Search results for: the nuclear shell model

Authors: Matthew Perkins-McVey

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The pharmacological arm of mental health treatment is in a state of crisis. The promises of the Prozac century have fallen short; the number of different therapeutically significant medications that successfully complete development shrinks with every passing year, and the demand for better treatments only grows. Answering these hardships is a renewed optimism concerning the efficacy of controlled psychedelic therapy, a renaissance that has seen the return of a familiar concept: intoxication as a model psychosis. First appearing in the mid-19th century and featuring in an array of 20th century efforts in psychedelic research, model psychosis has, once more, come to the foreground of psychedelic research. And yet, little has been made of where this peculiar, perhaps even intoxicatingly mad, the idea originates. This paper seeks to uncover the conceptual foundations underlying the early emergence of model psychosis. This narrative will explore the conceptual foundations behind their independent development of the concept of model psychosis, considering their similarities and differences. In the course of this examination, it becomes apparent that the definition of endogenous psychosis, which formed in the mid-19th century, is the direct product of emerging understandings of exogenous psychosis, or model psychosis. Ultimately, the goal is not merely to understand how and why model psychosis became thinkable but to examine how seemingly secondary concept changes can engender new ways of being a psychiatric subject.

Keywords: history of psychiatry, model psychosis, history of medicine, history of science

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Authors: Jang kyun Cho, Jeong-dong Lee

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The advent of the Internet, mobile communications, and social network services has stimulated social interactions among consumers, allowing people to affect one another’s innovation adoptions by exchanging information more frequently and more quickly. Previous diffusion models, such as the Bass model, however, face limitations in reflecting such recent phenomena in society. These models are weak in their ability to model interactions between agents; they model aggregated-level behaviors only. The agent based model, which is an alternative to the aggregate model, is good for individual modeling, but it is still not based on an economic perspective of social interactions so far. This study assumes the presence of social utility from other consumers in the adoption of innovation and investigates the effect of individual interactions on innovation diffusion by developing a new model called the interaction-based diffusion model. By comparing this model with previous diffusion models, the study also examines how the proposed model explains innovation diffusion from the perspective of economics. In addition, the study recommends the use of a small-world network topology instead of cellular automata to describe innovation diffusion. This study develops a model based on individual preference and heterogeneous social interactions using utility specification, which is expandable and, thus, able to encompass various issues in diffusion research, such as reservation price. Furthermore, the study proposes a new framework to forecast aggregated-level market demand from individual level modeling. The model also exhibits a good fit to real market data. It is expected that the study will contribute to our understanding of the innovation diffusion process through its microeconomic theoretical approach.

Keywords: innovation diffusion, agent based model, small-world network, demand forecasting

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Authors: Retius Chifurira

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Logistic regression model is the most used regression model to predict meteorological drought probabilities. When the dependent variable is extreme, the logistic model fails to adequately capture drought probabilities. In order to adequately predict drought probabilities, we use the generalized linear model (GLM) with the quantile function of the generalized extreme value distribution (GEVD) as the link function. The method maximum likelihood estimation is used to estimate the parameters of the generalized extreme value (GEV) regression model. We compare the performance of the logistic and the GEV regression models in predicting drought probabilities for Zimbabwe. The performance of the regression models are assessed using the goodness-of-fit tests, namely; relative root mean square error (RRMSE) and relative mean absolute error (RMAE). Results show that the GEV regression model performs better than the logistic model, thereby providing a good alternative candidate for predicting drought probabilities. This paper provides the first application of GLM derived from extreme value theory to predict drought probabilities for a drought-prone country such as Zimbabwe.

Keywords: generalized extreme value distribution, general linear model, mean annual rainfall, meteorological drought probabilities

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Authors: Dorota Miroslaw-Swiatek, Mateusz Grygoruk, Sylwia Szporak

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We applied a two-dimensional surface water flow model with irregular wet boundaries. In this model, flow equations are in the form of a 2-D, non-linear diffusion equations which allows to account spatial variations in flow resistance and topography. Calculation domain to simulate the flow pattern in the floodplain is congruent with a Digital Elevation Model (DEM) grid. The rate and direction of sheet flow in wetlands is affected by vegetation type and density, therefore the developed model take into account spatial distribution vegetation resistance to the water flow. The model was tested in a part of the Biebrza Valley, of an outstanding heterogeneity in the elevation and flow resistance distributions due to various ecohydrological conditions and management measures. In our approach we used the highest-possible quality of the DEM in order to obtain hydraulic slopes and vegetation distribution parameters for the modelling. The DEM was created from the cloud of points measured in the LiDAR technology. The LiDAR reflects both the land surface as well as all objects on top of it such as vegetation. Depending on the density of vegetation cover the ability of laser penetration is variable. Therefore to obtain accurate land surface model the “vegetation effect” was corrected using data collected in the field (mostly the vegetation height) and satellite imagery such as Ikonos (to distinguish different vegetation types of the floodplain and represent them spatially). Model simulation was performed for the spring thaw flood in 2009.

Keywords: floodplain flow, Biebrza valley, model simulation, 2D surface flow model

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Authors: Young-Hyun Seo, Hyunwoo Park, Dong-Kyu Kim, Seung-Young Kho

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The purpose of this study is providing an improved mode choice model considering parameters including age grouping of prime-aged and old age. In this study, 2010 Household Travel Survey data were used and improper samples were removed through the analysis. Chosen alternative, date of birth, mode, origin code, destination code, departure time, and arrival time are considered from Household Travel Survey. By preprocessing data, travel time, travel cost, mode, and ratio of people aged 45 to 55 years, 55 to 65 years and over 65 years were calculated. After the manipulation, the mode choice model was constructed using LIMDEP by maximum likelihood estimation. A significance test was conducted for nine parameters, three age groups for three modes. Then the test was conducted again for the mode choice model with significant parameters, travel cost variable and travel time variable. As a result of the model estimation, as the age increases, the preference for the car decreases and the preference for the bus increases. This study is meaningful in that the individual and households characteristics are applied to the aggregate model.

Keywords: age grouping, aging, mode choice model, multinomial logit model

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Authors: Li Xiaoge, Wang Chaodong

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We introduce the first Chinese Coreference Resolution Model based on BERT (CCRM-BERT) and show that it significantly outperforms all previous work. The key idea is to consider the features of the mention, such as part of speech, width of spans, distance between spans, etc. And the influence of each features on the model is analyzed. The model computes mention embeddings that combine BERT with features. Compared to the existing state-of-the-art span-ranking approach, our model significantly improves accuracy on the Chinese OntoNotes benchmark.

Keywords: BERT, coreference resolution, deep learning, nature language processing

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Authors: Awol Seid Ebrie

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HIV results as an incurable disease, AIDS. After a person is infected with virus, the virus gradually destroys all the infection fighting cells called CD4 cells and makes the individual susceptible to opportunistic infections which cause severe or fatal health problems. Several studies show that the CD4 cells count is the most determinant indicator of the effectiveness of the treatment or progression of the disease. The objective of this paper is to investigate the progression of the disease over time among patient under HAART treatment. Two main approaches of the generalized multilevel ordinal models; namely the proportional odds model and the nonproportional odds model have been applied to the HAART data. Also, the multilevel part of both models includes random intercepts and random coefficients. In general, four models are explored in the analysis and then the models are compared using the deviance information criteria. Of these models, the random coefficients nonproportional odds model is selected as the best model for the HAART data used as it has the smallest DIC value. The selected model shows that the progression of the disease increases as the time under the treatment increases. In addition, it reveals that gender, baseline clinical stage and functional status of the patient have a significant association with the progression of the disease.

Keywords: nonproportional odds model, proportional odds model, random coefficients model, random intercepts model

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Authors: Babak Bashari Rad

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A metamorphic computer virus uses different code transformation techniques to mutate its body in duplicated instances. Characteristics and function of new instances are mostly similar to their parents, but they cannot be easily detected by the majority of antivirus in market, as they depend on string signature-based detection techniques. The purpose of this research is to propose a Hidden Markov Model for classification of metamorphic viruses in executable files. In the proposed solution, portable executable files are inspected to extract the instructions opcodes needed for the examination of code. A Hidden Markov Model trained on portable executable files is employed to classify the metamorphic viruses of the same family. The proposed model is able to generate and recognize common statistical features of mutated code. The model has been evaluated by examining the model on a test data set. The performance of the model has been practically tested and evaluated based on False Positive Rate, Detection Rate and Overall Accuracy. The result showed an acceptable performance with high average of 99.7% Detection Rate.

Keywords: malware classification, computer virus classification, metamorphic virus, metamorphic malware, Hidden Markov Model

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Authors: Heung Sun Yoon, Jong Tae Kim

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In this paper, we present an activity diagram model for double-loop control self-adaptive braking system. Since activity diagram helps to improve visibility of self-adaption, we can easily find where improvement is needed on double-loop control. Double-loop control is adopted since the design conditions and actual conditions can be different. The system is reconfigured in runtime by using double-loop control. We simulated to verify and validate our model by using MATLAB. We compared single-loop control model with double-loop control model. Simulation results show that double-loop control provides more consistent brake power control than single-loop control.

Keywords: activity diagram, automotive, braking system, double-loop, self-adaptive, UML, vehicle

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Authors: Carlos G. Santos, Frederico A. Genezini, A. P. Dos Santos, H. Yorivaz, P. T. D. Siqueira

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The Prompt-Gamma Activation Analysis (PGAA) is a valuable technique for investigating the elemental composition of various samples. However, the installation of a PGAA system entails specific conditions such as filtering the neutron beam according to the target and providing adequate shielding for both users and detectors. These requirements incur substantial costs, exceeding $100,000, including manpower. Nevertheless, a cost-effective approach involves leveraging an existing neutron beam facility to create a hybrid system integrating PGAA and Neutron Tomography (NT). The IEA-R1 nuclear reactor at IPEN/USP possesses an NT facility with suitable conditions for adapting and implementing a PGAA device. The NT facility offers a thermal flux slightly colder and provides shielding for user protection. The key additional requirement involves designing detector shielding to mitigate high gamma ray background and safeguard the HPGe detector from neutron-induced damage. This study employs Monte Carlo simulations with the MCNP6 code to optimize the collimator plug for PGAA within the IEA-R1 NT facility. Three collimator models are proposed and simulated to assess their effectiveness in shielding gamma and neutron radiation from nucleon fission. The aim is to achieve a focused prompt-gamma signal while shielding ambient gamma radiation. The simulation results indicate that one of the proposed designs is particularly suitable for the PGAA-NT hybrid system.

Keywords: MCNP6.1, neutron, prompt-gamma ray, prompt-gamma activation analysis

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Authors: Ahmad Zaini, F. Muhammad Reza Hadafi, Surya Sumpeno, Muhtadin, Mochamad Hariadi

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The lack of information about museum’s collection reduces the number of visits of museum. Museum’s revitalization is an urgent activity to increase the number of visits. The research's roadmap is building a web-based application that visualizes museum in the virtual form including museum's statue reconstruction in the form of 3D. This paper describes implementation of three-dimensional model reconstruction method based on light-strip pattern on the museum statue using 3D scanner. Noise removal, alignment, meshing and refinement model's processes is implemented to get a better 3D object reconstruction. Model’s texture derives from surface texture mapping between object's images with reconstructed 3D model. Accuracy test of dimension of the model is measured by calculating relative error of virtual model dimension compared against the original object. The result is realistic three-dimensional model textured with relative error around 4.3% to 5.8%.

Keywords: 3D reconstruction, light pattern structure, texture mapping, museum

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Authors: Ae Ra Han, Taek Hoo Lee, Sun Zoo Kim, Hwa Young Lee

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Introduction: Ovarian endometrioma is one of the important causes of poor ovarian reserve and up to half of them have recurred. However, the treatment for recurrence prevention has limited efficiency and repeated surgical management makes worsen the ovarian reserve. To find better management for recurrence prevention, we investigated risk factors and biomarkers for the recurrence of ovarian endometrioma. Methods: The medical records of women with the history of surgical dissection for ovarian endometrioma were collected. After exclusion of the cases with concurrent hysterectomy, been menopaused during follow-up, incomplete medical record, and loss of follow-up, a total of 134 women were enrolled. Immunohistochemical staining for progesterone receptor isoform B (PR-B) and nuclear factor kappa B (NFκB) was done with the fixed tissue blocks of their endometriomas which were collected at the time of surgery. Results: Severity of dysmenorrhea and co-existence of adenomyosis had significant correlation with recurrence of endometrioma. Increased PR-B (P = .041) and decreased NFκB (P = .036) immunoreactivity were found in recurrent group. Serum CA-125 level at the time of recurrence was higher than the highest level of CA-125 during follow-up in unrecurred group (55.6 vs. 21.3 U/mL, P = .014). Conclusion: We found that the severity of dysmenorrhea and coexistence of adenomyosis are risk factors for recurrence of ovarian endometrioma, and serial follow-up of CA-125 is effective to detect and prevent the recurrence. However, to determine the possibility of immunoreactivity of PR-B and NFκB as biomarkers for ovarian endometrioma, further studies of various races and large numbers with prospective design are needed.

Keywords: endometriosis, recurrence, biomarker, risk factor

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Authors: Mengke Zhan, Cheng-Gang Xie, Jian-Jun Shu

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A venturi flowmeter is a common device used in multiphase flow rate measurement in the upstream oil and gas industry. Having a robust computational model for multiphase flow in a venturi is desirable for understanding the gas-liquid and fluid-pipe interactions and predicting pressure and phase distributions under various flow conditions. A steady Eulerian-Eulerian framework is used to simulate upward gas-liquid flow in a vertical venturi. The simulation results are compared with experimental measurements of venturi differential pressure and chord-averaged gas holdup in the venturi throat section. The choice of turbulence model is nontrivial in the multiphase flow modelling in a venturi. The performance cross-comparison of the k-ϵ model, Reynolds stress model (RSM) and shear-stress transport (SST) k-ω turbulence model is made in the study. In terms of accuracy and computational cost, the SST k-ω turbulence model is observed to be the most efficient.

Keywords: computational fluid dynamics (CFD), gas-liquid flow, turbulence modelling, venturi

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Authors: Kyeong Hoon Park, Taiji Mazuda

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High damping rubber (HDR) bearings are dissipating devices mainly used in seismic isolation systems and have a great damping performance. Although many studies have been conducted on the dynamic model of HDR bearings, few models can reflect phenomena such as dependency of experienced shear strain on initial history. In order to develop a model that can represent the dependency of experienced shear strain of HDR by Mullins effect, dynamic loading test was conducted using HDR specimen. The reaction of HDR was measured by applying a horizontal vibration using a hybrid actuator under a constant vertical load. Dynamic program analysis was also performed after dynamic loading test. The dynamic model applied in program analysis is a bilinear type double-target model. This model is modified from typical bilinear model. This model can express the nonlinear characteristics related to the initial history of HDR bearings. Based on the dynamic loading test and program analysis results, equivalent stiffness and equivalent damping ratio were calculated to evaluate the mechanical properties of HDR and the feasibility of the bilinear type double-target model was examined.

Keywords: base-isolation, bilinear model, high damping rubber, loading test

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Authors: Anurag Savarnya

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The reliability of the various parts of electric mining shovel has been assessed through the application of Weibull Model. The study was initiated to find reliability of components of electric mining shovel. The paper aims to optimize the reliability of components and increase the life cycle of component. A multilevel decomposition of the electric mining shovel was done and maintenance records were used to evaluate the failure data and appropriate system characterization was done to model the system in terms of reasonable number of components. The approach used develops a mathematical model to assess the reliability of the electric mining shovel components. The model can be used to predict reliability of components of the hydraulic mining shovel and system performance. Reliability is an inherent attribute to a system. When the life-cycle costs of a system are being analyzed, reliability plays an important role as a major driver of these costs and has considerable influence on system performance. It is an iterative process that begins with specification of reliability goals consistent with cost and performance objectives. The data were collected from an Indian open cast coal mine and the reliability of various components of the electric mining shovel has been assessed by following a Weibull Model.

Keywords: reliability, Weibull model, electric mining shovel

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Authors: Budi Nurani Ruchjana, Atje Setiawan Abdullah, I. Gede Nyoman Mindra Jaya, Eddy Hermawan

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In this paper, we propose the application package to estimate parameters of spatiotemporal model based on the multivariate time series analysis using the R open-source software. We build packages mainly to estimate the parameters of the Generalized Space Time Autoregressive (GSTAR) model. GSTAR is a combination of time series and spatial models that have parameters vary per location. We use the method of Ordinary Least Squares (OLS) and use the Mean Average Percentage Error (MAPE) to fit the model to spatiotemporal real phenomenon. For case study, we use oil production data from volcanic layer at Jatibarang Indonesia or climate data such as rainfall in Indonesia. Software R is very user-friendly and it is making calculation easier, processing the data is accurate and faster. Limitations R script for the estimation of model parameters spatiotemporal GSTAR built is still limited to a stationary time series model. Therefore, the R program under windows can be developed either for theoretical studies and application.

Keywords: GSTAR Model, MAPE, OLS method, oil production, R software

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Authors: Watcharin Sangma, Onsiri Chanmuang, Pitsanu Tongkhow

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A forecasting model for steel demand uncertainty in Thailand is proposed. It consists of trend, autocorrelation, and outliers in a hierarchical Bayesian frame work. The proposed model uses a cumulative Weibull distribution function, latent first-order autocorrelation, and binary selection, to account for trend, time-varying autocorrelation, and outliers, respectively. The Gibbs sampling Markov Chain Monte Carlo (MCMC) is used for parameter estimation. The proposed model is applied to steel demand index data in Thailand. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) criteria are used for model comparison. The study reveals that the proposed model is more appropriate than the exponential smoothing method.

Keywords: forecasting model, steel demand uncertainty, hierarchical Bayesian framework, exponential smoothing method

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Authors: Soroor K. H. Al-Khafaji, Manal Mohammad Abed

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The research aim of this paper is to evaluate the reliability of a complex engineering system and to design a fuzzy model for the reliability estimation. The designed model has been applied on Vegetable Oil Purification System (neutralization system) to help the specialist user based on the concept of FMEA (Failure Mode and Effect Analysis) to estimate the reliability of the repairable system at the vegetable oil industry. The fuzzy model has been used to predict the system reliability for a future time period, depending on a historical database for the two past years. The model can help to specify the system malfunctions and to predict its reliability during a future period in more accurate and reasonable results compared with the results obtained by the traditional method of reliability estimation.

Keywords: fuzzy logic, reliability, repairable systems, FMEA

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Authors: Kuan-Chou Chen

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This paper will demonstrate a simulation model of an information security system by using the systems dynamic approach. The relationships in the system model are designed to be simple and functional and do not necessarily represent any particular information security environments. The purpose of the paper aims to develop a generic system dynamic information security system model with implications on information security research. The interrelated and interdependent relationships of five primary sectors in the system dynamic model will be presented in this paper. The integrated information security systems model will include (1) information security characteristics, (2) users, (3) technology, (4) business functions, and (5) policy and management. Environments, attacks, government and social culture will be defined as the external sector. The interactions within each of these sectors will be depicted by system loop map as well. The proposed system dynamic model will not only provide a conceptual framework for information security analysts and designers but also allow information security managers to remove the incongruity between the management of risk incidents and the management of knowledge and further support information security managers and decision makers the foundation for managerial actions and policy decisions.

Keywords: system thinking, information security systems, security management, simulation

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Authors: Semih Sözer

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One of the most common issues in economic systems is understanding characteristics of economic activities in cities and regions. Although there are critics to economic base models in conceptual and empirical aspects, these models are useful tools to examining the economic structure of a nation, regions or cities. This paper uses one of the methodologies of economic base models namely the location quotients model. Data for this model includes employment numbers of provinces and NUTS II regions in Turkey. Time series of data covers the years of 1990, 2000, 2003, and 2009. Aim of this study is finding which sectors are export-base and which sectors are import-base in provinces and regions. Model results show that big provinces or powerful regions (population, size etc.) mostly have basic sectors in their economic system. However, interesting facts came from different sectors in different provinces and regions in the model results.

Keywords: economic base, location quotients model, regional economics, regional development

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Authors: Isabel Brás, Artur Figueirinha, Bruno Esteves, Luísa P. Cruz-Lopes

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The agriculture lignocellulosic by-products are receiving increased attention, namely in the search for filter materials that retain contaminants from water. These by-products, specifically almond and hazelnut shells are abundant in Portugal once almond and hazelnuts production is a local important activity. Hazelnut and almond shells have as main constituents lignin, cellulose and hemicelluloses, water soluble extractives and tannins. Along the adsorption of heavy metals from contaminated waters, water soluble compounds can leach from shells and have a negative impact in the environment. Usually, the chemical characterization of treated water by itself may not show environmental impact caused by the discharges when parameters obey to legal quality standards for water. Only biological systems can detect the toxic effects of the water constituents. Therefore, the evaluation of toxicity by biological tests is very important when deciding the suitability for safe water discharge or for irrigation applications. The main purpose of the present work was to assess the potential impacts of waters after been treated for heavy metal removal by hazelnut and almond shells adsorption systems, with short term acute toxicity tests. To conduct the study, water at pH 6 with 25 mg.L-1 of lead, was treated with 10 g of shell per litre of wastewater, for 24 hours. This procedure was followed for each bark. Afterwards the water was collected for toxicological assays; namely bacterial resistance, seed germination, Lemna minor L. test and plant grow. The effect in isolated bacteria strains was determined by disc diffusion method and the germination index of seed was evaluated using lettuce, with temperature and humidity germination control for 7 days. For aquatic higher organism, Lemnas were used with 4 days contact time with shell solutions, in controlled light and temperature. For terrestrial higher plants, biomass production was evaluated after 14 days of tomato germination had occurred in soil, with controlled humidity, light and temperature. Toxicity tests of water treated with shells revealed in some extent effects in the tested organisms, with the test assays showing a close behaviour as the control, leading to the conclusion that its further utilization may not be considered to create a serious risk to the environment.

Keywords: lignocellulosic wastes, adsorption, acute toxicity tests, risk assessment

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Authors: Albert Gyamfi

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Cocoa plays critical role in the socio-economic development of Ghana. Meanwhile, smallholder farmers most of whom are illiterate dominate the industry. According to the cocoa-based agricultural knowledge and information system (AKIS) model knowledge is created and transferred to the industry between three key actors: cocoa researchers, extension experts, and cocoa farmers. Dwelling on the SECI model, the media richness theory (MRT), and the AKIS model, a conceptual model of web 2.0-based AKIS model (AKIS 2.0) is developed and used to assess the possible effects of social media usage for knowledge creation in the Ghanaian cocoa industry. A mixed method approach with a survey questionnaire was employed, and a second-order multi-group structural equation model (SEM) was used to analyze the data. The study concludes that the use of web 2.0 applications for knowledge creation would lead to sustainable interactions among the key knowledge actors for effective knowledge creation in the cocoa industry in Ghana.

Keywords: agriculture, cocoa, knowledge, media, web 2.0

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Authors: Subhadip Biswas, Shivendra Maurya, Satish Chandra, Indrajit Ghosh

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Developing speed model is a challenging task particularly under mixed traffic condition where the traffic composition plays a significant role in determining vehicular speed. The present research has been conducted to model individual vehicular speed in the context of mixed traffic on an urban arterial. Traffic speed and volume data have been collected from three midblock arterial road sections in New Delhi. Using the field data, a volume based speed prediction model has been developed adopting the methodology of Artificial Neural Network (ANN). The model developed in this work is capable of estimating speed for individual vehicle category. Validation results show a great deal of agreement between the observed speeds and the predicted values by the model developed. Also, it has been observed that the ANN based model performs better compared to other existing models in terms of accuracy. Finally, the sensitivity analysis has been performed utilizing the model in order to examine the effects of traffic volume and its composition on individual speeds.

Keywords: speed model, artificial neural network, arterial, mixed traffic

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Authors: Meza-Quintero Myriam, Lobo Torrado Katty Andrea, Sanchez Picon Yesenia, Hurtado-Lugo Naudin

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The objective of the study was to evaluate the internal and external quality of the egg in the three production housing systems: floor, cage, and grazing of laying birds of the Isa Brown line, in the laying period between weeks 35 to 41; 135 hens distributed in 3 treatments of 45 birds per repetition were used (the replicas were the seven weeks of the trial). The feeding treatment supplied in the floor and cage systems contained 114 g/bird/day; for the grazing system, 14 grams less concentrate was provided. Nine eggs were collected to be studied and analyzed in the animal nutrition laboratory (3 eggs per housing system). The random statistical model was implemented: for the statistical analysis of the data, the statistical software of IBM® Statistical Products and Services Solution (SPSS) version 2.3 was used. The evaluation and follow-up instruments were the vernier caliper for the measurement in millimeters, a YolkFan™16 from Roche DSM for the evaluation of the egg yolk pigmentation, a digital scale for the measurement in grams, a micrometer for the measurement in millimeters and evaluation in the laboratory using dry matter, ashes, and ethereal extract. The results suggested that equivalent to the size of the egg (0.04 ± 3.55) and the thickness of the shell (0.46 ± 3.55), where P-Value> 0.05 was obtained, weight albumen (0.18 ± 3.55), albumen height (0.38 ± 3.55), yolk weight (0.64 ± 3.55), yolk height (0.54 ± 3.55) and for yolk pigmentation (1.23 ± 3.55). It was concluded that the hens in the three production systems, floor, cage, and grazing, did not show significant statistical differences in the internal and external quality of the chicken in the parameters studied egg for the production system.

Keywords: biological, territories, genetic resource, egg

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Authors: Anderson Ngowa Chembe, John Olukuru

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Greenhouse emissions by human activities are known to irreversibly increase global temperatures through the greenhouse effect. This study seeks to propose a mortality model with sensitivity to heat-change effects as one of the underlying parameters in the model. As such, the study sought to establish the relationship between greenhouse emissions and mortality indices in five OECD countries (USA, UK, Japan, Canada & Germany). Upon the establishment of the relationship using correlation analysis, an additional parameter that accounts for the sensitivity of heat-changes to mortality rates was incorporated in the Lee-Carter model. Based on the proposed model, new parameter estimates were calculated using iterative algorithms for optimization. Finally, the goodness of fit for the original Lee-Carter model and the proposed model were compared using deviance comparison. The proposed model provides a better fit to mortality rates especially in USA, UK and Germany where the mortality indices have a strong positive correlation with the level of greenhouse emissions. The results of this study are of particular importance to actuaries, demographers and climate-risk experts who seek to use better mortality-modeling techniques in the wake of heat effects caused by increased greenhouse emissions.

Keywords: climate risk, greenhouse emissions, Lee-Carter model, OECD

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Authors: Pratibha Srivastava, Ayyamperumal Jeyaprakash, Gary Steck, Jason Stanley, Leroy Whilby

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Exotic, invasive tephritid fruit flies (Diptera: Tephritidae) are a major threat to fruit and vegetable industries in the United States. The establishment of pest fruit fly in the agricultural industries and produce severe ecological and economic impacts on agricultural diversification and trade. Detection and identification of these agricultural pests in a timely manner will facilitate the possibility of eradication from newly invaded areas. Identification of larval stages to species level is difficult, but is required to determine pest loads and their pathways into the United States. The aim of this study is the New World genus, Anastrepha which includes pests of major economic importance. Mitochondrial cytochrome c oxidase I (COI) gene sequences were amplified from Anastrepha fraterculus specimens collected from South America (Ecuador and Peru). Phylogenetic analysis was performed to characterize the Anastrepha fraterculus complex at a molecular level. During phylogenetics analysis numerous nuclear mitochondrial pseudogenes (numts) were discovered in different specimens. The numts are nonfunctional copies of the mtDNA present in the nucleus and are easily coamplified with the mitochondrial COI gene copy by using conserved universal primers. This is problematic for DNA Barcoding, which attempts to characterize all living organisms by using the COI gene. This study is significant for national quarantine use, as morphological diagnostics to separate larvae of the various members remain poorly developed.

Keywords: tephritid, Anastrepha fraterculus, COI, numts

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Authors: Ibrahim A. Aref, Tarek El-Mihoub, Khadiga Ben Musa

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This paper presents Carrier Sense Multiple Access (CSMA) communication model based on SoC design methodology. Such model can be used to support the modelling of the complex wireless communication systems, therefore use of such communication model is an important technique in the construction of high performance communication. SystemC has been chosen because it provides a homogeneous design flow for complex designs (i.e. SoC and IP based design). We use a swarm system to validate CSMA designed model and to show how advantages of incorporating communication early in the design process. The wireless communication created through the modeling of CSMA protocol that can be used to achieve communication between all the agents and to coordinate access to the shared medium (channel).

Keywords: systemC, modelling, simulation, CSMA

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Authors: Vinayaka Gude Divya Sampath

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The research introduces an integrated prediction model to assess the susceptibility of roads in a future flooding event. The model consists of deep learning algorithm for forecasting gauge height data and Flood Inundation Mapper (FIM) for spatial flooding. An optimal architecture for Long short-term memory network (LSTM) was identified for the gauge located on Tangipahoa River at Robert, LA. Dropout was applied to the model to evaluate the uncertainty associated with the predictions. The estimates are then used along with FIM to identify the spatial flooding. Further geoprocessing in ArcGIS provides the susceptibility values for different roads. The model was validated based on the devastating flood of August 2016. The paper discusses the challenges for generalization the methodology for other locations and also for various types of flooding. The developed model can be used by the transportation department and other emergency response organizations for effective disaster management.

Keywords: deep learning, disaster management, flood prediction, urban flooding

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Authors: Oscar Javier Herrera Ochoa, Ivan Dario Romero Fonseca

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This paper presents a design of a model for planning the distribution logistics operation. The significance of this work relies on the applicability of this fact to the analysis of small and medium enterprises (SMEs) of dry freight in Bogotá. Two stages constitute this implementation: the first one is the place where optimal planning is achieved through a hybrid model developed with mixed integer programming, which considers the transhipment operation based on a combined load allocation model as a classic transshipment model; the second one is the specific routing of that operation through the heuristics of Clark and Wright. As a result, an integral model is obtained to carry out the step by step planning of the distribution of dry freight for SMEs in Bogotá. In this manner, optimum assignments are established by utilizing transshipment centers with that purpose of determining the specific routing based on the shortest distance traveled.

Keywords: transshipment model, mixed integer programming, saving algorithm, dry freight transportation

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Authors: Ma Lanting, S. Eguilior, A. Hurtado, Juan F. Llamas Borrajo

Abstract:

Horizontal hydraulic fracturing is a technology to increase natural gas flow and improve productivity in the low permeability formation. During this drilling operation tons of flowback and produced water which contains many organic compounds return to the surface with a potential risk of influencing the surrounding environment and human health. A mathematical model is urgently needed to represent organic compounds in water transportation process behavior and the concentration change with time throughout the hydraulic fracturing operation life cycle. A comprehensive model combined Organic Matter Transport Dynamic Model with Two-Compartment First-order Model Constant (TFRC) Model has been established to quantify the organic compounds concentration. This algorithm model is composed of two transportation parts based on time factor. For the fast part, the curve fitting technique is applied using flowback water data from the Marcellus shale gas site fracturing and the coefficients of determination (R2) from all analyzed compounds demonstrate a high experimental feasibility of this numerical model. Furthermore, along a decade of drilling the concentration ratio curves have been estimated by the slow part of this model. The result shows that the larger value of Koc in chemicals, the later maximum concentration in water will reach, as well as all the maximum concentrations percentage would reach up to 90% of initial concentration from shale formation within a long sufficient period.

Keywords: model, shale gas, concentration, organic compounds

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