Search results for: protein interaction networks

Authors: Mohammadjavad Sotoudeheian, Soroush Nematollahi

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Crohn’s disease (CD) is a chronic gastrointestinal segment inflammation encompassing immune dysregulation in a genetically susceptible individual in response to the environmental triggers and interaction between the microbiome and immune system. Uncontrolled inflammation leads to long-term complications, including fibrotic strictures and enteric fistulae. Increased production of Th1 and Th17-cell cytokines and defects in T-regulatory cells have been associated with CD. Th17-cells are essential for protection against extracellular pathogens, but their atypical activity can cause autoimmunity. Intrinsic defects in the control of programmed cell death in the mucosal T-cell compartment are strongly implicated in the pathogenesis of CD. The apoptosis defect in mucosal T-cells in CD has been endorsed as an imbalance of the Bcl-2 and the Bax. The immune system encounters foreign antigens through microbial colonization of mucosal surfaces or infections. In addition, FOSL downregulated IL-26 expression, a cytokine that marks inflammatory Th17-populations in patients suffering from CD. Furthermore, the expression of IL-23 is associated with the transcription factor primary leucine zipper transcription factor ATF-like (Batf). Batf-deficiency demonstrated the crucial role of Batf in colitis development. Batf and IL-23 mediate their effects by inducing IL-6 production. Strong association of IL-23R, Stat3, and Stat4 with IBD susceptibility point to a critical involvement of T-cells. IL-23R levels in transfer fistula were dependent on the AP-1 transcription factor JunB that additionally controlled levels of RORγt by facilitating DNA binding of Batf. T lymphocytes lacking JunB failed to induce IL-23- and Th17-mediated experimental colitis highlighting the relevance of JunB for the IL-23/ Th17 pathway. The absence of T-bet causes unrestrained Th17-cell differentiation. T-cells are central parts of immune-mediated colon fistula. Especially Th17-cells were highly prevalent in inflamed IBD tissues, as RORγt is effective in preventing colitis. Intraepithelial lymphocytes (IEL) contain unique T-cell subsets, including cells expressing RORγt. Increased activated Th17 and decreased T-regulatory cells in inflamed intestinal tissues had been seen. T-cells differentiate in response to many cytokines, including IL-1β, IL-6, IL-23, and TGF-β, into Th17-cells, a process which is critically dependent on the Batf. IL-23 promotes Th17-cell in the colon. Batf manages the generation of IL-23 induced IL-23R+ Th17-cells. Batf is necessary for TGF-β/IL-6-induced Th17-polarization. Batf-expressing T-cells are the core of T-cell-mediated colitis. The human-specific parts of three AP-1 transcription factors, FOSL1, FOSL2, and BATF, are essential during the early stages of Th17 differentiation. BATF supports the Th17 lineage. FOSL1, FOSL2, and BATF make possession of regulatory loci of genes in the Th17 lineage cascade. The AP1 transcription factor Batf is identified to control intestinal inflammation and seems to regulate pathways within lymphocytes, which could theoretically control the expression of several genes. It shows central regulatory properties over Th17-cell development and is intensely upregulated within IBD-affected tissues. Here, we demonstrated that targeting Batf in IBD appears as a therapeutic approach that reduces colitogenic T-cell activities during fistula formation while aiming to affect inflammation in the gut epithelial cells.

Keywords: immune system, Crohn’s Disease, BATF, T helper cells, Bcl, interleukin, FOSL

Procedia PDF Downloads 115

Authors: Linna Li

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The capability to move around places is doubtless very important for individuals to maintain good health and social functions. People’s activities in space and time have long been a research topic in behavioral and socio-economic studies, particularly focusing on the highly dynamic urban environment. By analyzing groups of people who share similar activity patterns, many socio-economic and socio-demographic problems and their relationships with individual behavior preferences can be revealed. Los Angeles, known for its large population, ethnic diversity, cultural mixing, and entertainment industry, faces great transportation challenges such as traffic congestion, parking difficulties, and long commuting. Understanding people’s travel behavior and movement patterns in this metropolis sheds light on potential solutions to complex problems regarding urban mobility. This project visualizes people’s trajectories in Greater Los Angeles (L.A.) Area over a period of two months using Twitter data. A Python script was used to collect georeferenced tweets within the Greater L.A. Area including Ventura, San Bernardino, Riverside, Los Angeles, and Orange counties. Information associated with tweets includes text, time, location, and user ID. Information associated with users includes name, the number of followers, etc. Both aggregated and individual activity patterns are demonstrated using various geovisualization techniques. Locations of individual Twitter users were aggregated to create a surface of activity hot spots at different time instants using kernel density estimation, which shows the dynamic flow of people’s movement throughout the metropolis in a twenty-four-hour cycle. In the 3D geovisualization interface, the z-axis indicates time that covers 24 hours, and the x-y plane shows the geographic space of the city. Any two points on the z axis can be selected for displaying activity density surface within a particular time period. In addition, daily trajectories of Twitter users were created using space-time paths that show the continuous movement of individuals throughout the day. When a personal trajectory is overlaid on top of ancillary layers including land use and road networks in 3D visualization, the vivid representation of a realistic view of the urban environment boosts situational awareness of the map reader. A comparison of the same individual’s paths on different days shows some regular patterns on weekdays for some Twitter users, but for some other users, their daily trajectories are more irregular and sporadic. This research makes contributions in two major areas: geovisualization of spatial footprints to understand travel behavior using the big data approach and dynamic representation of activity space in the Greater Los Angeles Area. Unlike traditional travel surveys, social media (e.g., Twitter) provides an inexpensive way of data collection on spatio-temporal footprints. The visualization techniques used in this project are also valuable for analyzing other spatio-temporal data in the exploratory stage, thus leading to informed decisions about generating and testing hypotheses for further investigation. The next step of this research is to separate users into different groups based on gender/ethnic origin and compare their daily trajectory patterns.

Keywords: geovisualization, human mobility pattern, Los Angeles, social media

Procedia PDF Downloads 92

Authors: June Keeling, Christina Athanasiades, Vaiva Hendrixson, Delyth Wyndham

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Recognition and education in violence, abuse, and neglect for medical and healthcare practitioners (REVAMP) is a trans-European project aiming to introduce a training programme that has been specifically developed by partners across seven European countries to meet the needs of medical and healthcare practitioners. Amalgamating the knowledge and experience of clinicians, researchers, and educators from interdisciplinary and multi-professional backgrounds, REVAMP has tackled the under-resourced and underdeveloped area of domestic violence and abuse. The team designed an online training programme to support medical and healthcare practitioners to recognise and respond appropriately to survivors of domestic violence and abuse at their point of contact with a health provider. The REVAMP partner countries include Europe: France, Lithuania, Germany, Greece, Iceland, Norway, and the UK. The training is delivered through a series of interactive online modules, adapting evidence-based pedagogical approaches to learning. Capturing and addressing the complexities of the project impacted the methodological decisions and approaches to evaluation. The challenge was to find an evaluation methodology that captured valid data across all partner languages to demonstrate the extent of the change in knowledge and understanding. Co-development by all team members was a lengthy iterative process, challenged by a lack of consistency in terminology. A mixed methods approach enabled both qualitative and quantitative data to be collected, at the start, during, and at the conclusion of the training for the purposes of evaluation. The module content and evaluation instrument were accessible in each partner country's language. Collecting both types of data provided a high-level snapshot of attainment via the quantitative dataset and an in-depth understanding of the impact of the training from the qualitative dataset. The analysis was mixed methods, with integration at multiple interfaces. The primary focus of the analysis was to support the overall project evaluation for the funding agency. A key project outcome was identifying that the trans-European approach posed several challenges. Firstly, the project partners did not share a first language or a legal or professional approach to domestic abuse and neglect. This was negotiated through complex, systematic, and iterative interaction between team members so that consensus could be achieved. Secondly, the context of the data collection in several different cultural, educational, and healthcare systems across Europe challenged the development of a robust evaluation. The participants in the pilot evaluation shared that the training was contemporary, well-designed, and of great relevance to inform practice. Initial results from the evaluation indicated that the participants were drawn from more than eight partner countries due to the online nature of the training. The primary results indicated a high level of engagement with the content and achievement through the online assessment. The main finding was that the participants perceived the impact of domestic abuse and neglect in very different ways in their individual professional contexts. Most significantly, the participants recognised the need for the training and the gap that existed previously. It is notable that a mixed-methods evaluation of a trans-European project is unusual at this scale.

Keywords: domestic violence, e-learning, health professionals, trans-European

Procedia PDF Downloads 54

Authors: Bangun F., Crevits B., Bellet T., Banet A., Boy G. A., Katili I.

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This paper seeks the incoherencies in cognitive process during an accident of Powered Two Wheelers (PTW) by understanding the factual sequences of events and causal relations for each case of accident. The principle of this approach is undertaking in-depth investigations on case per case of PTW accidents based on elaborate data acquisitions on accident sites that officially stamped in Police Crash Report (PCRs) 2012 of Medan with criteria, involved at least one PTW and resulted in serious injury and fatalities. The analysis takes into account four modules: accident chronologies, perpetrator, and victims, injury surveillance, vehicles and road infrastructures, comprising of traffic facilities, road geometry, road alignments and weather. The proposal for improvement could have provided a favorable influence on the chain of functional processes and events leading to collision. Decision Aiding Processes (DAP) assists in structuring different entities at different decisional levels, as each of these entities has its own objectives and constraints. The entities (A) are classified into 6 groups of accidents: solo PTW accidents; PTW vs. PTW; PTW vs. pedestrian; PTW vs. motor-trishaw; and PTW vs. other vehicles and consecutive crashes. The entities are also distinguished into 4 decisional levels: level of road users and street systems; operational level (crash-attended police officers or CAPO and road engineers), tactical level (Regional Traffic Police, Department of Transportation, and Department of Public Work), and strategic level (Traffic Police Headquarters (TCPHI)), parliament, Ministry of Transportation and Ministry of Public Work). These classifications will lead to conceptualization of Problem Situations (P) and Problem Formulations (I) in DAP context. The DAP concerns the sequences process of the incidents until the time the accident occurs, which can be modelled in terms of five activities of procedural rationality: identification on initial human features (IHF), investigation on proponents attributes (PrAT), on Injury Surveillance (IS), on the interaction between IHF and PrAt and IS (intercorrelation), then unravel the sequences of incidents; filtering and disclosure, which include: what needs to activate, modify or change or remove, what is new and what is priority. These can relate to the activation or modification or new establishment of law. The PrAt encompasses the problems of environmental, road infrastructure, road and traffic facilities, and road geometry. The evaluation model (MP) is generated to bridge P and I since MP is produced by the intercorrelations among IHF, PrAT and IS extracted from the PCRs 2012 of Medan. There are 7 findings of incoherences: lack of knowledge and awareness on the traffic regulations and the risks of accidents, especially when riding between 0 < x < 10 km from house, riding between 22 p.m.–05.30 a.m.; lack of engagements on procurement of IHF Data by CAPO; lack of competency of CAPO on data procurement in accident-sites; no intercorrelation among IHF and PrAt and IS in the database systems of PCRs; lack of maintenance and supervision on the availabilities and the capacities of traffic facilities and road infrastructure; instrumental bias with wash-back impacts towards the TCPHI; technical robustness with wash-back impacts towards the CAPO and TCPHI.

Keywords: decision aiding processes, evaluation model, PTW accidents, police crash reports

Procedia PDF Downloads 129

Authors: Norma Binti Alias, Che Rahim Che The, Norfarizan Mohd Said, Sakinah Abdul Hanan, Akhtar Ali

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This paper discusses on the transportation of magnetic drug targeting through blood within vessels, tissues and cells. There are three integrated mathematical models to be discussed and analyze the concentration of drug and blood flow through magnetic nanoparticles. The cell therapy brought advancement in the field of nanotechnology to fight against the tumors. The systematic therapeutic effect of Single Cells can reduce the growth of cancer tissue. The process of this nanoscale phenomena system is able to measure and to model, by identifying some parameters and applying fundamental principles of mathematical modeling and simulation. The mathematical modeling of single cell growth depends on three types of cell densities such as proliferative, quiescent and necrotic cells. The aim of this paper is to enhance the simulation of three types of models. The first model represents the transport of drugs by coupled partial differential equations (PDEs) with 3D parabolic type in a cylindrical coordinate system. This model is integrated by Non-Newtonian flow equations, leading to blood liquid flow as the medium for transportation system and the magnetic force on the magnetic nanoparticles. The interaction between the magnetic force on drug with magnetic properties produces induced currents and the applied magnetic field yields forces with tend to move slowly the movement of blood and bring the drug to the cancer cells. The devices of nanoscale allow the drug to discharge the blood vessels and even spread out through the tissue and access to the cancer cells. The second model is the transport of drug nanoparticles from the vascular system to a single cell. The treatment of the vascular system encounters some parameter identification such as magnetic nanoparticle targeted delivery, blood flow, momentum transport, density and viscosity for drug and blood medium, intensity of magnetic fields and the radius of the capillary. Based on two discretization techniques, finite difference method (FDM) and finite element method (FEM), the set of integrated models are transformed into a series of grid points to get a large system of equations. The third model is a single cell density model involving the three sets of first order PDEs equations for proliferating, quiescent and necrotic cells change over time and space in Cartesian coordinate which regulates under different rates of nutrients consumptions. The model presents the proliferative and quiescent cell growth depends on some parameter changes and the necrotic cells emerged as the tumor core. Some numerical schemes for solving the system of equations are compared and analyzed. Simulation and computation of the discretized model are supported by Matlab and C programming languages on a single processing unit. Some numerical results and analysis of the algorithms are presented in terms of informative presentation of tables, multiple graph and multidimensional visualization. As a conclusion, the integrated of three types mathematical modeling and the comparison of numerical performance indicates that the superior tool and analysis for solving the complete set of magnetic drug delivery system which give significant effects on the growth of the targeted cancer cell.

Keywords: mathematical modeling, visualization, PDE models, magnetic nanoparticle drug delivery model, drug release model, single cell effects, avascular tumor growth, numerical analysis

Procedia PDF Downloads 397

Authors: Naeem Ullah, Menglan Duan, Mac Darlington Uche Onuoha

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The lowering of subsea equipment into the deep waters is a challenging job due to the harsh offshore environment. Many researchers have introduced various installation systems to deploy the payload safely into the deep oceans. In general practice, dual floating vessels are not employed owing to the prevalent safety risks and hazards caused by ever-increasing dynamical effects sourced by mutual interaction between the bodies. However, while keeping in the view of the optimal grounds, such as economical one, the Y-method, the two conventional tugboats supporting the equipment by the two independent strands connected to a tri-plate above the equipment, has been employed to study multibody dynamics of the dual barge lifting operations. In this study, the two tugboats and the suspended payload (Y-method) are deployed for the lowering of subsea equipment into the deep waters as a multibody dynamic system. The two-wire ropes are used for the lifting and installation operation by this Y-method installation system. 6-dof (degree of freedom) for each body are considered to establish coupled 18-dof multibody model by embedding technique or velocity transformation technique. The fundamental and prompt advantage of this technique is that the constraint forces can be eliminated directly, and no extra computational effort is required for the elimination of the constraint forces. The inertial frame of reference is taken at the surface of the water as the time-independent frame of reference, and the floating frames of reference are introduced in each body as the time-dependent frames of reference in order to formulate the velocity transformation matrix. The local transformation of the generalized coordinates to the inertial frame of reference is executed by applying the Euler Angle approach. The spherical joints are articulated amongst the multibody as the kinematic joints. The hydrodynamic force, the two-strand forces, the hydrostatic force, and the mooring forces are taken into consideration as the external forces. The radiation force of the hydrodynamic force is obtained by employing the Cummins equation. The wave exciting part of the hydrodynamic force is obtained by using force response amplitude operators (RAOs) that are obtained by the commercial solver ‘OpenFOAM’. The strand force is obtained by considering the wire rope as an elastic spring. The nonlinear hydrostatic force is obtained by the pressure integration technique at each time step of the wave movement. The mooring forces are evaluated by using Faltinsen analytical approach. ‘The Runge Kutta Method’ of Fourth-Order is employed to evaluate the coupled equations of motion obtained for 18-dof multibody model. The results are correlated with the simulated Orcaflex Model. Moreover, the results from Orcaflex Model are compared with the MOSES Model from previous studies. The MBDS of single barge lifting operation from the former studies are compared with the MBDS of the established dual barge lifting operation. The dynamics of the dual barge lifting operation are found larger in magnitude as compared to the single barge lifting operation. It is noticed that the traction at the top connection point of the cable decreases with the increase in the length, and it becomes almost constant after passing through the splash zone.

Keywords: dual barge lifting operation, Y-method, multibody dynamics, shipbuilding, installation of subsea equipment, shipbuilding

Procedia PDF Downloads 174

Authors: Athanasios Karasimos, Vasiliki Makri

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This research focuses on the design and development of the first text Corpus based on Board Game Rulebooks (BGRC) with direct application on the morphological analysis of neologisms and tendencies in word-formation processes. Corpus linguistics is a dynamic field that examines language through the lens of vast collections of texts. These corpora consist of diverse written and spoken materials, ranging from literature and newspapers to transcripts of everyday conversations. By morphologically analyzing these extensive datasets, morphologists can gain valuable insights into how language functions and evolves, as these extensive datasets can reflect the byproducts of inflection, derivation, blending, clipping, compounding, and neology. This entails scrutinizing how words are created, modified, and combined to convey meaning in a corpus of challenging, creative, and straightforward texts that include rules, examples, tutorials, and tips. Board games teach players how to strategize, consider alternatives, and think flexibly, which are critical elements in language learning. Their rulebooks reflect not only their weight (complexity) but also the language properties of each genre and subgenre of these games. Board games are a captivating realm where strategy, competition, and creativity converge. Beyond the excitement of gameplay, board games also spark the art of word creation. Word games, like Scrabble, Codenames, Bananagrams, Wordcraft, Alice in the Wordland, Once uUpona Time, challenge players to construct words from a pool of letters, thus encouraging linguistic ingenuity and vocabulary expansion. These games foster a love for language, motivating players to unearth obscure words and devise clever combinations. On the other hand, the designers and creators produce rulebooks, where they include their joy of discovering the hidden potential of language, igniting the imagination, and playing with the beauty of words, making these games a delightful fusion of linguistic exploration and leisurely amusement. In this research, more than 150 rulebooks in English from all types of modern board games, either language-independent or language-dependent, are used to create the BGRC. A representative sample of each genre (family, party, worker placement, deckbuilding, dice, and chance games, strategy, eurogames, thematic, role-playing, among others) was selected based on the score from BoardGameGeek, the size of the texts and the level of complexity (weight) of the game. A morphological model with morphological networks, multi-word expressions, and word-creation mechanics based on the complexity of the textual structure, difficulty, and board game category will be presented. In enabling the identification of patterns, trends, and variations in word formation and other morphological processes, this research aspires to make avail of this creative yet strict text genre so as to (a) give invaluable insight into morphological creativity and innovation that (re)shape the lexicon of the English language and (b) test morphological theories. Overall, it is shown that corpus linguistics empowers us to explore the intricate tapestry of language, and morphology in particular, revealing its richness, flexibility, and adaptability in the ever-evolving landscape of human expression.

Keywords: board game rulebooks, corpus design, morphological innovations, neologisms, word-formation processes

Procedia PDF Downloads 58

Authors: Vishal Kumar, Soumitra Satapathi

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Föster Resonance Energy Transfer (FRET) is a powerful technique used to probe close-range molecular interactions. Physically, the FRET phenomenon manifests as a dipole–dipole interaction between closely juxtaposed fluorescent molecules (10–100 Å). Our effort is to employ this FRET technique to make a prototype device for highly sensitive detection of environment pollutant. Among the most common environmental pollutants, nitroaromatic compounds (NACs) are of particular interest because of their durability and toxicity. That’s why, sensitive and selective detection of small amounts of nitroaromatic explosives, in particular, 2,4,6-trinitrophenol (TNP), 2,4-dinitrotoluene (DNT) and 2,4,6-trinitrotoluene (TNT) has been a critical challenge due to the increasing threat of explosive-based terrorism and the need of environmental monitoring of drinking and waste water. In addition, the excessive utilization of TNP in several other areas such as burn ointment, pesticides, glass and the leather industry resulted in environmental accumulation, and is eventually contaminating the soil and aquatic systems. To the date, high number of elegant methods, including fluorimetry, gas chromatography, mass, ion-mobility and Raman spectrometry have been successfully applied for explosive detection. Among these efforts, fluorescence-quenching methods based on the mechanism of FRET show good assembly flexibility, high selectivity and sensitivity. Here, we report a FRET-based sensor system for the highly selective detection of NACs, such as TNP, DNT and TNT. The sensor system is composed of a copolymer Poly [(N,N-dimethylacrylamide)-co-(Boc-Trp-EMA)] (RP) bearing tryptophan derivative in the side chain as donor and dansyl tagged copolymer P(MMA-co-Dansyl-Ala-HEMA) (DCP) as an acceptor. Initially, the inherent fluorescence of RP copolymer is quenched by non-radiative energy transfer to DCP which only happens once the two molecules are within Förster critical distance (R0). The excellent spectral overlap (Jλ= 6.08×10¹⁴ nm⁴M⁻¹cm⁻¹) between donors’ (RP) emission profile and acceptors’ (DCP) absorption profile makes them an exciting and efficient FRET pair i.e. further confirmed by the high rate of energy transfer from RP to DCP i.e. 0.87 ns⁻¹ and lifetime measurement by time correlated single photon counting (TCSPC) to validate the 64% FRET efficiency. This FRET pair exhibited a specific fluorescence response to NACs such as DNT, TNT and TNP with 5.4, 2.3 and 0.4 µM LODs, respectively. The detection of NACs occurs with high sensitivity by photoluminescence quenching of FRET signal induced by photo-induced electron transfer (PET) from electron-rich FRET pair to electron-deficient NAC molecules. The estimated stern-volmer constant (KSV) values for DNT, TNT and TNP are 6.9 × 10³, 7.0 × 10³ and 1.6 × 104 M⁻¹, respectively. The mechanistic details of molecular interactions are established by time-resolved fluorescence, steady-state fluorescence and absorption spectroscopy confirmed that the sensing process is of mixed type, i.e. both dynamic and static quenching as lifetime of FRET system (0.73 ns) is reduced to 0.55, 0.57 and 0.61 ns DNT, TNT and TNP, respectively. In summary, the simplicity and sensitivity of this novel FRET sensor opens up the possibility of designing optical sensor of various NACs in one single platform for developing multimodal sensor for environmental monitoring and future field based study.

Keywords: FRET, nitroaromatic, stern-Volmer constant, tryptophan and dansyl tagged copolymer

Procedia PDF Downloads 102

Authors: M. Shahab Uddin, Pennung Warnitchai

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Currently more than half of the world’s populations are living in cities, and the number and sizes of cities are growing faster than ever. Cities rely on the effective functioning of complex and interdependent critical infrastructures networks to provide public services, enhance the quality of life, and save the community from hazards and disasters. In contrast, complex connectivity and interdependency among the urban critical infrastructures bring management challenges and make the urban system prone to the domino effect. Unplanned rapid growth, increased connectivity, and interdependency among the infrastructures, resource scarcity, and many other socio-political factors are affecting the typical state of an urban system and making it susceptible to numerous sorts of diversion. In addition to internal vulnerabilities, urban systems are consistently facing external threats from natural and manmade hazards. Cities are not just complex, interdependent system, but also makeup hubs of the economy, politics, culture, education, etc. For survival and sustainability, complex urban systems in the current world need to manage their vulnerabilities and hazardous incidents more wisely and more interactively. Coordinated management in such systems makes for huge potential when it comes to absorbing negative effects in case some of its components were to function improperly. On the other hand, ineffective management during a similar situation of overall disorder from hazards devastation may make the system more fragile and push the system to an ultimate collapse. Following the quantum, the current research hypothesizes that a hazardous event starts its journey as an emergency, and the system’s internal vulnerability and response capacity determine its destination. Connectivity and interdependency among the urban critical infrastructures during this stage may transform its vulnerabilities into dynamic damaging force. An emergency may turn into a disaster in the absence of effective management; similarly, mismanagement or lack of management may lead the situation towards a catastrophe. Situation awareness and factual decision-making is the key to win a battle. The current research proposed a contextual decision support system for an urban critical infrastructure system while integrating three different models: 1) Damage cascade model which demonstrates damage propagation among the infrastructures through their connectivity and interdependency, 2) Restoration model, a dynamic restoration process of individual infrastructure, which is based on facility damage state and overall disruptions in surrounding support environment, and 3) Optimization model that ensures optimized utilization and distribution of available resources in and among the facilities. All three models are tightly connected, mutually interdependent, and together can assess the situation and forecast the dynamic outputs of every input. Moreover, this integrated model will hold disaster managers and decision makers responsible when it comes to checking all the alternative decision before any implementation, and support to produce maximum possible outputs from the available limited inputs. This proposed model will not only support to reduce the extent of damage cascade but will ensure priority restoration and optimize resource utilization through adaptive and collaborative management. Complex systems predictably fail but in unpredictable ways. System understanding, situation awareness, and factual decisions may significantly help urban system to survive and sustain.

Keywords: disaster prevention, decision support system, emergency response, urban critical infrastructure system

Procedia PDF Downloads 193

Authors: Helena Pera, Arcadi Sanmartin, Albert Falques, Rafael Rebolo, Xavier Ametller, Heiko Zillgen, Cecile Prum, Boris Even, Eric Kapornyai

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Sheet piles system can be an interesting solution when dealing with harbors or quays designs. However, current design methods lead to conservative approaches due to the lack of specific basis of design. For instance, some design features still deal with pseudo-static approaches, although being a dynamic problem. Under this concern, the study particularly focuses on hydrodynamic water pressure definition and stability analysis of sheet pile system under seismic loads. During a seismic event, seawater produces hydrodynamic pressures on structures. Currently, design methods introduce hydrodynamic forces by means of Westergaard formulation and Eurocodes recommendations. They apply constant hydrodynamic pressure on the front sheet pile during the entire earthquake. As a result, the hydrodynamic load may represent 20% of the total forces produced on the sheet pile. Nonetheless, some studies question that approach. Hence, this study assesses the soil-structure-fluid interaction of sheet piles under seismic action in order to evaluate if current design strategies overestimate hydrodynamic pressures. For that purpose, this study performs various simulations by Plaxis 2D, a well-known geotechnical software, and CFD models, which treat fluid dynamic behaviours. Knowing that neither Plaxis nor CFD can resolve a soil-fluid coupled problem, the investigation imposes sheet pile displacements from Plaxis as input data for the CFD model. Then, it provides hydrodynamic pressures under seismic action, which fit theoretical Westergaard pressures if calculated using the acceleration at each moment of the earthquake. Thus, hydrodynamic pressures fluctuate during seismic action instead of remaining constant, as design recommendations propose. Additionally, these findings detect that hydrodynamic pressure contributes a 5% to the total load applied on sheet pile due to its instantaneous nature. These results are in line with other studies that use added masses methods for hydrodynamic pressures. Another important feature in sheet pile design is the assessment of the geotechnical overall stability. It uses pseudo-static analysis since the dynamic analysis cannot provide a safety calculation. Consequently, it estimates the seismic action. One of its relevant factors is the selection of the seismic reduction factor. A huge amount of studies discusses the importance of it but also about all its uncertainties. Moreover, current European standards do not propose a clear statement on that, and they recommend using a reduction factor equal to 1. This leads to conservative requirements when compared with more advanced methods. Under this situation, the study calibrates seismic reduction factor by fitting results from pseudo-static to dynamic analysis. The investigation concludes that pseudo-static analyses could reduce seismic action by 40-50%. These results are in line with some studies from Japanese and European working groups. In addition, it seems suitable to account for the flexibility of the sheet pile-soil system. Nevertheless, the calibrated reduction factor is subjected to particular conditions of each design case. Further research would contribute to specifying recommendations for selecting reduction factor values in the early stages of the design. In conclusion, sheet pile design still has chances for improving its design methodologies and approaches. Consequently, design could propose better seismic solutions thanks to advanced methods such as findings of this study.

Keywords: computational fluid dynamics, hydrodynamic pressures, pseudo-static analysis, quays, seismic design, steel sheet pile

Procedia PDF Downloads 118

Authors: Stefan K. Behfar

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The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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Authors: Utkarsh A. Mishra, Ankit Bansal

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At high temperature, radiative heat transfer is the dominant mode of heat transfer. It is governed by various phenomena such as photon emission, absorption, and scattering. The solution of the governing integrodifferential equation of radiative transfer is a complex process, more when the effect of participating medium and wavelength properties are taken into consideration. Although a generic formulation of such radiative transport problem can be modeled for a wide variety of problems with non-gray, non-diffusive surfaces, there is always a trade-off between simplicity and accuracy of the problem. Recently, solutions of complicated mathematical problems with statistical methods based on randomization of naturally occurring phenomena have gained significant importance. Photon bundles with discrete energy can be replicated with random numbers describing the emission, absorption, and scattering processes. Photon Monte Carlo (PMC) is a simple, yet powerful technique, to solve radiative transfer problems in complicated geometries with arbitrary participating medium. The method, on the one hand, increases the accuracy of estimation, and on the other hand, increases the computational cost. The participating media -generally a gas, such as CO₂, CO, and H₂O- present complex emission and absorption spectra. To model the emission/absorption accurately with random numbers requires a weighted sampling as different sections of the spectrum carries different importance. Importance sampling (IS) was implemented to sample random photon of arbitrary wavelength, and the sampled data provided unbiased training of MC estimators for better results. A better replacement to uniform random numbers is using deterministic, quasi-random sequences. Halton, Sobol, and Faure Low-Discrepancy Sequences are used in this study. They possess better space-filling performance than the uniform random number generator and gives rise to a low variance, stable Quasi-Monte Carlo (QMC) estimators with faster convergence. An optimal supervised learning scheme was further considered to reduce the computation costs of the PMC simulation. A one-dimensional plane-parallel slab problem with participating media was formulated. The history of some randomly sampled photon bundles is recorded to train an Artificial Neural Network (ANN), back-propagation model. The flux was calculated using the standard quasi PMC and was considered to be the training target. Results obtained with the proposed model for the one-dimensional problem are compared with the exact analytical and PMC model with the Line by Line (LBL) spectral model. The approximate variance obtained was around 3.14%. Results were analyzed with respect to time and the total flux in both cases. A significant reduction in variance as well a faster rate of convergence was observed in the case of the QMC method over the standard PMC method. However, the results obtained with the ANN method resulted in greater variance (around 25-28%) as compared to the other cases. There is a great scope of machine learning models to help in further reduction of computation cost once trained successfully. Multiple ways of selecting the input data as well as various architectures will be tried such that the concerned environment can be fully addressed to the ANN model. Better results can be achieved in this unexplored domain.

Keywords: radiative heat transfer, Monte Carlo Method, pseudo-random numbers, low discrepancy sequences, artificial neural networks

Procedia PDF Downloads 187

Authors: Antonis Skouloudis, Konstantinos Evangelinos, Walter Leal-Filho, Panagiotis Vouros, Ioannis Nikolaou

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Organizational resilience capacity to extreme weather events (EWEs) has sparked a growth in scholarly attention over the past decade as an essential aspect in business continuity management, with supporting evidence for this claim to suggest that it retains a key role in successful responses to adverse situations, crises and shocks. Small and medium-sized enterprises (SMEs) are more vulnerable to face floods compared to their larger counterparts, so they are disproportionately affected by such extreme weather events. The limited resources at their disposal, the lack of time and skills all conduce to inadequate preparedness to challenges posed by floods. SMEs tend to plan in the short-term, reacting to circumstances as they arise and focussing on their very survival. Likewise, they share less formalised structures and codified policies while they are most usually owner-managed, resulting in a command-and-control management culture. Such characteristics result in them having limited opportunities to recover from flooding and quickly turnaround their operation from a loss making to a profit making one. Scholars frame the capacity of business entities to be resilient upon an EWE disturbance (such as flash floods) as the rate of recovery and restoration of organizational performance to pre-disturbance conditions, the amount of disturbance (i.e. threshold level) a business can absorb before losing structural and/or functional components that will alter or cease operation, as well as the extent to which the organization maintains its function (i.e. impact resistance) before performance levels are driven to zero. Nevertheless, while it seems to be accepted as an essential trait of firms effectively transcending uncertain conditions, research deconstructing the enabling conditions and/or inhibitory factors of SMEs resilience capacity to natural hazards is still sparse, fragmentary and mostly fuelled by anecdotal evidence or normative assumptions. Focusing on the individual level of analysis, i.e. the individual enterprise and its endeavours to succeed, the emergent picture from this relatively new research strand delineates the specification of variables, conceptual relationships or dynamic boundaries of resilience capacity components in an attempt to provide prescriptions for policy-making as well as business management. This study will present the development of a flood resilience capacity index (FRCI) and its application to Greek SMEs. The proposed composite indicator pertains to cognitive, behavioral/managerial and contextual factors that influence an enterprise’s ability to shape effective responses to meet flood challenges. Through the proposed indicator-based approach, an analytical framework is set forth that will help standardize such assessments with the overarching aim of reducing the vulnerability of SMEs to flooding. This will be achieved by identifying major internal and external attributes explaining resilience capacity which is particularly important given the limited resources these enterprises have and that they tend to be primary sources of vulnerabilities in supply chain networks, generating Single Points of Failure (SPOF).

Keywords: Floods, Small & Medium-Sized enterprises, organizational resilience capacity, index development

Procedia PDF Downloads 157

Authors: M. Kadela

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The load caused by the traffic movement should be transferred in the road constructions in a harmless way to the pavement as follows: − on the stiff upper layers of the structure (e.g. layers of asphalt: abrading and binding), and − through the layers of principal and secondary substructure, − on the subsoil, directly or through an improved subsoil layer. Reliable description of the interaction proceeding in a system “road construction – subsoil” should be in such case one of the basic requirements of the assessment of the size of internal forces of structure and its durability. Analyses of road constructions are based on: − elements of mechanics, which allows to create computational models, and − results of the experiments included in the criteria of fatigue life analyses. Above approach is a fundamental feature of commonly used mechanistic methods. They allow to use in the conducted evaluations of the fatigue life of structures arbitrarily complex numerical computational models. Considering the work of the system “road construction – subsoil”, it is commonly accepted that, as a result of repetitive loads on the subsoil under pavement, the growth of relatively small deformation in the initial phase is recognized, then this increase disappears, and the deformation takes the character completely reversible. The reliability of calculation model is combined with appropriate use (for a given type of analysis) of constitutive relationships. Phenomena occurring in the initial stage of the system “road construction – subsoil” is unfortunately difficult to interpret in the modeling process. The classic interpretation of the behavior of the material in the elastic-plastic model (e-p) is that elastic phase of the work (e) is undergoing to phase (e-p) by increasing the load (or growth of deformation in the damaging structure). The paper presents the essence of the calibration process of cooperating subsystem in the calculation model of the system “road construction – subsoil”, created for the mechanistic analysis. Calibration process was directed to show the impact of applied constitutive models on its deformation and stress response. The proper comparative base for assessing the reliability of created. This work was supported by the on-going research project “Stabilization of weak soil by application of layer of foamed concrete used in contact with subsoil” (LIDER/022/537/L-4/NCBR/2013) financed by The National Centre for Research and Development within the LIDER Programme. M. Kadela is with the Department of Building Construction Elements and Building Structures on Mining Areas, Building Research Institute, Silesian Branch, Katowice, Poland (phone: +48 32 730 29 47; fax: +48 32 730 25 22; e-mail: m.kadela@ itb.pl). models should be, however, the actual, monitored system “road construction – subsoil”. The paper presents too behavior of subsoil under cyclic load transmitted by pavement layers. The response of subsoil to cyclic load is recorded in situ by the observation system (sensors) installed on the testing ground prepared for this purpose, being a part of the test road near Katowice, in Poland. A different behavior of the homogeneous subsoil under pavement is observed for different seasons of the year, when pavement construction works as a flexible structure in summer, and as a rigid plate in winter. Albeit the observed character of subsoil response is the same regardless of the applied load and area values, this response can be divided into: - zone of indirect action of the applied load; this zone extends to the depth of 1,0 m under the pavement, - zone of a small strain, extending to about 2,0 m.

Keywords: road structure, constitutive model, calculation model, pavement, soil, FEA, response of soil, monitored system

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Authors: José Silvestre Mendoza Figueroa, Anders Kvarnheden, Jesús Méndez Lozano, Edgar Antonio Rodríguez Negrete, Manuel Soriano García

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Agroindustrial plants such as cereals and pseudo cereals offer a substantial source of biomacromolecules, as they contain large amounts per tissue-gram of proteins, polysaccharides and lipids in comparison with other plants. In particular, Amaranthus hypochondriacus seeds have high levels of proteins in comparison with other cereal and pseudo cereal species, which makes the plant a good source of bioactive molecules such as peptides. Geminiviruses are one principal class of pathogens that causes important economic losses in crops, affecting directly the development and production of the plant. One such virus is the Tomato yellow leaf curl virus (TYLCV), which affects mainly Solanacea family plants such as tomato species. The symptoms of the disease are curling of leaves, chlorosis, dwarfing and floral abortion. The aim of this work was to get peptides derived from enzymatic hydrolysis of globulins and albumins from amaranth seeds with specific recognition of the replication origin in the TYLCV genome, and to test the antiviral activity on host plants with the idea to generate a direct control of this viral infection. Globulins and albumins from amaranth were extracted, the fraction was enzymatically digested with papain, and the aromatic peptides fraction was selected for further purification. Six peptides were tested against the replication origin (OR) using affinity assays, surface resonance plasmon and fluorescent titration, and two of these peptides showed high affinity values to the replication origin of the virus, dissociation constant values were calculated and showed specific interaction between the peptide Ampep1 and the OR. An in vitro replication test of the total TYLCV DNA was performed, in which the peptide AmPep1 was added in different concentrations to the system reaction, which resulted in a decrease of viral DNA synthesis when the peptide concentration increased. Also, we showed that the peptide can decrease the complementary DNA chain of the virus in Nicotiana benthamiana leaves, confirming that the peptide binds to the OR and that its expected mechanism of action is to decrease the replication rate of the viral genome. In an infection assay, N. benthamiana plants were agroinfected with TYLCV-Israel and TYLCV-Guasave. After confirming systemic infection, the peptide was infiltrated in new infected leaves, and the plants treated with the peptide showed a decrease of virus symptoms and viral titer. In order to confirm the antiviral activity in a commercial crop, tomato plants were infected with TYLCV. After confirming systemic infection, plants were infiltrated with peptide solution as above, and the symptom development was monitored 21 days after treatment, showing that tomato plants treated with peptides had lower symptom rates and viral titer. The peptide was also tested against other begomovirus such as Pepper huasteco yellow vein virus (PHYVV-Guasave), showing a decrease of symptoms in N. benthamiana infected plants. The model of direct biochemical control of TYLCV infection shown in this work can be extrapolated to other begomovirus infections, and the methods reported here can be used for design of antiviral agrochemicals for other plant virus infections.

Keywords: agrochemical screening, antiviral, begomovirus, geminivirus, peptides, plasmon, TYLCV

Procedia PDF Downloads 242

Authors: Simone Dell'Agnello

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There are laser retroreflectors on the Moon and no laser retroreflectors on Mars. Here we describe the design, construction, qualification and imminent deployment of next-generation, optimized laser retroreflectors on the Moon and on Mars (where they will be the first ones). These instruments are positioned by time-of-flight measurements of short laser pulses, the so-called 'laser ranging' technique. Data analysis is carried out with PEP, the Planetary Ephemeris Program of CfA (Center for Astrophysics). Since 1969 Lunar Laser Ranging (LLR) to Apollo/Lunokhod laser retro-reflector (CCR) arrays supplied accurate tests of General Relativity (GR) and new gravitational physics: possible changes of the gravitational constant Gdot/G, weak and strong equivalence principle, gravitational self-energy (Parametrized Post Newtonian parameter beta), geodetic precession, inverse-square force-law; it can also constraint gravitomagnetism. Some of these measurements also allowed for testing extensions of GR, including spacetime torsion, non-minimally coupled gravity. LLR has also provides significant information on the composition of the deep interior of the Moon. In fact, LLR first provided evidence of the existence of a fluid component of the deep lunar interior. In 1969 CCR arrays contributed a negligible fraction of the LLR error budget. Since laser station range accuracy improved by more than a factor 100, now, because of lunar librations, current array dominate the error due to their multi-CCR geometry. We developed a next-generation, single, large CCR, MoonLIGHT (Moon Laser Instrumentation for General relativity high-accuracy test) unaffected by librations that supports an improvement of the space segment of the LLR accuracy up to a factor 100. INFN also developed INRRI (INstrument for landing-Roving laser Retro-reflector Investigations), a microreflector to be laser-ranged by orbiters. Their performance is characterized at the SCF_Lab (Satellite/lunar laser ranging Characterization Facilities Lab, INFN-LNF, Frascati, Italy) for their deployment on the lunar surface or the cislunar space. They will be used to accurately position landers, rovers, hoppers, orbiters of Google Lunar X Prize and space agency missions, thanks to LLR observations from station of the International Laser Ranging Service in the USA, in France and in Italy. INRRI was launched in 2016 with the ESA mission ExoMars (Exobiology on Mars) EDM (Entry, descent and landing Demonstration Module), deployed on the Schiaparelli lander and is proposed for the ExoMars 2020 Rover. Based on an agreement between NASA and ASI (Agenzia Spaziale Italiana), another microreflector, LaRRI (Laser Retro-Reflector for InSight), was delivered to JPL (Jet Propulsion Laboratory) and integrated on NASA’s InSight Mars Lander in August 2017 (launch scheduled in May 2018). Another microreflector, LaRA (Laser Retro-reflector Array) will be delivered to JPL for deployment on the NASA Mars 2020 Rover. The first lunar landing opportunities will be from early 2018 (with TeamIndus) to late 2018 with commercial missions, followed by opportunities with space agency missions, including the proposed deployment of MoonLIGHT and INRRI on NASA’s Resource Prospectors and its evolutions. In conclusion, we will extend significantly the CCR Lunar Geophysical Network and populate the Mars Geophysical Network. These networks will enable very significantly improved tests of GR.

Keywords: general relativity, laser retroreflectors, lunar laser ranging, Mars geodesy

Procedia PDF Downloads 243

Authors: Camille Aouinaït, Danilo Christen, Christoph Carlen

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Introduction: Small and Medium-sized Enterprises (SMEs) are facing different challenges such as pressures on environmental resources, the rise of downstream power, and trade liberalization. Remaining competitive by implementing innovations and engaging in collaborations could be a strategic solution. In Switzerland, the Federal Institute for Research in Agriculture (Agroscope), the Federal schools of technology (EPFL and ETHZ), Cantonal universities and Universities of Applied Sciences (UAS) can provide substantial inputs. UAS were developed with specific missions to match the labor markets and society needs. Research projects produce patents, publications and improved networks of scientific expertise. The study’s goal is to measure the contribution of UAS and research organization to innovation and the impact of collaborations with partners in the non-academic environment in Swiss traditional fruit production. Materials and methods: The European projects Traditional Food Network to improve the transfer of knowledge for innovation (TRAFOON) and Social Impact Assessment of Productive Interactions between science and society (SIAMPI) frame the present study. The former aims to fill the gap between the needs of traditional food producing SMEs and innovations implemented following European projects. The latter developed a method to assess the impacts of scientific research. On one side, interviews with market players have been performed to make an inventory of needs of Swiss SMEs producing apricots and berries. The participative method allowed matching the current needs and the existing innovations coming from past European projects. Swiss stakeholders (e.g. producers, retailers, an inter-branch organization of fruits and vegetables) directly rated the needs on a five-Likert scale. To transfer the knowledge to SMEs, training workshops have been organized for apricot and berries actors separately, on specific topics. On the other hand, a mapping of a social network is drawn to characterize the links between actors, with a focus on the Swiss canton of Valais and UAS Valais Wallis. Type and frequency of interactions among actors have identified thanks to interviews. Preliminary results: A list of 369 SMEs needs grouped in 22 categories was produced with 37 fulfilled questionnaires. Swiss stakeholders rated 31 needs very important. Training workshops on apricot are focusing on varietal innovations, storage, disease (bacterial blight), pest (Drosophila suzukii), sorting and rootstocks. Entrepreneurship was targeted through trademark discussions in berry production. The UAS Valais Wallis collaborated on a few projects with Agroscope along with industries, at European and national levels. Political and public bodies interfere with the central area of agricultural vulgarization that induces close relationships between the research and the practical side. Conclusions: The needs identified by Swiss stakeholders are becoming part of training workshops to incentivize innovations. The UAS Valais Wallis takes part in collaboration projects with the research environment and market players that bring innovations helping SMEs in their contextual environment. Then, a Strategic Research and Innovation Agenda will be created in order to pursue research and answer the issues facing by SMEs.

Keywords: agriculture, innovation, knowledge transfer, university and research collaboration

Procedia PDF Downloads 362

Authors: Juan Pablo Botero Torres, Alba Avila, Luis Felipe Giraldo

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Independent navigation and mobility through unknown spaces pose a challenge for the autonomy of visually impaired people (VIP), who have relied on the use of traditional assistive tools like the white cane and trained dogs. However, emerging visually assistive technologies (VAT) have proposed several human-machine interfaces (HMIs) that could improve VIP’s ability for self-guidance. Hereby, we introduce the design and implementation of a visually assistive device, Anajaa – Visual Substitution System (AVSS). This system integrates ultrasonic sensors with custom electronics, and computer vision models (convolutional neural networks), in order to achieve a robust system that acquires information of the surrounding space and transmits it to the user in an intuitive and efficient manner. AVSS consists of two modules: the sensing and the actuation module, which are fitted to a chest mount and belt that communicate via Bluetooth. The sensing module was designed for the acquisition and processing of proximity signals provided by an array of ultrasonic sensors. The distribution of these within the chest mount allows an accurate representation of the surrounding space, discretized in three different levels of proximity, ranging from 0 to 6 meters. Additionally, this module is fitted with an RGB-D camera used to detect potentially threatening obstacles, like staircases, using a convolutional neural network specifically trained for this purpose. Posteriorly, the depth data is used to estimate the distance between the stairs and the user. The information gathered from this module is then sent to the actuation module that creates an HMI, by the means of a 3x2 array of vibration motors that make up the tactile display and allow the system to deliver haptic feedback. The actuation module uses vibrational messages (tactones); changing both in amplitude and frequency to deliver different awareness levels according to the proximity of the obstacle. This enables the system to deliver an intuitive interface. Both modules were tested under lab conditions, and the HMI was additionally tested with a focal group of VIP. The lab testing was conducted in order to establish the processing speed of the computer vision algorithms. This experimentation determined that the model can process 0.59 frames per second (FPS); this is considered as an adequate processing speed taking into account that the walking speed of VIP is 1.439 m/s. In order to test the HMI, we conducted a focal group composed of two females and two males between the ages of 35-65 years. The subject selection was aided by the Colombian Cooperative of Work and Services for the Sightless (COOTRASIN). We analyzed the learning process of the haptic messages throughout five experimentation sessions using two metrics: message discrimination and localization success. These correspond to the ability of the subjects to recognize different tactones and locate them within the tactile display. Both were calculated as the mean across all subjects. Results show that the focal group achieved message discrimination of 70% and a localization success of 80%, demonstrating how the proposed HMI leads to the appropriation and understanding of the feedback messages, enabling the user’s awareness of its surrounding space.

Keywords: computer vision on embedded systems, electronic trave aids, human-machine interface, haptic feedback, visual assistive technologies, vision substitution systems

Procedia PDF Downloads 49

Authors: Maayan Nakash

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The modern workplace is undergoing a revolution, with Generation Z (Gen-Z) at the forefront of this transformative shift. However, empirical investigations specifically targeting the workplace preferences of this generation remain limited. Through direct examination of their tendencies via a survey approach, this study offers vital insights for aligning organizational policies and practices. The results presented in this paper are part of a comprehensive study that explored Gen Z's viewpoints on various employment market aspects, likely to decisively influence the design of future work environments. Data were collected via an online survey distributed among a cohort of 461 individuals from Gen-Z, born between the mid-1990s and 2010, consisting of 241 males (52.28%) and 220 females (47.72%). Responses were gauged using Likert scale statements that probed preferences for teamwork versus individual work, virtual versus personal interactions, and open versus private workspaces. Descriptive statistics and analytical analyses were conducted to pinpoint key patterns. We discovered that a high proportion of respondents (81.99%, n=378) exhibited a preference for teamwork over individual work. Correspondingly, the data indicate strong support for the recognition of team-based tasks as a tool contributing to personal and professional development. In terms of communication, the majority of respondents (61.38%) either disagreed (n=154) or slightly agreed (n=129) with the exclusive reliance on virtual interactions with their organizational peers. This finding underscores that despite technological progress, digital natives place significant value on physical interaction and non-mediated communication. Moreover, we understand that they also value a quiet and private work environment, clearly preferring it over open and shared workspaces. Considering that Gen-Z does not necessarily experience high levels of stress within social frameworks in the workplace, this can be attributed to a desire for a space that allows for focused engagement with work tasks. A One-Sample Chi-Square Test was performed on the observed distribution of respondents' reactions to each examined statement. The results showed statistically significant deviations from a uniform distribution (p<.001), indicating that the response patterns did not occur by chance and that there were meaningful tendencies in the participants' responses. The findings expand the theoretical knowledge base on human resources in the dynamics of a multi-generational workforce, illuminating the values, approaches, and expectations of Gen-Z. Practically, the results may lead organizations to equip themselves with tools to create policies tailored to Gen-Z in the context of workspaces and social needs, which could potentially foster a fertile environment and aid in attracting and retaining young talent. Future studies might include investigating potential mitigating factors, such as cultural influences or individual personality traits, which could further clarify the nuances in Gen-Z's work style preferences. Longitudinal studies tracking changes in these preferences as the generation matures may also yield valuable insights. Ultimately, as the landscape of the workforce continues to evolve, ongoing investigations into the unique characteristics and aspirations of emerging generations remain essential for nurturing harmonious, productive, and future-ready organizational environments.

Keywords: workplace, future of work, generation Z, digital natives, human resources management

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Authors: Ariesny Vera, Rodrigo Montecinos

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The rare-earth elements (REEs) or rare-earth metals (REMs), correspond to seventeen chemical elements composed by the fifteen lanthanoids, as well as scandium and yttrium. Lanthanoids corresponds to lanthanum and the f-block elements, from cerium to lutetium. Scandium and yttrium are considered rare-earth elements because they have ionic radii similar to the lighter f-block elements. These elements were called rare earths because they are simply more difficult to extract and separate individually than the most metals and, generally, they do not accumulate in minerals, they are rarely found in easily mined ores and are often unfavorably distributed in common ores/minerals. REEs show unique chemical and physical properties, in comparison to the other metals in the periodic table. Nowadays, these physicochemical properties are utilized in a wide range of synthetic, catalytic, electronic, medicinal, and military applications. Because of their applications, the global demand for rare earth metals is becoming progressively more important in the transition to a self-sustaining society and greener economy. However, due to the difficult separation between lanthanoid ions, the high cost and pollution of these processes, the scientists search the development of a method that combines selectivity and quantitative separation of lanthanoids from the leaching liquor, while being more economical and environmentally friendly processes. This motivation has favored the design and development of more efficient and environmentally friendly cation extractors with the incorporation of compounds as ionic liquids, membrane inclusion polymers (PIM) and supramolecular systems. Supramolecular chemistry focuses on the development of host-guest systems, in which a host molecule can recognize and bind a certain guest molecule or ion. Normally, the formation of a host-guest complex involves non-covalent interactions Additionally, host-guest interactions can be influenced among others effects by the structural nature of host and guests. The different macrocyclic hosts for lanthanoid species that have been studied are crown ethers, cyclodextrins, cucurbituryls, calixarenes and pillararenes.Among all the factors that can influence and affect lanthanoid (III) coordination, perhaps the most basic of them is the systematic control using macrocyclic substituents that promote a selective coordination. In this sense, macrocycles pillar[n]arenes (P[n]As) present a relatively easy functionalization and they have more π-rich cavity than other host molecules. This gives to P[n]As a negative electrostatic potential in the cavity which would be responsible for the selectivity of these compounds towards cations. Furthermore, the cavity size, the linker, and the functional groups of the polar headgroups could be modified in order to control the association of lanthanoid cations. In this sense, different P[n]As systems, specifically derivatives of the pentamer P[5]A functionalized with amide, amine, phosphate and sulfate derivatives, have been designed in terms of experimental synthesis and molecular dynamics, and the interaction between these P[5]As and some lanthanoid ions such as La³+, Eu³+ and Lu³+ has been studied by physicochemical characterization by 1H-NMR, ITC and fluorescence in the case of Eu³+ systems. The molecular dynamics study of these systems was developed in hexane as solvent, also taking into account the lanthanoid ions mentioned above, and the respective comparison studies between the different ions.

Keywords: lanthanoids, macrocycles, pillar[n]arenes, rare-earth metal extraction, supramolecular chemistry, supramolecular complexes.

Procedia PDF Downloads 46

Authors: Ana Fonseca, Ana Gouveia, Edgar Ramalho, Rita Henriques, Filipa Figueiredo, João Nunes

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Due to persistent climate pressures, there is a need to find a resilient economic system that is regenerative in nature. Bioeconomy offers the possibility of replacing non-renewable and non-biodegradable materials derived from fossil fuels with ones that are renewable and biodegradable, while a Circular Economy aims at sustainable and resource-efficient operations. The term "Circular Bioeconomy", which can be summarized as all activities that transform biomass for its use in various product streams, expresses the interaction between these two ideas. Portugal has a very favourable context to promote a Circular Bioeconomy due to its variety of climates and ecosystems, availability of biologically based resources, location, and geomorphology. Recently, there have been political and legislative efforts to develop the Portuguese Circular Bioeconomy. The Action Plan for a Sustainable Bioeconomy, approved in 2021, is composed of five axes of intervention, ranging from sustainable production and the use of regionally based biological resources to the development of a circular and sustainable bioindustry through research and innovation. However, as some statistics show, Portugal is still far from achieving circularity. According to Eurostat, Portugal has circularity rates of 2.8%, which is the second lowest among the member states of the European Union. Some challenges contribute to this scenario, including sectorial heterogeneity and fragmentation, prevalence of small producers, lack of attractiveness for younger generations, and absence of implementation of collaborative solutions amongst producers and along value chains.Regarding the Portuguese industrial sector, there is a tendency towards complex bureaucratic processes, which leads to economic and financial obstacles and an unclear national strategy. Together with the limited number of incentives the country has to offer to those that pretend to abandon the linear economic model, many entrepreneurs are hesitant to invest the capital needed to make their companies more circular. Absence of disaggregated, georeferenced, and reliable information regarding the actual availability of biological resources is also a major issue. Low literacy on bioeconomy among many of the sectoral agents and in society in general directly impacts the decisions of production and final consumption. The WinBio project seeks to outline a strategic approach for the management of weaknesses/opportunities in the technology transfer process, given the reality of the territory, through road mapping and national and international benchmarking. The developed work included the identification and analysis of agents in the interior region of Portugal, natural endogenous resources, products, and processes associated with potential development. Specific flow of biological wastes, possible value chains, and the potential for replacing critical raw materials with bio-based products was accessed, taking into consideration other countries with a matured bioeconomy. The study found food industry, agriculture, forestry, and fisheries generate huge amounts of waste streams, which in turn provide an opportunity for the establishment of local bio-industries powered by this biomass. The project identified biological resources with potential for replication and applicability in the Portuguese context. The richness of natural resources and potentials known in the interior region of Portugal is a major key to developing the Circular Economy and sustainability of the country.

Keywords: circular bioeconomy, interior region of portugal, regional development., public policy

Procedia PDF Downloads 61

Authors: Joseph M. Rich, Vinay A. Duddalwar, Assad A. Oberai

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Prostate adenocarcinoma is the most common cancer in males, with osseous metastases as the commonest site of metastatic prostate carcinoma (mPC). Treatment monitoring is based on the evaluation and characterization of lesions on multiple imaging studies, including Computed Tomography (CT). Monitoring of the osseous disease burden, including follow-up of lesions and identification and characterization of new lesions, is a laborious task for radiologists. Deep learning algorithms are increasingly used to perform tasks such as identification and segmentation for osseous metastatic disease and provide accurate information regarding metastatic burden. Here, nnUNet was used to produce a model which can segment CT scan images of prostate adenocarcinoma vertebral bone metastatic lesions. nnUNet is an open-source Python package that adds optimizations to deep learning-based UNet architecture but has not been extensively combined with transfer learning techniques due to the absence of a readily available functionality of this method. The IRB-approved study data set includes imaging studies from patients with mPC who were enrolled in clinical trials at the University of Southern California (USC) Health Science Campus and Los Angeles County (LAC)/USC medical center. Manual segmentation of metastatic lesions was completed by an expert radiologist Dr. Vinay Duddalwar (20+ years in radiology and oncologic imaging), to serve as ground truths for the automated segmentation. Despite nnUNet’s success on some medical segmentation tasks, it only produced an average Dice Similarity Coefficient (DSC) of 0.31 on the USC dataset. DSC results fell in a bimodal distribution, with most scores falling either over 0.66 (reasonably accurate) or at 0 (no lesion detected). Applying more aggressive data augmentation techniques dropped the DSC to 0.15, and reducing the number of epochs reduced the DSC to below 0.1. Datasets have been identified for transfer learning, which involve balancing between size and similarity of the dataset. Identified datasets include the Pancreas data from the Medical Segmentation Decathlon, Pelvic Reference Data, and CT volumes with multiple organ segmentations (CT-ORG). Some of the challenges of producing an accurate model from the USC dataset include small dataset size (115 images), 2D data (as nnUNet generally performs better on 3D data), and the limited amount of public data capturing annotated CT images of bone lesions. Optimizations and improvements will be made by applying transfer learning and generative methods, including incorporating generative adversarial networks and diffusion models in order to augment the dataset. Performance with different libraries, including MONAI and custom architectures with Pytorch, will be compared. In the future, molecular correlations will be tracked with radiologic features for the purpose of multimodal composite biomarker identification. Once validated, these models will be incorporated into evaluation workflows to optimize radiologist evaluation. Our work demonstrates the challenges of applying automated image segmentation to small medical datasets and lays a foundation for techniques to improve performance. As machine learning models become increasingly incorporated into the workflow of radiologists, these findings will help improve the speed and accuracy of vertebral metastatic lesions detection.

Keywords: deep learning, image segmentation, medicine, nnUNet, prostate carcinoma, radiomics

Procedia PDF Downloads 67

Authors: Benjamin Thomas Greer, Grace Cotulla, Mandy Johnson

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Human trafficking is one of the fastest growing international crimes and human rights violations in the world. The United States Department of State (State Department) approximates some 800,000 to 900,000 people are annually trafficked across sovereign borders, with approximately 14,000 to 17,500 of these people coming into the United States. Today’s slavery is conducted by unscrupulous individuals who are often connected to organized criminal enterprises and transnational gangs, extracting huge monetary sums. According to the International Labour Organization (ILO), human traffickers collect approximately $32 billion worldwide annually. Surpassed only by narcotics dealing, trafficking of humans is tied with illegal arms sales as the second largest criminal industry in the world and is the fastest growing field in the 21st century. Perpetrators of this heinous crime abound. They are not limited to single or “sole practitioners” of human trafficking, but rather, often include Transnational Criminal Organizations (TCO), domestic street gangs, labor contractors, and otherwise seemingly ordinary citizens. Monetary gain is being elevated over territorial disputes and street gangs are increasingly operating in a collaborative effort with TCOs to further disguise their criminal activity; to utilizing their vast networks, in an attempt to avoid detection. Traffickers rely on a network of clandestine routes to sell their commodities with impunity. As law enforcement agencies seek to retard the expansion of transnational criminal organization’s entry into human trafficking, it is imperative that they develop reliable trafficking mapping of known exploitative routes. In a recent report given to the Mexican Congress, The Procuraduría General de la República (PGR) disclosed, from 2008 to 2010 they had identified at least 47 unique criminal networking routes used to traffic victims and that Mexico’s estimated domestic victims number between 800,000 adults and 20,000 children annually. Designing a reliable mapping system is a crucial step to effective law enforcement response and deploying a successful victim support system. Creating this mapping analytic is exceedingly difficult. Traffickers are constantly changing the way they traffic and exploit their victims. They swiftly adapt to local environmental factors and react remarkably well to market demands, exploiting limitations in the prevailing laws. This article will highlight how human trafficking has become one of the fastest growing and most high profile human rights violations in the world today; compile current efforts to map and illustrate trafficking routes; and will demonstrate how the proprietary analytical mapping analysis of point-source and destination-source mapping can help local law enforcement, governmental agencies and victim services providers effectively respond to the type and nature of trafficking to their specific geographical locale. Trafficking transcends state and international borders. It demands an effective and consistent cooperation between local, state, and federal authorities. Each region of the world has different impact factors which create distinct challenges for law enforcement and victim services. Our mapping system lays the groundwork for a targeted anti-trafficking response.

Keywords: human trafficking, mapping, routes, law enforcement intelligence

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Authors: Eylem Tas

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This empirical study aims to explore the development of students' entrepreneurial skills through problem-based learning within the context of university-industry collaborations (UICs) in curriculum co-design and co-delivery (CDD). The research question guiding this study is: "How do problem-based learning and university-industry collaborations influence the development of students' entrepreneurial skills in the context of curriculum co-design and co-delivery?” To address this question, the study was conducted in a big city in Germany and involved interviews with stakeholders from various industries, including the private sector, government agencies (govt), and non-governmental organizations (NGOs). These stakeholders had established collaborative partnerships with the targeted university for projects encompassing entrepreneurial development aspects in CDD. The study sought to gain insights into the intricacies and subtleties of UIC dynamics and their impact on fostering entrepreneurial skills. Qualitative content analysis, based on Mayring's guidelines, was employed to analyze the interview transcriptions. Through an iterative process of manual coding, 442 codes were generated, resulting in two main sections: "the role of problem-based learning and UIC in fostering entrepreneurship" and "challenges and requirements of problem-based learning within UIC for systematical entrepreneurship development.” The chosen experimental approach of semi-structured interviews was justified by its capacity to provide in-depth perspectives and rich data from stakeholders with firsthand experience in UICs in CDD. By enlisting participants with diverse backgrounds, industries, and company sizes, the study ensured a comprehensive and heterogeneous sample, enhancing the credibility of the findings. The first section of the analysis delved into problem-based learning and entrepreneurial self-confidence to gain a deeper understanding of UIC dynamics from an industry standpoint. It explored factors influencing problem-based learning, alignment of students' learning styles and preferences with the experiential learning approach, specific activities and strategies, and the role of mentorship from industry professionals in fostering entrepreneurial self-confidence. The second section focused on various interactions within UICs, including communication, knowledge exchange, and collaboration. It identified key elements, patterns, and dynamics of interaction, highlighting challenges and limitations. Additionally, the section emphasized success stories and notable outcomes related to UICs' positive impact on students' entrepreneurial journeys. Overall, this research contributes valuable insights into the dynamics of UICs and their role in fostering students' entrepreneurial skills. UICs face challenges in communication and establishing a common language. Transparency, adaptability, and regular communication are vital for successful collaboration. Realistic expectation management and clearly defined frameworks are crucial. Responsible data handling requires data assurance and confidentiality agreements, emphasizing the importance of trust-based relationships when dealing with data sharing and handling issues. The identified key factors and challenges provide a foundation for universities and industrial partners to develop more effective UIC strategies for enhancing students' entrepreneurial capabilities and preparing them for success in today's digital age labor market. The study underscores the significance of collaborative learning and transparent communication in UICs for entrepreneurial development in CDD.

Keywords: collaborative learning, curriculum co-design and co-delivery, entrepreneurial skills, problem-based learning, university-industry collaborations

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Authors: Asma'u Mahe, Abdullahi A. Imam, Adamu J. Alhassan, Nasiru Abdullahi, Sadiya A. Bichi, Nura Lawal, Kamaluddeen Babagana

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Malaria is a disease with global health significance. It is caused by parasites and transmitted by Anopheles mosquitoes. Increase in insecticide resistance threatens the disease vector control. The strength of selection pressure acting on a mosquito population in relation to insecticide resistance can be assess by determining the genetic diversity of a fragment spanning exon- 20 of IIS6 of the voltage gated sodium channel (VGSC). Larval samples reared to adulthood were identified and kdr (knock down resistance) profile was determined. The DNA sequences were used to assess the patterns of genetic differentiation by determining the levels of genetic variability between the Anopheles mosquitoes. Genetic differentiation of the Anopheles mosquitoes based on a portion of the voltage gated sodium channel gene was obtained. Polymorphisms were detected; sequence variation and analysis were presented as a phylogenetic tree. Phylogenetic tree of VGSC haplotypes was constructed for samples of the Anopheles mosquitoes using the maximum likelihood method in MEGA 6.0 software. DNA sequences were edited using BioEdit sequence editor. The edited sequences were aligned with reference sequence (Kisumu strain). Analyses were performed as contained in dnaSP 5.10. Results of genetic parameters of polymorphism and haplotype reconstruction were presented in count. Twenty sequences were used for the analysis. Regions selected were 1- 576, invariable (monomorphic) sites were 460 while variable (polymorphic) sites were 5 giving the number of total mutations observed in this study. Mutations obtained from the study were at codon 105: TTC- Phenylalanine replaces TCC- Serine, codon 513: TAG- Termination replaces TTG- Leucine, codon 153, 300 and 553 mutations were non-synonymous. From the constructed phylogenetic tree, some groups were shown to be closer with Exon20Gambiae Kisumu (Reference strain) having some genetic distance, while 5-Exon20Gambiae-F I13.ab1, 18-Exon20Gambiae-F C17.ab1, and 2-Exon20Gambiae-F C13.ab1 clustered together genetically differentiated away from others. Mutations observed in this study can be attributed to the high insecticide resistance profile recorded in the study areas. Haplotype networks of pattern of genetic variability and polymorphism for the fragment of the VGSC sequences of sampled Anopheles mosquitoes revealed low haplotypes for the present study. Haplotypes are set of closely linked DNA variation on X-chromosome. Haplotypes were scaled accordingly to reflect their respective frequencies. Low haplotype number, four VGSC-1014F haplotypes were observed in this study. A positive association was previously established between low haplotype number of VGSC diversity and pyrethroid resistance through kdr mechanism. Significant values at (P < 0.05) of Tajima D and Fu and Li D’ were observed for some of the results indicating possible signature of positive selection on the fragment of VGSC in the study. This is the first report of VGSC-1014F in the study site. Based on the results, the mutation was present in low frequencies. However, the roles played by the observed mutations need further investigation. Mutations, environmental factors among others can affect genetic diversity. The study area has recorded increase in insecticide resistance that can affect vector control in the area. This finding might affect the efforts made against malaria. Sequences were deposited in GenBank for Accession Number.

Keywords: anopheles mosquitoes, insecticide resistance, kdr, malaria, voltage gated sodium channel

Procedia PDF Downloads 22

Authors: Irmak Karaduman, Tugba Corlu, Sezin Galioglu, Burcu Akata, M. Ali Yildirim, Aytunç Ateş, Selim Acar

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Breath analysis represents a promising non-invasive, fast and cost-effective alternative to well-established diagnostic and monitoring techniques such as blood analysis, endoscopy, ultrasonic and tomographic monitoring. Portable, non-invasive, and low-cost breath analysis devices are becoming increasingly desirable for monitoring different diseases, especially asthma. Beacuse of this, NO gas sensing at low concentrations has attracted progressive attention for clinical analysis in asthma. Recently, nanomaterials based sensors are considered to be a promising clinical and laboratory diagnostic tool, because its large surface–to–volume ratio, controllable structure, easily tailored chemical and physical properties, which bring high sensitivity, fast dynamic processand even the increasing specificity. Among various nanomaterials, semiconducting metal oxides are extensively studied gas-sensing materials and are potential sensing elements for breathanalyzer due to their high sensitivity, simple design, low cost and good stability.The sensitivities of metal oxide semiconductor gas sensors can be enhanced by adding noble metals. Doping contents, distribution, and size of metallic or metal oxide catalysts are key parameters for enhancing gas selectivity as well as sensitivity. By manufacturing doping MOS structures, it is possible to develop more efficient sensor sensing layers. Zeolites are perhaps the most widely employed group of silicon-based nanoporous solids. Their well-defined pores of sub nanometric size have earned them the name of molecular sieves, meaning that operation in the size exclusion regime is possible by selecting, among over 170 structures available, the zeolite whose pores allow the pass of the desired molecule, while keeping larger molecules outside.In fact it is selective adsorption, rather than molecular sieving, the mechanism that explains most of the successful gas separations achieved with zeolite membranes. In view of their molecular sieving and selective adsorption properties, it is not surprising that zeolites have found use in a number of works dealing with gas sensing devices. In this study, the Cu doped ZnO nanostructure film was produced by SILAR method and investigated the NO gas sensing properties. To obtain the selectivity of the sample, the gases including CO,NH3,H2 and CH4 were detected to compare with NO. The maximum response is obtained at 85 C for 20 ppb NO gas. The sensor shows high response to NO gas. However, acceptable responses are calculated for CO and NH3 gases. Therefore, there are no responses obtain for H2 and CH4 gases. Enhanced to selectivity, Cu doped ZnO nanostructure film was coated with zeolite A thin film. It is found that the sample possess an acceptable response towards NO hardly respond to CO, NH3, H2 and CH4 at room temperature. This difference in the response can be expressed in terms of differences in the molecular structure, the dipole moment, strength of the electrostatic interaction and the dielectric constant. The as-synthesized thin film is considered to be one of the extremely promising candidate materials in electronic nose applications. This work is supported by The Scientific and Technological Research Council of Turkey (TUBİTAK) under Project No, 115M658 and Gazi University Scientific Research Fund under project no 05/2016-21.

Keywords: Cu doped ZnO, electrical characterization, gas sensing, zeolite

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Authors: Eduardo Rodrigues, Gisela Mendes, José M. Torres, José E. Sousa

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In the sequence of the liberalisation of the electricity sector a progressive engagement of consumers has been considered and targeted by sector regulatory policies. With the objective of promoting market competition while protecting consumers interests, by transferring some of the upstream benefits to the end users while reaching a fair distribution of system costs, different market models to value consumers’ demand flexibility at the energy community level are envisioned. Local Energy and Flexibility Markets (LEFM) involve stakeholders interested in providing or procure local flexibility for community, services and markets’ value. Under the scope of DOMINOES, a European research project supported by Horizon 2020, the local market concept developed is expected to: • Enable consumers/prosumers empowerment, by allowing them to value their demand flexibility and Distributed Energy Resources (DER); • Value local liquid flexibility to support innovative distribution grid management, e.g., local balancing and congestion management, voltage control and grid restoration; • Ease the wholesale market uptake of DER, namely small-scale flexible loads aggregation as Virtual Power Plants (VPPs), facilitating Demand Response (DR) service provision; • Optimise the management and local sharing of Renewable Energy Sources (RES) in Medium Voltage (MV) and Low Voltage (LV) grids, trough energy transactions within an energy community; • Enhance the development of energy markets through innovative business models, compatible with ongoing policy developments, that promote the easy access of retailers and other service providers to the local markets, allowing them to take advantage of communities’ flexibility to optimise their portfolio and subsequently their participation in external markets. The general concept proposed foresees a flow of market actions, technical validations, subsequent deliveries of energy and/or flexibility and balance settlements. Since the market operation should be dynamic and capable of addressing different requests, either prioritising balancing and prosumer services or system’s operation, direct procurement of flexibility within the local market must also be considered. This paper aims to highlight the research on the definition of suitable DR models to be used by the Distribution System Operator (DSO), in case of technical needs, and by the retailer, mainly for portfolio optimisation and solve unbalances. The models to be proposed and implemented within relevant smart distribution grid and microgrid validation environments, are focused on day-ahead and intraday operation scenarios, for predictive management and near-real-time control respectively under the DSO’s perspective. At local level, the DSO will be able to procure flexibility in advance to tackle different grid constrains (e.g., demand peaks, forecasted voltage and current problems and maintenance works), or during the operating day-to-day, to answer unpredictable constraints (e.g., outages, frequency deviations and voltage problems). Due to the inherent risks of their active market participation retailers may resort to DR models to manage their portfolio, by optimising their market actions and solve unbalances. The interaction among the market actors involved in the DR activation and in flexibility exchange is explained by a set of sequence diagrams for the DR modes of use from the DSO and the energy provider perspectives. • DR for DSO’s predictive management – before the operating day; • DR for DSO’s real-time control – during the operating day; • DR for retailer’s day-ahead operation; • DR for retailer’s intraday operation.

Keywords: demand response, energy communities, flexible demand, local energy and flexibility markets

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Authors: Ho-Ting Wu, Kai-Wei Ke, Bo-Yu Huang, Liang-Lin Yan, Chun-Ting Lin

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With the advances in advanced technology, wireless sensor network (WSN) has become one of the most promising candidates to implement the wireless industrial internet of things (IIOT) architecture. However, the legacy IEEE 802.15.4 based WSN technology such as Zigbee system cannot meet the stringent QoS requirement of low powered, real-time, and highly reliable transmission imposed by the IIOT environment. Recently, the IEEE society developed IEEE 802.15.4e Time Slotted Channel Hopping (TSCH) access mode to serve this purpose. Furthermore, the IETF 6TiSCH working group has proposed standards to integrate IEEE 802.15.4e with IPv6 protocol smoothly to form a complete protocol stack for IIOT. In this work, we develop key network technologies for IEEE 802.15.4e based wireless IIoT architecture, focusing on practical design and system implementation. We realize the OpenWSN-based wireless IIOT system. The system architecture is divided into three main parts: web server, network manager, and sensor nodes. The web server provides user interface, allowing the user to view the status of sensor nodes and instruct sensor nodes to follow commands via user-friendly browser. The network manager is responsible for the establishment, maintenance, and management of scheduling and topology information. It executes centralized scheduling algorithm, sends the scheduling table to each node, as well as manages the sensing tasks of each device. Sensor nodes complete the assigned tasks and sends the sensed data. Furthermore, to prevent scheduling error due to packet loss, a schedule inspection mechanism is implemented to verify the correctness of the schedule table. In addition, when network topology changes, the system will act to generate a new schedule table based on the changed topology for ensuring the proper operation of the system. To enhance the system performance of such system, we further propose dynamic bandwidth allocation and distributed scheduling mechanisms. The developed distributed scheduling mechanism enables each individual sensor node to build, maintain and manage the dedicated link bandwidth with its parent and children nodes based on locally observed information by exchanging the Add/Delete commands via two processes. The first process, termed as the schedule initialization process, allows each sensor node pair to identify the available idle slots to allocate the basic dedicated transmission bandwidth. The second process, termed as the schedule adjustment process, enables each sensor node pair to adjust their allocated bandwidth dynamically according to the measured traffic loading. Such technology can sufficiently satisfy the dynamic bandwidth requirement in the frequently changing environments. Last but not least, we propose a packet retransmission scheme to enhance the system performance of the centralized scheduling algorithm when the packet delivery rate (PDR) is low. We propose a multi-frame retransmission mechanism to allow every single network node to resend each packet for at least the predefined number of times. The multi frame architecture is built according to the number of layers of the network topology. Performance results via simulation reveal that such retransmission scheme is able to provide sufficient high transmission reliability while maintaining low packet transmission latency. Therefore, the QoS requirement of IIoT can be achieved.

Keywords: IEEE 802.15.4e, industrial internet of things (IIOT), scheduling mechanisms, wireless sensor networks (WSN)

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Authors: Mary Isobelle Mullaney

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The maxim "an unexamined life is not worth living," attributed to Socrates, prompts a contemplative reflection spanning over 32 years as a teacher educator in the Republic of Ireland. Taking time to contemplate the changes that have occurred and the current landscape provides valuable insights into the dynamic terrain of teacher preparation. The reflective journey traverses the impacts of global and societal shifts, responding to challenges, embracing advancements, and navigating the delicate balance between responsiveness to the world and the active shaping of it. The transformative events of the COVID-19 pandemic spotlighted the indispensable role of teachers in Ireland, reinforcing the critical nature of education for the well-being of pupils. Research solidifies the understanding that teachers matter and so it is worth exploring the pivotal role of the teacher educator. This reflective piece examines the changes in teacher education and explores the juxtapositions that have emerged in response to three decades of profound change. The attractiveness of teaching as a career is juxtaposed against the reality of the demands of the job, with conditions for public servants in Ireland undergoing a shift. High-level strategic discussions about increasing teacher numbers now contrast with a previous oversupply. The delicate balance between the imperative to increase enrolment (getting "bums on seats") and the gatekeeper role of teacher educators is explored, raising questions about maintaining high standards amid changing student profiles. Another poignant dichotomy involves the high demand for teachers versus the hurdles candidates face in becoming teachers. The rising cost and duration of teacher education courses raise concerns about attracting quality candidates. The perceived attractiveness of teaching as a career contends with the reality of increased demands on educators. One notable juxtaposition centres around the rapid evolution of Irish initial teacher education versus the potential risk of change overload. The Teaching Council of Ireland has spearheaded considerable changes, raising questions about the timing and evaluation of these changes. This reflection contemplates the vision of a professional teaching council versus its evolving reality and the challenges posed by the value placed on school placement in teacher preparation. The juxtapositions extend to the classroom, where theory may not seamlessly align with the lived experience. Inconsistencies between college expectations and the classroom reality prompt reflection on the effectiveness of teacher preparation programs. Addressing the changing demographic landscape of society and schools, there is a persistent incongruity between the diversity of Irish society and the profile of second-level teachers. As education undergoes a digital revolution, the enduring philosophies of education confront technological advances. This reflection highlights the tension between established practices and contemporary demands, acknowledging the irreplaceable value of face-to-face interaction while integrating technology into teacher training programs. In conclusion, this reflective journey encapsulates the intricate web of juxtapositions in Irish Initial Teacher Education. It emphasises the enduring commitment to fostering education, recognising the profound influence educators wield, and acknowledging the challenges and gratifications inherent in shaping the minds and futures of generations to come.

Keywords: Irish post primary teaching, juxtapositions, reflection, teacher education

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Authors: Martin Alexander Eder, Sergei Semenov

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Many glass-epoxy composite structures, such as large utility wind turbine rotor blades (WTBs), comprise of adhesive joints with typically thick bond lines used to connect the different components during assembly. Performance optimization of rotor blades to increase power output by simultaneously maintaining high stiffness-to-low-mass ratios entails intricate geometries in conjunction with complex anisotropic material behavior. Consequently, adhesive joints in WTBs are subject to multiaxial stress states with significant stress gradients depending on the local joint geometry. Moreover, the dynamic aero-elastic interaction of the WTB with the airflow generates non-proportional, variable amplitude stress histories in the material. Empiricism shows that a prominent failure type in WTBs is high cycle fatigue failure of adhesive bond line interfaces, which in fact over time developed into a design driver as WTB sizes increase rapidly. Structural optimization employed at an early design stage, therefore, sets high demands on computationally efficient interface fatigue models capable of predicting the critical locations prone for interface failure. The numerical stress-based interface fatigue model presented in this work uses the Drucker-Prager criterion to compute three different damage indices corresponding to the two interface shear tractions and the outward normal traction. The two-parameter Drucker-Prager model was chosen because of its ability to consider shear strength enhancement under compression and shear strength reduction under tension. The governing interface damage index is taken as the maximum of the triple. The damage indices are computed through the well-known linear Palmgren-Miner rule after separate rain flow-counting of the equivalent shear stress history and the equivalent pure normal stress history. The equivalent stress signals are obtained by self-similar scaling of the Drucker-Prager surface whose shape is defined by the uniaxial tensile strength and the shear strength such that it intersects with the stress point at every time step. This approach implicitly assumes that the damage caused by the prevailing multiaxial stress state is the same as the damage caused by an amplified equivalent uniaxial stress state in the three interface directions. The model was implemented as Python plug-in for the commercially available finite element code Abaqus for its use with solid elements. The model was used to predict the interface damage of an adhesively bonded, tapered glass-epoxy composite cantilever I-beam tested by LM Wind Power under constant amplitude compression-compression tip load in the high cycle fatigue regime. Results show that the model was able to predict the location of debonding in the adhesive interface between the webfoot and the cap. Moreover, with a set of two different constant life diagrams namely in shear and tension, it was possible to predict both the fatigue lifetime and the failure mode of the sub-component with reasonable accuracy. It can be concluded that the fidelity, robustness and computational efficiency of the proposed model make it especially suitable for rapid fatigue damage screening of large 3D finite element models subject to complex dynamic load histories.

Keywords: adhesive, fatigue, interface, multiaxial stress

Procedia PDF Downloads 140