Search results for: randomized response model

Authors: Suresh Hettiarachchi, Conrad Wasko, Ashish Sharma

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The ever changing and expanding urban landscape increases the stress on urban systems to support and maintain safe and functional living spaces. Flooding presents one of the more serious threats to this safety, putting a larger number of people in harm’s way in congested urban settings. Climate change is adding to this stress by creating a dichotomy in the urban flood response. On the one hand, climate change is causing storms to intensify, resulting in more destructive, rarer floods, while on the other hand, longer dry periods are decreasing the severity of more frequent, less intense floods. This variability is creating a need to be more agile and innovative in how we design for and manage urban flooding. Here, we argue that to cope with this challenge climate change brings, we need to move towards urban flood management through resilience rather than flood prevention. We also argue that dealing with the larger variation in flood response to climate change means that we need to look at flooding from all aspects rather than the single-dimensional focus of flood depths and extents. In essence, we need to rethink how we manage flooding in the urban space. This change in our thought process and approach to flood management requires a practical way to assess and quantify resilience that is built into the urban landscape so that informed decision-making can support the required changes in planning and infrastructure design. Towards that end, we propose a Simple Urban Flood Resilience Index (SUFRI) based on a robust definition of resilience as a tool to assess flood resilience. The application of a simple resilience index such as the SUFRI can provide a practical tool that considers urban flood management in a multi-dimensional way and can present solutions that were not previously considered. When such an index is grounded on a clear and relevant definition of resilience, it can be a reliable and defensible way to assess and assist the process of adapting to the increasing challenges in urban flood management with climate change.

Keywords: urban flood resilience, climate change, flood management, flood modelling

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Authors: A. A. Okafor, C. H. Achebe, J. L. Chukwuneke, C. G. Ozoegwu

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The performance of an engine whose basic design parameters are known can be predicted with the assistance of simulation programs into the less time, cost and near value of actual. This paper presents a comprehensive mathematical model of the performance parameters of four stroke spark ignition engine. The essence of this research work is to develop a mathematical model for the analysis of engine performance parameters of four stroke spark ignition engine before embarking on full scale construction, this will ensure that only optimal parameters are in the design and development of an engine and also allow to check and develop the design of the engine and it’s operation alternatives in an inexpensive way and less time, instead of using experimental method which requires costly research test beds. To achieve this, equations were derived which describe the performance parameters (sfc, thermal efficiency, mep and A/F). The equations were used to simulate and optimize the engine performance of the model for various engine speeds. The optimal values obtained for the developed bivariate mathematical models are: sfc is 0.2833kg/kwh, efficiency is 28.77% and a/f is 20.75.

Keywords: bivariate models, engine performance, injector engine, optimization, performance parameters, simulation, spark ignition

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Authors: Seema Dhariwal, Kiran Maan, Ruchi Baghel, Apoorva Sharma, Poonam Rana

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Introduction: Traumatic brain injury (TBI) is defined as the temporary or permanent alteration in brain function and pathology caused by an external mechanical force. It represents the leading cause of mortality and morbidity among children and youth individuals. Various models of TBI in rodents have been developed in the laboratory to mimic the scenario of injury. Blast overpressure injury is common among civilians and military personnel, followed by accidents or explosive devices. In addition to this, the lateral Controlled cortical impact (CCI) model mimics the blunt, penetrating injury. Method: In the present study, we have developed two different mild TBI models using blast and CCI injury. In the blast model, helium gas was used to create an overpressure of 130 kPa (±5) via a shock tube, and CCI injury was induced with an impact depth of 1.5mm to create diffusive and focal injury, respectively. C57BL/6J male mice (10-12 weeks) were divided into three groups: (1) control, (2) Blast treated, (3) CCI treated, and were exposed to different injury models. Serum was collected on Day1 and day7, followed by biphasic extraction using MTBE/Methanol/Water. Prepared samples were separated on Charged Surface Hybrid (CSH) C18 column and acquired on UHPLC-Q-TOF-MS using ESI probe with inhouse optimized parameters and method. MS peak list was generated using Markerview TM. Data were normalized, Pareto-scaled, and log-transformed, followed by multivariate and univariate analysis in metaboanalyst. Result and discussion: Untargeted profiling of lipids generated extensive data features, which were annotated through LIPID MAPS® based on their m/z and were further confirmed based on their fragment pattern by LipidBlast. There is the final annotation of 269 features in the positive and 182 features in the negative mode of ionization. PCA and PLS-DA score plots showed clear segregation of injury groups to controls. Among various lipids in mild blast and CCI, five lipids (Glycerophospholipids {PC 30:2, PE O-33:3, PG 28:3;O3 and PS 36:1 } and fatty acyl { FA 21:3;O2}) were significantly altered in both injury groups at Day 1 and Day 7, and also had VIP score >1. Pathway analysis by Biopan has also shown hampered synthesis of Glycerolipids and Glycerophospholipiods, which coincides with earlier reports. It could be a direct result of alteration in the Acetylcholine signaling pathway in response to TBI. Understanding the role of a specific class of lipid metabolism, regulation and transport could be beneficial to TBI research since it could provide new targets and determine the best therapeutic intervention. This study demonstrates the potential lipid biomarkers which can be used for injury severity diagnosis and identification irrespective of injury type (diffusive or focal).

Keywords: LipidBlast, lipidomic biomarker, LIPID MAPS®, TBI

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Authors: M. Alsharqawi, T. Zayed, S. Abu Dabous

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To ensure safety and serviceability of bridge infrastructure, accurate condition assessment and rating methods are needed to provide basis for bridge Maintenance, Repair and Replacement (MRR) decisions. In North America, the common practices to assess condition of bridges are through visual inspection. These practices are limited to detect surface defects and external flaws. Further, the thresholds that define the severity of bridge deterioration are selected arbitrarily. The current research discusses the main deteriorations and defects identified during visual inspection and Non-Destructive Evaluation (NDE). NDE techniques are becoming popular in augmenting the visual examination during inspection to detect subsurface defects. Quality inspection data and accurate condition assessment and rating are the basis for determining appropriate MRR decisions. Thus, in this paper, a novel method for bridge condition assessment using the Quality Function Deployment (QFD) theory is utilized. The QFD model is designed to provide an integrated condition by evaluating both the surface and subsurface defects for concrete bridges. Moreover, an integrated condition rating index with four thresholds is developed based on the QFD condition assessment model and using K-means clustering technique. Twenty case studies are analyzed by applying the QFD model and implementing the developed rating index. The results from the analyzed case studies show that the proposed threshold model produces robust MRR recommendations consistent with decisions and recommendations made by bridge managers on these projects. The proposed method is expected to advance the state of the art of bridges condition assessment and rating.

Keywords: concrete bridge decks, condition assessment and rating, quality function deployment, k-means clustering technique

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Authors: Mikhail Zarechnev, Bora I. Kumova

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A syllogism is a deductive inference scheme used to derive a conclusion from a set of premises. In a categorical syllogisms, there are only two premises and every premise and conclusion is given in form of a quantified relationship between two objects. The different order of objects in premises give classification known as figures. We have shown that the ordered combinations of 3 generalized quantifiers with certain figure provide in total of 108 syllogistic moods which can be considered as different inference rules. The classical syllogistic system allows to model human thought and reasoning with syllogistic structures always attracted the attention of cognitive scientists. Since automated reasoning is considered as part of learning subsystem of AI agents, syllogistic system can be applied for this approach. Another application of syllogistic system is related to inference mechanisms on the Semantic Web applications. In this paper we proposed the mathematical model and algorithm for syllogistic reasoning. Also the model of iterative syllogistic reasoning in case of continuous flows of incoming data based on case–based reasoning and possible applications of proposed system were discussed.

Keywords: categorical syllogism, case-based reasoning, cognitive architecture, inference on the semantic web, syllogistic reasoning

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Authors: Narimen Rdhaounia Mohamed Kouni

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Our aim in this paper is to identify the origins of inflation in Tunisia on the period from 1988 to 2018. In order to estimate the model, an ARDL methodology is used. We studied also the effect of informal economy on inflation. Indeed, we estimated the size of the informal economy in Tunisia based on Gutmann method. The results showed that there are three main origins of inflation. In fact, the first origin is the fiscal policy adopted by Tunisia, particularly after revolution. The second origin is the increase of monetary variables. Finally, informal economy played an important role in inflation.

Keywords: inflation, consumer price index, informal, gutmann method, ARDL model

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Authors: Yehya Rasool, Mohit Agrawal

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The site characterization and site response analysis are the crucial steps for reliable seismic microzonation of an area. So, the basic parameters involved in these fundamental steps are required to be chosen properly in order to efficiently characterize the vulnerable sites of the study region. In this study, efforts are made to delineate the variations in the physical parameter of the soil for the summer and monsoon seasons of the year (2021) by using Horizontal-to-Vertical Spectral Ratios (HVSRs) recorded at five sites of the Indian Institute of Technology (Indian School of Mines), Dhanbad, Jharkhand, India. The data recording at each site was done in such a way that less amount of anthropogenic noise was recorded at each site. The analysis has been done for five seismic parameters like predominant frequency, H/V ratio, the phase velocity of Rayleigh waves, shear wave velocity (Vs), compressional wave velocity (Vp), and Poisson’s ratio for both the seasons of the year. From the results, it is observed that these parameters majorly vary drastically for the upper layers of soil, which in turn may affect the amplification ratios and probability of exceedance obtained from seismic hazard studies. The HVSR peak comes out to be higher in monsoon, with a shift in predominant frequency as compared to the summer season of the year 2021. Also, the drastic reduction in shear wave velocity (up to ~10 m) of approximately 7%-15% is also perceived during the monsoon period with a slight decrease in compressional wave velocity. Generally, the increase in the Poisson ratios is found to have higher values during monsoon in comparison to the summer period. Our study may be very beneficial to various agricultural and geotechnical engineering projects.

Keywords: HVSR, shear wave velocity profile, Poisson ratio, microtremor data

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Authors: Sixing Chen, Shuai Yang

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Online celebrity business, also known as Internet celebrity business (or Wanghong business in Chinese), is an emerging relational C2C business model, and an alternative to traditional C2C transactional business models. There are already millions of these consumers, and this number is growing. In this model, consumer purchase decisions are driven by recommendations and endorsements in videos posted online by celebrities. The purpose of this paper is to determine the relational constructs within consumer relationships in the Internet celebrity business model and to investigate relationships between the constructs and consumer purchase intention. A questionnaire-based study was conducted with consumers who had an awareness of, or prior purchase experience with online celebrities. The results of exploratory factor analysis (EFA) and multiple regression analysis revealed three valid relational constructs: product experience sharing, lifestyle association, and real-time interaction. This study indicated that these constructs had the direct effect on consumer preference and purchase intention. The findings of this study provide insight into a business model in which online shopping is driven by celebrities. They suggest that online celebrities should pay more attention to product experience sharing, life style association and real-time interaction for managing their product promotions. These are the most salient factors with respect to the relational constructs identified in this study.

Keywords: customer relationship, customer to customer, Internet celebrity, online celebrity, online marketing, purchase intention

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Authors: Narupot Putwattana

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Changes in global situation such as environmental and economic crisis brought the new perspective for science education called integrative biology. STEM has been increasingly mentioned for several educational researches as the approach which combines the concept in Science (S), Technology (T), Engineering (E) and Mathematics (M) to apply in teaching and learning process so as to strengthen the 21st-century skills such as creativity and critical thinking. Recent studies demonstrated STEM as the pedagogy which described the engineering process along with the science classroom activities. So far, pedagogical contents for STEM explaining the content in biology have been scarce. A qualitative literature review was conducted so as to gather the articles based on electronic databases (google scholar). STEM education, engineering design, teaching and learning of biology were used as main keywords to find out researches involving with the application of STEM in biology teaching and learning process. All articles were analyzed to obtain appropriate teaching and learning model that unify the core concept of biology. The synthesized model comprised of engineering design, inquiry-based learning, biological prototype and biologically-inspired design (BID). STEM content and context integration were used as the theoretical framework to create the integrative biology instructional model for STEM education. Several disciplines contents such as biology, engineering, and technology were regarded for inquiry-based learning to build biological prototype. Direct and indirect integrations were used to provide the knowledge into the biology related STEM strategy. Meanwhile, engineering design and BID showed the occupational context for engineer and biologist. Technological and mathematical aspects were required to be inspected in terms of co-teaching method. Lastly, other variables such as critical thinking and problem-solving skills should be more considered in the further researches.

Keywords: biomimicry, engineering approach, STEM education, teaching and learning model

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Authors: Amit Kumar

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Accurate identification of deteriorated air quality regions is very helpful in devising better environmental practices and mitigation efforts. In the present study, an attempt has been made to identify the air pollutant dispersion patterns especially NOX due to vehicular and industrial sources over a rapidly developing urban city, Visakhapatnam (17°42’ N, 83°20’ E), India, during April 2009. Using the emission factors of different vehicles as well as the industry, a high resolution 1 km x 1 km gridded emission inventory has been developed for Visakhapatnam city. A dispersion model AERMOD with explicit representation of planetary boundary layer (PBL) dynamics and offline coupled through a developed coupler mechanism with a high resolution mesoscale model WRF-ARW resolution for simulating the dispersion patterns of NOX is used in the work. The meteorological as well as PBL parameters obtained by employing two PBL schemes viz., non-local Yonsei University (YSU) and local Mellor-Yamada-Janjic (MYJ) of WRF-ARW model, which are reasonably representing the boundary layer parameters are considered for integrating AERMOD. Significantly different dispersion patterns of NOX have been noticed between summer and winter months. The simulated NOX concentration is validated with available six monitoring stations of Central Pollution Control Board, India. Statistical analysis of model evaluated concentrations with the observations reveals that WRF-ARW of YSU scheme with AERMOD has shown better performance. The deteriorated air quality locations are identified over Visakhapatnam based on the validated model simulations of NOX concentrations. The present study advocates the utility of tNumerical Simulation of Air Pollutant Using Coupled AERMOD-WRF Modeling System over Visakhapatnam: A Case Studyhe developed gridded emission inventory of NOX with coupled WRF-AERMOD modeling system for air quality assessment over the study region.

Keywords: WRF-ARW, AERMOD, planetary boundary layer, air quality

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Authors: Jatinder Kumar, Ajay Bansal

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Simulation of a photocatalytic reactor helps in understanding the complex behavior of the photocatalytic degradation. Simulation also aids the designing and optimization of the photocatalytic reactor. Lack of simulation strategies is a huge hindrance in the commercialization of the photocatalytic technology. With the increased performance of computational resources, and development of simulation software, computational fluid dynamics (CFD) is becoming an affordable engineering tool to simulate and optimize reactor designs. In the present paper, a CFD (Computational fluid dynamics) model for simulating the performance of an immobilized-titanium dioxide based annular photocatalytic reactor was developed. The computational model integrates hydrodynamics, species mass transport, and chemical reaction kinetics using a commercial CFD code Fluent 6.3.26. The CFD model was based on the intrinsic kinetic parameters determined experimentally in a perfectly mixed batch reactor. Rhodamine B, a complex organic compound, was selected as a test pollutant for photocatalytic degradation. It was observed that CFD could become a valuable tool to understand and improve the photocatalytic systems.

Keywords: simulation, computational fluid dynamics (CFD), annular photocatalytic reactor, titanium dioxide

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Authors: Tahsien Mohamed Okasha

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We hypothesized that Post cardiac arrest patients with Glasgow coma scale (GCS) score of less than (8) and who will be exposed to therapeutic hypothermia protocol will exhibit improvement in their neurological performance. Purposive sample of 17 patients who were fulfilling the inclusion criteria during one year collected. The study carried out using Quasi-experimental research design. Four Tools used for data collection of this study: Demographic and medical data sheet, Post cardiac arrest health assessment sheet, Bedside Shivering Assessment Scale (BSAS), and Glasgow Pittsburgh cerebral performance category scale (CPC). Result: the mean age was X̅ ± SD = 53 ± 8.122 years, 47.1% were arrested because of cardiac etiology. 35.3% with initial arrest rhythm ventricular tachycardia (VT), 23.5% with ventricular fibrillation (VF), and 29.4% with A-Systole. Favorable neurological outcome was seen among 70.6%. There was significant statistical difference in WBC, Platelets, blood gases value, random blood sugar. Also Initial arrest rhythm, etiology of cardiac arrest, and shivering status were significantly correlated with cerebral performance categories score. therapeutic hypothermia has positive effects on neurological performance among post cardiac arrest patients with GCS score of less than (8). replication of the study on larger probability sample, with randomized control trial design. Further study for suggesting nursing protocol for patients undergoing therapeutic hypothermia.

Keywords: therapeutic hypothermia, neurological performance, after resuscitation from cardiac arrest., resuscitation

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Authors: Jelena R. Pejović, Nina N. Serdar

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This paper presents an analysis of the “Performance-Based” seismic design method, in order to overcome the perceived disadvantages and limitations of the existing seismic design approach based on force, in engineering practice. Bearing in mind, the specificity of the earthquake as a load and the fact that the seismic resistance of the structures solely depends on its behaviour in the nonlinear field, traditional seismic design approach based on force and linear analysis is not adequate. “Performance-Based” seismic design method is based on nonlinear analysis and can be used in everyday engineering practice. This paper presents the application of this method to eight-story high reinforced concrete building with combined structural system (reinforced concrete frame structural system in one direction and reinforced concrete ductile wall system in other direction). The nonlinear time-history analysis is performed on the spatial model of the structure using program Perform 3D, where the structure is exposed to forty real earthquake records. For considered building, large number of results were obtained. It was concluded that using this method we could, with a high degree of reliability, evaluate structural behavior under earthquake. It is obtained significant differences in the response of structures to various earthquake records. Also analysis showed that frame structural system had not performed well at the effect of earthquake records on soil like sand and gravel, while a ductile wall system had a satisfactory behavior on different types of soils.

Keywords: ductile wall, frame system, nonlinear time-history analysis, performance-based methodology, RC building

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Authors: Surya R. Niraula, Devendra B Chhetry, Girish K. Singh, S. Nagesh, Frederick A. Connell

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Background: Although random sampling is generally considered to be the gold standard for population-based research, the majority of drug abuse research is based on non-random sampling despite the well-known limitations of this kind of sampling. Method: We compared the statistical properties of two surveys of drug abuse in the same community: one using snowball sampling of drug users who then identified “friend controls” and the other using a random sample of non-drug users (controls) who then identified “friend cases.” Models to predict drug abuse based on risk factors were developed for each data set using conditional logistic regression. We compared the precision of each model using bootstrapping method and the predictive properties of each model using receiver operating characteristics (ROC) curves. Results: Analysis of 100 random bootstrap samples drawn from the snowball-sample data set showed a wide variation in the standard errors of the beta coefficients of the predictive model, none of which achieved statistical significance. One the other hand, bootstrap analysis of the random-sample data set showed less variation, and did not change the significance of the predictors at the 5% level when compared to the non-bootstrap analysis. Comparison of the area under the ROC curves using the model derived from the random-sample data set was similar when fitted to either data set (0.93, for random-sample data vs. 0.91 for snowball-sample data, p=0.35); however, when the model derived from the snowball-sample data set was fitted to each of the data sets, the areas under the curve were significantly different (0.98 vs. 0.83, p < .001). Conclusion: The proposed method of random sampling of controls appears to be superior from a statistical perspective to snowball sampling and may represent a viable alternative to snowball sampling.

Keywords: drug abuse, matched case-control study, non-probability sampling, probability sampling

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Authors: S. S. Singh, A. Bhattacharya, S. Bhattacharya

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The eukaryotic exosome complex plays a pivotal role in RNA biogenesis, maturation, surveillance and differential expression of various RNAs in response to varying environmental signals. The exosome is composed of evolutionary conserved nine core subunits and the associated exonucleases Rrp6 and Rrp44. Rrp6p is crucial for the processing of rRNAs, other non-coding RNAs, regulation of polyA tail length and termination of transcription. Rrp6p, a 3’-5’ exonuclease is required for degradation of 5’-external transcribed spacer (ETS) released from the rRNA precursors during the early steps of pre-rRNA processing. In the parasitic protist Entamoeba histolytica in response to growth stress, there occurs the accumulation of unprocessed pre-rRNA and 5’ ETS sub fragment. To understand the processes leading to this accumulation, we looked for Rrp6 and the exosome subunits in E. histolytica, by in silico approaches. Of the nine core exosomal subunits, seven had high percentage of sequence similarity with the yeast and human. The EhRrp6 homolog contained exoribonuclease and HRDC domains like yeast but its N- terminus lacked the PMC2NT domain. EhRrp6 complemented the temperature sensitive phenotype of yeast rrp6Δ cells suggesting conservation of biological activity. We showed 3’-5’ exoribonuclease activity of EhRrp6p with in vitro-synthesized appropriate RNAs substrates. Like the yeast enzyme, EhRrp6p degraded unstructured RNA, but could degrade the stem-loops slowly. Furthermore, immunolocalization revealed that EhRrp6 was nuclear-localized in normal cells but was diminished from nucleus during serum starvation, which could explain the accumulation of 5’ETS during stress. Our study shows functional conservation of EhRrp6p in E.histolytica, an early-branching eukaryote, and will help to understand the evolution of exosomal components and their regulatory function.

Keywords: entamoeba histolytica, exosome complex, rRNA processing, Rrp6

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Authors: A. J. Julius, E. Imoagene, O. A. Ganiyu

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The purpose of this study is to estimate the economic value of the services and functions rendered by the forest landscape using a conditional logit model. For this study, attributes and levels of forest landscape were chosen; specifically, attributes include topographical forest type, forest type, forest density, recreational factor (side trip, accessibility of valley), and willingness to participate (WTP). Based on these factors, 48 choices sets with balanced and orthogonal form using statistical analysis system (SAS) 9.1 was adopted. The efficiency of the questionnaire was 6.02 (D-Error. 0.1), and choice set and socio-economic variables were analyzed. To reduce the cognitive load of respondents, the 48 choice sets were divided into 4 types in the questionnaire, so that respondents could respond to 12 choice sets, respectively. The study populations were citizens from seven metropolitan cities including Ibadan, Ilorin, Osogbo, etc. and annual WTP per household was asked by using the interview questionnaire, a total of 267 copies were recovered. As a result, Oshogbo had 0.45, and the statistical similarities could not be found except for urban forests, forest density, recreational factor, and level of WTP. Average annual WTP per household for forest landscape was 104,758 Naira (Nigerian currency) based on the outcome from this model, total economic value of the services and functions enjoyed from Nigerian forest landscape has reached approximately 1.6 trillion Naira.

Keywords: economic valuation, urban cities, services, forest landscape, logit model, nigeria

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Authors: Lauren A. Bailey, Amber R. Childs, Nicola C. James, Murray I. Duncan, Alexander Winkler, Warren M. Potts

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For the persistence of fished populations in the Anthropocene, it is critical to predict how fished populations will respond to the coupled threats of exploitation and climate change for adaptive management. The resilience of fished populations will depend on their capacity for physiological plasticity and acclimatization in response to environmental shifts. However, there is evidence for the selection of physiological traits by capture fisheries. Hence, fish populations may have a limited scope for the rapid expansion of their tolerance ranges or physiological adaptation under fishing pressures. To determine the physiological vulnerability of fished populations in the Anthropocene, the metabolic performance was compared between a fished and spatially protected Chrysoblephus laticeps population in response to thermal variability. Individual aerobic scope phenotypes were quantified using intermittent flow respirometry by comparing changes in energy expenditure of each individual at ecologically relevant temperatures, mimicking variability experienced as a result of upwelling and downwelling events. The proportion of high and low-performance individuals were compared between the fished and spatially protected population. The fished population had limited aerobic scope phenotype diversity and fewer high-performance phenotypes, resulting in a significantly lower aerobic scope curve across low (10 °C) and high (24 °C) thermal treatments. The performance of fished populations may be compromised with predicted future increases in cold upwelling events. This requires the conservation of the physiologically fittest individuals in spatially protected areas, which can recruit into nearby fished areas, as a climate resilience tool.

Keywords: climate change, fish physiology, metabolic shifts, over-fishing, respirometry

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Authors: Louise Moles, Steve Riley, Sarah D. Lichenstein, Marzieh Babaeianjelodar, Robert Kohler, Annie Cheng, Corey Horien Abigail Greene, Wenjing Luo, Jonathan Ahern, Bohan Xu, Yize Zhao, Chun Chieh Fan, R. Todd Constable, Sarah W. Yip

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Background: Risks for depression are myriad and include both genetic and brain-based factors. However, relationships between these systems are poorly understood, limiting understanding of disease etiology, particularly at the developmental level. Methods: We use a data-driven machine learning approach connectome-based predictive modeling (CPM) to identify functional connectivity signatures associated with polygenic risk scores for depression (DEP-PRS) among youth from the Adolescent Brain and Cognitive Development (ABCD) study across diverse brain states, i.e., during resting state, during affective working memory, during response inhibition, during reward processing. Results: Using 10-fold cross-validation with 100 iterations and permutation testing, CPM identified connectivity signatures of DEP-PRS across all examined brain states (rho’s=0.20-0.27, p’s<.001). Across brain states, DEP-PRS was positively predicted by increased connectivity between frontoparietal and salience networks, increased motor-sensory network connectivity, decreased salience to subcortical connectivity, and decreased subcortical to motor-sensory connectivity. Subsampling analyses demonstrated that model accuracies were robust across random subsamples of N’s=1,000, N’s=500, and N’s=250 but became unstable at N’s=100. Conclusions: These data, for the first time, identify neural networks of polygenic depression risk in a large sample of youth before the onset of significant clinical impairment. Identified networks may be considered potential treatment targets or vulnerability markers for depression risk.

Keywords: genetics, functional connectivity, pre-adolescents, depression

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Authors: Jean Yves Trepanier, Sami Ammar, Sagnik Banik

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Lattice Boltzmann Method has been advantageous in simulating complex boundary conditions and solving for fluid flow parameters by streaming and collision processes. This paper includes the study of three different test cases in a confined domain using the method of the Lattice Boltzmann model. 1. An SRT (Single Relaxation Time) approach in the Lattice Boltzmann model is used to simulate Lid Driven Cavity flow for different Reynolds Number (100, 400 and 1000) with a domain aspect ratio of 1, i.e., square cavity. A moment-based boundary condition is used for more accurate results. 2. A Thermal Lattice BGK (Bhatnagar-Gross-Krook) Model is developed for the Rayleigh Benard convection for both test cases - Horizontal and Vertical Temperature difference, considered separately for a Boussinesq incompressible fluid. The Rayleigh number is varied for both the test cases (10^3 ≤ Ra ≤ 10^6) keeping the Prandtl number at 0.71. A stability criteria with a precise forcing scheme is used for a greater level of accuracy. 3. The phase change problem governed by the heat-conduction equation is studied using the enthalpy based Lattice Boltzmann Model with a single iteration for each time step, thus reducing the computational time. A double distribution function approach with D2Q9 (density) model and D2Q5 (temperature) model are used for two different test cases-the conduction dominated melting and the convection dominated melting. The solidification process is also simulated using the enthalpy based method with a single distribution function using the D2Q5 model to provide a better understanding of the heat transport phenomenon. The domain for the test cases has an aspect ratio of 2 with some exceptions for a square cavity. An approximate velocity scale is chosen to ensure that the simulations are within the incompressible regime. Different parameters like velocities, temperature, Nusselt number, etc. are calculated for a comparative study with the existing works of literature. The simulated results demonstrate excellent agreement with the existing benchmark solution within an error limit of ± 0.05 implicates the viability of this method for complex fluid flow problems.

Keywords: BGK, Nusselt, Prandtl, Rayleigh, SRT

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Authors: Saima Ali, Pathamanathan Rajeev, Imteaz A. Monzur

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In this paper, a brief review of the corrosion mechanism in buried pipe and modes of failure is provided together with the available corrosion models. Moreover, the sensitivity analysis is performed to understand the influence of corrosion model parameters on the remaining life estimation. Further, the probabilistic analysis is performed to propagate the uncertainty in the corrosion model on the estimation of the renaming life of the pipe. Finally, the comparison among the corrosion models on the basis of the remaining life estimation will be provided to improve the renewal plan.

Keywords: corrosion, pit depth, sensitivity analysis, exposure period

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Authors: A. M. Plante, F. O’Halloran, A. L. McCarthy

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By 2050 it is projected that 2 billion of the global population will be more than 60 years old. Older adults have unique dietary requirements and aging is associated with physiological changes that affect appetite, sensory perception, metabolism, and digestion. Therefore, it is essential that foods recommended and designed for older adults promote healthy aging. To assess cheese as a functional food for the elderly, a range of commercial cheese products were selected and compared for their antioxidant properties. Cheese from various milk sources (bovine, goats, sheep) with different textures and fat content, including cheddar, feta, goats, brie, roquefort, halloumi, wensleydale and gouda, were initially digested with two different simulated in vitro gastrointestinal digestion (SGID) models. One SGID model represented a validated in vitro adult digestion system and the second model, an elderly SGID, was designed to consider the physiological changes associated with aging. The antioxidant potential of all cheese digestates was investigated using in vitro chemical-based antioxidant assays, (2,2-Diphenyl-1-picrylhydrazyl (DPPH) radical scavenging, ferric reducing antioxidant power (FRAP) and total phenolic content (TPC)). All adult model digestates had high antioxidant activity across both DPPH ( > 70%) and FRAP ( > 700 µM Fe²⁺/kg.fw) assays. Following in vitro digestion using the elderly SGID model, full-fat red cheddar, low-fat white cheddar, roquefort, halloumi, wensleydale, and gouda digestates had significantly lower (p ≤ 0.05) DPPH radical scavenging properties compared to the adult model digestates. Full-fat white cheddar had higher DPPH radical scavenging activity following elderly SGID digestion compared to the adult model digestate, but the difference was not significant. All other cheese digestates from the elderly model were comparable to the digestates from the adult model in terms of radical scavenging activity. The FRAP of all elderly digestates were significantly lower (p ≤ 0.05) compared to the adult digestates. Goats cheese was significantly higher (p ≤ 0.05) in FRAP (718 µM Fe²/kg.fw) compared to all other digestates in the elderly model. TPC levels in the soft cheeses (feta, goats) and low-fat cheeses (red cheddar, white cheddar) were significantly lower (p ≤ 0.05) in the elderly digestates compared to the adult digestates. There was no significant difference in TPC levels, between the elderly and adult model for full-fat cheddar (red, white), roquefort, wensleydale, gouda, and brie digestates. Halloumi cheese was the only cheese that was significantly higher in TPC levels following elderly digestion compared to adult digestates. Low fat red cheddar had significantly higher (p ≤ 0.05) TPC levels compared to all other digestates for both adult and elderly digestive systems. Findings from this study demonstrate that aging has an impact on the bioactivity of cheese, as antioxidant activity and TPC levels were lower, following in vitro elderly digestion compared to the adult model. For older adults, soft cheese, particularly goats cheese, was associated with high radical scavenging and reducing power, while roquefort cheese had low antioxidant activity. Also, elderly digestates of halloumi and low-fat red cheddar were associated with high TPC levels. Cheese has potential as a functional food for the elderly, however, bioactivity can vary depending on the cheese matrix. Funding for this research was provided by the RISAM Scholarship Scheme, Cork Institute of Technology, Ireland.

Keywords: antioxidants, cheese, in-vitro digestion, older adults

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Authors: Murat Erdoğdu, Murat Koçyiğit

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Brand image and brand loyalty are among the most important relational marketing elements for brand owners to be able to set up long – term relationships with their customers and to maintain these relationships. Brand owners improve their brand images with the positive perceptions remaining in the consumers’ minds. In addition, they try to find the customers that are both emotionally and behaviourally faithful to themselves in order to set up long – term relationships. Therefore, the aim of this study is to analyse the effects of the brand image that has a very important role among relational marketing elements on the brand loyalty in terms of the variables such as the perceived value, the trust in brand and the brand satisfaction. In this context, a conceptual model was created to determine the effect of the brand image on the brand loyalty thanks to the Structural Equation Model (SEM). According to this aim and this model, the study was carried out in the scope of the data collected through the questionnaires in Konya with the method of convenience sampling. The results of the research showed that the brand image has positive significant effects on the perceived value and the trust in brand and that the trust in brand has positive significant effects on the brand satisfaction, and that the brand satisfaction has positive significant effects on the brand loyalty. Thus, the hypotheses that the brand image has direct effects on the perceived value and the trust in brand and that the trust in brand has direct effects on the brand satisfaction and that the brand satisfaction has direct effects on the brand loyalty were supported. In addition, the findings about whether the perceived value has a significant effect on the brand satisfaction were also acquired.

Keywords: brand image, brand loyalty, perceived value, satisfaction, trust

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Authors: Lucas Wilman Crispim, Patrícia Hallack, Maikel Ballester

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This work aims at modeling electric discharges in gas mixtures. The mathematical model mimics the ignition process in a commercial spark-plug when a high voltage is applied to the plug terminals. A longitudinal unidimensional Cartesian domain is chosen for the simulation region. Energy and mass transfer are considered for a macroscopic fluid representation, while energy transfer in molecular collisions and chemical reactions are contemplated at microscopic level. The macroscopic model is represented by a set of uncoupled partial differential equations. Microscopic effects are studied within a discrete model for electronic and molecular collisions in the frame of ZDPlasKin, a plasma modeling numerical tool. The BOLSIG+ solver is employed in solving the electronic Boltzmann equation. An operator splitting technique is used to separate microscopic and macroscopic models. The simulation gas is a mixture of atomic Argon neutral, excited and ionized. Spatial and temporal evolution of such species and temperature are presented and discussed.

Keywords: CFD, electronic discharge, ignition, spark plug

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Authors: Wenjiang Deng, Tian Mou, Yudi Pawitan, Trung Nghia Vu

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Estimation of isoform-level gene expression from RNA-seq data depends on simplifying assumptions, such as uniform reads distribution, that are easily violated in real data. Such violations typically lead to biased estimates. Most existing methods provide a bias correction step(s), which is based on biological considerations, such as GC content–and applied in single samples separately. The main problem is that not all biases are known. For example, new technologies such as single-cell RNA-seq (scRNA-seq) may introduce new sources of bias not seen in bulk-cell data. This study introduces a method called XAEM based on a more flexible and robust statistical model. Existing methods are essentially based on a linear model Xβ, where the design matrix X is known and derived based on the simplifying assumptions. In contrast, XAEM considers Xβ as a bilinear model with both X and β unknown. Joint estimation of X and β is made possible by simultaneous analysis of multi-sample RNA-seq data. Compared to existing methods, XAEM automatically performs empirical correction of potentially unknown biases. XAEM implements an alternating expectation-maximization (AEM) algorithm, alternating between estimation of X and β. For speed XAEM utilizes quasi-mapping for read alignment, thus leading to a fast algorithm. Overall XAEM performs favorably compared to other recent advanced methods. For simulated datasets, XAEM obtains higher accuracy for multiple-isoform genes, particularly for paralogs. In a differential-expression analysis of a real scRNA-seq dataset, XAEM achieves substantially greater rediscovery rates in an independent validation set.

Keywords: alternating EM algorithm, bias correction, bilinear model, gene expression, RNA-seq

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Authors: K. Cartelier, D. Aime, V. Vernoud, J. Buitink, J. M. Prosperi, K. Gallardo, C. Le Signor

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Legumes can produce protein-rich seeds without nitrogen fertilizer through root symbiosis with nitrogen-fixing rhizobia. Rich in lysine, these proteins are used for human nutrition and animal feed. However, the instability of seed protein yield and quality due to environmental fluctuations limits the wider use of legumes such as pea. Breeding efforts are needed to optimize and stabilize seed nutritional value, which requires to identify the genetic determinism of seed protein plasticity in response to the environment. Towards this goal, we have studied the plasticity of protein content and composition of seeds from a collection of 200 Medicago truncatula ecotypes grown under four controlled conditions (optimal, drought, and winter/spring sowing). A quantitative analysis of one-dimensional protein profiles of these mature seeds was performed and plasticity indices were calculated from each abundant protein band. Genome-Wide Association Studies (GWAS) from these data identified major GWAS hotspots, from which a list of candidate genes was obtained. A Gene Ontology Enrichment Analysis revealed an over-representation of genes involved in several amino acid metabolic pathways. This led us to propose that environmental variations are likely to modulate amino acid balance, thus impacting seed protein composition. The selection of candidate genes for controlling the plasticity of seed protein composition was refined using transcriptomics data from developing Medicago truncatula seeds. The pea orthologs of key genes were identified for functional studies by mean of TILLING (Targeting Induced Local Lesions in Genomes) lines in this crop. We will present how this study highlighted mechanisms that could govern seed protein plasticity, providing new cues towards the stabilization of legume seed quality.

Keywords: GWAS, Medicago truncatula, plasticity, seed, storage proteins

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Authors: Ella Tyuryumina, Alexey Neznanov

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Finding algorithms to predict the growth of tumors has piqued the interest of researchers ever since the early days of cancer research. A number of studies were carried out as an attempt to obtain reliable data on the natural history of breast cancer growth. Mathematical modeling can play a very important role in the prognosis of tumor process of breast cancer. However, mathematical models describe primary tumor growth and metastases growth separately. Consequently, we propose a mathematical growth model for primary tumor and primary metastases which may help to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoM-IV and corresponding software. We are interested in: 1) modelling the whole natural history of primary tumor and primary metastases; 2) developing adequate and precise CoM-IV which reflects relations between PT and MTS; 3) analyzing the CoM-IV scope of application; 4) implementing the model as a software tool. The CoM-IV is based on exponential tumor growth model and consists of a system of determinate nonlinear and linear equations; corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and primary metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for primary metastases; 3) ‘visible period’ for primary metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. Thus, the CoM-IV model and predictive software: a) detect different growth periods of primary tumor and primary metastases; b) make forecast of the period of primary metastases appearance; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of BC and facilitate optimization of diagnostic tests. The following are calculated by CoM-IV: the number of doublings for ‘nonvisible’ and ‘visible’ growth period of primary metastases; tumor volume doubling time (days) for ‘nonvisible’ and ‘visible’ growth period of primary metastases. The CoM-IV enables, for the first time, to predict the whole natural history of primary tumor and primary metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-IV describes correctly primary tumor and primary distant metastases growth of IV (T1-4N0-3M1) stage with (N1-3) or without regional metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and manifestation of primary metastases.

Keywords: breast cancer, exponential growth model, mathematical modelling, primary metastases, primary tumor, survival

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Authors: Mohammad Moonesun, Ehsan Asadi Asrami, Julia Bodnarchuk

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In the case of Solar Autonomous Underwater Vehicle, which uses photovoltaic panels to provide its required power, due to limitation of energy, accurate estimation of resistance and energy has major sensitivity. In this work, hydrodynamic calculations by numerical method for a solar autonomous underwater vehicle equipped by two 50 W photovoltaic panels has been studied. To evaluate the required power and energy, hull hydrodynamic resistance in several velocities should be taken into account. To do this assessment, the ANSYS FLUENT 18 applied as Computational Fluid Dynamics (CFD) tool that solves Reynolds Average Navier Stokes (RANS) equations around AUV hull, and K-ω SST is used as turbulence model. To validate of solution method and modeling approach, the model of Myring submarine that it’s experimental data was available, is simulated. There is good agreement between numerical and experimental results. Also, these results showed that the K-ω SST Turbulence model is an ideal method to simulate the AUV motion in low velocities.

Keywords: underwater vehicle, hydrodynamic resistance, numerical modelling, CFD, RANS

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Authors: Jutamas Wisansing, Thanakarn Vongvisitsin, Udom Hongchatikul

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Food could be used to open up a dialogue about local heritage. Contributing to the world sustainable consumption mission, this research aims to explore the linkages between agriculture, senses of place and performing arts. Thailand and its destination marketing ‘Discover Thainess’ was selected as a working principle, enabling a case example of how the three elements could be conceptualized. The model offered an integrated institutional arrangement where diverse entities could be formed to design how Thainess (local heritage) could be interpreted and embedded into an art of food. Using case study research approach, three areas (Chiangmai, Samutsongkram and Ban Rai Gong King) representing 3 different scales of tourism development were selected. Based on a theoretical analysis, a working model was formulated. An action research was then designed to experiment how the model could be materialized. Brainstorming elicitation and in-depth interview were employed to reflect on how each element could be integrated. The result of this study offered an innovation on how food tourism could be profoundly interpreted and how tourism development could enhance value creation for agricultural based community. The outcomes of the research present co-creative multi-stakeholder model and the value creation method through the whole supply chain of Thai gastronomy. The findings have been eventually incorporated into ‘gastro-diplomacy’ strategy for Thai tourism.

Keywords: community-based tourism, gastro-diplomacy, gastronomy tourism, sustainable tourism development

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Authors: Gunawan Prayitno, Kakuya Matshusima, Kiyoshi Kobayashi

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Indonesia’s rural regions are characterized by wide-spread poverty, under-employment, and surplus of low-skilled labor. The aim of this paper is to empirically prove the effect of social ties (strong and weak tie) as social capital construct on households’ migration decision in the case of developing country (Indonesia). The methodology incorporated indicators of observe variables (four demographic attributes data: income, occupation, education, and family members) and indicators of latent variables (ties to neighbors, ties to community and sense of place) provided by responses to survey questions to aid in estimating the model. Using structural equation model that we employed in Mplus program, the result of our study shows that ties to community positively have a significant impact to the decision of respondents (migrate or not). Besides, education as observed variable directly influences the migration decisions. It seems that higher level of education have impact on migration decision. Our current model so far could explain the relation between social capital and migration decision choice.

Keywords: migration, ties to community, ties to neighbors, education

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Authors: Mohd Salim Mahtab, Izharul Haq Farooqi, Anwar Khursheed

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Advanced oxidation processes (AOPs) based on Fenton are versatile options for treating complex wastewaters containing refractory compounds. However, the classical Fenton process (CFP) has limitations, such as high sludge production and reagent dosage, which limit its broad use and result in secondary contamination. As a result, long-term solutions are required for process intensification and the removal of these impediments. This study shows that Fenton sludge could serve as a catalyst in the Fe³⁺/Fe²⁺ reductive pathway, allowing non-regenerated sludge to be reused for complex wastewater treatment, such as landfill leachate treatment, even in the absence of Fenton's reagents. Experiments with and without pH adjustments in stages I and II demonstrated that an acidic pH is desirable. Humic compounds in leachate could improve the cycle of Fe³⁺/Fe²⁺ under optimal conditions, and the chemical oxygen demand (COD) removal efficiency was 22±2% and 62±2%% in stages I and II, respectively. Furthermore, excellent total suspended solids (TSS) removal (> 95%) and color removal (> 80%) were obtained in stage II. The processes underlying synergistic (oxidation/coagulation/adsorption) effects were addressed. The design of the experiment (DOE) is growing increasingly popular and has thus been implemented in the chemical, water, and environmental domains. The relevance of the statistical model for the desired response was validated using the explicitly stated optimal conditions. The operational factors, characteristics of reused sludge, toxicity analysis, cost calculation, and future research objectives were also discussed. Reusing non-regenerated Fenton sludge, according to the study's findings, can minimize hazardous solid toxic emissions and total treatment costs.

Keywords: advanced oxidation processes, catalysis, Fe³⁺/Fe²⁺ cycle, fenton sludge

Procedia PDF Downloads 78