Efficient probabilistic inversion of geophysical data

Estimation of uncertainties is critical for subsequent decision making in all applications of geosciences such as geological hazard analysis and risk mitigation, management and exploitation of subsurface resources, and environmental waste disposal. More efficient probabilistic inversion methods in geosciences are vital to making rapid and improved predictions of geological hazards and estimation of subsurface resources from geophysical data, and estimation of associated uncertainties. While this thesis focuses on seismic data inversion for the estimation of geological properties, the methods developed may find a wide variety of applications in all fields of research that involve spatial data analysis. New concepts, models and methods are developed to perform more efficient probabilistic inversion by making use of the latest developments in machine learning and Bayesian inverse theory to solve geophysical inverse problems. The major contribution of this thesis is the development of efficient geostatistical inversion methods for approximate inference for structured inverse problems where probabilistic dependence between unknown model parameters may be expressed as a Markov random field (MRF). These methods are many orders of magnitude faster than the corresponding sampling based methods in such types of inverse problems. Further, some of the commonly used but avoidable assumptions in conventional geostatistical inversion methods are progressively relaxed and finally removed in this research. The faster inversion methods allow more complex models to be evaluated for more accurate predictions and improved estimation of uncertainty for given compute power and time. Most existing geostatistical inversion methods are based on the localized likelihoods assumption, whereby the seismic data at a location are assumed to depend on the geology only at that location. Such an assumption is unrealistic because of imperfect seismic data acquisition and processing, and fundamental limitations of seismic imaging methods. It is also assumed in most such previous research that the data are completely free of any correlated noise or errors. Although these requirements are almost never met in reality, existing methods use these assumptions to make solutions computationally tractable. Both of these assumptions are progressively removed in this thesis while still allowing computationally tractable solutions to be found for suitably structured problems. The class of problems considered here spans a broad range of spatial data analysis and geosciences, where geology at a location is assumed to depend directly only on the geology within some pre-specified neighbourhood of that location – the so called Markovian assumption – which is the core assumption across the entire literature of geostatistics and has been proven to be valid for all practical purposes. Exact Bayesian inference is intractable in most models of practical interest because it requires normalization of the posterior distribution by integrating model parameters over a very high dimensional space. Therefore, approximate inference is used in practice. Stochastic sampling (e.g., by using Markov-chain Monte Carlo – McMC) is the most commonly used approximate inference method but is computationally expensive and detection of its convergence is often based on subjective criteria and hence is unreliable. New Bayesian inversion methods are introduced that estimate the spatial distribution of geological properties from attributes of seismic data, by showing how the usual probabilistic inverse problem can be solved using an optimization framework while still providing full probabilistic results – the so called variational inference approach. The intractable posterior distribution is replaced by a tractable approximation in the variational approach. Inference can then be performed using the approximate distribution in an optimization framework, thus circumventing the need for sampling, while still providing probabilistic results. The methods developed in this thesis infer the post-inversion (posterior) probability density of the unknown model parameters from seismic data and geological prior information. These methods are shown to be robust against weak prior information and correlated noise in the data. The methods are computationally efficient, and are expected to be applicable to 3D models of realistic size on modern computers without incurring any significant computational limitations

Public investment, private investment, governance and tourism growth in five South Asian Association for Regional Cooperation countries

The present research investigates the effects of public and private investment in Travel and Tourism (T&T), and their interaction effect on tourism growth in five South Asian Association for Regional Cooperation (SAARC) countries. It also examines the interaction effect of public and private investment with governance on tourism growth in the region. The panel data for the five SAARC countries, from 1996 to 2015, is analyzed using Fully Modified Ordinary Least Squares and Pooled Mean Group methods. The study findings reveal that public investment, private investments, and their interaction positively affect tourism growth. The interaction effects of governance with public and private investments produce mixed results for the three indicators of governance. The interaction of political stability and absence of violence with private investment shows positive effect, however, its interaction with public investment illustrates negative effect on tourism growth. In addition, the interaction effect of control of corruption and public investment on tourism growth is positive, while there is an evidence of negative effect of the interaction of control of corruption and private investment. Similarly, the interaction effect of rule of law and public investment on tourism growth is positive, whereas, it is negative in case of the interaction of rule of law and private investment. Therefore, it is recommended that public investment needs to be increased in T&T, in addition to ensure conducive environment for private sector participation in order to reap its full potential. The study also suggests improving the governance, as it enhances the efficiency and productivity of public and private investments in T&T

Impact evaluation of structural adjustment program: a case of Pakistan

We analyzed the effect of Structural Adjustment Program (SAP) on macroeconomic variables of Pakistan using annual time series data for the years 1981-2001. The impact of four policy instruments of SAP, i.e. reduction in budget deficit, increase in indirect taxes,adjusting the exchange rate and sliding down of subsidies, on employment, income distribution, per-capita income and inflation has been analyzed. It is found that the first policy instrument, i.e. decrease in budget deficit has affected employment, income distribution and inflation adversely. The second policy instrument of imposition of indirect tax negatively affected the employment, income distribution, per capita income and positively affected the inflation. The third policy instrument of SAP was adjustment of exchange rate. It is estimated that adjusting exchange rate has resulted into increased unemployment and inflation. The fourth policy instrument of shrink in subsidies augmented the unemployment, unequal distribution of income and inflation and dwindled the percapita income. It appears that SAP has adversely affected the major socioeconomic variables of the economy. Currently the government is considering for loan from IMF, so it is proposed to avoid such type of policy directives from IMF.Structural Adjustment Program, Budget deficit, Indirect taxes, Exchange rate, Subsidies, Employment, Income distribution, Per-capita income, Inflation,Pakistan

Pituitary stalk interruption syndrome presenting in a euthyroid adult with short stature

Pituitary stalk interruption syndrome (PSIS) is a distinct and rare clinical entity responsible for congenital hypopituitarism resulting in deficiency of pituitary hormones with deficiency of the growth hormone (100%) and gonadotropins (97.2%) being its most common presentation at the time of hospital encounter (Wang et al., 2015). Isolated sparing of thyroid-stimulating hormone (TSH) with deficiency of the remaining anterior pituitary hormones may be present in PSIS, as is true in our case. Therefore, it should be kept in mind at the time of examination in suspected cases of PSIS

Vascular Surprises in Calot’s Triangle during Laproscopic Choleystectomy

Background: To identify the vascular anomalies,variations of Calot’s triangle during laparoscopic cholecystectomy  Methods:  In this prospective observational study one thousand patients with a diagnosis of cholithiasis were included. Exclusion criteria were patients younger than 12 years and older than 80 year.  Calot’s triangle dissection was done meticulously.Cystic artery and hepatic artery anomalies and variations were observed and analyzed on SPSS 21.   Results: The age varied from 12 to 80 years. On the basis of distributional variation the cystic artery was single in 90% cases, branched in 7% cases and absent in 3% cases. On positional variations the cystic artery was superomedial to the cystic duct in 85% cases, anterior in 7% cases, and posterior in 3% cases and low lying in 5% of the cases. On the basis of length variation results showed that 80% cases had a normal cystic artery .A short cystic artery was found in 5% cases and a long cystic artery was present in 5%. Other arterial variations are of hepatic artery i.eMoynihan’s Hump (3%) and right hepatic artery present in Calots triangle in 5% Conclusions:  For the safety of laparoscopic cholecystectomy one should be well aware of the anatomical variations of the cystic and hepatic arter

Pattern of Presentation of Spinal Dysraphism: A Study of 72 Patients in Hayatabad Medical Complex Peshawar, Pakistan

Objective:  To review the pattern of presentation and current understanding of patients with spinal dysraphism in our local population. Material and Methods:  Cases of spinal dysraphism of any gender and age were admitted via OPD, emergency or referred from another department were included in the study. Information on demographics, developmental history, presenting symptoms , presence/absence of back swelling, hairy patches, a nevus, dimple, an appendage/ skin tag, lower limb function, sensory/ motor deficit, bowel and bladder dysfunction were recorded. MRI spine was done in all patients to know the exact diagnosis. Results:  Out of 72 cases, 52 (72.2%) presented with spina bifida Aperta (spina bifida cystica) while 20 (27.7%) with spina bifida occulta. Total 53 (73.6%) patients presented at the age of 0 – 1 years. 41 (56.9%) of the patient presented with visible sac, 35 (48.6%) swelling over the back, in 5 (6.9%) of patient have hairy patch and dermal sinus each, while 28 (38.8%) patients have neurological deficit. Most common type of spinal dysraphism was myelomeningocele 45 (62.5%). Postoperative course of patients with spinal dysraphism was found to be uneventful in 56 (77.7%), wound infection was seen in 11 (15.2%), deterioration of neurological status in 3 (4.16%) of cases. Conclusion:  Spinal dysraphism is not an uncommon condition in our local population its clinical presentation and features are in line with internationally reported literature. Our population is least aware of the adverse neurological outcomes of the condition and face difficulties to access the adequate healthcare for spinal dysraphism

The nexus between external debt, corruption and economic growth: evidence from five SSA countries

Purpose: The purpose of this paper is to examine the impact of external debt and corruption on economic growth in the selected five Sub-Saharan African (SSA) countries, from 1990 to 2015. Design/methodology/approach: Panel unit root and panel cointegration tests are employed to test for stationarity of the series and the long-run relationship, respectively. Fully modified OLS and dynamic OLS techniques are also employed to examine the long-run coefficients of the variables of the model, as well as panel Granger causality test, in order to examine the direction of causality among the variables. Findings: The results indicate that there is a negative relationship between external debt and economic growth, as well as a bi-directional causality between the two variables. The findings also indicate a positive relationship between corruption and economic growth, as well as a uni-directional causality running from economic growth through corruption. Research limitations/implications: The study recommends that the governments of the selected countries should address the menace of rising external debt through the adoption of other sources of capital for investment. Such include more openness of the economy for more capital, by easing restrictions on genuine imports and exports of valuable goods and services. It also suggests that the issue of corruption be tackled head-on, by such penalties that tend to make corruption less attractive. Originality/value: While the relationship between economic growth and external debt, on the one hand, and corruption and economic growth, on the other hand, have received considerable attentions, the trio of external debt, corruption and economic growth have not been found combined in a model, to the best of the authors’ knowledge. Also, the countries under consideration, who jointly account for about 47 percent of the entire SSA countries’ stock of external debt, have not been jointly found in any recent panel studies involving the selected variables