Spatio-temporal Deep Learning Architectures for Data-Driven Learning of Brain’s Network Connectivity

Brain disorders are often linked to disruptions in the dynamics of the brain\u27s intrinsic functional networks. It is crucial to identify these networks and determine disruptions in their interactions to classify, understand, and possibly cure brain disorders. Brain\u27s network interactions are commonly assessed via functional (network)\ connectivity, captured as an undirected matrix of Pearson correlation coefficients. Functional connectivity can represent static and dynamic relations. However, often these are modeled using a fixed choice for the data window. Alternatively, deep learning models may flexibly learn various representations from the same data based on the model architecture and the training task. The representations produced by deep learning models are often difficult to interpret and require additional posthoc methods, e.g., saliency maps. Also, deep learning models typically require many input samples to learn features and perform the downstream task well. This dissertation introduces deep learning architectures that work on functional MRI data to estimate disorder-specific brain network connectivity and provide high classification accuracy in discriminating controls and patients. To handle the relatively low number of labeled subjects in the field of neuroimaging, this research proposes deep learning architectures that leverage self-supervised pre-training to increase downstream classification. To increase the interpretability and avoid using a posthoc method, deep learning architectures are proposed that expose a directed graph layer representing the model\u27s learning about relevant brain connectivity. The proposed models estimate task-specific directed connectivity matrices for each subject using the same data but training different models on their own discriminative tasks. The proposed architectures are tested with multiple neuroimaging datasets to discriminate controls and patients with schizophrenia, autism, and dementia, as well as age and gender prediction. The proposed approach reveals that differences in connectivity among sensorimotor networks relative to default-mode networks are an essential indicator of dementia and gender. Dysconnectivity between networks, especially sensorimotor and visual, is linked with schizophrenic patients. However, schizophrenic patients show increased intra-network default-mode connectivity compared to healthy controls. Sensorimotor connectivity is vital for both dementia and schizophrenia prediction, but the differences are in inter and intra-network connectivity

Deep Learning for Medical Imaging in a Biased Environment

Deep learning (DL) based applications have successfully solved numerous problems in machine perception. In radiology, DL-based image analysis systems are rapidly evolving and show progress in guiding treatment decisions, diagnosing, localizing disease on medical images, and improving radiologists\u27 workflow. However, many DL-based radiological systems fail to generalize when deployed in new hospital settings, and the causes of these failures are not always clear. Although significant effort continues to be invested in applying DL algorithms to radiological data, many open questions and issues that arise from incomplete datasets remain. To bridge the gap, we first review the current state of artificial intelligence applied to radiology data, followed by juxtaposing the use of classical computer vision features (i.e., hand-crafted features) with the recent advances caused by deep learning. However, using DL is not an excuse for a lack of rigorous study design, which we demonstrate by proposing sanity tests that determine when a DL system is right for the wrong reasons. Having established the appropriate way to assess DL systems, we then turn to improve their efficacy and generalizability by leveraging prior information about human physiology and data derived from dual energy computed tomography scans. In this dissertation, we address the gaps in the radiology literature by introducing new tools, testing strategies, and methods to mitigate the influence of dataset biases

Exchange Rate Determination in Pakistan: A Simultaneous Equation Model

In recent years the gap between real exchange rate (RER) and nominal exchange rate (NER) has widened in Pakistan. A proper understanding of the determinants of real exchange rate can be extremely useful for the management of current account deficit. The results of this study show that the Simultaneous Equation Model gives better results than the Single Equation Model. The estimated coefficients reveal that changes in both monetary and real sector variables affect the equilibrium path of RER. The distinction between traded and non-traded goods can also help in proper real exchange rate management.

National Finance Commission Awards in Pakistan : A Historical Perspective

This study explores the evolution of fiscal resource distribution in Pakistan. Pakistan is a federation comprising four provinces, federallyadministered areas, and the Islamabad Capital Territory. Being a central type of government, most of the revenues are collected by the centre and then redistributed vertically between the federal and the provincial governments, and horizontally among the provinces. Provinces then also redistribute revenues among lower tiers of the government, through a revenue-sharing formula. A thorough look at the history indicates that this process has been complex and has a far-reaching impact. A less systematic approach has been adopted to decentralise the financial matters. Over time, the divisible pool has expanded due to heavy reliance on indirect taxes as well as improvement in the collection. Population is the sole distribution criteria, adopted in all NFC awards from the divisible pool. This has raised friction among the provinces, necessitating inclusion of other potential variables evolved from international best practices. In addition to that, absence of technical experts and permanency of the NFC is another impediment. The NFC is supposed to provide the framework for amicable distribution of resources between the federal and the provincial governments for the joint goal of development and prosperity.NFC, Pakistan, fiscal federalism, Rule and Discretion, political economy, Population, Subventions, Doing the Business of Government

National Finance Commission Awards in Pakistan: A Historical Perspective

This study explores the evolution of fiscal resource distribution in Pakistan. Pakistan is a federation comprising four provinces, federally-administered areas, and the Islamabad Capital Territory. Being a central type of government, most of the revenues are collected by the centre and then redistributed vertically between the federal and the provincial governments, and horizontally among the provinces. Provinces then also redistribute revenues among lower tiers of the government, through a revenue-sharing formula. A thorough look at the history indicates that this process has been complex and has a far-reaching impact. A less systematic approach has been adopted to decentralise the financial matters. Over time, the divisible pool has expanded due to heavy reliance on indirect taxes as well as improvement in the collection. Population is the sole distribution criteria, adopted in all NFC awards from the divisible pool. This has raised friction among the provinces, necessitating inclusion of other potential variables evolved from international best practices. In addition to that, absence of technical experts and permanency of the NFC is another impediment. The NFC is supposed to provide the framework for amicable distribution of resources between the federal and the provincial governments for the joint goal of development and prosperity.NFC, Pakistan, Fiscal Federalism, Rule and Discretion, Political Economy, Population, Subventions, Doing the Business of Government

National Finance Commission Awards in Pakistan: A Historical Perspective

This study explores the evolution of fiscal resource distribution in Pakistan. Pakistan is a federation comprising four provinces, federallyadministered areas, and the Islamabad Capital Territory. Being a central type of government, most of the revenues are collected by the centre and then redistributed vertically between the federal and the provincial governments, and horizontally among the provinces. Provinces then also redistribute revenues among lower tiers of the government, through a revenue-sharing formula. A thorough look at the history indicates that this process has been complex and has a far-reaching impact. A less systematic approach has been adopted to decentralise the financial matters. Over time, the divisible pool has expanded due to heavy reliance on indirect taxes as well as improvement in the collection. Population is the sole distribution criteria, adopted in all NFC awards from the divisible pool. This has raised friction among the provinces, necessitating inclusion of other potential variables evolved from international best practices. In addition to that, absence of technical experts and permanency of the NFC is another impediment. The NFC is supposed to provide the framework for amicable distribution of resources between the federal and the provincial governments for the joint goal of development and prosperity.NFC; Pakistan; Fiscal Federalism; Rule and Discretion; Political Economy; Population; Subventions; Doing the Business of Government

Public Waqf in Punjab Province Pakistan: Challenges and Opportunities

The aim of this study is to explore the challenges and opportunities in Public Waqf in Punjab. Punjab is the biggest province of Pakistan regarding population. The public waqf in Punjab is managed and administered by Auqaf Organization Punjab. The organization is autonomous body under the provincial government. This organization in Punjab province owns biggest portion of Public waqf of the country. Public waqf in Punjab includes: cash waqf, commercial and agriculture properties, welfare institutions, shrines, mosques, graveyards etc. This study has been actualised by qualitative research method, observations, primary and secondary data and internet explorations. Furthermore, the investigation of problems and exploration of opportunities are backed by practical knowledge. This research will prove to be Beneficial for the public waqf in Punjab. The findings of the study based on challenges faced by public waqf in Punjab province of Pakistan and as well explore the opportunities that can be helpful for the development and improvement of public waqf. Auqaf in Punjab facing various challenges that affect the potential of the waqf assets and causing inefficiency. For that reason, the study findings portray the huge waqf properties are underdeveloped.The study discussed in many ways potential opportunities that can counter and reduce these challenges. This study diagnosis the problems and offers solutions to these problems.This study provides primary and practical experience from the practitioners and waqf experts who provide a framework for similar type of study in the waqf management  

Exchange Rate Determination in Pakistan: A Simultaneous Equation Model

In recent years the gap between real exchange rate (RER) and nominal exchange rate (NER) has widened in Pakistan. A proper understanding of the determinants of real exchange rate can be extremely useful for the management of current account deficit. The results of this study show that the Simultaneous Equation Model gives better results than the Single Equation Model. The estimated coefficients reveal that changes in both monetary and real sector variables affect the equilibrium path of RER. The distinction between traded and non-traded goods can also help in proper real exchange rate management

Rooftop Rain Water Harvesting Technology and Women Time Allocation in District Bagh and Battagram Pakistan.

Water is essential requirement of life and its accessibility is the basic right of all human beings. Safe drinking water is an essential component of primary health. It plays a vital role in livelihood, food security and sustainable development. Rooftop Rainwater Harvesting Technology (RRWH) is a best alternative approach to conserve and supply water. Especially, it is crucial in seismically sensitive, geographically uneven, and countryside areas. A large majority of population in Pakistan is living in areas, where access to safe drinking water is very serious issue. In these areas most vulnerable segment of population is women because they are the ones who have to fetch water from far flung areas for their daily consumption. In order to resolve the issue of water in Pakistan, a number of public and private agencies are working in this field. Different approaches, techniques, and practices are being adopted to address this issue. Present study evaluates the impact of RRWH technology with special reference to women time allocation in Bagh and Battagram districts of Pakistan. Analyses were carried out using Ordinary Least Square (OLS) technique to quantify the results. The results reveal that RRWH technology is viable, time saving, women friendly, and sustainable source of safe drinking water supply, especially in seismically sensitive, geographically uneven, and countryside areas of Pakistan. JEL classification: O13, Q25, Q56, Q58, R28 Keywords: Rooftop Rain Water Harvesting: Safe Drinking Water, Seismically Sensitive, Geographically Uneven, and Countryside: Women, AJK and KP, Pakistan