Search results for: stochastic dynamic programming

Authors: Hyejin Song, Jin Baek

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Based on the idea of bricolage that a new meaning beyond that of each of objects can be created through combination and juxtaposition of various objets, this study finds a way of morphological-recomposing of urban space through combination and juxtaposition of existing urban fabric and new fabric and suggests this idea as new direction of urban regeneration. This study sets concept of bricolage as a philosophical ground of interpreting contemporary urban situation. In this concept, urban objects such as buildings from various zeitgeists are positively considered as potential textures which can construct meaningful context. Seoul, as the city having long history and experiencing colonization and development, appears dynamic urban structure full of various objects from various periods. However, in contrast with successful plazas and streets in Europe, objects in Seoul do not make a meaningful context as public space due to thoughtless development. This study defines this situation as ‘disorgnized-fabric’. Following the concept of bricolage, to find the way for those existing scattered objects to be organized as a context of meaningful public space, this study firstly researches the case of successful public space by morphological analysis. Secondly, this study carefully explores urban space in Seoul, and draws figure-ground diagram to grasp the form of current urban fabric by various urban-objects. As a result of exploration, a lot of urban spaces from Myeong-dong, one of vibrant commercial district in Seoul, to declining residential area are judged as having potential fabric which can become meaningful context by just small adjustment of relationship between existing objects. This study also confirmed that by inserting a new object with consideration of form of existing fabric, it is possible to accord a new context as plaza to existing void which have broken as several parts. This study defines it as form-based urban reconstruction through the idea of bricolage, and suggests that it could be one of philosophical ground of successful urban regeneration.

Keywords: adjustment of relationship between existing objets, bricolage, morphological analysis of urban fabric, urban regeneration, urban reconstruction

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Authors: Bidzina Matsaberidze, Anna Sikharulidze, Gia Sirbiladze, Bezhan Ghvaberidze

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In the modern world emergency management decision support systems are actively used by state organizations, which are interested in extreme and abnormal processes and provide optimal and safe management of supply needed for the civil and military facilities in geographical areas, affected by disasters, earthquakes, fires and other accidents, weapons of mass destruction, terrorist attacks, etc. Obviously, these kinds of extreme events cause significant losses and damages to the infrastructure. In such cases, usage of intelligent support technologies is very important for quick and optimal location-transportation of emergency service in order to avoid new losses caused by these events. Timely servicing from emergency service centers to the affected disaster regions (response phase) is a key task of the emergency management system. Scientific research of this field takes the important place in decision-making problems. Our goal was to create an expert knowledge-based intelligent support system, which will serve as an assistant tool to provide optimal solutions for the above-mentioned problem. The inputs to the mathematical model of the system are objective data, as well as expert evaluations. The outputs of the system are solutions for Fuzzy Multi-Objective Emergency Location-Transportation Problem (FMOELTP) for disasters’ regions. The development and testing of the Intelligent Support System were done on the example of an experimental disaster region (for some geographical zone of Georgia) which was generated using a simulation modeling. Four objectives are considered in our model. The first objective is to minimize an expectation of total transportation duration of needed products. The second objective is to minimize the total selection unreliability index of opened humanitarian aid distribution centers (HADCs). The third objective minimizes the number of agents needed to operate the opened HADCs. The fourth objective minimizes the non-covered demand for all demand points. Possibility chance constraints and objective constraints were constructed based on objective-subjective data. The FMOELTP was constructed in a static and fuzzy environment since the decisions to be made are taken immediately after the disaster (during few hours) with the information available at that moment. It is assumed that the requests for products are estimated by homeland security organizations, or their experts, based upon their experience and their evaluation of the disaster’s seriousness. Estimated transportation times are considered to take into account routing access difficulty of the region and the infrastructure conditions. We propose an epsilon-constraint method for finding the exact solutions for the problem. It is proved that this approach generates the exact Pareto front of the multi-objective location-transportation problem addressed. Sometimes for large dimensions of the problem, the exact method requires long computing times. Thus, we propose an approximate method that imposes a number of stopping criteria on the exact method. For large dimensions of the FMOELTP the Estimation of Distribution Algorithm’s (EDA) approach is developed.

Keywords: epsilon-constraint method, estimation of distribution algorithm, fuzzy multi-objective combinatorial programming problem, fuzzy multi-objective emergency location/transportation problem

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Authors: Salim Al Harthy, Alexandre A. Bachkirov

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This study delves into the complexities of competitive aggressiveness in the oil and gas industry, focusing on the characteristics of the identified competitive actions. The current quantitative research on competitive aggressiveness lacks agreement on the connection between antecedents and outcomes, prompting a qualitative investigation. To address this gap, the research utilizes qualitative interviews with CEOs from Oman's oil and gas service industry to explore the dynamics of competitive aggressiveness. Using Noklenain's typology, the study categorizes and analyzes identified actions, shedding light on the spectrum of competitive behaviors within the industry. Notably, actions predominantly fall under the "Bring about" and "Preserve" elements, with a notable absence in the "Forebear" and "Destroy" categories, possibly linked to the study's focus on service-oriented businesses. The study also explores the detectability of actions, revealing that "Bring about" actions are detectable, while those in "Preserve" and "Suppress" are not. This challenges conventional definitions of competitive aggressiveness, suggesting that not all actions are readily detectable despite being considered competitive. The presence of non-detectable actions introduces complexity to measurement methods reliant on visible empirical data. Moreover, the study contends that companies can adopt an aggressive competitive approach without directly challenging rivals. This challenges traditional views and emphasizes the innovative and entrepreneurial aspects of actions not explicitly aimed at competitors. By not revealing strategic intentions, such actions put rivals at a disadvantage, underscoring the need for a nuanced understanding of competitive aggressiveness. In summary, the lack of consensus in existing literature regarding the relationship between antecedents and outcomes in competitive aggressiveness is addressed. The study reveals a spectrum of detectable and undetectable actions, posing challenges in measurement and emphasizing the need for alternative methods to assess undetectable actions in competitive behavior. This research contributes to a more nuanced understanding of competitive aggressiveness, acknowledging the diverse actions shaping a company's strategic positioning in dynamic business environments.

Keywords: competitive aggressiveness, qualitative exploration, noklenain's typology, oil and gas industry

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Authors: Kevin A. Droguett, Edwin G. Pérez, Denis Fuentealba, Margarita E. Aliaga, Angélica M. Fierro

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Supramolecular chemistry is a field of growing interest. Moreover, studying the formation of host-guest complexes between macrocycles and dyes is highly attractive due to their potential applications. Examples of the above are drug delivery, catalytic process, and sensing, among others. There are different dyes of interest in the literature; one example is the quinolinone derivatives. Those molecules have good optical properties and chemical and thermal stability, making them suitable for developing fluorescent probes. Secondly, several macrocycles can be seen in the literature. One example is the cucurbiturils. This water-soluble macromolecule family has a hydrophobic cavity and two identical carbonyl portals. Additionally, the thermodynamic analysis of those supramolecular systems could help understand the affinity between the host and guest, their interaction, and the main stabilization energy of the complex. In this work, two 7-(diethylamino) quinoline-2 (1H)-one derivative (QD1-2) and their interaction with cucurbit[7]uril (CB[7]) were studied from an experimental and in-silico point of view. For the experimental section, the complexes showed a 1:1 stoichiometry by HRMS-ESI and isothermal titration calorimetry (ITC). The inclusion of the derivatives on the macrocycle lends to an upward shift in the fluorescence intensity, and the pKa value of QD1-2 exhibits almost no variation after the formation of the complex. The thermodynamics of the inclusion complexes was investigated using ITC; the results demonstrate a non-classical hydrophobic effect with a minimum contribution from the entropy term and a constant binding on the order of 106 for both ligands. Additionally, dynamic molecular studies were carried out during 300 ns in an explicit solvent at NTP conditions. Our finding shows that the complex remains stable during the simulation (RMSD ~1 Å), and hydrogen bonds contribute to the stabilization of the systems. Finally, thermodynamic parameters from MMPBSA calculations were obtained to generate new computational insights to compare with experimental results.

Keywords: host-guest complexes, molecular dynamics, quinolin-2(1H)-one derivatives dyes, thermodynamics

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Authors: Kaushik Sathupadi, Sandesh Achar

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Pervasive computing is a growing research field that aims to acknowledge human physical life routines (HPLR) based on body-worn sensors such as MEMS sensors-based technologies. The use of these technologies for human activity recognition is progressively increasing. On the other hand, personalizing human life routines using numerous machine-learning techniques has always been an intriguing topic. In contrast, various methods have demonstrated the ability to recognize basic movement patterns. However, it still needs to be improved to anticipate the dynamics of human living patterns. This study introduces state-of-the-art techniques for recognizing static and dy-namic patterns and forecasting those challenging activities from multi-fused sensors. Further-more, numerous MEMS signals are extracted from one self-annotated IM-WSHA dataset and two benchmarked datasets. First, we acquired raw data is filtered with z-normalization and denoiser methods. Then, we adopted statistical, local binary pattern, auto-regressive model, and intrinsic time scale decomposition major features for feature extraction from different domains. Next, the acquired features are optimized using maximum relevance and minimum redundancy (mRMR). Finally, the artificial neural network is applied to analyze the whole system's performance. As a result, we attained a 90.27% recognition rate for the self-annotated dataset, while the HARTH and KU-HAR achieved 83% on nine living activities and 90.94% on 18 static and dynamic routines. Thus, the proposed HPLR system outperformed other state-of-the-art systems when evaluated with other methods in the literature.

Keywords: artificial intelligence, machine learning, gait analysis, local binary pattern (LBP), statistical features, micro-electro-mechanical systems (MEMS), maximum relevance and minimum re-dundancy (MRMR)

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Authors: Sabika Khalid, Endale Fantahun Tadesse

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Unlike other professional sectors, a great deal of studies has addressed the overwhelming gender disparity phenomena in the early childhood education (ECE) workforce, which is acknowledged for the dominance of women over men teachers. The irony of ECE being a gendered working environment is not only observed in societies that are ruled by gender roles but also in Western countries that claim to margin the gender gap in several professions. The participation of male teachers in ECE across most countries ranged from 1% to 3% of the total preschool or kindergarten teachers. When it comes to a dynamic Chinese society tempered with a deep-rooted tradition and cultural ideology, the ECE has no less place for males, and males have a low place for ECE. According to the Ministry of Education of China (2020), there are over 5 million kindergarten teachers and staff members, while only 2.3% are accounted for male teachers. The traditional gender-based discourse asserts that giving care and guidance for young children related to nurturing ‘mothering’ labels the profession in ECE as women’s work derived from originated from their ‘naturality.’ Although a large volume of evidence sheds light on the cause for low male teachers, the perception of parents, female teachers working with male teachers, and the experience of male teachers working in ECE, less is known and understood before being a teacher. Hence, this study argues that the promotion of the involvement of male teachers in light of their masculinity identity asset in the children's learning environment is comprehended to understand the construction of male student teachers' (preservice) professional identity during early childhood teacher training that allows obtaining substantial evidence that provides a feasible and robust implication in the preparation of competent and professional male preschool teachers that understand, cherish, and bring harmony in Chinese ECE through professionalism socialization with the stakeholders. This study intended to reveal male ECE preservice teachers’ knowledge of their professional identity, i.e., how they perceive themselves as a teacher and what factors agents these perceptions towards their professional identity.

Keywords: male teachers, Early Childhood Education (ECE), self-identity, perception of stakeholders

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Authors: Vistorina Amputu, Katja Tielboerger, Nichola Knox

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Primary productivity in dry savannahs is constraint by moisture availability and under increasing anthropogenic pressure. Thus, considering climate change and the unprecedented pace and scale of rangeland deterioration, methods for assessing the status of such rangelands should be easy to apply, yield reliable and repeatable results that can be applied over large spatial scales. Global and local scale monitoring of rangelands through satellite data and labor-intensive field measurements respectively, are limited in accurately assessing the spatiotemporal heterogeneity of vegetation dynamics to provide crucial information that detects degradation in its early stages. Fortunately, newly emerging techniques such as unmanned aerial vehicles (UAVs), associated miniaturized sensors and improving digital photogrammetric software provide an opportunity to transcend these limitations. Yet, they have not been extensively calibrated in natural systems to encompass their complexities if they are to be integrated for long-term monitoring. Limited research using drone technology has been conducted in arid savannas, for example to assess the health status of this dynamic two-layer vegetation ecosystem. In our study, we fill this gap by testing the relationship between UAV-estimated cover of rangeland functional attributes and field data collected in discrete sample plots in a Namibian dryland savannah along a degradation gradient. The first results are based on a supervised classification performed on the ultra-high resolution multispectral imagery to distinguish between rangeland functional attributes (bare, non-woody, and woody), with a relatively good match to the field observations. Integrating UAV-based observations to improve rangeland monitoring could greatly assist in climate-adapted rangeland management.

Keywords: arid savannah, degradation gradient, field observations, narrow-band sensor, supervised classification

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Authors: Yusuf Ersoy Yildirim, Ismail Tas, Ceren Gorgusen, Tugba Yeter, Aysegul Boyacioglu, K. Mehmet Tugrul, Murat Tugrul, Ayten Namli, H. Sabri Ozturk, M. Onur Akca

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In recent years, a lot of research has been done for the sustainable use of scarce resources in the world. Especially, effective and sustainable use of water resources has been researched for many years. Sub-surface drip irrigation (SDI) is one of the most effective irrigation methods in which efficient and sustainable use of irrigation water can be achieved. When the literature is taken into consideration, it is often emphasized that, besides its numerous advantages, it also allows the application of irrigation water to the plant root zone along with air. It is stated in different studies that the air applied to the plant root zone with irrigation water has a positive effect on the root zone. Plants need sufficient oxygen for root respiration as well as for the metabolic functions of the roots. Decreased root respiration due to low oxygen content reduces transpiration, disrupts the flow of ions, and increases the ingress of salt reaching toxic levels, seriously affecting plant growth. Lack of oxygen (Hypoxia) can affect the survival of plants. The lack of oxygen in the soil is related to the exchange of gases in the soil with the gases in the atmosphere. Soil aeration is an important physical parameter of a soil. It is highly dynamic and is closely related to the amount of water in the soil and its bulk weight. Subsurface drip irrigation; It has higher water use efficiency compared to irrigation methods such as furrow irrigation and sprinkler irrigation. However, in heavy clay soils, subsurface drip irrigation creates continuous wetting fronts that predispose the rhizosphere region to hypoxia or anoxia. With subsurface drip irrigation, the oxygen is limited for root microbial respiration and root development, with the continuous spreading of water to a certain region of the root zone. In this study, the change in sugar beet yield caused by air application in the SDI system will be explained.

Keywords: sugar beet, subsurface drip irrigation, air application, irrigation efficiency

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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

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Authors: Mehrdad Abkenari, Orod Zarrinkafsh, Mohsen Ramezan Shirazi

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Construction projects initiate in complicated dynamic environments and, due to the close relationships between project parameters and the unknown outer environment, they are faced with several uncertainties and risks. Success in time, cost and quality in large scale construction projects is uncertain in consequence of technological constraints, large number of stakeholders, too much time required, great capital requirements and poor definition of the extent and scope of the project. Projects that are faced with such environments and uncertainties can be well managed through utilization of the concept of risk management in project’s life cycle. Although the concept of risk is dependent on the opinion and idea of management, it suggests the risks of not achieving the project objectives as well. Furthermore, project’s risk analysis discusses the risks of development of inappropriate reactions. Since evaluation and prioritization of construction projects has been a difficult task, the network structure is considered to be an appropriate approach to analyze complex systems; therefore, we have used this structure for analyzing and modeling the issue. On the other hand, we face inadequacy of data in deterministic circumstances, and additionally the expert’s opinions are usually mathematically vague and are introduced in the form of linguistic variables instead of numerical expression. Owing to the fact that fuzzy logic is used for expressing the vagueness and uncertainty, formulation of expert’s opinion in the form of fuzzy numbers can be an appropriate approach. In other words, the evaluation and prioritization of construction projects on the basis of risk factors in real world is a complicated issue with lots of ambiguous qualitative characteristics. In this study, evaluated and prioritization the risk parameters and factors with fuzzy logy method by combination of three method DEMATEL (Decision Making Trial and Evaluation), ANP (Analytic Network Process) and TOPSIS (Technique for Order-Preference by Similarity Ideal Solution) on Construction Management.

Keywords: fuzzy logy, risk, prioritization, assessment

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Authors: Munaza Mubeen

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The colonial Urdu literature has played a significant role in uplifting the overall status of the Indians. Taking example of the Bhopal State, the contribution of the Royal ladies holds no match in the contemporary age. Similarly, the efforts of the Begamat-e-Bhopal in the field of education had been acknowledged across the Sub-continent. It had been noticed that with the downfall of the Mughal Empire at the hands of the British Raj, the local culture in the Indian sub-continent in general and in Bhopal State in proper got deteriorated. This led to uncertainty, chaos and an anti-British sentiment which created hatred against them in the entire sub-continent. Likely, in Bhopal State, the role of women in field of education also vanished. However, this change was felt by the ladies in the Royal Household where they struggled for restoration of the status quo with their personal efforts. The prominent contributors from the Royal household included Qudseya Begum, Nawab Sikander Begum, Nawab Shah Jahan Begum and Nawab Sultan Johan-they are known as Begamat-i-Bhopal. They established schools, colleges and universities to impart formal and non-formal education respectively. Their systematic approach and continued efforts constituted a dynamic aspect of women’ empowerment. Focused on the female education, however, one of the by-products of their efforts was an introduction of socio-cultural and politico-religious awareness among the middle class womenfolk. Unfortunately, the role of these Bagamat-i-Bhopal has been left untouched or ignored by the academic scholars. This study critically analyzed the role of Beghamat-i-Bhopal regarding female education in Hindustan in general and in Bhopal in particular. Similarly, the contribution of the contemporary writers in development of female education in Bhopal has also been discussed in this paper. This paper is based on the 'historico-textual' approach following structural reason which has established a justifiable argument. The researcher, therefore, has taken into consideration all the chronological nuances in order to accord greater visibility to the contents. The data has been described, analyzed and interpreted inclusively and in generalized manner.

Keywords: colonialism, Begamaat e Bhopal, female education, State of Bhopal

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Authors: M. Schapira, S. Françoise, F. Maheux, O. Pierre-Duplessix, E. Rabiller, B. Simon, R. Le Gendre

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Pico- and nano-phytoplankton are abundant and ecologically critical components of the autotrophic communities in the pelagic realm. While the role of physical forcing related to tidal cycle, water mass intrusion, nutrient availability, mixing and stratification on microphytoplankton blooms have been widely investigated, these are often overlooked for pico- and nano-phytoplankton especially in estuarine waters. This study investigates changes in abundances and community composition of pico- and nano-phytoplankton under different estuarine tidal conditions in the mouth of the Seine River in relation to nutrient availability, water column stratification and spatially localized currents. Samples were collected each day at high tide, over spring tide to neap tide cycle, from 21 stations homogeneously distributed in the Seine river month in May 2011. Vertical profiles of temperature, salinity and fluorescence were realized at each sampling station. Sub-surface water samples (i.e. 1 m depth) were collected for nutrients (i.e. N, P and Si), phytoplankton biomass (i.e. Chl a) and pico- and nano-phytoplankton enumeration and identification. Pico- and nano-phytoplankton populations were identified and quantified using flow cytometry. Total abundances tend to decrease from spring tide to neap tide. Samples were characterized by high abundances of Synechococcus and Cryptophyceae. The composition of the pico- and nano-phytoplankton varied greatly under the different estuarine tidal conditions. Moreover, at the scale of the river mouth, the pico- and nano-phytoplankton population exhibited patchy distribution patterns that were closely controlled by water mass intrusion from the Sea, freshwater inputs from the Seine River and the geomorphology of the river mouth. This study highlights the importance of physical forcing to the community composition of pico- and nano-phytoplankton that may be critical for the structure of the pelagic food webs in estuarine and adjacent coastal seas.

Keywords: nanophytoplancton, picophytoplankton, physical forcing, river mouth, tidal cycle

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Authors: Maryam S. Ghoraishi, John E. Hawk, Thomas Thundat

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Understanding liquid properties in small scale has become important in recent decades as immerging new microelectromechanical systems (MEMS) devices have been widely used for micro pumps, drug delivery, and many other laboratory-on-microchips analysis. Often in microfluidic devices, fluids are transported electrokinetically. Therefore, extensive knowledge of fluid flow, heat transport, electrokinetics and electrochemistry are key to successful lab on a chip design. Among different microfluidic devices, recently developed hollow channel cantilever offers an ideal platform to study different fluid properties simultaneously without drastic decrease in quality factor which normally occurs when traditional cantilevers operate in the liquid phase. Using hollow channel cantilever, we monitor changes in density and viscosity of liquid while simultaneously investigating dielectric properties of alcohol water binary mixtures. Considerable research has been conducted on alcohol-water mixtures since such a mixture is a typical prototype for biomolecules, Micelle formation, and structural stability of proteins (to name a few). Here we show that hollow channel cantilever can be employed to investigate dielectric properties of ethanol/water mixtures in different concentrations. We study dynamic amplitude shifts of hollow channel cantilever oscillation at different concentrations of ethanol/water for different voltages. Our results show how interactions between solute and solvent, and possibly cluster formation, could change dielectric properties and dipole reorientation of the mixture, as well as the resulting force on the hollow cantilever. For comparison, we also examine higher conductivity ionic mixtures of sodium sulfate solution under the same conditions as low conductivity ethanol/water mixtures. We will show the results from systematic investigation of solvent effects on dielectric properties of the binary mixture. We will also address the question of resolution limits in dielectric study of analyte molecules imposed by solvent concentrations.

Keywords: dielectric constant, cantilever sensors, ethanol water mixtures, low frequency

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Authors: M. R. Vijayakumar, Sanjay Kumar Singh, Lakshmi, Hithesh Dewangan, Sanjay Singh

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Trans resveratrol (RES) is a natural molecule proved for cancer preventive and therapeutic activities devoid of any potential side effects. However, the therapeutic application of RES in disease management is limited because of its rapid elimination from blood circulation thereby low biological half life in mammals. Therefore, the main objective of this study is to enhance the circulation as well as therapeutic efficacy using PEGylated liposomes. D-α-tocopheryl polyethylene glycol 1000 succinate (vitamin E TPGS) is applied as steric surface decorating agent to prepare RES liposomes by thin film hydration method. The prepared nanoparticles were evaluated by various state of the art techniques such as dynamic light scattering (DLS) technique for particle size and zeta potential, TEM for shape, differential scanning calorimetry (DSC) for interaction analysis and XRD for crystalline changes of drug. Encapsulation efficiency and invitro drug release were determined by dialysis bag method. Cancer cell viability studies were performed by MTT assay, respectively. Pharmacokinetic studies were performed in sprague dawley rats. The prepared liposomes were found to be spherical in shape. Particle size and zeta potential of prepared formulations varied from 64.5±3.16 to 262.3±7.45 nm and -2.1 to 1.76 mV, respectively. DSC study revealed absence of potential interaction. XRD study revealed presence of amorphous form in liposomes. Entrapment efficiency was found to be 87.45±2.14 % and the drug release was found to be controlled up to 24 hours. Minimized MEC in MTT assay and tremendous enhancement in circulation time of RES PEGylated liposomes than its pristine form revealed that the stearic stabilized PEGylated liposomes can be an alternative tool to commercialize this molecule for chemopreventive and therapeutic applications in cancer.

Keywords: trans resveratrol, cancer nanotechnology, long circulating liposomes, bioavailability enhancement, liposomes for cancer therapy, PEGylated liposomes

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Authors: Daniel Karthik, Vijay Baheti, Jiri Militky, Sundaramurthy Palanisamy

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Fibre based nano particles are presently considered as one of the potential filler materials for the improvement of mechanical and physical properties of polymer composites. Due to high matrix-filler interfacial area there will be uniform and homogeneous dispersion of nanoparticles. In micro/nano filler reinforced composites, resin material is usually tailored by organic or inorganic nanoparticles to have improved matrix properties. The objective of this study was to compare the potential of reinforcement of different organic and inorganic micro/nano fillers in epoxy composites. Industrial and agricultural waste of fibres like Agave Americana, cornhusk, jute, basalt, carbon, glass and fly ash was utilized to prepare micro/nano particles. Micro/nano particles were obtained using high energy planetary ball milling process in dry condition. Milling time and ball size were kept constant throughout the ball milling process. Composites were fabricated by hand lay method. Particle loading was kept constant to 3% wt. for all composites. In present study, loading of fillers was selected as 3 wt. % for all composites. Dynamic mechanical properties of the nanocomposite films were performed in three-point bending mode with gauge length and sample width of 50 mm and 10 mm respectively. The samples were subjected to an oscillating frequency of 1 Hz, 5 Hz and 10 Hz and 100 % oscillating amplitude in the temperature ranges of 30°C to 150°C at the heating rate of 3°C/min. Damping was found to be higher with the jute composites. Amongst organic fillers lowest damping factor was observed with Agave Americana particles, this means that Agave americana fibre particles have betters interface adhesion with epoxy resin. Basalt, fly ash and glass particles have almost similar damping factors confirming better interface adhesion with epoxy.

Keywords: ball milling, damping factor, matrix-filler interface, particle reinforcements

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Authors: Singh Divya, Rohan Singh, Anjana Pandey

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Reviewers' Comments: The study provides valuable insights into the anti-pneumonia properties of flavonoids against LytB. Authors could further validate findings through in vitro studies and consider exploring combination therapies for enhanced efficacy Response: Thankyou for your valuable comments. This study has been conducted further via experimental validation of the in-silico findings. The study uses Streptococcus pneumoniae D39 strain and examine the anti-pneumonia effect of kaempferol, quercetin and apigenin at various concentrations ranging from 9ug/ml to 200ug/ml. From results, it can be concluded that the kaempferol has shown the highest cytotoxic effect (72.1% of inhibition) against S. pneumoniae at concentration of 40ug/ml compare to apigenin and quercetin. The treatment of S. pneumoniae with concoction of kaempferol, quercetin and apigenin has also been performed, it is noted that conc. of 200ug/ml was most effect in achieving 75% inhibition. As S. pneumoniae D39 is a virulent encapsulated strain, the capsule interferes with the uptake of large size drug formulation. For instance, S. pneumoniae D39 with kaempferol and gold nano urchin (GNU) formulation, but the large size of GNU has resulted in reduced cytotoxic effect of kaempferol (27%). To achieve near 100% cytotoxic effect on the MDR S. pneumoniae D39 strain, the study will target the development of kaempferol-engineered gold nano-urchin’ conjugates, where gold nanocrystal will be of small size (less than or equal to 5nm) and decorated with hydroxyl, sulfhydryl, carboxyl, amine and groups. This approach is expected to enhance the anti-pneumonia effect of kaempferol (polyhydroxylated flavonoid). The study will also examine the interactive study among lung epithelial cell line (A549), kaempferol-engineered gold nano urchins, and S. pneumoniae for exploring the colonization, invasion, and biofilm formation of S. pneumoniae on A549 cells resembling the upper respiratory surface of humans.

Keywords: streptococcus pneumoniae, β-endo-Acetylglucosaminidase, apigenin, quercetin kaempferol, molecular dynamic simulation, interactome study and GROMACS

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: S. Gokul Prassad, S. Aakash, K. Malar Mohan

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In the process to cope with the challenges faced by the automobile industry in providing ride comfort, the electronics and control systems play a vital role. The control systems in an automobile monitor various parameters, controls the performances of the systems, thereby providing better handling characteristics. The automobile suspension system is one of the main systems that ensure the safety, stability and comfort of the passengers. The system is solely responsible for the isolation of the entire automobile from harmful road vibrations. Thus, integration of the control systems in the automobile suspension system would enhance its performance. The diverse road conditions of India demand the need of an efficient suspension system which can provide optimum ride comfort in all road conditions. For any passenger vehicle, the design of the suspension system plays a very important role in assuring the ride comfort and handling characteristics. In recent years, the air suspension system is preferred over the conventional suspension systems to ensure ride comfort. In this article, the ride comfort of the adaptive suspension system is compared with that of the passive suspension system. The schema is created in MATLAB/Simulink environment. The system is controlled by a proportional integral differential controller. Tuning of the controller was done with the Particle Swarm Optimization (PSO) algorithm, since it suited the problem best. Ziegler-Nichols and Modified Ziegler-Nichols tuning methods were also tried and compared. Both the static responses and dynamic responses of the systems were calculated. Various random road profiles as per ISO 8608 standard are modelled in the MATLAB environment and their responses plotted. Open-loop and closed loop responses of the random roads, various bumps and pot holes are also plotted. The simulation results of the proposed design are compared with the available passive suspension system. The obtained results show that the proposed adaptive suspension system is efficient in controlling the maximum over shoot and the settling time of the system is reduced enormously.

Keywords: automobile suspension, MATLAB, control system, PID, PSO

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Authors: Aleksandra Szurlej-Kielanska, Lucyna Pilacka, Dariusz Górecki

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The dynamic development of wind energy requires the simultaneous implementation of effective systems minimizing the risk of collisions between birds and wind turbines. Wind turbines are installed in more and more challenging locations, often close to the natural environment of birds. More and more countries and organizations are defining guidelines for the necessary functionality of such systems. The minimum bird detection distance, trajectory tracking, and shutdown time are key factors in eliminating collisions. Since 2020, we have continued the survey on the validation of the subsequent version of the BPS detection and reaction system. Bird protection system (BPS) is a fully automatic camera system which allows one to estimate the distance of the bird to the turbine, classify its size and autonomously undertake various actions depending on the bird's distance and flight path. The BPS was installed and tested in a real environment at a wind turbine in northern Poland and Central Spain. The performed validation showed that at a distance of up to 300 m, the BPS performs at least as well as a skilled ornithologist, and large bird species are successfully detected from over 600 m. In addition, data collected by BPS systems installed in Spain showed that 60% of the detections of all birds of prey were from individuals approaching the turbine, and these detections meet the turbine shutdown criteria. Less than 40% of the detections of birds of prey took place at wind speeds below 2 m/s while the turbines were not working. As shown by the analysis of the data collected by the system over 12 months, the system classified the improved size of birds with a wingspan of more than 1.1 m in 90% and the size of birds with a wingspan of 0.7 - 1 m in 80% of cases. The collected data also allow the conclusion that some species keep a certain distance from the turbines at a wind speed of over 8 m/s (Aquila sp., Buteo sp., Gyps sp.), but Gyps sp. and Milvus sp. remained active at this wind speed on the tested area. The data collected so far indicate that BPS is effective in detecting and stopping wind turbines in response to the presence of birds of prey with a wingspan of more than 1 m.

Keywords: protecting birds, birds monitoring, wind farms, green energy, sustainable development

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Authors: Sonal Tuljaram Kame

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Growth and development is based on proper diet. A balanced diet contains all the nutrients in required quantum. Although physical growth is completed by young adulthood, the body tissues remain in a dynamic state with catabolism slightly exceeding anabolism, resulting in a net decrease in the number of cells. After the years of adolescence which cause upheavals in the life of the person, the individual struggle to emerge as an adult who know who he is and what his goals are. During this period nutrients are needed for maintaining the health and energy is required for physical functions and physical activities. The nutritional requirement in young adulthood differs from other periods of life. Iron is needed for haemoglobin synthesis and necessitates by the considerable examination of blood volume. Young adult girls need to ensure adequate intake of iron as they loose 0.5 mg/day by way of menstruation. This is complete awareness about nutritional and health on the other side there is widespread ignorance about nutrition and health among young adult girls. The young adult girls who are aware about nutrition and health seem to be very conscious about nutritional intake and health. Figure consciousness and fear of obesity leads to self imposed intake of nutrients. It may result in various health problems. The study was planned to investigate nutrient intake, find relation between nutritional intake, clinical examination score and health status of young adult girls. The present study is based on the data collected from 120 young adult girls studying in four different competitive exams coaching academies in Akola city of Maharashtra. It was found that nutritional intake of these young adult girls was below the recommended level, nutritional knowledge level and nutritional intake are associated attributes, calories, calcium and protein intake is positively correlated with clinical examination and health status. It was concluded that well planned nutritional counseling for the young adult girls can help prevent nutritional deficiency diseases and disorders which may lead to anaemic condition in young adult girls. Girls need to be educated on intake of iron and vitamin B12.

Keywords: nutritional intake, health status, young adult girls, correlation studies

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Authors: Anna Rinaldi, Pierfrancesco Dellino

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COVID-19 vaccine hesitancy can be observed at different rates in different countries. In June 2021, 1,068 people were surveyed in France and Italy to inquire about individual potential acceptance, focusing on time preferences in a risk-return framework: having the vaccination today, in a month, and in 3 months; perceived risks of vaccination and COVID-19; and expected benefit of the vaccine. A randomized controlled trial was conducted to understand how everyday stimuli like fact-based news about vaccines impact an audience's acceptance of vaccination. The main experiment involved two groups of participants and two different articles about vaccine-related thrombosis taken from two Italian newspapers. One article used a more abstract description and language, and the other used a more anecdotal description and concrete language; each group read only one of these articles. Two other groups were assigned categorization tasks; one was asked to complete a concrete categorization task, and the other an abstract categorization task. Individual preferences for vaccination were found to be variable and unstable over time, and individual choices of accepting, refusing, or delaying could be affected by the way news is written. In order to understand these dynamic preferences, the present work proposes a new model based on seven categories of human behaviors that were validated by a neural network. A treatment effect was observed: participants who read the articles shifted to vaccine hesitancy categories more than participants assigned to other treatments and control. Furthermore, there was a significant gender effect, showing that the type of language leading to a lower hesitancy rate for men is correlated with a higher hesitancy rate for women and vice versa. This outcome should be taken into consideration for an appropriate gender-based communication campaign aimed at achieving herd immunity. The trial was registered at ClinicalTrials.gov NCT05582564 (17/10/2022).

Keywords: vaccine hesitancy, risk elicitation, neural network, covid19

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Authors: Majid Aldalbahi

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In 2009, over 3.4 billion people in the world resided in urban areas as a result of rapid urban growth. This figure is estimated to increase to 6.5 billion by 2050. This urban growth phenomenon has raised challenges for many countries in both the developing and developed worlds. Urban growth is a complicated process involving the spatiotemporal changes of all socio-economic and physical components at different scales. The socio-economic components of urban growth are related to urban population growth and economic growth, while physical components of urban growth and economic growth are related to spatial expansion, land cover change and land use change which are the focus of this research. The interactions between these components are complex and no-linear. Several factors and forces cause these complex interactions including transportation and communication, internal and international migrations, public policies, high natural growth rates of urban populations and public policies. Urban growth has positive and negative consequences. The positive effects relates to planned and orderly urban growth, while negative effects relate to unplanned and scattered growth, which is called sprawl. Although urban growth is considered as necessary for sustainable urbanization, uncontrolled and rapid growth cause various problems including consumption of precious rural land resources at urban fringe, landscape alteration, traffic congestion, infrastructure pressure, and neighborhood conflicts. Traditional urban planning approaches in fast growing cities cannot accommodate the negative consequences of rapid urban growth. Microsimulation programme, and modelling techniques are effective means to provide new urban development, management and planning methods and approaches. This paper aims to use these techniques to understand and analyse the complex interactions for the case study of Riyadh city, a fast growing city in Saudi Arabia.

Keywords: policy implications, urban planning, traffic congestion, urban growth, Suadi Arabia, Riyadh

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Authors: Ngoc-Nguyen Nguyen, Hsiu-Ling Chen, Thanh-Truc Lai Huynh

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In foreign language learning, vocabulary acquisition has consistently posed challenges to learners, especially for those at lower levels. Conventional approaches often fail to promote vocabulary learning and ensure engaging experiences alike. The emergence of mobile learning, particularly the integration of chatbot systems, has offered alternative ways to facilitate this practice. Chatbots have proven effective in educational contexts by offering interactive learning experiences in a constructivist manner. These tools have caught attention in the field of mobile-assisted language learning (MALL) in recent years. This research is conducted in an English for Specific Purposes (ESP) course at the A2 level of the CEFR, designed for non-English majors. Participants are first-year Vietnamese students aged 18 to 20 at a university. This quasi-experimental study follows a pretest-posttest control group design over five weeks, with two classes randomly assigned as the experimental and control groups. The experimental group engages in chatbot-assisted spaced practice with SRL components, while the control group uses the same spaced practice without SRL. The two classes are taught by the same lecturer. Data are collected through pre- and post-tests, cognitive load surveys, and semi-structured interviews. The combination of self-regulated learning (SRL) and distributed practice, grounded in the spacing effect, forms the basis of the present study. SRL elements, which concern goal setting and strategy planning, are integrated into the system. The spaced practice method, similar to those used in widely recognized learning platforms like Duolingo and Anki flashcards, spreads out learning over multiple sessions. This study’s design features quizzes progressively increasing in difficulty. These quizzes are aimed at targeting both the Recognition-Recall and Comprehension-Use dimensions for a comprehensive acquisition of vocabulary. The mobile-based chatbot system is built using Golang, an open-source programming language developed by Google. It follows a structured flow that guides learners through a series of 4 quizzes in each week of teacher-led learning. The quizzes start with less cognitively demanding tasks, such as multiple-choice questions, before moving on to more complex exercises. The integration of SRL elements allows students to self-evaluate the difficulty level of vocabulary items, predict scores achieved, and choose appropriate strategy. This research is part one of a two-part project. The initial findings will determine the development of an upgraded chatbot system in part two, where adaptive features in response to the integration of SRL components will be introduced. The research objectives are to assess the effectiveness of the chatbot-assisted approach, based on the combination of spaced practice and SRL, in improving vocabulary acquisition and managing cognitive load, as well as to understand students' perceptions of this learning tool. The insights from this study will contribute to the growing body of research on mobile-assisted language learning and offer practical implications for integrating chatbot systems with spaced practice into educational settings to enhance vocabulary learning.

Keywords: mobile learning, mobile-assisted language learning, MALL, chatbots, vocabulary learning, spaced practice, spacing effect, self-regulated learning, SRL, self-regulation, EFL, cognitive load

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Authors: Borislava Dimitrova, Didem Kepir Savoly

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The movie analysis offers a dynamic and multifaceted lens in order to explore and understand various aspects of human behavior and relationship, emotion, and cognition. Cinema therapy can be an important tool for counselor education and counselors in therapy. Therefore, this paper aims to delve deeper into human relationships and individual behavior patterns and analyze some of their most vivid aspects in light of the transactional analysis and its main components. While describing certain human behaviors and emotional states in real life, sometimes it can be difficult even for mental health practitioners to become aware of the subtle social cues and hints that are being transmitted, often in a rushed and swift manner. To address this challenge, the current paper focuses on the relationship dynamics as conveyed through the plot of the movie “Sunset Boulevard”, and examines slightly exaggerated yet true-to-life examples. The movie was directed by Billy Wilder and written by Charles Brackett, Billy Wilder, and D.M. Marshman Jr. The scenes of interest were examined through Transactional Analysis concepts: the different ego states, strokes, the various kinds of transactions, the paradigm of games in transactional analysis, and lastly, with the help of the drama triangle. The addressed themes comprised mainly the way the main characters engaged in game playing, which eventually had a negative outcome on the sequences of interactions between the individuals and the desired payoffs that they craved as a result. Furthermore, counselor educators can use the result of this paper for educational purposes, such as for teaching theoretical knowledge about Transactional Analysis, and for utilizing characters’ interactions and behaviors as real-life situations that can serve as case studies and role-playing activities. Finally, the paper aims to foster the use of movies as materials for psychological analysis which can assist the teaching of new mental health professionals in the field.

Keywords: transactional analysis, movie analysis, drama triangle, games, ego-state

Procedia PDF Downloads 102

Authors: Hervice Roméo Fogno Fotsoa, Germaine Djuidje Kenmoe, Claude Vidal Aloyem Kazé

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One of the main applications of machine learning is the prediction of time series. But a more accurate prediction requires a more optimal model of machine learning. Several optimization techniques have been developed, but without considering the input variables disposition of the system. Thus, this work aims to present a new machine learning architecture optimization technique based on their optimal input variables disposition. The validations are done on the prediction of wind time series, using data collected in Cameroon. The number of possible dispositions with four input variables is determined, i.e., twenty-four. Each of the dispositions is used to perform the prediction, with the main criteria being the training and prediction performances. The results obtained from a static architecture and a dynamic architecture of neural networks have shown that these performances are a function of the input variable's disposition, and this is in a different way from the architectures. This analysis revealed that it is necessary to take into account the input variable's disposition for the development of a more optimal neural network model. Thus, a new neural network training algorithm is proposed by introducing the search for the optimal input variables disposition in the traditional back-propagation algorithm. The results of the application of this new optimization approach on the two single neural network architectures are compared with the previously obtained results step by step. Moreover, this proposed approach is validated in a collaborative optimization method with a single objective optimization technique, i.e., genetic algorithm back-propagation neural networks. From these comparisons, it is concluded that each proposed model outperforms its traditional model in terms of training and prediction performance of time series. Thus the proposed optimization approach can be useful in improving the accuracy of time series forecasts. This proves that the proposed optimization approach can be useful in improving the accuracy of time series prediction based on machine learning.

Keywords: input variable disposition, machine learning, optimization, performance, time series prediction

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Authors: Sonam Chorol, Sharvan Kumar, Pritam Mukhopadhyay

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In biology, supramolecular systems require the use of chemical fuels to stay in sustained nonequilibrium steady states termed dissipative self-assembly in contrast to synthetic self-assembly. Biomimicking these natural dynamic systems, some studies have demonstrated artificial self-assembly under nonequilibrium utilizing various forms of energies (fuel) such as chemical, redox, and pH. Naphthalene diimides (NDIs) are well-known organic molecules in supramolecular architectures with high electron affinity and have applications in controlled electron transfer (ET) reactions, etc. Herein, we report the endergonic ET from tetraphenylborate to highly electron-deficient phosphonium NDI²+ dication to generate NDI•+ radical. The formation of radicals was confirmed by UV-Vis-NIR absorption spectroscopy. Electron-donor and electron-acceptor energy levels were calculated from experimental electrochemistry and theoretical DFT analysis. The HOMO of the electron donor locates below the LUMO of the electro-acceptor. This indicates that electron transfer is endergonic (ΔE°ET = negative). The endergonic ET from NaBPh₄ to NDI²+ dication was achieved thermodynamically by the formation of coupled biphenyl product confirmed by GC-MS analysis. NDI molecule bearing octyl phosphonium at the core and H-bond forming imide moieties at the axial position forms a gel. The rheological properties of purified radical ion NDI⦁+ gels were evaluated. The atomic force microscopy studies reveal the formation of large branching-type networks with a maximum height of 70-80 nm. The endergonic ET from NaBPh₄ to NDI²+ dication was used to design the assembly and disassembly redox reaction cycle using reducing (NaBPh₄) and oxidizing agents (Br₂) as chemical fuels. A part of NaBPh₄ is used to drive assembly, while a fraction of the NaBPh₄ is dissipated by forming a useful product. The system goes back to the disassembled NDI²+ dication state with the addition of Br₂. We think bioinspired dissipative self-assembly is the best approach to developing future lifelike materials with autonomous behavior.

Keywords: Ionic-gel, redox-cycle, self-assembly, useful product

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Authors: Maureen Royce, Joshi Jariwala, Sally Kah

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Change is inevitable, but the change process is progressive. Organisational change is the process in which an organisation changes strategies, operational methods, systems, culture, and structure to affect something different in the organisation. This process can be continuous or developed over a period and driven by internal and external factors. Organisational change is essential if organisations are to survive in dynamic and uncertain environments. However, evidence from research shows that many change initiatives fail, leading to severe consequences for organisations and their resources. The complex models of third sector organisations, i.e., social enterprise, compounds the levels of change in these organisations. Interestingly, innovation is associated with a change in social enterprises due to the hybridity of product and service development. Furthermore, the creation of social intervention has offered a new process and outcomes to the lifecycle of change. Therefore, different forms of organisational innovation are developed, i.e., total, evolutionary, expansionary, and developmental, which affect the interventions of social enterprises. This raises both theoretical and business concerns on how the competing hybrid nature of social enterprises change, how change is managed, and the impact on these organisations. These perspectives present critical questions for further investigation. In this study, we investigate the impact of organisational change on employees and organisational development at DaDaFest –a disability arts organisation with a social focus based in Liverpool. The three main objectives are to explore the drivers of change and the implementation process; to examine the impact of organisational change on employees and; to identify barriers to organisation change and development. To address the preceding research objectives, qualitative research design is adopted using semi-structured interviews. Data is analysed using a six-step thematic analysis framework, which enables the study to develop themes depicting the impact of change on employees and organisational development. This study presents theoretical and practical contributions for academics and practitioners. The knowledge contributions encapsulate the evolution of change and the change cycle in a social enterprise. However, practical implications provide critical insights into the change management process and the impact of change on employees and organisational development.

Keywords: organisational change, change management, organisational change system, social enterprise

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Authors: A. Aulinger, A. M. Backes, J. Bieser, V. Matthias, M. Quante

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High concentrations of particles pose a threat to human health. Thus, legal maximum concentrations of PM10 and PM2.5 in ambient air have been steadily decreased over the years. In central Europe, the inorganic species ammonium sulphate and ammonium nitrate make up a large fraction of fine particles. Many studies investigate the influence of emission reductions of sulfur- and nitrogen oxides on aerosol concentration. Here, we focus on the influence of ammonia (NH3) emissions. While emissions of sulphate and nitrogen oxides are quite well known, ammonia emissions are subject to high uncertainty. This is due to the uncertainty of location, amount, time of fertilizer application in agriculture, and the storage and treatment of manure from animal husbandry. For this study, we implemented a crop growth model into the SMOKE emission model. Depending on temperature, local legislation, and crop type individual temporal profiles for fertilizer and manure application are calculated for each model grid cell. Additionally, the diffusion from soils and plants and the direct release from open and closed barns are determined. The emission data was used as input for the Community Multiscale Air Quality (CMAQ) model. Comparisons to observations from the EMEP measurement network indicate that the new ammonia emission module leads to a better agreement of model and observation (for both ammonia and ammonium). Finally, the ammonia emission model was used to create emission scenarios. This includes emissions based on future European legislation, as well as a dynamic evaluation of the influence of different agricultural sectors on particle formation. It was found that a reduction of ammonia emissions by 50% lead to a 24% reduction of total PM2.5 concentrations during winter time in the model domain. The observed reduction was mainly driven by reduced formation of ammonium nitrate. Moreover, emission reductions during winter had a larger impact than during the rest of the year.

Keywords: ammonia, ammonia abatement strategies, ctm, seasonal impact, secondary aerosol formation

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Authors: Lonna Mabandla, Godfrey Musvoto

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Transportation is a catalytic feature in cities. Transport and land use activity are interdependent and have a feedback loop between how land is developed and how transportation systems are designed and used. This recursive relationship between land use and transportation is reflected in how public transportation routes internal to the inner-city enhance accessibility, therefore creating spaces that are conducive to business activity, while the business activity also informs public transportation routes. It is for this reason that the focus of this research is on public transportation within inner-city areas where the dynamic is evident. Durban is the chosen case study where the dominating form of public transportation within the central business district (CBD) is minibus taxis. The paradox here is that minibus taxis still form part of the informal economy even though they are the leading form of public transportation in South Africa. There have been many attempts to formalise this industry to follow more regulatory practices, but minibus taxis are privately owned, therefore complicating any proposed intervention. The argument of this study is that the application of collaborative planning through a sustainable partnership between the public and private sectors will improve the social and environmental sustainability of public transportation. One of the major challenges that exist within such collaborative endeavors is power dynamics. As a result, a key focus of the study is on power relations. Practically, power relations should be observed over an extended period, specifically when the different stakeholders engage with each other, to reflect valid data. However, a lengthy data collection process was not possible to observe during the data collection phase of this research. Instead, interviews were conducted focusing on existing procedural planning practices between the inner-city minibus taxi association (South and North Beach Taxi Association), the eThekwini Transport Authority (ETA), and the eThekwini Town Planning Department. Conclusions and recommendations were then generated based on these data.

Keywords: collaborative planning, sustainability, public transport, minibus taxis

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Authors: Maciej Jedrzejczyk, Karolina Marzantowicz

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Traditional utility value chain is being transformed during last few years into unbundled markets. Increased distributed generation of energy is one of considerable challenges faced by Smart Grid networks. New sources of energy introduce volatile demand response which has a considerable impact on traditional middlemen in E&U market. The purpose of this research is to search for ways to allow near-real-time electricity markets to transact with surplus energy based on accurate time synchronous measurements. A proposed framework evaluates the use of secure peer-2-peer (P2P) communication and distributed transaction ledgers to provide flat hierarchy, and allow real-time insights into present and forecasted grid operations, as well as state and health of the network. An objective is to achieve dynamic grid operations with more efficient resource usage, higher security of supply and longer grid infrastructure life cycle. Methods used for this study are based on comparative analysis of different distributed ledger technologies in terms of scalability, transaction performance, pluggability with external data sources, data transparency, privacy, end-to-end security and adaptability to various market topologies. An intended output of this research is a design of a framework for safer, more efficient and scalable Smart Grid network which is bridging a gap between traditional components of the energy network and individual energy producers. Results of this study are ready for detailed measurement testing, a likely follow-up in separate studies. New platforms for Smart Grid achieving measurable efficiencies will allow for development of new types of Grid KPI, multi-smart grid branches, markets, and businesses.

Keywords: autonomous agents, Distributed computing, distributed ledger technologies, large scale systems, micro grids, peer-to-peer networks, Self-organization, self-stabilization, smart grids

Procedia PDF Downloads 300