Inflation method for ensemble Kalman filter in soil hydrology

The ensemble Kalman filter (EnKF) is a popular data assimilation method in soil hydrology. In this context, it is used to estimate states and parameters simultaneously. Due to unrepresented model errors and a limited ensemble size, state and parameter uncertainties can become too small during assimilation. Inflation methods are capable of increasing state uncertainties, but typically struggle with soil hydrologic applications. We propose a multiplicative inflation method specifically designed for the needs in soil hydrology. It employs a Kalman filter within the EnKF to estimate inflation factors based on the difference between measurements and mean forecast state within the EnKF. We demonstrate its capabilities on a small soil hydrologic test case. The method is capable of adjusting inflation factors to spatiotemporally varying model errors. It successfully transfers the inflation to parameters in the augmented state, which leads to an improved estimation.</p

Balancing Surface Energy Terms for Stable Growth of Planar Surfaces

We investigate the driving forces that determine the growth mode of heteroepitaxial Ge layers grown from solution on Si substrates with orientations (001), (011) and (111) by transmission electron microscopy (TEM) and atomic force microscopy (AFM). Using liquid phase epitaxy, we can study the influences of strain and surface energy terms independently on effects due to limited surface diffusion. In (001) and (011) orientated layers, {111} faceted islands form (Stranski-Krastanov growth). In contrast, (111) orientated layers grow in a two-dimensional step flow growth mode (Frank-van der Merwe growth). We model these investigations in terms of energy minimisation considering surface energy reduction by formation of faceted islands and elastic strain energy relaxation by island formation. The strain energy relaxation by island formation is calculated by the finite element method. According to our considerations, two-dimensional growth is obtained by selective increase of the free surface energy of the low indices facet planes to a value higher than that of the substrate surface. Formation of faceted islands thus would increase the total surface energy; as a consequence, island formation is suppressed. By choosing the appropriate solvent and temperature in solution growth, we can provide for thermodynamically stable two-dimensional growth

Time‐variability of flow recession dynamics : Application of machine learning and learning from the machine

Flow recession analysis, relating discharge Q and its time rate of change −dQ/dt, has been widely used to understand catchment scale flow dynamics. However, data points in the recession plot, the plot of −dQ/dt versus Q, typically form a wide point cloud due to noise and hysteresis in the storage-discharge relationship, and it is still unclear what information we can extract from the plot and how to understand the information. There seem to be two contrasting approaches to interpret the plot. One emphasizes the importance of the ensemble characteristics of many recessions (i.e., the lower envelope or a measure of central tendency), and the other highlights the importance of the event scale analysis and questions the meaning of the ensemble characteristics. We examine if those approaches can be reconciled. We utilize a machine learning tool to capture the point cloud using the past trajectory of daily discharge. Our model results for a catchment show that most of the data points can be captured using 5 days of past discharge. We show that we can learn the catchment scale flow recession dynamics from what the machine learned. We analyze patterns learned by the machine and explain and hypothesize why the machine learned those characteristics. The hysteresis in the plot mainly occurs during the early time dynamics, and the flow recession dynamics eventually converge to an attractor in the plot, which represents the master recession curve. We also illustrate that a hysteretic storage-discharge relationship can be estimated based on the attractor

Mind the Gap! Working Toward Gender Equity in Pediatric and Congenital Heart Disease: Present and Future.

Evidence from medicine and other fields has shown that gender diversity results in better decision making and outcomes. The incoming workforce of congenital heart specialists (especially in pediatric cardiology) appears to be more gender balanced, but past studies have shown many inequities. Gender-associated differences in leadership positions, opportunities presented for academic advancement, and recognition for academic contributions to the field persist. In addition, compensation packages remain disparate if evaluated based on gender with equivalent experience and expertise. This review explores these inequities and has suggested individual and institutional changes that could be made to recruit and retain women, monitor the climate of the institution, and identify and eliminate bias in areas like salary and promotions

Integrating Human Health into Environmental Impact Assessment: An Unrealized Opportunity for Environmental Health and Justice

The National Environmental Policy Act and related state laws require many public agencies to analyze and disclose potentially significant environmental effects of agency actions, including effects on human health. In this paper we review the purpose and procedures of environmental impact assessment (EIA), existing regulatory requirements for health effects analysis, and potential barriers to and opportunities for improving integration of human health concerns within the EIA process. We use statutes, regulations, guidelines, court opinions, and empirical research on EIA along with recent case examples of integrated health impact assessment (HIA)/EIA at both the state and federal level. We extract lessons and recommendations for integrated HIA/EIA practice from both existing practices as well as case studies. The case studies demonstrate the adequacy, scope, and power of existing statutory requirements for health analysis within EIA. The following support the success of integrated HIA/EIA: a proponent recognizing EIA as an available regulatory strategy for public health; the openness of the agency conducting the EIA; involvement of public health institutions; and complementary objectives among community stakeholders and health practitioners. We recommend greater collaboration among institutions responsible for EIA, public health institutions, and affected stakeholders along with guidance, resources, and training for integrated HIA/EIA practice

Donated chemical probes for open science.

Potent, selective and broadly characterized small molecule modulators of protein function (chemical probes) are powerful research reagents. The pharmaceutical industry has generated many high-quality chemical probes and several of these have been made available to academia. However, probe-associated data and control compounds, such as inactive structurally related molecules and their associated data, are generally not accessible. The lack of data and guidance makes it difficult for researchers to decide which chemical tools to choose. Several pharmaceutical companies (AbbVie, Bayer, Boehringer Ingelheim, Janssen, MSD, Pfizer, and Takeda) have therefore entered into a pre-competitive collaboration to make available a large number of innovative high-quality probes, including all probe-associated data, control compounds and recommendations on use (https://openscienceprobes.sgc-frankfurt.de/). Here we describe the chemical tools and target-related knowledge that have been made available, and encourage others to join the project