Search results for: nested logit

Authors: Babak Mirbaha, Mahmoud Saffarzadeh, Atieh Asgari Toorzani

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Pedestrians are the most vulnerable road users since they do not have a protective shell. One of the most common collisions for them is pedestrian-vehicle at intersections. In order to develop appropriate countermeasures to improve safety for them, researches have to be conducted to identify the factors that affect the risk of getting involved in such collisions. More specifically, this study investigates factors such as the influence of walking alone or having a baby while crossing the street, the observable age of pedestrian, the speed of pedestrians and the speed of approaching vehicles on risk perception of pedestrians. A nested logit model was used for modeling the behavioral structure of pedestrians. The results show that the presence of more lanes at intersections and not being alone especially having a baby while crossing, decrease the probability of taking a risk among pedestrians. Also, it seems that teenagers show more risky behaviors in crossing the street in comparison to other age groups. Also, the speed of approaching vehicles was considered significant. The probability of risk taking among pedestrians decreases by increasing the speed of approaching vehicle in both the first and the second lanes of crossings.

Keywords: pedestrians, intersection, nested logit, risk

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Authors: Patricia Heredia, Isabel Saz, Marta Fernández

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This article proposes that the decision regarding exporting and the choice of export channel are nested and non-independent decisions. We assume that firms make two sequential decisions before arriving at their final choice: the decision to access foreign markets and the decision about the type of channel. This hierarchical perspective of the choices involved in the process is appealing for two reasons. First, it supports the idea that people have a limited analytical capacity. Managers often break down a complex decision into a hierarchical process because this makes it more manageable. Secondly, it recognizes that important differences exist between entry modes. In light of the above, the objective of this study is to test different entry mode choice processes: independent decisions and nested and non-independent decisions. To do this, the methodology estimates and compares the following two models: (i) a simultaneous single-stage model with three entry mode choices (using a multinomial logit model); ii) a two-stage model with the export decision preceding the channel decision using a sequential logit model. The study uses resource-based factors in determining these decision processes concerning internationalization and the study carries out empirical analysis using a DOC Rioja sample of 177 firms.Using the Akaike and Schwarz Information Criteria, the empirical evidence supports the existence of a nested structure, where the decision about exporting precedes the export mode decision. The implications and contributions of the findings are discussed.

Keywords: sequential logit model, two-stage choice process, export mode, wine industry

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Authors: Mustafa Aydın, Ali Murat Sunbul

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Hierarchical or nested data structures usually are seen in many research areas. Especially, in the field of education, if we examine most of the studies, we can see the nested structures. Students in classes, classes in schools, schools in cities and cities in regions are similar nested structures. In a hierarchical structure, students being in the same class, sharing the same physical conditions and similar experiences and learning from the same teachers, they demonstrate similar behaviors between them rather than the students in other classes.

Keywords: hierarchical linear modeling, nested data, hierarchical structure, data structure

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Authors: Md. Fazlul Karim, Ahmad Izani Md. Ismail, Mohammed Ashaque Meah

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This paper focuses on the development of a 2-D Boundary Fitted and Nested Grid (BFNG) model to compute the tsunami propagation of Indonesian tsunami 2004 along the coastal region of Penang in Peninsular Malaysia. In the presence of a curvilinear coastline, boundary fitted grids are suitable to represent the model boundaries accurately. On the other hand, when large gradient of velocity within a confined area is expected, the use of a nested grid system is appropriate to improve the numerical accuracy with the least grid numbers. This paper constructs a shallow water nested and orthogonal boundary fitted grid model and presents computational results of the tsunami impact on the Penang coast due to the Indonesian tsunami of 2004. The results of the numerical simulations are compared with available data.

Keywords: boundary fitted nested model, tsunami, Penang Island, 2004 Indonesian Tsunami

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Authors: Shuo Liu, Dan Liu

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In the field of named entity recognition, most of the research has been conducted around simple entities. However, for nested named entities, which still contain entities within entities, it has been difficult to identify them accurately due to their boundary ambiguity. In this paper, a hierarchical recognition model is constructed based on the grammatical structure and semantic features of Chinese text for boundary calculation based on lexical features. The analysis is carried out at different levels in terms of granularity, semantics, and lexicality, respectively, avoiding repetitive work to reduce computational effort and using the semantic features of words to calculate the boundaries of entities to improve the accuracy of the recognition work. The results of the experiments carried out on web-based microblogging data show that the model achieves an accuracy of 86.33% and an F1 value of 89.27% in recognizing nested named entities, making up for the shortcomings of some previous recognition models and improving the efficiency of recognition of nested named entities.

Keywords: coarse-grained, nested named entity, Chinese natural language processing, word embedding, T-SNE dimensionality reduction algorithm

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Authors: Kajingulu Malandala, Ranganai Edmore

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The asymmetric Laplace distribution (ADL) is commonly used as the likelihood function of the Bayesian quantile regression, and it offers different families of likelihood method for quantile regression. Notwithstanding their popularity and practicality, ADL is not smooth and thus making it difficult to maximize its likelihood. Furthermore, Bayesian inference is time consuming and the selection of likelihood may mislead the inference, as the Bayes theorem does not automatically establish the posterior inference. Furthermore, ADL does not account for greater skewness and Kurtosis. This paper develops a new aspect of quantile regression approach for count data based on inverse of the cumulative density function of the Poisson, binomial and Delaporte distributions using the integrated nested Laplace Approximations. Our result validates the benefit of using the integrated nested Laplace Approximations and support the approach for count data.

Keywords: quantile regression, Delaporte distribution, count data, integrated nested Laplace approximation

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Authors: Yungtai Lo

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Two-part random effects models have been used to fit semi-continuous longitudinal data where the response variable has a point mass at 0 and a continuous right-skewed distribution for positive values. We review methods proposed in the literature for analyzing data with excess zeros. A two-part logit-log-normal random effects model, a two-part logit-truncated normal random effects model, a two-part logit-gamma random effects model, and a two-part logit-skew normal random effects model were used to examine effects of a bottle-weaning intervention on reducing bottle use and daily milk intake from bottles in toddlers aged 11 to 13 months in a randomized controlled trial. We show in all four two-part models that the intervention promoted bottle-weaning and reduced daily milk intake from bottles in toddlers drinking from a bottle. We also show that there are no differences in model fit using either the logit link function or the probit link function for modeling the probability of bottle-weaning in all four models. Furthermore, prediction accuracy of the logit or probit link function is not sensitive to the distribution assumption on daily milk intake from bottles in toddlers not off bottles.

Keywords: two-part model, semi-continuous variable, truncated normal, gamma regression, skew normal, Pearson residual, receiver operating characteristic curve

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Authors: Fazlul Karim, Esa Al-Islam

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Many problems in oceanography and environmental sciences require the solution of shallow water equations on physical domains having curvilinear coastlines and abrupt changes of ocean depth near the shore. Finite-difference technique for the shallow water equations representing the boundary as stair step may give inaccurate results near the coastline where results are of greatest interest for various applications. This suggests the use of methods which are capable of incorporating the irregular boundary in coastal belts. At the same time, large velocity gradient is expected near the beach and islands as water depth vary abruptly near the coast. A nested numerical scheme with fine resolution is the best resort to enhance the numerical accuracy with the least grid numbers for the region of interests where the velocity changes rapidly and which is unnecessary for the away of the region. This paper describes the development of a boundary fitted nested grid (BFNG) model to compute tsunami propagation of 2004 Indonesian tsunami in Southern Thailand coastal waters. In this paper, we develop a numerical model employing the shallow water nested model and an orthogonal boundary fitted grid to investigate the tsunami impact on the Southern Thailand due to the Indonesian tsunami of 2004. Comparisons of water surface elevation obtained from numerical simulations and field measurements are made.

Keywords: Indonesian tsunami of 2004, Boundary-fitted nested grid model, Southern Thailand, finite difference method

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Authors: Ali Bagherpour

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The aim of this study was to determinate the variety of Anaplasma species among cattle of Khuzestan province, Iran. From April 2013 to June 2013, a total of 200 blood samples were collected via the jugular vein from healthy cattle (100), randomly. The extracted DNA from blood cells were amplified by Anaplasma-all primers, which amplify an approximately 1468bp DNA fragment from region of 16S rRNA gene from various members of the genus Anaplasma. For raising the test sensivity, the PCR products were amplified with the primers, which were designed from the region flanked by the first primers. The amplified nested PCR product had an expected PCR product with 345 nucleotides in length. 44 out of 100 cattle blood samples were Anaplasma spp. positive by first PCR and nested PCR. All cattle positive samples were further analyzed for the presence of A. centrale, A. bovis and A. phagocytophilum by specific nested PCR. A.phagocytophilum was identified by specific nested PCR in 3% of cattle blood samples. The extracted DNA from positive Anaplasma spp. samples were amplified by Anaplasma marginale/ovis specific primers, which amplify an approximately 866bp DNA fragment from region of msp4 gene. 41 out of 100 cattle blood samples (41%) were positive for Anaplasma marginale and Anaplasma ovis, respectively.

Keywords: Iran, Khuzestan, Anaplasma species, Cattle, A. marginale, A. ovis, A. phagocytophilum, PCR

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Authors: Zhenming Wang, Jun Zhu, Yuchen Yang, Ning Zhao

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In the present paper, an alternative framework is proposed to construct a class of finite difference multi-resolution nested weighted essentially non-oscillatory (WENO) schemes with an increasingly higher order of accuracy for solving inviscid Euler equations. These WENO schemes firstly obtain a set of reconstruction polynomials by a hierarchy of nested central spatial stencils, and then recursively achieve a higher order approximation through the lower-order precision WENO schemes. The linear weights of such WENO schemes can be set as any positive numbers with a requirement that their sum equals one and they will not pollute the optimal order of accuracy in smooth regions and could simultaneously suppress spurious oscillations near discontinuities. Numerical results obtained indicate that these alternative finite-difference multi-resolution nested WENO schemes with different accuracies are very robust with low dissipation and use as few reconstruction stencils as possible while maintaining the same efficiency, achieving the high-resolution property without any equivalent multi-resolution representation. Besides, its finite volume form is easier to implement in unstructured grids.

Keywords: finite-difference, WENO schemes, high order, inviscid Euler equations, multi-resolution

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Authors: Othmane Zarhali, Cécilia Aubrun, Emmanuel Bacry, Jean-Philippe Bouchaud, Jean-François Muzy

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The Nested factor model was introduced by Bouchaud and al., where the asset return fluctuations are explained by common factors representing the market economic sectors and residuals (noises) sharing with the factors a common dominant volatility mode in addition to the idiosyncratic mode proper to each residual. This construction infers that the factors-residuals log volatilities are correlated. Here, we consider the case of a single factor where the only dominant common mode is a S-fbm process (introduced by Peng, Bacry and Muzy) with Hurst exponent H around 0.11 and the residuals having in addition to the previous common mode idiosyncratic components with Hurst exponents H around 0. The reason for considering this configuration is twofold: preserve the Nested factor model’s characteristics introduced by Bouchaud and al. and propose a framework through which the stylized fact reported by Peng and al. is reproduced, where it has been observed that the Hurst exponents of stock indices are large as compared to those of individual stocks. In this work, we show that the Log S-fbm Nested factor model’s construction leads to a Hurst exponent of single stocks being the ones of the idiosyncratic volatility modes and the Hurst exponent of the index being the one of the common volatility modes. Furthermore, we propose a statistical procedure to estimate the Hurst factor exponent from the stock returns dynamics together with theoretical guarantees, with good results in the limit where the number of stocks N goes to infinity. Last but not least, we show that the factor can be seen as an index constructed from the single stocks weighted by specific coefficients.

Keywords: hurst exponent, log S-fbm model, nested factor model, small intermittency approximation

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Authors: Nattabhorn Leamcharaskul

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This study aims to examine determining factors of the dynamics of poverty in Thailand by using panel data of 3,567 households in 2007-2017. Four techniques of estimation are employed to analyze the situation of poverty across households and time periods: the multinomial logit model, the sequential logit model, the quantile regression model, and the difference in difference model. Households are categorized based on their experiences into 5 groups, namely chronically poor, falling into poverty, re-entering into poverty, exiting from poverty and never poor households. Estimation results emphasize the effects of demographic and socioeconomic factors as well as unexpected events on the economic status of a household. It is found that remittances have positive impact on household’s economic status in that they are likely to lower the probability of falling into poverty or trapping in poverty while they tend to increase the probability of exiting from poverty. In addition, not only receiving a secondary source of household income can raise the probability of being a never poor household, but it also significantly increases household income per capita of the chronically poor and falling into poverty households. Public work programs are recommended as an important tool to relieve household financial burden and uncertainty and thus consequently increase a chance for households to escape from poverty.

Keywords: difference in difference, dynamic, multinomial logit model, panel data, poverty, quantile regression, remittance, sequential logit model, Thailand, transfer

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Authors: Yong Eun Yoon, Eric N. Johnson, Liling Ren

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Multirotor is one of the most popular types of small unmanned aircraft systems and has already been used in many areas including transport, military, surveillance, and leisure. Together with its popularity, the needs for proper flight control is growing because in most applications it is required to conduct its missions autonomously, which is in many aspects based on autonomous flight control. There have been many studies about the flight control for multirotor, but there is still room for enhancements in terms of performance and efficiency. This paper presents an autonomous flight control method for multirotor based on alternative input output linearization coupled with nested saturations. With alternative choice of the output of the multirotor flight control system, we can reduce computational cost regarding Lie algebra, and the linearized system can be stabilized with the introduction of nested saturations with real poles of our own design. Stabilization of internal dynamics is also based on the nested saturations and accompanies the determination of part of desired states. In particular, outer control loops involving state variables which originally are not included in the output of the flight control system is naturally rendered through this internal dynamics stabilization. We can also observe that desired tilting angles are determined by error dynamics from outer loops. Simulation results show that in any tracking situations multirotor stabilizes itself with small time constants, preceded by tuning process for control parameters with relatively low degree of complexity. Future study includes control of piecewise linear behavior of multirotor with actuator saturations, and the optimal determination of desired states while tracking multiple waypoints.

Keywords: automatic flight control, input output linearization, multirotor, nested saturations

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Authors: Patria Yunita

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Kuznets’ environmental curve analysis suggests sacrificing economic development to reduce environmental problems. However, we hope to achieve sustainable economic development. In this case, Islamic social finance, especially that of waqf in Indonesia, can be used as a solution to bridge the problem of environmental damage to the sustainability of economic development. The Panel Logit Regression method was used to analyze the probability of increasing economic growth and the role of waqf in the environmental impact of CO₂ emissions. This study uses panel data from 33 Indonesian provinces. The data used were the National Waqf Index, Forest Area, Waqf Land Area, Growth Rate of Regional Gross Domestic Product (YoY), and CO₂ Emissions for 2018-2022. Data were obtained from the Indonesian Waqf Board, Climate World Data, the Ministry of the Environment, and the Bank of Indonesia. The results prove that CO₂ emissions have a negative effect on regional economic growth and that waqf governance in the waqf index has a positive effect on regional economic growth in 33 provinces.

Keywords: waqf, CO₂ emissions, panel logit analysis, sustainable economic development

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Authors: Svetlana Pushkar

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Eco-indicator 99 (EI99) considers fundamental life cycle assessment (LCA) uncertainties via egalitarian/egalitarian (e/e), hierarchist/hierarchist (h/h), individualist/individualist (i/i), individualist/average (i/a), egalitarian/average (e/a), and hierarchist/average (h/a) methodological options. The objective of this study is to provide a reliable two-stage nested mixed balanced Analysis of Variance (ANOVA) test as a supplemental test to EI99 to address the problematic combination of similarly and not similarly produced materials usually found in building technologies. The robustness of the test was determined from both the “EI99 (all options)” stage (including e/e, i/i, h/h, e/a, i/a, and h/a - all methodological options) and the “EI99 (perspectives)” stage (including e/e, i/i, and h/h methodological options of EI99 - the methodological options with their particular weighting set or e/a, i/a, and h/a methodological options of EI99 - the methodological options with the average weighting set) of evaluating building technologies.

Keywords: building technologies, LCA uncertainty, Eco-indicator 99, two-stage nested mixed ANOVA test

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Authors: Babak Rezavand

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Pneumocystis carinii pneumonia (PCP) is one of the main causes of morbidity and mortality among immunocompromised and HIV-positive patients and remained one of the most important common opportunistic infections in these individuals in the world. Pneumocystis infection has been reported in many mammals. The aim of this study was to determine the Pneumocystis infection in wild rats as natural reservoirs of this organism in Tehran city, Iran. Fifty three rats (Rattus rattus) were live trapped in different areas of Tehran city, Iran. After isolation of their lung tissues and homogenization in sterile conditions, DNA was extracted. DNAs from all of the Pneumocystis species were amplified by pAZ102-H and pAZ102-E primers, and Nested PCR was performed using pAZ102-X and pAZ102-W primers from the initial PCR product for all the species of Pneumocystis. Amplification of the genome revealed the presence of Pneumocystis in the lungs of 17 rats (32%) through a PCR product with a bandwidth of 346 bp. In the Nested PCR amplification, from the PCR product of 53 rats, 64.2% of the samples were positive with a bandwidth of 261bp. Pneumocystis SPP infestation is highly prevalent among wild rats in Tehran city, indicating the existence of infection in the natural ecosystem of these rodents. As a host, rat plays an important role in the transmission of the microorganism in the world.

Keywords: pneumocystis SPP, rattus rattus, nested PCR, Tehran

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Authors: S. Masoud Barakati, Mohsen Rahmani Haredasht

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Recently, the use of T-type nested neutral point clamped (T-NNPC) converter has increased in medium voltage applications. However, the T-NNPC converter architecture's reliability and continuous operation are at risk by including semiconductor switches. Semiconductor switches are a prone option for open-circuit faults. As a result, fault-tolerant converters are required to improve the system's reliability and continuous functioning. This study's primary goal is to provide a fault-tolerant T-NNPC converter configuration. In the proposed design utilizing the cold reservation approach, a redundant phase is considered, which replaces the faulty phase once the fault is diagnosed in each phase. The suggested fault-tolerant configuration can be easily implemented in practical applications due to the use of a simple PWM control mechanism. The performance evaluation of the proposed configuration under different scenarios in the MATLAB-Simulink environment proves its efficiency.

Keywords: T-type nested neutral point clamped converter, reliability, continuous operation, open-circuit faults, fault-tolerant converters

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Authors: Festus M. Epetimehin

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This study was conducted to identify the effect of National Directorate of Employment (NDE) training on the profit of Agricultural-Small and Medium Enterprises (SMEs) and to evaluate the factors that influenced farmers' participation in NDE training, as well as the type and frequency of training farmers and other agro-allied entrepreneurs in Nigeria. Using a multi-stage sampling procedure, a total of 384 respondents were sampled, including 192 beneficiaries and 192 non-beneficiaries in Oyo and Lagos States, respectively. Data were analysed using Binary Logit regression and Propensity Score Matching techniques. According to the binary logit analysis, respondents’ gender, availability to extension services, and the location of respondent’s operation were determinant factors influencing NDE training enrolment. All identified factors are related to the probability of respondents’ involvement in a positive way. Propensity score matching revealed that Agricultural-SMEs who participated in the NDE program boosted their profit by N341,072.18. The positive outcome of the effect implies that NDE training enhances Agri-SME performance in Nigeria. The study concluded that greater funding should be provided for the NDE for performance-enhancing training of the Agri-SMEs.

Keywords: PSM, binary logit model, Agri-SME

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Authors: Dimiter M. Dimitrov, Abdullah Sadaawi

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The National Assessment for Schools (NAFS) in Saudi Arabia consists of standardized tests in Mathematics, Reading, and Science for school grade levels 3, 6, and 9. One main goal is to classify students into four categories of NAFS performance (minimal, basic, proficient, and advanced) by schools and the entire national sample. The NAFS scoring and equating is performed on a bounded scale (D-scale: ranging from 0 to 1) in the framework of the recently developed “D-scoring method of measurement.” The specificity of the NAFS measurement framework and data complexity presented both challenges and opportunities to (a) the estimation of score reliability for schools, (b) setting cut-scores for the classification of students into categories of performance, and (c) generating plausible values for distributions of student performance on the D-scale. The estimation of score reliability at the school level was performed in the framework of generalizability theory (GT), with students “nested” within schools and test items “nested” within test forms. The GT design was executed via a multilevel modeling syntax code in R. Cut-scores (on the D-scale) for the classification of students into performance categories was derived via a recently developed method of standard setting, referred to as “Response Vector for Mastery” (RVM) method. For each school, the classification of students into categories of NAFS performance was based on distributions of plausible values for the students’ scores on NAFS tests by grade level (3, 6, and 9) and subject (Mathematics, Reading, and Science). Plausible values (on the D-scale) for each individual student were generated via random selection from a statistical logit-normal distribution with parameters derived from the student’s D-score and its conditional standard error, SE(D). All procedures related to D-scoring, equating, generating plausible values, and classification of students into performance levels were executed via a computer program in R developed for the purpose of NAFS data analysis.

Keywords: large-scale assessment, reliability, generalizability theory, plausible values

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Authors: Masoud Soltanialvar, Ali Bagherpour

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The aim of this study was to determinate the variety of Anaplasma species among sheep of khouzestan province, Iran. From April 2013 to June 2013, a total of 200 blood samples were collected via the jugular vein from healthy sheep (100), randomly. The extracted DNA from blood cells were amplified by Anaplasma-all primers, which amplify an approximately 1468bp DNA fragment from region of 16S rRNA gene from various members of the genus Anaplasma. For raising the test sensivity, the PCR products were amplified with the primers, which were designed from the region flanked by the first primers. The amplified nested PCR product had an expected PCR product with 345 nucleotides in length. In 100 sheep blood samples, 7 samples were Anaplasma spp. positive by first PCR and nested PCR. The results showed that 2 of total 100 blood samples (2%) were A.phagocytophilum positive by specific nested PCR based on 16S rRNA gene. The extracted DNA from positive Anaplasma spp. samples were amplified by Anaplasma ovis specific primers, which amplify an approximately 866bp DNA fragment from region of msp4 gene. 5 out of 100 sheep blood samples (5%) were positive for Anaplasma ovis. This study is the first molecular detection of A. ovis and A.phagocytophilum from sheep in Iran.

Keywords: Iran, anaplasma species, sheep, A. ovis, A. phagocytophilum, PCR

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Authors: Kalandi Charan Pradhan

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In this study, we investigate does weather variation determine temporary labour migration using 210 sample households from six Semi-Arid Tropic (SAT) villages for the period of 2005-2014 in India. The study has made an attempt to examine how households use temporary labour migration as a coping mechanism to minimise the risk rather than maximize the utility of the households. The study employs panel Logit regression model to predict the probability of household having at least one temporary labour migrant. As per as econometrics result, it is found that along with demographic and socioeconomic factors; weather variation plays an important role to determine the decision of migration at household level. In order to capture the weather variation, the study uses mean crop yield deviation over the study periods. Based on the random effect logit regression result, the study found that there is a concave relationship between weather variation and decision of temporary labour migration. This argument supports the theory of New Economics of Labour Migration (NELM), which highlights the decision of labour migration not only maximise the households’ utility but it helps to minimise the risks.

Keywords: temporary migration, socioeconomic factors, weather variation, crop yield, logit estimation

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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: Alma Sobrevilla

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Using panel data from Mexico, this paper studies the determinants of women’s intrahousehold decision-making power using a generalised ordered logit model. Fixed effects estimations are also carried out to solve potential endogeneity coming from unobservable time-invariant factors. Finally, the paper analyses quadratic and community divergence effects of education on power. Results show heterogeneity in the effect of each of the determinants across different levels of decision-making power and suggest the presence of a significant quadratic effect of education. Having more education than the community average has a negative effect on power, supporting the notion that women tend to compensate their success outside the household with submissive attitudes at home.

Keywords: women, decision-making power, intrahousehold, Mexico

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Authors: Dina Athariah, Desriani Desriani, Bugi Ratno Budiarto, Abinawanto Abinawanto, Dwi Wulandari

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Breast cancer is a regulated by many genes. Defect in PIK3CA gene especially at position of exon 9 (E542K and E545K), called hot spot mutation induce early transformation of breast cells. The early detection of breast cancer based on mutation profile of this hot spot region would be hampered by the existence of pseudogene, marked by its substitution mutation at base 1658 (E545A) and deletion at 1659 that have been previously proven in several cancers. To the best of the authors’ knowledge, until recently no studies have been reported about pseudogene phenomenon in breast cancer. Here, we reported PCR optimization to to obtain true exon 9 of PIK3CA gene from its pseudogene hence increasing the validity of data. Material and methods: two genomic DNA with Dev and En code were used in this experiment. Two pairs of primer were design for Standard PCR method. The size of PCR products for each primer is 200bp and 400bp. While other primer was designed for Nested-PCR followed with DNA sequencing method. For Nested-PCR, we optimized the annealing temperature in first and second run of PCR, and the PCR cycle for first run PCR (15x versus 25x). Result: standard PCR using both primer pairs designed is failed to detect the true PIK3CA gene, appearing a substitution mutation at 1658 and deletion at 1659 of PCR product in sequence chromatogram indicated pseudogene. Meanwhile, Nested-PCR with optimum condition (annealing temperature for the first round at 55oC, annealing temperatung for the second round at 60,7oC with 15x PCR cycles) and could detect the true PIK3CA gene. Dev sample were identified as WT while En sample contain one substitution mutation at position 545 of exon 9, indicating amino acid changing from E to K. For the conclusion, pseudogene also exists in breast cancer and the apllication of optimazed Nested-PCR in this study could detect the true exon 9 of PIK3CA gene.

Keywords: breast cancer, exon 9, hotspot mutation, PIK3CA, pseudogene

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Authors: Leah Wright, Trevor Townsend

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Mode choice models are crucial instruments in the analysis of travel behaviour. These models show the relationship between an individual’s choice of transportation mode for a given O-D pair and the individual’s socioeconomic characteristics such as household size and income level, age and/or gender, and the features of the transportation system. The most popular functional forms of these models are based on Utility-Based Choice Theory, which addresses the uncertainty in the decision-making process with the use of an error term. However, with the development of artificial intelligence, many researchers have started to take a different approach to travel demand modelling. In recent times, researchers have looked at using neural networks, fuzzy logic and rough set theory to develop improved mode choice formulas. The concept of cloud theory has recently been introduced to model decision-making under uncertainty. Unlike the previously mentioned theories, cloud theory recognises a relationship between randomness and fuzziness, two of the most common types of uncertainty. This research aims to investigate the use of cloud theory in mode choice models. This paper highlights the conceptual framework of the mode choice model using cloud theory. Merging decision-making under uncertainty and mode choice models is state of the art. The cloud theory model is expected to address the issues and concerns with the nested logit and improve the design of mode choice models and their use in travel demand.

Keywords: Cloud theory, decision-making, mode choice models, travel behaviour, uncertainty

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Authors: Tayebeh Saghapour, Sara Moridpour, Russell George Thompson

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One of the common aims of transport policy makers is to switch people’s travel to active transport. For this purpose, a variety of transport goals and investments should be programmed to increase the propensity towards active transport mode choice. This paper aims to investigate whether built environment features in neighbourhoods could enhance the odds of active transportation. The present study introduces an index measuring public transport accessibility (PTAI), and a walkability index along with socioeconomic variables to investigate mode choice behaviour. Using travel behaviour data, an ordered logit regression model is applied to examine the impacts of explanatory variables on walking trips. The findings indicated that high rates of active travel are consistently associated with higher levels of walking and public transport accessibility.

Keywords: active transport, public transport accessibility, walkability, ordered logit model

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Authors: Mequanent Wale Mekonen, Edoardo Otranto, Angela Alibrandi

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Diabetic kidney disease is one of the main microvascular complications caused by diabetes. Several clinical and biochemical variables are reported to be associated with diabetic kidney disease in people with type 2 diabetes. However, their interrelations could distort the effect estimation of these variables for the disease's progression. The objective of the study is to determine how the biochemical and clinical variables in people with type 2 diabetes are interrelated with each other and their effects on kidney disease progression through advanced statistical methods. First, principal component analysis was used to explore how the biochemical and clinical variables intercorrelate with each other, which helped us reduce a set of correlated biochemical variables to a smaller number of uncorrelated variables. Then, ordered logit regression models (cumulative, stage, and adjacent) were employed to assess the effect of biochemical and clinical variables on the order-level response variable (progression of kidney function) by considering the proportionality assumption for more robust effect estimation. This retrospective cross-sectional study retrieved data from a type 2 diabetic cohort in a polyclinic hospital at the University of Messina, Italy. The principal component analysis yielded three uncorrelated components. These are principal component 1, with negative loading of glycosylated haemoglobin, glycemia, and creatinine; principal component 2, with negative loading of total cholesterol and low-density lipoprotein; and principal component 3, with negative loading of high-density lipoprotein and a positive load of triglycerides. The ordered logit models (cumulative, stage, and adjacent) showed that the first component (glycosylated haemoglobin, glycemia, and creatinine) had a significant effect on the progression of kidney disease. For instance, the cumulative odds model indicated that the first principal component (linear combination of glycosylated haemoglobin, glycemia, and creatinine) had a strong and significant effect on the progression of kidney disease, with an effect or odds ratio of 0.423 (P value = 0.000). However, this effect was inconsistent across levels of kidney disease because the first principal component did not meet the proportionality assumption. To address the proportionality problem and provide robust effect estimates, alternative ordered logit models, such as the partial cumulative odds model, the partial adjacent category model, and the partial continuation ratio model, were used. These models suggested that clinical variables such as age, sex, body mass index, medication (metformin), and biochemical variables such as glycosylated haemoglobin, glycemia, and creatinine have a significant effect on the progression of kidney disease.

Keywords: diabetic kidney disease, ordered logit model, principal component analysis, type 2 diabetes

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Authors: Saheed Olakunle Sanusi, Israel Ajibade Adedeji

Abstract:

The study analysed the effect of microfinance on the profit level of small and medium scale enterprises in Lagos. The data for the study were obtained by simple random sampling, and total of one hundred and fifty (150) small and medium scale enterprises (SMEs) were sampled for the study. Seventy-five (75) each are microfinance users and non-users. Data were analysed using descriptive statistics, logit model, t-test and ordinary least square (OLS) regression. The mean profit of the enterprises using microfinance is ₦16.8m, while for the non-users of microfinance is ₦5.9m. The mean profit of microfinance users is statistically different from the non-users. The result of the logit model specified for the determinant of access to microfinance showed that three of specified variables- educational status of the enterprise head, credit utilisation and volume of business investment are significant at P < 0.01. Enterprises with many years of experience, highly educated enterprise heads and high volume of business investment have more potential access to microfinance. The OLS regression model indicated that three parameters namely number of school years, the volume of business investment and (dummy) participation in microfinance were found to be significant at P < 0.05. These variables are therefore significant determinants of impacts of microfinance on profit level in the study area. The study, therefore, concludes and recommends that to improve the status of small and medium scale enterprises for an increase in profit, the full benefit of access to microfinance can be enhanced through investment in social infrastructure and human capital development. Also, concerted efforts should be made to encouraged non-users of microfinance among SMEs to use it in order to boost their profit.

Keywords: credit utilisation, logit model, microfinance, small and medium enterprises

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Authors: A. Novikova, L. Rocchi, G. Startiene

Abstract:

Market and non-market outputs are produced jointly in agriculture. Their supply depends on the intensity and type of production. The role of agriculture as an economic activity and its effects are important for the Lithuanian case study, as agricultural land covers more than a half of country. Positive and negative externalities, created in agriculture are not considered in the market. Therefore, specific techniques such as stated preferences methods, in particular choice experiments (CE) are used for evaluation of non-market outputs in agriculture. The main aim of this paper is to present construction of the research path for evaluation of non-market farming system outputs in Lithuania. The conventional and organic farming, covering crops (including both cereal and industrial crops) and livestock (including dairy and cattle) production has been selected. The CE method and nested logit (NL) model were selected as appropriate for evaluation of non-market outputs of different farming systems in Lithuania. A pilot survey was implemented between October–November 2018, in order to test and improve the CE questionnaire. The results of the survey showed that the questionnaire is accepted and well understood by the respondents. The econometric modelling showed that the selected NL model could be used for the main survey. The understanding of the differences between organic and conventional farming by residents was identified. It was revealed that they are more willing to choose organic farming in comparison to conventional farming.

Keywords: choice experiments, farming system, Lithuania market outputs, non-market outputs

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Authors: Okolie Pius Ifeanyi, Emerenini Emilymary Chima

Abstract:

Aims: The study investigated the diversity and identities of Lactic Acid Bacteria (LAB) isolated from different fresh fruits using Molecular Nested PCR analysis and the efficacy of cell free supernatants from Lactic Acid Bacteria (LAB) isolated from fresh fruits for in vitro control of some tomato pathogens. Study Design: Nested PCR approach was used in this study employing universal 16S rRNA gene primers in the first round PCR and LAB specific Primers in the second round PCR with the view of generating specific Nested PCR products for the LAB diversity present in the samples. The inhibitory potentials of supernatant obtained from LAB isolates of fruits origin that were molecularly characterized were investigated against some tomato phytopathogens using agar-well method with the view to develop biological agents for some tomato disease causing organisms. Methodology: Gram positive, catalase negative strains of LAB were isolated from fresh fruits on Man Rogosa and Sharpe agar (Lab M) using streaking method. Isolates obtained were molecularly characterized by means of genomic DNA extraction kit (Norgen Biotek, Canada) method. Standard methods were used for Nested Polymerase Chain Reaction (PCR) amplification targeting the 16S rRNA gene using universal 16S rRNA gene and LAB specific primers, agarose gel electrophoresis, purification and sequencing of generated Nested PCR products (Macrogen Inc., USA). The partial sequences obtained were identified by blasting in the non-redundant nucleotide database of National Center for Biotechnology Information (NCBI). The antimicrobial activities of characterized LAB against some tomato phytopathogenic bacteria which include (Xanthomonas campestries, Erwinia caratovora, and Pseudomonas syringae) were obtained by using the agar well diffusion method. Results: The partial sequences obtained were deposited in the database of National Centre for Biotechnology Information (NCBI). Isolates were identified based upon the sequences as Weissella cibaria (4, 18.18%), Weissella confusa (3, 13.64%), Leuconostoc paramensenteroides (1, 4.55%), Lactobacillus plantarum (8, 36.36%), Lactobacillus paraplantarum (1, 4.55%) and Lactobacillus pentosus (1, 4.55%). The cell free supernatants of LAB from fresh fruits origin (Weissella cibaria, Weissella confusa, Leuconostoc paramensenteroides, Lactobacillus plantarum, Lactobacillus paraplantarum and Lactobacillus pentosus) can inhibits these bacteria by creating clear zones of inhibition around the wells containing cell free supernatants of the above mentioned strains of lactic acid bacteria. Conclusion: This study shows that potentially LAB can be quickly characterized by molecular methods to specie level by nested PCR analysis of the bacteria isolate genomic DNA using universal 16S rRNA primers and LAB specific primer. Tomato disease causing organisms can be most likely biologically controlled by using extracts from LAB. This finding will reduce the potential hazard from the use of chemical herbicides on plant.

Keywords: nested pcr, molecular characterization, 16s rRNA gene, lactic acid bacteria

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