Search results for: mathematical modeling membrane bioreactor

Authors: Thomas Rockstuhl, Soon Ang, Kok Yee Ng, Linn Van Dyne

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Intercultural interactions are often challenging and fraught with conflicts. To shed light on how to interact effectively across cultures, academics and practitioners alike have advanced a plethora of intercultural competence models. However, the majority of this work has emphasized distal outcomes, such as job performance and cultural adjustment, rather than proximal outcomes, such as how individuals resolve inevitable intercultural conflicts. As a consequence, the processes by which individuals negotiate challenging intercultural conflicts are not well understood. The current study advances theorizing on intercultural conflict resolution by exploring antecedents of how people resolve intercultural conflicts. To this end, we examine creativity – the generation of novel and useful ideas – in the context of resolving cultural conflicts in intercultural interactions. Based on the dual-identity theory of creativity, we propose that individuals with greater international experience will display greater creativity and that the relationship is accentuated by individual’s cultural intelligence. Two studies test these hypotheses. The first study comprises 84 senior university students, drawn from an international organizational behavior course. The second study replicates findings from the first study in a sample of 89 executives from eleven countries. Participants in both studies provided protocols of their strategies for resolving two intercultural conflicts, as depicted in two multimedia-vignettes of challenging intercultural work-related interactions. Two research assistants, trained in intercultural management but blind to the study hypotheses, coded all strategies for their novelty and usefulness following scoring procedures for creativity tasks. Participants also completed online surveys of demographic background information, including their international experience, and cultural intelligence. Hierarchical linear modeling showed that surprisingly, while international experience is positively associated with usefulness, it is unrelated to novelty. Further, a person’s cultural intelligence strengthens the positive effect of international experience on usefulness and mitigates the effect of international experience on novelty. Theoretically, our findings offer an important theoretical extension to the dual-identity theory of creativity by identifying cultural intelligence as an important individual difference moderator that qualifies the relationship between international experience and creative conflict resolution. In terms of novelty, individuals higher in cultural intelligence seem less susceptible to rigidity effects of international experiences. Perhaps they are more capable of assessing which aspects of culture are relevant and apply relevant experiences when they brainstorm novel ideas. For utility, individuals high in cultural intelligence are better able to leverage on their international experience to assess the viability of their ideas because their richer and more organized cultural knowledge structure allows them to assess possible options more efficiently and accurately. In sum, our findings suggest that cultural intelligence is an important and promising intercultural competence that fosters creative resolutions to intercultural conflicts. We hope that our findings stimulate future research on creativity and conflict resolution in intercultural contexts.

Keywords: cultural Intelligence, intercultural conflict, intercultural creativity, international experience

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Authors: Marek Vondra, Petr Bobák

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Vacuum evaporation is a reliable and well-proven technology with a wide application range which is frequently used in food, chemical or pharmaceutical industries. Recently, numerous remarkable studies have been carried out to investigate utilization of this technology in the area of wastewater treatment. One of the most successful applications of vacuum evaporation principal is connected with seawater desalination. Since 1950’s, multi-stage flash distillation (MSF) has been the leading technology in this field and it is still irreplaceable in many respects, despite a rapid increase in cheaper reverse-osmosis-based installations in recent decades. MSF plants are conveniently operated in countries with a fluctuating seawater quality and at locations where a sufficient amount of waste heat is available. Nowadays, most of the MSF research is connected with alternative heat sources utilization and with hybridization, i.e. merging of different types of desalination technologies. Some of the studies are concerned with basic principles of the static flash phenomenon, but only few scientists have lately focused on the fundamentals of continuous multi-stage evaporation. Limited measurement possibilities at operating plants and insufficiently equipped experimental facilities may be the reasons. The aim of the presented study was to design, construct and test an up-to-date test rig with an advanced measurement system which will provide real time monitoring options of all the important operational parameters under various conditions. The whole system consists of a conventionally designed MSF unit with 8 evaporation chambers, versatile heating circuit for different kinds of feed water (e.g. seawater, waste water), sophisticated system for acquisition and real-time visualization of all the related quantities (temperature, pressure, flow rate, weight, conductivity, pH, water level, power input), access to a wide spectrum of operational media (salt, fresh and softened water, steam, natural gas, compressed air, electrical energy) and integrated transparent features which enable a direct visual control of selected physical mechanisms (water evaporation in chambers, water level right before brine and distillate pumps). Thanks to the adjustable process parameters, it is possible to operate the test unit at desired operational conditions. This allows researchers to carry out statistical design and analysis of experiments. Valuable results obtained in this manner could be further employed in simulations and process modeling. First experimental tests confirm correctness of the presented approach and promise interesting outputs in the future. The presented experimental apparatus enables flexible and efficient research of the whole MSF process.

Keywords: design of experiment, multi-stage flash distillation, test rig, vacuum evaporation

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Authors: Elisa Boatti, Ulisse Stefanelli, Alessandro Reali, Ferdinando Auricchio

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Thanks to their unusual properties, shape memory alloys (SMAs) are good candidates for advanced applications in a wide range of engineering fields, such as automotive, robotics, civil, biomedical, aerospace. In the last decades, the ever-growing interest for such materials has boosted several research studies aimed at modeling their complex nonlinear behavior in an effective and robust way. Since the constitutive response of SMAs is strongly thermomechanically coupled, the investigation of the non-isothermal evolution of the material must be taken into consideration. The present study considers an existing three-dimensional phenomenological model for SMAs, able to reproduce the main SMA properties while maintaining a simple user-friendly structure, and proposes a variational reformulation of the full non-isothermal version of the model. While the considered model has been thoroughly assessed in an isothermal setting, the proposed formulation allows to take into account the full nonisothermal problem. In particular, the reformulation is inspired to the GENERIC (General Equations for Non-Equilibrium Reversible-Irreversible Coupling) formalism, and is based on a generalized gradient flow of the total entropy, related to thermal and mechanical variables. Such phrasing of the model is new and allows for a discussion of the model from both a theoretical and a numerical point of view. Moreover, it directly implies the dissipativity of the flow. A semi-implicit time-discrete scheme is also presented for the fully coupled thermomechanical system, and is proven unconditionally stable and convergent. The correspondent algorithm is then implemented, under a space-homogeneous temperature field assumption, and tested under different conditions. The core of the algorithm is composed of a mechanical subproblem and a thermal subproblem. The iterative scheme is solved by a generalized Newton method. Numerous uniaxial and biaxial tests are reported to assess the performance of the model and algorithm, including variable imposed strain, strain rate, heat exchange properties, and external temperature. In particular, the heat exchange with the environment is the only source of rate-dependency in the model. The reported curves clearly display the interdependence between phase transformation strain and material temperature. The full thermomechanical coupling allows to reproduce the exothermic and endothermic effects during respectively forward and backward phase transformation. The numerical tests have thus demonstrated that the model can appropriately reproduce the coupled SMA behavior in different loading conditions and rates. Moreover, the algorithm has proved effective and robust. Further developments are being considered, such as the extension of the formulation to the finite-strain setting and the study of the boundary value problem.

Keywords: generalized gradient flow, GENERIC formalism, shape memory alloys, thermomechanical coupling

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Authors: Sharon Hovav, Ilya Levner, Oren Nahum, Istvan Szabo

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In modern large-scale logistic centers (e.g., big automated warehouses), complex logistic operations performed by human staff (pickers) need to be coordinated with the operations of automated facilities (robots, conveyors, cranes, lifts, flow racks, etc.). The efficiency of advanced logistic centers strongly depends on optimizing picking technologies in synch with the facility/product layout, as well as on optimal distribution of material flows (products) in the system. The challenge is to develop a mathematical operations research (OR) tool that will optimize system cost-effectiveness. In this work, we propose a model that describes an automatic logistic center consisting of a set of workstations located at several galleries (floors), with each station containing a known number of flow racks. The requirements of each product and the working capacity of stations served by a given set of workers (pickers) are assumed as predetermined. The goal of the model is to maximize system efficiency. The proposed model includes two echelons. The first is the setting of the (optimal) number of workstations needed to create the total processing/logistic system, subject to picker capacities. The second echelon deals with the assignment of the products to the workstations and flow racks, aimed to achieve maximal throughputs of picked products over the entire system given picker capacities and budget constraints. The solutions to the problems at the two echelons interact to balance the overall load in the flow racks and maximize overall efficiency. We have developed an operations research model within each echelon. In the first echelon, the problem of calculating the optimal number of workstations is formulated as a non-standard bin-packing problem with capacity constraints for each bin. The problem arising in the second echelon is presented as a constrained product-workstation-flow rack assignment problem with non-standard mini-max criteria in which the workload maximum is calculated across all workstations in the center and the exterior minimum is calculated across all possible product-workstation-flow rack assignments. The OR problems arising in each echelon are proved to be NP-hard. Consequently, we find and develop heuristic and approximation solution algorithms based on exploiting and improving local optimums. The LC model considered in this work is highly dynamic and is recalculated periodically based on updated demand forecasts that reflect market trends, technological changes, seasonality, and the introduction of new items. The suggested two-echelon approach and the min-max balancing scheme are shown to work effectively on illustrative examples and real-life logistic data.

Keywords: logistics center, product-workstation, assignment, maximum performance, load balancing, fast algorithm

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Authors: Anna Lower, Michal Lower, Robert Masztalski, Agnieszka Szumilas

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Contemporary cities are facing serious congestion and parking problems. In urban transport policy the introduction of the park and ride system (P&R) is an increasingly popular way of limiting vehicular traffic. The determining of P&R facilities location is a key aspect of the system. Criteria for assessing the quality of the selected location are formulated generally and descriptively. The research outsourced to specialists are expensive and time consuming. The most focus is on the examination of a few selected places. The practice has shown that the choice of the location of these sites in a intuitive way without a detailed analysis of all the circumstances, often gives negative results. Then the existing facilities are not used as expected. Methods of location as a research topic are also widely taken in the scientific literature. Built mathematical models often do not bring the problem comprehensively, e.g. assuming that the city is linear, developed along one important communications corridor. The paper presents a new method where the expert knowledge is applied to fuzzy inference model. With such a built system even a less experienced person could benefit from it, e.g. urban planners, officials. The analysis result is obtained in a very short time, so a large number of the proposed location can also be verified in a short time. The proposed method is intended for testing of car parks location in a city. The paper will show selected examples of locations of the P&R facilities in cities planning to introduce the P&R. The analysis of existing objects will also be shown in the paper and they will be confronted with the opinions of the system users, with particular emphasis on unpopular locations. The research are executed using the fuzzy inference model which was built and described in more detail in the earlier paper of the authors. The results of analyzes are compared to documents of P&R facilities location outsourced by the city and opinions of existing facilities users expressed on social networking sites. The research of existing facilities were conducted by means of the fuzzy model. The results are consistent with actual users feedback. The proposed method proves to be good, but does not require the involvement of a large experts team and large financial contributions for complicated research. The method also provides an opportunity to show the alternative location of P&R facilities. The performed studies show that the method has been confirmed. The method can be applied in urban planning of the P&R facilities location in relation to the accompanying functions. Although the results of the method are approximate, they are not worse than results of analysis of employed experts. The advantage of this method is ease of use, which simplifies the professional expert analysis. The ability of analyzing a large number of alternative locations gives a broader view on the problem. It is valuable that the arduous analysis of the team of people can be replaced by the model's calculation. According to the authors, the proposed method is also suitable for implementation on a GIS platform.

Keywords: fuzzy logic inference, park and ride system, P&R facilities, P&R location

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Authors: A. F. G. Van Woezik, L. M. A. Braakman-Jansen, O. A. Kulyk, J. E. W. C. Van Gemert-Pijnen

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Background: Zoonoses pose a serious threat to public health and economies worldwide, especially as antimicrobial resistance grows and newly emerging zoonoses can cause unpredictable outbreaks. In order to prevent and control emerging and re-emerging zoonoses, collaboration between veterinary, human health and public health domains is essential. In reality however, there is a lack of cooperation between these three disciplines and uncertainties exist about their tasks and responsibilities. The objective of this ongoing research project (ZonMw funded, 2014-2018) is to develop an online education and communication One Health platform, “eZoon”, for the general public and professionals working in veterinary, human health and public health domains to support the risk communication of non-alimentary zoonoses in the Netherlands. The main focus is on education and communication in times of outbreak as well as in daily non-outbreak situations. Methods: A participatory development approach was used in which stakeholders from veterinary, human health and public health domains participated. Key stakeholders were identified using business modeling techniques previously used for the design and implementation of antibiotic stewardship interventions and consisted of a literature scan, expert recommendations, and snowball sampling. We used a stakeholder salience approach to rank stakeholders according to their power, legitimacy, and urgency. Semi-structured interviews were conducted with stakeholders (N=20) from all three disciplines to identify current problems in risk communication and stakeholder values for the One Health platform. Interviews were transcribed verbatim and coded inductively by two researchers. Results: The following key values were identified (but were not limited to): (a) need for improved awareness of veterinary and human health of each other’s fields, (b) information exchange between veterinary and human health, in particularly at a regional level; (c) legal regulations need to match with daily practice; (d) professionals and general public need to be addressed separately using tailored language and information; (e) information needs to be of value to professionals (relevant, important, accurate, and have financial or other important consequences if ignored) in order to be picked up; and (f) need for accurate information from trustworthy, centrally organised sources to inform the general public. Conclusion: By applying a participatory development approach, we gained insights from multiple perspectives into the main problems of current risk communication strategies in the Netherlands and stakeholder values. Next, we will continue the iterative development of the One Health platform by presenting key values to stakeholders for validation and ranking, which will guide further development. We will develop a communication platform with a serious game in which professionals at the regional level will be trained in shared decision making in time-critical outbreak situations, a smart Question & Answer (Q&A) system for the general public tailored towards different user profiles, and social media to inform the general public adequately during outbreaks.

Keywords: ehealth, one health, risk communication, stakeholder, zoonosis

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Authors: Georges Ghazi, Magali Gelhaye, Ruxandra Botez

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Over the years, the Flight Management System (FMS) has experienced a continuous improvement of its many features, to the point of becoming the pilot’s primary interface for flight planning operation on the airplane. With the assistance of the FMS, the concept of distance and time has been completely revolutionized, providing the crew members with the determination of the optimized route (or flight plan) from the departure airport to the arrival airport. To accomplish this function, the FMS needs an accurate Aircraft Performance Model (APM) of the aircraft. In general, APMs that equipped most modern FMSs are established before the entry into service of an individual aircraft, and results from the combination of a set of ordinary differential equations and a set of performance databases. Unfortunately, an aircraft in service is constantly exposed to dynamic loads that degrade its flight characteristics. These degradations endow two main origins: airframe deterioration (control surfaces rigging, seals missing or damaged, etc.) and engine performance degradation (fuel consumption increase for a given thrust). Thus, after several years of service, the performance databases and the APM associated to a specific aircraft are no longer representative enough of the actual aircraft performance. It is important to monitor the trend of the performance deterioration and correct the uncertainties of the aircraft model in order to improve the accuracy the flight management system predictions. The basis of this research lies in the new ability to continuously update an Aircraft Performance Model (APM) during flight using an adaptive lookup table technique. This methodology was developed and applied to the well-known Cessna Citation X business aircraft. For the purpose of this study, a level D Research Aircraft Flight Simulator (RAFS) was used as a test aircraft. According to Federal Aviation Administration the level D is the highest certification level for the flight dynamics modeling. Basically, using data available in the Flight Crew Operating Manual (FCOM), a first APM describing the variation of the engine fan speed and aircraft fuel flow w.r.t flight conditions was derived. This model was next improved using the proposed methodology. To do that, several cruise flights were performed using the RAFS. An algorithm was developed to frequently sample the aircraft sensors measurements during the flight and compare the model prediction with the actual measurements. Based on these comparisons, a correction was performed on the actual APM in order to minimize the error between the predicted data and the measured data. In this way, as the aircraft flies, the APM will be continuously enhanced, making the FMS more and more precise and the prediction of trajectories more realistic and more reliable. The results obtained are very encouraging. Indeed, using the tables initialized with the FCOM data, only a few iterations were needed to reduce the fuel flow prediction error from an average relative error of 12% to 0.3%. Similarly, the FCOM prediction regarding the engine fan speed was reduced from a maximum error deviation of 5.0% to 0.2% after only ten flights.

Keywords: aircraft performance, cruise, trajectory optimization, adaptive lookup tables, Cessna Citation X

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Authors: Niyongabo Elyse

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Prefabricated building construction is a pioneering approach that combines design, production, and assembly to attain energy efficiency, environmental sustainability, and economic feasibility. Despite continuous development in the industry in China, the low technical maturity of standardized design, factory production, and construction assembly introduces uncertainties affecting prefabricated component production and on-site assembly processes. This research focuses on enhancing project management performance under uncertainty to help enterprises navigate these challenges and optimize project resources. The study introduces a perspective on how uncertain factors influence the implementation of prefabricated building construction projects. It proposes a theoretical model considering project process management ability, adaptability to uncertain environments, and collaboration ability of project participants. The impact of uncertain factors is demonstrated through case studies and quantitative analysis, revealing constraints on implementation time, cost, quality, and safety. To address uncertainties in prefabricated component production scheduling, a fuzzy model is presented, expressing processing times in interval values. The model utilizes a cooperative co-evolution evolution algorithm (CCEA) to optimize scheduling, demonstrated through a real case study showcasing reduced project duration and minimized effects of processing time disturbances. Additionally, the research addresses on-site assembly construction scheduling, considering the relationship between task processing times and assigned resources. A multi-objective model with fuzzy activity durations is proposed, employing a hybrid cooperative co-evolution evolution algorithm (HCCEA) to optimize project scheduling. Results from real case studies indicate improved project performance in terms of duration, cost, and resilience to processing time delays and resource changes. The study also introduces a multistage dynamic process control model, utilizing IoT technology for real-time monitoring during component production and construction assembly. This approach dynamically adjusts schedules when constraints arise, leading to enhanced project management performance, as demonstrated in a real prefabricated housing project. Key contributions include a fuzzy prefabricated components production scheduling model, a multi-objective multi-mode resource-constrained construction project scheduling model with fuzzy activity durations, a multi-stage dynamic process control model, and a cooperative co-evolution evolution algorithm. The integrated mathematical model addresses the complexity of prefabricated building construction project management, providing a theoretical foundation for practical decision-making in the field.

Keywords: prefabricated construction, project management performance, uncertainty, fuzzy scheduling

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Authors: Sahithi Yarlagadda

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The design of antenna is constrained by mathematical and geometrical parameters. Though there are diverse antenna structures with wide range of feeds yet, there are many geometries to be tried, which cannot be customized into predefined computational methods. The antenna design and optimization qualify to apply evolutionary algorithmic approach since the antenna parameters weights dependent on geometric characteristics directly. The evolutionary algorithm can be explained simply for a given quality function to be maximized. We can randomly create a set of candidate solutions, elements of the function's domain, and apply the quality function as an abstract fitness measure. Based on this fitness, some of the better candidates are chosen to seed the next generation by applying recombination and permutation to them. In conventional approach, the quality function is unaltered for any iteration. But the antenna parameters and geometries are wide to fit into single function. So, the weight coefficients are obtained for all possible antenna electrical parameters and geometries; the variation is learnt by mining the data obtained for an optimized algorithm. The weight and covariant coefficients of corresponding parameters are logged for learning and future use as datasets. This paper drafts an approach to obtain the requirements to study and methodize the evolutionary approach to automated antenna design for our past work on Vivaldi antenna as test candidate. The antenna parameters like gain, directivity, etc. are directly caged by geometries, materials, and dimensions. The design equations are to be noted here and valuated for all possible conditions to get maxima and minima for given frequency band. The boundary conditions are thus obtained prior to implementation, easing the optimization. The implementation mainly aimed to study the practical computational, processing, and design complexities that incur while simulations. HFSS is chosen for simulations and results. MATLAB is used to generate the computations, combinations, and data logging. MATLAB is also used to apply machine learning algorithms and plotting the data to design the algorithm. The number of combinations is to be tested manually, so HFSS API is used to call HFSS functions from MATLAB itself. MATLAB parallel processing tool box is used to run multiple simulations in parallel. The aim is to develop an add-in to antenna design software like HFSS, CSTor, a standalone application to optimize pre-identified common parameters of wide range of antennas available. In this paper, we have used MATLAB to calculate Vivaldi antenna parameters like slot line characteristic impedance, impedance of stripline, slot line width, flare aperture size, dielectric and K means, and Hamming window are applied to obtain the best test parameters. HFSS API is used to calculate the radiation, bandwidth, directivity, and efficiency, and data is logged for applying the Evolutionary genetic algorithm in MATLAB. The paper demonstrates the computational weights and Machine Learning approach for automated antenna optimizing for Vivaldi antenna.

Keywords: machine learning, Vivaldi, evolutionary algorithm, genetic algorithm

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Authors: Qaisar Ali, Waqar A. Khan, Shafiq R. Qureshi

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Heat transfer in Power Law Fluids across cylindrical surfaces has copious engineering applications. These applications comprises of areas such as underwater pollution, bio medical engineering, filtration systems, chemical, petroleum, polymer, food processing, recovery of geothermal energy, crude oil extraction, pharmaceutical and thermal energy storage. The quantum of research work with diversified conditions to study the effects of combined heat transfer and fluid flow across porous media has increased considerably over last few decades. The most non-Newtonian fluids of practical interest are highly viscous and therefore are often processed in the laminar flow regime. Several studies have been performed to investigate the effects of free and mixed convection in Newtonian fluids along vertical and horizontal cylinder embedded in a saturated porous medium, whereas very few analysis have been performed on Power law fluids along wedge. In this study, boundary layer analysis under the effects of radiation-mixed convection in power law fluids along vertical wedge in porous medium have been investigated using an implicit finite difference method (Keller box method). Steady, 2-D laminar flow has been considered under prescribed surface heat flux condition. Darcy, Boussinesq and Roseland approximations are assumed to be valid. Neglecting viscous dissipation effects and the radiate heat flux in the flow direction, the boundary layer equations governing mixed convection flow over a vertical wedge are transformed into dimensionless form. The single mathematical model represents the case for vertical wedge, cone and plate by introducing the geometry parameter. Both similar and Non- similar solutions have been obtained and results for Non similar case have been presented/ plotted. Effects of radiation parameter, variable heat flux parameter, wedge angle parameter ‘m’ and mixed convection parameter have been studied for both Newtonian and Non-Newtonian fluids. The results are also compared with the available data for the analysis of heat transfer in the prescribed range of parameters and found in good agreement. Results for the details of dimensionless local Nusselt number, temperature and velocity fields have also been presented for both Newtonian and Non-Newtonian fluids. Analysis of data revealed that as the radiation parameter or wedge angle is increased, the Nusselt number decreases whereas it increases with increase in the value of heat flux parameter at a given value of mixed convection parameter. Also, it is observed that as viscosity increases, the skin friction co-efficient increases which tends to reduce the velocity. Moreover, pseudo plastic fluids are more heat conductive than Newtonian and dilatant fluids respectively. All fluids behave identically in pure forced convection domain.

Keywords: porous medium, power law fluids, surface heat flux, vertical wedge

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Authors: Panagiotis Lemonakis, Nikolaos Moisiadis, Andromachi Gkoutzini, George Kaliabetsos, Nikos Eliou

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The proper surface water drainage not only affects vehicle movement dynamics but also increases the likelihood of an accident due to the fact that inadequate drainage is associated with potential hydroplaning and splash and spray driving conditions. Nine solutions have been proposed to address hydroplaning in sections with inadequate drainage, e.g., augmented superelevation and longitudinal rates, reduction of runoff length, and skew superelevation. The latter has been extensively implemented in highways recently, enhancing the safety level in the applied road segments in regards to the effective drainage of the rainwater. However, the concept of the skew superelevation has raised concerns regarding the driver’s comfort when traveling over skew superelevation sections, particularly at high speeds. These concerns alleviated through the concept of the round-up skew superelevation, which reduces both the lateral and the vertical acceleration imposed to the drivers and hence, improves comfort and traffic safety. Various research studies aimed at investigating driving comfort by evaluating the lateral and vertical accelerations sustained by the road users and vehicles. These studies focused on the influence of the skew superelevation to passenger cars, buses and trucks, and the drivers themselves, traveling at a certain range of speeds either below or above the design speed. The outcome of these investigations which based on the use of simulations, revealed that the imposed accelerations did not exceed the statutory thresholds even when the travelling speed was significantly greater than the design speed. Nevertheless, the effect of the skew superelevation to other vehicle types for instance, motorcycles, has not been investigated so far. The present research study aims to bridge this gap by investigating the impact of skew superelevation on the motorcycle rider’s comfort. Power two-wheeler riders are susceptible to any changes on the pavement surface and therefore a comparison between the traditional superelevation practice and the skew superelevation concept is of paramount importance. The methodology based on the utilization of sophisticated software in order to design the model of the road for several values of the longitudinal slope. Based on the values of the slopes and the use of a mathematical equation, the accelerations imposed on the wheel of the motorcycle were calculated. Due to the fact that the final aim of the study is the influence of the skew superelevation to the rider, it was deemed necessary to convey the calculated accelerations from the wheel to the rider. That was accomplished by implementing the quarter car suspension model adjusted to the features of two-wheeler vehicles. Finally, the accelerations derived from this process evaluated according to specific thresholds originated from the International Organization for Standardization, which correspond to certain levels of comfort. The most important conclusion drawn is that the comfort of the riders is not dependent on the form of road gradient to a great extent due to the fact that the vertical acceleration imposed to the riders took similar values regardless of the value of the longitudinal slope.

Keywords: acceleration, comfort, motorcycle, safety, skew superelevation

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Authors: Trina Isabel D. Santiago, Juan Raphael M. Perez, Maria Angelica O. Soriano, Teresita B. Suing, Jumee F. Tayaban

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To achieve universal healthcare for everyone, the World Health Organization has emphasized the importance of National Medicines Policies for increased accessibility and utilization of high-quality and affordable medications. In the Philippines, significant challenges have been identified surrounding the sustainability of essential medicines, resulting in limited access such as high cost and dominance and market dominance and monopoly of multinational companies (MNCs) in the Philippine pharmaceutical industry. These identified challenges have been addressed by several initiatives, such as the Philippine National Drug Policy and Generics Act of 1988 (Republic Act 6675), to attempt to reduce drug prices. Despite these efforts, the concerns with drug accessibility and affordability continue to persist; hence, Republic Act 9502 was enacted. This paper attempts to review RA 9502 in the pursuit of making medicines more affordable for Filipinos, analyze and critique the problems and challenges associated with the law, and provide recommendations to address identified problems and challenges. A literature search and review, as well as an analysis of the law, has been done to evaluate the policy. RA 9502 recognizes the importance of market competition in drug price reduction and quality medicine accessibility. Contentious issues prior to enactment of the law include 1) parallel importation, pointing out that the drug price will depend on the global market price, 2) contrasting approaches in the drafting of the law as the House version focused on medicine price control while the Senate version prioritized market competition, and 3) MNCs opposing the amendments with concerns on discrimination, constitutional violations, and noncompliance with international treaty obligations. There are also criticisms and challenges with the implementation of the law in terms of content or modeling, interpretation and implementation, and other external factors or hindrances. The law has been criticized for its narrow scope as it only covers specific essential medicines with no cooperation with the national health insurance program. Moreover, the law has sections taking advantage of the TRIPS flexibilities, which disallow smaller countries to reap the benefits of flexibilities. The sanctions and penalties have an insignificant role in implementation as they only ask for a small portion of the income of MNCs. Proposed recommendations for policy improvement include aligning existing legislation through strengthened price regulation and expanded law coverage, strengthening penalties to promote law adherence, and promoting research and development to encourage and support local initiatives. Through these comprehensive recommendations, the issues surrounding the policy can be addressed, and the goal of enhancing the affordability and accessibility of medicines in the country can be achieved.

Keywords: drug accessibility, drug affordability, price regulation, Republic Act 9502

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Authors: Rawan Ashraf, Ahmed E. Gomaa, Gehan Safwat, Ayman Diab

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Background: Three-dimensional (3D) bio-printing has become a versatile and powerful method for generating a variety of biological constructs, including bone or extracellular matrix scaffolds endo- or epithelial, muscle tissue, as well as organoids. Aim of the study: Fabricate a low cost DIY 3D bio-printer to produce 3D bio-printed products such as anti-microbial packaging or multi-organs on chips. We demonstrate the alignment between two types of 3D printer technology (3D Bio-printer and DLP) on Multi-organ-on-a-chip (multi-OoC) devices fabrication. Methods: First, Design and Fabrication of the Syringe Unit for Modification of an Off-the-Shelf 3D Printer, then Preparation of Hydrogel based on natural polymers Sodium Alginate and Gelatin, followed by acquisition of the cell suspension, then modeling the desired 3D structure. Preparation for 3D printing, then Cell-free and cell-laden hydrogels went through the printing process at room temperature under sterile conditions and finally post printing curing process and studying the printed structure regards physical and chemical characteristics. The hard scaffold of the Organ on chip devices was designed and fabricated using the DLP-3D printer, following similar approaches as the Microfluidics system fabrication. Results: The fabricated Bio-Ink was based onHydrogel polymer mix of sodium alginate and gelatin 15% to 0.5%, respectively. Later the 3D printing process was conducted using a higher percentage of alginate-based hydrogels because of it viscosity and the controllable crosslinking, unlike the thermal crosslinking of Gelatin. The hydrogels were colored to simulate the representation of two types of cells. The adaption of the hard scaffold, whether for the Microfluidics system or the hard-tissues, has been acquired by the DLP 3D printers with fabricated natural bioactive essential oils that contain antimicrobial activity, followed by printing in Situ three complex layers of soft-hydrogel as a cell-free Bio-Ink to simulate the real-life tissue engineering process. The final product was a proof of concept for a rapid 3D cell culturing approaches that uses an engineered hard scaffold along with soft-tissues, thus, several applications were offered as products of the current prototype, including the Organ-On-Chip as a successful integration between DLP and 3D bioprinter. Conclusion: Multiple designs for the organ-on-a-chip (multi-OoC) devices have been acquired in our study with main focus on the low cost fabrication of such technology and the potential to revolutionize human health research and development. We describe circumstances in which multi-organ models are useful after briefly examining the requirement for full multi-organ models with a systemic component. Following that, we took a look at the current multi-OoC platforms, such as integrated body-on-a-chip devices and modular techniques that use linked organ-specific modules.

Keywords: 3d bio-printer, hydrogel, multi-organ on chip, bio-inks

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Authors: Gizem Kayar, Ramazan Bakir, M. Ilkay Koşar, Ceren U. Gencer, Alperen Ayyildiz

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Anatomy classes are crucial for general education of medical students, whereas learning anatomy is quite challenging and requires memorization of thousands of structures. In traditional teaching methods, learning materials are still based on books, anatomy mannequins, or videos. This results in forgetting many important structures after several years. However, more interactive teaching methods like virtual reality, augmented reality, gamification, and motion sensors are becoming more popular since such methods ease the way we learn and keep the data in mind for longer terms. During our study, we designed a virtual reality based digital head anatomy platform to investigate whether a fully interactive anatomy platform is effective to learn anatomy and to understand the level of teaching and learning optimization. The Head is one of the most complicated human anatomy structures, with thousands of tiny, unique structures. This makes the head anatomy one of the most difficult parts to understand during class sessions. Therefore, we developed a fully interactive digital tool with 3D model marking, quiz structures, 2D/3D puzzle structures, and VR support so as to integrate the power of VR and gamification. The project has been developed in Unity game engine with HTC Vive Cosmos VR headset. The head anatomy 3D model has been selected with full skeletal, muscular, integumentary, head, teeth, lymph, and vein system. The biggest issue during the development was the complexity of our model and the marking of it in the 3D world system. 3D model marking requires to access to each unique structure in the counted subsystems which means hundreds of marking needs to be done. Some parts of our 3D head model were monolithic. This is why we worked on dividing such parts to subparts which is very time-consuming. In order to subdivide monolithic parts, one must use an external modeling tool. However, such tools generally come with high learning curves, and seamless division is not ensured. Second option was to integrate tiny colliders to all unique items for mouse interaction. However, outside colliders which cover inner trigger colliders cause overlapping, and these colliders repel each other. Third option is using raycasting. However, due to its own view-based nature, raycasting has some inherent problems. As the model rotate, view direction changes very frequently, and directional computations become even harder. This is why, finally, we studied on the local coordinate system. By taking the pivot point of the model into consideration (back of the nose), each sub-structure is marked with its own local coordinate with respect to the pivot. After converting the mouse position to the world position and checking its relation with the corresponding structure’s local coordinate, we were able to mark all points correctly. The advantage of this method is its applicability and accuracy for all types of monolithic anatomical structures.

Keywords: anatomy, e-learning, virtual reality, 3D model marking

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Authors: Mauro Cristeche

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This paper approaches the intervention of the American State in the social arena and the modeling of the rights system from the Argentinian experience, by observing the characteristics of its federal budgetary system, the evolution of social public spending and welfare programs in recent years, labor and poverty statistics, and the changes on the labor market structure. The analysis seeks to combine different methodologies and sources: in-depth interviews with specialists, analysis of theoretical and mass-media material, and statistical sources. Among the results, it could be mentioned that the tendency to state interventionism (what has been called ‘nationalization of social life’) is quite evident in the United States, and manifests itself in multiple forms. The bibliography consulted, and the experts interviewed pointed out this increase of the state presence in historical terms (beyond short-term setbacks) in terms of increase of public spending, fiscal pressure, public employment, protective and control mechanisms, the extension of welfare policies to the poor sectors, etc. In fact, despite the significant differences between both countries, the United States and Argentina have common patterns of behavior in terms of the aforementioned phenomena. On the other hand, dissimilarities are also important. Some of them are determined by each country's own political history. The influence of political parties on the economic model seems more decisive in the United States than in Argentina, where the tendency to state interventionism is more stable. The centrality of health spending is evident in America, while in Argentina that discussion is more concentrated in the social security system and public education. The biggest problem of the labor market in the United States is the disqualification as a consequence of the technological development while in Argentina it is a result of its weakness. Another big difference is the huge American public spending on Defense. Then, the more federal character of the American State is also a factor of differential analysis against a centralized Argentine state. American public employment (around 10%) is comparatively quite lower than the Argentinian (around 18%). The social statistics show differences, but inequality and poverty have been growing as a trend in the last decades in both countries. According to public rates, poverty represents 14% in The United States and 33% in Argentina. American public spending is important (welfare spending and total public spending represent around 12% and 34% of GDP, respectively), but a bit lower than Latin-American or European average). In both cases, the tendency to underemployment and disqualification unemployment does not assume a serious gravity. Probably one of the most important aspects of the analysis is that private initiative and public intervention are much more intertwined in the United States, which makes state intervention more ‘fuzzy’, while in Argentina the difference is clearer. Finally, the power of its accumulation of capital and, more specifically, of the industrial and services sectors in the United States, which continues to be the engine of the economy, express great differences with Argentina, supported by its agro-industrial power and its public sector.

Keywords: state intervention, welfare policies, labor market, system of rights, United States of America

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Authors: Olivier Delage, Thierry Portafaix, Hassan Bencherif, Guillaume Guimbretiere

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Most observation data sequences in geophysics can be interpreted as resulting from the interaction of several physical processes at several time and space scales. As a consequence, measurements time series in geophysics have often characteristics of non-linearity and non-stationarity and thereby exhibit strong fluctuations at all time-scales and require a time-frequency representation to analyze their variability. Empirical Mode Decomposition (EMD) is a relatively new technic as part of a more general signal processing method called the Hilbert-Huang transform. This analysis method turns out to be particularly suitable for non-linear and non-stationary signals and consists in decomposing a signal in an auto adaptive way into a sum of oscillating components named IMFs (Intrinsic Mode Functions), and thereby acts as a bank of bandpass filters. The advantages of the EMD technic are to be entirely data driven and to provide the principal variability modes of the dynamics represented by the original time series. However, the main limiting factor is the frequency resolution that may give rise to the mode mixing phenomenon where the spectral contents of some IMFs overlap each other. To overcome this problem, J. Gilles proposed an alternative entitled “Empirical Wavelet Transform” (EWT) which consists in building from the segmentation of the original signal Fourier spectrum, a bank of filters. The method used is based on the idea utilized in the construction of both Littlewood-Paley and Meyer’s wavelets. The heart of the method lies in the segmentation of the Fourier spectrum based on the local maxima detection in order to obtain a set of non-overlapping segments. Because linked to the Fourier spectrum, the frequency resolution provided by EWT is higher than that provided by EMD and therefore allows to overcome the mode-mixing problem. On the other hand, if the EWT technique is able to detect the frequencies involved in the original time series fluctuations, EWT does not allow to associate the detected frequencies to a specific mode of variability as in the EMD technic. Because EMD is closer to the observation of physical phenomena than EWT, we propose here a new technic called EAWD (Empirical Adaptive Wavelet Decomposition) based on the coupling of the EMD and EWT technics by using the IMFs density spectral content to optimize the segmentation of the Fourier spectrum required by EWT. In this study, EMD and EWT technics are described, then EAWD technic is presented. Comparison of results obtained respectively by EMD, EWT and EAWD technics on time series of ozone total columns recorded at Reunion island over [1978-2019] period is discussed. This study was carried out as part of the SOLSTYCE project dedicated to the characterization and modeling of the underlying dynamics of time series issued from complex systems in atmospheric sciences

Keywords: adaptive filtering, empirical mode decomposition, empirical wavelet transform, filter banks, mode-mixing, non-linear and non-stationary time series, wavelet

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Authors: Jérôme de Reffye, Marc Antoni

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Following the development of the ERTMS system, we think it is interesting to develop another software-based track circuit system which would fit secondary railway lines with an easy-to-work implementation and a low sensitivity to rail-wheel impedance variations. We called this track circuit 'Track Railway by Automatic Circuits.' To be internationally implemented, this system must not have any mechanical component and must be compatible with existing track circuit systems. For example, the system is independent from the French 'Joints Isolants Collés' that isolate track sections from one another, and it is equally independent from component used in Germany called 'Counting Axles,' in French 'compteur d’essieux.' This track circuit is fully interoperable. Such universality is obtained by replacing the train detection mechanical system with a space-time filtering of train position. The various track sections are defined by the frequency of a continuous signal. The set of frequencies related to the track sections is a set of orthogonal functions in a Hilbert Space. Thus the failure probability of track sections separation is precisely calculated on the basis of signal-to-noise ratio. SNR is a function of the level of traction current conducted by rails. This is the reason why we developed a very powerful algorithm to reject noise and jamming to obtain an SNR compatible with the precision required for the track circuit and SIL 4 level. The SIL 4 level is thus reachable by an adjustment of the set of orthogonal functions. Our major contributions to railway engineering signalling science are i) Train space localization is precisely defined by a calibration system. The operation bypasses the GSM-R radio system of the ERTMS system. Moreover, the track circuit is naturally protected against radio-type jammers. After the calibration operation, the track circuit is autonomous. ii) A mathematical topology adapted to train space localization by following the train through a linear time filtering of the received signal. Track sections are numerically defined and can be modified with a software update. The system was numerically simulated, and results were beyond our expectations. We achieved a precision of one meter. Rail-ground and rail-wheel impedance sensitivity analysis gave excellent results. Results are now complete and ready to be published. This work was initialised as a research project of the French Railways developed by the Pi-Ramses Company under SNCF contract and required five years to obtain the results. This track circuit is already at Level 3 of the ERTMS system, and it will be much cheaper to implement and to work. The traffic regulation is based on variable length track sections. As the traffic growths, the maximum speed is reduced, and the track section lengths are decreasing. It is possible if the elementary track section is correctly defined for the minimum speed and if every track section is able to emit with variable frequencies.

Keywords: track section, track circuits, space-time crossing, adaptive track section, automatic railway signalling

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Authors: Akanksha Bhatnagar, Sandhya Kortegare, Felice Elefant

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Context: Alzheimer's disease (AD) is a neurodegenerative disorder that is characterized by progressive cognitive decline and memory loss. The cause of AD is not fully understood, but it is thought to be caused by a combination of genetic, environmental, and lifestyle factors. One of the hallmarks of AD is the loss of neurons in the hippocampus, a brain region that is important for memory and learning. This loss of neurons is thought to be caused by a decrease in histone acetylation, which is a process that regulates gene expression. Research Aim: The research aim of the study was to develop mall molecule compounds that can enhance the activity of Tip60, a histone acetyltransferase that is important for memory and learning. Methodology/Analysis: The researchers used in silico structural modeling and a pharmacophore-based virtual screening approach to design and synthesize small molecule compounds strongly predicted to target and enhance Tip60’s HAT activity. The compounds were then tested in vitro and in vivo to assess their ability to enhance Tip60 activity and rescue cognitive deficits in AD models. Findings: The researchers found that several of the compounds were able to enhance Tip60 activity and rescue cognitive deficits in AD models. The compounds were also developed to cross the blood-brain barrier, which is an important factor for the development of potential AD therapeutics. Theoretical Importance: The findings of this study suggest that Tip60 HAT activators have the potential to be developed as therapeutic agents for AD. The compounds are specific to Tip60, which suggests that they may have fewer side effects than other HDAC inhibitors. Additionally, the compounds are able to cross the blood-brain barrier, which is a major hurdle for the development of AD therapeutics. Data Collection: The study collected data from a variety of sources, including in vitro assays and animal models. The in vitro assays assessed the ability of compounds to enhance Tip60 activity using histone acetyltransferase (HAT) enzyme assays and chromatin immunoprecipitation assays. Animal models were used to assess the ability of the compounds to rescue cognitive deficits in AD models using a variety of behavioral tests, including locomotor ability, sensory learning, and recognition tasks. The human clinical trials will be used to assess the safety and efficacy of the compounds in humans. Questions: The question addressed by this study was whether Tip60 HAT activators could be developed as therapeutic agents for AD. Conclusions: The findings of this study suggest that Tip60 HAT activators have the potential to be developed as therapeutic agents for AD. The compounds are specific to Tip60, which suggests that they may have fewer side effects than other HDAC inhibitors. Additionally, the compounds are able to cross the blood-brain barrier, which is a major hurdle for the development of AD therapeutics. Further research is needed to confirm the safety and efficacy of these compounds in humans.

Keywords: Alzheimer's disease, cognition, neuroepigenetics, drug discovery

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Authors: Efstratios Karavasilis, Foteini Christidi, Georgios Velonakis, Agapi Plousi, Kalliopi Platoni, Nikolaos Kelekis, Ioannis Evdokimidis, Efstathios Efstathopoulos

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Introduction: Advanced structural and functional neuroimaging techniques contribute to the study of anatomical and functional brain connectivity and its role in the pathophysiology and symptoms’ heterogeneity in several neurodegenerative disorders, including multiple sclerosis (MS). Aim: In the present study, we applied multiparametric neuroimaging techniques to investigate the structural and functional cortico-cerebellar changes in MS patients. Material: We included 51 MS patients (28 with clinically isolated syndrome [CIS], 31 with relapsing-remitting MS [RRMS]) and 51 age- and gender-matched healthy controls (HC) who underwent MRI in a 3.0T MRI scanner. Methodology: The acquisition protocol included high-resolution 3D T1 weighted, diffusion-weighted imaging and echo planar imaging sequences for the analysis of volumetric, tractography and functional resting state data, respectively. We performed between-group comparisons (CIS, RRMS, HC) using CAT12 and CONN16 MATLAB toolboxes for the analysis of volumetric (cerebellar gray matter density) and functional (cortico-cerebellar resting-state functional connectivity) data, respectively. Brainance suite was used for the analysis of tractography data (cortico-cerebellar white matter integrity; fractional anisotropy [FA]; axial and radial diffusivity [AD; RD]) to reconstruct the cerebellum tracts. Results: Patients with CIS did not show significant gray matter (GM) density differences compared with HC. However, they showed decreased FA and increased diffusivity measures in cortico-cerebellar tracts, and increased cortico-cerebellar functional connectivity. Patients with RRMS showed decreased GM density in cerebellar regions, decreased FA and increased diffusivity measures in cortico-cerebellar WM tracts, as well as a pattern of increased and mostly decreased functional cortico-cerebellar connectivity compared to HC. The comparison between CIS and RRMS patients revealed significant GM density difference, reduced FA and increased diffusivity measures in WM cortico-cerebellar tracts and increased/decreased functional connectivity. The identification of decreased WM integrity and increased functional cortico-cerebellar connectivity without GM changes in CIS and the pattern of decreased GM density decreased WM integrity and mostly decreased functional connectivity in RRMS patients emphasizes the role of compensatory mechanisms in early disease stages and the disintegration of structural and functional networks with disease progression. Conclusions: In conclusion, our study highlights the added value of multimodal neuroimaging techniques for the in vivo investigation of cortico-cerebellar brain changes in neurodegenerative disorders. An extension and future opportunity to leverage multimodal neuroimaging data inevitably remain the integration of such data in the recently-applied mathematical approaches of machine learning algorithms to more accurately classify and predict patients’ disease course.

Keywords: advanced neuroimaging techniques, cerebellum, MRI, multiple sclerosis

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Authors: Nikeshala Weerasekara, Roshan Ajward

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Contemporary business environment, given the circumstance of stringent scrutiny toward corporate behavior, organizations are under pressure to develop and implement solid overarching Corporate Social Responsibility (CSR) strategies. In that milieu, in order to differentiate themselves from competitors and maintain stakeholder confidence banks spend millions of dollars on CSR programmes. However, knowledge on how non-western bank employees perceive such activities is inconclusive. At the same time recently only researchers have shifted their focus on positive effects of compassion at work or the organizational conditions under which it arises. Nevertheless, mediation mechanisms between CSR and compassion at work have not been adequately examined leaving a vacuum to be explored. Despite finding a purpose in work that is greater than extrinsic outcomes of the work is important to employees, meaningful work has not been examined adequately. Thus, in addition to examining the direct relationship between CSR and compassion at work, this study examined the mediating capability of meaningful work between these variables. Specifically, the researcher explored how CSR enables employees to sense work as meaningful which in turn would enhance their level of compassion at work. Hypotheses were developed to examine the direct relationship between CSR and compassion at work and the mediating effect of meaningful work on the relationship between CSR and compassion at work. Both Social Identity Theory (SIT) and Social Exchange Theory (SET) were used to theoretically support the relationships. The sample comprised of 450 respondents covering different levels of the bank. A convenience sampling strategy was used to secure responses from 13 local licensed commercial banks in Sri Lanka. Data was collected using a structured questionnaire which was developed based on a comprehensive review of literature and refined using both expert opinions and a pilot survey. Structural equation modeling using Smart Partial Least Square (PLS) was utilized for data analysis. Findings indicate a positive and significant (p < .05) relationship between CSR and compassion at work. Also, it was found that meaningful work partially mediates the relationship between CSR and compassion at work. As per the findings it is concluded that bank employees’ perception of CSR engagement not only directly influence compassion at work but also impact such through meaningful work as well. This implies that employees consider working for a socially responsible bank since it creates greater meaningfulness of work to retain with the organization, which in turn trigger higher level of compassion at work. By utilizing both SIT and SET in explaining relationships between CSR and compassion at work it amounts to theoretical significance of the study. Enhance existing literature on CSR and compassion at work. Also, adds insights on mediating capability of psychologically related variables such as meaningful work. This study is expected to have significant policy implications in terms of increasing compassion at work where managers must understand the importance of including CSR activities into their strategy in order to thrive. Finally, it provides evidence of suitability of using Smart PLS to test models with mediating relationships involving non normal data.

Keywords: compassion at work, corporate social responsibility, employee commitment, meaningful work, positive affect

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Authors: Ha Phuong Tran, Feng Wang, Jo Dewulf, Hai Trung Huynh, Thomas Schaubroeck

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The fast increase and complex components have made waste of electrical and electronic equipment (or e-waste) one of the most problematic waste streams worldwide. Precise information on its size on national, regional and global level has therefore been highlighted as prerequisite to obtain a proper management system. However, this is a very challenging task, especially in developing countries where both formal e-waste management system and necessary statistical data for e-waste estimation, i.e. data on the production, sale and trade of electrical and electronic equipment (EEE), are often lacking. Moreover, there is an inflow of non-registered electronic and electric equipment, which ‘invisibly’ enters the EEE domestic market and then is used for domestic consumption. The non-registration/invisibility and (in most of the case) illicit nature of this flow make it difficult or even impossible to be captured in any statistical system. The e-waste generated from it is thus often uncounted in current e-waste estimation based on statistical market data. Therefore, this study focuses on enhancing e-waste estimation in developing countries and proposing a calculation pathway to quantify the magnitude of the non-registered EEE inflow. An advanced Input-Out Analysis model (i.e. the Sale–Stock–Lifespan model) has been integrated in the calculation procedure. In general, Sale-Stock-Lifespan model assists to improve the quality of input data for modeling (i.e. perform data consolidation to create more accurate lifespan profile, model dynamic lifespan to take into account its changes over time), via which the quality of e-waste estimation can be improved. To demonstrate the above objectives, a case study on televisions (TVs) in Vietnam has been employed. The results show that the amount of waste TVs in Vietnam has increased four times since 2000 till now. This upward trend is expected to continue in the future. In 2035, a total of 9.51 million TVs are predicted to be discarded. Moreover, estimation of non-registered TV inflow shows that it might on average contribute about 15% to the total TVs sold on the Vietnamese market during the whole period of 2002 to 2013. To tackle potential uncertainties associated with estimation models and input data, sensitivity analysis has been applied. The results show that both estimations of waste and non-registered inflow depend on two parameters i.e. number of TVs used in household and the lifespan. Particularly, with a 1% increase in the TV in-use rate, the average market share of non-register inflow in the period 2002-2013 increases 0.95%. However, it decreases from 27% to 15% when the constant unadjusted lifespan is replaced by the dynamic adjusted lifespan. The effect of these two parameters on the amount of waste TV generation for each year is more complex and non-linear over time. To conclude, despite of remaining uncertainty, this study is the first attempt to apply the Sale-Stock-Lifespan model to improve the e-waste estimation in developing countries and to quantify the non-registered EEE inflow to domestic consumption. It therefore can be further improved in future with more knowledge and data.

Keywords: e-waste, non-registered electrical and electronic equipment, TVs, Vietnam

Procedia PDF Downloads 248

Authors: Node Smith

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Developmental psychology has long focused on modeling consciousness, often neglecting practical application and clinical utility. This paper aims to bridge this gap by exploring the practical application of physical and sensory tracking and awareness in fostering essential skills for conscious development. Higher conscious development requires practical skills such as self-agency, the ability to hold multiple perspectives, and genuine altruism. These are not personality characteristics but areas of skillfulness that address many cultural deficiencies impacting our world. They are intertwined with individual as well as collective conscious development. Physical, sensory tracking and awareness are crucial for developing these skills and offer the added benefit of cultivating healthy communication, emotional regulation, and introspection. Unlike skills such as throwing a baseball, which can be developed through practice or innate ability, the ability to introspect, track physical sensations, and observe oneself objectively is essential for advancing consciousness. Lacking these skills leads to cultural and individual anxiety, helplessness, and a lack of agency, manifesting as blame-shifting and irresponsibility. The inability to hold multiple perspectives stifles altruism, as genuine consideration for a global community requires accepting other perspectives without conditions. Physical and sensory tracking enhances self-awareness by grounding individuals in their bodily experiences. This grounding is critical for emotional regulation, allowing individuals to identify and process emotions in real-time, preventing overwhelm and fostering balance. Techniques like mindfulness meditation and body scan exercises attune individuals to their physical sensations, providing insights into their emotional states. Sensory awareness also facilitates healthy communication by fostering empathy and active listening. When individuals are in tune with their physical sensations, they become more present in interactions, picking up on subtle cues and responding thoughtfully. This presence reduces misunderstandings and conflicts, promoting more effective communication. The ability to introspect and observe oneself objectively is key to emotional introspection. This skill allows individuals to reflect on their thoughts, feelings, and behaviors, identify patterns, recognize areas for growth, and make conscious choices aligned with their values and goals. In conclusion, physical and sensory tracking and awareness are vital for developing the skills necessary for higher consciousness development. By fostering self-agency, emotional regulation, and the ability to hold multiple perspectives, these practices contribute to healthier communication, deeper emotional introspection, and a more altruistic and connected global community. Integrating these practices into developmental psychology and therapeutic interventions holds significant promise for both individual and societal transformation.

Keywords: conscious development, emotional introspection, emotional regulation, self-agency, stages of development

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Authors: Magdalena Idzikowska, Katarzyna Pająk, Kamil Kowalczyk

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Seafloor topography is a fundamental issue in geological, geophysical, and oceanographic studies. Single-beam or multibeam sonars attached to the hulls of ships are used to emit a hydroacoustic signal from transducers and reproduce the topography of the seabed. This solution provides relevant accuracy and spatial resolution. Bathymetric data from ships surveys provides National Centers for Environmental Information – National Oceanic and Atmospheric Administration. Unfortunately, most of the seabed is still unidentified, as there are still many gaps to be explored between ship survey tracks. Moreover, such measurements are very expensive and time-consuming. The solution is raster bathymetric models shared by The General Bathymetric Chart of the Oceans. The offered products are a compilation of different sets of data - raw or processed. Indirect data for the development of bathymetric models are also measurements of gravity anomalies. Some forms of seafloor relief (e.g. seamounts) increase the force of the Earth's pull, leading to changes in the sea surface. Based on satellite altimetry data, Sea Surface Height and marine gravity anomalies can be estimated, and based on the anomalies, it’s possible to infer the structure of the seabed. The main goal of the work is to create regional bathymetric models and models of the sea surface in the area of the east coast of North America – a region of seamounts and undulating seafloor. The research includes an analysis of the methods and techniques used, an evaluation of the interpolation algorithms used, model thickening, and the creation of grid models. Obtained data are raster bathymetric models in NetCDF format, survey data from multibeam soundings in MB-System format, and satellite altimetry data from Copernicus Marine Environment Monitoring Service. The methodology includes data extraction, processing, mapping, and spatial analysis. Visualization of the obtained results was carried out with Geographic Information System tools. The result is an extension of the state of the knowledge of the quality and usefulness of the data used for seabed and sea surface modeling and knowledge of the accuracy of the generated models. Sea level is averaged over time and space (excluding waves, tides, etc.). Its changes, along with knowledge of the topography of the ocean floor - inform us indirectly about the volume of the entire water ocean. The true shape of the ocean surface is further varied by such phenomena as tides, differences in atmospheric pressure, wind systems, thermal expansion of water, or phases of ocean circulation. Depending on the location of the point, the higher the depth, the lower the trend of sea level change. Studies show that combining data sets, from different sources, with different accuracies can affect the quality of sea surface and seafloor topography models.

Keywords: seafloor, sea surface height, bathymetry, satellite altimetry

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Authors: S. Fares, K. Mellakh, A. Hmouri

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The StorMer project aims to set up a network of researchers to study traditional hydraulic rainwater harvesting systems in the Mediterranean basin, a region suffering from the major impacts of climate change and limited natural water resources. The arid and semi-arid Mediterranean basin has a long history of pioneering water management practices. The region has developed various ancient traditional water management systems, such as cisterns and qanats, to sustainably manage water resources under historical conditions of scarcity. Therefore, the StorMer project brings together Spain, France, Italy, Greece, Jordan and Morocco to explore traditional rainwater harvesting practices and systems in the Mediterranean region and to develop accurate modeling to simulate the performance and sustainability of these technologies under present-day climatic conditions. The ultimate goal of this project was to resuscitate and valorize these practices in the context of contemporary challenges. This project was intended to establish a Mediterranean network to serve as a basis for a more ambitious project. The ultimate objective was to analyze traditional hydraulic systems and create a prototype hydraulic ecosystem using a coupled environmental approach and traditional and ancient know-how, with the aim of reinterpreting them in the light of current techniques. The combination of ‘traditional’ and ‘modern knowledge/techniques’ is expected to lead to proposals for innovative hydraulic systems. The pandemic initially slowed our progress, but in the end it forced us to carry out the fieldwork in Morocco and Saudi Arabia, and so restart the project. With the participation of colleagues from chronologically distant fields (archaeology, sociology), we are now prepared to share our observations and propose the next steps. This interdisciplinary approach should give us a global vision of the project's objectives and challenges. A diachronic approach is needed to tackle the question of the long-term adaptation of societies in a Mediterranean context that has experienced several periods of water stress. The next stage of the StorMer project is the implementation of pilots in non-urbanized regions. These pilots will test the implementation of traditional systems and will be maintained and evaluated in terms of effectiveness, cost and acceptance. Based on these experiences, larger projects will be proposed and could provide information for regional water management policies. One of the most important lessons learned from this project is the highly social nature of managing traditional rainwater harvesting systems. Unlike modern, centralized water infrastructures, these systems often require the involvement of communities, which assume ownership and responsibility for them. This kind of community engagement leads to greater maintenance and, therefore, sustainability of the systems. Knowledge of the socio-cultural characteristics of these communities means that the systems can be adapted to the needs of each location, ensuring greater acceptance and efficiency.

Keywords: oasis, rainfall harvesting, arid regions, Mediterranean

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Authors: Devansh Desai, Rahul Nigam

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Crop water stress (W) at a given growth stage starts to set in as moisture availability (M) to roots falls below 75% of maximum. It has been found that ratio of crop evapotranspiration (ET) and reference evapotranspiration (ET0) is an indicator of moisture adequacy and is strongly correlated with ‘M’ and ‘W’. The spatial variability of ET0 is generally less over an agricultural farm of 1-5 ha than ET, which depends on both surface and atmospheric conditions, while the former depends only on atmospheric conditions. Solutions from surface energy balance (SEB) and thermal infrared (TIR) remote sensing are now known to estimate latent heat flux of ET. In the present study, ET and moisture adequacy index (MAI) (=ET/ET0) have been estimated over two contrasting western India agricultural farms having rice-wheat system in semi-arid climate and arid grassland system, limited by moisture availability. High-resolution multi-band TIR sensing observations at 65m from ECOSTRESS (ECOsystemSpaceborne Thermal Radiometer Experiment on Space Station) instrument on-board International Space Station (ISS) were used in an analytical SEB model, STIC (Surface Temperature Initiated Closure) to estimate ET and MAI. The ancillary variables used in the ET modeling and MAI estimation were land surface albedo, NDVI from close-by LANDSAT data at 30m spatial resolution, ET0 product at 4km spatial resolution from INSAT 3D, meteorological forcing variables from short-range weather forecast on air temperature and relative humidity from NWP model. Farm-scale ET estimates at 65m spatial resolution were found to show low RMSE of 16.6% to 17.5% with R2 >0.8 from 18 datasets as compared to reported errors (25 – 30%) from coarser-scale ET at 1 to 8 km spatial resolution when compared to in situ measurements from eddy covariance systems. The MAI was found to show lower (<0.25) and higher (>0.5) magnitudes in the contrasting agricultural farms. The study showed the potential need of high-resolution high-repeat spaceborne multi-band TIR payloads alongwith optical payload in estimating farm-scale ET and MAI for estimating consumptive water use and water stress. A set of future high-resolution multi-band TIR sensors are planned on-board Indo-French TRISHNA, ESA’s LSTM, NASA’s SBG space-borne missions to address sustainable irrigation water management at farm-scale to improve crop water productivity. These will provide precise and fundamental variables of surface energy balance such as LST (Land Surface Temperature), surface emissivity, albedo and NDVI. A synchronization among these missions is needed in terms of observations, algorithms, product definitions, calibration-validation experiments and downstream applications to maximize the potential benefits.

Keywords: thermal remote sensing, land surface temperature, crop water stress, evapotranspiration

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Authors: Ian O'Loughlin

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Memory networks aim to integrate some of the recent successes in machine learning with a dynamic memory base that can be updated and deployed in artificial reasoning tasks. These models involve training networks to identify, update, and operate over stored elements in a large memory array in order, for example, to ably perform question and answer tasks parsing real-world and simulated discourses. This family of approaches still faces numerous challenges: the performance of these network models in simulated domains remains considerably better than in open, real-world domains, wide-context cues remain elusive in parsing words and sentences, and even moderately complex sentence structures remain problematic. This innovation, employing an array of stored and updatable ‘memory’ elements over which the system operates as it parses text input and develops responses to questions, is a compelling one for at least two reasons: first, it addresses one of the difficulties that standard machine learning techniques face, by providing a way to store a large bank of facts, offering a way forward for the kinds of long-term reasoning that, for example, recurrent neural networks trained on a corpus have difficulty performing. Second, the addition of a stored long-term memory component in artificial reasoning seems psychologically plausible; human reasoning appears replete with invocations of long-term memory, and the stored but dynamic elements in the arrays of memory networks are deeply reminiscent of the way that human memory is readily and often characterized. However, this apparent psychological plausibility is belied by a recent turn in the study of human memory in cognitive science. In recent years, the very notion that there is a stored element which enables remembering, however dynamic or reconstructive it may be, has come under deep suspicion. In the wake of constructive memory studies, amnesia and impairment studies, and studies of implicit memory—as well as following considerations from the cognitive neuroscience of memory and conceptual analyses from the philosophy of mind and cognitive science—researchers are now rejecting storage and retrieval, even in principle, and instead seeking and developing models of human memory wherein plasticity and dynamics are the rule rather than the exception. In these models, storage is entirely avoided by modeling memory using a recurrent neural network designed to fit a preconceived energy function that attains zero values only for desired memory patterns, so that these patterns are the sole stable equilibrium points in the attractor network. So although the array of long-term memory elements in memory networks seem psychologically appropriate for reasoning systems, they may actually be incurring difficulties that are theoretically analogous to those that older, storage-based models of human memory have demonstrated. The kind of emergent stability found in the attractor network models more closely fits our best understanding of human long-term memory than do the memory network arrays, despite appearances to the contrary.

Keywords: artificial reasoning, human memory, machine learning, neural networks

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Authors: Federico Capra, Emanuele Martelli, Matteo Gazzani, Marco Mazzotti, Maurizio Notaro

Abstract:

Natural gas is a major energy source in the current global economy, contributing to roughly 21% of the total primary energy consumption. Production of natural gas starting from renewable energy sources is key to limit the related CO2 emissions, especially for those sectors that heavily rely on natural gas use. In this context, biomethane produced via biogas upgrading represents a good candidate for partial substitution of fossil natural gas. The upgrading process of biogas to biomethane consists in (i) the removal of pollutants and impurities (e.g. H2S, siloxanes, ammonia, water), and (ii) the separation of carbon dioxide from methane. Focusing on the CO2 removal process, several technologies can be considered: chemical or physical absorption with solvents (e.g. water, amines), membranes, adsorption-based systems (PSA). However, none emerged as the leading technology, because of (i) the heterogeneity in plant size, ii) the heterogeneity in biogas composition, which is strongly related to the feedstock type (animal manure, sewage treatment, landfill products), (iii) the case-sensitive optimal tradeoff between purity and recovery of biomethane, and iv) the destination of the produced biomethane (grid injection, CHP applications, transportation sector). With this contribution, we explore the use of a technology for biogas upgrading and we compare the resulting performance with benchmark technologies. The proposed technology makes use of a chemical sorbent, which is engineered by RSE and consists of Di-Ethanol-Amine deposited on a solid support made of γ-Alumina, to chemically adsorb the CO2 contained in the gas. The material is packed into fixed beds that cyclically undergo adsorption and regeneration steps. CO2 is adsorbed at low temperature and ambient pressure (or slightly above) while the regeneration is carried out by pulling vacuum and increasing the temperature of the bed (vacuum-temperature swing adsorption - VTSA). Dynamic adsorption tests were performed by RSE and were used to tune the mathematical model of the process, including material and transport parameters (i.e. Langmuir isotherms data and heat and mass transport). Based on this set of data, an optimal VTSA cycle was designed. The results enabled a better understanding of the interplay between material and cycle tuning. As exemplary application, the upgrading of biogas for grid injection, produced by an anaerobic digester (60-70% CO2, 30-40% CH4), for an equivalent size of 1 MWel was selected. A plant configuration is proposed to maximize heat recovery and minimize the energy consumption of the process. The resulting performances are very promising compared to benchmark solutions, which make the VTSA configuration a valuable alternative for biomethane production starting from biogas.

Keywords: biogas upgrading, biogas upgrading energetic cost, CO2 adsorption, VTSA process modelling

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Authors: Boris G. German, Edward Jiménez, Sebastián Espinoza, Andrés G. Chico, Ricardo A. Narváez

Abstract:

The unique flora and fauna of The Galapagos Islands has leveraged a tourism-driven growth in the islands. Nonetheless, such development is energy-intensive and requires thousands of gallons of diesel each year for thermoelectric electricity generation. The needed transport of fossil fuels from the continent has generated oil spillages and affectations to the fragile ecosystem of the islands. The Zero Fossil Fuels initiative for The Galapagos proposed by the Ecuadorian government as an alternative to reduce the use of fossil fuels in the islands, considers the replacement of diesel in thermoelectric generators, by Jatropha curcas vegetable oil. However, the Jatropha oil supply cannot entirely cover yet the demand for electricity generation in Galapagos. Within this context, the present work aims to provide an optimization model that can be used as a selection criterion for approving new Jatropha Curcas collection points in rural areas of Manabi-Ecuador. For this purpose, existing Jatropha collection points in Manabi were grouped under three regions: north (7 collection points), center (4 collection points) and south (9 collection points). Field work was carried out in every region in order to characterize the collection points, to establish local Jatropha supply and to determine transportation costs. Data collection was complemented using GIS software and an objective function was defined in order to determine the profit associated to Jatropha oil production. The market price of both Jatropha oil and residual cake, were considered for the total revenue; whereas Jatropha price, transportation and oil extraction costs were considered for the total cost. The tonnes of Jatropha fruit and seed, transported from collection points to the extraction plant, were considered as variables. The maximum and minimum amount of the collected Jatropha from each region constrained the optimization problem. The supply chain was optimized using linear programming in order to maximize the profits. Finally, a sensitivity analysis was performed in order to find a profit-based criterion for the acceptance of future collection points in Manabi. The maximum profit reached a value of $ 4,616.93 per year, which represented a total Jatropha collection of 62.3 tonnes Jatropha per year. The northern region of Manabi had the biggest collection share (69%), followed by the southern region (17%). The criteria for accepting new Jatropha collection points in the rural areas of Manabi can be defined by the current maximum profit of the zone and by the variation in the profit when collection points are removed one at a time. The definition of new feasible collection points plays a key role in the supply chain associated to Jatropha oil production. Therefore, a mathematical model that assists decision makers in establishing new collection points while assuring profitability, contributes to guarantee a continued Jatropha oil supply for Galapagos and a sustained economic growth in the rural areas of Ecuador.

Keywords: collection points, Jatropha curcas, linear programming, supply chain

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Authors: I. Hosni, L. Bennaceur Farah, N. Saber, R Bennaceur

Abstract:

Soil moisture content is a key variable in many environmental sciences. Even though it represents a small proportion of the liquid freshwater on Earth, it modulates interactions between the land surface and the atmosphere, thereby influencing climate and weather. Accurate modeling of the above processes depends on the ability to provide a proper spatial characterization of soil moisture. The measurement of soil moisture content allows assessment of soil water resources in the field of hydrology and agronomy. The second parameter in interaction with the radar signal is the geometric structure of the soil. Most traditional electromagnetic models consider natural surfaces as single scale zero mean stationary Gaussian random processes. Roughness behavior is characterized by statistical parameters like the Root Mean Square (RMS) height and the correlation length. Then, the main problem is that the agreement between experimental measurements and theoretical values is usually poor due to the large variability of the correlation function, and as a consequence, backscattering models have often failed to predict correctly backscattering. In this study, surfaces are considered as band-limited fractal random processes corresponding to a superposition of a finite number of one-dimensional Gaussian process each one having a spatial scale. Multiscale roughness is characterized by two parameters, the first one is proportional to the RMS height, and the other one is related to the fractal dimension. Soil moisture is related to the complex dielectric constant. This multiscale description has been adapted to two-dimensional profiles using the bi-dimensional wavelet transform and the Mallat algorithm to describe more correctly natural surfaces. We characterize the soil surfaces and sub-surfaces by a three layers geo-electrical model. The upper layer is described by its dielectric constant, thickness, a multiscale bi-dimensional surface roughness model by using the wavelet transform and the Mallat algorithm, and volume scattering parameters. The lower layer is divided into three fictive layers separated by an assumed plane interface. These three layers were modeled by an effective medium characterized by an apparent effective dielectric constant taking into account the presence of air pockets in the soil. We have adopted the 2D multiscale three layers small perturbations model including, firstly air pockets in the soil sub-structure, and then a vegetable canopy in the soil surface structure, that is to simulate the radar backscattering. A sensitivity analysis of backscattering coefficient dependence on multiscale roughness and new soil moisture has been performed. Later, we proposed to change the dielectric constant of the multilayer medium because it takes into account the different moisture values of each layer in the soil. A sensitivity analysis of the backscattering coefficient, including the air pockets in the volume structure with respect to the multiscale roughness parameters and the apparent dielectric constant, was carried out. Finally, we proposed to study the behavior of the backscattering coefficient of the radar on a soil having a vegetable layer in its surface structure.

Keywords: multiscale, bidimensional, wavelets, backscattering, multilayer, SPM, air pockets

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Authors: Hatem Abou-Senna, Essam Radwan

Abstract:

With increasing traffic and limited resources, accommodating left-turning traffic has been a challenge for traffic engineers as they seek balance between intersection capacity and safety; these are two conflicting goals in the operation of a signalized intersection that are mitigated through signal phasing techniques. Hence, to increase the left-turn capacity and reduce the delay at the intersections, the Florida Department of Transportation (FDOT) moves forward with a vision of optimizing intersection control using innovative intersection designs through the Transportation Systems Management & Operations (TSM&O) program. These alternative designs successfully eliminate the left-turn phase, which otherwise reduces the conventional intersection’s (CI) efficiency considerably, and divide the intersection into smaller networks that would operate in a one-way fashion. This study focused on the Crossover Displaced Left-turn intersections (XDL), also known as Continuous Flow Intersections (CFI). The XDL concept is best suited for intersections with moderate to high overall traffic volumes, especially those with very high or unbalanced left turn volumes. There is little guidance on determining whether partial XDL intersections are adequate to mitigate the overall intersection condition or full XDL is always required. The primary objective of this paper was to evaluate the overall intersection performance in the case of different partial XDL designs compared to a full XDL. The XDL alternative was investigated for 4 different scenarios; partial XDL on the east-west approaches, partial XDL on the north-south approaches, partial XDL on the north and east approaches and full XDL on all 4 approaches. Also, the impact of increasing volume on the intersection performance was considered by modeling the unbalanced volumes with 10% increment resulting in 5 different traffic scenarios. The study intersection, located in Orlando Florida, is experiencing recurring congestion in the PM peak hour and is operating near capacity with volume to a capacity ratio closer to 1.00 due to the presence of two heavy conflicting movements; southbound and westbound. The results showed that a partial EN XDL alternative proved to be effective and compared favorably to a full XDL alternative followed by the partial EW XDL alternative. The analysis also showed that Full, EW and EN XDL alternatives outperformed the NS XDL and the CI alternatives with respect to the throughput, delay and queue lengths. Significant throughput improvements were remarkable at the higher volume level with percent increase in capacity of 25%. The percent reduction in delay for the critical movements in the XDL scenarios compared to the CI scenario ranged from 30-45%. Similarly, queue lengths showed percent reduction in the XDL scenarios ranging from 25-40%. The analysis revealed how partial XDL design can improve the overall intersection performance at various demands, reduce the costs associated with full XDL and proved to outperform the conventional intersection. However, partial XDL serving low volumes or only one of the critical movements while other critical movements are operating near or above capacity do not provide significant benefits when compared to the conventional intersection.

Keywords: continuous flow intersections, crossover displaced left-turn, microscopic traffic simulation, transportation system management and operations, VISSIM simulation model

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