Simulating Scattering of Composite Particles

We develop a non-perturbative approach to simulating scattering on classical and quantum computers, in which the initial and final states contain a fixed number of composite particles. The construction is designed to mimic a particle collision, wherein two composite particles are brought in contact. The initial states are assembled via consecutive application of operators creating eigenstates of the interacting theory from vacuum. These operators are defined with the aid of the M{\o}ller wave operator, which can be constructed using such methods as adiabatic state preparation or double commutator flow equation. The approach is well-suited for studying strongly coupled systems in both relativistic and non-relativistic settings. For relativistic systems, we employ the language of light-front quantization, which has been previously used for studying the properties of individual bound states, as well as for simulating their scattering in external fields, and is now adopted to the studies of scattering of bound state systems. For simulations on classical computers, we describe an algorithm for calculating exact (in the sense of a given discretized theory) scattering probabilities, which has cost (memory and time) exponential in momentum grid size. Such calculations may be interesting in their own right and can be used for benchmarking results of a quantum simulation algorithm, which is the main application of the developed framework. We illustrate our ideas with an application to the $\phi^4$ theory in $1+1\rm D$.Comment: 32 pages, 10 figures, 3 table

Error management theory and the adaptive significance of transgenerational maternal‐stress effects on offspring phenotype

It is well established that circulating maternal stress hormones (glucocorticoids, GCs) can alter offspring phenotype. There is also a growing body of empirical work, within ecology and evolution, indicating that maternal GCs link the environment experienced by the mother during gestation with changes in offspring phenotype. These changes are considered to be adaptive if the maternal environment matches the offspring’s environment and maladaptive if it does not. While these ideas are conceptually sound, we lack a testable framework that can be used to investigate the fitness costs and benefits of altered offspring phenotypes across relevant future environments. We present error management theory as the foundation for a framework that can be used to assess the adaptive potential of maternal stress hormones on offspring phenotype across relevant postnatal scenarios. To encourage rigorous testing of our framework, we provide field‐testable hypotheses regarding the potential adaptive role of maternal stress across a diverse array of taxa and life histories, as well as suggestions regarding how our framework might provide insight into past, present, and future research. This perspective provides an informed lens through which to design and interpret experiments on the effects of maternal stress, provides a framework for predicting and testing variation in maternal stress across and within taxa, and also highlights how rapid environmental change that induces maternal stress may lead to evolutionary traps.This article provides a quantitative framework as a means of generating field‐testable hypotheses regarding the adaptive potential of maternal stress under different scenario combinations. By providing a mechanistic basis for examining the adaptive potential of maternal stress effects, our overall aim is not only to provide a means for explaining patterns and testing new hypotheses, but to catalyze the study of maternal stress effects under this framework across a diversity of species, life histories, and environments.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/145404/1/ece34074_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/145404/2/ece34074.pd

Error management theory and the adaptive significance of transgenerational maternal-stress effects on offspring phenotype

It is well established that circulating maternal stress hormones (glucocorticoids, GCs) can alter offspring phenotype. There is also a growing body of empirical work, within ecology and evolution, indicating that maternal GCs link the environment experienced by the mother during gestation with changes in offspring phenotype. These changes are considered to be adaptive if the maternal environment matches the offspring\u27s environment and maladaptive if it does not. While these ideas are conceptually sound, we lack a testable framework that can be used to investigate the fitness costs and benefits of altered offspring phenotypes across relevant future environments. We present error management theory as the foundation for a framework that can be used to assess the adaptive potential of maternal stress hormones on offspring phenotype across relevant postnatal scenarios. To encourage rigorous testing of our framework, we provide field-testable hypotheses regarding the potential adaptive role of maternal stress across a diverse array of taxa and life histories, as well as suggestions regarding how our framework might provide insight into past, present, and future research. This perspective provides an informed lens through which to design and interpret experiments on the effects of maternal stress, provides a framework for predicting and testing variation in maternal stress across and within taxa, and also highlights how rapid environmental change that induces maternal stress may lead to evolutionary traps

Error management theory and the adaptive significance of transgenerational maternal-stress effects on offspring phenotype

It is well established that circulating maternal stress hormones (glucocorticoids, GCs) can alter offspring phenotype. There is also a growing body of empirical work, within ecology and evolution, indicating that maternal GCs link the environment experienced by the mother during gestation with changes in offspring phenotype. These changes are considered to be adaptive if the maternal environment matches the offspring\u27s environment and maladaptive if it does not. While these ideas are conceptually sound, we lack a testable framework that can be used to investigate the fitness costs and benefits of altered offspring phenotypes across relevant future environments. We present error management theory as the foundation for a framework that can be used to assess the adaptive potential of maternal stress hormones on offspring phenotype across relevant postnatal scenarios. To encourage rigorous testing of our framework, we provide field-testable hypotheses regarding the potential adaptive role of maternal stress across a diverse array of taxa and life histories, as well as suggestions regarding how our framework might provide insight into past, present, and future research. This perspective provides an informed lens through which to design and interpret experiments on the effects of maternal stress, provides a framework for predicting and testing variation in maternal stress across and within taxa, and also highlights how rapid environmental change that induces maternal stress may lead to evolutionary traps

Daily HIV pre-exposure prophylaxis (PrEP) with tenofovir disoproxil fumarate-emtricitabine reduced Streptococcus and increased Erysipelotrichaceae in rectal microbiota.

Daily PrEP is highly effective at preventing HIV-1 acquisition, but risks of long-term tenofovir disoproxil fumarate plus emtricitabine (TDF-FTC) include renal decline and bone mineral density decrease in addition to initial gastrointestinal side effects. We investigated the impact of TDF-FTC on the enteric microbiome using rectal swabs collected from healthy MSM before PrEP initiation and after 48 to 72 weeks of adherent PrEP use. The V4 region of the 16S ribosomal RNA gene sequencing showed that Streptococcus was significantly reduced from 12.0% to 1.2% (p = 0.036) and Erysipelotrichaceae family was significantly increased from 0.79% to 3.3% (p = 0.028) after 48-72 weeks of daily PrEP. Catenibacterium mitsuokai, Holdemanella biformis and Turicibacter sanguinis were increased within the Erysipelotrichaceae family and Streptococcus agalactiae, Streptococcus oralis, Streptococcus mitis were reduced. These changes were not associated with host factors including PrEP duration, age, race, tenofovir diphosphate blood level, any drug use and drug abuse, suggesting that the observed microbiome shifts were likely induced by daily PrEP use. Long-term PrEP resulted in increases of Catenibacterium mitsuokai and Holdemanella biformis, which have been associated with gut microbiome dysbiosis. Our observations can aid in characterizing PrEP's side effects, which is likely to improve PrEP adherence, and thus HIV-1 prevention

Prediction of Maximal Oxygen Consumption from Rating of Perceived Exertion (RPE) using a Modified Total-body Recumbent Stepper

International Journal of Exercise Science 8(4): 414-424, 2015. Exercise training is crucial to improve cardiovascular health and quality of life in people with spinal cord injuries (SCI). A key limitation is the lack of validated submaximal tests to evaluate and predict cardiovascular fitness in this population. The purpose of this study was to validate a submaximal test to predict maximal oxygen consumption for individuals with SCI. Ten able-bodied participants and two individuals with SCI completed a rating of perceived exertion (RPE)-based submaximal oxygen consumption test and a graded maximal oxygen consumption test on a NuStep T4 recumbent stepper. Prediction of VO2max from an RPE-based protocol is feasible and can produce reliable predicted VO2max values in the able bodied population. This study is a proof of concept to the implementation of a submaximal test protocol using a total body recumbent stepper to predict VO2max in able-bodied individuals. Additionally, this study shows evidence of feasibility of performing this test in SCI individuals

Static and Dynamic DNA Loops form AP-1-Bound Activation Hubs during Macrophage Development

The three-dimensional arrangement of the human genome comprises a complex network of structural and regulatory chromatin loops important for coordinating changes in transcription during human development. To better understand the mechanisms underlying context-specific 3D chromatin structure and transcription during cellular differentiation, we generated comprehensive in situ Hi-C maps of DNA loops during human monocyte-to-macrophage differentiation. We demonstrate that dynamic looping events are regulatory rather than structural in nature and uncover widespread coordination of dynamic enhancer activity at preformed and acquired DNA loops. Enhancer-bound loop formation and enhancer-activation of preformed loops represent two distinct modes of regulation that together form multi-loop activation hubs at key macrophage genes. Activation hubs connect 3.4 enhancers per promoter and exhibit a strong enrichment for Activator Protein 1 (AP-1) binding events, suggesting multi-loop activation hubs driven by cell-type specific transcription factors may represent an important class of regulatory chromatin structures for the spatiotemporal control of transcription

Uranium(III) coordination chemistry and oxidation in a flexible small-cavity macrocycle

U(III) complexes of the conformationally flexible, small-cavity macrocycle trans-calix[2]benzene[2]pyrrolide (L)2–, [U(L)X] (X = O-2,6-tBu2C6H3, N(SiMe3)2), have been synthesized from [U(L)BH4] and structurally characterized. These complexes show binding of the U(III) center in the bis(arene) pocket of the macrocycle, which flexes to accommodate the increase in the steric bulk of X, resulting in long U–X bonds to the ancillary ligands. Oxidation to the cationic U(IV) complex [U(L)X][B(C6F5)4] (X = BH4) results in ligand rearrangement to bind the smaller, harder cation in the bis(pyrrolide) pocket, in a conformation that has not been previously observed for (L)2–, with X located between the two ligand arene rings

Dynamic Modeling of Workforce Planning for Infrastructure Projects

Workforce planning (WP) for infrastructure projects provides a readily available pool of skilled labor that can deliver a nation’s societal needs. However, achieving a robust and reliable workforce prediction is a constant challenge, as a variety of variables and factors must be considered. Despite various forecasting techniques and approaches being developed, government’s worldwide continue to produce inaccurate forecasts and consequently fail to maintain the balanced workforce required to deliver infrastructure projects. To address this problem, a system dynamics (SD) model for the construction and civil engineering industry is developed, as traditional WP modeling approaches are static and unable to accommodate the changing complex dynamics that influence workforce supply and demand. The SD model is tested and used to formulate training policies that ensure workforce equilibrium and in turn, nurture sustainable infrastructure development