Search results for: enhanced unicast

Authors: Meredith Jones, Susan Catapano, Carol McNulty

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Study abroad experiences create unique learning opportunities for preservice teachers to strengthen their reflective thinking practices through applied learning experiences. Not only do study abroad experiences provide opportunities for students to expand their cultural sensitivity, but incorporating applied learning experiences in study abroad trips creates unique opportunities for preservice teachers to engage in critical reflection on their teaching skills. Applied learning experiences are designed to nurture learning and growth through a reflective, experiential process outside the traditional classroom setting. As students participate in applied learning experiences, they engage in critical reflection independently, with their peers, and with university faculty. Critical reflection within applied learning contexts generates, deepens, and documents learning but must be intentionally designed to be effective. Grounded in Dewey’s model of reflection, this qualitative study examines longitudinal data from various study abroad cohorts from a particular university. Reflective data was collected during the study abroad trip, and follow up data on critical reflection of teaching practices were collected six months and a year after the trip. Dewey’s model of reflection requires preservice teachers to make sense of their experiences by reflecting on theoretical knowledge, experiences, and pedagogical knowledge. Guided reflection provides preservice teachers with a framework to respond to questions and ideas critical to the applied learning outcomes. Prompts are used to engage preservice teachers in reflecting on situations they have experienced and how they can be transferred to their teaching. Findings from this study noted that students with previous field experiences, or work in the field, engaged in more critical reflection on pedagogical knowledge throughout their applied learning experience. Preservice teachers with limited experiences in the field benefited from engaging in critical reflection prompted by university faculty during the applied learning experience. However, they were able to independently engage in critical reflection once they began work in the field through university field placements, internships, or student teaching. Finally, students who participated in study abroad applied learning experiences reported their critical reflection on their teaching practices, and cultural sensitivity enhanced their teaching and relationships with children once they formally entered the teaching profession.

Keywords: applied learning experiences, critical reflection, cultural sensitivity, preservice teachers, teacher education

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Authors: Marzouk Benali, Jawad Jeaidi, Behrang Mansoornejad, Olumoye Ajao, Banafsheh Gilani, Nima Ghavidel Mehr

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Canadian forest industry is seeking to identify and implement transformational strategies for enhanced financial performance through the emerging bioeconomy or more specifically through the concept of the biorefinery. For example, processing forest residues or surplus of biomass available on the mill sites for the production of biofuels, biochemicals and/or biomaterials is one of the attractive strategies along with traditional wood and paper products and cogenerated energy. There are many possible process-product biorefinery pathways, each associated with specific product portfolios with different levels of risk. Thus, it is not obvious which unique strategy forest industry should select and implement. Therefore, there is a need for analytical and design tools that enable evaluating biorefinery strategies based on a set of criteria considering a perspective of sustainability over the short and long terms, while selecting the existing core products as well as selecting the new product portfolio. In addition, it is critical to assess the manufacturing flexibility to internalize the risk from market price volatility of each targeted bio-based product in the product portfolio, prior to invest heavily in any biorefinery strategy. The proposed paper will focus on introducing a systematic methodology for designing integrated biorefineries using process systems engineering tools as well as a multi-criteria decision making framework to put forward the most effective biorefinery strategies that fulfill the needs of the forest industry. Topics to be covered will include market analysis, techno-economic assessment, cost accounting, energy integration analysis, life cycle assessment and supply chain analysis. This will be followed by describing the vision as well as the key features and functionalities of the I-BIOREF software platform, developed by CanmetENERGY of Natural Resources Canada. Two industrial case studies will be presented to support the robustness and flexibility of I-BIOREF software platform: i) An integrated Canadian Kraft pulp mill with lignin recovery process (namely, LignoBoost™); ii) A standalone biorefinery based on ethanol-organosolv process.

Keywords: biorefinery strategies, bioproducts, co-production, multi-criteria decision making, tool

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Authors: Dona Shaini Abhilasha Nanayakkara, Kurugamage Jude Pravinda Gregory Perera

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E-commerce platforms have revolutionized the shopping experience, offering convenient ways for consumers to make purchases. To improve interactions with customers and optimize marketing strategies, it is essential for businesses to understand user behavior, preferences, and needs on these platforms. This paper focuses on recommending businesses to customize interactions with users based on their behavioral patterns, leveraging data-driven analysis and machine learning techniques. Businesses can improve engagement and boost the adoption of e-commerce platforms by aligning behavioral patterns with user goals of usability and satisfaction. We propose TheAnalyzer, a clustering-based system designed to enhance business productivity by analyzing user-profiles and improving human-computer interaction. The Analyzer seamlessly integrates with business applications, collecting relevant data points based on users' natural interactions without additional burdens such as questionnaires or surveys. It defines five key user analytics as features for its dataset, which are easily captured through users' interactions with e-commerce platforms. This research presents a study demonstrating the successful distinction of users into specific groups based on the five key analytics considered by TheAnalyzer. With the assistance of domain experts, customized business rules can be attached to each group, enabling The Analyzer to influence business applications and provide an enhanced personalized user experience. The outcomes are evaluated quantitatively and qualitatively, demonstrating that utilizing TheAnalyzer’s capabilities can optimize business outcomes, enhance customer satisfaction, and drive sustainable growth. The findings of this research contribute to the advancement of personalized interactions in e-commerce platforms. By leveraging user behavioral patterns and analyzing both new and existing users, businesses can effectively tailor their interactions to improve customer satisfaction, loyalty and ultimately drive sales.

Keywords: data clustering, data standardization, dimensionality reduction, human computer interaction, user profiling

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Authors: Harithas Aruchchunan

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Silage production is an essential aspect of dairy farming, used to provide high-quality feed to ruminants. However, dairy farmers in Northern Province Sri Lanka are facing multiple challenges that compromise the quality and quantity of silage produced. To tackle these challenges, promoting silage feeding has become an essential component of sustainable dairy farming practices. In this study, silage bale samples were collected from a newly started silage baling factory in Jaffna, Northern province and their quality was analysed at the Veterinary Research Institute laboratory in Kandy in March 2023. The results show the nutritional composition of three Napier grass cultivars: Super Napier, CO6, and Indian Red Napier (BH18). The main parameters analysed were dry matter, pH, lactic acid, soluble carbohydrate, ammonia nitrogen, ash, crude protein, NDF, and ADF. The results indicate that Super Napier and CO6 have higher crude protein content and lower ADF levels, making them suitable for producing high-quality silage. The pH levels of all three cultivars were safe, and the ammonia nitrogen levels were considered appropriate. However, laboratory results indicate that the quality of silage bales produced can be further enhanced. Dairy farmers should be encouraged to adopt these cultivars to achieve better yields as they are high in protein and are better suited to Northern Province's soil and climate. Therefore, it is vital to educate small-scale fodder producers, who supply the raw material to silage factories, on the best practices of cultivating these new cultivars. To improve silage bale production and quality in Northern Province Sri Lanka, we recommend increasing public awareness about silage feeding, providing education and training to dairy farmers and small-scale fodder producers on modern silage production techniques and improving the availability of raw materials for silage production. Additionally, Napier grass cultivars need to be promoted among dairy farmers for better production and quality of silage bales. Failing to improve the quality and quantity of silage bale production could not only lead to the decline of dairy farming in Northern Province Sri Lanka but also the negative impact on the economy

Keywords: silage bales, dairy farming, economic crisis, Sri Lanka

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Authors: Moawia Abulgader Gdara

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En -Naga sub - basin considered to be the most southern of the concessions in the Sirte Basin operated by HOO. En Naga Sub – basin have likely been point-sourced of CO2 accumulations during the last 7 million years from local satellite intrusives associated with the Haruj Al Aswad igneous complex. CO2 occurs in the En Naga Sub-basin as a result of the igneous activity of the Al Harouge Al Aswad complex. Igneous extrusive have been pierced in the subsurface are exposed at the surface. The lower cretaceous Bahi Sandstone facies are recognized in the En Naga Sub-basin. They result from the influence of paleotopography on the processes associated with continental deposition over the Sirt Unconformity and the Cenomanian marine transgression In the Lower Cretaceous Bahi Sandstones, the presence of trapped carbon dioxide is proven within the En Naga Sub-basin. This makes it unique in providing an abundance of CO2 gas reservoirs with almost pure magmatic CO2, which can be easily sampled. Huge amounts of CO2 exist in the Lower Cretaceous Bahi Sandstones in the En-Naga sub-basin, where the economic value of CO2 is related to its use for enhanced oil recovery (EOR) Based on the production tests for the drilled wells that makes Lower Cretaceous Bahi sandstones the principle reservoir rocks for CO2 where large volumes of CO2 gas have been discovered in the Bahi Formation on and near EPSA 120/136(En -Naga sub basin). The Bahi sandstones are generally described as a good reservoir rock. Intergranular porosities and permeabilities are highly variable and can exceed 25% and 100 MD.In the (En Naga sub – basin), The very high pressures assumed associated with local igneous intrusives may account for the abnormally high Bahi (and Lidam Formation) reservoir pressures. The best gas tests from this facies are at F1-72 on the (Barrut I structure) from part of a 458 feet+ section having an estimated high value of CO2 as 98% overpressured. Bahi CO2 prospectivity is thought to be excellent in the central to western areas where At U1-72 (En Naga O structure) a significant CO2 gas kick occurred at 11,971 feet and quickly led to blowout conditions due to uncontrollable leaks in the surface equipment. Which reflects a better reservoir quality sandstones associated with Paleostructural highs. Condensate and gas prospectivity increases to the east as the CO2 prospectivity decreases with distance away from the Al Haruj Al Aswad igneous complex. To date, it has not been possible to accurately determine the volume of these strategically valuable reserves although there are positive indications that they are very large.

Keywords: 1)en naga sub basin, 2)alharouge al aswad igneous complex, 3)co2 generation and migration, 4)lower cretaceous bahi sandstone

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Authors: Zakaria Kharbouch, Mustapha Bouchaara, F. Elkouihen, A. Habbal, A. Ratnani, A. Faik

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Solid-state lithium-ion batteries have garnered increasing interest in modern energy research due to their potential for safer, more efficient, and sustainable energy storage systems. Among the critical components of these batteries, the electrolyte plays a pivotal role, with LLZO garnet-based electrolytes showing significant promise. Garnet materials offer intrinsic advantages such as high Li-ion conductivity, wide electrochemical stability, and excellent compatibility with lithium metal anodes. However, optimizing ionic conductivity in garnet structures poses a complex challenge, primarily due to the multitude of potential dopants that can be incorporated into the LLZO crystal lattice. The complexity of material design, influenced by numerous dopant options, requires a systematic method to find the most effective combinations. This study highlights the utility of machine learning (ML) techniques in the materials discovery process to navigate the complex range of factors in garnet-based electrolytes. Collaborators from the materials science and ML fields worked with a comprehensive dataset previously employed in a similar study and collected from various literature sources. This dataset served as the foundation for an extensive data refinement phase, where meticulous error identification, correction, outlier removal, and garnet-specific feature engineering were conducted. This rigorous process substantially improved the dataset's quality, ensuring it accurately captured the underlying physical and chemical principles governing garnet ionic conductivity. The data refinement effort resulted in a significant improvement in the predictive performance of the machine learning model. Originally starting at an accuracy of 0.32, the model underwent substantial refinement, ultimately achieving an accuracy of 0.88. This enhancement highlights the effectiveness of the interdisciplinary approach and underscores the substantial potential of machine learning techniques in materials science research.

Keywords: lithium batteries, all-solid-state batteries, machine learning, solid state electrolytes

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Authors: Sanaa Riaz

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Spirits occupy a world that simultaneously dwells between the divine and the earthly binary while speaking to all forces of nature, marginality, and extremity in between. This paper examines the conceptualizations, interactions with, and experience of spiritual beings in relation to the concept of self and social agency, defined as a continuum of cooperation leaving those involved with an enhanced or diminished perception of self-agency. To do justice to the diverse mythological and popular interpretations of spirit entities, ethnographic examples from Africa, in particular, will be used. An examination of the nature and role of spirits in Africa allows one to understand the ways in which colonial influences brought by Catholicism and Islam added to the pre-colonial repertoire and syncretic imaginations of spirits. A comprehensive framework to analyze spirits requires situating them as a cognitive configuration of humans to communicate with other humans and forces of nature to receive knowledge about the normative in social roles, conduct, and action. Understanding spirits also requires a rethinking of the concept of self as not one encapsulated in the individual but one representing positionalities in collective negotiations, adversity, and alliances. To use the postmodern understanding of identity as a far from a coherent collection of selves fluidly moving between and dialoguing with gravitational and contradictory social forces, benevolent and maleficent spirit forces represent how people make sense of their origin, physiological and ecological changes, subsistence, and political environment and social relations. A discussion on spirits requires examining the rituals and mediational forces and their performance that allow participants to tackle adversity, voicelessness and continue to work safely and morally for the collective good. Moreover, it is important to see the conceptualization of spirits in unison with sorcery and spirit possession, central to voodoo practices, also because they speak volumes about the experiences of slavery and marginalization. This paper has two motives: It presents a critical literature review of ethnographic accounts of spirit entities in African spiritual experiences to examine the ways in which spirits become mediums through which the self is conceptualized and asserted. Second, the paper highlights the ways in which spirits become a medium to represent political and sociocultural ambiguities and desires along a spectrum of social agencies, including joint agency, vicarious agency, and interfered agency.

Keywords: spirits, social agency, self, ethnographic case studies

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Authors: Qianqian He, Naian Liu, Xiaodong Xie, Linhe Zhang, Yang Zhang, Weidong Yan

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In the wild, the vegetation layer with exceptionally complex fuel composition and heterogeneous spatial distribution strongly affects the rate of fire spread (ROS) and fire intensity. Clarifying the influence of fuel bed structure on fire spread behavior is of great significance to wildland fire management and prediction. The packing ratio is one of the key physical parameters describing the property of the fuel bed. There is a threshold value of the packing ratio for ROS, but little is known about the controlling mechanism. In this study, to address this deficiency, a series of fire spread experiments were performed across a discrete fuel bed composed of some regularly arranged laser-cut cardboards, with constant wind speed and different packing ratios (0.0125-0.0375). The experiment aims to explore the relative importance of the internal and surface heat transfer with packing ratio. The dependence of the measured ROS on the packing ratio was almost consistent with the previous researches. The data of the radiative and total heat fluxes show that the internal heat transfer and surface heat transfer are both enhanced with increasing packing ratio (referred to as ‘Stage 1’). The trend agrees well with the variation of the flame length. The results extracted from the video show that the flame length markedly increases with increasing packing ratio in Stage 1. Combustion intensity is suggested to be increased, which, in turn, enhances the heat radiation. The heat flux data shows that the surface heat transfer appears to be more important than the internal heat transfer (fuel preheating inside the fuel bed) in Stage 1. On the contrary, the internal heat transfer dominates the fuel preheating mechanism when the packing ratio further increases (referred to as ‘Stage 2’) because the surface heat flux keeps almost stable with the packing ratio in Stage 2. As for the heat convection, the flow velocity was measured using Pitot tubes both inside and on the upper surface of the fuel bed during the fire spread. Based on the gas velocity distribution ahead of the flame front, it is found that the airflow inside the fuel bed is restricted in Stage 2, which can reduce the internal heat convection in theory. However, the analysis indicates not the influence of inside flow on convection and combustion, but the decreased internal radiation of per unit fuel is responsible for the decrease of ROS.

Keywords: discrete fuel bed, fire spread, packing ratio, wildfire

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Authors: Awadh O. Al-Anazi

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As part of the organizational needs toward successful maintaining activities, a proper management system need to be put in place, ensuring the effectiveness of maintenance activities. The management system shall clearly describes the process of identifying, prioritizing, planning, scheduling, execution, and providing valuable feedback for all maintenance activities. Completion and accuracy of the system with proper implementation shall provide the organization with a strong platform for effective maintenance activities that are resulted in efficient outcomes toward business success. The purpose of this research was to introduce a practical tool for measuring the maintenance efficiency level within Saudi organizations. A comprehensive study was launched across many maintenance professionals throughout Saudi leading organizations. The study covered five main categories: work process, identification, planning and scheduling, execution, and performance monitoring. Each category was evaluated across many dimensions to determine its current effectiveness through a five-level scale from 'process is not there' to 'mature implementation'. Wide participation was received, responses were analyzed, and the study was concluded by highlighting major gaps and improvement opportunities within Saudi organizations. One effective implementation of the efficiency enhancement efforts was deployed in Saudi Kayan (one of Sabic affiliates). Below details describes the project outcomes: SK overall maintenance wrench time was measured at 20% (on average) from the total daily working time. The assessment indicates the appearance of several organizational gaps, such as a high amount of reactive work, poor coordination and teamwork, Unclear roles and responsibilities, as well as underutilization of resources. Multidiscipline team was assigned to design and implement an appropriate work process that is capable to govern the execution process, improve the maintenance workforce efficiency, and maximize wrench time (targeting > 50%). The enhanced work process was introduced through brainstorming and wide benchmarking, incorporated with a proper change management plan and leadership sponsorship. The project was completed in 2018. Achieved Results: SK WT was improved to 50%, which resulted in 1) reducing the Average Notification completion time. 2) reducing maintenance expenses on OT and manpower support (3.6 MSAR Actual Saving from Budget within 6 months).

Keywords: efficiency, enhancement, maintenance, work force, wrench time

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Authors: Mohammad Khazaei, Reza Rostami, Hassan Gharayagh Zandi, Ruhollah Basatnia, Mahboubeh Ghayour Najafabadi

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Introduction: This study delves into the influence of diverse interventions on brain functional connectivity among young male basketball players. Given the significance of understanding how interventions affect cognitive functions in athletes, particularly in the context of basketball, this research contributes to the growing body of knowledge in sports neuroscience. Methods: Three distinct groups were selected for comprehensive investigation: the Motivational Interview Group, Placebo Consumption Group, and Ritalin Consumption Group. The study involved assessing brain functional connectivity using various frequency bands (Delta, Theta, Alpha, Beta1, Beta2, Gamma, and Total Band) before and after the interventions. The participants were subjected to specific interventions corresponding to their assigned groups. Results: The findings revealed substantial differences in brain functional connectivity across the studied groups. The Motivational Interview Group exhibited optimal outcomes in PLI (Total Band) connectivity. The Placebo Consumption Group demonstrated a marked impact on PLV (Alpha) connectivity, and the Ritalin Consumption Group experienced a considerable enhancement in imCoh (Total Band) connectivity. Discussion: The observed variations in brain functional connectivity underscore the nuanced effects of different interventions on young male basketball players. The enhanced connectivity in specific frequency bands suggests potential cognitive and performance improvements. Notably, the Motivational Interview and Placebo Consumption groups displayed unique patterns, emphasizing the multifaceted nature of interventions. These findings contribute to the understanding of tailored interventions for optimizing cognitive functions in young male basketball players. Conclusion: This study provides valuable insights into the intricate relationship between interventions and brain functional connectivity in young male basketball players. Further research with expanded sample sizes and more sophisticated statistical analyses is recommended to corroborate and expand upon these initial findings. The implications of this study extend to the broader field of sports neuroscience, aiding in the development of targeted interventions for athletes in various disciplines.

Keywords: electroencephalography, Ritalin, Placebo effect, motivational interview

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Authors: Heerak Banerjee, Sourov Roy

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Supersymmetry, one of the most celebrated fields of study for explaining experimental observations where the standard model (SM) falls short, is reeling from the lack of experimental vindication. At the same time, the idea of additional gauge symmetry, in particular, the gauged Lμ-Lτ symmetric models have also generated significant interest. They have been extensively proposed in order to explain the tantalizing discrepancy in the predicted and measured value of the muon anomalous magnetic moment alongside several other issues plaguing the SM. While very little parameter space within these models remain unconstrained, this work finds that the γ + Missing Energy (ME) signal at the Belle-II detector will be a smoking gun for supersymmetry (SUSY) in the presence of a gauged U(1)Lμ-Lτ symmetry. A remarkable consequence of breaking the enhanced symmetry appearing in the limit of degenerate (s)leptons is the nondecoupling of the radiative contribution of heavy charged sleptons to the γ-Z΄ kinetic mixing. The signal process, e⁺e⁻ →γZ΄→γ+ME, is an outcome of this ubiquitous feature. Taking the severe constraints on gauged Lμ-Lτ models by several low energy observables into account, it is shown that any significant excess in all but the highest photon energy bin would be an undeniable signature of such heavy scalar fields in SUSY coupling to the additional gauge boson Z΄. The number of signal events depends crucially on the logarithm of the ratio of stau to smuon mass in the presence of SUSY. In addition, the number is also inversely proportional to the e⁺e⁻ collision energy, making a low-energy, high-luminosity collider like Belle-II an ideal testing ground for this channel. This process can probe large swathes of the hitherto free slepton mass ratio vs. additional gauge coupling (gₓ) parameter space. More importantly, it can explore the narrow slice of Z΄ mass (MZ΄) vs. gₓ parameter space still allowed in gauged U(1)Lμ-Lτ models for superheavy sparticles. The spectacular finding that the signal significance is independent of individual slepton masses is an exciting prospect indeed. Further, the prospect that signatures of even superheavy SUSY particles that may have escaped detection at the LHC may show up at the Belle-II detector is an invigorating revelation.

Keywords: additional gauge symmetry, electron-positron collider, kinetic mixing, nondecoupling radiative effect, supersymmetry

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Authors: Maciej Zasuwa, Grzegorz Ptasinski, Antoni Kopyt

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Nowadays flight simulators offer tremendous possibilities for safe and cost-effective pilot training, by utilization of powerful, computational tools. Due to technology outpacing methodology, vast majority of training related work is done by human instructors. It makes assessment not efficient, and vulnerable to instructors’ subjectivity. The research presents an Objective Assessment Tool (gOAT) developed at the Warsaw University of Technology, and tested on SW-4 helicopter flight simulator. The tool uses database of the predefined manoeuvres, defined and integrated to the virtual environment. These were implemented, basing on Aeronautical Design Standard Performance Specification Handling Qualities Requirements for Military Rotorcraft (ADS-33), with predefined Mission-Task-Elements (MTEs). The core element of the gOAT enhanced algorithm that provides instructor a new set of information. In details, a set of objective flight parameters fused with report about psychophysical state of the pilot. While the pilot performs the task, the gOAT system automatically calculates performance using the embedded algorithms, data registered by the simulator software (position, orientation, velocity, etc.), as well as measurements of physiological changes of pilot’s psychophysiological state (temperature, sweating, heart rate). Complete set of measurements is presented on-line to instructor’s station and shown in dedicated graphical interface. The presented tool is based on open source solutions, and flexible for editing. Additional manoeuvres can be easily added using guide developed by authors, and MTEs can be changed by instructor even during an exercise. Algorithm and measurements used allow not only to implement basic stress level measurements, but also to reduce instructor’s workload significantly. Tool developed can be used for training purpose, as well as periodical checks of the aircrew. Flexibility and ease of modifications allow the further development to be wide ranged, and the tool to be customized. Depending on simulation purpose, gOAT can be adjusted to support simulator of aircraft, helicopter, or unmanned aerial vehicle (UAV).

Keywords: automated assessment, flight simulator, human factors, pilot training

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Authors: Jingyi Li, Laurence Stamford, Alejandro Gallego-Schmid

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Renewable electricity has become an indispensable contributor to achieving net-zero by the mid-century to tackle climate change. Unlike solar, wind, or hydro, geothermal was stagnant in its electricity production development for decades. However, with the significant breakthrough made in recent years, especially the implementation of enhanced geothermal systems (EGS) in various regions globally, geothermal electricity could play a pivotal role in alleviating greenhouse gas emissions. Life cycle assessment has been applied to analyze specific geothermal power generation technologies, which proposed suggestions to optimize its environmental performance. For instance, selecting a high heat gradient region enables a higher flow rate from the production well and extends the technical lifespan. Although such process-level improvements have been made, the significance of geothermal power generation technologies so far has not explicitly displayed its competitiveness on a broader horizon. Therefore, this review-based study integrates a circular economy framework into life cycle assessment, clarifying the underlying added values for geothermal power plants to complete the sustainability profile. The derived results have provided an enlarged platform to discuss geothermal power generation technologies: (i) recover the heat and electricity from the process to reduce the fossil fuel requirements; (ii) recycle the construction materials, such as copper, steel, and aluminum for future projects; (iii) extract the lithium ions from geothermal brine and make geothermal reservoir become a potential supplier of the lithium battery industry; (iv) repurpose the abandoned oil and gas wells to build geothermal power plants; (v) integrate geothermal energy with other available renewable energies (e.g., solar and wind) to provide heat and electricity as a hybrid system at different weather; (vi) rethink the fluids used in stimulation process (EGS only), replace water with CO2 to achieve negative emissions from the system. These results provided a new perspective to the researchers, investors, and policymakers to rethink the role of geothermal in the energy supply network.

Keywords: climate, renewable energy, R strategies, sustainability

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Authors: Seyedahmad Hosseini, Mohammadjavad Sotoudeheian

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Introduction: Allergic asthma is a heterogeneous immuno-inflammatory disease based on Th-2-mediated inflammation. Histopathologic abnormalities of the airways characteristic of asthma include epithelial damage and subepithelial collagen deposition. Objectives: Human bronchial epithelial cell genome expression of TNF‑α, IL‑6, ICAM‑1, VCAM‑1, nuclear factor (NF)‑κB signaling pathways up-regulate during inflammatory cascades. Moreover, immunofluorescence assays confirmed the nuclear translocation of NF‑κB p65 during inflammatory responses. An absolute LDH leakage assays suggestedLPS-inducedcells injury, and the associated mechanisms are co-incident events. LPS-induced phosphorylation of ERKand JNK causes inflammation in epithelial cells through inhibition of ERK and JNK activation and NF-κB signaling pathway. Furthermore, the inhibition of NF-κB mRNA expression and the nuclear translocation of NF-κB lead to anti-inflammatory events. Likewise, activation of SUMF2 which inhibits IL-13 and reduces Th2-cytokines, NF-κB, and IgE levels to ameliorate asthma. On the other hand, TNFα-induced mucus production reduced NF-κB activation through inhibition of the activation status of Rac1 and IκBα phosphorylation. In addition, bradykinin B2 receptor (B2R), which mediates airway remodeling, regulates through NF-κB. Bronchial B2R expression is constitutively elevated in allergic asthma. In addition, certain NF-κB -dependent chemokines function to recruit eosinophils in the airway. Besides, bromodomain containing 4 (BRD4) plays a significant role in mediating innate immune response in human small airway epithelial cells as well as transglutaminase 2 (TG2), which is detectable in saliva. So, the guanine nucleotide-binding regulatory protein α-subunit, Gα16, expresses a κB-driven luciferase reporter. This response was accompanied by phosphorylation of IκBα. Furthermore, expression of Gα16 in saliva markedly enhanced TNF-α-induced κB reporter activity. Methods: The applied method to form NF-κB activation is the electromobility shift assay (EMSA). Also, B2R-BRD4-TG2 complex detection by immunoassay method within saliva with EMSA of NF-κB activation may be a novel biomarker for asthma diagnosis and follow up. Conclusion: This concept introduces NF-κB signaling pathway as potential asthma biomarkers and promising targets for the development of new therapeutic strategies against asthma.

Keywords: NF-κB, asthma, saliva, T-helper

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Authors: Ewa Kamarad

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Recent problems with adopting the EU Regulation on matrimonial property regimes have clearly proven that Member States are unable to agree on the scope of the Regulation and, therefore, on the definitions of matrimonial property and marriage itself. Taking into account that the Regulation on the law applicable to divorce and legal separation, as well as the Regulation on matrimonial property regimes, were adopted in the framework of enhanced cooperation, it is evident that lack of a unified definition of marriage has very wide-ranging consequences. The main problem with the unified definition of marriage is that the EU is not entitled to adopt measures in the domain of material family law, as this area remains under the exclusive competence of the Member States. Because of that, the legislation on marriage in domestic legal orders of the various Member States is very different. These differences concern not only issues such as form of marriage or capacity to enter into marriage, but also the most basic matter, namely the core of the institution of marriage itself. Within the 28 Member States, we have those that allow both different-sex and same-sex marriages, those that have adopted special, separate institutions for same-sex couples, and those that allow only marriage between a man and a woman (e.g. Hungary, Latvia, Lithuania, Poland, Slovakia). Because of the freedom of movement within the European Union, it seems necessary to somehow recognize the civil effects of a marriage that was concluded in another Member State. The most crucial issue is how far that recognition should go. The thesis presented in the presentation is that, at an absolute minimum, the authorities of all Member States must recognize the civil status of the persons who enter into marriage in another Member State. Lack of such recognition might cause serious problems, both for the spouses and for other individuals. The authorities of some Member States may treat the marriage as if it does not exist because it was concluded under foreign law that defines marriage differently. Because of that, it is possible for the spouse to obtain a certificate of civil status stating that he or she is single and thus eligible to enter into marriage – despite being legally married under the law of another Member State. Such certificate can then be used in another country to serve as a proof of civil status. Eventually the lack of recognition can lead to so-called “international bigamy”. The biggest obstacle to recognition of marriages concluded under the law of another Member State that defines marriage differently is the impossibility of transcription of a foreign civil certificate in the case of such a marriage. That is caused by the rule requiring that a civil certificate issued (or transcribed) under one country's law can contain only records of legal institutions recognized by that country's legal order. The presentation is going to provide possible solutions to this problem.

Keywords: civil status, recognition of marriage, conflict of laws, private international law

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Authors: Anila Naz, Arusa Lakhani, Kiran Mubeen, Yasmeen Amarsi

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Pakistan's neonatal mortality rate has the highest proportion in the South Asian region and it is higher in the rural areas as compared to the urban areas. Poor resuscitation techniques and lack of basic newborn resuscitation skills in birth attendants, are contributing factors towards neonatal deaths. Based on the significant outcomes of the Helping Baby Breath (HBB) training, a similar training was implemented for Community Midwives (CMWs) in a low resource setting in Gujrat, Pakistan, to improve their knowledge and skills. The training evaluation was conducted and participant feedback was obtained through both qualitative and quantitative methods. The findings of the quantitative assessment of the training evaluation will be published elsewhere. This paper presents the qualitative evaluation of the training. Objective: The objective of the study was to determine the perceptions of HBB trained CMWs about the effectiveness of the HBB training, and the challenges faced in the implementation of HBB skills for newborn resuscitation, at their work settings. The qualitative descriptive design was used in this study. The purposive sampling technique was chosen to recruit midwives and key informants as participants of the training. Interviews were conducted by using a semi-structured interview guide. The study included a total of five interviews: two focus group interviews for CMWs (10 in each group), and three individual interviews of key informants. The content analysis of the qualitative data yielded three themes: the effectiveness of training, challenges, and suggestions. The findings revealed that the HBB training was effective for the CMWs in terms of its usability, regarding improvement in newborn resuscitation knowledge and skills. Moreover, it enhanced confidence and satisfaction in CMWs. However, less volume of patients was a challenge for a few CMWs with regards to practicing their skills. Due to the inadequate number of patients and less opportunities of practice for several CMWs, they required such trainings frequently, in order to maintain their competency. The CMWs also recommended that HBB training should be part of the Midwifery program curriculum. Moreover, similar trainings were also recommended for other healthcare providers working in low resource settings, including doctors and nurses.

Keywords: neonatal resuscitation technique, helping baby breathe, community midwives, training evaluation

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Authors: Ruchi Pathania, Ahmad Ahmad, Shireesh Srivastava

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Cyanobacteria is a promising microbe that can capture and convert atmospheric CO₂ and light into valuable industrial bio-products like biofuels, biodegradable plastics, etc. Among their most attractive traits are faster autotrophic growth, whole year cultivation using non-arable land, high photosynthetic activity, much greater biomass and productivity and easy for genetic manipulations. Cyanobacteria store carbon in the form of glycogen which can be hydrolyzed to release glucose and fermented to form bioethanol or other valuable products. Marine cyanobacterial species are especially attractive for countries with scarcity of freshwater. We recently identified a marine native cyanobacterium Synechococcus sp. BDU 130192 which has good growth rate and high level of polyglucans accumulation compared to Synechococcus PCC 7002. In this study, firstly we sequenced the whole genome and the sequences were annotated using the RAST server. Genome scale metabolic model (GSMM) was reconstructed through COBRA toolbox. GSMM is a computational representation of the metabolic reactions and metabolites of the target strain. GSMMs construction through the application of Flux Balance Analysis (FBA), which uses external nutrient uptake rates and estimate steady state intracellular and extracellular reaction fluxes, including maximization of cell growth. The model, which we have named isyn942, includes 942 reactions and 913 metabolites having 831 metabolic, 78 transport and 33 exchange reactions. The phylogenetic tree obtained by BLAST search revealed that the strain was a close relative of Synechococcus PCC 7002. The flux balance analysis (FBA) was applied on the model iSyn942 to predict the theoretical yields (mol product produced/mol CO₂ consumed) for native and non-native products like acetone, butanol, etc. under phototrophic condition by applying metabolic engineering strategies. The reported strain can be a viable strain for biotechnological applications, and the model will be helpful to researchers interested in understanding the metabolism as well as to design metabolic engineering strategies for enhanced production of various bioproducts.

Keywords: cyanobacteria, flux balance analysis, genome scale metabolic model, metabolic engineering

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Authors: Ju Peng Poh, Jun Yu Charles Lee, Jonathan Chew Hoe Khoo

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The emergence of digital twin technology, a digital replica of physical world, has improved the real-time access to data from sensors about the performance of buildings. This digital transformation has opened up many opportunities to improve the management of the building by using the data collected to help monitor consumption patterns and energy leakages. One example is the integration of predictive models for anomaly detection. In this paper, we use the GAM (Generalised Additive Model) for the anomaly detection of Air Handling Units (AHU) power consumption pattern. There is ample research work on the use of GAM for the prediction of power consumption at the office building and nation-wide level. However, there is limited illustration of its anomaly detection capabilities, prescriptive analytics case study, and its integration with the latest development of digital twin technology. In this paper, we applied the general GAM modelling framework on the historical data of the AHU power consumption and cooling load of the building between Jan 2018 to Aug 2019 from an education campus in Singapore to train prediction models that, in turn, yield predicted values and ranges. The historical data are seamlessly extracted from the digital twin for modelling purposes. We enhanced the utility of the GAM model by using it to power a real-time anomaly detection system based on the forward predicted ranges. The magnitude of deviation from the upper and lower bounds of the uncertainty intervals is used to inform and identify anomalous data points, all based on historical data, without explicit intervention from domain experts. Notwithstanding, the domain expert fits in through an optional feedback loop through which iterative data cleansing is performed. After an anomalously high or low level of power consumption detected, a set of rule-based conditions are evaluated in real-time to help determine the next course of action for the facilities manager. The performance of GAM is then compared with other approaches to evaluate its effectiveness. Lastly, we discuss the successfully deployment of this approach for the detection of anomalous power consumption pattern and illustrated with real-world use cases.

Keywords: anomaly detection, digital twin, generalised additive model, GAM, power consumption, supervised learning

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Authors: Ariadne C. Catto, Luis F. da Silva, Khalifa Aguir, Valmor Roberto Mastelaro

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Zinc oxide (ZnO) pure or doped are one of the most promising metal oxide semiconductors for gas sensing applications due to the well-known high surface-to-volume area and surface conductivity. It was shown that ZnO is an excellent gas-sensing material for different gases such as CO, O2, NO2 and ethanol. In this context, pure and doped ZnO exhibiting different morphologies and a high surface/volume ratio can be a good option regarding the limitations of the current commercial sensors. Different studies showed that the sensitivity of metal-doped ZnO (e.g. Co, Fe, Mn,) enhanced its gas sensing properties. Motivated by these considerations, the aim of this study consisted on the investigation of the role of Co ions on structural, morphological and the gas sensing properties of nanostructured ZnO samples. ZnO and Zn1-xCoxO (0 < x < 5 wt%) thin films were obtained via the polymeric precursor method. The sensitivity, selectivity, response time and long-term stability gas sensing properties were investigated when the sample was exposed to a different concentration range of ozone (O3) at different working temperatures. The gas sensing property was probed by electrical resistance measurements. The long and short-range order structure around Zn and Co atoms were investigated by X-ray diffraction and X-ray absorption spectroscopy. X-ray photoelectron spectroscopy measurement was performed in order to identify the elements present on the film surface as well as to determine the sample composition. Microstructural characteristics of the films were analyzed by a field-emission scanning electron microscope (FE-SEM). Zn1-xCoxO XRD patterns were indexed to the wurtzite ZnO structure and any second phase was observed even at a higher cobalt content. Co-K edge XANES spectra revealed the predominance of Co2+ ions. XPS characterization revealed that Co-doped ZnO samples possessed a higher percentage of oxygen vacancies than the ZnO samples, which also contributed to their excellent gas sensing performance. Gas sensor measurements pointed out that ZnO and Co-doped ZnO samples exhibit a good gas sensing performance concerning the reproducibility and a fast response time (around 10 s). Furthermore, the Co addition contributed to reduce the working temperature for ozone detection and improve the selective sensing properties.

Keywords: cobalt-doped ZnO, nanostructured, ozone gas sensor, polymeric precursor method

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Authors: Mohamed S. Selim, Nesreen A. Fatthallah, Shimaa A. Higazy, Hekmat R. Madian, Sherif A. El-Safty, Mohamed A. Shenashen

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After the 2003 prohibition on employing TBT-based antifouling coatings, polysiloxane antifouling nano-coatings have gained in popularity as environmentally friendly and cost-effective replacements. A series of non-toxic polydimethylsiloxane nanocomposites filled with nanosheets of graphene oxide (GO) decorated with magnetite nanospheres (GO-Fe₃O₄ nanospheres) were developed and cured via a catalytic hydrosilation method. Various GO-Fe₃O₄ hybrid concentrations were mixed with the silicone resin via solution casting technique to evaluate the structure–property connection. To generate GO nanosheets, a modified Hummers method was applied. A simple co-precipitation method was used to make spherical magnetite particles under inert nitrogen. Hybrid GO-Fe₃O₄ composite fillers were developed by a simple ultrasonication method. Superhydrophobic PDMS/GO-Fe₃O₄ nanocomposite surface with a micro/nano-roughness, reduced surface-free energy (SFE), high fouling release (FR) efficiency was achieved. The physical, mechanical, and anticorrosive features of the virgin and GO-Fe₃O₄ filled nanocomposites were investigated. The synergistic effects of GO-Fe₃O4 hybrid's well-dispersion on the water-repellency and surface topological roughness of the PDMS/GO-Fe₃O₄ nanopaints were extensively studied. The addition of the GO-Fe₃O₄ hybrid fillers till 1 wt.% could increase the coating's water contact angle (158°±2°), minimize its SFE to 12.06 mN/m, develop outstanding micro/nano-roughness, and improve its bulk mechanical and anticorrosion properties. Several microorganisms were employed for examining the fouling-resistance of the coated specimens for 1 month. Silicone coatings filled with 1 wt.% GO-Fe₃O₄ nanofiller showed the least biodegradability% among all the tested microorganisms. Whereas GO-Fe₃O4 with 5 wt.% nanofiller possessed the highest biodegradability% potency by all the microorganisms. We successfully developed non-toxic and low cost nanostructured FR composite coating with high antifouling-resistance, reproducible superhydrophobic character, and enhanced service-time for maritime navigation.

Keywords: silicone antifouling, environmentally friendly, nanocomposites, nanofillers, fouling repellency, hydrophobicity

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Authors: Mei-Hui Liu

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This paper reports the progression of language teachers’ learning to assess students’ speech act performance via online videos in a cross-tier professional growth community. This yearlong research project collected multiple data sources from several stakeholders, including 12 preservice and 4 inservice English as a foreign language (EFL) teachers, 4 English professionals, and 82 high school students. Data sources included surveys, (focus group) interviews, online reflection journals, online video-based assessment items/scores, and artifacts related to teacher professional learning. The major findings depicted the effectiveness of this proposed learning module on language teacher development in pragmatic assessment as well as its impact on student learning experience. All these teachers appreciated this professional learning experience which enhanced their knowledge in assessing students’ pragmalinguistic and sociopragmatic performance in an English speech act (i.e., making refusals). They learned how to design online video-based assessment items by attending to specific linguistic structures, semantic formula, and sociocultural issues. They further became aware of how to sharpen pragmatic instructional skills in the near future after putting theories into online assessment and related classroom practices. Additionally, data analysis revealed students’ achievement in and satisfaction with the designed online assessment. Yet, during the professional learning process most participating teachers encountered challenges in reaching a consensus on selecting appropriate video clips from available sources to present the sociocultural values in English-speaking refusal contexts. Also included was to construct test items which could testify the influence of interlanguage transfer on students’ pragmatic performance in various conversational scenarios. With pedagogical implications and research suggestions, this study adds to the increasing amount of research into integrating preservice and inservice EFL teacher education in pragmatic assessment and relevant instruction. Acknowledgment: This research project is sponsored by the Ministry of Science and Technology in the Republic of China under the grant number of MOST 106-2410-H-029-038.

Keywords: cross-tier professional development, inservice EFL teachers, pragmatic assessment, preservice EFL teachers, student learning experience

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Authors: Tatsuhiko Aizawa, Yohei Suzuki, Tomomi Shiratori

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The austenitic stainless steel type AISI316 has been widely utilized as structural members and mold die substrates. The low temperature plasma nitriding has been utilized to harden these AISI316 members, parts, and dies without loss of intrinsic corrosion resistance to AISI316 stainless steels. Formation of CrN precipitates by normal plasma nitriding processes resulted in severe deterioration of corrosion toughness. Most previous studies on this low temperature nitriding of AISI316 only described the lattice expansion of original AISI316 lattices by the occupation of nitrogen interstitial solutes into octahedral vacancy sites, the significant hardening by nitrogen solid solution, and the enhancement of corrosion toughness. In addition to those engineering items, this low temperature nitriding process was characterized by the nitrogen supersaturation and nitrogen diffusion processes. The nitrogen supersaturated zones expanded by the nitrogen solute occupation to octahedral vacancy sites, and the un-nitrided surroundings to these zones were plastically strained to compensate for the mismatch strains across these nitrided and nitrided zones. The microstructure of nitrided AISI316 was refined by this plastic straining. The nitrogen diffusion process was enhanced to transport nitrogen solute atoms through the refined zone boundaries. This synergetic collaboration among the nitrogen supersaturation, the lattice expansion, the plastic straining, and the grain refinement yielded a thick nitrogen supersaturated layer. This synergetic relation was also characterized by the multilevel two-phase structuring. In XRD (X-Ray Diffraction) analysis, the nitrided AISI316 layer had - and -phases with the peak shifts from original lattices. After EBSD (Electron Back Scattering Diffraction) analysis, -grains and -grains homogeneously distributed in the nitrided layer. The scanning transmission electron microscopy (STEM) revealed that g-phase zone is N-poor cluster and a-phase zone is N-rich cluster. This proves that nitrogen supersaturated AISI316 stainless steels have multi-level two-phase structure in a very fine granular system.

Keywords: AISI316 stainless steels, chemical affinity to nitrogen solutes, multi-level two-phase structuring, nitrogen supersaturation

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Authors: Gurfateh Singh, Mu Khan, Razia Khanam, Govind Mohan

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Objective: The present study has been designed to investigate the beneficial role of Fenofibrate & Clofibrate in attenuated the cardioprotective effect of ischemic preconditioning (IPC) in hyperlipidemic rat hearts. Materials & Methods: Experimental hyperlipidemia was produced by feeding high fat diet to rats for a period of 28 days. Isolated langendorff’s perfused normal and hyperlipidemic rat hearts were subjected to global ischemia for 30 min followed by reperfusion for 120 min. The myocardial infarct size was assessed macroscopically using triphenyltetrazolium chloride staining. Coronary effluent was analyzed for lactate dehydrogenase (LDH) and creatine kinase-MB release to assess the extent of cardiac injury. Moreover, the oxidative stress in heart was assessed by measuring thiobarbituric acid reactive substance, superoxide anion generation and reduced form of glutathione. Results: The ischemia-reperfusion (I/R) has been noted to induce oxidative stress by increasing TBARS, superoxide anion generation and decreasing reduced form of glutathione in normal and hyperlipidemic rat hearts. Moreover, I/R produced myocardial injury, which was assessed in terms of increase in myocardial infarct size, LDH and CK-MB release in coronary effluent and decrease in coronary flow rate in normal and hyperlipidemic rat hearts. In addition, the hyperlipidemic rat hearts showed enhanced I/R-induced myocardial injury with high degree of oxidative stress as compared with normal rat hearts subjected to I/R. Four episodes of IPC (5 min each) afforded cardioprotection against I/R-induced myocardial injury in normal rat hearts as assessed in terms of improvement in coronary flow rate and reduction in myocardial infarct size, LDH, CK-MB and oxidative stress. On the other hand, IPC mediated myocardial protection against I/R-injury was abolished in hyperlipidemic rat hearts. However, Treatment with Fenofibrate (100 mg/kg/day, i.p.), Clofibrate (300mg/kg/day, i.p.) as a agonists of PPAR-α have not affected the cardioprotective effect of IPC in normal rat hearts, but its treatment markedly restored the cardioprotective potentials of IPC in hyperlipidemic rat hearts. Conclusion: It is noted that the high degree of oxidative stress produced in hyperlipidemic rat heart during reperfusion and consequent down regulation of PPAR-α may be responsible to abolish the cardioprotective potentials of IPC.

Keywords: Hyperlipidemia, ischemia-reperfusion injury, ischemic preconditioning, PPAR-α

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Authors: Ella Sèdé Maforikan

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Accurate land cover mapping is essential for effective environmental monitoring and natural resources management. This study focuses on assessing the classification performance of two satellite datasets and evaluating the impact of different input feature combinations on classification accuracy in the Beterou catchment, situated in the northern part of Benin. Landsat-8 and Sentinel-2 images from June 1, 2020, to March 31, 2021, were utilized. Employing the Random Forest (RF) algorithm on Google Earth Engine (GEE), a supervised classification categorized the land into five classes: forest, savannas, cropland, settlement, and water bodies. GEE was chosen due to its high-performance computing capabilities, mitigating computational burdens associated with traditional land cover classification methods. By eliminating the need for individual satellite image downloads and providing access to an extensive archive of remote sensing data, GEE facilitated efficient model training on remote sensing data. The study achieved commendable overall accuracy (OA), ranging from 84% to 85%, even without incorporating spectral indices and terrain metrics into the model. Notably, the inclusion of additional input sources, specifically terrain features like slope and elevation, enhanced classification accuracy. The highest accuracy was achieved with Sentinel-2 (OA = 91%, Kappa = 0.88), slightly surpassing Landsat-8 (OA = 90%, Kappa = 0.87). This underscores the significance of combining diverse input sources for optimal accuracy in land cover mapping. The methodology presented herein not only enables the creation of precise, expeditious land cover maps but also demonstrates the prowess of cloud computing through GEE for large-scale land cover mapping with remarkable accuracy. The study emphasizes the synergy of different input sources to achieve superior accuracy. As a future recommendation, the application of Light Detection and Ranging (LiDAR) technology is proposed to enhance vegetation type differentiation in the Beterou catchment. Additionally, a cross-comparison between Sentinel-2 and Landsat-8 for assessing long-term land cover changes is suggested.

Keywords: land cover mapping, Google Earth Engine, random forest, Beterou catchment

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Authors: Wahhaj Ahmed Farooqi, Bilal Ahmad, Sandra Maritza Zambrano Bernal

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In view of structural engineering, monitoring of structural responses over time is of great importance with respect to recent developments of construction technologies. Recently, developments of advanced computing tools have enabled researcher’s better execution of structural health monitoring (SHM) and control systems. In the last decade, building information modeling (BIM) has substantially enhanced the workflow of planning and operating engineering structures. Typically, building information can be stored and exchanged via model files that are based on the Industry Foundation Classes (IFC) standard. In this study a modeling approach for semantic modeling of SHM and control systems is integrated into the BIM methodology using the IFC standard. For validation of the modeling approach, a laboratory test structure, a four-story shear frame structure, is modeled using a conventional BIM software tool. An IFC schema extension is applied to describe information related to monitoring and control of a prototype SHM and control system installed on the laboratory test structure. The SHM and control system is described by a semantic model applying Unified Modeling Language (UML). Subsequently, the semantic model is mapped into the IFC schema. The test structure is composed of four aluminum slabs and plate-to-column connections are fully fixed. In the center of the top story, semi-active tuned liquid column damper (TLCD) is installed. The TLCD is used to reduce effects of structural responses in context of dynamic vibration and displacement. The wireless prototype SHM and control system is composed of wireless sensor nodes. For testing the SHM and control system, acceleration response is automatically recorded by the sensor nodes equipped with accelerometers and analyzed using embedded computing. As a result, SHM and control systems can be described within open BIM, dynamic responses and information of damages can be stored, documented, and exchanged on the formal basis of the IFC standard.

Keywords: structural health monitoring, open building information modeling, industry foundation classes, unified modeling language, semi-active tuned liquid column damper, nondestructive testing

Procedia PDF Downloads 151

Authors: Muhammad Saleem

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Background: The teaching of sports sciences encompasses a broad spectrum of disciplines, including biomechanics, physiology, psychology, and coaching. Effective pedagogical techniques are crucial in imparting both theoretical knowledge and practical skills necessary for students to excel in the field. The impact of these techniques on students’ learning outcomes, engagement, and professional preparedness remains a vital area of study. Objective: This study aims to evaluate the effectiveness of various pedagogical techniques used in the teaching of sports sciences. It seeks to identify which methods most significantly enhance student learning, retention, engagement, and practical application of knowledge. Methods: A mixed-methods approach was employed, including both quantitative and qualitative analyses. The study involved a comparative analysis of traditional lecture-based teaching, experiential learning, problem-based learning (PBL), and technology-enhanced learning (TEL). Data were collected through surveys, interviews, and academic performance assessments from students enrolled in sports sciences programs at multiple universities. Statistical analysis was used to evaluate academic performance, while thematic analysis was applied to qualitative data to capture student experiences and perceptions. Results: The findings indicate that experiential learning and PBL significantly improve students' understanding and retention of complex sports science concepts compared to traditional lectures. TEL was found to enhance engagement and provide students with flexible learning opportunities, but its impact on deep learning varied depending on the quality of the digital resources. Overall, a combination of experiential learning, PBL, and TEL was identified as the most effective pedagogical approach, leading to higher student satisfaction and better preparedness for real-world applications. Conclusion: The study underscores the importance of adopting diverse and student-centered pedagogical techniques in the teaching of sports sciences. While traditional lectures remain useful for foundational knowledge, integrating experiential learning, PBL, and TEL can substantially improve student outcomes. These findings suggest that educators should consider a blended approach to pedagogy to maximize the effectiveness of sports science education.

Keywords: sport sciences, pedagogical techniques, health and physical education, problem-based learning, student engagement

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Authors: Zeta Dooly, Aidan Duane

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The collaborative European funded research and development landscape provides prime environmental conditions for multi-disciplinary teams to learn and enhance their knowledge beyond the capability of training and learning within their own organisation cocoons. Whilst the emergence of the academic entrepreneur has changed the focus of educational institutions to that of quasi-businesses, the training and professional development of lecturers and academic staff are often not formalised to the same level as industry. This research focuses on industry and academic collaborative research funded by the European Commission. The impact of research is scalable if an optimum research network is created and managed effectively. This paper investigates network embeddedness, the nature of relationships, links, and nodes within a research network, and the enhancement of the network’s knowledge. The contribution of this paper extends our understanding of establishing and maintaining effective collaborative research networks. The effects of network embeddedness are recognized in the literature as pertinent to innovation and the economy. Network theory literature claims that networks are essential to innovative clusters such as Silicon valley and innovation in high tech industries. This research provides evidence to support the impact collaborative research has on the disparate individuals toward their innovative contributions to their organisations and their own professional development. This study adopts a qualitative approach and uncovers some of the challenges of multi-disciplinary research through case study insights. The contribution of this paper recommends the establishment of scaffolding to accommodate cooperation in research networks, role appointment, and addressing contextual complexities early to avoid problem cultivation. Furthermore, it suggests recommendations in relation to network formation, intra-network challenges in relation to open data, competition, friendships, and competency enhancement. The network capability is enhanced by the adoption of the relevant theories; network theory, open innovation, and social exchange, with the understanding that the network structure has an impact on innovation and social exchange in research networks. The research concludes that there is an opportunity to deepen our understanding of the impact of network reuse and network hoping that provides scaffolding for the network members to enhance and build upon their knowledge using a progressive approach.

Keywords: research networks, competency building, network theory, case study

Procedia PDF Downloads 126

Authors: John-Nelson Ekumah, Selorm Yao-Say Solomon Adade, Mingming Zhong, Yufan Sun, Qiufang Liang, Muhammad Safiullah Virk, Xorlali Nunekpeku, Nana Adwoa Nkuma Johnson, Bridget Ama Kwadzokpui, Xiaofeng Ren

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Enhancing starch gel strength and stability is crucial. However, traditional gel property assessment methods are destructive, time-consuming, and resource-intensive. Thus, understanding ethanol treatment effects on kudzu starch gel strength and developing a rapid, nondestructive gel strength assessment method is essential for optimizing the treatment process and ensuring product quality consistency. This study investigated the effects of different ethanol concentrations on the microstructure of kudzu starch gels using a comprehensive microstructural analysis. We also developed a nondestructive method for predicting gel strength and classifying treatment levels using near-infrared (NIR) spectroscopy, and advanced data analytics. Scanning electron microscopy revealed progressive network densification and pore collapse with increasing ethanol concentration, correlating with enhanced mechanical properties. NIR spectroscopy, combined with various variable selection methods (CARS, GA, and UVE) and modeling algorithms (PLS, SVM, and ELM), was employed to develop predictive models for gel strength. The UVE-SVM model demonstrated exceptional performance, with the highest R² values (Rc = 0.9786, Rp = 0.9688) and lowest error rates (RMSEC = 6.1340, RMSEP = 6.0283). Pattern recognition algorithms (PCA, LDA, and KNN) successfully classified gels based on ethanol treatment levels, achieving near-perfect accuracy. This integrated approach provided a multiscale perspective on ethanol-induced starch gel modification, from molecular interactions to macroscopic properties. Our findings demonstrate the potential of NIR spectroscopy, coupled with advanced data analysis, as a powerful tool for rapid, nondestructive quality assessment in starch gel production. This study contributes significantly to the understanding of starch modification processes and opens new avenues for research and industrial applications in food science, pharmaceuticals, and biomaterials.

Keywords: kudzu starch gel, near-infrared spectroscopy, gel strength prediction, support vector machine, pattern recognition algorithms, ethanol treatment

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Authors: Huzaifa Bilal

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Russian wheat aphid (Diuraphis noxia, Kurdjumov) is considered an economically important wheat (Triticum aestivum L.) pest worldwide and in South Africa. The RWA damages wheat plants and reduces annual yields by more than 10%. Even though pest management by pesticides and resistance breeding is an attractive option, chemicals can cause harm to the environment. Furthermore, the evolution of resistance-breaking aphid biotypes has out-paced the release of resistant cultivars. An alternative strategy to reduce the impact of aphid damage on plants, such as priming, which sensitizes plants to respond effectively to subsequent attacks, is necessary. In this study, wheat plants at the seedling and flag leaf stages were primed by salicylic acid and isolate representative of two races of the leaf rust pathogen Puccinia triticina Eriks. (Pt), before RWA (South African RWA biotypes 1 and 4) infestation. Randomized complete block design experiments were conducted in the greenhouse to study plant-pest interaction in primed and non-primed plants. Analysis of induced aphid damage indicated salicylic acid differentially primed wheat cultivars for increased resistance to the RWASA biotypes. At the seedling stage, all cultivars were primed for enhanced resistance to RWASA1, while at the flag leaf stage, only PAN 3111, SST 356 and Makalote were primed for increased resistance. The Puccinia triticina efficaciously primed wheat cultivars for excellent resistance to RWASA1 at the seedling and flag leaf stages. However, Pt failed to enhance the four Lesotho cultivars' resistance to RWASA4 at the seedling stage and PAN 3118 at the flag leaf stage. The induced responses at the seedling and flag leaf stages were positively correlated in all the treatments. Primed plants induced high activity of antioxidant enzymes like peroxidase, ascorbate peroxidase and superoxide dismutase. High antioxidant activity indicates activation of resistant responses in primed plants (primed by salicylic acid and Puccina triticina). Isolates of avirulent Pt races can be a worthy priming agent for improved resistance to RWA infestation. Further confirmation of the priming effects needs to be evaluated at the field trials to investigate its application efficiency.

Keywords: Russian wheat aphis, salicylic acid, puccina triticina, priming

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Authors: Sudha T., Naveen C.

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Dengue is a serious public health issue that causes significant annual economic and welfare burdens on nations. However, enhanced optimization techniques and quantitative modeling approaches can predict the incidence of dengue. By advocating for a data-driven approach, public health officials can make informed decisions, thereby improving the overall effectiveness of sudden disease outbreak control efforts. The National Oceanic and Atmospheric Administration and the Centers for Disease Control and Prevention are two of the U.S. Federal Government agencies from which this study uses environmental data. Based on environmental data that describe changes in temperature, precipitation, vegetation, and other factors known to affect dengue incidence, many predictive models are constructed that use different machine learning methods to estimate weekly dengue cases. The first step involves preparing the data, which includes handling outliers and missing values to make sure the data is prepared for subsequent processing and the creation of an accurate forecasting model. In the second phase, multiple feature selection procedures are applied using various machine learning models and optimization techniques. During the third phase of the research, machine learning models like the Huber Regressor, Support Vector Machine, Gradient Boosting Regressor (GBR), and Support Vector Regressor (SVR) are compared with several optimization techniques for feature selection, such as Harmony Search and Genetic Algorithm. In the fourth stage, the model's performance is evaluated using Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) as assistance. Selecting an optimization strategy with the least number of errors, lowest price, biggest productivity, or maximum potential results is the goal. In a variety of industries, including engineering, science, management, mathematics, finance, and medicine, optimization is widely employed. An effective optimization method based on harmony search and an integrated genetic algorithm is introduced for input feature selection, and it shows an important improvement in the model's predictive accuracy. The predictive models with Huber Regressor as the foundation perform the best for optimization and also prediction.

Keywords: deep learning model, dengue fever, prediction, optimization

Procedia PDF Downloads 65