From Entropic Dynamics to Quantum Theory

Non-relativistic quantum theory is derived from information codified into an appropriate statistical model. The basic assumption is that there is an irreducible uncertainty in the location of particles: positions constitute a configuration space and the corresponding probability distributions constitute a statistical manifold. The dynamics follows from a principle of inference, the method of Maximum Entropy. The concept of time is introduced as a convenient way to keep track of change. A welcome feature is that the entropic dynamics notion of time incorporates a natural distinction between past and future. The statistical manifold is assumed to be a dynamical entity: its curved and evolving geometry determines the evolution of the particles which, in their turn, react back and determine the evolution of the geometry. Imposing that the dynamics conserve energy leads to the Schroedinger equation and to a natural explanation of its linearity, its unitarity, and of the role of complex numbers. The phase of the wave function is explained as a feature of purely statistical origin. There is a quantum analogue to the gravitational equivalence principle.Comment: Extended and corrected version of a paper presented at MaxEnt 2009, the 29th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (July 5-10, 2009, Oxford, Mississippi, USA). In version v3 I corrected a mistake and considerably simplified the argument. The overall conclusions remain unchange

Casimir Energy of a Relativistic Perfect Fluid Confined to a D-dimensional Hypercube

Compact formulas are obtained for the Casimir energy of a relativistic perfect fluid confined to a $D$-dimensional hypercube with von Neumann or Dirichlet boundary conditions. The formulas are conveniently expressed as a finite sum of the well-known gamma and Riemann zeta functions. Emphasis is placed on the mathematical technique used to extract the Casimir energy from a $D$-dimensional infinite sum regularized with an exponential cut-off. Numerical calculations show that initially the Dirichlet energy decreases rapidly in magnitude and oscillates in sign, being positive for even $D$ and negative for odd $D$. This oscillating pattern stops abruptly at the critical dimension of D=36 after which the energy remains negative and the magnitude increases. We show that numerical calculations performed with 16-digit precision are inaccurate at higher values of $D$.Comment: 20 pages, 4 figure

EVALUATING AND CREATING GENOMIC TOOLS FOR CASSAVA BREEDING

The genetic improvement of Manihot esculenta, or cassava, has historically been slow, largely because its biology renders traditional breeding techniques inefficient and because of little interest from the private sector. The goal of the Next Generation Cassava Breeding project (NEXTGEN) is to assist breeding institutions in Nigeria, Uganda, and Tanzania with increasing the rate of genetic improvement of cassava through implementation of genomic selection (GS). The three chapters of my thesis outline my work and involvement with the NEXTGEN project. The first chapter details our investigation of two questions: 1) can we use existing imputation methods developed by the human genetics community to impute missing genotypes in datasets derived from non-human species and 2) are these methods, which were developed and optimized to impute ascertained variants, amenable for imputation of missing genotypes at next-generation sequencing (NGS)-derived variants? In the second chapter, we introduce a statistical method, BIGRED (Bayes Inferred Genotype Replicate Error Detector), for detecting mislabeled and contaminated samples using shallow-depth sequence data. BIGRED addresses key limitations of existing approaches and produced highly accurate results in simulation experiments. In the third chapter, we outline how we used the multi-generational pedigree and genotyping-by-sequencing (GBS) data from the International Institute of Tropical Agriculture (IITA) to characterize the recombination landscape across the 18 chromosomes of cassava. We detected SNP intervals containing crossover events using SHAPEIT2 and duoHMM, constructed a genetic map using these intervals, compared it to an existing map constructed by the International Cassava Genetic Map Consortium (ICGMC), and constructed sex-specific genetic maps to see if cassava displays sexual dimorphism in crossover distribution and frequency

The function of Shp2 tyrosine phosphatase in the dispersal of acetylcholine receptor clusters

<p>Abstract</p> <p>Background</p> <p>A crucial event in the development of the vertebrate neuromuscular junction (NMJ) is the postsynaptic enrichment of muscle acetylcholine (ACh) receptors (AChRs). This process involves two distinct steps: the local clustering of AChRs at synapses, which depends on the activation of the muscle-specific receptor tyrosine kinase MuSK by neural agrin, and the global dispersal of aneural or "pre-patterned" AChR aggregates, which is triggered by ACh or by synaptogenic stimuli. We and others have previously shown that tyrosine phosphatases, such as the SH2 domain-containing phosphatase Shp2, regulate AChR cluster formation in muscle cells, and that tyrosine phosphatases also mediate the dispersal of pre-patterned AChR clusters by synaptogenic stimuli, although the specific phosphatases involved in this latter step remain unknown.</p> <p>Results</p> <p>Using an assay system that allows AChR cluster assembly and disassembly to be studied separately and quantitatively, we describe a previously unrecognized role of the tyrosine phosphatase Shp2 in AChR cluster disassembly. Shp2 was robustly expressed in embryonic Xenopus muscle in vivo and in cultured myotomal muscle cells, and treatment of the muscle cultures with an inhibitor of Shp2 (NSC-87877) blocked the dispersal of pre-patterned AChR clusters by synaptogenic stimuli. In contrast, over-expression in muscle cells of either wild-type or constitutively active Shp2 accelerated cluster dispersal. Significantly, forced expression in muscle of the Shp2-activator SIRPα1 (signal regulatory protein α1) also enhanced the disassembly of AChR clusters, whereas the expression of a truncated SIRPα1 mutant that suppresses Shp2 signaling inhibited cluster disassembly.</p> <p>Conclusion</p> <p>Our results suggest that Shp2 activation by synaptogenic stimuli, through signaling intermediates such as SIRPα1, promotes the dispersal of pre-patterned AChR clusters to facilitate the selective accumulation of AChRs at developing NMJs.</p

Towards Understanding the Effect of Pretraining Label Granularity

In this paper, we study how pretraining label granularity affects the generalization of deep neural networks in image classification tasks. We focus on the "fine-to-coarse" transfer learning setting where the pretraining label is more fine-grained than that of the target problem. We experiment with this method using the label hierarchy of iNaturalist 2021, and observe a 8.76% relative improvement of the error rate over the baseline. We find the following conditions are key for the improvement: 1) the pretraining dataset has a strong and meaningful label hierarchy, 2) its label function strongly aligns with that of the target task, and most importantly, 3) an appropriate level of pretraining label granularity is chosen. The importance of pretraining label granularity is further corroborated by our transfer learning experiments on ImageNet. Most notably, we show that pretraining at the leaf labels of ImageNet21k produces better transfer results on ImageNet1k than pretraining at other coarser granularity levels, which supports the common practice. Theoretically, through an analysis on a two-layer convolutional ReLU network, we prove that: 1) models trained on coarse-grained labels only respond strongly to the common or "easy-to-learn" features; 2) with the dataset satisfying the right conditions, fine-grained pretraining encourages the model to also learn rarer or "harder-to-learn" features well, thus improving the model's generalization

A Facile Method for Separation of the Cryptic Methionine Sulfoxide Diastereomers, Structural Assignment and DFT Analysis

Methionine (Met) oxidation is an important biological redox node, with hundreds if not thousands of protein targets. The process yields methionine oxide (MetO). It renders the sulfur chiral, producing two distinct, diastereomerically related products. Despite the biological significance of Met oxidation, a reliable protocol to separate the resultant MetO diastereomers is currently lacking. This hampers our ability to make peptides and proteins that contain stereochemically defined MetO to then study their structural and functional properties. We have developed a facile method that uses supercritical CO₂ chromatography and allows obtaining both diastereomers in purities exceeding 99 %. ¹H NMR spectra were correlated with X‐ray structural information. The stereochemical interconversion barrier at sulfur was calculated as 45.2 kcal mol⁻¹, highlighting the remarkable stereochemical stability of MetO sulfur chirality. Our protocol should open the road to synthesis and study of a wide variety of stereochemically defined MetO‐containing proteins and peptides

Rapid Scale-Up of Antiretroviral Treatment in Ethiopia: Successes and System-Wide Effects

Yibeltal Assefa and colleagues describe the successes and challenges of the scale-up of antiretroviral treatment across Ethiopia, including its impact on other health programs and the country's human resources for health

Theta lifts of Bianchi modular forms and applications to paramodularity

We explain how the work of Johnson-Leung and Roberts on lifting Hilbert modular forms for real quadratic fields to Siegel modular forms can be adapted to imaginary quadratic fields. For this, we use archimedean results from Harris, Soudry and Taylor and replace the global arguments of Roberts by the non-vanishing result of Takeda. As an application of our lifting result, we exhibit an abelian surface B defined over Q, which is not a restriction of scalars of an elliptic curve and satisfies the paramodularity Conjecture of Brumer and Kramer