Moving Forward from the Arab Spring: Predicting the Level of Democracy in a Nation Post-Revolution

The Arab Spring consisted of a series of revolutions throughout the Arab world that attempted to remove dictatorial powers and institute democratic reform. However, the events after the Arab Spring beg the question of whether these nations will achieve their intended ends. Various factors have been identified to affect the level of democracy in nation including income levels, colonization history, and income inequality, among others. However, recent literature focuses on the role that cultural values play in affecting the development of political institutions. Cultural values play an interesting role during political disequilibrium. Revolutions represent the breakdown of formal institutions. During this time, prior research finds that people use informal institutions (culture) to guide their decision making. The level of democracy after a revolution should be highly affected by the cultural values on the people within a nation. Using an OLS and two stage least squares approach, I develop models to predict the level of democracy after a period of political disequilibrium. The PolityIV database marks points of disequilibrium using special measures based on foreign intervention, anarchy and political transition. The average level of democracy after disequilibrium can be predicted with a model using various explanatory variables including income per capita, colonization history, income inequality and culture. Using instruments for cultural values, we find that values such as individualism have a significant impact on the level of democracy after a period of political disequilibrium

Charge Trap Transistors (CTT): Turning Logic Transistors into Embedded Non-Volatile Memory for Advanced High-k/Metal Gate CMOS Technologies

While need for embedded non-volatile memory (eNVM) in modern computing systems continues to grow rapidly, the options have been limited due to integration and scaling challenges as well as operational voltage incompatibilities. Introduced in this work is a unique multi-time programmable memory (MTPM) solution for advanced high-k/metal-gate (HKMG) CMOS technologies which turns as-fabricated standard logic transistors into eNVM elements, without the need for any process adders or additional masks. These logic transistors, when employed as eNVM elements, are dubbed “Charge Trap Transistors” (CTTs). The fundamental device physics, principles of operation, and technological breakthroughs required for employing logic transistors as eNVM are presented. Implementation of CTT eNVM in 32 nm, 22 nm, 14 nm, and 7 nm production technologies has been realized and demonstrated in this work. The emerging memory technology landscape and the space that the CTT technology occupies therein are examined.The motivation behind this work is to develop an eNVM technology that is completely process/mask-free, multi-time programmable, operable at low/logic-compatible voltages, scalable, and secure. The CTT technology satisfies all of the aforementioned criteria. CTTs offer a data retention lifetime of > 10 years at 125 �C and an operation temperature range of -55�-125� C. Hardware results demonstrate an endurance of > 10^4 program/erase cycles which is more than adequate for most embedded applications. Hardware security enhancement, on-chip reconfigurable encryption, firmware, BIOS, chip ID, redundancy, repair at wafer and module test and in the field, performance tailoring, and chip configuration are a few of the applications of CTT eNVM. Moreover, the CTT array in its native (unprogrammed) state measures very well as an entropy source for potential PUF (Physically Unclonable Function) applications such as identification, authentication, anti-counterfeiting, secure boot, and cryptographic IP. In addition to the numerous digital applications, CTTs can also be utilized as an analog memory for applications like neuromorphic computing for machine learning (ML) and artificial intelligence (AI)

Bidirectional Learning in Recurrent Neural Networks Using Equilibrium Propagation

Neurobiologically-plausible learning algorithms for recurrent neural networks that can perform supervised learning are a neglected area of study. Equilibrium propagation is a recent synthesis of several ideas in biological and artificial neural network research that uses a continuous-time, energy-based neural model with a local learning rule. However, despite dealing with recurrent networks, equilibrium propagation has only been applied to discriminative categorization tasks. This thesis generalizes equilibrium propagation to bidirectional learning with asymmetric weights. Simultaneously learning the discriminative as well as generative transformations for a set of data points and their corresponding category labels, bidirectional equilibrium propagation utilizes recurrence and weight asymmetry to share related but non-identical representations within the network. Experiments on an artificial dataset demonstrate the ability to learn both transformations, as well as the ability for asymmetric-weight networks to generalize their discriminative training to the untrained generative task

Modelling of Self-Ignition in Spark-Ignition Engine Using Reduced Chemical Kinetics for Gasoline Surrogates

A numerical and experimental investigation in to the role of gasoline surrogates and their reduced chemical kinetic mechanisms in spark ignition (SI) engine knocking has been carried out. In order to predict autoignition of gasoline in a spark ignition engine three reduced chemical kinetic mechanisms have been coupled with quasi-dimensional thermodynamic modelling approach. The modelling was supported by measurements of the knocking tendencies of three fuels of very different compositions yet an equivalent Research Octane Number (RON) of 90 (ULG90, PRF90 and 71.5% by volume toluene blended with n-heptane) as well as iso-octane. The experimental knock onsets provided a benchmark for the chemical kinetic predictions of autoignition and also highlighted the limitations of characterisation of the knock resistance of a gasoline in terms of the Research and Motoring octane numbers and the role of these parameters in surrogate formulation. Two approaches used to optimise the surrogate composition have been discussed and possible surrogates for ULG90 have been formulated and numerically studied. A discussion has also been made on the various surrogates from the literature which have been tested in shock tube and rapid compression machines for their autoignition times and are a source of chemical kinetic mechanism validation. The differences in the knock onsets of the tested fuels have been explained by modelling their reactivity using semi-detailed chemical kinetics. Through this work, the weaknesses and challenges of autoignition modelling in SI engines through gasoline surrogate chemical kinetics have been highlighted. Adequacy of a surrogate in simulating the autoignition behaviour of gasoline has also been investigated as it is more important for the surrogate to have the same reactivity as the gasoline at all engine relevant p−T conditions than having the same RON and Motored Octane Number (MON)

Pre-anaesthetic assessment of intracranial pressure using optic nerve sheath diameter in patients scheduled for elective tumour craniotomy

Background: The objective of study was to determine the pre-anaesthetic status of intracranial pressure (ICP), using ultrasonographic measurement of optic nerve sheath diameter (ONSD) inpatient scheduled for elective tumour craniotomy. The secondary objective was to compare the diagnostic accuracy of ONSD guided rise in ICP with clinical and radiographic parameters. This is prospective observational study, conducted at single neurosurgical theatre of The Aga Khan University over a period of one year.Methods: After getting ethical approval and informed consent patient fulfilling inclusion criteria and planned for elective tumour craniotomy were enrolled in study. The clinical and radiographic signs predicting the status of ICP were recorded. The ultrasonographic measurement of ONSD was done using liner array probe. Value more than 5 mm was considered as abnormal.Results: Total 26 cases were enrolled. Seventy percent patients showed rise in ICP based on clinical parameters, while 65% diagnosed to have raised ICP on the basis of radiographic findings. The ultrasonographic measurement of ONSD predicted this rise in 61% of cases. The diagnostic accuracy of ONSD in detecting raised ICP in comparison to clinical and radiographic evidence was 87.5% respectively.Conclusions: The ultrasonographic-guided ONSD was used successfully for predicting the status of ICP in pre-induction phase of anaesthesia. It also showed good correlation in diagnosing rise in ICP as compared to clinical and radiographic parameters, which indicates that test can be used reliably in preoperative period for patients planned for tumour craniotomy

Transcriptomics studies under water-deficit stress: towards genetic improvement of Bambara groundnut (Vigna subterranea (L.) Verdc.)

With the world population estimated to be nine billion by 2050, the need to exploit plant genetic diversity in order to increase and diversify global food supply, and minimise the over-reliance for food on a few staple crops is of the utmost importance to address food security challenges. Bambara groundnut (Vigna subterranea (L) Verdc.), is an underutilised legume indigenous to Africa, rich in carbohydrates, with reasonable amounts of protein. It is known to be drought tolerant, able to grow on marginal lands where other major crops cannot with minimal rainfall (<700 mm) and no chemical inputs. The present study aimed to investigate and evaluate transcriptomic changes in two bambara groundnut genotypes; DipC and TN (Tiga Nicuru), derived from landraces, in response to drought stress using microarray XSpecies and next generation RNA sequencing approaches by utilising data, resources and approaches derived from major crops and model plants. Crop improvement for abiotic stress tolerance and increasing/stabilising yield have been difficult to achieve due to the complex nature of these stresses, and the genotype x environment interaction (GxE). Using bambara groundnut as an exemplar species this study also highlights how a number of recent technologies and approaches used for major crop research, can be translated for use in the research of minor crops for a better understanding of the genetics governing drought traits. To investigate the drought tolerance of bambara groundnut, microarray XSpecies and next generation RNA sequencing (RNA-seq) analysis was completed on leaf tissue from DipC and TN under drought and control (irrigation) conditions at different developmental stages (vegetative, reproductive and pod development). This is the first drought experiment reported in bambara groundnut employing the RNA-seq approach. Both investigation of mild (microarray XSpecies) and relatively severe (RNA-seq) drought stress for the DipC and TN genotypes, adapted to similar environmental conditions, provided initial evidence that the two genotypes used different sets of genes to achieve drought response traits (including; ABA synthesis, hormone signaling, osmotic adjustment, accumulation of antioxidants, lignin synthesis, down-regulation of photosynthesis related genes, carbohydrate metabolism, cell-wall modification and transporters). Hence, both genotypes may have adapted in different ways to enable them to grow in the semi-arid conditions, suggesting that there may be more than a single way to achieve resilience in the face of drought stress. The key enzymes involved in metabolic pathways, such as carbohydrate metabolism, redox homeostasis, lipid metabolism, photosynthesis, generation of precursor metabolites/energy, and cell wall component biogenesis were affected by drought stress in both genotypes. XSpecies microarray experiment identified several differentially expressed genes (DEG) in each genotype and the four potential drought candidate genes (PAL1, Beta-fructofuranosidase, COMT, UBC-2) identified were validated utilising quantitative reverse transcriptase PCR (qRT-PCR). In addition, both drought experiments (mild and severe) also showed that the two genotypes expressed a number of genes of what are classically considered to be ‘drought-response’ genes even under the control condition. These results suggest that high expression of drought-response genes even under control conditions in both genotypes may lead to greater root growth and other avoidance traits which prime the plant for future dry periods, hence preparing for drought conditions. Morphological differences and the rapid reduction in photosynthesis, stomatal conductance and transpiration observed in both genotypes under drought stress provides a platform to link these physiological data with gene expression data. The observed physiological responses (i.e reduction in stomatal conductance and photosynthesis) under drought stress were backed up by high expression of genes related to stomatal closure via ABA signaling and down-regulation of photosynthesis-associated genes. A selection of genes chosen from microarray XSpecies and RNA-seq experiments were further used to identify their approximate chromosomal location in bambara groundnut using a cross-species approach. A total of 4 genes (HOX, AUX_IAA, acid phosphatase and dehydrin) were found to be near or within the confidence intervals of the QTLs underlying two drought traits (stomatal density/leaf area and CID). The initial results suggest that some of the locations of genes identified in XSpecies microarray and RNA-seq experiments could underlie QTL involved in controlling drought traits in bambara groundnut. These data provide the basis for drought trait improvement in bambara groundnut, which will facilitate functional genomics studies. Analysis of this dataset have suggested that both genotypes are primed to respond to drought stress and have adapted in different ways to achieve drought tolerance. This will help in understanding the mechanisms underlying the ability of crops to produce viable yields under drought conditions. Future work should verify whether the identified genes are associated with the trait of interest