Search results for: Computational Fluid Dynamics

Authors: Salima R. Rajwani, Tazeen Ali, Rubina Barolia, Yasmin Parpio, Nasreen Alwani, Salima B. Virani

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Introduction: Nurses and physicians have a critical role in initiating lifesaving interventions during cardiac arrest. It is important that timely delivery of high quality Cardio Pulmonary Resuscitation (CPR) with advanced resuscitation skills and management of cardiac arrhythmias is a key dimension of code during cardiac arrest. It will decrease the chances of patient survival if the healthcare professionals are unable to initiate CPR timely. Moreover, traditional training will not prepare physicians and nurses at a competent level and their knowledge level declines over a period of time. In this regard, simulation training has been proven to be effective in promoting resuscitation skills. Simulation teaching learning strategy improves knowledge level, and skills performance during resuscitation through experiential learning without compromising patient safety in real clinical situations. The purpose of the study is to evaluate the effectiveness of simulation training in Advanced Cardiac Life Support Courses by using the selfefficacy tool. Methods: The study design is a quantitative research design and non-randomized quasi-experimental study design. The study examined the effectiveness of simulation through self-efficacy in two instructional methods; one is Medium Fidelity Simulation (MFS) and second is Traditional Training Method (TTM). The sample size was 220. Data was compiled by using the SPSS tool. The standardized simulation based training increases self-efficacy, knowledge, and skills and improves the management of patients in actual resuscitation. Results: 153 students participated in study; CG: n = 77 and EG: n = 77. The comparison was done between arms in pre and post-test. (F value was 1.69, p value is <0.195 and df was 1). There was no significant difference between arms in the pre and post-test. The interaction between arms was observed and there was no significant difference in interaction between arms in the pre and post-test. (F value was 0.298, p value is <0.586 and df is 1. However, the results showed self-efficacy scores were significantly higher within experimental group in post-test in advanced cardiac life support resuscitation courses as compared to Traditional Training Method (TTM) and had overall (p <0.0001) and F value was 143.316 (mean score was 45.01 and SD was 9.29) verses pre-test result showed (mean score was 31.15 and SD was 12.76) as compared to TTM in post-test (mean score was 29.68 and SD was 14.12) verses pre-test result showed (mean score was 42.33 and SD was 11.39). Conclusion: The standardized simulation-based training was conducted in the safe learning environment in Advanced Cardiac Life Suport Courses and physicians and nurses benefited from self-confidence, early identification of life-threatening scenarios, early initiation of CPR, and provides high-quality CPR, timely administration of medication and defibrillation, appropriate airway management, rhythm analysis and interpretation, and Return of Spontaneous Circulation (ROSC), team dynamics, debriefing, and teaching and learning strategies that will improve the patient survival in actual resuscitation.

Keywords: advanced cardiac life support, cardio pulmonary resuscitation, return of spontaneous circulation, simulation

Procedia PDF Downloads 80

Authors: Katarina Pogacnik, Ursa Zakrajsek, Nejc Sirk, Ziga Lampret

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Due to an increase in living standards along with global population growth and a trend of urbanization, municipalities and regions are faced with an ever rising energy demand. A challenge has arisen for cities around the world to modify the energy supply chain in order to reduce its consumption and CO₂ emissions. The aim of our work is the development of a computational-analytical platform for dynamic support in decision-making and the determination of economic and technical indicators of energy efficiency in a smart city, named Energy Atlas. Similar products in this field focuse on a narrower approach, whereas in order to achieve its aim, this platform encompasses a wider spectrum of beneficial and important information for energy planning on a local or regional scale. GIS based interactive maps provide an extensive database on the potential, use and supply of energy and renewable energy sources along with climate, transport and spatial data of the selected municipality. Beneficiaries of Energy atlas are local communities, companies, investors, contractors as well as residents. The Energy Atlas platform consists of three modules named E-Planning, E-Indicators and E-Cooperation. The E-Planning module is a comprehensive data service, which represents a support towards optimal decision-making and offers a sum of solutions and feasibility of measures and their effects in the area of efficient use of energy and renewable energy sources. The E-Indicators module identifies, collects and develops optimal data and key performance indicators and develops an analytical application service for dynamic support in managing a smart city in regards to energy use and sustainable environment. In order to support cooperation and direct involvement of citizens of the smart city, the E-cooperation is developed with the purpose of integrating the interdisciplinary and sociological aspects of energy end-users. Interaction of all the above-described modules contributes to regional development because it enables for a precise assessment of the current situation, strategic planning, detection of potential future difficulties and also the possibility of public involvement in decision-making. From the implementation of the technology in Slovenian municipalities of Ljubljana, Piran, and Novo mesto, there is evidence to suggest that the set goals are to be achieved to a great extent. Such thorough urban energy planning tool is viewed as an important piece of the puzzle towards achieving a low-carbon society, circular economy and therefore, sustainable society.

Keywords: circular economy, energy atlas, energy management, energy planning, low-carbon society

Procedia PDF Downloads 306

Authors: Zografou Konstantina, Anagnostellis Konstantinos, Brokaki Marina, Kaltsouni Eleftheria, Dimaki Maria, Kati Vassiliki

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Body size is crucial to ecology, influencing everything from individual reproductive success to the dynamics of communities and ecosystems. Understanding how temperature affects variations in body size is vital for both theoretical and practical purposes, as changes in size can modify trophic interactions by altering predator-prey size ratios and changing the distribution and transfer of biomass, which ultimately impacts food web stability and ecosystem functioning. Notably, a decrease in body size is frequently mentioned as the third "universal" response to climate warming, alongside shifts in distribution and changes in phenology. This trend is backed by ecological theories like the temperature-size rule (TSR) and Bergmann's rule, which have been observed in numerous species, indicating that many species are likely to shrink in size as temperatures rise. However, the thermal responses related to body size are still contradictory, and further exploration is needed. To tackle this challenge, we developed the MEIOSIS project, aimed at providing valuable insights into the relationship between the body size of species, species’ traits, environmental factors, and their response to climate change. We combined a digitized collection of butterflies from the Swiss Federal Institute of Technology in Zürich with our newly digitized butterfly collection from Goulandris Natural History Museum in Greece to analyse trends in time. For a total of 23868 images, the length of the right forewing was measured using ImageJ software. Each forewing was measured from the point at which the wing meets the thorax to the apex of the wing. The forewing length of museum specimens has been shown to have a strong correlation with wing surface area and has been utilized in prior studies as a proxy for overall body size. Temperature data corresponding to the years of collection were also incorporated into the datasets. A second dataset was generated when a custom computer vision tool was implemented for the automated morphological measuring of samples for the digitized collection in Zürich. Using the second dataset, we corrected manual measurements with ImageJ, and a final dataset containing 31922 samples was used for analysis. Setting time as a smoother variable, species identity as a random factor, and the length of right-wing size (a proxy for body size) as the response variable, we ran a global model for a maximum period of 110 years (1900 – 2010). Then, we investigated functional variability between different terrestrial biomes in a second model. Both models confirmed our initial hypothesis and resulted in a decreasing trend in body size over the years. We expect that this first output can be provided as basic data for the next challenge, i.e., to identify the ecological traits that influence species' temperature-size responses, enabling us to predict the direction and intensity of a species' reaction to rising temperatures more accurately.

Keywords: butterflies, shrinking body size, museum specimens, climate change

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Authors: Soheila Sadeghi

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Infrastructure projects often encounter contract variations that can significantly deviate from the original tender estimates, leading to cost overruns, schedule delays, and financial implications. This research aims to quantitatively assess the impact of changes in contract variations on project performance by conducting an in-depth analysis of a comprehensive dataset from the Regional Airport Car Park project. The dataset includes tender budget, contract quantities, rates, claims, and revenue data, providing a unique opportunity to investigate the effects of variations on project outcomes. The study focuses on 21 specific variations identified in the dataset, which represent changes or additions to the project scope. The research methodology involves establishing a baseline for the project's planned cost and scope by examining the tender budget and contract quantities. Each variation is then analyzed in detail, comparing the actual quantities and rates against the tender estimates to determine their impact on project cost and schedule. The claims data is utilized to track the progress of work and identify deviations from the planned schedule. The study employs statistical analysis using R to examine the dataset, including tender budget, contract quantities, rates, claims, and revenue data. Time series analysis is applied to the claims data to track progress and detect variations from the planned schedule. Regression analysis is utilized to investigate the relationship between variations and project performance indicators, such as cost overruns and schedule delays. The research findings highlight the significance of effective variation management in construction projects. The analysis reveals that variations can have a substantial impact on project cost, schedule, and financial outcomes. The study identifies specific variations that had the most significant influence on the Regional Airport Car Park project's performance, such as PV03 (additional fill, road base gravel, spray seal, and asphalt), PV06 (extension to the commercial car park), and PV07 (additional box out and general fill). These variations contributed to increased costs, schedule delays, and changes in the project's revenue profile. The study also examines the effectiveness of project management practices in managing variations and mitigating their impact. The research suggests that proactive risk management, thorough scope definition, and effective communication among project stakeholders can help minimize the negative consequences of variations. The findings emphasize the importance of establishing clear procedures for identifying, assessing, and managing variations throughout the project lifecycle. The outcomes of this research contribute to the body of knowledge in construction project management by demonstrating the value of analyzing tender, contract, claims, and revenue data in variation impact assessment. However, the research acknowledges the limitations imposed by the dataset, particularly the absence of detailed contract and tender documents. This constraint restricts the depth of analysis possible in investigating the root causes and full extent of variations' impact on the project. Future research could build upon this study by incorporating more comprehensive data sources to further explore the dynamics of variations in construction projects.

Keywords: contract variation impact, quantitative analysis, project performance, claims analysis

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Authors: Felipe M. de Freitas, Icaro V. Soares, Lucas L. L. Fortes, Sandro T. M. Gonçalves, Úrsula D. C. Resende

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The SPICE-based simulators are quite robust and widely used for simulation of electronic circuits, their algorithms support linear and non-linear lumped components and they can manipulate an expressive amount of encapsulated elements. Despite the great potential of these simulators based on SPICE in the analysis of quasi-static electromagnetic field interaction, that is, at low frequency, these simulators are limited when applied to microwave hybrid circuits in which there are both lumped and distributed elements. Usually the spatial discretization of the FDTD (Finite-Difference Time-Domain) method is done according to the actual size of the element under analysis. After spatial discretization, the Courant Stability Criterion calculates the maximum temporal discretization accepted for such spatial discretization and for the propagation velocity of the wave. This criterion guarantees the stability conditions for the leapfrogging of the Yee algorithm; however, it is known that for the field update, the stability of the complete FDTD procedure depends on factors other than just the stability of the Yee algorithm, because the FDTD program needs other algorithms in order to be useful in engineering problems. Examples of these algorithms are Absorbent Boundary Conditions (ABCs), excitation sources, subcellular techniques, grouped elements, and non-uniform or non-orthogonal meshes. In this work, the influence of the stability of the FDTD method in the modeling of concentrated elements such as resistive sources, resistors, capacitors, inductors and diode will be evaluated. In this paper is proposed, therefore, the electromagnetic modeling of electronic components in order to create models that satisfy the needs for simulations of circuits in ultra-wide frequencies. The models of the resistive source, the resistor, the capacitor, the inductor, and the diode will be evaluated, among the mathematical models for lumped components in the LE-FDTD method (Lumped-Element Finite-Difference Time-Domain), through the parametric analysis of Yee cells size which discretizes the lumped components. In this way, it is sought to find an ideal cell size so that the analysis in FDTD environment is in greater agreement with the expected circuit behavior, maintaining the stability conditions of this method. Based on the mathematical models and the theoretical basis of the required extensions of the FDTD method, the computational implementation of the models in Matlab® environment is carried out. The boundary condition Mur is used as the absorbing boundary of the FDTD method. The validation of the model is done through the comparison between the obtained results by the FDTD method through the electric field values and the currents in the components, and the analytical results using circuit parameters.

Keywords: hybrid circuits, LE-FDTD, lumped element, parametric analysis

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Authors: Saurabh Sharma, Yong Sun, Bruce Vernham

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Accurate prediction of NOx emission is a continuous challenge in the field of diesel engine-out emission modeling. Performing experiments for each conditions and scenario cost significant amount of money and man hours, therefore model-based development strategy has been implemented in order to solve that issue. NOx formation is highly dependent on the burn gas temperature and the O₂ concentration inside the cylinder. The current empirical models are developed by calibrating the parameters representing the engine operating conditions with respect to the measured NOx. This makes the prediction of purely empirical models limited to the region where it has been calibrated. An alternative solution to that is presented in this paper, which focus on the utilization of in-cylinder combustion parameters to form a predictive semi-empirical NOx model. The result of this work is shown by developing a fast and predictive NOx model by using the physical parameters and empirical correlation. The model is developed based on the steady state data collected at entire operating region of the engine and the predictive combustion model, which is developed in Gamma Technology (GT)-Power by using Direct Injected (DI)-Pulse combustion object. In this approach, temperature in both burned and unburnt zone is considered during the combustion period i.e. from Intake Valve Closing (IVC) to Exhaust Valve Opening (EVO). Also, the oxygen concentration consumed in burnt zone and trapped fuel mass is also considered while developing the reported model.  Several statistical methods are used to construct the model, including individual machine learning methods and ensemble machine learning methods. A detailed validation of the model on multiple diesel engines is reported in this work. Substantial numbers of cases are tested for different engine configurations over a large span of speed and load points. Different sweeps of operating conditions such as Exhaust Gas Recirculation (EGR), injection timing and Variable Valve Timing (VVT) are also considered for the validation. Model shows a very good predictability and robustness at both sea level and altitude condition with different ambient conditions. The various advantages such as high accuracy and robustness at different operating conditions, low computational time and lower number of data points requires for the calibration establishes the platform where the model-based approach can be used for the engine calibration and development process. Moreover, the focus of this work is towards establishing a framework for the future model development for other various targets such as soot, Combustion Noise Level (CNL), NO₂/NOx ratio etc.

Keywords: diesel engine, machine learning, NOₓ emission, semi-empirical

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Authors: Pedro M. Rodrigues, Claudia Raposo, Denise Schrama, Marco Cerqueira

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Farmed fish welfare is a very recent concept, widely discussed among the scientific community. Consumers’ interest regarding farmed animal welfare standards has significantly increased in the last years posing a huge challenge to producers in order to maintain an equilibrium between good welfare principles and productivity, while simultaneously achieve public acceptance. The major bottleneck of standard aquaculture is to impair considerably fish welfare throughout the production cycle and with this, the quality of fish protein. Welfare assessment in farmed fish is undertaken through the evaluation of fish stress responses. Primary and secondary stress responses include release of cortisol and glucose and lactate to the blood stream, respectively, which are currently the most commonly used indicators of stress exposure. However, the reliability of these indicators is highly dubious, due to a high variability of fish responses to an acute stress and the adaptation of the animal to a repetitive chronic stress. Our objective is to use comparative proteomics to identify and validate a fingerprint of proteins that can present an more reliable alternative to the already established welfare indicators. In this way, the culture conditions will improve and there will be a higher perception of mechanisms and metabolic pathway involved in the produced organism’s welfare. Due to its high economical importance in Portuguese aquaculture Gilthead seabream will be the elected species for this study. Protein extracts from Gilthead Seabream fish muscle, liver and plasma, reared for a 3 month period under optimized culture conditions (control) and induced stress conditions (Handling, high densities, and Hipoxia) are collected and used to identify a putative fish welfare protein markers fingerprint using a proteomics approach. Three tanks per condition and 3 biological replicates per tank are used for each analisys. Briefly, proteins from target tissue/fluid are extracted using standard established protocols. Protein extracts are then separated using 2D-DIGE (Difference gel electrophoresis). Proteins differentially expressed between control and induced stress conditions will be identified by mass spectrometry (LC-Ms/Ms) using NCBInr (taxonomic level - Actinopterygii) databank and Mascot search engine. The statistical analysis is performed using the R software environment, having used a one-tailed Mann-Whitney U-test (p < 0.05) to assess which proteins were differentially expressed in a statistically significant way. Validation of these proteins will be done by comparison of the RT-qPCR (Quantitative reverse transcription polymerase chain reaction) expressed genes pattern with the proteomic profile. Cortisol, glucose, and lactate are also measured in order to confirm or refute the reliability of these indicators. The identified liver proteins under handling and high densities induced stress conditions are responsible and involved in several metabolic pathways like primary metabolism (i.e. glycolysis, gluconeogenesis), ammonia metabolism, cytoskeleton proteins, signalizing proteins, lipid transport. Validition of these proteins as well as identical analysis in muscle and plasma are underway. Proteomics is a promising high-throughput technique that can be successfully applied to identify putative welfare protein biomarkers in farmed fish.

Keywords: aquaculture, fish welfare, proteomics, welfare biomarkers

Procedia PDF Downloads 157

Authors: Ankit Khurana

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The sufficient heat storage capacity or ability to dissipate heat is the most decisive parameter to have an effective and efficient functioning of Friction-based Brake Disc systems. The primary aim of the research was to analyse the effect of multiple coatings on lightweight disk rotors surface which not only alleviates the mass of vehicle & also, augments heat transfer. This research is projected to aid the automobile fraternity with an enunciated view over the thermal aspects in a braking system. The results of the project indicate that with the advent of modern coating technologies a brake system’s thermal curtailments can be removed and together with forced convection, heat transfer processes can see a drastic improvement leading to increased lifetime of the brake rotor. Other advantages of modifying the surface of a lightweight rotor substrate will be to reduce the overall weight of the vehicle, decrease the risk of thermal brake failure (brake fade and fluid vaporization), longer component life, as well as lower noise and vibration characteristics. A mathematical model was constructed in MATLAB which encompassing the various thermal characteristics of the proposed coatings and substrate materials required to approximate the heat flux values in a free and forced convection environment; resembling to a real-time braking phenomenon which could easily be modelled into a full cum scaled version of the alloy brake rotor part in ABAQUS. The finite element of a brake rotor was modelled in a constrained environment such that the nodal temperature between the contact surfaces of the coatings and substrate (Wrought Aluminum alloy) resemble an amalgamated solid brake rotor element. The initial results obtained were for a Plasma Electrolytic Oxidized (PEO) substrate wherein the Aluminum alloy gets a hard ceramic oxide layer grown on its transitional phase. The rotor was modelled and then evaluated in real-time for a constant ‘g’ braking event (based upon the mathematical heat flux input and convective surroundings), which reflected the necessity to deposit a conducting coat (sacrificial) above the PEO layer in order to inhibit thermal degradation of the barrier coating prematurely. Taguchi study was then used to bring out certain critical factors which may influence the maximum operating temperature of a multi-coated brake disc by simulating brake tests: a) an Alpine descent lasting 50 seconds; b) an Autobahn stop lasting 3.53 seconds; c) a Six–high speed repeated stop in accordance to FMVSS 135 lasting 46.25 seconds. Thermal Barrier coating thickness and Vane heat transfer coefficient were the two most influential factors and owing to their design and manufacturing constraints a final optimized model was obtained which survived the 6-high speed stop test as per the FMVSS -135 specifications. The simulation data highlighted the merits for preferring Wrought Aluminum alloy 7068 over Grey Cast Iron and Aluminum Metal Matrix Composite in coherence with the multiple coating depositions.

Keywords: lightweight brakes, surface modification, simulated braking, PEO, aluminum

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Authors: Anthony F. Peressini

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The concept of race has recently come prominently back into discussion in the context of medicine and medical science, along with renewed effort to biologize racial concepts. This paper argues that this renewed effort to biologize race by way of medicine and population genetics fail on their own terms, and more importantly, that the philosophical project of biologizing race ought to be recognized for what it is—a retrograde racial project—and abandoned. There is clear agreement that standard racial categories and concepts cannot be grounded in the old way of racial naturalism, which understand race as a real, interest-independent biological/metaphysical category in which its members share “physical, moral, intellectual, and cultural characteristics.” But equally clear is the very real and pervasive presence of racial concepts in individual and collective consciousness and behavior, and so it remains a pressing area in which to seek deeper understanding. Recent philosophical work has endeavored to reconcile these two observations by developing a “thin” conception of race, grounded in scientific concepts but without the moral and metaphysical content. Such “thin,” science-based analyses take the “commonsense” or “folk” sense of race as it functions in contemporary society as the starting point for their philosophic-scientific projects to biologize racial concepts. A “philosophic-scientific analysis” is a special case of the cornerstone of analytic philosophy: a conceptual analysis. That is, a rendering of a concept into the more perspicuous concepts that constitute it. Thus a philosophic-scientific account of a concept is an attempt to work out an analysis of a concept that makes use of empirical science's insights to ground, legitimate and explicate the target concept in terms of clearer concepts informed by empirical results. The focus in this paper is on three recent philosophic-scientific cases for retaining “race” that all share this general analytic schema, but that make use of “medical necessity,” population genetics, and human genetic clustering, respectively. After arguing that each of these three approaches suffers from internal difficulties, the paper considers the general analytic schema employed by such biologizations of race. While such endeavors are inevitably prefaced with the disclaimer that the theory to follow is non-essentialist and non-racialist, the case will be made that such efforts are not neutral scientific or philosophical projects but rather are what sociologists call a racial project, that is, one of many competing efforts that conjoin a representation of what race means to specific efforts to determine social and institutional arrangements of power, resources, authority, etc. Accordingly, philosophic-scientific biologizations of race, since they begin from and condition their analyses on “folk” conceptions, cannot pretend to be “prior to” other disciplinary insights, nor to transcend the social-political dynamics involved in formulating theories of race. As a result, such traditional philosophical efforts can be seen to be disciplinarily parochial and to address only a caricature of a large and important human problem—and thereby further contributing to the unfortunate isolation of philosophical thinking about race from other disciplines.

Keywords: population genetics, ontology of race, race-based medicine, racial formation theory, racial projects, racism, social construction

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Authors: David Gottlieb, Jason Yoder

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The feeling of loneliness is not uncommon in modern society, and yet, there is a fundamental lack of understanding in its origins and purpose in nature. One interpretation of loneliness is that it is a subjective experience that punishes a lack of social behavior, and thus its emergence in human evolution is seemingly tied to the survival of early human tribes. Still, a common counterintuitive response to loneliness is a state of hypervigilance, resulting in social withdrawal, which may appear maladaptive to modern society. So far, no computational model of loneliness’ effect during evolution yet exists; however, agent-based models (ABM) can be used to investigate social behavior, and applying evolution to agents’ behaviors can demonstrate selective advantages for particular behaviors. We propose an ABM where each agent contains four social behaviors, and one goal-seeking behavior, letting evolution select the best behavioral patterns for resource allocation. In our paper, we use an algorithm similar to the boid model to guide the behavior of agents, but expand the set of rules that govern their behavior. While we use cohesion, separation, and alignment for simple social movement, our expanded model adds goal-oriented behavior, which is inspired by particle swarm optimization, such that agents move relative to their personal best position. Since agents are given the ability to form connections by interacting with each other, our final behavior guides agent movement toward its social connections. Finally, we introduce a mechanism to represent a state of loneliness, which engages when an agent's perceived social involvement does not meet its expected social involvement. This enables us to investigate a minimal model of loneliness, and using evolution we attempt to elucidate its value in human survival. Agents are placed in an environment in which they must acquire resources, as their fitness is based on the total resource collected. With these rules in place, we are able to run evolution under various conditions, including resource-rich environments, and when disease is present. Our simulations indicate that there is strong selection pressure for social behavior under circumstances where there is a clear discrepancy between initial resource locations, and against social behavior when disease is present, mirroring hypervigilance. This not only provides an explanation for the emergence of loneliness, but also reflects the diversity of response to loneliness in the real world. In addition, there is evidence of a richness of social behavior when loneliness was present. By introducing just two resource locations, we observed a divergence in social motivation after agents became lonely, where one agent learned to move to the other, who was in a better resource position. The results and ongoing work from this project show that it is possible to glean insight into the evolutionary advantages of even simple mechanisms of loneliness. The model we developed has produced unexpected results and has led to more questions, such as the impact loneliness would have at a larger scale, or the effect of creating a set of rules governing interaction beyond adjacency.

Keywords: agent-based, behavior, evolution, loneliness, social

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Authors: Pornpimol Chaiwuttisak, Honora Smith, Yue Wu

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Blood is a perishable product which suffers from physical deterioration with specific fixed shelf life. Although its value during the shelf life is constant, fresh blood is preferred for treatment. However, transportation costs are a major factor to be considered by administrators of Regional Blood Centres (RBCs) which act as blood collection and distribution centres. A trade-off must therefore be reached between transportation costs and short-term holding costs. In this paper we propose a number of algorithms for online allocation and routing of blood supplies, for use in conditions of variable and insufficient blood supply. A case study in northern Thailand provides an application of the allocation and routing policies tested. The plan proposed for daily allocation and distribution of blood supplies consists of two components: firstly, fixed routes are determined for the supply of hospitals which are far from an RBC. Over the planning period of one week, each hospital on the fixed routes is visited once. A robust allocation of blood is made to hospitals on the fixed routes that can be guaranteed on a suitably high percentage of days, despite variable supplies. Secondly, a variable daily route is employed for close-by hospitals, for which more than one visit per week may be needed to fulfil targets. The variable routing takes into account the amount of blood available for each day’s deliveries, which is only known on the morning of delivery. For hospitals on the variables routes, the day and amounts of deliveries cannot be guaranteed but are designed to attain targets over the six-day planning horizon. In the conditions of blood shortage encountered in Thailand, and commonly in other developing countries, it is often the case that hospitals request more blood than is needed, in the knowledge that only a proportion of all requests will be met. Our proposal is for blood supplies to be allocated and distributed to each hospital according to equitable targets based on historical demand data, calculated with regard to expected daily blood supplies. We suggest several policies that could be chosen by the decision makes for the daily distribution of blood. The different policies provide different trade-offs between transportation and holding costs. Variations in the costs of transportation, such as the price of petrol, could make different policies the most beneficial at different times. We present an application of the policies applied to a realistic case study in the RBC at Chiang Mai province which is located in Northern region of Thailand. The analysis includes a total of more than 110 hospitals, with 29 hospitals considered in the variable route. The study is expected to be a pilot for other regions of Thailand. Computational experiments are presented. Concluding remarks include the benefits gained by the online methods and future recommendations.

Keywords: online algorithm, blood distribution, developing country, insufficient blood supply

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Authors: Hameed Rukayat Opeyemi, Pericles Pilidis, Pagone Emanuele

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Climate change represents one of the single most challenging problems facing the world today. According to the National Oceanic and Administrative Association, Atmospheric temperature rose almost 25% since 1958, Artic sea ice has shrunk 40% since 1959 and global sea levels have risen more than 5.5 cm since 1990. Power plants are the major culprits of GHG emission to the atmosphere. Several technologies have been proposed to reduce the amount of GHG emitted to the atmosphere from power plant, one of which is the less researched Advanced zero emission power plant. The advanced zero emission power plants make use of mixed conductive membrane (MCM) reactor also known as oxygen transfer membrane (OTM) for oxygen transfer. The MCM employs membrane separation process. The membrane separation process was first introduced in 1899 when Walter Hermann Nernst investigated electric current between metals and solutions. He found that when a dense ceramic is heated, current of oxygen molecules move through it. In the bid to curb the amount of GHG emitted to the atmosphere, the membrane separation process was applied to the field of power engineering in the low carbon cycle known as the Advanced zero emission power plant (AZEP cycle). The AZEP cycle was originally invented by Norsk Hydro, Norway and ABB Alstom power (now known as Demag Delaval Industrial turbo machinery AB), Sweden. The AZEP drew a lot of attention because its ability to capture ~100% CO2 and also boasts of about 30-50 % cost reduction compared to other carbon abatement technologies, the penalty in efficiency is also not as much as its counterparts and crowns it with almost zero NOx emissions due to very low nitrogen concentrations in the working fluid. The advanced zero emission power plants differ from a conventional gas turbine in the sense that its combustor is substituted with the mixed conductive membrane (MCM-reactor). The MCM-reactor is made up of the combustor, low temperature heat exchanger LTHX (referred to by some authors as air pre-heater the mixed conductive membrane responsible for oxygen transfer and the high temperature heat exchanger and in some layouts, the bleed gas heat exchanger. Air is taken in by the compressor and compressed to a temperature of about 723 Kelvin and pressure of 2 Mega-Pascals. The membrane area needed for oxygen transfer is reduced by increasing the temperature of 90% of the air using the LTHX; the temperature is also increased to facilitate oxygen transfer through the membrane. The air stream enters the LTHX through the transition duct leading to inlet of the LTHX. The temperature of the air stream is then increased to about 1150 K depending on the design point specification of the plant and the efficiency of the heat exchanging system. The amount of oxygen transported through the membrane is directly proportional to the temperature of air going through the membrane. The AZEP cycle was developed using the Fortran software and economic analysis was conducted using excel and Matlab followed by optimization case study. This paper discusses techno-economic analysis of four possible layouts of the AZEP cycle. The Simple bleed gas heat exchange layout (100 % CO2 capture), Bleed gas heat exchanger layout with flue gas turbine (100 % CO2 capture), Pre-expansion reheating layout (Sequential burning layout) – AZEP 85 % (85 % CO2 capture) and Pre-expansion reheating layout (Sequential burning layout) with flue gas turbine– AZEP 85 % (85 % CO2 capture). This paper discusses Montecarlo risk analysis of four possible layouts of the AZEP cycle.

Keywords: gas turbine, global warming, green house gases, power plants

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Authors: Ali H. Daraji, Jack M. Hale, Ye Jianqiao

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With the extensive use of high specific strength structures to optimise the loading capacity and material cost in aerospace and most engineering applications, much effort has been expended to develop intelligent structures for active vibration reduction and structural health monitoring. These structures are highly flexible, inherently low internal damping and associated with large vibration and long decay time. The modification of such structures by adding lightweight piezoelectric sensors and actuators at efficient locations integrated with an optimal control scheme is considered an effective solution for structural vibration monitoring and controlling. The size and location of sensor and actuator are important research topics to investigate their effects on the level of vibration detection and reduction and the amount of energy provided by a controller. Several methodologies have been presented to determine the optimal location of a limited number of sensors and actuators for small-scale structures. However, these studies have tackled this problem directly, measuring the fitness function based on eigenvalues and eigenvectors achieved with numerous combinations of sensor/actuator pair locations and converging on an optimal set using heuristic optimisation techniques such as the genetic algorithms. This is computationally expensive for small- and large-scale structures subject to optimise a number of s/a pairs to suppress multiple vibration modes. This paper proposes an efficient method to determine optimal locations for a limited number of sensor/actuator pairs for active vibration reduction of a flexible structure based on finite element method and Hamilton’s principle. The current work takes the simplified approach of modelling a structure with sensors at all locations, subjecting it to an external force to excite the various modes of interest and noting the locations of sensors giving the largest average percentage sensors effectiveness measured by dividing all sensor output voltage over the maximum for each mode. The methodology was implemented for a cantilever plate under external force excitation to find the optimal distribution of six sensor/actuator pairs to suppress the first six modes of vibration. It is shown that the results of the optimal sensor locations give good agreement with published optimal locations, but with very much reduced computational effort and higher effectiveness. Furthermore, it is shown that collocated sensor/actuator pairs placed in these locations give very effective active vibration reduction using optimal linear quadratic control scheme.

Keywords: optimisation, plate, sensor effectiveness, vibration control

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Authors: Chevonne Reynolds, Res Altwegg, Andrew Balmford, Claire N. Spottiswoode

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Modern agriculture has revolutionised the planet’s capacity to support humans, yet has simultaneously had a greater negative impact on biodiversity than any other human activity. Balancing the demand for food with the conservation of biodiversity is one of the most pressing issues of our time. Biodiversity-friendly farming (‘land sharing’), or alternatively, separation of conservation and production activities (‘land sparing’), are proposed as two strategies for mediating the trade-off between agriculture and biodiversity. However, there is much debate regarding the efficacy of each strategy, as this trade-off has typically been addressed by short term studies at fine spatial scales. These studies ignore processes that are relevant to biodiversity at larger scales, such as meta-population dynamics and landscape connectivity. Therefore, to better understand species response to agricultural land-use and provide evidence to underpin the planning of better production landscapes, we need to determine the merits of each strategy at larger scales. In South Africa, a remarkable citizen science project - the South African Bird Atlas Project 2 (SABAP2) – collates an extensive dataset describing the occurrence of birds at a 5-min by 5-min grid cell resolution. We use these data, along with fine-resolution data on agricultural land-use, to determine which strategy optimises the agriculture-biodiversity trade-off in a southern African context, and at a spatial scale never considered before. To empirically test this trade-off, we model bird species population density, derived for each 5-min grid cell by Royle-Nicols single-species occupancy modelling, against both the amount and configuration of different types of agricultural production in the same 5-min grid cell. In using both production amount and configuration, we can show not only how species population densities react to changes in yield, but also describe the production landscape patterns most conducive to conservation. Furthermore, the extent of both the SABAP2 and land-cover datasets allows us to test this trade-off across multiple regions to determine if bird populations respond in a consistent way and whether results can be extrapolated to other landscapes. We tested the land sparing/sharing trade-off for 281 bird species across three different biomes in South Africa. Overall, a higher proportion of species are classified as losers, and would benefit from land sparing. However, this proportion of loser-sparers is not consistent and varies across biomes and the different types of agricultural production. This is most likely because of differences in the intensity of agricultural land-use and the interactions between the differing types of natural vegetation and agriculture. Interestingly, we observe a higher number of species that benefit from agriculture than anticipated, suggesting that agriculture is a legitimate resource for certain bird species. Our results support those seen at smaller scales and across vastly different agricultural systems, that land sparing benefits the most species. However, our analysis suggests that land sparing needs to be implemented at spatial scales much larger than previously considered. Species persistence in agricultural landscapes will require the conservation of large tracts of land, and is an important consideration in developing countries, which are undergoing rapid agricultural development.

Keywords: agriculture, birds, land sharing, land sparing

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Authors: Sudeshna Chandra, Christian Gäbler, Christian Schliebe, Heinrich Lang

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Highly branched dendrimers provide structural homogeneity, controlled composition, comparable size to biomolecules, internal porosity and multiple functional groups for conjugating reactions. Electro-active dendrimers containing multiple redox units have generated great interest in their use as electrode modifiers for development of biosensors. The electron transfer between the redox-active dendrimers and the biomolecules play a key role in developing a biosensor. Ferrocenes have multiple and electrochemically equivalent redox units that can act as electron “pool” in a system. The ferrocenyl-terminated polyamidoamine dendrimer is capable of transferring multiple numbers of electrons under the same applied potential. Therefore, they can be used for dual purposes: one in building a film over the electrode for immunosensors and the other for immobilizing biomolecules for sensing. Electrochemical immunosensor, thus developed, exhibit fast and sensitive analysis, inexpensive and involve no prior sample pre-treatment. Electrochemical amperometric immunosensors are even more promising because they can achieve a very low detection limit with high sensitivity. Detection of the cancer biomarkers at an early stage can provide crucial information for foundational research of life science, clinical diagnosis and prevention of disease. Elevated concentration of biomarkers in body fluid is an early indication of some type of cancerous disease and among all the biomarkers, IgG is the most common and extensively used clinical cancer biomarkers. We present an IgG (=immunoglobulin) electrochemical immunosensor using a newly synthesized redox-active ferrocenyl dendrimer of generation 2 (G2Fc) as glassy carbon electrode material for immobilizing the antibody. The electrochemical performance of the modified electrodes was assessed in both aqueous and non-aqueous media using varying scan rates to elucidate the reaction mechanism. The potential shift was found to be higher in an aqueous electrolyte due to presence of more H-bond which reduced the electrostatic attraction within the amido groups of the dendrimers. The cyclic voltammetric studies of the G2Fc-modified GCE in 0.1 M PBS solution of pH 7.2 showed a pair of well-defined redox peaks. The peak current decreased significantly with the immobilization of the anti-goat IgG. After the immunosensor is blocked with BSA, a further decrease in the peak current was observed due to the attachment of the protein BSA to the immunosensor. A significant decrease in the current signal of the BSA/anti-IgG/G2Fc/GCE was observed upon immobilizing IgG which may be due to the formation of immune-conjugates that blocks the tunneling of mass and electron transfer. The current signal was found to be directly related to the amount of IgG captured on the electrode surface. With increase in the concentration of IgG, there is a formation of an increasing amount of immune-conjugates that decreased the peak current. The incubation time and concentration of the antibody was optimized for better analytical performance of the immunosensor. The developed amperometric immunosensor is sensitive to IgG concentration as low as 2 ng/mL. Tailoring of redox-active dendrimers provides enhanced electroactivity to the system and enlarges the sensor surface for binding the antibodies. It may be assumed that both electron transfer and diffusion contribute to the signal transformation between the dendrimers and the antibody.

Keywords: ferrocenyl dendrimers, electrochemical immunosensors, immunoglobulin, amperometry

Procedia PDF Downloads 338

Authors: Vera G. Dianova, Lori P. Montross, Charles M. Burke

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In the digital age, the widespread and frequently excessive use of mobile phones amongst university students is recognized as a significant distractor which interferes with their ability to enter a deep state of concentration during studies and diminishes their prospects of experiencing the enjoyable and instrumental state of flow, as defined and described by psychologist M. Csikszentmihalyi. This study has targeted 50 university students with the aim of teaching them to cultivate their ability to engage in deep work and to attain the state of flow, fostering more effective and enjoyable learning experiences. Prior to the start of the intervention, all participating students completed a comprehensive survey based on a variety of validated scales assessing their inclination toward lifelong learning, frequency of flow experiences during study, frustration tolerance, sense of agency, as well as their love of learning and daily time devoted to non-academic mobile phone activities. Several days after this initial assessment, students received a 90-minute lecture on the principles of flow and deep work, accompanied by a critical discourse on the detrimental effects of excessive mobile phone usage. They were encouraged to practice deep work and strive for frequent flow states throughout the semester. Subsequently, students submitted weekly surveys, including the 10-item CORE Dispositional Flow Scale, a 3-item agency scale and furthermore disclosed their average daily hours spent on non-academic mobile phone usage. As a final step, at the end of the semester students engaged in reflective report writing, sharing their experiences and evaluating the intervention's effectiveness. They considered alterations in their love of learning, reflected on the implications of their mobile phone usage, contemplated improvements in their tolerance for boredom and perseverance in complex tasks, and pondered the concept of lifelong learning. Additionally, students assessed whether they actively took steps towards managing their recreational phone usage and towards improving their commitment to becoming lifelong learners. Employing a mixed-methods approach our study offers insights into the dynamics of concentration, flow, mobile phone usage and attitudes towards learning among undergraduate and graduate university students. The findings of this study aim to promote profound contemplation, on the part of both students and instructors, on the rapidly evolving digital-age higher education environment. In an era defined by digital and AI advancements, the ability to concentrate, to experience the state of flow, and to love learning has never been more crucial. This study underscores the significance of addressing mobile phone distractions and providing strategies for cultivating deep concentration. The insights gained can guide educators in shaping effective learning strategies for the digital age. By nurturing a love for learning and encouraging lifelong learning, educational institutions can better prepare students for a rapidly changing labor market, where adaptability and continuous learning are paramount for success in a dynamic career landscape.

Keywords: deep work, flow, higher education, lifelong learning, love of learning

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Authors: Eliana Bergamin

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This philosophical inquiry, influenced by the seminal works of Annemarie Mol and Jeannette Pols, critically examines the transformative impact of artificial intelligence (AI) on emotional caregiving practices within virtual healthcare. Rooted in the traditions of philosophy of care, philosophy of emotions, and applied philosophy, this study seeks to unravel nuanced shifts in the moral and emotional fabric of healthcare mediated by AI-powered technologies. Departing from traditional empirical studies, the approach embraces the foundational principles of care ethics and phenomenology, offering a focused exploration of the ethical and existential dimensions of AI-mediated emotional caregiving. At its core, this research addresses the introduction of AI-powered technologies mediating emotional and care practices in the healthcare sector. By drawing on Mol and Pols' insights, the study offers a focused exploration of the ethical and existential dimensions of AI-mediated emotional caregiving. Anchored in ethnographic research within a pioneering private healthcare company in the Netherlands, this critical philosophical inquiry provides a unique lens into the dynamics of AI-mediated emotional practices. The study employs in-depth, semi-structured interviews with virtual caregivers and care receivers alongside ongoing ethnographic observations spanning approximately two and a half months. Delving into the lived experiences of those at the forefront of this technological evolution, the research aims to unravel subtle shifts in the emotional and moral landscape of healthcare, critically examining the implications of AI in reshaping the philosophy of care and human connection in virtual healthcare. Inspired by Mol and Pols' relational approach, the study prioritizes the lived experiences of individuals within the virtual healthcare landscape, offering a deeper understanding of the intertwining of technology, emotions, and the philosophy of care. In the realm of philosophy of care, the research elucidates how virtual tools, particularly those driven by AI, mediate emotions such as empathy, sympathy, and compassion—the bedrock of caregiving. Focusing on emotional nuances, the study contributes to the broader discourse on the ethics of care in the context of technological mediation. In the philosophy of emotions, the investigation examines how the introduction of AI alters the phenomenology of emotional experiences in caregiving. Exploring the interplay between human emotions and machine-mediated interactions, the nuanced analysis discerns implications for both caregivers and caretakers, contributing to the evolving understanding of emotional practices in a technologically mediated healthcare environment. Within applied philosophy, the study transcends empirical observations, positioning itself as a reflective exploration of the moral implications of AI in healthcare. The findings are intended to inform ethical considerations and policy formulations, bridging the gap between technological advancements and the enduring values of caregiving. In conclusion, this focused philosophical inquiry aims to provide a foundational understanding of the evolving landscape of virtual healthcare, drawing on the works of Mol and Pols to illuminate the essence of human connection, care, and empathy amid technological advancements.

Keywords: applied philosophy, artificial intelligence, healthcare, philosophy of care, philosophy of emotions

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Authors: Efrain Rodriguez, Cristhian Riano, Alberto Alvares

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In recent years, robots manipulators with parallel architectures are used in additive manufacturing processes – 3D printing. These robots have advantages such as speed and lightness that make them suitable to help with the efficiency and productivity of these processes. Consequently, the interest for the development of parallel robots for additive manufacturing applications has increased. This article deals with the conceptual design and dimensional synthesis of the linear delta robot for additive manufacturing. Firstly, a methodology based on structured processes for the development of products through the phases of informational design, conceptual design and detailed design is adopted: a) In the informational design phase the Mudge diagram and the QFD matrix are used to aid a set of technical requirements, to define the form, functions and features of the robot. b) In the conceptual design phase, the functional modeling of the system through of an IDEF0 diagram is performed, and the solution principles for the requirements are formulated using a morphological matrix. This phase includes the description of the mechanical, electro-electronic and computational subsystems that constitute the general architecture of the robot. c) In the detailed design phase, a digital model of the robot is drawn on CAD software. A list of commercial and manufactured parts is detailed. Tolerances and adjustments are defined for some parts of the robot structure. The necessary manufacturing processes and tools are also listed, including: milling, turning and 3D printing. Secondly, a dimensional synthesis method applied on design of the linear delta robot is presented. One of the most important key factors in the design of a parallel robot is the useful workspace, which strongly depends on the joint space, the dimensions of the mechanism bodies and the possible interferences between these bodies. The objective function is based on the verification of the kinematic model for a prescribed cylindrical workspace, considering geometric constraints that possibly lead to singularities of the mechanism. The aim is to determine the minimum dimensional parameters of the mechanism bodies for the proposed workspace. A method based on genetic algorithms was used to solve this problem. The method uses a cloud of points with the cylindrical shape of the workspace and checks the kinematic model for each of the points within the cloud. The evolution of the population (point cloud) provides the optimal parameters for the design of the delta robot. The development process of the linear delta robot with optimal dimensions for additive manufacture is presented. The dimensional synthesis enabled to design the mechanism of the delta robot in function of the prescribed workspace. Finally, the implementation of the robotic platform developed based on a linear delta robot in an additive manufacturing application using the Fused Deposition Modeling (FDM) technique is presented.

Keywords: additive manufacturing, delta parallel robot, dimensional synthesis, genetic algorithms

Procedia PDF Downloads 190

Authors: Margherita Tufarelli, Leonardo Giliberti, Elena Pucci

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The fashion industry's interest in virtuality is linked, on the one hand, to the emotional and immersive possibilities of digital resources and the resulting languages and, on the other, to the greater efficiency that can be achieved throughout the value chain. The interaction between digital innovation and deep-rooted manufacturing traditions today translates into a paradigm shift for the entire fashion industry where, for example, the traditional values of industrial secrecy and know-how give way to experimentation in an open as well as participatory way, and the complete emancipation of virtual reality from actual 'reality'. The contribution aims to investigate the theme of digitisation in the Italian fashion industry, analysing its opportunities and the criticalities that have hindered its diffusion. There are two reasons why the most common approach in the fashion sector is still analogue: (i) the fashion product lives in close contact with the human body, so the sensory perception of materials plays a central role in both the use and the design of the product, but current technology is not able to restore the sense of touch; (ii) volumes are obtained by stitching flat surfaces that once assembled, given the flexibility of the material, can assume almost infinite configurations. Managing the fit and styling of virtual garments involves a wide range of factors, including mechanical simulation, collision detection, and user interface techniques for garment creation. After briefly reviewing some of the salient historical milestones in the resolution of problems related to the digital simulation of deformable materials and the user interface for the procedures for the realisation of the clothing system, the paper will describe the operation and possibilities offered today by the latest generation of specialised software. Parametric avatars and digital sartorial approach; drawing tools optimised for pattern making; materials both from the point of view of simulated physical behaviour and of aesthetic performance, tools for checking wearability, renderings, but also tools and procedures useful to companies both for dialogue with prototyping software and machinery and for managing the archive and the variants to be made. The article demonstrates how developments in technology and digital procedures now make it possible to intervene in different stages of design in the fashion industry. An integrated and additive process in which the constructed 3D models are usable both in the prototyping and communication of physical products and in the possible exclusively digital uses of 3D models in the new generation of virtual spaces. Mastering such tools requires the acquisition of specific digital skills and, at the same time, traditional skills for the design of the clothing system, but the benefits are manifold and applicable to different business dimensions. We are only at the beginning of the global digital transformation: the emergence of new professional figures and design dynamics leaves room for imagination, but in addition to applying digital tools to traditional procedures, traditional fashion know-how needs to be transferred into emerging digital practices to ensure the continuity of the technical-cultural heritage beyond the transformation.

Keywords: digital fashion, digital technology and couture, digital fashion communication, 3D garment simulation

Procedia PDF Downloads 74

Authors: Momoka Sunohara, Ashley J. Lemieux, Esther Yakobov, Andrew G. Ryder, Tomas Jurcik

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Immigration brings changes in many aspects of an individual's life, from social support dynamics, to housing and language, as well as difficulties with regards to discrimination, trauma, and loss. Past research has mostly emphasized individual differences in mental health and has neglected the impact of social-ecological context, such as acculturation and ethnic density. Purpose: The present study aimed to assess the relationship between variables associated with social integration such as perceived ethnic density and ways of coping, as well as psychological adjustment in a rapidly growing non-visible minority group of immigrants in Canada. Data: A small subset of an archival data from our previously published study was reanalyzed with additional variables. Data included information from 269 Russian-Speaking immigrants in Montreal, Canada. Method: Canonical correlation analysis (CCA) investigated the relationship between two sets of variables. SAS PROC CANCORR was used to conduct CCA on a set of social integration variables, including ethnic density, discrimination, social support, family functioning, and acculturation, and a set of psychological well-being variables, including distress, depression, self-esteem, and life satisfaction. In addition, canonical redundancy analysis was performed to calculate the proportion of variances of original variables explained by their own canonical variates. Results: Significance tests using Rao’s F statistics indicated that the first two canonical correlations (i.e., r1 = 0.64, r2 = 0.40) were statistically significant (p-value < 0.0001). Additionally, canonical redundancy analysis showed that the first two well-being canonical variates explained separately 62.9% and 12.8% variances of the standardized well-being variables, whereas the first two social integration canonical variates explained separately 14.7% and 16.7% variances of the standardized social integration variables. These results support the selection of the first two canonical correlations. Then, we interpreted the derived canonical variates based on their canonical structure (i.e., correlations with original variables). Two observations can be concluded. First, individuals who have adequate social support, and who, as a family, cope by acquiring social support, mobilizing others and reframing are more likely to have better self-esteem, greater life satisfaction and experience less feelings of depression or distress. Second, individuals who feel discriminated yet rate higher on a mainstream acculturation scale, and who, as a family, cope by acquiring social support, mobilizing others and using spirituality, while using less passive strategies are more likely to have better life satisfaction but also higher degree of depression. Implications: This model may serve to explain the complex interactions that exist between social and emotional adjustment and aid in facilitating the integration of individuals immigrating into new communities. The same group may experience greater depression but paradoxically improved life satisfaction associated with their coping process. Such findings need to be placed in the context of Russian cultural values. For instance, some Russian-speakers may value the expression of negative emotions with significant others during the integration process; this in turn may make negative emotions more salient, but also facilitate a greater sense of family and community connection, as well as life satisfaction.

Keywords: acculturation, ethnic density, mental health, Russian-speaking

Procedia PDF Downloads 483

Authors: Bhargavi G. Iyer, Ojaswi Bhagat

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It is often noted that the value of a novel idea lies in its successful implementation. However, successful implementation requires the nurturing and encouragement of innovation. Nascent competitors are a true representation of innovation in any given industry. A nascent competitor is an entity whose prospective innovation poses a future threat to an incumbent dominant competitor. While a nascent competitor benefits in several ways, it is also exposed significantly and is at greater risk of facing the brunt of exclusionary practises and abusive conduct by dominant incumbent competitors in the industry. This research paper aims to explore the risks and threats faced by nascent competitors and analyse the benefits they accrue as well as the advantages they proffer to the economy; through an analytical, critical study. In such competitive market environments, a rise of the acquisitions of nascent competitors by the incumbent dominants is observed. Therefore, this paper will examine the dynamics of nascent acquisition. Further, this paper hopes to specifically delve into the role of antitrust bodies in regulating nascent acquisition. This paper also aspires to deal with the question how to distinguish harmful from harmless acquisitions in order to facilitate ideal enforcement practice. This paper proposes mechanisms of scrutiny in order to ensure healthy market practises and efficient merger control in the context of nascent acquisitions. Taking into account the scope and nature of the topic, as well as the resources available and accessible, a combination of the methods of doctrinal research and analytical research were employed, utilising secondary sources in order to assess and analyse the subject of research. While legally evaluating the Killer Acquisition theory and the Nascent Potential Acquisition theory, this paper seeks to critically survey the precedents and instances of nascent acquisitions. In addition to affording a compendious account of the legislative framework and regulatory mechanisms in the United States, the United Kingdom, and the European Union; it hopes to suggest an internationally practicable legal foundation for domestic legislation and enforcement to adopt. This paper hopes to appreciate the complexities and uncertainties with respect to nascent acquisitions and attempts to suggest viable and plausible policy measures in antitrust law. It additionally attempts to examine the effects of such nascent acquisitions upon the consumer and the market economy. This paper weighs the argument of shifting the evidentiary burden on to the merging parties in order to improve merger control and regulation and expounds on its discovery of the strengths and weaknesses of the approach. It is posited that an effective combination of factual, legal, and economic analysis of both the acquired and acquiring companies possesses the potential to improve ex post and ex ante merger review outcomes involving nascent companies; thus, preventing anti-competitive practises. This paper concludes with an analysis of the possibility and feasibility of industry-specific identification of anti-competitive nascent acquisitions and implementation of measures accordingly.

Keywords: acquisition, antitrust law, exclusionary practises merger control, nascent competitor

Procedia PDF Downloads 163

Authors: Simone Cinquemani, Lorenzo Mantovani, Aleksander Dabek

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New technologies in agriculture are opening new challenges and new opportunities. Among these, certainly, robotics, vision, and artificial intelligence are the ones that will make a significant leap, compared to traditional agricultural techniques, possible. In particular, the indoor farming sector will be the one that will benefit the most from these solutions. Vertical farming is a new field of research where mechanical engineering can bring knowledge and know-how to transform a highly labor-based business into a fully autonomous system. The aim of the research is to develop a multi-purpose, modular, and perfectly integrated platform for crop production in indoor vertical farming. Activities will be based both on hardware development such as automatic tools to perform different activities on soil and plants, as well as research to introduce an extensive use of monitoring techniques based on machine learning algorithms. This paper presents the preliminary results of a research project of a vertical farm living lab designed to (i) develop and test vertical farming cultivation practices, (ii) introduce a very high degree of mechanization and automation that makes all processes replicable, fully measurable, standardized and automated, (iii) develop a coordinated control and management environment for autonomous multiplatform or tele-operated robots in environments with the aim of carrying out complex tasks in the presence of environmental and cultivation constraints, (iv) integrate AI-based algorithms as decision support system to improve quality production. The coordinated management of multiplatform systems still presents innumerable challenges that require a strongly multidisciplinary approach right from the design, development, and implementation phases. The methodology is based on (i) the development of models capable of describing the dynamics of the various platforms and their interactions, (ii) the integrated design of mechatronic systems able to respond to the needs of the context and to exploit the strength characteristics highlighted by the models, (iii) implementation and experimental tests performed to test the real effectiveness of the systems created, evaluate any weaknesses so as to proceed with a targeted development. To these aims, a fully automated laboratory for growing plants in vertical farming has been developed and tested. The living lab makes extensive use of sensors to determine the overall state of the structure, crops, and systems used. The possibility of having specific measurements for each element involved in the cultivation process makes it possible to evaluate the effects of each variable of interest and allows for the creation of a robust model of the system as a whole. The automation of the laboratory is completed with the use of robots to carry out all the necessary operations, from sowing to handling to harvesting. These systems work synergistically thanks to the knowledge of detailed models developed based on the information collected, which allows for deepening the knowledge of these types of crops and guarantees the possibility of tracing every action performed on each single plant. To this end, artificial intelligence algorithms have been developed to allow synergistic operation of all systems.

Keywords: automation, vertical farming, robot, artificial intelligence, vision, control

Procedia PDF Downloads 45

Authors: U.K. Sarkar, G. Karnatak, P. Mishal, Lianthuamluaia, S. Kumari, S.K. Das, B.K. Das

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Inland open water fisheries provide food, income, livelihood and nutritional security to millions of fishers across the globe. However, the open water ecosystem and fisheries are threatened due to climate change and anthropogenic pressures, which are more visible in the recent six decades, making the resources vulnerable. Understanding the interaction between meteorological parameters and inland fisheries is imperative to develop mitigation and adaptation strategies. As per IPCC 5th assessment report, the earth is warming at a faster rate in recent decades. Global mean surface temperature (GMST) for the decade 2006–2015 (0.87°C) was 6 times higher than the average over the 1850–1900 period. The direct and indirect impacts of climatic parameters on the ecology of fisheries ecosystem have a great bearing on fisheries due to alterations in fish physiology. The impact of meteorological factors on ecosystem health and fish food organisms brings about changes in fish diversity, assemblage, reproduction and natural recruitment. India’s average temperature has risen by around 0.7°C during 1901–2018. The studies show that the mean air temperature in the Ganga basin has increased in the range of 0.20 - 0.47 °C and annual rainfall decreased in the range of 257-580 mm during the last three decades. The studies clearly indicate visible impacts of climatic and environmental factors on inland open water fisheries. Besides, a significant reduction in-depth and area (37.20–57.68% reduction), diversity of natural indigenous fish fauna (ranging from 22.85 to 54%) in wetlands and progression of trophic state from mesotrophic to eutrophic were recorded. In this communication, different applications of biometeorology in inland fisheries management with special reference to the assessment of ecosystem and species vulnerability to climatic variability and change have been discussed. Further, the paper discusses the impact of climate anomaly and extreme climatic events on inland fisheries and emphasizes novel modeling approaches for understanding the impact of climatic and environmental factors on reproductive phenology for identification of climate-sensitive/resilient fish species for the adoption of climate-smart fisheries in the future. Adaptation and mitigation strategies to enhance fish production and the role of culture-based fisheries and enclosure culture in converting sequestered carbon into blue carbon have also been discussed. In general, the type and direction of influence of meteorological parameters on fish biology in open water fisheries ecosystems are not adequately understood. The optimum range of meteorological parameters for sustaining inland open water fisheries is yet to be established. Therefore, the application of biometeorology in inland fisheries offers ample scope for understanding the dynamics in changing climate, which would help to develop a database on such least, addressed research frontier area. This would further help to project fisheries scenarios in changing climate regimes and develop adaptation and mitigation strategies to cope up with adverse meteorological factors to sustain fisheries and to conserve aquatic ecosystem and biodiversity.

Keywords: biometeorology, inland fisheries, aquatic ecosystem, modeling, India

Procedia PDF Downloads 196

Authors: Lucas M. Furlan, Cesar A. Moreira, Jepherson F. Sales, Guilherme T. Bueno, Manuel E. Ferreira, Carla V. S. Coelho, Vania Rosolen

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Located in the western part of the State of Minas Gerais, Brazil, the study area consists of a savanna environment, represented by sedimentary plateau and a soil cover composed by lateritic and hydromorphic soils - in the latter, occurring the deferruginization and concentration of high-alumina clays, exploited as refractory material. In the hydromorphic topographic depressions (wetlands) the hydropedogical relationships are little known, but it is observed that in times of rainfall, the depressed region behaves like a natural seasonal reservoir - which suggests that the wetlands on the surface of the plateau are places of recharge of the aquifer. The aquifer recharge areas are extremely important for the sustainable social, economic and environmental development of societies. The understanding of hydrodynamics in relation to the functioning of the ferruginous and hydromorphic lateritic soils system in the savanna environment is a subject rarely explored in the literature, especially its understanding through the joint application of geoprocessing by UAV (Unmanned Aerial Vehicle) and electrical tomography. The objective of this work is to understand the hydrogeological dynamics in a wetland (with an area of 426.064 m²), in the Brazilian savanna,as well as the understanding of the subsurface architecture of hydromorphic depressions in relation to the recharge of aquifers. The wetland was compartmentalized in three different regions, according to the geoprocessing. Hydraulic conductivity studies were performed in each of these three portions. Electrical tomography was performed on 9 lines of 80 meters in length and spaced 10 meters apart (direction N45), and a line with 80 meters perpendicular to all others. With the data, it was possible to generate a 3D cube. The integrated analysis showed that the area behaves like a natural seasonal reservoir in the months of greater precipitation (December – 289mm; January – 277,9mm; February – 213,2mm), because the hydraulic conductivity is very low in all areas. In the aerial images, geotag correction of the images was performed, that is, the correction of the coordinates of the images by means of the corrected coordinates of the Positioning by Precision Point of the Brazilian Institute of Geography and Statistics (IBGE-PPP). Later, the orthomosaic and the digital surface model (DSM) were generated, which with specific geoprocessing generated the volume of water that the wetland can contain - 780,922m³ in total, 265,205m³ in the region with intermediate flooding and 49,140m³ in the central region, where a greater accumulation of water was observed. Through the electrical tomography it was possible to identify that up to the depth of 6 meters the water infiltrates vertically in the central region. From the 8 meters depth, the water encounters a more resistive layer and the infiltration begins to occur horizontally - tending to concentrate the recharge of the aquifer to the northeast and southwest of the wetland. The hydrodynamics of the area is complex and has many challenges in its understanding. The next step is to relate hydrodynamics to the evolution of the landscape, with the enrichment of high-alumina clays, and to propose a management model for the seasonal reservoir.

Keywords: electrical tomography, hydropedology, unmanned aerial vehicle, water resources management

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Authors: Emma Pope, Demos Parapanos

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Rural tourism has become more obvious and prevalent, with tourists’ increasingly seeking authentic experiences. This movement accelerated post-Covid, putting destinations in danger of reaching levels of saturation called ‘overtourism’. Whereas the phenomenon of overtourism has been frequently discussed in the urban context by academics and practitioners over recent years, it has hardly been referred to in the context of rural tourism, where perhaps it is even more difficult to manage. Rural tourism was historically considered small-scale, marked by its traditional character and by having little impact on nature and rural society. The increasing number of rural areas experiencing overtourism, however, demonstrates the need for new approaches, especially as the impacts and enablers of overtourism are context specific. Cumbria, with approximately 47 million visitors each year, and 23,000 operational enterprises, is one of these rural areas experiencing overtourism in the UK. Using the county of Cumbria as an example, this paper aims to explore better planning and management in rural destinations by clustering the area into rural and ‘urban-rural’ tourism zones. To achieve the aim, this study uses secondary data from a variety of sources to identify variables relating to visitor economy development and demand. These data include census data relating to population and employment, tourism industry-specific data including tourism revenue, visitor activities, and accommodation stock, and big data sources such as Trip Advisor and All Trails. The combination of these data sources provides a breadth of tourism-related variables. The subsequent analysis of this data draws upon various validated models. For example, tourism and hospitality employment density, territorial tourism pressure, and accommodation density. In addition to these statistical calculations, other data are utilized to further understand the context of these zones, for example, tourist services, attractions, and activities. The data was imported into ARCGIS where the density of the different variables is visualized on maps. This study aims to provide an understanding of the geographical context of visitor economy development and tourist behavior in rural areas. The findings contribute to an understanding of the spatial dynamics of tourism within the region of Cumbria through the creation of thematized maps. Different zones of tourism industry clusters are identified, which include elements relating to attractions, enterprises, infrastructure, tourism employment and economic impact. These maps visualize hot and cold spots relating to a variety of tourism contexts. It is believed that the strategy used to provide a visual overview of tourism development and demand in Cumbria could provide a strategic tool for rural areas to better plan marketing opportunities and avoid overtourism. These findings can inform future sustainability policy and destination management strategies within the areas through an understanding of the processes behind the emergence of both hot and cold spots. It may mean that attract and disperse needs to be reviewed in terms of a strategic option. In other words, to use sector or zonal policies for the individual hot or cold areas with transitional zones dependent upon local economic, social and environmental factors.

Keywords: overtourism, rural tourism, sustainable tourism, tourism planning, tourism zones

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Authors: Guilherme Oliveira

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The assimilation of images and their potential symbolism into lived experiences is inherent. It is through this exercise of recognition via imagistic records that the questioning of the origins of a constant narrative stimulated by the media arises. The construction of the "Man" archetype and the reflections of active masculine imagery in the 21st century, when conveyed through media channels, could potentially have detrimental effects. Addressing this systematic behavioral chronology of virile cisgender, permeated imagistically through these means, involves exploring potential resolutions. Thus, an investigation process is initiated into the potential representation of the 'hero' in this media emulation through idols contextualized in the political sphere, with the purpose of elucidating the processes of simulation and emulation of narratives based on mythical, historical, and sacred accounts. In this process of sharing, the narratives contained in the imagistic structuring offered by information dissemination channels seek validation through a process of public acceptance. To achieve this consensus, a visual set adorned with mythological and sacred symbolisms adapted to the intended environment is promoted, thus utilizing sociocultural characteristics in favor of political marketing. Visual recognition, therefore, becomes a direct reflection of a cultural heritage acquired through lived human experience, stimulated by continuous representations throughout history. Echoes of imagery and narratives undergo a constant process of resignification of their concepts, sharpened by their premises, and adapted to the environment in which they seek to establish themselves. Political figures analyzed in this article employ the practice of taking possession of symbolisms, mythological stories, and heroisms and adapt their visual construction through a continuous praxis of emulation. Thus, they utilize iconic mythological narratives to gain credibility through belief. Utilizing iconic mythological narratives for credibility through belief, the idol becomes the very act of release of trauma, offering believers liberation from preconceived concepts and allowing for the attribution of new meanings. To dissolve this issue and highlight the subjectivities within the intention of the image, a linguistic, semiotic, and anthropological methodology is created. Linguistics uses expressions like 'Blaming the Image' to create a mechanism of expressive action in questioning why to blame a construction or visual composition and thus seek answers in the first act. Semiotics and anthropology develop an imagistic atlas of graphic analysis, seeking to make connections, comparisons, and relations between modern and sacred/mystical narratives, emphasizing the different subjective layers of embedded symbolism. Thus, it constitutes a performative act of disarming the image. It creates a disenchantment of the superficial gaze under the constant reproduction of visual content stimulated by virtual networks, enabling a discussion about the acceptance of caricatures characterized by past fables.

Keywords: image, heroic narrative, media heroism, virile politics, political, myth, sacred performance, visual mythmaking, characterization dynamics

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Authors: Francesca Crivellari, Nicholas Mavrogiannis, Zachary Gagnon

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Portable diagnostic methods have become increasingly important for a number of different purposes: point-of-care screening in developing nations, environmental contamination studies, bio/chemical warfare agent detection, and end-user use for commercial health monitoring. The cheapest and most portable methods currently available are paper-based – lateral flow and dipstick methods are widely available in drug stores for use in pregnancy detection and blood glucose monitoring. These tests are successful because they are cheap to produce, easy to use, and require minimally invasive sampling. While adequate for their intended uses, in the realm of blood-borne pathogens and numerous cancers, these paper-based methods become unreliable, as they lack the nM/pM sensitivity currently achieved by clinical diagnostic methods. Clinical diagnostics, however, utilize techniques involving surface plasmon resonance (SPR) and enzyme-linked immunosorbent assays (ELISAs), which are expensive and unfeasible in terms of portability. To develop a better, competitive biosensor, we must reduce the cost of one, or increase the sensitivity of the other. Electric fields are commonly utilized in microfluidic devices to manipulate particles, biomolecules, and cells. Applications in this area, however, are primarily limited to interfaces formed between immiscible interfaces. Miscible, liquid-liquid interfaces are common in microfluidic devices, and are easily reproduced with simple geometries. Here, we demonstrate the use of electrical fields at liquid-liquid electrical interfaces, known as fluidic dielectrophoresis, (fDEP) for biodetection in a microfluidic device. In this work, we apply an AC electric field across concurrent laminar streams with differing conductivities and permittivities to polarize the interface and induce a discernible, near-immediate, frequency-dependent interfacial tilt. We design this aqueous electrical interface, which becomes the biosensing “substrate,” to be intelligent – it “moves” only when a target of interest is present. This motion requires neither labels nor expensive electrical equipment, so the biosensor is inexpensive and portable, yet still capable of sensitive detection. Nanoparticles, due to their high surface-area-to-volume ratio, are often incorporated to enhance detection capabilities of schemes like SPR and fluorimetric assays. Most studies currently investigate binding at an immobilized solid-liquid or solid-gas interface, where particles are adsorbed onto a planar surface, functionalized with a receptor to create a reactive substrate, and subsequently flushed with a fluid or gas with the relevant analyte. These typically involve many preparation and rinsing steps, and are susceptible to surface fouling. Our microfluidic device is continuously flowing and renewing the “substrate,” and is thus not subject to fouling. In this work, we demonstrate the ability to electrokinetically detect biomolecules binding to functionalized nanoparticles at liquid-liquid interfaces using fDEP. In biotin-streptavidin experiments, we report binding detection limits on the order of 1-10 pM, without amplifying signals or concentrating samples. We also demonstrate the ability to detect this interfacial motion, and thus the presence of binding, using impedance spectroscopy, allowing this scheme to become non-optical, in addition to being label-free.

Keywords: biodetection, dielectrophoresis, microfluidics, nanoparticles

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Authors: Laverne Seales

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When most people think of Panama, they immediately think of the Canal; however, the construction and the people who made it possible are often omitted and seldom acknowledged. The reality is that the construction of this waterway was achieved through forced migration and discriminatory practices toward people of African descent, specifically black people from the Caribbean. From the colonial period to the opening and subsequent operation of the Panama Canal by the United States, this paper goes through the rich layers of Panamanian history to examine the life of Afro-Caribbeans and their descendants in Panama. It also considers the role of the United States in Panama; it explores how the United States in Panama forged a racially complex country that made the integration of Afro-Caribbeans and their descendants difficult. After laying a historical foundation, the exploration of Afro-Caribbean people and Panamanians of Afro-Caribbean descent are analyzed through Afro-Panamanian writer Carlos Guillermo ‘Cubena’ Wilson's novels, short stories, and poetry. This study focuses on how Cubena addresses racism, discrimination, inequality, and social justice issues towards Afro-Caribbeans and their descendants who traveled to Panama to construct the Canal. Content analysis methodology can yield several significant contributions, and analyzing Carlos Guillermo Wilson's literature under this framework allows us to consider social commentary and critique of Panamanian society. It identifies the social issues and concerns of Afro-Caribbeans and people of Afro-Caribbean descent, such as inequality, corruption, racism, political oppression, and cultural identity. Analysis methodology allows us to explore how Cubena's literature engages with questions of cultural identity and belonging in Panamanian society. By examining themes related to race, ethnicity, language, and heritage, this research uncovers the complexities of Panamanian cultural identity, allowing us to interrogate power dynamics and social hierarchies in Panamanian society. Analyzing the portrayal of different social groups, institutions, and power structures helps uncover how power is wielded, contested, and resisted; Cubena's fictional world allows us to see how it functions in Panama. Content analysis methodology also provides for critiquing political systems and governance in Panama. By examining the representation and presentation of political figures, institutions, and events in Cubena's literature, we uncover his commentary on corruption, authoritarianism, governance, and the role of the United States in Panama. Content analysis highlights how Wilson's literature amplifies the voices and experiences of marginalized individuals and communities in Panamanian society. By centering the narratives of Afro-Panamanians and other marginalized groups, this researcher uncovers Cubena's commitment to social justice and inclusion in his writing and helps the reader engage with historical narratives and collective memory in Panama. Overall, analyzing Carlos Guillermo ‘Cubena’ Wilson's literature as a platform for social commentary and critique of Panamanian society using content analysis methodology provides valuable insights into the cultural, social, and political dimensions of Afro-Panamanians during and after the construction of the Panama Canal.

Keywords: Afro-Caribbean, Panama Canal, race, Afro-Panamanian, identity, history

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Authors: Dan Kanmegne

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Africa will become the most populated continent by the end of the century, with around 4 billion inhabitants. Food security and climate changes will become continental issues since agricultural practices depend on climate but also contribute to global emissions and land degradation. Agroforestry has been identified as a cost-efficient and reliable strategy to address these two issues. It is defined as the integrated management of trees and crops/animals in the same land unit. Agroforestry provides benefits in terms of goods (fruits, medicine, wood, etc.) and services (windbreaks, fertility, etc.), and is acknowledged to have a great potential for carbon sequestration; therefore it can be integrated into reduction mechanisms of carbon emissions. Particularly in sub-Saharan Africa, the constraint stands in the lack of information about both areas under agroforestry and the characterization (composition, structure, and management) of each agroforestry system at the country level. This study describes and quantifies “what is where?”, earliest to the quantification of carbon stock in different systems. Remote sensing (RS) is the most efficient approach to map such a dynamic technology as agroforestry since it gives relatively adequate and consistent information over a large area at nearly no cost. RS data fulfill the good practice guidelines of the Intergovernmental Panel On Climate Change (IPCC) that is to be used in carbon estimation. Satellite data are getting more and more accessible, and the archives are growing exponentially. To retrieve useful information to support decision-making out of this large amount of data, satellite data needs to be organized so to ensure fast processing, quick accessibility, and ease of use. A new solution is a data cube, which can be understood as a multi-dimensional stack (space, time, data type) of spatially aligned pixels and used for efficient access and analysis. A data cube for Burkina Faso has been set up from the cooperation project between the international service provider WASCAL and Germany, which provides an accessible exploitation architecture of multi-temporal satellite data. The aim of this study is to map and characterize agroforestry systems using the Burkina Faso earth observation data cube. The approach in its initial stage is based on an unsupervised image classification of a normalized difference vegetation index (NDVI) time series from 2010 to 2018, to stratify the country based on the vegetation. Fifteen strata were identified, and four samples per location were randomly assigned to define the sampling units. For safety reasons, the northern part will not be part of the fieldwork. A total of 52 locations will be visited by the end of the dry season in February-March 2020. The field campaigns will consist of identifying and describing different agroforestry systems and qualitative interviews. A multi-temporal supervised image classification will be done with a random forest algorithm, and the field data will be used for both training the algorithm and accuracy assessment. The expected outputs are (i) map(s) of agroforestry dynamics, (ii) characteristics of different systems (main species, management, area, etc.); (iii) assessment report of Burkina Faso data cube.

Keywords: agroforestry systems, Burkina Faso, earth observation data cube, multi-temporal image classification

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Authors: T. Ul Rehman, S. Agnello, F. M. Gelardi, M. M. Calvino, G. Lazzara, G. Buscarino, M. Cannas

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Metal-Organic Frameworks (MOFs) have emerged as promising candidates for detecting metal ions owing to their large surface area, customizable porosity, and diverse functionalities. In recent years, there has been a surge in research focused on MOFs with luminescent properties. These frameworks are constructed through coordinated bonding between metal ions and multi-dentate ligands, resulting in inherent fluorescent structures. Their luminescent behavior is influenced by factors like structural composition, surface morphology, pore volume, and interactions with target analytes, particularly metal ions. MOFs exhibit various sensing mechanisms, including photo-induced electron transfer (PET) and charge transfer processes such as ligand-to-metal (LMCT) and metal-to-ligand (MLCT) transitions. Among these, MIL-53(Al) stands out due to its flexibility, stability, and specific affinity towards certain metal ions, making it a promising platform for selective metal ion sensing. This study investigates the structural, thermal, and luminescent properties of MIL-53(Al) metal-organic framework (MOF) upon Fe3+ cation exchange. Two separate sets of samples were prepared to activate the MOF powder at different temperatures. The first set of samples, referred to as MIL-53(Al), activated (120°C), was prepared by activating the raw powder in a glass tube at 120°C for 12 hours and then sealing it. The second set of samples, referred to as MIL-53(Al), activated (300°C), was prepared by activating the MIL-53(Al) powder in a glass tube at 300°C for 70 hours. Additionally, 25 mg of MIL-53(Al) powder was dispersed in 5 mL of Fe3+ solution at various concentrations (0.1-100 mM) for the cation exchange experiment. The suspension was centrifuged for five minutes at 10,000 rpm to extract MIL-53(Al) powder. After three rounds of washing with ultrapure water, MIL-53(Al) powder was heated at 120°C for 12 hours. For PXRD and TGA analyses, a sample of the obtained MIL-53(Al) was used. We also activated the cation-exchanged samples for time-resolved photoluminescence (TRPL) measurements at two distinct temperatures (120 and 300°C) for comparative analysis. Powder X-ray diffraction patterns reveal amorphization in samples with higher Fe3+ concentrations, attributed to alterations in coordination environments and ion exchange dynamics. Thermal decomposition analysis shows reduced weight loss in Fe3+-exchanged MOFs, indicating enhanced stability due to stronger metal-ligand bonds and altered decomposition pathways. Raman spectroscopy demonstrates intensity decrease, shape disruption, and frequency shifts, indicative of structural perturbations induced by cation exchange. Photoluminescence spectra exhibit ligand-based emission (π-π* or n-π*) and ligand-to-metal charge transfer (LMCT), influenced by activation temperature and Fe3+ incorporation. Quenching of luminescence intensity and shorter lifetimes upon Fe3+ exchange result from structural distortions and Fe3+ binding to organic linkers. In a nutshell, this research underscores the complex interplay between composition, structure, and properties in MOFs, offering insights into their potential for diverse applications in catalysis, gas storage, and luminescent devices.

Keywords: Fe³⁺ cation exchange, luminescent metal-organic frameworks (LMOFs), MIL-53(Al), solid-state analysis

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