CSM-182 - Manchester Computer Architectures, 1948 - 1975

Because of changes in computer technology and terminology, it is often difficult for present-day observers to judge the significance of early digital computer projects. In this paper we follow some architectural themes of interest, as they evolved in the design of three innovative Manchester University computers: the Mark I, Atlas and MU5. Themes such as operand address-generation, instruction formats and memory-management are traced during the period 1948-75. These themes are illustrated by a set of normalised diagrams which may act as an aid to further study of original references

A Probabilistic Modeling Approach to CRISPR-Cas9

CRISPR-Cas, a particular type of microbial immune response system, has in recent years been modified to make precise changes to an organisms DNA. In the early 2000s scientists discovered through the study of Streptococcus pyogenes, that a unique CRISPR locus (Cas9) exhibited specific RNA-guided cleavage near short trinucleotide motifs (PAMs). Further research on Cas9 eventually led researchers to create methods that actively edit genomes through Cas9-dependent cleavage and to manipulate transcription of genes through engineered nuclease-deficient Cas9 (dCas9). These techniques have enabled new avenues for analyzing existing gene functions or engineering new ones, manipulating gene expression, gene therapy, and much more.While great strides have been made over the last decade, CRISPR is still prone to inaccuracies which often generate sub-optimal editing efficiency or off-target effects. The primary interest of this thesis is the investigation of targeting efficiency concerning changes in the guide RNA (gRNA) composition. While many different factors affect the ability with which a given gRNA can target a DNA sequence, we have focused our research primarily on the formation of the R-loop: the hybrid structure formed when the Cas9/dCas9:gRNA complex binds to a host DNA site.In our investigation, we have attempted to account for several experimental findings reported in the literature as influential for binding efficiency. These include position dependence, base pair composition dependence, and the effects of runs of consecutive mismatches. Using a Gambler’s Ruin Markov model to mimic the process of R-loop formation, we fit our model to experimental data and show that the match/mismatch configuration between the gRNA and the DNA target allows for accurate predictions of R-loop formation in bacteria

Population Genetics and Experiments in Metabolic Enzymes of Drosophila melanogaster

Control of metabolic flux, the flow of metabolites through a complex metabolic network, is of importance to understand how an organism is sensing, and responding to, nutrient changes in its environment. Metabolic flux control can be measured for, and a control coefficient assigned to, each enzyme in a pathway. Measuring metabolic flux control in multicellular organisms is complicated by the fact that nutrient sensing and metabolic flux control may vary by tissue type. Major effects should be detectable in genomic information, as enzymes with high control coefficients will exhibit genetic patterns of adaptation when the pathway is under selection pressure. I used genetic variation within and among populations of Drosophila melanogaster, as well as divergence between D. melanogaster and the closely related D. simulans, to identify candidate genes for experimental study. I then conducted experiments with candidate genes using tissue specific RNA interference knockdown, focusing on two enzymes comprising the glycerophosphate shuttle in the context of starvation resistance, adipokinetic hormone (AKH) signaling, the Drosophila analog of glucagon signaling, and Insulin/Insulin-like signaling. None of the genes that I studied had a significant effect on starvation resistance when knocked down in Insulin-like protein secreting cells. I found that glycerophosphate oxidase, but not glycerophosphate dehydrogenase, significantly increased the average time to death in starvation conditions when knocked down in AKH secreting cells. Because the glycerophosphate shuttle is important in transferring nicotinamide adenine dinucleotide equivalents between the cytosol and inner matrix of the mitochondrion, this result implicates the coupling of reduction-oxidation state with AKH signaling. | 99 page

Target-based Surrogates for Stochastic Optimization

We consider minimizing functions for which it is expensive to compute the (possibly stochastic) gradient. Such functions are prevalent in reinforcement learning, imitation learning and adversarial training. Our target optimization framework uses the (expensive) gradient computation to construct surrogate functions in a \emph{target space} (e.g. the logits output by a linear model for classification) that can be minimized efficiently. This allows for multiple parameter updates to the model, amortizing the cost of gradient computation. In the full-batch setting, we prove that our surrogate is a global upper-bound on the loss, and can be (locally) minimized using a black-box optimization algorithm. We prove that the resulting majorization-minimization algorithm ensures convergence to a stationary point of the loss. Next, we instantiate our framework in the stochastic setting and propose the $SSO$ algorithm, which can be viewed as projected stochastic gradient descent in the target space. This connection enables us to prove theoretical guarantees for $SSO$ when minimizing convex functions. Our framework allows the use of standard stochastic optimization algorithms to construct surrogates which can be minimized by any deterministic optimization method. To evaluate our framework, we consider a suite of supervised learning and imitation learning problems. Our experiments indicate the benefits of target optimization and the effectiveness of $SSO$

A global corporate census: publicly traded and close companies in 1910

In 1910 the world had almost half a million corporations, only one-hundredth of today's total. About one-fifth—with over half of corporate capital—were publicly tradable, higher portions than today. Most publicly quoted corporations traded in Europe and the British Empire, but most close (private) corporations operated in the US, which, until the 1940s, had more corporations per capita than anywhere else. The 83 countries surveyed here differed markedly in company numbers, corporate capital/GDP ratios, and average corporate size. Enclave economies—dominated by quoted (and often foreign-owned) companies—had the largest average sizes, while other nations had more varied mixes of large quoted corporations and close company small and medium enterprises

A Diffusion-Model of Joint Interactive Navigation

Simulation of autonomous vehicle systems requires that simulated traffic participants exhibit diverse and realistic behaviors. The use of prerecorded real-world traffic scenarios in simulation ensures realism but the rarity of safety critical events makes large scale collection of driving scenarios expensive. In this paper, we present DJINN - a diffusion based method of generating traffic scenarios. Our approach jointly diffuses the trajectories of all agents, conditioned on a flexible set of state observations from the past, present, or future. On popular trajectory forecasting datasets, we report state of the art performance on joint trajectory metrics. In addition, we demonstrate how DJINN flexibly enables direct test-time sampling from a variety of valuable conditional distributions including goal-based sampling, behavior-class sampling, and scenario editing.Comment: 10 pages, 4 figure

CSM-180 - An SQL Interface for the IFS/2 Knowledge-Baseserver: Release 2

A version of the IFS/2, known as the IFS/Q, has been designed to give direct support to SQL programs running on a host computer. This report gives detailed specifications of one external and two internal software and firmware interfaces which have been created for IFS/Q. Release 2 differs from Release 1 mainly in the Interface B details (see section 4). We have also tidied up the IFS/Q library procedures, which are described in a companion document - (see ref 9); for convenience this is included as Appendix B to this report

Video Killed the HD-Map: Predicting Driving Behavior Directly From Drone Images

The development of algorithms that learn behavioral driving models using human demonstrations has led to increasingly realistic simulations. In general, such models learn to jointly predict trajectories for all controlled agents by exploiting road context information such as drivable lanes obtained from manually annotated high-definition (HD) maps. Recent studies show that these models can greatly benefit from increasing the amount of human data available for training. However, the manual annotation of HD maps which is necessary for every new location puts a bottleneck on efficiently scaling up human traffic datasets. We propose a drone birdview image-based map (DBM) representation that requires minimal annotation and provides rich road context information. We evaluate multi-agent trajectory prediction using the DBM by incorporating it into a differentiable driving simulator as an image-texture-based differentiable rendering module. Our results demonstrate competitive multi-agent trajectory prediction performance when using our DBM representation as compared to models trained with rasterized HD maps