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Today biodiversity is rapidly decreasing and an increasing number of threatened species live in modified and human dominated landscapes. Therefore it is essential to learn more about how species cope with the changes of their habitat. The focus of this study lies on a primate species, the critically endangered Javan slow loris (Nycticebus javanicus), endemic to the densely populated island of Java, Indonesia.  In cooperation with the Little fire face project in West Java, I used a step selection function (SSF) framework, to understand how landscape structure affects the movement of Javan slow lorises within a fragmented mountain-agroforest landscape of Cipaganti, West Java. To investigate the movement and fine scale habitat selection of slow lorises I used one hour locations of 6 radio-collared slow lorises. The habitat and vegetation of observed and random steps was investigated in multiple variables such as presence of food trees and signs of human disturbance. For the analysis I paired observed steps (1h relocations) with 3 random habitat locations and used a conditional logistic regression to parameterize the SSF, which represents the probability of a focal slow loris to select a given step as a function of the habitat and vegetation factors surveyed. In average the slow lorises travelled about 450 m each night and most frequently they used a step length of about 0 – 50 m. My result reveals that slow lorises fine scale habitat selection is positively influenced by the presence of trees and tree trunk cover (indirect increasing the canopy cover and connectivity). They are also to a high extent positively affected by the presence of a feeding tree species, Calliandra calothyrsus. Surprisingly slow lorises selected steps associated with a higher number of fields (fields may indicate an increased biodiversity within the location). The results also indicate that slow lorises are limited in their movement by the presence of fields or rivers, which indicates that slow lorises are negatively influenced in their movement by a declining ability to move and forage within Cipaganti. I found no significant differences between sexes in their distance travelled. The recommendation for future conservation of slow lorises in Cipaganti is to prevent further habitat loss and fragmentation through activities that protect or maintain the present suitable slow loris habitat. Further research is needed to increase the knowledge of these primates’ abilities to live in this modified landscape.

In this study, the effect of speed was investigated on the breakage rate of UG2 platinum ore in a batch mill of 5 dm3 and 175 mm internal diameter. One size fraction method was carried out to perform the experiment. Five mono-sized fractions in the range of 1.180 mm to 0.212 mm separated by √2 series interval were prepared. The fractions were milled at different grinding times (0.5, 2, 4, 15 and 30 min) and three fractions of mill critical speed were considered (20%, 30%, and 40%). The target of critical speed below 50% was due to the need of lower energy consumption in milling processes. The selection and breakage function parameters were determined and compared for fractions of critical speed. First the grinding kinetics of the ore was determined and it was found that the material breaks in non-first order manner. Thereafter, effective mean rate of breakage was determined. It was found that the rate of breakage increased with increase of mill speed and optimum speed was not reached in the range of chosen mill speed fractions. Again the rate of breakage was plotted as a function of particle size, the optimum size was 0.8 mm when milling at 30% critical speed. As for 20% and 30% optimum size was not reached. The selection function parameters estimated at 30% critical speed were 𝑎0 = 0.04 min−1 , 𝛼 = 1.36, 𝜇 = 0.9 mm, and Λ = 3. Breakage function parameters were determined and was noticed that the material UG2 platinum ore is non-normalised, i.e. Φ value was changing from 0.25 to 0.90 depending on feed size and mill speed. The parameters 𝛽 and 𝛾 were constant at 7.3 and 1.17 respectively. / College of Science, Engineering and Technology / M. Tech. (Chemical Engineering)

Em ecologia, o comportamento dos animais é freqüentemente estudado para entender melhor suas preferências por diferentes tipos de alimento e habitat. O presente trabalho esta relacionado a este tópico, dividindo-se em três capítulos. O primeiro capitulo refere-se à estimação da função da probabilidade da seleção de recurso (RSPF) comparado com um modelo de escolha discreta (DCM) com uma escolha, usando as estatísticas qui-quadrado para obter as estimativas. As melhores estimativas foram obtidas pelo método DCM com uma escolha. No entanto, os animais não fazem a sua seleção baseados apenas em uma escolha. Com RSPF, as estimativas de máxima verossimilhança, usadas pela regressão logística ainda não atingiram os objetivos, já que os animais têm mais de uma escolha. R e o software Minitab e a linguagem de programação Fortran foram usados para obter os resultados deste capítulo. No segundo capítulo discutimos mais a verossimilhança do primeiro capítulo. Uma nova verossimilhança para a RSPF é apresentada, a qual considera as unidades usadas e não usadas, e métodos de bootstrapping paramétrico e não paramétrico são usados para estudar o viés e a variância dos estimadores dos parâmetros, usando o programa FORTRAN para obter os resultados. No terceiro capítulo, a nova verossimilhança apresentada no capítulo 2 é usada com um modelo de escolha discreta, para resolver parte do problema apresentado no primeiro capítulo. A estrutura de encaixe é proposta para modelar a seleção de habitat de 28 corujas manchadas (Strix occidentalis), assim como a uma generalização do modelo logit encaixado, usando a maximização da utilidade aleatória e a RSPF aleatória. Métodos de otimização numérica, e o sistema computacional SAS, são usados para estimar os parâmetros de estrutura de encaixe. / In ecology, the behavior of animals is often studied to better understand their preferences for different types of habitat and food. The present work is concerned with this topic. It is divided into three chapters. The first concerns the estimation of a resource selection probability function (RSPF) compared with a discrete choice model (DCM) using chi-squared to obtain estimates. The best estimates were obtained by the DCM method. Nevertheless, animals were not selected based on choice alone. With RSPF, the maximum likelihood estimates used with the logistic regression still did not reach the objectives, since the animals have more than one choice. R and Minitab software and the FORTRAN programming language were used for the computations in this chapter. The second chapter discusses further the likelihood presented in the first chapter. A new likelihood for a RSPF is presented, which takes into account the units used and not used, and parametric and non-parametric bootstrapping are employed to study the bias and variance of parameter estimators, using a FORTRAN program for the calculations. In the third chapter, the new likelihood presented in chapter 2, with a discrete choice model is used to resolve a part of the problem presented in the first chapter. A nested structure is proposed for modelling selection by 28 spotted owls (Strix occidentalis) as well as a generalized nested logit model using random utility maximization and a random RSPF. Numerical optimization methods and the SAS system were employed to estimate the nested structural parameters.

Em ecologia, o comportamento dos animais é freqüentemente estudado para entender melhor suas preferências por diferentes tipos de alimento e habitat. O presente trabalho esta relacionado a este tópico, dividindo-se em três capítulos. O primeiro capitulo refere-se à estimação da função da probabilidade da seleção de recurso (RSPF) comparado com um modelo de escolha discreta (DCM) com uma escolha, usando as estatísticas qui-quadrado para obter as estimativas. As melhores estimativas foram obtidas pelo método DCM com uma escolha. No entanto, os animais não fazem a sua seleção baseados apenas em uma escolha. Com RSPF, as estimativas de máxima verossimilhança, usadas pela regressão logística ainda não atingiram os objetivos, já que os animais têm mais de uma escolha. R e o software Minitab e a linguagem de programação Fortran foram usados para obter os resultados deste capítulo. No segundo capítulo discutimos mais a verossimilhança do primeiro capítulo. Uma nova verossimilhança para a RSPF é apresentada, a qual considera as unidades usadas e não usadas, e métodos de bootstrapping paramétrico e não paramétrico são usados para estudar o viés e a variância dos estimadores dos parâmetros, usando o programa FORTRAN para obter os resultados. No terceiro capítulo, a nova verossimilhança apresentada no capítulo 2 é usada com um modelo de escolha discreta, para resolver parte do problema apresentado no primeiro capítulo. A estrutura de encaixe é proposta para modelar a seleção de habitat de 28 corujas manchadas (Strix occidentalis), assim como a uma generalização do modelo logit encaixado, usando a maximização da utilidade aleatória e a RSPF aleatória. Métodos de otimização numérica, e o sistema computacional SAS, são usados para estimar os parâmetros de estrutura de encaixe. / In ecology, the behavior of animals is often studied to better understand their preferences for different types of habitat and food. The present work is concerned with this topic. It is divided into three chapters. The first concerns the estimation of a resource selection probability function (RSPF) compared with a discrete choice model (DCM) using chi-squared to obtain estimates. The best estimates were obtained by the DCM method. Nevertheless, animals were not selected based on choice alone. With RSPF, the maximum likelihood estimates used with the logistic regression still did not reach the objectives, since the animals have more than one choice. R and Minitab software and the FORTRAN programming language were used for the computations in this chapter. The second chapter discusses further the likelihood presented in the first chapter. A new likelihood for a RSPF is presented, which takes into account the units used and not used, and parametric and non-parametric bootstrapping are employed to study the bias and variance of parameter estimators, using a FORTRAN program for the calculations. In the third chapter, the new likelihood presented in chapter 2, with a discrete choice model is used to resolve a part of the problem presented in the first chapter. A nested structure is proposed for modelling selection by 28 spotted owls (Strix occidentalis) as well as a generalized nested logit model using random utility maximization and a random RSPF. Numerical optimization methods and the SAS system were employed to estimate the nested structural parameters.