This LWD case study has given added value in geothermal borehole characterization for both drilling operation and subsurface. Identified challenges while running LWD in this geothermal environment need to be addressed for future improvements, such as the effect of tool eccentricity and the impact of vibration. A perusal of both real-time and recorded drilling mechanics and caliper data has opened various possibilities for maximizing sensor usage in future wells.

Keywords: geothermal drilling, geothermal formation, geothermal technologies, logging-while-drilling, vibration, caliper, case study

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Authors: Chatrabhuti Pipop, Visessri Supattra, Charinpanitkul Tawatchai

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Durian is one of the top agricultural products exported by Thailand. There is the massive market potential for the durian industry. While the global demand for Thai durians, especially the demand from China, is very high, Thailand's durian supply is far from satisfying strong demand. Poor agricultural practices result in low yields and poor quality of fruit. Most irrigation systems currently used by the farmers are fixed schedule or fixed rates that ignore actual weather conditions and crop water requirements. In addition, the technologies emerging are too difficult and complex and prices are too high for the farmers to adopt and afford. Many farmers leave the durian trees to grow naturally. With improper irrigation and nutrient management system, durians are vulnerable to a variety of issues, including stunted growth, not flowering, diseases, and death. Technical development or research for durian is much needed to support the wellbeing of the farmers and the economic development of the country. However, there are a limited number of studies or development projects for durian because durian is a perennial crop requiring a long time to obtain the results to report. This study, therefore, aims to address the problem of durian production by developing an autonomous and precision irrigation system. The system is designed and equipped with an industrial programmable controller, a weather station, and a digital flow meter. Daily water requirements are computed based on weather data such as rainfall and evapotranspiration for daily irrigation with variable flow rates. A prediction model is also designed as a part of the system to enhance the irrigation schedule. Before the system was installed in the field, a simulation model was built and tested in a laboratory setting to ensure its accuracy. Water consumption was measured daily before and after the experiment for further analysis. With this system, the crop water requirement is precisely estimated and optimized based on the data from the weather station. Durian will be irrigated at the right amount and at the right time, offering the opportunity for higher yield and higher income to the farmers.

Keywords: Durian, precision irrigation, precision agriculture, smart farm

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Authors: Chow Jeng Hei, Pavel Tkalich, Low Kai Sheng Bryan

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Due to the growing demand for sustainability in the maritime industry, there has been a significant increase in focus on alternative fuels such as biofuels, liquefied natural gas (LNG), hydrogen, methanol and ammonia to reduce the carbon footprint of vessels. Alternative fuels offer efficient transportability and significantly reduce carbon dioxide emissions, a critical factor in combating global warming. In an era where the world is determined to tackle climate change, the utilization of methanol is projected to witness a consistent rise in demand, even during downturns in the oil and gas industry. Since 2022, there has been an increase in methanol loading and discharging operations for industrial use in Singapore. These operations were conducted across various storage tank terminals at Jurong Island of varying capacities, which are also used to store alternative fuels for bunkering requirements. The key objective of this research is to support the green shipping industries in the transformation to new fuels such as methanol and ammonia, especially in evolving the capability to inform risk assessment and management of spills. In the unlikely event of accidental spills, a highly reliable forecasting system must be in place to provide mitigation measures and ahead planning. The outcomes of this research would lead to an enhanced metocean prediction capability and, together with advanced sensing, will continuously build up a robust digital twin of the bunkering operating environment. Outputs from the developments will contribute to management strategies for alternative marine fuel spills, including best practices, safety challenges and crisis management. The outputs can also benefit key port operators and the various bunkering, petrochemicals, shipping, protection and indemnity, and emergency response sectors. The forecasted datasets provide a forecast of the expected atmosphere and hydrodynamic conditions prior to bunkering exercises, enabling a better understanding of the metocean conditions ahead and allowing for more refined spill incident management planning

Keywords: clean fuels, hydrodynamics, coastal engineering, impact assessments

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Authors: P. Pérez-Martín, G. Pedrós, P. Martínez-Jiménez, M. Varo-Martínez

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In recent decades, family habits related to children’s displacements to school have changed, increasing motorized travels against active modes. This entails a major negative impact on the urban environment, road safety in cities and the physical and psychological development of children. One of the more common actions used to reverse this trend is Walking School Bus (WSB), which consists of a predefined adult-scorted pedestrian route to school with several stops along the path where schoolchildren are collected. At Tirso de Molina School in Cordoba (Spain), a new ICT-based methodology to deploy WSB has been tested. A mobile app that allows the geoposition of the group, the notification of the arrival and real-time communication between the WSB participants have been presented to the families in order to organize and register the daily participation. After an initial survey to know the travel mode and the spatial distribution of the interested families, three WSB routes have been established and the families have been trained in the app usage. During nine weeks, 33 children have joined the WSB and their parents have accompanied the groups in turns. A high recurrence in the attendance has been registered. Through a final survey, participants have valued highly the tool and the methodology designed, emphasizing as most useful features of the mobile app: notifications system, chat and real-time monitoring. It has also been found that the tool has had a major impact on the degree of confidence of parents regarding the autonomous on foot displacement of their children to school. Moreover, 37,9% of the participant families have reported a total or partial modal shift from car to walking, and the benefits more reported are an increment of the parents available time and less problems in the travel to school daily organization. As a consequence, It has been proved the effectiveness of this user-centric innovative ICT-based methodology to reduce the levels of private car drop offs, minimize barriers of time constraints, volunteer recruitment, and parents’ safety concerns, while, at the same time, increase convenience and time savings for families. This pilot study can offer guidance for community coordinated actions and local authority interventions to support sustainable school travel outcomes.

Keywords: active travel, mobile app, sustainable mobility, urban transportation planning, walking school bus

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Authors: Mohammed Abdullah Alshahrani

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The research focuses on investigating the use of partial least squares (PLS) methodology for addressing challenges associated with high-dimensional correlated data. Recent technological advancements have led to experiments producing data characterized by a large number of variables compared to observations, with substantial inter-variable correlations. Such data patterns are common in chemometrics, where near-infrared (NIR) spectrometer calibrations record chemical absorbance levels across hundreds of wavelengths, and in genomics, where thousands of genomic regions' copy number alterations (CNA) are recorded from cancer patients. PLS serves as a widely used method for analyzing high-dimensional data, functioning as a regression tool in chemometrics and a classification method in genomics. It handles data complexity by creating latent variables (components) from original variables. However, applying PLS can present challenges. The study investigates key areas to address these challenges, including unifying interpretations across three main PLS algorithms and exploring unusual negative shrinkage factors encountered during model fitting. The research presents an alternative approach to addressing the interpretation challenge of predictor weights associated with PLS. Sparse estimation of predictor weights is employed using a penalty function combining a lasso penalty for sparsity and a Cauchy distribution-based penalty to account for variable dependencies. The results demonstrate sparse and grouped weight estimates, aiding interpretation and prediction tasks in genomic data analysis. High-dimensional data scenarios, where predictors outnumber observations, are common in regression analysis applications. Ordinary least squares regression (OLS), the standard method, performs inadequately with high-dimensional and highly correlated data. Copy number alterations (CNA) in key genes have been linked to disease phenotypes, highlighting the importance of accurate classification of gene expression data in bioinformatics and biology using regularized methods like PLS for regression and classification.

Keywords: partial least square regression, genetics data, negative filter factors, high dimensional data, high correlated data

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Authors: Abisha Isaac Mohanlal

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Amidst all suspicions and cynicism raised by the legal fraternity, Artificial Intelligence has found its way into the legal system and has revolutionized the conventional forms of legal services delivery. Be it legal argumentation and research or resolution of complex legal disputes; artificial intelligence has crept into all legs of modern day legal services. Its impact has been largely felt by way of big data, legal expert systems, prediction tools, e-lawyering, automated mediation, etc., and lawyers around the world are forced to upgrade themselves and their firms to stay in line with the growth of technology in law. Researchers predict that the future of legal services would belong to artificial intelligence and that the age of human lawyers will soon rust. But as far as the Judiciary is concerned, even in the developed countries, the system has not fully drifted away from the orthodoxy of preferring Natural Intelligence over Artificial Intelligence. Since Judicial decision-making involves a lot of unstructured and rather unprecedented situations which have no single correct answer, and looming questions of legal interpretation arise in most of the cases, discretion and Emotional Intelligence play an unavoidable role. Added to that, there are several ethical, moral and policy issues to be confronted before permitting the intrusion of Artificial Intelligence into the judicial system. As of today, the human judge is the unrivalled master of most of the judicial systems around the globe. Yet, scientists of Artificial Intelligence claim that robot judges can replace human judges irrespective of how daunting the complexity of issues is and how sophisticated the cognitive competence required is. They go on to contend that even if the system is too rigid to allow robot judges to substitute human judges in the recent future, Artificial Intelligence may still aid in other judicial tasks such as drafting judicial documents, intelligent document assembly, case retrieval, etc., and also promote overall flexibility, efficiency, and accuracy in the disposal of cases. By deconstructing the major challenges that Artificial Intelligence has to overcome in order to successfully invade the human- dominated judicial sphere, and critically evaluating the potential differences it would make in the system of justice delivery, the author tries to argue that penetration of Artificial Intelligence into the Judiciary could surely be enhancive and reparative, if not fully transformative.

Keywords: artificial intelligence, judicial decision making, judicial systems, legal services delivery

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Authors: Mohammed Elghazy, Ahmed El Refai, Usama Ebead, Antonio Nanni

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Rehabilitating corrosion-damaged reinforced concrete (RC) structures has been accomplished using various techniques such as steel plating, external post-tensioning, and external bonding of fiber reinforced polymer (FRP) composites. This paper reports on the use of an innovative technique to strengthen corrosion-damaged RC structures using fabric-reinforced cementitious matrix (FRCM) composites. FRCM consists of dry-fiber fabric embedded in cement-based matrix. Twelve large-scale RC beams were constructed and tested in flexural monotonic and fatigue loads. Prior to testing, ten specimens were subjected to accelerated corrosion process for 140 days leading to an average mass loss in the tensile steel bars of 18.8 %. Corrosion was restricted to the main reinforcement located in the middle third of the beam span. Eight corroded specimens were repaired and strengthened while two virgin and two corroded-unrepaired/unstrengthened beams were used as benchmarks for comparison purpose. The test parameters included the FRCM materials (Carbon-FRCM, PBO-FRCM), the number of FRCM plies, the strengthening scheme, and the type of loading (monotonic and fatigue). The effects of the pervious parameters on the flexural response, the mode of failure, and the fatigue life were reported. Test results showed that corrosion reduced the yield and ultimate strength of the beams. The corroded-unrepaired specimen failed to meet the provisions of the ACI-318 code for crack width criteria. The use of FRCM significantly increased the ultimate strength of the corroded specimen by 21% and 65% more than that of the corroded-unrepaired specimen. Corrosion significantly decreased the fatigue life of the corroded-unrepaired beam by 77% of that of the virgin beam. The fatigue life of the FRCM repaired-corroded beams increased to 1.5 to 3.8 times that of the corroded-unrepaired beam but was lower than that of the virgin specimen. The specimens repaired with U-wrapped PBO-FRCM strips showed higher fatigue life than those repaired with the end-anchored bottom strips having similar number of PBO-FRCM-layers. PBO-FRCM was more effective than Carbon-FRCM in restoring the fatigue life of the corroded specimens.

Keywords: corrosion, concrete, fabric-reinforced cementitious matrix (FRCM), fatigue, flexure, repair

Procedia PDF Downloads 296