262 research outputs found

    Electrostatic Effects on Model Bilayer Stability and Structure

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    Inclusive Approaches for Measuring Demographics of Underrepresented Populations in STEM and Biomedical Research Training Programs

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    As federal strategic plans prioritize increasing diversity within the biomedical workforce, and STEM training and outreach programs seek to recruit and retain students from historically underrepresented populations, there is a need for interrogation of traditional demographic descriptors and careful consideration of best practices for obtaining demographic data. To accelerate this work, equity-focused researchers and leaders from STEM programs convened to examine approaches for measuring demographic variables. Gender, race/ethnicity, disability, and disadvantaged background were prioritized given their focus by federal funding agencies. Categories of sex minority, sexual (orientation) minority, and gender minority (SSGM) should be included in demographic measures collected by STEM programs, consistent with recommendations from White House Executive Orders and federal reports. Our manuscript offers operationalized phrasing for demographic questions and recommendations for use across student-serving programs. Inclusive demographics permit the identification of individuals who are being excluded, marginalized, or improperly aggregated, increasing capacity to address inequities in biomedical research training. As trainees do not enter training programs with equal access, accommodations, or preparation, inclusive demographic measures can welcome trainees and inform a nuanced set of program outcomes that facilitate research on intersectionality to support the recruitment and retention of underrepresented students in biomedical research

    Financial incentives for large-scale wetland restoration: beyond markets to common asset trusts

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    Wetlands provide $47.4 trillion/year worth of ecosystem services globally and support immense biodiversity, yet face widespread drainage and pollution, and large-scale wetlands restoration is urgently needed. Payment for ecosystem service (PES) schemes provide a viable avenue for funding large-scale wetland restoration. However, schemes around the globe differ substantially in their goals, structure, challenges, and effectiveness in supporting large-scale wetland restoration. Here, we suggest wetland-based PES schemes use common asset trusts (CATs) to build investment portfolios of wetlands across landscapes that sustain and enhance overall provision of multiple ecosystem services. CATs can meet the needs of multiple investors, permit bundled payments, and provide flexibility to invest in the restoration of numerous services/values, all using a coordinated, highly collaborative, prioritized, and transparent process. CATs would support financial viability, facilitate efficiency to reduce administrative burdens, and enable credibility and social licence building to restore wetland values and services globally

    Virtual Machine Support for Many-Core Architectures: Decoupling Abstract from Concrete Concurrency Models

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    The upcoming many-core architectures require software developers to exploit concurrency to utilize available computational power. Today's high-level language virtual machines (VMs), which are a cornerstone of software development, do not provide sufficient abstraction for concurrency concepts. We analyze concrete and abstract concurrency models and identify the challenges they impose for VMs. To provide sufficient concurrency support in VMs, we propose to integrate concurrency operations into VM instruction sets. Since there will always be VMs optimized for special purposes, our goal is to develop a methodology to design instruction sets with concurrency support. Therefore, we also propose a list of trade-offs that have to be investigated to advise the design of such instruction sets. As a first experiment, we implemented one instruction set extension for shared memory and one for non-shared memory concurrency. From our experimental results, we derived a list of requirements for a full-grown experimental environment for further research

    Detection of Reflection Features in the Neutron Star Low-Mass X-Ray Binary Serpens X-1 with NICER

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    We present Neutron Star Interior Composition Explorer (NICER) observations of the neutron star (NS) low-mass X-ray binary Serpens X-1 during the early mission phase in 2017. With the high spectral sensitivity and low-energy X-ray passband of NICER, we are able to detect the Fe L line complex in addition to the signature broad, asymmetric Fe K line. We confirm the presence of these lines by comparing the NICER data to archival observations with XMM-Newton/Reflection Grating Spectrometer (RGS) and NuSTAR. Both features originate close to the innermost stable circular orbit (ISCO). When modeling the lines with the relativistic line model relline, we find that the Fe L blend requires an inner disk radius of 1.4 [superscript +0.2][subscript -0.01] R ISCO and Fe K is at 1.03[superscript +0.13][subscript -0.03]R ISCO (errors quoted at 90%). This corresponds to a position of 17.3[superscript +2.5][subscript -0.1] km and 12.7[superscript +1.6][subscript -0.04] km for a canonical NS mass (M[subscript NS] = 1.4 M[superscript ⨀]) and dimensionless spin value of a = 0. Additionally, we employ a new version of the relxill model tailored for NSs and determine that these features arise from a dense disk and supersolar Fe abundance

    A Federated Design for a Neurobiological Simulation Engine: The CBI Federated Software Architecture

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    Simulator interoperability and extensibility has become a growing requirement in computational biology. To address this, we have developed a federated software architecture. It is federated by its union of independent disparate systems under a single cohesive view, provides interoperability through its capability to communicate, execute programs, or transfer data among different independent applications, and supports extensibility by enabling simulator expansion or enhancement without the need for major changes to system infrastructure. Historically, simulator interoperability has relied on development of declarative markup languages such as the neuron modeling language NeuroML, while simulator extension typically occurred through modification of existing functionality. The software architecture we describe here allows for both these approaches. However, it is designed to support alternative paradigms of interoperability and extensibility through the provision of logical relationships and defined application programming interfaces. They allow any appropriately configured component or software application to be incorporated into a simulator. The architecture defines independent functional modules that run stand-alone. They are arranged in logical layers that naturally correspond to the occurrence of high-level data (biological concepts) versus low-level data (numerical values) and distinguish data from control functions. The modular nature of the architecture and its independence from a given technology facilitates communication about similar concepts and functions for both users and developers. It provides several advantages for multiple independent contributions to software development. Importantly, these include: (1) Reduction in complexity of individual simulator components when compared to the complexity of a complete simulator, (2) Documentation of individual components in terms of their inputs and outputs, (3) Easy removal or replacement of unnecessary or obsoleted components, (4) Stand-alone testing of components, and (5) Clear delineation of the development scope of new components
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