Quasiparticle spectrum of the cuprate BiSrCaCuO: Possible connection to the phase diagram

We previously introduced [T. Cren et al., Europhys. Lett. 52, 203 (2000)] an energy-dependant gap function, $\Delta(E)$, that fits the unusual shape of the quasiparticle (QP) spectrum for both BiSrCaCuO and YBaCuO. A simple anti-resonance in $\Delta(E)$ accounts for the pronounced QP peaks in the density of states, at an energy $\Delta_p$, and the dip feature at a higher energy, $E_{dip}$. Here we go a step further : our gap function is consistent with the ($T, p$) phase diagram, where $p$ is the carrier density. For large QP energies ($E >> \Delta_p$), the total spectral gap is $\Delta(E) \simeq \Delta_p + \Delta_\phi$, where $\Delta_\phi$ is tied to the condensation energy. From the available data, a simple $p$-dependance of $\Delta_p$ and $\Delta_\phi$ is found, in particular $\Delta_\phi(p) \simeq 2.3 k_B T_c(p)$. These two distinct energy scales of the superconducting state are interpreted by comparing with the normal and pseudogap states. The various forms of the QP density of states, as well as the spectral function $A(k,E)$, are discussed

Interactional Structure Applied to the Identification and Generation of Visual Interactive Behavior: Robots that (Usually) Follow the Rules

Peer reviewe

Contributions of the VitisGen2 project to grapevine breeding and genetics

The VitisGen projects (2011-2022) have improved the tools available for breeding new grapevine cultivars with regional adaptation, high quality, and disease resistance. VitisGen2 (the second project in the series) was a multi-state collaboration (USDA-Geneva, New York; University of California, Davis; USDA-Parlier, California; Cornell University; Missouri State University; University of Minnesota; South Dakota State University; Washington State University; North Dakota State University; and E&J Gallo, California) to develop improved genetic mapping technology; to identify useful DNA marker-trait associations; and to incorporate marker-assisted selection (MAS) into breeding programs. A novel genetic mapping platform (rhAmpSeq) now provides 2000 + markers that are transferable across the Vitis genus. rhAmpSeq has been used in California, New York, Missouri, and South Dakota to identify new QTL for powdery and downy mildew resistance. In addition, fruit/flower traits that would normally take years to phenotype have been associated with predictive markers accessible from seedling DNA (e.g. malate metabolism, anthocyanin acylation, bloom phenology and flower sex). Since 2011, the project has used MAS to screen thousands of grape seedlings from public breeding programs in the United States and has produced “Ren- Stack” public domain lines to enable simultaneous access to 4 or 6 powdery mildew resistance loci from single source genotypes. High-throughput phenotyping for powdery and downy mildew resistance has been revolutionized with the Blackbird automated-imaging system powered by artificial intelligence for image analysis. Affordable DNA sequencing along with phenotyping innovations are transforming grapevine breeding

A comparison of statistical emulation methodologies for multi-wave calibration of environmental models

Expensive computer codes, particularly those used simulating environmental or geological processes such as climate models, require calibration (sometimes called tuning). When calibrating expensive simulators using uncertainty quantification methods, it is usually necessary to use a statistical model called an emulator in place of the computer code when running the calibration algorithm. Though emulators based on Gaussian processes are typically many orders of magnitude faster to evaluate than the simulator they mimic, many applications have sought to speed up the computations by using regression-only emulators within the calculations instead, arguing that the extra sophistication brought using the Gaussian process is not worth the extra computational power. This was the case for the analysis that produced the UK climate projections in 2009. In this paper we compare the effectiveness of both emulation approaches upon a multi-wave calibration framework that is becoming popular in the climate modelling community called \history matching". We find that Gaussian processes offer significant benefits to the reduction of parametric uncertainty over regression-only approaches. We find that in a multi-wave experiment, a combination of regression-only emulators initially, followed by Gaussian process emulators for refocussing experiments can be nearly as effective as using Gaussian processes throughout for a fraction of the computational cost. We also discover a number of design and emulator-dependent features of the multi-wave history matching approach that can cause apparent, yet premature, convergence of our estimates of parametric uncertainty. We compare these approaches to calibration in idealised examples and apply it to a well-known geological reservoir mode

The impact of injecting networks on hepatitis C transmission and treatment in people who inject drugs

With the development of new highly efficacious direct acting antiviral treatments (DAAs) for hepatitis C (HCV), the concept of treatment as prevention is gaining credence. To date the majority of mathematical models assume perfect mixing with injectors having equal contact with all other injectors. This paper explores how using a networks based approach to treat people who inject drugs (PWID) with DAAs affects HCV prevalence. Method: Using observational data we parameterized an Exponential Random Graph Model containing 524 nodes. We simulated transmission of HCV through this network using a discrete time, stochastic transmission model. The effect of five treatment strategies on the prevalence of HCV was investigated; two of these strategies were 1) treat randomly selected nodes and 2) “treat your friends” where an individual is chosen at random for treatment and all their infected neighbours are treated. Results: As treatment coverage increases, HCV prevalence at 10 years reduces for both the high efficacy and low efficacy treatment. Within each set of parameters, the “treat your friends” strategy performed better than the random strategy being most marked for higher efficacy treatment. For example over 10 years of treating 25 per 1000 PWID, the prevalence drops from 50% to 40% for the random strategy, and to 33% for the “treat your friends” strategy (6.5% difference, 95% CI 5.1 – 8.1%). Discussion: “Treat your friends” is a feasible means of utilising network strategies to improve treatment efficiency. In an era of highly efficacious and highly tolerable treatment such an approach will benefit not just the individual but the community more broadly by reducing the prevalence of HCV amongst PWID

Skin, Thermal and Umbilical Cord Care Practices for Neonates in Southern, Rural Zambia: A Qualitative Study

Background: In Choma District, southern Zambia, the neonatal mortality rate is approximately 40 per 1000 live births and, although the rate is decreasing, many deliveries take place outside of formal facilities. Understanding local practices during the postnatal period is essential for optimizing newborn care programs. Methods: We conducted 36 in-depth interviews, five focus groups and eight observational sessions with recently-delivered women, traditional birth attendants, and clinic and hospital staff from three sites, focusing on skin, thermal and cord care practices for newborns in the home. Results: Newborns were generally kept warm by application of hats and layers of clothing. While thermal protection is provided for preterm and small newborns, the practice of nighttime bathing with cold water was common. The vernix was considered important for the preterm newborn but dangerous for HIV-exposed infants. Mothers applied various substances to the skin and umbilical cord, with special practices for preterm infants. Applied substances included petroleum jelly, commercial baby lotion, cooking oil and breastmilk. The most common substances applied to the umbilical cord were powders made of roots, burnt gourds or ash. To ward off malevolent spirits, similar powders were reportedly placed directly into dermal incisions, especially in ill children. Conclusions: Thermal care for newborns is commonly practiced but co-exists with harmful practices. Locally appropriate behavior change interventions should aim to promote chlorhexidine in place of commonly-reported application of harmful substances to the skin and umbilical cord, reduce bathing of newborns at night, and address the immediate bathing of HIV-infected newborns

The interaction of lean and building information modeling in construction

Lean construction and Building Information Modeling are quite different initiatives, but both are having profound impacts on the construction industry. A rigorous analysis of the myriad specific interactions between them indicates that a synergy exists which, if properly understood in theoretical terms, can be exploited to improve construction processes beyond the degree to which it might be improved by application of either of these paradigms independently. Using a matrix that juxtaposes BIM functionalities with prescriptive lean construction principles, fifty-six interactions have been identified, all but four of which represent constructive interaction. Although evidence for the majority of these has been found, the matrix is not considered complete, but rather a framework for research to explore the degree of validity of the interactions. Construction executives, managers, designers and developers of IT systems for construction can also benefit from the framework as an aid to recognizing the potential synergies when planning their lean and BIM adoption strategies

EU support for biofuels and bioenergy, environmental sustainability criteria, and trade policy

This paper presents physics-based surrogate modeling algorithms for systems governed by parameterized partial differential equations (PDEs) commonly encountered in design optimization and uncertainty analysis. We first outline unsupervised learning approaches that leverage advances in the machine learning literature for a meshfree solution of PDEs. Subsequently, we propose continuum and discrete formulations for systems governed by parameterized steady-state PDEs. We consider the case of both deterministically and randomly parameterized systems. The basic idea is to embody the design variables or uncertain parameters in additional dimensions of the governing PDEs along with the spatial coordinates. We show that the undetermined parameters of the surrogate model can be estimated by minimizing a physics-based objective function derived using a multidimensional least-squares collocation or the Bubnov-Galerkin scheme. This potentially allows us to construct surrogate models without using data from computer experiments on a deterministic analysis code. Finally, we also outline an extension of the present approach to directly approximate the density function of random algebraic equations