Search results for: simplified conceptual models

Authors: Marcela Dávalos López

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In Mexico, the distribution of hygienistarchitecture during the 20th century had different rhythms. The culmination of the urban hygiene system (from sewers to showers, passing through garbage collection) forced neighbors and citizens to participate in the common welfare. This turned the urban references and dissociated the ways of living and led to comfort and health. However, the contrast between two Mexicancities, Cuernavaca and Mexico City shows us very different cultural practices regarding the use of hygienicarchitectures: in the first, thenature of its deepravines marked the destiny of residential architecture, while in Mexico City, state participation alteredthelandscape and homogenized the architectural models of domestic and intímate spaces.

Keywords: Cultural Practices, Dissociated Ways To Comfort, Hygiene Architecture , Mexico

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Authors: Ruchika Goyal, Ashwani Kumar, Sandeep Jain

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The experimental data for anticancer potential of curcumin nanoparticles was calculated by means of eclectic data. The optimal descriptors were examined using Monte Carlo method based CORAL SEA software. The statistical quality of the model is following: n = 14, R² = 0.6809, Q² = 0.5943, s = 0.175, MAE = 0.114, F = 26 (sub-training set), n =5, R²= 0.9529, Q² = 0.7982, s = 0.086, MAE = 0.068, F = 61, Av Rm² = 0.7601, ∆R²m = 0.0840, k = 0.9856 and kk = 1.0146 (test set) and n = 5, R² = 0.6075 (validation set). This data can be used to build predictive QSAR models for anticancer activity.

Keywords: anticancer potential, curcumin, model, nanoparticles, optimal descriptors, QSAR

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Authors: Esha Banerjee, Atul Kumar Ojha, Girish Nath Jha

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This study aims to develop an intonation labeled database for Hindi. Although no single standard for prosody labeling exists in Hindi, researchers in the past have employed perceptual and statistical methods in literature to draw inferences about the behavior of prosody patterns in Hindi. Based on such existing research and largely agreed upon intonational theories in Hindi, this study attempts to develop a manually annotated prosodic corpus of Hindi speech data, which can be used for training speech models for natural-sounding speech in the future. 100 sentences ( 500 words) each for declarative and interrogative types have been labeled using Praat.

Keywords: speech dataset, Hindi, intonation, labeled corpus

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Authors: Laila Oubahman, Duleba Szabolcs

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Public transport stakeholders aim to increase the ridership ratio by encouraging citizens to use common transportation modes. For this sight, improving service quality is a crucial option to reach the quality desired by users and reduce the gap between desired and perceived quality. Multi-criteria decision aid has been applied in literature in recent decades because it provides efficient models to assess the most impacting criteria on the overall assessment. In this paper, the PROMETHEE method is combined with the best-worst approach to construct a consensual model that avoids rank reversal to support stakeholders in ameliorating service quality.

Keywords: best-worst method, MCDA, PROMETHEE, public transport

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Authors: K. O'Malley

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Background: The emergence and rapid evolution of large language models (LLMs) (i.e., models of generative artificial intelligence, or AI) has been unprecedented. ChatGPT is one of the most widely used LLM platforms. Using natural language processing technology, it generates customized responses to user prompts, enabling it to mimic human conversation. Responses are generated using predictive modeling of vast internet text and data swathes and are further refined and reinforced through user feedback. The popularity of LLMs is increasing, with a growing number of students utilizing these platforms for study and revision purposes. Notwithstanding its many novel applications, LLM technology is inherently susceptible to bias and error. This poses a significant challenge in the educational setting, where academic integrity may be undermined. This study aims to evaluate the performance of the latest iteration of ChatGPT (ChatGPT4.0) in standardized state medical licensing examinations. Methods: A considered search strategy was used to interrogate the PubMed electronic database. The keywords ‘ChatGPT’ AND ‘medical education’ OR ‘medical school’ OR ‘medical licensing exam’ were used to identify relevant literature. The search included all peer-reviewed literature published in the past five years. The search was limited to publications in the English language only. Eligibility was ascertained based on the study title and abstract and confirmed by consulting the full-text document. Data was extracted into a Microsoft Excel document for analysis. Results: The search yielded 345 publications that were screened. 225 original articles were identified, of which 11 met the pre-determined criteria for inclusion in a narrative synthesis. These studies included performance assessments in national medical licensing examinations from the United States, United Kingdom, Saudi Arabia, Poland, Taiwan, Japan and Germany. ChatGPT 4.0 achieved scores ranging from 67.1 to 88.6 percent. The mean score across all studies was 82.49 percent (SD= 5.95). In all studies, ChatGPT exceeded the threshold for a passing grade in the corresponding exam. Conclusion: The capabilities of ChatGPT in standardized academic assessment in medicine are robust. While this technology can potentially revolutionize higher education, it also presents several challenges with which educators have not had to contend before. The overall strong performance of ChatGPT, as outlined above, may lend itself to unfair use (such as the plagiarism of deliverable coursework) and pose unforeseen ethical challenges (arising from algorithmic bias). Conversely, it highlights potential pitfalls if users assume LLM-generated content to be entirely accurate. In the aforementioned studies, ChatGPT exhibits a margin of error between 11.4 and 32.9 percent, which resonates strongly with concerns regarding the quality and veracity of LLM-generated content. It is imperative to highlight these limitations, particularly to students in the early stages of their education who are less likely to possess the requisite insight or knowledge to recognize errors, inaccuracies or false information. Educators must inform themselves of these emerging challenges to effectively address them and mitigate potential disruption in academic fora.

Keywords: artificial intelligence, ChatGPT, generative ai, large language models, licensing exam, medical education, medicine, university

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Authors: Olfat A. Mohamed

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Rhamnolipids biosurfactants have distinct properties given them importance in many industrial applications, especially their great new future applications in cosmetic and pharmaceutical industries. These applications have encouraged the search for diverse and renewable resources to control the cost of production. The experimental results were then applied to find a suitable mathematical model for obtaining the design criteria of the batch bioreactor. This research aims to produce Rhamnolipids from different oily wastewater sources such as petroleum crude oil (PO) and vegetable oil (VO) by using Pseudomonas aeruginosa ATCC 9027. Different concentrations of the PO and the VO are added to the media broth separately are in arrangement (0.5 1, 1.5, 2, 2.5 % v/v) and (2, 4, 6, 8 and 10%v/v). The effect of the initial concentration of oil residues and the addition of glycerol and palmitic acid was investigated as an inducer in the production of rhamnolipid and the surface tension of the broth. It was found that 2% of the waste (PO) and 6% of the waste (VO) was the best initial substrate concentration for the production of rhamnolipids (2.71, 5.01 g rhamnolipid/l) as arrangement. Addition of glycerol (10-20% v glycerol/v PO) to the 2% PO fermentation broth led to increase the rhamnolipid production (about 1.8-2 times fold). However, the addition of palmitic acid (5 and 10 g/l) to fermentation broth contained 6% VO rarely enhanced the production rate. The experimental data for 2% initially (PO) was used to estimate the various kinetic parameters. The following results were obtained, maximum rate or velocity of reaction (Vmax) = 0.06417 g/l.hr), yield of cell weight per unit weight of substrate utilized (Yx/s = 0.324 g Cx/g Cs) maximum specific growth rate (μmax = 0.05791 hr⁻¹), yield of rhamnolipid weight per unit weight of substrate utilized (Yp/s)=0.2571gCp/g Cs), maintenance coefficient (Ms =0.002419), Michaelis-Menten constant, (Km=6.1237 gmol/l), endogenous decay coefficient (Kd=0.002375 hr⁻¹). Predictive parameters and advanced mathematical models were applied to evaluate the time of the batch bioreactor. The results were as follows: 123.37, 129 and 139.3 hours in respect of microbial biomass, substrate and product concentration, respectively compared with experimental batch time of 120 hours in all cases. The expected mathematical models are compatible with the laboratory results and can, therefore, be considered as tools for expressing the actual system.

Keywords: batch bioreactor design, glycerol, kinetic parameters, petroleum crude oil, Pseudomonas aeruginosa, rhamnolipids biosurfactants, vegetable oil

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Authors: Valentina Marutyan

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Healthcare data mining is a rapidly developing field at the intersection of technology and medicine that has the potential to change our understanding and approach to providing healthcare. Healthcare and data mining is the process of examining huge amounts of data to extract useful information that can be applied in order to improve patient care, treatment effectiveness, and overall healthcare delivery. This field looks for patterns, trends, and correlations in a variety of healthcare datasets, such as electronic health records (EHRs), medical imaging, patient demographics, and treatment histories. To accomplish this, it uses advanced analytical approaches. Predictive analysis using historical patient data is a major area of interest in healthcare data mining. This enables doctors to get involved early to prevent problems or improve results for patients. It also assists in early disease detection and customized treatment planning for every person. Doctors can customize a patient's care by looking at their medical history, genetic profile, current and previous therapies. In this way, treatments can be more effective and have fewer negative consequences. Moreover, helping patients, it improves the efficiency of hospitals. It helps them determine the number of beds or doctors they require in regard to the number of patients they expect. In this project are used models like logistic regression, random forests, and neural networks for predicting diseases and analyzing medical images. Patients were helped by algorithms such as k-means, and connections between treatments and patient responses were identified by association rule mining. Time series techniques helped in resource management by predicting patient admissions. These methods improved healthcare decision-making and personalized treatment. Also, healthcare data mining must deal with difficulties such as bad data quality, privacy challenges, managing large and complicated datasets, ensuring the reliability of models, managing biases, limited data sharing, and regulatory compliance. Finally, secret code of data mining in healthcare helps medical professionals and hospitals make better decisions, treat patients more efficiently, and work more efficiently. It ultimately comes down to using data to improve treatment, make better choices, and simplify hospital operations for all patients.

Keywords: data mining, healthcare, big data, large amounts of data

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Authors: Mario Perez-Won, Roberto Lemus-Mondaca, Constanza Olivares-Rivera, Fernanda Marin-Monardez

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This research presents the simultaneous application of high hydrostatic pressure (HHP) and osmotic dehydration (DO) as a pretreatment to hot –air drying of jumbo squid (Dosidicus gigas) cubes. The drying time was reduced to 2 hours at 60ºC and 5 hours at 40°C as compared to the jumbo squid samples untreated. This one was due to osmotic pressure under high-pressure treatment where increased salt saturation what caused an increasing water loss. Thus, a more reduced time during convective drying was reached, and so water effective diffusion in drying would play an important role in this research. Different working conditions such as pressure (350-550 MPa), pressure time (5-10 min), salt concentration, NaCl (10 y 15%) and drying temperature (40-60ºC) were optimized according to kinetic parameters of each mathematical model. The models used for drying experimental curves were those corresponding to Weibull, Page and Logarithmic models, however, the latest one was the best fitted to the experimental data. The values for water effective diffusivity varied from 4.82 to 6.59x10-9 m2/s for the 16 curves (DO+HHP) whereas the control samples obtained a value of 1.76 and 5.16×10-9 m2/s, for 40 and 60°C, respectively. On the other hand, quality characteristics such as color, texture, non-enzymatic browning, water holding capacity (WHC) and rehydration capacity (RC) were assessed. The L* (lightness) color parameter increased, however, b * (yellowish) and a* (reddish) parameters decreased for the DO+HHP treated samples, indicating treatment prevents sample browning. The texture parameters such as hardness and elasticity decreased, but chewiness increased with treatment, which resulted in a product with a higher tenderness and less firmness compared to the untreated sample. Finally, WHC and RC values of the most treatments increased owing to a minor damage in tissue cellular compared to untreated samples. Therefore, a knowledge regarding to the drying kinetic as well as quality characteristics of dried jumbo squid samples subjected to a pretreatment of osmotic dehydration under high hydrostatic pressure is extremely important to an industrial level so that the drying process can be successful at different pretreatment conditions and/or variable processes.

Keywords: diffusion coefficient, drying process, high pressure, jumbo squid, modelling, quality aspects

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Authors: Federica Floridi

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The long tradition of contrastive idiom research has essentially been focusing on three domains: the comparison of structural types of idioms (e.g. verbal idioms, idioms with noun-phrase structure, etc.), the description of idioms belonging to the same thematic groups (Sachgruppen), the identification of different types of cross-linguistic equivalents (i.e. full equivalents, partial equivalents, phraseological parallels, non-equivalents). The diastratic, diachronic and diatopic aspects of the compared idioms, as well as their syntactic, pragmatic and semantic properties, have been rather ignored. Corpora (both monolingual and parallel) give the opportunity to investigate the actual use of correlating idioms in authentic texts of L1 and L2. Adopting the corpus-based approach, it is possible to draw attention to the frequency of occurrence of idioms, their syntactic embedding, their potential syntactic transformations (e.g., nominalization, passivization, relativization, etc.), their combinatorial possibilities, the variations of their lexical structure, their connotations in terms of stylistic markedness or register. This paper aims to present the results of a contrastive analysis of Russian and Italian idioms referring to the concepts of ‘beginning’ and ‘end’, that has been carried out by using the Russian National Corpus and the ‘La Repubblica’ corpus. Beyond the digital corpora, bilingual dictionaries, like Skvorcova - Majzel’, Dobrovol’skaja, Kovalev, Čerdanceva, as well as monolingual resources, have been consulted. The study has shown that many of the idioms that have been traditionally indicated as cross-linguistic equivalents on bilingual dictionaries cannot be considered correspondents. The findings demonstrate that even those idioms, that are formally identical in Russian and Italian and are presumably derived from the same source (e.g., conceptual metaphor, Bible, classical mythology, World literature), exhibit differences regarding usage. The ultimate purpose of this article is to highlight that it is necessary to review and improve the existing bilingual dictionaries considering the empirical data collected in corpora. The materials gathered in this research can contribute to this sense.

Keywords: corpora, cross-linguistic equivalence, idioms, Italian, Russian

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Authors: Hugo Daneluzzo, Christelle Rabbat, Alan Jean-Marie

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Water electrolysis is one of the most advanced technologies for producing hydrogen and can be easily combined with electricity from different sources. Under the influence of electric current, water molecules can be split into oxygen and hydrogen. The production of hydrogen by water electrolysis favors the integration of renewable energy sources into the energy mix by compensating for their intermittence through the storage of the energy produced when production exceeds demand and its release during off-peak production periods. Among the various electrolysis technologies, anion exchange membrane (AEM) electrolyser cells are emerging as a reliable technology for water electrolysis. Modeling and simulation are effective tools to save time, money, and effort during the optimization of operating conditions and the investigation of the design. The modeling and simulation become even more important when dealing with multiphysics dynamic systems. One of those systems is the AEM electrolysis cell involving complex physico-chemical reactions. Once developed, models may be utilized to comprehend the mechanisms to control and detect flaws in the systems. Several modeling methods have been initiated by scientists. These methods can be separated into two main approaches, namely equation-based modeling and graph-based modeling. The former approach is less user-friendly and difficult to update as it is based on ordinary or partial differential equations to represent the systems. However, the latter approach is more user-friendly and allows a clear representation of physical phenomena. In this case, the system is depicted by connecting subsystems, so-called blocks, through ports based on their physical interactions, hence being suitable for multiphysics systems. Among the graphical modelling methods, the bond graph is receiving increasing attention as being domain-independent and relying on the energy exchange between the components of the system. At present, few studies have investigated the modelling of AEM systems. A mathematical model and a bond graph model were used in previous studies to model the electrolysis cell performance. In this study, experimental data from literature were simulated using OpenModelica using bond graphs and mathematical approaches. The polarization curves at different operating conditions obtained by both approaches were compared with experimental ones. It was stated that both models predicted satisfactorily the polarization curves with error margins lower than 2% for equation-based models and lower than 5% for the bond graph model. The activation polarization of hydrogen evolution reactions (HER) and oxygen evolution reactions (OER) were behind the voltage loss in the AEM electrolyzer, whereas ion conduction through the membrane resulted in the ohmic loss. Therefore, highly active electro-catalysts are required for both HER and OER while high-conductivity AEMs are needed for effectively lowering the ohmic losses. The bond graph simulation of the polarisation curve for operating conditions at various temperatures has illustrated that voltage increases with temperature owing to the technology of the membrane. Simulation of the polarisation curve can be tested virtually, hence resulting in reduced cost and time involved due to experimental testing and improved design optimization. Further improvements can be made by implementing the bond graph model in a real power-to-gas-to-power scenario.

Keywords: hydrogen production, anion-exchange membrane, electrolyzer, mathematical modeling, multiphysics modeling

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Authors: Ozcan Yavas, Berrak Erol Nalbur, Sermin Gunarslan

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A materiality matrix is a tool that organizations use to prioritize their activities and adapt to the increasing sustainability requirements in recent years. For the materiality index to move from business models to the sustainability business model stage, it must be done with all partners in the raw material, supply, production, product, and end-of-life product stages. Within the scope of this study, the Materiality Matrix was used to transform the business model into a sustainability business model and to create a sustainability roadmap in a factory producing electric buses. This matrix determines the necessary roadmap for all stakeholders to participate in the process, especially in sectors that produce sustainable products, such as the electric vehicle sector, and to act together with the cradle-to-cradle approach of sustainability roadmaps. Global Reporting Initiative analysis was used in the study conducted with 1150 stakeholders within the scope of the study, and 43 questions were asked to the stakeholders under the main headings of 'Legal Compliance Level,' 'Environmental Strategies,' 'Risk Management Activities,' 'Impact of Sustainability Activities on Products and Services,' 'Corporate Culture,' 'Responsible and Profitable Business Model Practices' and 'Achievements in Leading the Sector' and Economic, Governance, Environment, Social and Other. The results of the study aimed to include five 1st priority issues and four 2nd priority issues in the sustainability strategies of the organization in the short and medium term. When the studies carried out in the short term are evaluated in terms of Sustainability and Environmental Risk Management, it is seen that the studies are still limited to the level of legal legislation (60%) and individual studies in line with the strategies (20%). At the same time, the stakeholders expect the company to integrate sustainability activities into its business model within five years (35%) and to carry out projects to become the first company that comes to mind with its success leading the sector (20%). Another result obtained within the study's scope is identifying barriers to implementation. It is seen that the most critical obstacles identified by stakeholders with climate change and environmental impacts are financial deficiency and lack of infrastructure in the dissemination of sustainable products. These studies are critical for transitioning to sustainable business models for the electric vehicle sector to achieve the EU Green Deal and CBAM targets.

Keywords: sustainability business model, materiality matrix, electricity bus, carbon neutrality, sustainability management

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Authors: Ahmad Saleem

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Ethereum is the second largest crypto currency in blockchain ecosystem. Along with standard transactions, it supports smart contracts and NFT’s. Current research trends are focused on analyzing the overall structure of the network its growth and behavior. Ethereum addresses are anonymous and can be created on fly. The nature of Ethereum network and addresses make it hard to predict their behavior. The activity period of an ethereum address is not much analyzed. Using machine learning we can make early prediction about the disposability of the address. In this paper we analyzed the lifetime of the addresses. We also identified and predicted the disposable addresses using machine learning models and compared the results.

Keywords: blockchain, Ethereum, cryptocurrency, prediction

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Authors: Hamza Javar Magnier, Robin Curtis

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There have been rapid advances in the upstream processing of protein therapeutics, which has shifted the bottleneck to downstream purification and formulation. Finding liquid formulations with shelf lives of up to two years is increasingly difficult for some of the newer therapeutics, which have been engineered for activity, but their formulations are often viscous, can phase separate, and have a high propensity for irreversible aggregation1. We explore means to develop improved predictive ability from a better understanding of how protein-protein interactions on formulation conditions (pH, ionic strength, buffer type, presence of excipients) and how these impact upon the initial steps in protein self-association and aggregation. In this work, we study the initial steps in the aggregation pathways using a minimal protein model based on square-well potentials and discontinuous molecular dynamics. The effect of model parameters, including range of interaction, stiffness, chain length, and chain sequence, implies that protein models fold according to various pathways. By reducing the range of interactions, the folding- and collapse- transition come together, and follow a single-step folding pathway from the denatured to the native state2. After parameterizing the model interaction-parameters, we developed an understanding of low-temperature conformational properties and fluctuations, and the correlation to the folding transition of proteins in isolation. The model fluctuations increase with temperature. We observe a low-temperature point, below which large fluctuations are frozen out. This implies that fluctuations at low-temperature can be correlated to the folding transition at the melting temperature. Because proteins “breath” at low temperatures, defining a native-state as a single structure with conserved contacts and a fixed three-dimensional structure is misleading. Rather, we introduce a new definition of a native-state ensemble based on our understanding of the core conservation, which takes into account the native fluctuations at low temperatures. This approach permits the study of a large range of length and time scales needed to link the molecular interactions to the macroscopically observed behaviour. In addition, these models studied are parameterized by fitting to experimentally observed protein-protein interactions characterized in terms of osmotic second virial coefficients.

Keywords: protein folding, native-ensemble, conformational fluctuation, aggregation

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Authors: S. R. Dehghani, G. F. Naterer, Y. S. Muzychka

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Wave-impact sea spray creates many droplets which form a spray cloud traveling over marine objects same as marine vessels and offshore structures. In cold climates such as Arctic reigns, sea spray icing, which is ice accretion on cold substrates, is strongly dependent on the wave-impact sea spray. The rate of cooling of droplets affects the process of icing that can yield to dry or wet ice accretion. Trajectories of droplets determine the potential places for ice accretion. Combining two models of trajectories and heat transfer for droplets can predict the risk of ice accretion reasonably. The majority of the cooling of droplets is because of droplet evaporations. In this study, a combined model using trajectory and heat transfer evaluate the situation of a cloud of spray from the generation to impingement. The model uses some known geometry and initial information from the previous case studies. The 3D model is solved numerically using a standard numerical scheme. Droplets are generated in various size ranges from 7 mm to 0.07 mm which is a suggested range for sea spray icing. The initial temperature of droplets is considered to be the sea water temperature. Wind velocities are assumed same as that of the field observations. Evaluations are conducted using some important heading angles and wind velocities. The characteristic of size-velocity dependence is used to establish a relation between initial sizes and velocities of droplets. Time intervals are chosen properly to maintain a stable and fast numerical solution. A statistical process is conducted to evaluate the probability of expected occurrences. The medium size droplets can reach the highest heights. Very small and very large droplets are limited to lower heights. Results show that higher initial velocities create the most expanded cloud of spray. Wind velocities affect the extent of the spray cloud. The rate of droplet cooling at the start of spray formation is higher than the rest of the process. This is because of higher relative velocities and also higher temperature differences. The amount of water delivery and overall temperature for some sample surfaces over a marine vessel are calculated. Comparing results and some field observations show that the model works accurately. This model is suggested as a primary model for ice accretion on marine vessels.

Keywords: evaporation, sea spray, marine icing, numerical solution, trajectory

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Authors: Misuk Kim, Seokho Kang, Jehyuk Lee, Hyunchang Cho, Sungzoon Cho

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In semiconductor manufacturing, virtual metrology (VM) refers to methods to predict properties of a wafer based on machine parameters and sensor data of the production equipment, without performing the (costly) physical measurement of the wafer properties (Wikipedia). Additional benefits include avoidance of human bias and identification of important factors affecting the quality of the process which allow improving the process quality in the future. It is however rare to find VM applied to other areas of manufacturing. In this work, we propose to use VM to copper clad laminate (CCL) manufacturing. CCL is a core element of a printed circuit board (PCB) which is used in smartphones, tablets, digital cameras, and laptop computers. The manufacturing of CCL consists of three processes: Treating, lay-up, and pressing. Treating, the most important process among the three, puts resin on glass cloth, heat up in a drying oven, then produces prepreg for lay-up process. In this process, three important quality factors are inspected: Treated weight (T/W), Minimum Viscosity (M/V), and Gel Time (G/T). They are manually inspected, incurring heavy cost in terms of time and money, which makes it a good candidate for VM application. We developed prediction models of the three quality factors T/W, M/V, and G/T, respectively, with process variables, raw material, and environment variables. The actual process data was obtained from a CCL manufacturer. A variety of variable selection methods and learning algorithms were employed to find the best prediction model. We obtained prediction models of M/V and G/T with a high enough accuracy. They also provided us with information on “important” predictor variables, some of which the process engineers had been already aware and the rest of which they had not. They were quite excited to find new insights that the model revealed and set out to do further analysis on them to gain process control implications. T/W did not turn out to be possible to predict with a reasonable accuracy with given factors. The very fact indicates that the factors currently monitored may not affect T/W, thus an effort has to be made to find other factors which are not currently monitored in order to understand the process better and improve the quality of it. In conclusion, VM application to CCL’s treating process was quite successful. The newly built quality prediction model allowed one to reduce the cost associated with actual metrology as well as reveal some insights on the factors affecting the important quality factors and on the level of our less than perfect understanding of the treating process.

Keywords: copper clad laminate, predictive modeling, quality control, virtual metrology

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Authors: Melisa Mete, Gary Davies, Susan Whelan

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Maintaining a good employer brand image is crucial for companies since it has numerous advantages such as better recruitment, retention and employee engagement, and commitment. This study aims to understand the relationship between employer brand image and employee satisfaction and engagement in the British context. A panel survey data (N=228) is tested via the regression models from the Hayes (2012) PROCESS macro, in IBM SPSS 23.0. The results are statistically significant and proves that the more positive employer brand image, the greater employee’ engagement and satisfaction, and the greater is employee satisfaction, the greater their engagement.

Keywords: employer brand, employer brand image, employee engagement, employee satisfaction

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Authors: Md. Awal Hossain Mollah

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The aim of this study was to evaluate the relation between the free, fair and credible election in ensuring democratic governance in Bangladesh. The paper is a case (Bangladesh) study and qualitative in nature and based on secondary sources of materials. For doing this study, conceptual clarification has been done first and identified few elements of free, fair and credible elections. Then, how far these elements have been ensured in Bangladeshi elections has been evaluated by analyzing all the national elections held since independence. Apart from these, major factors and challenges of holding a free, fair and credible election in Bangladesh have been examined through using the following research questions: 1. Does role of election commission matter for free, fair and credible elections to form a democratic government? 2. Does role of political parties matter for democratic governance? 3. Do role of government matter for conducting the free, fair and credible election in ensuring democratic governance? 4. Does non-party caretaker government matter for conducting a free, fair and credible election? 5. Does democratic governance depend on multi-dimensional factors and actors? Major findings of this study are: Since the independence of Bangladesh, 10 national elections held in various regimes. 4 out of 10 national elections have been found free, fair and credible which have been conducted by the non-party caretaker government. Rests of the elections are not out of controversy and full of manipulation held under elected government. However, the caretaker government has already been abolished by the AL government through 15th amendment of the constitution. The present AL government is elected by the 10th parliamentary election under incumbent (AL) government, but a major opposition allies (20 parties) lead by BNP boycotted this election and 154 of the total 300 seats being uncontested. As a result, AL again came to the power without a competitive election and most of the national and International election observers including media world consider this election as unfair and the government is suffering from lack of legitimacy. Therefore, the governance of present Bangladesh is not democratic at all and it is to be considered as one party (14 parties’ allies lead by AL) authoritarian governance in the shade of parliamentary governance. Both the position and opposition of the parliament is belonging in 14 parties’ alliances lead by AL.

Keywords: democracy, governance, free, fair and credible elections, Bangladesh

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Authors: Laura Simmer, Maria Kalt, Oliver Schauer

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Freight transport is growing fast, but many vehicles are empty or just partially loaded. The vision and concepts of the Physical Internet (PI) proposes to eliminate these inefficiencies. Aiming for a radical sustainability improvement, the PI – inspired by the Digital Internet – is a hyperconnected global logistic system, enabling seamless asset sharing and flow consolidation. The implementation of a PI in its full expression will be a huge challenge: the industry needs innovation and implementation support including change management approaches, awareness creation and good practices diffusion, legislative actions to remove antitrust and international commerce barriers, standardization and public incentives policies. In order to take a step closer to this future the project ‘Atropine - Fast Track to the Physical Internet’ funded under the Strategic Economic and Research Program ‘Innovative Upper Austria 2020’ was set up. The two-year research project unites several research partners in this field, but also industrial partners and logistics service providers. With Atropine, the consortium wants to actively shape the mobility landscape in Upper Austria and make an innovative contribution to an energy-efficient, environmentally sound and sustainable development in the transport area. This paper should, on the one hand, clarify the questions what the project Atropine is about and, on the other hand, how a proof of concept will be reached. Awareness building plays an important role in the project as the PI requires a reorganization of the supply chain and the design of completely new forms of inter-company co-operation. New business models have to be developed and should be verified by simulation. After the simulation process one of these business models will be chosen and tested in real life with the partner companies. The developed results - simulation model and demonstrator - are used to determine how the concept of the PI can be applied in Upper Austria. Atropine shall pave the way for a full-scale development of the PI vision in the next few decades and provide the basis for pushing the industry toward a new level of co-operation with more shared resources and increased standardization.

Keywords: Atropine, inter-company co-operation, Physical Internet, shared resources, sustainable logistics

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Authors: Amit R. Bhende, G. K. Awari

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Remaining useful life (RUL) prediction is one of key technologies to realize prognostics and health management that is being widely applied in many industrial systems to ensure high system availability over their life cycles. The present work proposes a data-driven method of RUL prediction based on multiple health state assessment for rolling element bearings. Bearing degradation data at three different conditions from run to failure is used. A RUL prediction model is separately built in each condition. Feed forward back propagation neural network models are developed for prediction modeling.

Keywords: bearing degradation data, remaining useful life (RUL), back propagation, prognosis

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Authors: Natasha Sharma, Kulbhushan Agnihotri

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Cellular Automata are discrete dynamical systems which are based on local character and spatial disparateness of the spreading process. These factors are generally neglected by traditional models based on differential equations for epidemic spread. The aim of this work is to introduce an SEIR model based on cellular automata on graphs to imitate epidemic spreading. Distinctively, it is an SEIR-type model where the population is divided into susceptible, exposed, infected and recovered individuals. The results obtained from simulations are in accordance with the spreading behavior of a real time epidemics.

Keywords: cellular automata, epidemic spread, graph, susceptible

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Authors: Juan Sepúlveda

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Energy is a fundamental component in sustainability, the access and use of this resource is related with economic growth, social improvements, and environmental impacts. In this sense, energy efficiency has been studied as a factor that enhances the positive impacts of energy in communities; however, the implementation of efficiency requires strong policy and strategies that usually rely on individual measures focused in independent dimensions. In this paper, the problem of energy efficiency as a multi-objective problem is studied, using scientometric analysis to discover trends and patterns that allow to identify the main variables and study approximations related with a further development of models to integrate energy efficiency and MCA into policy making for small communities.

Keywords: energy efficiency, MCA, scientometric, trends

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Authors: Francesca Spagnoli, Shenja van der Graaf, Pieter Ballon

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Humans do not behave rationally. We are emotional, easily influenced by others, as well as by our context. The study of human behaviour became a supreme endeavour within many academic disciplines, including economics, sociology, and clinical and social psychology. Understanding what motivates humans and triggers them to perform certain activities, and what it takes to change their behaviour, is central both for researchers and companies, as well as policy makers to implement efficient public policies. While numerous theoretical approaches for diverse domains such as health, retail, environment have been developed, the methodological models guiding the evaluation of such research have reached for a long time their limits. Within this context, digitisation, the Information and communication technologies (ICT) and wearable, the Internet of Things (IoT) connecting networks of devices, and new possibilities to collect and analyse massive amounts of data made it possible to study behaviour from a realistic perspective, as never before. Digital technologies make it possible to (1) capture data in real-life settings, (2) regain control over data by capturing the context of behaviour, and (3) analyse huge set of information through continuous measurement. Within this complex context, this paper describes a new framework for initiating behavioural change, capitalising on the digital developments in applied research projects and applicable both to academia, enterprises and policy makers. By applying this model, behavioural research can be conducted to address the issues of different domains, such as mobility, environment, health or media. The Modular Behavioural Analysis Approach (MBAA) is here described and firstly validated through a concrete use case within the domain of health. The results gathered have proven that disclosing information about health in connection with the use of digital apps for health, can be a leverage for changing behaviour, but it is only a first component requiring further follow-up actions. To this end, a clear definition of different 'behavioural profiles', towards which addressing several typologies of interventions, it is essential to effectively enable behavioural change. In the refined version of the MBAA a strong focus will rely on defining a methodology for shaping 'behavioural profiles' and related interventions, as well as the evaluation of side-effects on the creation of new business models and sustainability plans.

Keywords: behavioural change, framework, health, nudging, sustainability

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Authors: Abdullah Al Mamoon, Niels E. Joergensen, Ataur Rahman, Hassan Qasem

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Intergovernmental Panel for Climate Change (IPCC) in its fourth Assessment Report AR4 predicts a more extreme climate towards the end of the century, which is likely to impact the design of engineering infrastructure projects with a long design life. A recent study in 2013 developed new design rainfall for Qatar, which provides an improved design basis of drainage infrastructure for the State of Qatar under the current climate. The current design standards in Qatar do not consider increased rainfall intensity caused by climate change. The focus of this paper is to update recently developed design rainfalls in Qatar under the changing climatic conditions based on IPCC's AR4 allowing a later revision to the proposed design standards, relevant for projects with a longer design life. The future climate has been investigated based on the climate models released by IPCC’s AR4 and A2 story line of emission scenarios (SRES) using a stationary approach. Annual maximum series (AMS) of predicted 24 hours rainfall data for both wet (NCAR-CCSM) scenario and dry (CSIRO-MK3.5) scenario for the Qatari grid points in the climate models have been extracted for three periods, current climate 2010-2039, medium term climate (2040-2069) and end of century climate (2070-2099). A homogeneous region of the Qatari grid points has been formed and L-Moments based regional frequency approach is adopted to derive design rainfalls. The results indicate no significant changes in the design rainfall on the short term 2040-2069, but significant changes are expected towards the end of the century (2070-2099). New design rainfalls have been developed taking into account climate change for 2070-2099 scenario and by averaging results from the two scenarios. IPCC’s AR4 predicts that the rainfall intensity for a 5-year return period rain with duration of 1 to 2 hours will increase by 11% in 2070-2099 compared to current climate. Similarly, the rainfall intensity for more extreme rainfall, with a return period of 100 years and duration of 1 to 2 hours will increase by 71% in 2070-2099 compared to current climate. Infrastructure with a design life exceeding 60 years should add safety factors taking the predicted effects from climate change into due consideration.

Keywords: climate change, design rainfalls, IDF, Qatar

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Authors: D. Habibinia, M. R. Feyzi

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Nowadays, specialized software is vastly used to verify the performance of an electric machine prototype by evaluating a model of the system. These models mainly consist of electrical parameters such as inductances and resistances. However, when the operating frequency of the device is above one kHz, the effect of parasitic capacitances grows significantly. In this paper, a software-based procedure is introduced to model these capacitances within the electromagnetic simulation of the device. The case study is a high-frequency high-voltage pulse transformer. The Finite Element Analysis (FEA) software with coupled field analysis is used in this method.

Keywords: finite element analysis, parasitic capacitance, pulse transformer, high frequency

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Authors: Muntanavadee Maytapattana

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This research aims to study the effects of the Parent Training Program for Obesity Reduction (PTPOR) on child waist circumference and health behaviors of pre-school children at the Samut-Songkhram kindergarten school, Samut-Songkhram province, Thailand. The objective of this research is to evaluate the effectiveness of the PTPOR on child waist circumference and health behaviors of the pre-school children. The conceptual framework of this study is developed on the basis of the Ecological Systems Theory (EST), not only do the individual factors such as child characteristics and child risk factors contribute to the child’s weight status, but also other factors such as parenting style and family characteristics, as well as community and demographic factors. This research is a quasi-experimental study. Participants were pre-school overweight and obese children and their parents. Forty-one parent-child dyads were recruited into the program. Parents participated in two sessions including an educational session and a group discussion session. Research methodology uses Paired-Samples t-test to determine the difference between groups in the mean scores of the outcome variables of the children and parents. The research results show that there was significant difference between child waist circumferences mean score at the baseline and finishing the program at the 0.01 level (p = 0.001), mean score of the child waist circumference was decrease after finishing the program. And there was no significant difference between child exercise health behaviors mean score at the baseline and finishing the program at the 0.05 level; however, mean score of the child exercise behavior was increase after finishing the program. Meanwhile, there was significant difference between child dietary health behavior mean score at the baseline and finishing the program at the 0.01 level (p = 0.001), mean score of the child dietary was increase after finishing the program.

Keywords: PTPOR, child waist circumference, child health behaviors, pre-school children

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Authors: Yasir Ali Soomro

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Companies that demonstrate corporate social responsibilities (CSR) are more likely to withstand any downturn or crises because of the trust built with stakeholders. Many firms are utilizing CSR marketing to improve the interactions with their various stakeholders, mainly the consumers. Most previous research on CSR has focused on the impact of CSR on customer responses and behaviors toward a company. As online food ordering and grocery shopping remains inevitable. This study will investigate structural relationships among consumer positive emotions (CPE) and negative emotions (CNE), Corporate Reputation (CR), Customer Trust (CT), Brand Image (BI), and Brand attitude (BA) on behavioral outcomes such as Online purchase intention (OPI) and Word of mouth (WOM) in retail grocery and food restaurants setting. Hierarchy of Effects Model will be used as theoretical, conceptual framework. The model describes three stages of consumer behavior: (i) cognitive, (ii) affective, and (iii) conative. The study will apply a quantitative method to test the hypotheses; a self-developed questionnaire with non-probability sampling will be utilized to collect data from 500 consumers belonging to generation X, Y, and Z residing in KSA. The study will contribute by providing empirical evidence to support the link between CSR and customer affective and conative experiences in Saudi Arabia. The theoretical contribution of this study will be empirically tested comprehensive model where CPE, CNE, CR, CT, BI, and BA act as mediating variables between the perceived CSR & Online purchase intention (OPI) and Word of mouth (WOM). Further, the study will add more to how the emotional/ psychological process mediates in the CSR literature, especially in the Middle Eastern context. The proposed study will also explain the effect of perceived CSR marketing initiatives directly and indirectly on customer behavioral responses.

Keywords: corporate social responsibility, corporate reputation, consumer emotions, loyalty, online purchase intention, word-of-mouth, structural equation modeling

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Authors: Deni̇z Ezgi̇ Gülmez, Mesut Kirca

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Nanoporous (np) metals have attracted considerable attention owing to their cellular morphological features at atomistic scale which yield ultra-high specific surface area awarding a great potential to be employed in diverse applications such as catalytic, electrocatalytic, sensing, mechanical and optical. As one of the carbon based nanostructures, fullerenes are also another type of outstanding nanomaterials that have been extensively investigated due to their remarkable chemical, mechanical and optical properties. In this study, the idea of improving the mechanical behavior of nanoporous metals by inclusion of the fullerenes, which offers a new metal-carbon nanocomposite material, is examined and discussed. With this motivation, tensile mechanical behavior of nanoporous metals reinforced with carbon fullerenes is investigated by classical molecular dynamics (MD) simulations. Atomistic models of the nanoporous metals with ultrathin ligaments are obtained through a stochastic process simply based on the intersection of spherical volumes which has been used previously in literature. According to this technique, the atoms within the ensemble of intersecting spherical volumes is removed from the pristine solid block of the selected metal, which results in porous structures with spherical cells. Following this, fullerene units are added into the cellular voids to obtain final atomistic configurations for the numerical tensile tests. Several numerical specimens are prepared with different number of fullerenes per cell and with varied fullerene sizes. LAMMPS code was used to perform classical MD simulations to conduct uniaxial tension experiments on np models filled by fullerenes. The interactions between the metal atoms are modeled by using embedded atomic method (EAM) while adaptive intermolecular reactive empirical bond order (AIREBO) potential is employed for the interaction of carbon atoms. Furthermore, atomic interactions between the metal and carbon atoms are represented by Lennard-Jones potential with appropriate parameters. In conclusion, the ultimate goal of the study is to present the effects of fullerenes embedded into the cellular structure of np metals on the tensile response of the porous metals. The results are believed to be informative and instructive for the experimentalists to synthesize hybrid nanoporous materials with improved properties and multifunctional characteristics.

Keywords: fullerene, intersecting spheres, molecular dynamic, nanoporous metals

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Authors: A. Mihoc, K. Cater

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On the bridge of a ship the officers are looking for visual aids to guide navigation in order to reconcile the outside world with the position communicated by the digital navigation system. Aids to navigation include: Lighthouses, lightships, sector lights, beacons, buoys, and others. They are designed to help navigators calculate their position, establish their course or avoid dangers. In poor visibility and dense traffic areas, it can be very difficult to identify these critical aids to guide navigation. The paper presents the usage of Augmented Reality (AR) as a means to present digital information about these aids to support navigation. To date, nautical navigation related mobile AR applications have been limited to the leisure industry. If proved viable, this prototype can facilitate the creation of other similar applications that could help commercial officers with navigation. While adopting a user centered design approach, the team has developed the prototype based on insights from initial research carried on board of several ships. The prototype, built on Nexus 9 tablet and Wikitude, features a head-up display of the navigational aids (lights) in the area, presented in AR and a bird’s eye view mode presented on a simplified map. The application employs the aids to navigation data managed by Hydrographic Offices and the tablet’s sensors: GPS, gyroscope, accelerometer, compass and camera. Sea trials on board of a Navy and a commercial ship revealed the end-users’ interest in using the application and further possibility of other data to be presented in AR. The application calculates the GPS position of the ship, the bearing and distance to the navigational aids; all within a high level of accuracy. However, during testing several issues were highlighted which need to be resolved as the prototype is developed further. The prototype stretched the capabilities of Wikitude, loading over 500 objects during tests in a major port. This overloaded the display and required over 45 seconds to load the data. Therefore, extra filters for the navigational aids are being considered in order to declutter the screen. At night, the camera is not powerful enough to distinguish all the lights in the area. Also, magnetic interference with the bridge of the ship generated a continuous compass error of the AR display that varied between 5 and 12 degrees. The deviation of the compass was consistent over the whole testing durations so the team is now looking at the possibility of allowing users to manually calibrate the compass. It is expected that for the usage of AR in professional maritime contexts, further development of existing AR tools and hardware is needed. Designers will also need to implement a user-centered design approach in order to create better interfaces and display technologies for enhanced solutions to aid navigation.

Keywords: compass error, GPS, maritime navigation, mobile augmented reality

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Authors: João Pedro Zanella, Michel J. O. Fagundes

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Introduction: Drug use has been practised by humans universally for millennia, not excluding any population from these habits, however, the rampant drug use is a global concern due to the harm that affects the health of the world population. In this sense, it is observed the reduction of lasting and effective public policies for the resolution, increasing the demand for treatment services. With this comes ibogaine, an alkaloid derived from the root of an African bush (Tabernanthe Iboga), found mostly in Gabon and used widely by the native Bwiti population in rituals, and also other social groups, which demonstrates efficacy against chemical dependence, psychic and emotional disorders, opioid withdrawal was first confirmed by a study in rats done by Michailo Dzoljic and associates in 1988 and again in 1994. Methods: A brief description of the plant, its neurohumoral potential and the effects caused by ingested doses, in a simplified and objective way, will be discussed in the course of this abstract. Results: Ibogaine is not registered or passed by Anvisa, regarding safety and efficacy, and cannot be sold in Brazil. Its illegal trade reaches R$ 5 thousand for a session with the proceeds of the root, and its effect can last up to 72 hours, attributing Iboga's psychoactive effects to the alkaloid called ibogaine. The shrub where Ibogaine is located has pink and yellow flowers, and its fruit produced does not have psychoactive substances, but its root bark contains 6 to 7% indolic alkaloids. Besides extraction from the iboga plant, ibogaine hydrochloride can be semisynthesized from voacangine, another plant alkaloid that acts as a precursor. Its potential has the ability to perform multiple interactions with the neurotransmitter system, which are closely associated with addiction, including nicotinic, opioid and serotoninergic systems. Studies carried out by Edwards found that the doses administered of Iboga should be determined by a health professional when its purpose is to treat individuals for dependence on other drugs. Its use in small doses may cause an increase in sensibility, impaired vision and motor alterations; in moderate quantities, hallucinations, motor and neurological alterations and impaired vision; in high quantities it may cause hallucinations with personal events at a deeper level lasting up to 24 hours or more, followed by motor and visual alterations. Conclusion: The product extracted from the Iboga plant is of great importance in controlling addiction, reducing the need for the use of narcotics by patients, thus gaining a space of extreme importance in the treatment of users of psychoactive substances. It is remarkable the progress of the latest’s research about the usefulness of Ibogaine, and its benefits for certain treatments, even with the restriction of its sale in Brazil. Besides this, Ibogaine has an additional benefit of helping the patient to gain self-control over their destructive behaviours.

Keywords: alkaloids, dependence, Gabon, ibogaine

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Authors: Jeffrey Tzu-Hao Tsai, Yi-Shan Wong

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This article proposes a cohort-age-period (CAP) model to characterize multi-population mortality processes using cohort, age, and period variables. Distinct from the factor-based Lee-Carter-type decomposition mortality model, this approach is empirically based and includes the age, period, and cohort variables into the equation system. The model not only provides a fruitful intuition for explaining multivariate mortality change rates but also has a better performance in forecasting future patterns. Using the US and the UK mortality data and performing ten-year out-of-sample tests, our approach shows smaller mean square errors in both countries compared to the models in the literature.

Keywords: longevity risk, stochastic mortality model, multivariate mortality rate, risk management

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