Hierarchical Re-estimation of Topic Models for Measuring Topical Diversity

A high degree of topical diversity is often considered to be an important characteristic of interesting text documents. A recent proposal for measuring topical diversity identifies three elements for assessing diversity: words, topics, and documents as collections of words. Topic models play a central role in this approach. Using standard topic models for measuring diversity of documents is suboptimal due to generality and impurity. General topics only include common information from a background corpus and are assigned to most of the documents in the collection. Impure topics contain words that are not related to the topic; impurity lowers the interpretability of topic models and impure topics are likely to get assigned to documents erroneously. We propose a hierarchical re-estimation approach for topic models to combat generality and impurity; the proposed approach operates at three levels: words, topics, and documents. Our re-estimation approach for measuring documents' topical diversity outperforms the state of the art on PubMed dataset which is commonly used for diversity experiments.Comment: Proceedings of the 39th European Conference on Information Retrieval (ECIR2017

Convergence in measure under Finite Additivity

We investigate the possibility of replacing the topology of convergence in probability with convergence in $L^1$. A characterization of continuous linear functionals on the space of measurable functions is also obtained

Retrospective model-based inference guides model-free credit assignment

An extensive reinforcement learning literature shows that organisms assign credit efficiently, even under conditions of state uncertainty. However, little is known about credit-assignment when state uncertainty is subsequently resolved. Here, we address this problem within the framework of an interaction between model-free (MF) and model-based (MB) control systems. We present and support experimentally a theory of MB retrospective-inference. Within this framework, a MB system resolves uncertainty that prevailed when actions were taken thus guiding an MF credit-assignment. Using a task in which there was initial uncertainty about the lotteries that were chosen, we found that when participants’ momentary uncertainty about which lottery had generated an outcome was resolved by provision of subsequent information, participants preferentially assigned credit within a MF system to the lottery they retrospectively inferred was responsible for this outcome. These findings extend our knowledge about the range of MB functions and the scope of system interactions

Deriving utility scores for co-morbid conditions: a test of the multiplicative model for combining individual condition scores

BACKGROUND: The co-morbidity of health conditions is becoming a significant health issue, particularly as populations age, and presents important methodological challenges for population health research. For example, the calculation of summary measures of population health (SMPH) can be compromised if co-morbidity is not taken into account. One popular co-morbidity adjustment used in SMPH computations relies on a straightforward multiplicative combination of the severity weights for the individual conditions involved. While the convenience and simplicity of the multiplicative model are attractive, its appropriateness has yet to be formally tested. The primary objective of the current study was therefore to examine the empirical evidence in support of this approach. METHODS: The present study drew on information on the prevalence of chronic conditions and a utility-based measure of health-related quality of life (HRQoL), namely the Health Utilities Index Mark 3 (HUI3), available from Cycle 1.1 of the Canadian Community Health Survey (CCHS; 2000–01). Average HUI3 scores were computed for both single and co-morbid conditions, and were also purified by statistically removing the loss of functional health due to health problems other than the chronic conditions reported. The co-morbidity rule was specified as a multiplicative combination of the purified average observed HUI3 utility scores for the individual conditions involved, with the addition of a synergy coefficient s for capturing any interaction between the conditions not explained by the product of their utilities. The fit of the model to the purified average observed utilities for the co-morbid conditions was optimized using ordinary least squares regression to estimate s. Replicability of the results was assessed by applying the method to triple co-morbidities from the CCHS cycle 1.1 database, as well as to double and triple co-morbidities from cycle 2.1 of the CCHS (2003–04). RESULTS: Model fit was optimized at s = .99 (i.e., essentially a straightforward multiplicative model). These results were closely replicated with triple co-morbidities reported on CCHS 2000–01, as well as with double and triple co-morbidities reported on CCHS 2003–04. CONCLUSION: The findings support the simple multiplicative model for computing utilities for co-morbid conditions from the utilities for the individual conditions involved. Future work using a wider variety of conditions and data sources could serve to further evaluate and refine the approach

Transgenic Bt Cotton

Not AvailableCotton is one of the major fibre crops of global significance. It is cultivated in tropical and subtropical regions of more than eighty countries of world occupying nearly 33 m ha with an annual production of 19 to 20 million tones of bales. China, U.S.A., India, Pakistan, Uzbekistan, Australia, Brazil, Greece, Argentina and Egypt are major cotton producing countries. These countries contribute nearly 85% of the global cotton production. In India, cotton is being cultivated in 9.0 m ha and stands first in acreage. The crop is grown in varied agro-climatic situation across nine major states viz. Maharashtra, Gujarat, Madhya Pradesh, Punjab, Haryana, Rajasthan, Andhra Pradesh, Karnataka and Tamil Nadu. The crop is also grown on small area in Orissia, Assam, U.P and West Bengal. Nearly 60 million people are engaged in cotton production, marketing and processing. The textile industry which utilizes the cotton provides employment to about 16% of the total workforce. Cotton in its various forms also serves as raw material for more than 25 industries

Mortality in Central Java: results from the indonesian mortality registration system strengthening project

Background. Mortality statistics from death registration systems are essential for health policy and development. Indonesia has recently mandated compulsory death registration across the entire country in December 2006. This article describes the methods and results from activities to ascertain causes of registered deaths in two pilot registration areas in Central Java during 2006-2007. The methods involved several steps, starting with adaptation of international standards for reporting causes of registered deaths for implementation in two sites, Surakarta (urban) and Pekalongan (rural). Causes for hospital deaths were certified by attending physicians. Verbal autopsies were used for home deaths. Underlying causes were coded using ICD-10. Completeness of registration was assessed in a sample of villages and urban wards by triangulating data from the health sector, the civil registration system, and an independent household survey. Finally, summary mortality indicators and cause of death rankings were developed for each site. Findings. A total of 10,038 deaths were registered in the two sites during 2006-2007; yielding annual crude death rates of 5.9 to 6.8 per 1000. Data completeness was higher in rural areas (72.5%) as compared to urban areas (52%). Adjusted life expectancies at birth were higher for both males and females in the urban population as compared to the rural population. Stroke, ischaemic heart disease and chronic respiratory disease are prominent causes in both populations. Other important causes are diabetes and cancer in urban areas; and tuberculosis and diarrhoeal diseases in rural areas. Conclusions. Non-communicable diseases cause a significant proportion of premature mortality in Central Java. Implementing cause of death reporting in conjunction with death registration appears feasible in Indonesia. Better collaboration between health and registration sectors is required to improve data quality. These are the first local mortality measures for health policy and monitoring in Indonesia. Strong demand for data from different stakeholders can stimulate further strengthening of mortality registration systems

Verifying causes of death in Thailand: rationale and methods for empirical investigation

Background: Cause-specific mortality statistics by age and sex are primary evidence for epidemiological research and health policy. Annual mortality statistics from vital registration systems in Thailand are of limited utility because about 40% of deaths are registered with unknown or nonspecific causes. This paper reports the rationale, methods, and broad results from a comprehensive study to verify registered causes in Thailand.Methods: A nationally representative sample of 11,984 deaths was selected using a multistage stratified cluster sampling approach, distributed across 28 districts located in nine provinces of Thailand. Registered causes were verified through medical record review for deaths in hospitals and standard verbal autopsy procedures for deaths outside hospitals, the results of which were used to measure validity and reliability of registration data. Study findings were used to develop descriptive estimates of cause-specific mortality by age and sex in Thailand.Results: Causes of death were verified for a total of 9,644 deaths in the study sample, comprised of 3,316 deaths in hospitals and 6,328 deaths outside hospitals. Field studies yielded specific diagnoses in almost all deaths in the sample originally assigned an ill-defined cause of death at registration. Study findings suggest that the leading causes of death in Thailand among males are stroke (9.4%); transport accidents (8.1%); HIV/AIDS (7.9%); ischemic heart diseases (6.4%); and chronic obstructive lung diseases (5.7%). Among females, the leading causes are stroke (11.3%); diabetes (8%); ischemic heart disease (7.5%); HIV/AIDS (5.7%); and renal diseases (4%).Conclusions: Empirical investigation of registered causes of death in the study sample yielded adequate information to enable estimation of cause-specific mortality patterns in Thailand. These findings will inform burden of disease estimation and economic evaluation of health policy choices in the country. The development and implementation of research methods in this study will contribute to improvements in the quality of annual mortality statistics in Thailand. Similar research is recommended for other countries where the quality of mortality statistics is poor

Giant cell tumor of the temporal bone – a case report

BACKGROUND: Giant cell tumor is a benign but locally aggressive bone neoplasm which uncommonly involves the skull. The petrous portion of the temporal bone forms a rare location for this tumor. CASE PRESENTATION: The authors report a case of a large giant cell tumor involving the petrous and squamous portions of the temporal bone in a 26 year old male patient. He presented with right side severe hearing loss and facial paresis. Radical excision of the tumor was achieved but facial palsy could not be avoided. CONCLUSION: Radical excision of skull base giant cell tumor may be hazardous but if achieved is the optimal treatment and may be curative