The following research aims to examine the interaction of law, either hard law (legislation) or soft law (governing body regulation), on achieving a balance between racial equality and success in sport. Nearly all national jurisdictions have legislated to some degree in an attempt to affect equality or equality of opportunity for its citizens. This might be based on achieving equality of opportunity or by means of affirmative action. The research aim is to ascertain how far racial discrimination laws have positive or negative impacts on the success of sports in different countries. The research also has a series of supplementary objectives: to ascertain and consider critically the extent to which the law in various jurisdictions (Malaysia, South Africa, England and the United States) has been used to promote equality; to develop a sequential model to describe general trends to predict the influence of affirmative action and equal opportunity legislation upon the potential success of countries’ sporting achievements; to review tensions inherent in reconciling the equality of citizens at a national level and their impacts upon the international sporting success of that nation; to establish a correlative relationship between the types of anti-discrimination law within nations and the impact of these upon the degree of international sporting success of those nations. The research conducted concentrates primarily on qualitative methods by first adopting a doctrinal approach in a comparative legal study of four jurisdictions (Malaysia, South Africa, England and the United States). A non-doctrinal approach is then adopted and a qualitative intrinsic case study completed, including interviews concerning the subject area. Thus, the research has used multi-method qualitative approaches. The research indicated different anti-discrimination approaches taken in achieving equality. This can be typified by countries such as the United States or England based primarily on meritocracy and countries such as South Africa and Malaysia based primarily on preferential treatment. There is evidence to suggest that these approaches do have a certain correlation, albeit not similar in the outcome of achieving equality for selection. From the evidence presented, the overall study illustrates that racial discrimination laws in the four jurisdictions produced a mixed outcome in relation to the success of professional team sports. Specifically, England and the United States witnessed a positive impact in terms of achieving international success in sports even though there are inherent difficulties in reconciling the equality of citizens at a national level. For Malaysia and South Africa, the result tends to be positive in general at this stage although it is equally recognised that this approach might result in some negative impacts in the long run. The research however is subject to certain limitations which are outside the scope of this thesis, but it is recognised that these might affect the overall success of professional team sports within those countries.

Background: Physical Dating Violence (PDV) victimization is a major public health concern among adolescents in the United States. Research has shown that determinants of PDV victimization are different for male and female adolescents. However, inconsistent findings entail that further research needs to be done using a representative sample of male and female adolescents.Objective: To identify gender-specific determinants of PDV victimization utilizing a nationally representative sample of high school adolescents.Methods: Data from the 2005 National Youth Risk Behavior Survey was used for this analysis. The study population included 6.951 male and 6,807 female students in grades 9 through 12. Bivariate and multivariate analyses were conducted and three predictor models were generated. The first model examined predictors of PDV in the total population. The second and third models identified predictors of PDV in male and female participants, respectively.Results: PDV affects approximately 1 in every 11 youth in the United States, with males and females exhibiting prevalence rates (males: 9.0%, females: 9.2%). Being currently sexually active, using alcohol, engaging in a physical fight, experiencing sexual victimization, and having suicidal thoughts were significant predictors of PDV for both male and female participants. Poor body images were found to be a significant predictor among females but not in males. On the other hand, illicit drug use was a significant predictor among males but not in females.Conclusions: This study provided evidence that there is some gender difference in the determinants of PDV. It is essential that counselors and care providers give particular attention to female adolescents with poor body image and male adolescents who report illicit drug use.

La rabia es una enfermedad viral, con una alta tasa de mortalidad, la cual es principalmente transmitida por el perro doméstico y el murciélago hematófago, Desmodus rotundus. A pesar de las acciones de prevención y control aún es endémica en el Perú. Los principales objetivos del presente trabajo fueron la descripción de la rabia humana y animal en el Perú, como también el desarrollo de un modelo predictivo de transmisión del virus de la rabia en el ganado bovino. Se utilizaron los reportes nacionales oficiales de casos y brotes de rabia humana y animal entre los años del 2001 al 2017. Los resultados indicaron que los casos de rabia humana ocurren principalmente como consecuencia del ciclo silvestre, y se presentan con mayor frecuencia en las regiones amazónicas. Mientras que los casos de rabia canina han sufrido un reciente aumento debido al brote de la enfermedad en el sur del Perú. Por otro lado, los focos de la rabia bovina han sido bastantes frecuentes a lo largo de los años, y se encuentran distribuidos especialmente a lo largo de los valles interandinos y regiones amazónicas del Perú. Asimismo, el riesgo de transmisión de rabia de murciélagos hematófagos para bovinos se estimó mediante la adaptación de un modelo de receptividad y vulnerabilidad basado en árboles de decisión, para el desarrollo de un modelo predictivo de rabia bovina por distritos. Los datos oficiales de los brotes de la enfermedad en bovinos y la información sobre alteraciones ambientales se utilizaron como covariables. La densidad de bovinos y las características geomorfológicas de cada distrito fueron obtenidas a través del último censo nacional agropecuario y de los sistemas de información geográfica disponibles. El modelo fue validado a través de la evaluación de algunos escenarios que fueron concebidos a partir de diferentes puntos de corte de las variables de receptividad en comparación con la información de los brotes de los últimos 6 años, a fin de encontrar el grado de predicción más adecuado para la ocurrencia de brotes de rabia por distrito. Entre las principales conclusiones, se encuentra la importancia del mantenimiento de las políticas nacionales de prevención y promoción de la salud de la rabia humana y animal en el Perú. Además, del desarrollo de nuevos criterios de intervención que prioricen la ecología de los transmisores del virus a las poblaciones susceptibles, lo que puede representar una mejor opción que otras medidas preventivas que no han tenido el éxito esperado. Finalmente, el modelo de predicción para la rabia bovina propuesto, a pesar de depender de la información generada por la vigilancia epidemiológica de la enfermedad, representa una herramienta interesante para optimizar su funcionamiento a nivel nacional. / Rabies is a viral disease, with a high mortality rate, that is mainly transmitted by the domestic dogs and the hematophagous bat, Desmodus rotundus. Despite the prevention and control actions, it is still endemic in Peru. The main objectives of the present work were the description of human and animal rabies in Peru, as well as the development of a predictive model of transmission of rabies virus in livestock. The official national reports of cases and outbreaks of human and animal rabies between the years 2001 to 2017 were used. The results indicated that human cases of rabies mainly occur as a consequence of the wild cycle, that are presented with higher frequency in the Amazonian regions. While dog cases of rabies have suffered a recent increase due to the outbreak of the disease in Southern Peru. On the other hand, the outbreaks of bovine rabies were frequent over the years being distributed particularly along the inter-Andean valleys and Amazonian regions of Peru. Additionally, the risk of rabies transmission from hematophagous bats to bovines was estimated through the adaptation of a receptivity and vulnerability model based on decision trees, for the development of a predictive model of bovine rabies by districts. The official data of outbreaks of the disease in bovines and the information on environmental alterations were used as covariates. The density of livestock and the geomorphological characteristics of each district were obtained through the last national livestock census and the geographic information systems available. The model was validated through the evaluation of some scenarios that were conceived from different cut points of the receptivity variables compared to the information of the outbreaks from the last 6 years, in order to find the most suitable degree of prediction for the occurrence of rabies outbreaks by district. Among the main conclusions, is the importance of maintainance of the national policies of prevention and health promotion of human and animal rabiesin Peru. Moreover, the developing of new intervention criteria that prioritize the ecology of the transmitters of the virus to the susceptible populations, which may represent a better option than other preventive measures that havent had the expected success. Finally, the proposed bovine rabies prediction model, despite being dependent on the information generated by the epidemiological surveillance of the disease, represents an interesting tool to optimize its functioning at national level.

Sarcopenia (Sc) é uma doença caracterizada por sintomas patológicos sem causas específicas que acomete parte dos idosos. A Sc promove reduções na massa muscular (MM) e força muscular (FM), com sérios impactos funcionais e motores. A força de preensão manual (FPM) utilizada para diagnosticar Sc não é representativa da FM global, especialmente para FM de membros inferiores (MMII), quando idosos passam por intervenção com treinamento de FM. Embora utilizada para definir a Sc, FM é considerada de forma absoluta ou relativizada pela massa corporal (MC), cuja relação nem sempre é linear. Assim, o objetivo deste estudo foi estabelecer parâmetros válidos para diagnóstico da Sc, a partir de diferentes expressões da FM de MMII em idosos. Uma amostra de 98 idosos fisicamente independentes foi medida pela absorciometria radiológia de dupla energia (DXA) para determinação do Tecido Mole Magro apendicular. Os idosos foram classificados por sexo e Sc (1=Sc; 0=não Sc), segundo os critérios do European Working Group on Sarcopenia in Older People (EWGSOP). A FM de extensão de joelhos (FMEJ) isocinética determinada a 60º/s (Biodex, System 4 Pro), foi considerada como FM referencial (FMEJTorquePico-60°/s), e a FMEJ Estimada em cadeira extensora (CMáxEstFMEJcad-ext), em protocolo de repetição máxima. Análise descritiva com medidas de tendência central foi utilizada para caracterização da amostra. A validação da FMEJ Estimada foi testada por correlação com a FMEJ de referência. Os valores de CMáxEstFMEJcad-ext foram relativizados pela massa corporal (FMEJ/MC) e por ajustes alométricos (FMEJ/MCb), onde b é o expoente gerado por regressão log-linear entre FMEJ e MC. Para determinar um modelo explicativo da Sc a partir de cada expressão da CMáxEstFMEJcad-ext (absoluta, FMEJ/MC e FMEJ/MCb) foi empregada a regressão logística simples. Os pontos de corte para Sc a partir da CMáxEstFMEJcad-ext foram definidos pela curva Característica de Operação do Receptor (ROC) e localizados pelo índice de Youden. As análises foram realizadas no Statistical Product and Service Solutions (SPSS) 20.0 e MedCalc 15.2 com níveis de significância previamente estabelecidos (?=0,05). Os resultados indicaram que a Sc esteve presente em 12,9% dos homens e 9,0% das mulheres. Houve alta correlação entre a medida de FMEJ de referência e a Estimada (r=0,81), mesmo entre idosos com Sc (r=0,72). Os expoentes b obtidos foram de 0,96 e 0,70 para homens e mulheres, respectivamente. Na regressão logística, as expressões relativas (FMEJ/MC e FMEJ/MCb) não explicaram a probabilidade para ocorrência da Sc em nenhum dos sexos. Somente a CMáxEstFMEJcad-ext absoluta explicou a chance para homens (?2=3,869; p=0,049) e mulheres (?2=4,145; p=0,042). A área abaixo da curva foi elevada (AUC>0,70), com pontos de corte de 65,0kg para homens e 34,9kg para mulheres. Conclui-se que a CMáxEstFMEJcad-ext é uma medida válida para monitorar Sc como parâmetro de FM em idosos, mesmo quando apresentam Sc. Os limiares de carga (kg) propostos como pontos de corte podem ser usados em um simples teste FMEJ da prática clínica profissional. Além disso, tem boa sensibilidade para monitorar a distância do ponto corte para Sc, o que não é possível com o modelo dicotômico do EWGSOP / Sarcopenia (Sc) is a disease characterized by pathological symptoms without specific causes that affects part of the elderly. Sc promotes reductions in muscle mass (MM) and muscle strength (MS), with serious functional and motor impacts. The handgrip strength (HS) used to diagnose Sc is not representative of global MS, especially for lower limb (LL) MS, when the elderly go through an intervention with MS training. Although used to define Sc, MS is considered absolutely or relativized by body mass (BM), whose relationship is not always linear. Thus, the objective of this study was to establish valid parameters for the diagnosis of Sc, from different MS expressions of LL in the elderly. A sample of 98 physically independent elderly subjects was measured by dual energy absorptiometry (DXA) to determine appendicular lean soft tissue. The elderly were classified by sex and Sc (1=Sc; 0=not Sc), according to the criteria of the European Working Group on Sarcopenia in Older People (EWGSOP). The isokinetic knee extension MS (KEMS) determined at 60º/s (Biodex, System 4 Pro) was considered as referential (KEMSPeakTork-60°/s), and KEMS Estimated in extensor chair (EstMaxLoadKEMSext-ch), in maximal repetition protocol. Descriptive analysis with measures of central tendency was used to characterize the sample. Validation of the estimated KEMS was tested by correlation with the reference KEMS. The values of EstMaxLoadKEMSext-ch were relativized by body mass (KEMS/BM) and by allometric adjustments (KEMS/BMb), where b is the allometric exponent generated from the log-linear regression between KEMS and BM. To determine an explanatory model of Sc from each expression of EstMaxLoadKEMSext-ch (absolute, KEMS/BM and KEMS/BMb), simple logistic regression was used. The cutoff points for Sc from the EstMaxLoadKEMSext-ch were defined by the Receiver Operating Characteristic (ROC) curve and located by the Youden index. The analyzes were performed in Statistical Product and Service Solutions (SPSS) 20.0 and MedCalc 15.2 with previously established levels of significance (? = 0.05). The results indicated that Sc was present in 12.9% of men and 9.0% of women. There was a high correlation between the reference KEMS and the estimated (r=0.81), even among the elderly with Sc (r=0.72). The exponent b obtained was 0.96 and 0.70 for men and women, respectively. In the logistic regression, the relative expressions (KEMS/BM and KEMS/BMb) did not explain the probability for occurrence of Sc in any of the sexes. Only absolute EstMaxLoadKEMSext-ch explained the chance for males (?2=3,869, p=0.049) and females (?2=4.145, p=0.042). The area below the curve was elevated (AUC>0.70), with cutoff points of 65.0kg for men and 34.9kg for women. It is concluded that the EstMaxLoadKEMSext-ch is a valid measure to monitor Sc as MS parameter in the elderly, even when they present Sc. Load thresholds (kg) proposed as cutoff points can be used in a simple clinical practice test. In addition, it has good sensitivity to monitor the distance from the cut point to MS, which is not possible with the dichotomous model of the EWGSOP

Introdução: O impacto da doença renal na saúde é alto para os pacientes e para os serviços de saúde em todo o mundo, e a triagem para doença renal crônica (DRC) tem sido cada vez mais defendida. Estudos de base populacional referentes à prevalência da DRC na comunidade são limitados. Objetivos: Estudamos prospectivamente se a estratificação pelos valores do SCORED registrados poderá ser útil para identificar indivíduos que estão em alto risco de ter doença renal crônica em uma amostra da população geral e comparamos com os métodos de diagnósticos convencionais para DRC. Casuística e métodos: A freqüência de indivíduos com alto risco para a DRC foi determinada utilizando um estudo transversal de 873 indivíduos adultos em Palmas, Tocantins, Brasil. Os indivíduos entrevistados foram selecionados aleatoriamente através de um método estratificado por conglomerados. Idade, sexo e raça foram semelhantes à população urbana de Palmas. DRC foi definida através do ritmo de filtração glomerular estimado (RFGe) <60 ml/min/1.73 m2. Resultados: Um RFGe <60 ml/min/ 1.73 m2 estava presente em 46 (5,3%) dos participantes estudados. O risco de ter doença renal crônica foi maior em mulheres que em homens, e aumentou com a idade de 2,7% no grupo de 18-44 anos de idade para 19,0% naqueles com 65 anos de idade ou mais. As freqüências da DRC nos estágios 3, 4 e 5 foram de 4,8%, 0,5% e 0%, respectivamente. Os valores do SCORED incluíram 224 (25,7%) indivíduos com altos valores ( 4), e 649 (74,3%) indivíduos com baixos valores. Indivíduos com maiores valores na pontuação do SCORED tiveram um risco significativamente maior de ter doença renal crônica em comparação com aqueles que tinham menores valores pontuados (12,9% vs 2,6%, 2 = 35,58, p <0,001). A sensibilidade para prever DRC por esse modelo foi de 63% e a especificidade foi de 76%, o valor preditivo positivo foi de 13%, enquanto o valor preditivo negativo foi de 76%. Conclusão: Valores elevados do SCORED foram associados a um risco maior de ter doença renal crônica em uma amostra da população geral. Esta ferramenta simples de triagem foi uma ferramenta útil para identificar indivíduos de alto risco para DRC / Background and objective: The health burden of renal disease is high for patients and health services worldwide, and screening for chronic kidney disease (CKD) has been increasingly advocated. Population-based studies relating to the prevalence of CKD in the community are limited. We prospective studied whether stratification by SCORED values could be useful to identify subjects who are at high-risk for having CKD in a general population-based sampling. Design, participants & methods: The frequency of individuals at high-risk for CKD was determined using a cross-sectional study of 873 adult households in Palmas, Brazil, randomly selected using a stratified, cluster method. Age, gender, and race were similar to the entire Palmas´ urban population. Results: An estimated GFR <60 ml/min/1.73 m2 was present in 46 (5.3%) of participants studied, and the risk for having CKD was greater in women than in men, and it increased with age from 2.7% in the 18 to 44 yr age group to 19.0% in those 65 yr of age older. The frequencies of CKD Stage 3, 4 and 5 were 4.8%, 0.5% and 0%, respectively. SCORED values included 224 (25.7%) patients with high SCORED values (4), and 649 (74.3%) subjects with low SCORED values. Subjects with higher SCORED values were at a significantly higher risk of having CKD compared with those who had lower SCORED values (12.9% vs 2.6%, 2 = 35.58; p <0.001). The sensivity for predicting CKD by SCORED model was 63% and the specificity was 76%; the positive predictive value was 13%, whereas the negative predictive value was 76%. Conclusion: High SCORED values were associated with a higher risk for having CKD in a general population-based sampling. This simple screening tool was a useful tool to identify individuals at high-risk for CKD

Wastewater treatment plants (WWTP) involve several complex physical, biological and chemical processes. Often these processes exhibit non-linear behavior that is difficult to describe by classical mathematical models. Safer operation and control of a WWTP can be achieved by developing a modeling tool for predicting the plant performance. In the last decade, many studies were realized in wastewater treatment based on intelligent methods which are related to modeling WWTP. These studies are about predictions of WWTP parameters, process control of WWTP, estimating WWTP output parameters characteristics. In many studies, neural network models were used to model chemical and physical attributes in the flow rate. In this Thesis, a data-driven approach for analyzing water quality is introduced. Improvements in the data collection of information system allow collection of large volumes of data. Although improvements in data collection systems have given researchers sufficient information about various systems, they must be used in conjunction with novel data-mining algorithms to build models and recognize patterns in large data sets. Since the mid 1990's, data mining has been successfully used for model extraction and describing various phenomena of interest.

It is widely known that the world is losing biodiversity and primarily it is thought to be caused by anthropogenic activities. Many of these activities have been identified. However, we still lack a clear understanding of the causal relationships between human activities and the pressures they place on the environment and biodiversity. We need to know how ecosystems and individual species respond to changes in human activities and therefore how best to moderate our actions and reduce the rate of loss of biodiversity. One of the ways to detect these changes is to use indicators of ecosystem conditions. Indicators are statistics following changes in a particular factor usually over time. These indicators are used to summarise a complex set of data, and are seen as being representative of the wider situation in that field. So it can be assumed that if that particular factor is declining or improving, then the situation in general is also declining or improving. They are used to check the status and trends of biodiversity by both the public and policy makers. Indicators are also used to assess national performance and can be used to identify the actions required at the policy level. In this manner, they provide an important link between policy-makers and scientists collecting the data. The current thesis investigates the possibility of using bird species as indicators of biodiversity for better management of natural terrestrial ecosystems, by identifying their habitats according to various environmental factors. The study is established by drawing upon three main scientific areas: ecology, geographical information system (GIS), and statistical modelling. The Mornington Peninsula and Western Port Biosphere Reserve (MPWPBR) (Victoria, Australia) was chosen for the study area because of the combination of suburban and natural environments that made it optimum for this type of study. Once the study area was defined, the necessary data for the research were obtained from various sources. Birds Australia provided data on recorded observation of 271 bird species within the study area. Based on the nature of this study, seven species were selected for the study. The criteria for this selection are discussed in Chapter 3. Most literature state that the primary determinant for bird abundance is vegetation and land cover. Because of this, Ecological Vegetation Class (EVC) layer was used to determine which type(s) of vegetation have the greatest impact on habitat selection. Each species showed a relationship to a number of v vegetation types. These EVCs were combined to produce vegetation patches, and were considered as potentially suitable habitats of corresponding bird species. For each of the species, these habitat patches were analysed for the different aspects of patch characteristics (such as the level of patchiness, connectivity, size, shape, weighted distance between patches, etc.) by using the Landscape Context Tool (a GIS add-on). This process assisted the understanding of the importance of patch quality in habitat selection among different bird species by analysing the location of bird observation sites relative to habitat patches. In this way, the association between bird presence and the conditions of a habitat patch was identified by performing a discriminant function analysis. To investigate the probability of a species presence according to different environmental factors, a model of species distribution was created. Binary logistic regression was used to indicate the level of effect of each variable. The model was then successfully validated in the field. To define the indicators of environmental factors, it was essential to separate bird species based on their dependency on one or more of the studied variables. For this purpose, One-Way ANOVA was used. This analysis showed that some bird species can be considered as indicators of urban areas, while others could be good indicators of wellpreserved large forests. Finally, it must be mentioned that the type and quality of the datasets are crucial to this type of study, because some species have a higher degree of sensitivity to certain types of vegetation or land cover. Therefore, the vegetation data must be produced as detailed as possible. At the same time, the species data needs to be collected based on the presence and absence (versus presence-only) of the birds.

The development of predictive appearance models for organic tissues is a challenging task due to the inherent complexity of these materials. In this thesis, we closely examine the biophysical processes responsible for the appearance attributes of whole blood, one the most fundamental of these materials. We describe a new appearance model that simulates the mechanisms of light propagation and absorption within the cellular and fluid portions of this specialized tissue. The proposed model employs a comprehensive, and yet flexible first principles approach based on the morphological, optical and biochemical properties of blood cells. This approach allows for environment driven changes in the cells' anatomy and orientation to be appropriately included into the light transport simulations. The correctness and predictive capabilities of the proposed model are quantitatively and qualitatively evaluated through comparisons of modeled results with actual measured data and experimental observations reported in the scientific literature. Its incorporation into rendering systems is illustrated through images of blood samples depicting appearance variations controlled by physiologically meaningful parameters. Besides the contributions to the modeling of material appearance, the research presented in this thesis is also expected to have applications in a wide range of biomedical areas, from optical diagnostics to the visualization and noninvasive imaging of blood-perfused tissues.

This dissertation has mainly two parts. In the first part, we propose a bivariate nonlinear multivariate measurement error model to understand the distribution of dietary intake and extend it to a multivariate model to capture dietary patterns in nutrition epidemiology. In the second part, we propose regression-based predictive models to accurately predict surgery duration in healthcare. Understanding the distribution of episodically consumed dietary components is an important problem in public health. Short-term measurements of episodically consumed dietary components are zero-inflated skewed distributions. So-called two-part models have been developed for such data. However, there is much greater public health interest in the usual intake adjusted for caloric intake. Recently a nonlinear mixed effects model has been developed and fit by maximum likelihood using nonlinear mixed effects programs. However, the fitting is slow and unstable. We develop a Monte-Carlo-based fitting method in Chapter II. We demonstrate numerically that our methods lead to increased speed of computation, converge to reasonable solutions, and have the flexibility to be used in either a frequentist or a Bayesian manner. Diet consists of numerous foods, nutrients and other components, each of which have distinctive attributes. Increasingly nutritionists are interested in exploring them collectively to capture overall dietary patterns. We thus extend the bivariate model described in Chapter III to multivariate level. We use survey-weighted MCMC computations to fit the model, with uncertainty estimation coming from balanced repeated replication. The methodology is illustrated through an application of estimating the population distribution of the Healthy Eating Index-2005 (HEI-2005), a multi-component dietary quality index , among children aged 2-8 in the United States. The second part of this dissertation is to accurately predict surgery duration. Prior research has identified the current procedural terminology (CPT) codes as the most important factor when predicting surgical case durations but there has been little reporting of a general predictive methodology using it effectively. In Chapter IV, we propose two regression-based predictive models. However, the naively constructed design matrix is singular. We thus devise a systematic procedure to construct a fullranked design matrix. Using surgical data from a central Texas hospital, we compare the proposed models with a few benchmark methods and demonstrate that our models lead to a remarkable reduction in prediction errors.

This study aims to construct a predictive model that investigates patterning of settlement mounds by employing environmental variables. The results then will help to search for unknown sites of the same age. The methodology is applied to the Lake District of Anatolia for the period of 9000B.C. &amp / #8211 / 5500B.C. Four main sets of data are used in this study. The first set is the settlement data, which includes the names, coordinates, and periods of the sites. The sources of independent datasets are topography, lithology and soil. The study starts with the straightforward procedure of plotting the sites in the region. Then the layers (independent variables), populated with their sub-fields, are included in the model in the GIS to construct a predictive model by using logistic regression. Results reveal some high potential areas with no known occupation, as well as some zones which need more research. Also, hierarchy of environmental variables is detected, which affected the settlement patterning of the study area.