A Generalized Estimating Equations Approach to Model Heterogeneity and Time Dependence in Capture-Recapture Studies

Individual heterogeneity in capture probabilities and time dependence are fundamentally important for estimating the closed animal population parameters in capture-recapture studies. A generalized estimating equations (GEE) approach accounts for linear correlation among capture-recapture occasions, and individual heterogeneity in capture probabilities in a closed population capture-recapture individual heterogeneity and time variation model. The estimated capture probabilities are used to estimate animal population parameters. Two real data sets are used for illustrative purposes. A simulation study is carried out to assess the performance of the GEE estimator. A Quasi-Likelihood Information Criterion (QIC) is applied for the selection of the best fitting model. This approach performs well when the estimated population parameters depend on the individual heterogeneity and the nature of linear correlation among capture-recapture occasions

Technological Progress and Emergence of Policies with Priorities for the Development of Land-Poor Farmers in Bangladesh

This macro-level research analyzed sequential changes in agricultural policies and evaluated their impacts among various groups of farmers classified based on the land ownership. All supply-side agricultural policies from their origins to current year were divided into four phases where, government supports for agriculture were changed from adverse circumstances support, to direct enormous support, to reform-embedded support, and finally to collaborative support with private sector and Non-government Organizations (NGOs). The changing policies favored all types of farmers among whose reform policies contributed more. The small farmers in the past were not benefited from government policies but they were lately more benefited from coherent policies emphasized on the development of land-poor farmers.

Prediction and modelling of complex social networks and their evolution.

This thesis focuses on complex social networks in the context of computational approaches for their prediction and modelling. The increasing popularity and advancement of social net- works paired with the availability of social network data enable empirical analysis, inference, prediction and modelling of social patterns. This data-driven approach towards social science is continuously evolving and is crucial for modelling and understanding of human social behaviour including predicting future social interactions for a wide range of applications. The main difference between traditional datasets and network datasets is the presence of the relational components (links) between instances (nodes) of the network. These links and nodes induce intricate local and global patterns, defining the topology of a network. The topology is ever evolving, determining the dynamics of such a networked system. The work presented in this thesis starts with an extensive analysis of three standard network models, in terms of their properties and self-interactions as well as the size and density of the resultant graphs. These crucial analysis and understanding of the main network models are utilised to later develop a comprehensive network simulation framework. A set of novel nature-inspired link prediction approaches are then developed to predict the evolution of networks, based solely on their topologies. Building on top of these approaches, enhanced topological representations of networks are subsequently combined with node characteristics for the purpose of node classification. Finally, the proposed classification methods are extensively evaluated using simulated networks from our network simulation framework as well as two real-world citation networks. The link prediction approaches proposed in this research show that the topology of the network can be further exploited to improve the prediction of future relationships. Moreover, this research demonstrates the potential of blending state-of-the-art Machine Learning techniques with graph theory. To accelerate such advancements in the field of network science, this research also offers an open- source software to provide high-quality synthetic datasets

Ideology and Power in the Headlines: A Critical Discourse Analysis of Bangladesh-China Relations

Using the framework of Critical Discourse Analysis CDA this study aims to explore how Bangladesh s news agency BSS 1975-2016 represents the relationship between Bangladesh and China Within this framework three methods are employed to collect data i content analysis of the 41- year media coverage ii interviews and iii observations at the newsrooms By examining 140 news headlines this article shows how the BSS under government control represents China and Bangladesh-China relations The news headline falls into macro and micro levels of analysis The macro-level analysis focuses on the ownership and control factors of the BSS while the micro-level analysis deals with the content analysis The findings show that the BSS editor has concentrated more on diplomatic news items occurring in Dhaka than in Beijing highly reported with government officials Then this paper adopts the framework of CDA which is mainly concerned with the relationship between language ideology and power Utilizing Halliday s Systemic Functional Grammar as a tool for CDA this study aims to explore the ideological meanings in the news headline termed as a micro story A pair of questions will answer how the subjects are historically represented through the BSS media discourse on the topic Therefore CDA has promoted the diplomatic relation between Bangladesh and China established in 1975 This paper clearly explains how CDA generally reflects social practice ideology and power relations between Bangladesh and China at the time of reportin

Dietary Exposure Among Adults in Selangor, Malaysia, to Heterocyclic Amines and Polycyclic Aromatic Hydrocarbons in Cooked Meat and Fish

Heterocyclic amines (HCAs) and polycyclic aromatic hydrocarbons (PAHs) are possible human carcinogens and potent mutagens which increase the incidence of colon, mammary, prostate, breast and other cancers in rodents. Food containing meat and fish are the most important source of exposure to HCAs and PAHs in the diet and heat-treated foods, especially those which are fried, broiled and grilled. The intake of HCAs and PAHs are influenced by the amount and type of meat and fish ingested, frequency of consumption, cooking methods, cooking temperature and duration of cooking. The aim of the present study was to determine the level of HCAs and PAHs in the most consumed foods in Selangor, Malaysia in order to estimate their exposure to these toxic compounds. The dietary intake of HCAs and PAHs in foods consumed by people in Selangor, Malaysia was determined. Levels of six HCAs, namely: 2-amino-3-methylimidazo[4,5-f]quinoline (IQ), 2-amino-3-4-dimethylimidazo[4,5-f] quinoline (MeIQ), 2-amino-3-8-dimethylimidazo[4,5-f]quinoxaline (MeIQx), 2-amino-3,4,8-trimethylimidazo[4,5-f]quinoxaline (4, 8-DiMeIQx), 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) and 2-amino-3,7,8-trimethylimidazo[4,5f] quinoxaline (7,8-DiMeIQx) and three PAHs, fluoranthene, benzo[b]fluoranthene and benzo[a]pyrene were measured. Forty-two samples of meat and fish were included in the study. High-performance liquid chromatography with photodiode array detector and fluorescence detector was used to analyze HCAs and PAHs, respectively. Dietary food consumption data (g/day), including meat type and cooking method were obtained using food frequency questionnaires, which were completed by 600 randomly selected subjects aged above 18 years. Results of the study showed that the level of total HCAs in food samples studied ranged from 0 to 38.7 ng/g whereas the level of total PAHs was, 0 to 66.28 ng/g. Among the analyzed HCAs and PAHs, PhIP (30.6 ng/g) and fluoranthene (50.96 ng/g) showed the highest level, respectively. The highest level of total HCAs was found in grilled chicken satay (38.7 ng/g) and for PAHs it was in grilled beef satay (66.28 ng/g). The most abundant HCAs such as PhIP and MeIQx, and for PAHs such as fluoranthene were detected in the food products studied. The 4,8-DiMeIQx, 7,8-DiMeIQx (HCAs) for HCAs and benzo[a]pyrene for PAHs were found in 12 and 22% of the meat and fish dishes. The average daily intake level of HCAs was 553.7 ng/capita/day and for PAHs of 297.58 ng/capita/day. The intake of PhIP was the highest, followed by MeIQx and MeIQ, whereas intake of fluoranthene was the highest, followed by benzo[b]fluoranthene and benzo[a]pyrene. The results reveal that grilled and fried meat and fish products were the major contributors to the exposure of HCAs and PAH

Ideational Meaning: Media Representations of Sino-Bangladesh Relation and Its Actors

This study, within the frameworks of Systemic Functional Grammar and Critical Discourse Analysis, aims to explore how Bangladesh’s news agency BSS (1975-2016) represents Sino-Bangladesh relations. Three methods are employed to collect the data: (i) the 40 year media coverage, (ii) questionnaire and (iii) observations at the newsrooms. By examining 140 news reports and investigating linguistic features, this study shows how the BSS under government control represents China and Sino-Bangladesh relations.  This study will focus only on the analysis of the news headline as a ‘micro story’, while the news body is completely excluded from the analysis. The findings will show how the social actors are constructed through the BSS media discourse on the topic. This study will detail the representations of the actors at the clause as a representation. The main reason for historical change is the establishment of the diplomatic ties between Bangladesh and China in 1975. This paper clearly explains how the media representation generally reflects social practice, ideology and power relations in social structures at the time of reporting. Keywords: critical discourse analysis, systemic functional grammar, Sino-Bangladesh relation, BSS media discourse, representation DOI: 10.7176/JLLL/52-1

Supercritical Carbon Dioxide Extraction Of Mango Seed Kernel Fat Blended With Palm Oil Mid-Fraction And Palm Stearin To Formulate Cocoa Butter Replacers

Mango (Mangifera indica L.) is an important annual tropical fruit. Mango seed kernel (MSK) which is industrial by-product contains considerable amount of cocoa butter analogy fats. It is remarkable that no reports on the extraction of the mango seed kernel fat (MSKF) using supercritical carbon dioxide (SC-CO2) have been published. The aim of this work is to blend SC-CO2 extracted MSKF with palm oil mid-fraction (POMF) and palm stearin (PS) to formulate new cocoa butter replacers (CBRs). The physico-chemical properties, thermal properties, solid fat content (SFC) and morphology for the blends of MSKF: POMF and MSKF: PS conducted using different chromatographic and thermal techniques. Optimization of the SC-CO2 extraction parameters of MSKF from MSK were conducted using central composite design (CCD) of response surface methodology (RSM). The variables considered in the study are pressure (20-50 MPa), temperature (40-80 °C), and CO2 flow rate (1-4 ml/min). The optimized fat yield was predicted to be 11.29% at 44.2 MPa, 72.2 ºC and CO2 flow rate of 3.4 ml/min which was close to the fat yield (11.7%) of Soxhlet extraction. The blends containing 70 to 85% of MSKF had physico-chemical properties like fatty acid profiles, iodine value (IV), slip melting point (SMP), saponification value (SPV) and acid value (AV) close to that of commercial CB. Results showed that the major TG ranges in all blends were POP 11-38.8%, SOS 22.1-36.9%, and POS 15.4-16.2%, respectively

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59·4 (IQR 35·4–67·3), ranging from a low of 11·6 (95% uncertainty interval 9·6–14·0) to a high of 84·9 (83·1–86·7). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030. Funding: Bill & Melinda Gates Foundation