Search results for: robust modeling

Authors: Roxane A. Legaie, Kjiana E. Schwab, Caroline E. Gargett

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Studies looking at the changes in gene expression from RNAseq data often make use of linear models. It is also common practice to focus on a subset of data for a comparison of interest, leaving aside the samples not involved in this particular comparison. This work shows the importance of including all observations in the modeling process to better estimate variance parameters, even when the samples included are not directly used in the comparison under test. The human endometrium is a dynamic tissue, which undergoes cycles of growth and regression with each menstrual cycle. The mesenchymal stem cells (MSCs) present in the endometrium are likely responsible for this remarkable regenerative capacity. However recent studies suggest that MSCs also plays a role in the pathogenesis of endometriosis, one of the most common medical conditions affecting the lower abdomen in women in which the endometrial tissue grows outside the womb. In this study we compared gene expression profiles between MSCs and non-stem cell counterparts (‘non-MSC’) obtained from women with (‘E’) or without (‘noE’) endometriosis from RNAseq. Raw read counts were used for differential expression analysis using a linear model with the limma-voom R package, including either all samples in the study or only the samples belonging to the subset of interest (e.g. for the comparison ‘E vs noE in MSC cells’, including only MSC samples from E and noE patients but not the non-MSC ones). Using the full dataset we identified about 100 differentially expressed (DE) genes between E and noE samples in MSC samples (adj.p-val < 0.05 and |logFC|>1) while only 9 DE genes were identified when using only the subset of data (MSC samples only). Important genes known to be involved in endometriosis such as KLF9 and RND3 were missed in the latter case. When looking at the MSC vs non-MSC cells comparison, the linear model including all samples identified 260 genes for noE samples (including the stem cell marker SUSD2) while the subset analysis did not identify any DE genes. When looking at E samples, 12 genes were identified with the first approach and only 1 with the subset approach. Although the stem cell marker RGS5 was found in both cases, the subset test missed important genes involved in stem cell differentiation such as NOTCH3 and other potentially related genes to be used for further investigation and pathway analysis.

Keywords: differential expression, endometriosis, linear model, RNAseq

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Authors: Thomas Monahan, Nicolas Gorius, Thanh Nguyen

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Exoplanet atmospheric parameters retrieval is a complex, computationally intensive, inverse modeling problem in which an exoplanet’s atmospheric composition is extracted from an observed spectrum. Traditional Bayesian sampling methods require extensive time and computation, involving algorithms that compare large numbers of known atmospheric models to the input spectral data. Runtimes are directly proportional to the number of parameters under consideration. These increased power and runtime requirements are difficult to accommodate in space missions where model size, speed, and power consumption are of particular importance. The use of traditional Bayesian sampling methods, therefore, compromise model complexity or sampling accuracy. The Atmospheric Retrievals conditional Generative Adversarial Network (ARcGAN) is a deep convolutional generative adversarial network that improves on the previous model’s speed and accuracy. We demonstrate the efficacy of artificial intelligence to quickly and reliably predict atmospheric parameters and present it as a viable alternative to slow and computationally heavy Bayesian methods. In addition to its broad applicability across instruments and planetary types, ARcGAN has been designed to function on low power application-specific integrated circuits. The application of edge computing to atmospheric retrievals allows for real or near-real-time quantification of atmospheric constituents at the instrument level. Additionally, edge computing provides both high-performance and power-efficient computing for AI applications, both of which are critical for space missions. With the edge computing chip implementation, ArcGAN serves as a strong basis for the development of a similar machine-learning algorithm to reduce the downlinked data volume from the Compact Ultraviolet to Visible Imaging Spectrometer (CUVIS) onboard the DAVINCI mission to Venus.

Keywords: deep learning, generative adversarial network, edge computing, atmospheric parameters retrieval

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Authors: Guannan Ren, Thomas Mazzuchi, Shahram Sarkani

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Electric vehicle battery recycling has emerged as a critical process in the transition toward sustainable transportation. As the demand for electric vehicles continues to rise, so does the need to address the end-of-life management of their batteries. Electric vehicle battery recycling benefits resource recovery and supply chain stability by reclaiming valuable metals like lithium, cobalt, nickel, and graphite. The reclaimed materials can then be reintroduced into the battery manufacturing process, reducing the reliance on raw material extraction and the environmental impacts of waste. Current battery recycling rates are insufficient to meet the growing demands for raw materials. While significant progress has been made in electric vehicle battery recycling, many areas can still improve. Standardization of battery designs, increased collection and recycling infrastructures, and improved efficiency in recycling processes are essential for scaling up recycling efforts and maximizing material recovery. This work delves into key factors, such as regulatory frameworks, economic incentives, and technological processes, that influence the cost-effectiveness and efficiency of battery recycling systems. A system dynamics model that considers variables such as battery production rates, demand and price fluctuations, recycling infrastructure capacity, and the effectiveness of recycling processes is created to study how these variables are interconnected, forming feedback loops that affect the overall supply chain efficiency. Such a model can also help simulate the effects of stricter regulations on battery disposal, incentives for recycling, or investments in research and development for battery designs and advanced recycling technologies. By using the developed model, policymakers, industry stakeholders, and researchers may gain insights into the effects of applying different policies or process updates on electric vehicle battery recycling rates.

Keywords: environmental engineering, modeling and simulation, circular economy, sustainability, transportation science, policy

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Authors: Sunil Arora, Anitya Kumar Jena, S. A. Ravi

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India is at the cusp of major reforms in the hydrocarbon sector. Oil and gas sector is highly liberalised to attract private investment and to increase domestic production. Major hydrocarbon Exploration & Production (E&P) activity here have been undertaken by Government owned companies but with easing up and reworking of hydro carbon exploration licensing policies private players have also joined the fray towards achieving energy security for India. Government of India has come up with policy and administrative reforms including Hydrocarbon Exploration and Licensing Policy (HELP), Sagarmala (port-led development with coastal connectivity), and Development of Small Discovered Fields, etc. with the intention to make industry friendly conditions for investment, ease of doing business and reduce gestation period. To harness the potential resources of Deep water and Ultra deep water, High Pressure – High Temperature (HP-HT) regions, Coal Bed Methane (CBM), Shale Hydrocarbons besides Gas Hydrates, participation shall be required from both domestic and international players. Companies engaged in E&P activities in India have traditionally been managing through their captive supply base, but with crude prices under hammer, the need is being felt to outsource non-core activities. This necessitates establishment of a robust support services to cater to E&P Industry, which is currently non-existent to meet the bourgeon challenges. This paper outlines an agenda for creating an Integrated Services Hub (ISH) under Special Economic Zone (SEZ) to facilitate complete gamut of non-core support activities of E&P industry. This responsive and proficient multi-usage facility becomes viable with better resource utilization, economies of scale to offer cost effective services. The concept envisages companies to bring-in their core technical expertise leaving complete hardware peripherals outsourced to this ISH. The Integrated Services Hub, complying with the best in class global standards, shall typically provide following Services under Single Window Solution, but not limited to: a) Logistics including supply base operations, transport of manpower and material, helicopters, offshore supply vessels, warehousing, inventory management, sourcing and procurement activities, international freight forwarding, domestic trucking, customs clearance service etc. b) Trained/Experienced pool of competent Manpower (Technical, Security etc.) will be available for engagement by companies on either short or long term basis depending upon the requirements with provisions of meeting any training requirements. c) Specialized Services through tie-up with global best companies for Crisis Management, Mud/Cement, Fishing, Floating Dry-dock besides provision of Workshop, Repair and Testing facilities, etc. d) Tools and Tackles including drill strings, etc. A pre-established Integrated Services Hub shall facilitate an early start-up of activities with substantial savings in time lines. This model can be replicated at other parts of the world to expedite E&P activities.

Keywords: integrated service hub, India, oil gas, offshore supply base

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Authors: Sungin Jeong

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This paper presents a linear oscillating generator of cylindrical type for hybrid electric vehicle application. The focus of the study is the suggestion of the optimal model and the design rule of the cylindrical linear oscillating generator with permanent magnet in the back-iron translator. The cylindrical topology is achieved using equivalent magnetic circuit considering leakage elements as initial modeling. This topology with permanent magnet in the back-iron translator is described by number of phases and displacement of stroke. For more accurate analysis of an oscillating machine, it will be compared by moving just one-pole pitch forward and backward the thrust of single-phase system and three-phase system. Through the analysis and comparison, a single-phase system of cylindrical topology as the optimal topology is selected. Finally, the detailed design of the optimal topology takes the magnetic saturation effects into account by finite element analysis. Besides, the losses are examined to obtain more accurate results; copper loss in the conductors of machine windings, eddy-current loss of permanent magnet, and iron-loss of specific material of electrical steel. The considerations of thermal performances and mechanical robustness are essential, because they have an effect on the entire efficiency and the insulations of the machine due to the losses of the high temperature generated in each region of the generator. Besides electric machine with linear oscillating movement requires a support system that can resist dynamic forces and mechanical masses. As a result, the fatigue analysis of shaft is achieved by the kinetic equations. Also, the thermal characteristics are analyzed by the operating frequency in each region. The results of this study will give a very important design rule in the design of linear oscillating machines. It enables us to more accurate machine design and more accurate prediction of machine performances.

Keywords: equivalent magnetic circuit, finite element analysis, hybrid electric vehicle, linear oscillating generator

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Authors: Fitih Ademe, Kibebew Kibret, Sheleme Beyene, Mezgebu Getnet, Gashaw Meteke

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Changes in precipitation, temperature and atmospheric CO2 concentration are expected to alter agricultural productivity patterns worldwide. The interactive effects of soil moisture and nutrient availability are the two key edaphic factors that determine crop yield and are sensitive to climatic changes. The study assessed the potential impacts of climate change on maize yield and corresponding water productivity and nutrient use efficiency under climate change scenarios for the Central Rift Valley of Ethiopia by mid (2041-2070) and end century (2071-2100). Projected impacts were evaluated using climate scenarios generated from four General Circulation Models (GCMs) dynamically downscaled by the Swedish RCA4 Regional Climate Model (RCM) in combination with two Representative Concentration Pathways (RCP 4.5 and RCP8.5). Decision Support System for Agro-technology Transfer cropping system model (DSSAT-CSM) was used to simulate yield, water and nutrient use for the study periods. Results indicate that rainfed maize yield might decrease on average by 16.5 and 23% by the 2050s and 2080s, respectively, due to climate change. Water productivity is expected to decline on average by 2.2 and 12% in the CRV by mid and end centuries with respect to the baseline. Nutrient uptake and corresponding nutrient use efficiency (NUE) might also be negatively affected by climate change. Phosphorus uptake probably will decrease in the CRV on average by 14.5 to 18% by 2050s, while N uptake may not change significantly at Melkassa. Nitrogen and P use efficiency indicators showed decreases in the range between 8.5 to 10.5% and between 9.3 to 10.5%, respectively, by 2050s relative to the baseline average. The simulation results further indicated that a combination of increased water availability and optimum nutrient application might increase both water productivity and nutrient use efficiency in the changed climate, which can ensure modest production in the future. Potential options that can improve water availability and nutrient uptake should be identified for the study locations using a crop modeling approach.

Keywords: crop model, climate change scenario, nutrient uptake, nutrient use efficiency, water productivity

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Authors: Kasuri Kaushalya Pathirana Pahamunu Pathirannehelage

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Recent changes in the international system challenged the traditional idea of citizenship, prompting a need for a clearer definition. With the rapid globalization and shifting geopolitical dynamics, the concept of dual citizenship has emerged as a focal point of debate regarding its implications for state interests. As borders become less rigid and people identify with multiple nationalities, the traditional idea of citizenship is changing. This change is especially important given the increased connections between countries and the challenges that sovereign states face. While many countries accept dual citizenship, others are hesitant, seeing it as a potential threat to their national goals. This difference underscores the complicated relationship between national interests and the evolving concept of citizenship in the modern world. This study seeks to critically assess whether dual citizenship represents a significant threat to sovereign states by examining its effects across economic, social, and political sectors. Employing qualitative methodologies, including the analysis of published articles, reports, government acts, and a mix of primary and secondary sources, this research delves into the complexities surrounding dual citizenship. The findings reveal a nuanced landscape, showcasing both positive and negative impacts on state sovereignty and international cooperation. By exploring the tension between multinationalism and state interests, particularly through the lens of Sri Lanka’s evolving policies, this study aims to contribute valuable insights to the fields of political science and international relations, ultimately addressing the question of dual citizenship's implications for state interests. The evolving framework of dual citizenship in Sri Lanka provides a unique opportunity to examine its implications for various aspects of the nation. Specifically, this study will analyse the impact of dual citizenship on the country's economy, international cooperation, and social development. By exploring these dimensions, the research aims to provide a comprehensive understanding of how dual citizenship influences not only individual rights but also broader state interests and development goals within the context of globalization. It’s crucial to assess the potential threats posed by dual citizenship, as it can impact national security, economic stability, social unity, and political issues within countries. Understanding these effects is important for policymakers and researchers as they work to balance globalization with the need to protect state sovereignty. Dual citizenship presents a complex interplay of challenges and benefits to state interests, influencing critical areas such as international cooperation and state sovereignty. On the one hand, it can foster stronger ties between nations, enhance economic collaboration, and encourage cultural exchange, ultimately contributing to more robust international relationships. On the other hand, it may create tensions related to national identity, complicate governance, and raise concerns about loyalty and allegiance, which can challenge the notion of state sovereignty. As countries navigate these dual realities, it becomes essential to carefully assess and manage the implications of dual citizenship. By doing so, states can harness the potential advantages while addressing the associated risks, ultimately striving for a balance that promotes both national interests and international relations.

Keywords: dual citizenship, globalization, sustainable development, nationalism

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Authors: Dirson Santos De Campos, Deller James Ferreira, Anderson Cavalcante Gonçalves, Uyara Ferreira Silva

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Rubrics to learning research provide many evaluation criteria and expected performance standards linked to defined student activity for learning and pedagogical objectives. Despite the rubric being used in education at all levels, academic literature on rubrics as a tool to support research in SQL Education is quite rare. There is a large class of SQL queries is syntactically correct, but certainly, not all are semantically correct. Detecting and correcting errors is a recurring problem in SQL education. In this paper, we usthe Rubric Abstract Framework (RAF), which consists of steps, that allows us to map the information to measure student performance guided by didactic objectives defined by the teacher as long as it is contextualized domain modeling by rubric. An empirical study was done that demonstrates how rubrics can mitigate student difficulties in finding logical errors and easing teacher workload in SQL education. Detecting and correcting logical errors is an important skill for students. Researchers have proposed several ways to improve SQL education because understanding this paradigm skills are crucial in software engineering and computer science. The RAF instantiation was using in an empirical study developed during the COVID-19 pandemic in database course. The pandemic transformed face-to-face and remote education, without presential classes. The lab activities were conducted remotely, which hinders the teaching-learning process, in particular for this research, in verifying the evidence or statements of knowledge, skills, and abilities (KSAs) of students. Various research in academia and industry involved databases. The innovation proposed in this paper is the approach used where the results obtained when using rubrics to map logical errors in query formulation have been analyzed with gains obtained by students empirically verified. The research approach can be used in the post-pandemic period in both classroom and distance learning.

Keywords: rubric, logical error, structured query language (SQL), empirical study, SQL education

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Authors: Jeena Gupta

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In the today’s world of pharmaceutical products, one should not forget the healing properties of inexpensive food materials especially spices. They are known to possess hidden pharmaceutical ingredients, imparting them the qualities of being anti-microbial, anti-oxidant, anti-inflammatory and anti-carcinogenic. Further aberrant epigenetic regulatory mechanisms like DNA methylation, histone modifications or altered microRNA expression patterns, which regulates gene expression without changing DNA sequence, contribute significantly in the development of various diseases. Changing lifestyles and diets exert their effect by influencing these epigenetic mechanisms which are thus the target of dietary phytochemicals. Bioactive components of plants have been in use since ages but their potential to reverse epigenetic alterations and prevention against diseases is yet to be explored. Spices being rich repositories of many bioactive constituents are responsible for providing them unique aroma and taste. Some spices like curcuma and garlic have been well evaluated for their epigenetic regulatory potential, but for others, it is largely unknown. We have evaluated the biological activity of phyto-active components of Fennel, Cardamom and Fenugreek by in silico molecular modeling, in vitro and in vivo studies. Ligand-based similarity studies were conducted to identify structurally similar compounds to understand their biological phenomenon. The database searching has been done by using Fenchone from fennel, Sabinene from cardamom and protodioscin from fenugreek as a query molecule in the different small molecule databases. Moreover, the results of the database searching exhibited that these compounds are having potential binding with the different targets found in the Protein Data Bank. Further in addition to being epigenetic modifiers, in vitro study had demonstrated the antimicrobial, antifungal, antioxidant and cytotoxicity protective effects of Fenchone, Sabinene and Protodioscin. To best of our knowledge, such type of studies facilitate the target fishing as well as making the roadmap in drug design and discovery process for identification of novel therapeutics.

Keywords: epigenetics, spices, phytochemicals, fenchone

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Authors: Purna Bahadur Lamichhane

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Education planning and management are foundational pillars for developing effective educational systems. However, in many educational contexts, especially in developing nations, technology-enabled management is still emerging. In such settings, manual-based systems, where instructions and guidelines are physically documented, remain central to educational planning and management. This paper examines the effectiveness, challenges, and potential of manual-based education planning systems in fostering structured, reliable, and adaptable management frameworks. The objective of this study is to explore how a manual-based approach can successfully guide administrators, educators, and policymakers in delivering high-quality education. By using structured, accessible instructions, this approach serves as a blueprint for educational governance, offering clear, actionable steps to achieve institutional goals. Through an analysis of case studies from various regions, the paper identifies key strategies for planning school schedules, managing resources, and monitoring academic and administrative performance without relying on automated systems. The findings underscore the significance of organized documentation, standard operating procedures, and comprehensive manuals that establish uniformity and maintain educational standards across institutions. With a manual-based approach, management can remain flexible, responsive, and user-friendly, especially in environments where internet access and digital literacy are limited. Moreover, it allows for localization, where instructions can be tailored to the unique cultural and socio-economic contexts of the community, thereby increasing relevancy and ownership among local stakeholders. This paper also highlights several challenges associated with manual-based education management. Manual systems often require significant time and human resources for maintenance and updating, potentially leading to inefficiencies and inconsistencies over time. Furthermore, manual records can be susceptible to loss, damage, and limited accessibility, which may affect decision-making and institutional memory. There is also the risk of siloed information, where crucial data resides with specific individuals rather than being accessible across the organization. However, with proper training and regular oversight, many of these limitations can be mitigated. The study further explores the potential for hybrid approaches, combining manual planning with selected digital tools for record-keeping, reporting, and analytics. This transitional strategy can enable schools and educational institutions to gradually embrace digital solutions without discarding the familiarity and reliability of manual instructions. In conclusion, this paper advocates for a balanced, context-sensitive approach to education planning and management. While digital systems hold the potential to streamline processes, manual-based systems offer resilience, inclusivity, and adaptability for institutions where technology adoption may be constrained. Ultimately, by reinforcing the importance of structured, detailed manuals and instructional guides, educational institutions can build robust management frameworks that facilitate both short-term successes and long-term growth in their educational mission. This research aims to provide a reference for policymakers, educators, and administrators seeking practical, low-cost, and adaptable solutions for sustainable educational planning and management.

Keywords: educatoin, planning, management, manual

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Authors: Nishaben Desai Dholakiya, Anirban Roy, Ranjan Dey

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Understanding ocean thermodynamics has become increasingly critical as Earth's oceans serve as the primary planetary heat regulator, absorbing approximately 93% of excess heat energy from anthropogenic greenhouse gas emissions. This investigation presents a comprehensive analysis of Arabian Sea surface seawater thermodynamics, focusing specifically on heat capacity (Cp) and thermal expansion coefficient (α) - parameters fundamental to global heat distribution patterns. Through high-precision experimental measurements of ultrasonic velocity and density across varying temperature (293.15-318.15K) and salinity (0.5-35 ppt) conditions, it characterize critical thermophysical parameters including specific heat capacity, thermal expansion, and isobaric and isothermal compressibility coefficients in natural seawater systems. The study employs advanced machine learning frameworks - Random Forest, Gradient Booster, Stacked Ensemble Machine Learning (SEML), and AdaBoost - with SEML achieving exceptional accuracy (R² > 0.99) in heat capacity predictions. the findings reveal significant temperature-dependent molecular restructuring: enhanced thermal energy disrupts hydrogen-bonded networks and ion-water interactions, manifesting as decreased heat capacity with increasing temperature (negative ∂Cp/∂T). This mechanism creates a positive feedback loop where reduced heat absorption capacity potentially accelerates oceanic warming cycles. These quantitative insights into seawater thermodynamics provide crucial parametric inputs for climate models and evidence-based environmental policy formulation, particularly addressing the critical knowledge gap in thermal expansion behavior of seawater under varying temperature-salinity conditions.

Keywords: climate change, arabian sea, thermodynamics, machine learning

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Authors: A. Kalaei, A. H. W. Ngan

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In this study, a mesoscopic continuum dislocation dynamics (CDD) approach is applied to simulate the intergranular slip transfer. The CDD scheme applies an efficient kinematics equation to model the evolution of the “all-dislocation density,” which is the line-length of dislocations of each character per unit volume. As the consideration of every dislocation line can be a limiter for the simulation of slip transfer in large scales with a large quantity of participating dislocations, a coarse-grained, extensive description of dislocations in terms of their density is utilized to resolve the effect of collective motion of dislocation lines. For dynamics closure, namely, to obtain the dislocation velocity from a velocity law involving the effective glide stress, mutual elastic interaction of dislocations is calculated using Mura’s equation after singularity removal at the core of dislocation lines. The developed scheme for slip transfer can therefore resolve the effects of the elastic interaction and pile-up of dislocations, which are important physics omitted in coarser models like crystal plasticity finite element methods (CPFEMs). Also, the length and timescales of the simulationareconsiderably larger than those in molecular dynamics (MD) and discrete dislocation dynamics (DDD) models. The present work successfully simulates that, as dislocation density piles up in front of a grain boundary, the elastic stress on the other side increases, leading to dislocation nucleation and stress relaxation when the local glide stress exceeds the operation stress of dislocation sources seeded on the other side of the grain boundary. More importantly, the simulation verifiesa phenomenological misorientation factor often used by experimentalists, namely, the ease of slip transfer increases with the product of the cosines of misorientation angles of slip-plane normals and slip directions on either side of the grain boundary. Furthermore, to investigate the effects of the critical stress-intensity factor of the grain boundary, dislocation density sources are seeded at different distances from the grain boundary, and the critical applied stress to make slip transfer happen is studied.

Keywords: grain boundary, dislocation dynamics, slip transfer, elastic stress

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Authors: Adeaga Ibiyemi Iyabo, Adeaga Oyetunde Adeoye

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Interestingly, mechanical drying methods has played a major role in the commercialization of agricultural and agricultural allied sectors. In the overall, drying enhances the favorable storability and preservation of agricultural produce which in turn promotes its producibility, marketability, salability, and profitability. Recent researches have shown that solar drying is easier, affordable, controllable, and of course, cleaner and purer than other means of drying methods. It is, therefore, needful to persistently appraise solar dryers with a view to improving on the existing advantages. In this paper, mathematical equations were formulated for solar dryer using mass conservation law, material balance law and least cost savings method. Computer codes were written in Visual Basic.Net. The developed computer software, which considered Ibadan, a strategic south-western geographical location in Nigeria, was used to investigate the relationship between variable orientation angle of flat plate collector on solar energy trapped, derived monthly heat load, available energy supplied by solar and fraction supplied by solar energy when 50000 Kg/Month of produce was dried over a year. At variable collector tilt angle of 10°.13°,15°,18°, 20°, the derived monthly heat load, available energy supplied by solar were 1211224.63MJ, 102121.34MJ, 0.111; 3299274.63MJ, 10121.34MJ, 0.132; 5999364.706MJ, 171222.859MJ, 0.286; 4211224.63MJ, 132121.34MJ, 0.121; 2200224.63MJ, 112121.34MJ, 0.104, respectively .These results showed that if optimum collector angle is not reached, those factors needed for efficient and cost reduction drying will be difficult to attain. Therefore, this software has revealed that off - optimum collector angle in commercial solar drying does not worth it, hence the importance of the software in decision making as to the optimum collector angle of orientation.

Keywords: energy, ibadan, heat - load, visual-basic.net

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Authors: Javier Sandoval Bustamante, Pardis Sheikhzadeh, Vijayanarasimha Hindupur Pakka

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In the pursuit of achieving net-zero carbon emissions, the integration of low carbon technologies into electricity distribution networks is paramount. This paper delves into the critical assessment of how the integration of low carbon technologies, such as heat pumps, electric vehicle chargers, and photovoltaic systems, impacts the infrastructure and operation of electricity distribution networks. The study employs rigorous methodologies, including power flow analysis and headroom analysis, to evaluate the feasibility and implications of integrating these technologies into existing distribution systems. Furthermore, the research utilizes Local Area Energy Planning (LAEP) methodologies to guide local authorities and distribution network operators in formulating effective plans to meet regional and national decarbonization objectives. Geospatial analysis techniques, coupled with building physics and electric energy systems modeling, are employed to develop geographic datasets aimed at informing the deployment of low carbon technologies at the local level. Drawing upon insights from the Local Energy Net Zero Accelerator (LENZA) project, a comprehensive case study illustrates the practical application of these methodologies in assessing the rollout potential of LCTs. The findings not only shed light on the technical feasibility of integrating low carbon technologies but also provide valuable insights into the broader transition towards a sustainable and electrified energy future. This paper contributes to the advancement of knowledge in power electrical engineering by providing empirical evidence and methodologies to support the integration of low carbon technologies into electricity distribution networks. The insights gained are instrumental for policymakers, utility companies, and stakeholders involved in navigating the complex challenges of energy transition and achieving long-term sustainability goals.

Keywords: energy planning, energy systems, digital twins, power flow analysis, headroom analysis

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Authors: Asma Ameur, Dhafer Malouche

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Nowadays, user comments on the Internet have an important impact on hotel bookings. This confirms that the e-reputation issue can influence the likelihood of customer loyalty to a hotel. In this way, e-reputation has become a real differentiator between hotels. For this reason, we have a unique opportunity in the opinion mining field to analyze the comments. In fact, this field provides the possibility of extracting information related to the polarity of user reviews. This sentimental study (Opinion Mining) represents a new line of research for analyzing the unstructured textual data. Knowing the score of e-reputation helps the hotelier to better manage his marketing strategy. The score we then obtain is translated into the image of hotels to differentiate between them. Therefore, this present research highlights the importance of hotel satisfaction ‘scoring. To calculate the satisfaction score, the sentimental analysis can be manipulated by several techniques of machine learning. In fact, this study treats the extracted textual data by using the Artificial Neural Networks Approach (ANNs). In this context, we adopt the aforementioned technique to extract information from the comments available in the ‘Trip Advisor’ website. This actual paper details the description and the modeling of the ANNs approach for the scoring of online hotel reviews. In summary, the validation of this used method provides a significant model for hotel sentiment analysis. So, it provides the possibility to determine precisely the polarity of the hotel users reviews. The empirical results show that the ANNs are an accurate approach for sentiment analysis. The obtained results show also that this proposed approach serves to the dimensionality reduction for textual data’ clustering. Thus, this study provides researchers with a useful exploration of this technique. Finally, we outline guidelines for future research in the hotel e-reputation field as comparing the ANNs with other technique.

Keywords: clustering, consumer behavior, data mining, e-reputation, machine learning, neural network, online hotel ‘reviews, opinion mining, scoring

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Authors: Yulin Zhang, Kaixi Dong, Guozhen Zhao

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Background: Different levels of life satisfaction are associated with some individual differences. Understanding the mechanism between them will help to enhance an individual’s well-being. On the one hand, traditional personality such as extraversion has been considered as the most stable and effective factor in predicting life satisfaction to the author’s best knowledge. On the other, individual emotional difference, such as alexithymia (difficulties identifying and describing one’s own feelings), is also closely related to life satisfaction. With the development of positive psychology, positive personalities such as virtues attract wide attention. And according to the broaden-and-build theory, social connectivity may mediate between emotion and life satisfaction. Therefore, the current study aims to explore the mediating role of social connectivity in the effect of positive personality and alexithymia on life satisfaction. Method: This study was conducted with 318 healthy Chinese college students whose age range from 18 to 30. Positive personality (including interpersonal, vitality, and cautiousness) was measured by the Chinese version of Values in Action Inventory of Strengths (VIA-IS). Alexithymia was measured by the Toronto Alexithymia Scale (TAS), and life satisfaction was measured by Satisfaction With Life Scale (SWLS). And social connectivity was measured by six items which have been used in previous studies. Each scale showed high reliability and validity. The mediating model was examined in Mplus 7.2 within a structural equation modeling (SEM) framework. Findings: The model fitted well and results revealed that both positive personality (95% confidence interval of indirect effect was [0.023, 0.097]) and alexithymia (95% confidence interval of indirect effect was [-0.270, -0.089]) predicted life satisfaction level significantly through social connectivity. Also, only positive personality significantly and directly predicted life satisfaction compared to alexithymia (95% confidence interval of direct effect was [0.109, 0.260]). Conclusion: Alexithymia predicts life satisfaction only through social connectivity, which emphasizes the importance of social bonding in enhancing the well-being of Chinese college students with alexithymia. And the positive personality can predict life satisfaction directly or through social connectivity, which provides implications for enhancing the well-being of Chinese college students by cultivating their virtue and positive psychological quality.

Keywords: alexithymia, life satisfaction, positive personality, social connectivity

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Authors: Joshua Kaufman, Felix Tan, Morgan Monroe, Ayman Abouraddy

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Textiles and clothing have been a staple of human existence for millennia, yet the basic structure and functionality of textile fibers and yarns has remained unchanged. While color and appearance are essential characteristics of a textile, an advancement in the fabrication of yarns that allows for user-controlled dynamic changes to the color or appearance of a garment has been lacking. Touch-activated and photosensitive pigments have been used in textiles, but these technologies are passive and cannot be controlled by the user. The technology described here allows the owner to control both when and in what pattern the fabric color-change takes place. In addition, the manufacturing process is compatible with mass-producing the user-controlled, color-changing yarns. The yarn fabrication utilizes a fiber spinning system that can produce either monofilament or multifilament yarns. For products requiring a more robust fabric (backpacks, purses, upholstery, etc.), larger-diameter monofilament yarns with a coarser weave are suitable. Such yarns are produced using a thread-coater attachment to encapsulate a 38-40 AWG metal wire inside a polymer sheath impregnated with thermochromic pigment. Conversely, products such as shirts and pants requiring yarns that are more flexible and soft against the skin comprise multifilament yarns of much smaller-diameter individual fibers. Embedding a metal wire in a multifilament fiber spinning process has not been realized to date. This research has required collaboration with Hills, Inc., to design a liquid metal-injection system to be combined with fiber spinning. The new system injects molten tin into each of 19 filaments being spun simultaneously into a single yarn. The resulting yarn contains 19 filaments, each with a tin core surrounded by a polymer sheath impregnated with thermochromic pigment. The color change we demonstrate is distinct from garments containing LEDs that emit light in various colors. The pigment itself changes its optical absorption spectrum to appear a different color. The thermochromic color-change is induced by a temperature change in the inner metal wire within each filament when current is applied from a small battery pack. The temperature necessary to induce the color change is near body temperature and not noticeable by touch. The prototypes already developed either use a simple push button to activate the battery pack or are wirelessly activated via a smart-phone app over Wi-Fi. The app allows the user to choose from different activation patterns of stripes that appear in the fabric continuously. The power requirements are mitigated by a large hysteresis in the activation temperature of the pigment and the temperature at which there is full color return. This was made possible by a collaboration with Chameleon International to develop a new, customized pigment. This technology enables a never-before seen capability: user-controlled, dynamic color and pattern change in large-area woven and sewn textiles and fabrics with wide-ranging applications from clothing and accessories to furniture and fixed-installation housing and business décor. The ability to activate through Wi-Fi opens up possibilities for the textiles to be part of the ‘Internet of Things.’ Furthermore, this technology is scalable to mass-production levels for wide-scale market adoption.

Keywords: activation, appearance, color, manufacturing

Procedia PDF Downloads 278

Authors: Daniel Aberdam

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Haploinsufficiency of PAX6 in humans is the main cause of congenital aniridia, a rare eye disease characterized by reduced visual acuity. Patients have also progressive disorders including cataract, glaucoma and corneal abnormalities making their condition very challenging to manage. Aniridia-related keratopathy (ARK), caused by a combination of factors including limbal stem-cell deficiency, impaired healing response, abnormal differentiation, and infiltration of conjunctival cells onto the corneal surface, affects up to 95% of patients. It usually begins in the first decade of life resulting in recurrent corneal erosions, sub-epithelial fibrosis with corneal decompensation and opacification. Unfortunately, current treatment options for aniridia patients are currently limited. Although animal models partially recapitulate this disease, there is no in vitro cellular model of AKT needed for drug/therapeutic tools screening and validation. We used genome editing (CRISPR/Cas9 technology) to introduce a nonsense mutation found in patients into one allele of the PAX6 gene into limbal stem cells. Resulting mutated clones, expressing half of the amount of PAX6 protein and thus representative of haploinsufficiency were further characterized. Sequencing analysis showed that no off-target mutations were induced. The mutated cells displayed reduced cell proliferation and cell migration but enhanced cell adhesion. Known PAX6 targets expression was also reduced. Remarkably, addition of soluble recombinant PAX6 protein into the culture medium was sufficient to activate endogenous PAX6 gene and, as a consequence, rescue the phenotype. It strongly suggests that our in vitro model recapitulates well the epithelial defect and becomes a powerful tool to identify drugs that could rescue the corneal defect in patients. Furthermore, we demonstrate that the homeotic transcription factor Pax6 is able to be uptake naturally by recipient cells to function into the nucleus.

Keywords: Pax6, crispr/cas9, limbal stem cells, aniridia, gene therapy

Procedia PDF Downloads 207

Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

Procedia PDF Downloads 218

Authors: Shanhua Hu

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Social media as a critical propagandizing form of film, video games, and digital products has received substantial research attention, but there exists several critical barriers such as: (1) few studies exploring the internal and external connections of a product as part of the multimodal context that gives rise to readability and commercial return; (2) the lack of study of multimodal analysis in product’s official account of game publishers and its impact on users’ behaviors including purchase intention, social media engagement, and playing time; (3) no standardized ecologically-valid, game type-varying data can be used to study the complexity of official account’s postings within a time period. This proposed research helps to tackle these limitations in order to develop a model of readability study that is more ecologically valid, robust, and thorough. To accomplish this objective, this paper provides a more diverse dataset comprising different visual elements and messages collected from the official Twitter accounts of the Top 20 best-selling games of 2021. Video game companies target potential users through social media, a popular approach is to set up an official account to maintain exposure. Typically, major game publishers would create an official account on Twitter months before the game's release date to update on the game's development, announce collaborations, and reveal spoilers. Analyses of tweets from those official Twitter accounts would assist publishers and marketers in identifying how to efficiently and precisely deploy advertising to increase game sales. The purpose of this research is to determine how official game accounts use Twitter to attract new customers, specifically which types of messages are most effective at increasing sales. The dataset includes the number of days until the actual release date on Twitter posts, the readability of the post (Flesch Reading Ease Score, FRES), the number of emojis used, the number of hashtags, the number of followers of the mentioned users, the categorization of the posts (i.e., spoilers, collaborations, promotions), and the number of video views. The timeline of Twitter postings from official accounts will be compared to the history of pre-orders and sales figures to determine the potential impact of social media posts. This study aims to determine how the above-mentioned characteristics of official accounts' Twitter postings influence the sales of the game and to examine the possible causes of this influence. The outcome will provide researchers with a list of potential aspects that could influence people's judgments in limited-word posts. With the increased average online time, users would adapt more quickly than before in online information exchange and readings, such as the word to use sentence length, and the use of emojis or hashtags. The study on the promotion of official game accounts will not only enable publishers to create more effective promotion techniques in the future but also provide ideas for future research on the influence of social media posts with a limited number of words on consumers' purchasing decisions. Future research can focus on more specific linguistic aspects, such as precise word choice in advertising.

Keywords: engagement, official account, promotion, twitter, video game

Procedia PDF Downloads 76

Authors: M. S. Nikitenko, S. A. Kizilov, D. Y. Khudonogov

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The paper considers an approach to a machine vision operating system combined with using a grid of light markers. This approach is used to solve several scientific and technical problems, such as measuring the capability of an apron feeder delivering coal from a lining return port to a conveyor in the technology of mining high coal releasing to a conveyor and prototyping an autonomous vehicle obstacle detection system. Primary verification of a method of calculating bulk material volume using three-dimensional modeling and validation in laboratory conditions with relative errors calculation were carried out. A method of calculating the capability of an apron feeder based on a machine vision system and a simplifying technology of a three-dimensional modelled examined measuring area with machine vision was offered. The proposed method allows measuring the volume of rock mass moved by an apron feeder using machine vision. This approach solves the volume control issue of coal produced by a feeder while working off high coal by lava complexes with release to a conveyor with accuracy applied for practical application. The developed mathematical apparatus for measuring feeder productivity in kg/s uses only basic mathematical functions such as addition, subtraction, multiplication, and division. Thus, this fact simplifies software development, and this fact expands the variety of microcontrollers and microcomputers suitable for performing tasks of calculating feeder capability. A feature of an obstacle detection issue is to correct distortions of the laser grid, which simplifies their detection. The paper presents algorithms for video camera image processing and autonomous vehicle model control based on obstacle detection machine vision systems. A sample fragment of obstacle detection at the moment of distortion with the laser grid is demonstrated.

Keywords: machine vision, machine vision operating system, light markers, measuring capability, obstacle detection system, autonomous transport

Procedia PDF Downloads 114

Authors: Pinel Sebastien, Bourrin François, De Madron Du Rieu Xavier, Ludwig Wolfgang, Arnau Pedro

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Heavy precipitation constitutes a major meteorological threat in the western Mediterranean. Research has investigated the relationship between the states of the Mediterranean Sea and the atmosphere with the precipitation for short temporal windows. However, at a larger temporal scale, the precursor signals of heavy rainfall in the sea and atmosphere have drawn little attention. Moreover, despite ongoing improvements in numerical weather prediction, the medium-term forecasting of rainfall events remains a difficult task. Here, we aim to investigate the influence of early-spring environmental parameters on the following autumnal heavy precipitations. Hence, we develop a machine learning model to predict extreme autumnal rainfall with a 6-month lead time over the Spanish Catalan coastal area, based on i) the sea pattern (main current-LPC and Sea Surface Temperature-SST) at the mesoscale scale, ii) 4 European weather teleconnection patterns (NAO, WeMo, SCAND, MO) at synoptic scale, and iii) the hydrological regime of the main local river (Rhône River). The accuracy of the developed model classifier is evaluated via statistical analysis based on classification accuracy, logarithmic and confusion matrix by comparing with rainfall estimates from rain gauges and satellite observations (CHIRPS-2.0). Sensitivity tests are carried out by changing the model configuration, such as sea SST, sea LPC, river regime, and synoptic atmosphere configuration. The sensitivity analysis suggests a negligible influence from the hydrological regime, unlike SST, LPC, and specific teleconnection weather patterns. At last, this study illustrates how public datasets can be integrated into a machine learning model for heavy rainfall prediction and can interest local policies for management purposes.

Keywords: extreme hazards, sensitivity analysis, heavy rainfall, machine learning, sea-atmosphere modeling, precipitation forecasting

Procedia PDF Downloads 136

Authors: Jalal Haghighat Monfared, Zahra Akbari

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Today, business executives need to have useful information to make better decisions. Banks have also been using information tools so that they can direct the decision-making process in order to achieve their desired goals by rapidly extracting information from sources with the help of business intelligence. The research seeks to investigate whether there is a relationship between the quality of decision making and the business intelligence capabilities of Mellat Bank. Each of the factors studied is divided into several components, and these and their relationships are measured by a questionnaire. The statistical population of this study consists of all managers and experts of Mellat Bank's General Departments (including 190 people) who use commercial intelligence reports. The sample size of this study was 123 randomly determined by statistical method. In this research, relevant statistical inference has been used for data analysis and hypothesis testing. In the first stage, using the Kolmogorov-Smirnov test, the normalization of the data was investigated and in the next stage, the construct validity of both variables and their resulting indexes were verified using confirmatory factor analysis. Finally, using the structural equation modeling and Pearson's correlation coefficient, the research hypotheses were tested. The results confirmed the existence of a positive relationship between decision quality and business intelligence capabilities in Mellat Bank. Among the various capabilities, including data quality, correlation with other systems, user access, flexibility and risk management support, the flexibility of the business intelligence system was the most correlated with the dependent variable of the present research. This shows that it is necessary for Mellat Bank to pay more attention to choose the required business intelligence systems with high flexibility in terms of the ability to submit custom formatted reports. Subsequently, the quality of data on business intelligence systems showed the strongest relationship with quality of decision making. Therefore, improving the quality of data, including the source of data internally or externally, the type of data in quantitative or qualitative terms, the credibility of the data and perceptions of who uses the business intelligence system, improves the quality of decision making in Mellat Bank.

Keywords: business intelligence, business intelligence capability, decision making, decision quality

Procedia PDF Downloads 112

Authors: Mohammad-Ali Latifi, Harry Bouwman

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Changes in the business environment accelerated dramatically over the last decades as a result of changes in technology, regulation, market, and competitors’ behavior. Firms need to change the way they do business in order to survive or maintain their growth. Innovating business model (BM) can create competitive advantages and enhance firm performance. However, many companies fail to achieve expected outcomes in practice, mostly due to irreversible fundamental changes in key components of the company’s BM. This leads to more ambiguity, uncertainty, and risks associated with business performance. However, the relationship among BM Innovation, moderating factors, and the firm’s overall performance is by and large ignored in the current literature. In this study, we identified twenty moderating factors from our comprehensive literature review. We categorized these factors based on two criteria regarding the extent to which: the moderating factors can be controlled and managed by firms, and they are generic or specific changes to the firms. This leads to four moderation groups. The first group is BM implementation, which includes management support, employees’ commitment, employees’ skills, communication, detailed plan. The second group is called BM practices, which consists of BM tooling, BM experimentation, the scope of change, speed of change, degree of novelty. The third group is Firm characteristics, including firm size, age, and ownership. The last group is called Industry characteristics, which considers the industry sector, competitive intensity, industry life cycle, environmental dynamism, high-tech vs. low-tech industry. Through collecting data from 508 European small and medium-sized enterprises (SMEs) and using the structural equation modeling technique, the developed moderation model was examined. Results revealed that all factors highlighted through these four groups moderate the relation between BMI and firm performance significantly. Particularly, factors related to BM-Implementation and BM-Practices are more manageable and would potentially improve firm overall performance. We believe that this result is more important for researchers and practitioners since the possibility of working on factors in Firm characteristics and Industry characteristics groups are limited, and the firm can hardly control and manage them to improve the performance of BMI efforts.

Keywords: business model innovation, firm performance, implementation, moderation

Procedia PDF Downloads 120

Authors: Keith Schofield, Garry R. Prentice

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The perceptions of the work an academic does, and the environment in which they do it, contributes to the professional identity of that academic. In turn, this has implications for the level of involvement they have in their job, their satisfaction, and their work product. This research explores academic identities in British and Irish institutions and considers the complex interplay between identity, practice, and participation. Theoretical assumptions made in this paper assert that meaningful work has positive effects on work pride, organisational commitment, organisational citizenship, and motivation; when employees participate enthusiastically they are likely to be more engaged, more successful, and more satisfied. Further examination is given to the context in which this participation happens; the nature of institutional process, management, and relationships with colleagues, team members, and students is considered. The present study follows a mixed-methods approach to explore work satisfaction constructs in a number of academic contexts in the UK and Ireland. The quantitative component of this research (Convenience Sample: 155 academics, and support/ administrative staff; 36.1% male, 63.9% female; 60.8% academic staff, 39.2% support/ administration staff; across a number of universities in the UK and Ireland) was based on an established emotional labour model and was tested across gender groups, job roles, and years of service. This was complimented by qualitative semi-structured interviews (Purposive Sample: 10 academics, and 5 support/ administrative staff across the same universities in the UK and Ireland) to examine various themes including values within academia, work conditions, professional development, and transmission of knowledge to students. Experiences from both academic and support perspectives were sought in order to gain a holistic view of academia and to provide an opportunity to explore the dynamic of the academic/administrator relationship within the broader institutional context. The quantitative emotional labour model, tested via a path analysis, provided a robust description of the relationships within the data. The significant relationships found within the quantitative emotional labour model included a link between non-expression of true feelings resulting in emotional labourious work and lower levels of intrinsic motivation and higher levels of extrinsic motivation. Higher levels of intrinsic motivation also linked positively to work pride. These findings were further explored in the qualitative elements of the research where themes emerged including the disconnection between faculty management and staff, personal fulfilment and the friction between the identities of teacher, researcher/ practitioner and administrator. The implications of the research findings from this study are combined and discussed in relation to possible identity-related and emotional labour management-related interventions. Further, suggestions are made to institutions concerning the application of these findings including the development of academic practices, with specific reference to the duality of identity required to service the combined teacher/ researcher role. Broader considerations of the paper include how individuals and institutions may engage with the changing nature of students-as-consumers as well as a recommendation to centralise personal fulfillment through the development of professional academic identities.

Keywords: academic work, emotional labour, identity friction, mixed methods

Procedia PDF Downloads 276

Authors: Ferdinando Montemari, Antonio Vitale, Nicola Genito, Giovanni Cuciniello

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The introduction of tilt-rotor aircraft into the existing civilian air transportation system will provide beneficial effects due to tilt-rotor capability to combine the characteristics of a helicopter and a fixed-wing aircraft into one vehicle. The disposability of reliable tilt-rotor simulation models supports the development of such vehicle. Indeed, simulation models are required to design automatic control systems that increase safety, reduce pilot's workload and stress, and ensure the optimal aircraft configuration with respect to flight envelope limits, especially during the most critical flight phases such as conversion from helicopter to aircraft mode and vice versa. This article presents a process to build a simplified tilt-rotor simulation model, derived from the analysis of flight data. The model aims to reproduce the complex dynamics of tilt-rotor during the in-flight conversion phase. It uses a set of scheduled linear transfer functions to relate the autopilot reference inputs to the most relevant rigid body state variables. The model also computes information about the rotor flapping dynamics, which are useful to evaluate the aircraft control margin in terms of rotor collective and cyclic commands. The rotor flapping model is derived through a mixed theoretical-empirical approach, which includes physical analytical equations (applicable to helicopter configuration) and parametric corrective functions. The latter are introduced to best fit the actual rotor behavior and balance the differences existing between helicopter and tilt-rotor during flight. Time-domain system identification from flight data is exploited to optimize the model structure and to estimate the model parameters. The presented model-building process was applied to simulated flight data of the ERICA Tilt-Rotor, generated by using a high fidelity simulation model implemented in FlightLab environment. The validation of the obtained model was very satisfying, confirming the validity of the proposed approach.

Keywords: flapping dynamics, flight dynamics, system identification, tilt-rotor modeling and simulation

Procedia PDF Downloads 199

Authors: Mirzet SeHo, Alaa Alaabed, Mansur Masih

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In theory, risk-sharing-based financing (RSF) is considered a corner stone of Islamic finance. It is argued to render Islamic banks more resilient to shocks. In practice, however, this feature of Islamic financial products is almost negligible. Instead, debt-based instruments, with conventional like features, have overwhelmed the nascent industry. In addition, the framework of present-day economic, regulatory and financial reality inevitably exposes Islamic banks in dual banking systems to problems of conventional banks. This includes, but is not limited to, interest rate risk. Empirical evidence has, thus far, confirmed such exposures, despite Islamic banks’ interest-free operations. This study applies system GMM in modeling the determinants of RSF, and finds that RSF is insensitive to changes in interest rates. Hence, our results provide support to the “stability” view of risk-sharing-based financing. This suggests RSF as the way forward for risk management at Islamic banks, in the absence of widely acceptable Shariah compliant hedging instruments. Further support to the stability view is given by evidence of counter-cyclicality. Unlike debt-based lending that inflates artificial asset bubbles through credit expansion during the upswing of business cycles, RSF is negatively related to GDP growth. Our results also imply a significantly strong relationship between risk-sharing deposits and RSF. However, the pass-through of these deposits to RSF is economically low. Only about 40% of risk-sharing deposits are channeled to risk-sharing financing. This raises questions on the validity of the industry’s claim that depositors accustomed to conventional banking shun away from risk sharing and signals potential for better balance sheet management at Islamic banks. Overall, our findings suggest that, on the one hand, Islamic banks can gain ‘independence’ from conventional banks and interest rates through risk-sharing products, the potential for which is enormous. On the other hand, RSF could enable policy makers to improve systemic stability and restrain excessive credit expansion through its countercyclical features.

Keywords: Islamic banks, risk-sharing, financing, interest rate, dynamic system GMM

Procedia PDF Downloads 316

Authors: Pedro Llanos, Diego García

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Spaceflight is considered the last frontier in terms of science, technology, and engineering. But it is also the next frontier in terms of human physiology and performance. After more than 200,000 years humans have evolved under earth’s gravity and atmospheric conditions, spaceflight poses environmental stresses for which human physiology is not adapted. Hypoxia, accelerations, and radiation are among such stressors, our research involves suborbital flights aiming to develop effective countermeasures in order to assure sustainable human space presence. The physiologic baseline of spaceflight participants is subject to great variability driven by age, gender, fitness, and metabolic reserve. The objective of the present study is to characterize different physiologic variables in a population of STEM practitioners during an aerobatic flight. Cardiovascular and pulmonary responses were determined in Science Astronaut Candidates (SACs) during unusual attitude aerobatic flight indoctrination. Physiologic data recordings from 20 subjects participating in high-G flight training were analyzed. These recordings were registered by wearable sensor-vest that monitored electrocardiographic tracings (ECGs), signs of dysrhythmias or other electric disturbances during all the flight. The same cardiovascular parameters were also collected approximately 10 min pre-flight, during each high-G/unusual attitude maneuver and 10 min after the flights. The ratio (pre-flight/in-flight/post-flight) of the cardiovascular responses was calculated for comparison of inter-individual differences. The resulting tracings depicting the cardiovascular responses of the subjects were compared against the G-loads (Gs) during the aerobatic flights to analyze cardiovascular variability aspects and fluid/pressure shifts due to the high Gs. In-flight ECG revealed cardiac variability patterns associated with rapid Gs onset in terms of reduced heart rate (HR) and some scattered dysrhythmic patterns (15% premature ventricular contractions-type) that were considered as triggered physiological responses to high-G/unusual attitude training and some were considered as instrument artifact. Variation events were observed in subjects during the +Gz and –Gz maneuvers and these may be due to preload and afterload, sudden shift. Our data reveal that aerobatic flight influenced the breathing rate of the subject, due in part by the various levels of energy expenditure due to the increased use of muscle work during these aerobatic maneuvers. Noteworthy was the high heterogeneity in the different physiological responses among a relatively small group of SACs exposed to similar aerobatic flights with similar Gs exposures. The cardiovascular responses clearly demonstrated that SACs were subjected to significant flight stress. Routine ECG monitoring during high-G/unusual attitude flight training is recommended to capture pathology underlying dangerous dysrhythmias in suborbital flight safety. More research is currently being conducted to further facilitate the development of robust medical screening, medical risk assessment approaches, and suborbital flight training in the context of the evolving commercial human suborbital spaceflight industry. A more mature and integrative medical assessment method is required to understand the physiology state and response variability among highly diverse populations of prospective suborbital flight participants.

Keywords: g force, aerobatic maneuvers, suborbital flight, hypoxia, commercial astronauts

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Authors: Angelo Corallo, Maria Elena Latino, Marta Menegoli

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Agri-food value chain involves various stakeholders with different roles. All of them abide by national and international rules and leverage marketing strategies to advance their products. Food products and related processing phases carry with it a big mole of data that are often not used to inform final customer. Some data, if fittingly identified and used, can enhance the single company, and/or the all supply chain creates a math between marketing techniques and voluntary traceability strategies. Moreover, as of late, the world has seen buying-models’ modification: customer is careful on wellbeing and food quality. Food citizenship and food democracy was born, leveraging on transparency, sustainability and food information needs. Internet of Things (IoT) and Analytics, some of the innovative technologies of Industry 4.0, have a significant impact on market and will act as a main thrust towards a genuine ‘4.0 change’ for agriculture. But, realizing a traceability system is not simple because of the complexity of agri-food supply chain, a lot of actors involved, different business models, environmental variations impacting products and/or processes, and extraordinary climate changes. In order to give support to the company involved in a traceability path, starting from business model analysis and related business process a Framework to Manage Product Data in Agri-Food Supply Chain for Voluntary Traceability was conceived. Studying each process task and leveraging on modeling techniques lead to individuate information held by different actors during agri-food supply chain. IoT technologies for data collection and Analytics techniques for data processing supply information useful to increase the efficiency intra-company and competitiveness in the market. The whole information recovered can be shown through IT solutions and mobile application to made accessible to the company, the entire supply chain and the consumer with the view to guaranteeing transparency and quality.

Keywords: agriculture 4.0, agri-food suppy chain, industry 4.0, voluntary traceability

Procedia PDF Downloads 147

Authors: María Dolores Caro, Eugenio M. Fedriani, Ángel F. Tenorio

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When lorries transport dangerous goods, there exist some legal stipulations in the European Union for assuring the security of the rest of road users as well as of those goods being transported. At this respect, lorry drivers cannot park in usual parking areas, because they must use parking areas with special conditions, including permanent supervision of security personnel. Moreover, drivers are compelled to satisfy additional regulations about resting and driving times, which involve in the practical possibility of reaching the suitable parking areas under these time parameters. The “European Agreement concerning the International Carriage of Dangerous Goods by Road” (ADR) is the basic regulation on transportation of dangerous goods imposed under the recommendations of the United Nations Economic Commission for Europe. Indeed, nowadays there are no enough parking areas adapted for dangerous goods and no complete study have suggested the best locations to build new areas or to adapt others already existing to provide the areas being necessary so that lorry drivers can follow all the regulations. The goal of this paper is to show how many additional parking areas should be built in the Iberian Peninsula to allow that lorry drivers may park in such areas under their restrictions in resting and driving time. To do so, we have modeled the problem via graph theory and we have applied a new efficient algorithm which determines an optimal solution for the problem of locating new parking areas to complement those already existing in the ADR for the Iberian Peninsula. The solution can be considered minimal since the number of additional parking areas returned by the algorithm is minimal in quantity. Obviously, graph theory is a natural way to model and solve the problem here proposed because we have considered as nodes: the already-existing parking areas, the loading-and-unloading locations and the bifurcations of roads; while each edge between two nodes represents the existence of a road between both nodes (the distance between nodes is the edge's weight). Except for bifurcations, all the nodes correspond to parking areas already existing and, hence, the problem corresponds to determining the additional nodes in the graph such that there are less up to 100 km between two nodes representing parking areas. (maximal distance allowed by the European regulations).

Keywords: dangerous goods, parking areas, Iberian peninsula, graph-based modeling

Procedia PDF Downloads 581