Increasing plant water stress and decreasing summer streamflow in response to a warmer and wetter climate in seasonally snow-covered forests
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Environmental Sciences & Ecology↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Plant community responses to stand-level nutrient fertilization in a secondary tropical dry forest
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Environmental Sciences & Ecology↗
Vegetation water sources in California's Sierra Nevada (USA) are young and change over time, a multi-isotope ( δ 18 O, δ 2 H, 3 H) tracer approach.
Sierra Nevada forests transpire a significant amount of California's water resources, sparking interest in applying forest management to improve California's water supply. Determining the source water of evapotranspiration enables forest managers to make informed decisions. To this end, a significant interest in critical zone science is to develop new methods to work across time scales to predict subsurface water storage and use. Here, forest vegetation accessed young water and switched sources depending on availability, suggesting that forest drought vulnerability may depend on the range of water sources available (rain, snowmelt and deeply stored water). This finding also suggests that changes in transpiration rates may have immediate effects on water sources in close proximity to vegetation, and delayed effects on storage and runoff. New δ 18 O, δ 2 H and 3 H data were used to track precipitation, runoff, evapotranspiration and storage through the critical zone seasonally, including seasons where evapotranspiration and snowmelt were in phase (winter snowmelt) and out of phase (seasonally dry summer). The main source of this headwater catchment's runoff is derived from its meadow saturated zone water, which was dominated by snowmelt. Water that originated as snowmelt contributed to transpiration, unless other sources, such as recent rain, became available. In cases where xylem δ 18 O and δ 2 H signatures matched those of deeper saturated zone water, 3 H data showed that xylem water was distinctly younger than the deep saturated zone water. During 2016, which experienced relatively normal snowpack in winter and seasonally dry summer conditions, mean summer saturated zone water and vegetation water were similar in δ 18 O, –12.4 ± 0.04 ‰ and – 12.5 ± 0.3 ‰, respectively, but were distinctly different in 3 H, 5.5 ± 0.2 pCi/L and 13.7 ± 1.1 pCi/L, respectively. While δ 18 O shows that vegetation and meadow saturated zone water have similar origins, 3 H shows they have dissimilar ages.
58 GEOSCIENCES↗
Environmental life cycle of fentanyl: From the cradle to an unknown grave
The lack of available information on the presence and persistence of fentanyl in the environment is a significant gap in the technical literature. Although the origins of the opioid in the environment are well-known because they follow the same pathways of other drug-related environmental contaminants, the downstream effects of fentanyl in the water supply and its retention in soil are less understood. The characterization of fentanyl and its potential degradation products in complex environmental samples such as soil is severely understudied. Very few articles are available that work to identify fentanyl and its degradation products in complex samples or name the possible hazards that may result from environmental exposure and degradation. Therefore, the objectives were to identify available articles focused on environmental fentanyl and its pathways and highlight quantifiable research or results that included specific degradation products or downstream effects. Research articles focused on fentanyl between 2000 and 2024 were identified and reviewed and then filtered using Boolean search terms for environmental parameters. Various studies have determined that trace levels of fentanyl can be found in a variety of environments, and additional data suggest preferential partitioning into soils from water and long-term persistence. Despite this knowledge, very little data exists on the long-term downstream effects of fentanyl or its analogs. As the chronic effects from low-level fentanyl exposure are currently unknown, this lack of insight brings to the forefront the need for further research to improve our understanding of fentanyl persistence, degradation, and toxicity within the environment.
54 ENVIRONMENTAL SCIENCES↗
Open‐source photovoltaic model pipeline validation against well‐characterized system data
Abstract All freely available plane‐of‐array (POA) transposition models and photovoltaic (PV) temperature and performance models in pvlib‐python and pvpltools‐python were examined against multiyear field data from Albuquerque, New Mexico. The data include different PV systems composed of crystalline silicon modules that vary in cell type, module construction, and materials. These systems have been characterized via IEC 61853‐1 and 61853‐2 testing, and the input data for each model were sourced from these system‐specific test results, rather than considering any generic input data (e.g., manufacturer's specification [spec] sheets or generic Panneau Solaire [PAN] files). Six POA transposition models, 7 temperature models, and 12 performance models are included in this comparative analysis. These freely available models were proven effective across many different types of technologies. The POA transposition models exhibited average normalized mean bias errors (NMBEs) within ±3%. Most PV temperature models underestimated temperature exhibiting mean and median residuals ranging from −6.5°C to 2.7°C; all temperature models saw a reduction in root mean square error when using transient assumptions over steady state. The performance models demonstrated similar behavior with a first and third interquartile NMBEs within ±4.2% and an overall average NMBE within ±2.3%. Although differences among models were observed at different times of the day/year, this study shows that the availability of system‐specific input data is more important than model selection. For example, using spec sheet or generic PAN file data with a complex PV performance model does not guarantee a better accuracy than a simpler PV performance model that uses system‐specific data.
14 SOLAR ENERGY↗
UnigeneFinder: An Automated Pipeline for Gene Calling From Transcriptome Assemblies Without a Reference Genome
ABSTRACT For most species, transcriptome data are much more readily available than genome data. Without a reference genome, gene calling is cumbersome and inaccurate because of the high degree of redundancy in de novo transcriptome assemblies. To simplify and increase the accuracy of de novo transcriptome assembly in the absence of a reference genome, we developed UnigeneFinder. Combining several clustering methods, UnigeneFinder substantially reduces the redundancy typical of raw transcriptome assemblies. This pipeline offers an effective solution to the problem of inflated transcript numbers, achieving a closer representation of the actual underlying genome. UnigeneFinder performs comparably or better, compared with existing tools, on plant species with varying genome complexities. UnigeneFinder is the only available transcriptome redundancy solution that fully automates the generation of primary transcript, coding region, and protein sequences, analogous to those available for high‐quality reference genomes. These features, coupled with the pipeline’s cross‐platform implementation, focus on automation, and an accessible, user‐friendly interface, make UnigeneFinder a useful tool for many downstream sequence‐based analyses in nonmodel organisms lacking a reference genome, including differential gene expression analysis, accurate ortholog identification, functional enrichments, and evolutionary analyses. UnigeneFinder also runs efficiently both on high‐performance computing (HPC) systems and personal computers, further reducing barriers to use.
Xue, Bo [Plant Resilience Institute Michigan State↗
Materials data analytics for 9% Cr family steel
A materials data analytics (MDA) methodology was developed in this study to evaluate publicly available information on 9% Cr family steel and to handle nonlinear relationships and the sparsity in materials data for this alloy class. The overarching goal is to accelerate the design process as well as to reduce the time and expense associated with qualification testing of new alloys for fossil energy applications. Data entries in the analyzed data set for 82 iron–base alloy compositions, several processing parameters, and results of tensile mechanical tests selected for this study were arranged in 34 columns by 915 rows. While detailed microstructural information was not available, it is assumed that the compositional space for the 9 to 12% Cr steels is limited such that all data entries have a tempered martensitic microstructure during service. Establishing a hierarchy of first–order trends in the publicly available data requires the MDA to filter out the biases. Complexity of the phase transformations and microstructure evolution in the multicomponent alloys (using 21 chemical elements) with major influence on mechanical properties, leads to inefficiency in direct application of unbiased linear regression across the entire data space. To address the nonlinearity, analyses of tensile data were performed in composition–based clusters. Clusters corresponding to moderately frequent patterns and maximized information gain were further refined by using p–norm distance measures, matching the alloy classification groups adopted by industry. Lastly, the evolutionary method of propagating an ensemble of competing cluster–based models proved to be a viable option in dealing with scarce, multidimensional data.
36 MATERIALS SCIENCE↗
Generating short-term probabilistic wind power scenarios via nonparametric forecast error density estimators: Generating short-term probabilistic wind power scenarios via nonparametric forecast error density estimators
Forecasts of available wind power are critical in key electric power systems operations planning problems, including economic dispatch and unit commitment. Such forecasts are necessarily uncertain, limiting the reliability and cost effectiveness of operations planning models based on a single deterministic or “point” forecast. A common approach to address this limitation involves the use of a number of probabilistic scenarios, each specifying a possible trajectory of wind power production, with associated probability. We present and analyze a novel method for generating probabilistic wind power scenarios, leveraging available historical information in the form of forecasted and corresponding observed wind power time series. We estimate non-parametric forecast error densities, specifically using epi-spline basis functions, allowing us to capture the skewed and non-parametric nature of error densities observed in real-world data. We then describe a method to generate probabilistic scenarios from these basis functions that allows users to control for the degree to which extreme errors are captured.We compare the performance of our approach to the current state-of-the-art considering publicly available data associated with the Bonneville Power Administration, analyzing aggregate production of a number of wind farms over a large geographic region. Finally, we discuss the advantages of our approach in the context of specific power systems operations planning problems: stochastic unit commitment and economic dispatch. Here, our methodology is embodied in the joint Sandia – University of California Davis Prescient software package for assessing and analyzing stochastic operations strategies.
17 WIND ENERGY↗
RDPM: An Extensible Tool for Resilience Design Patterns Modelling
Resilience to faults, errors, and failures in extreme-scale high-performance computing (HPC) systems is a critical challenge. Resilience design patterns offer a new, structured hardware and software design approach for improving resilience. While prior work focused on developing performance, reliability, and availability models for resilience design patterns, this paper extends it by providing a Resilience Design Patterns Modeling (RDPM) tool which allows (1) exploring performance, reliability, and availability of each resilience design pattern, (2) offering customization of parameters to optimize performance, reliability, and availability, and (3) allowing investigation of trade-off models for combining multiple patterns for practical resilience solutions.
Kumar, Mohit↗
Resonant anomaly detection with multiple reference datasets
An important class of techniques for resonant anomaly detection in high energy physics builds models that can distinguish between reference and target datasets, where only the latter has appreciable signal. Such techniques, including Classification Without Labels (CWoLa) and Simulation Assisted Likelihood-free Anomaly Detection (SALAD) rely on a single reference dataset. They cannot take advantage of commonly available multiple datasets and thus cannot fully exploit available information. In this work, we propose generalizations of CWoLa and SALAD for settings where multiple reference datasets are available, building on weak supervision techniques. We demonstrate improved performance in a number of settings with realistic and synthetic data. As an added benefit, our generalizations enable us to provide finite-sample guarantees, improving on existing asymptotic analyses.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Texture analysis of small renal cell carcinomas at MDCT for predicting relevant histologic and protein biomarkers
Purpose: To assess CT texture features of small renal cell carcinomas (≤ 4cm) for association with key pathologic features including protein biomarkers. Methods: Quantitative CT texture analysis (CTTA) of small renal cancers (≤ 4cm) was performed on non-contrast and portal venous phase abdominal MDCT scans with an ROI drawn at the largest cross-sectional diameter of the tumor using commercially available software. Texture parameters including mean pixel attenuation, the standard deviation (SD) of the pixel distribution histogram, entropy, the mean of positive pixels, the skewness (i.e., asymmetry) of the pixel histogram, kurtosis (i.e., peakness) of the pixel histogram, and the percentage of positive pixels were correlated with pathologic data from surgical resection, including histology and nuclear grade, as well as microarray analysis in a subset (n = 40) including Ki67 index, CRP, and neovascularization (CD105/CD31). Results: Portal venous phase images were available in 249 patients (105 women, 144 men; mean age, 56.7 years) with tumors ≤ 4cm (mean, median, range, ± SD; 2.66, 2.60, 0.3–4.0 ± 0.85 cm). CT texture features of standard deviation, mean of the positive pixels, and entropy of the pixel histogram were significantly associated with histologic cell type (clear vs. non-clear; p < 0.001). Entropy and mean of the positive pixels also showed an association with nuclear grade, although not statistically significant. In the microarray analysis subset, kurtosis of the pixel histogram was associated with CD105/CD31 (p = 0.05). SD also showed some association with CD 105 positivity (p = 0.02) and CAIX expression (p = 0.01). Non-contrast CT images were available in 174 patients (72 women, 102 men; mean age, 57.5 years). Although the association with histology was not as strong as on the portal venous phase, in the subset of patients with microarray data, SD was found to correlate with CRP (p = 0.08), kurtosis with CRP (p = 0.004), CD105/CD31 (p = 0.002), and with Ki 67 index (p < 0.001). Conclusion: CT texture features were significantly associated with important histopathologic features in small renal cancers. These non-invasive measures can be performed retrospectively and may provide useful information when determining follow-up and treatment of small renal cancers.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Vascular Closure Devices in Interventional Radiology Practice
Manual compression (MC) is a well-established technique for haemostasis following percutaneous arterial intervention. However, MC is labour and time intensive with potential limitations, particularly for patients who are coagulopathic, unable to comply with bed rest or obese and when large sheaths or anti-coagulants are used. There are a variety of vascular closure devices (VCDs) available to overcome these limitations. This review gives an overview of current VCDs, their mechanism of action, individual strengths and weaknesses, evidence base and utility in interventional radiology (IR) practice. The majority of the published evidence on VCDs is derived from patients undergoing cardiac interventions, which should be borne in mind when considering the applicability and transfer of this data for general IR practice. Overall, the evidence suggests that most VCDs are effective in achieving haemostasis with a similar rate of complications to MC although the complication profile associated with VCDs is distinct to that of MC. There is insufficient evidence to comparatively analyse the different types of VCDs currently available or reliably judge their cost-effectiveness. The interventional radiologist should have a thorough understanding of the available techniques for haemostasis and be able to identify and utilise the most appropriate strategy and closure technique for the individual patient.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Insights from 20 years of bacterial genome sequencing
Since the first two complete bacterial genome sequences were published in 1995, the science of bacteria has dramatically changed. Using third-generation DNA sequencing, it is possible to completely sequence a bacterial genome in a few hours and identify some types of methylation sites along the genome as well. Sequencing of bacterial genome sequences is now a standard procedure, and the information from tens of thousands of bacterial genomes has had a major impact on our views of the bacterial world. In this review, we explore a series of questions to highlight some insights that comparative genomics has produced. To date, there are genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. However, the distribution is quite skewed towards a few phyla that contain model organisms. But the breadth is continuing to improve, with projects dedicated to filling in less characterized taxonomic groups. The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas system provides bacteria with immunity against viruses, which outnumber bacteria by tenfold. How fast can we go? Second-generation sequencing has produced a large number of draft genomes (close to 90 % of bacterial genomes in GenBank are currently not complete); third-generation sequencing can potentially produce a finished genome in a few hours, and at the same time provide methlylation sites along the entire chromosome. The diversity of bacterial communities is extensive as is evident from the genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. Genome sequencing can help in classifying an organism, and in the case where multiple genomes of the same species are available, it is possible to calculate the pan- and core genomes; comparison of more than 2000 Escherichia coli genomes finds an E. coli core genome of about 3100 gene families and a total of about 89,000 different gene families. Why do we care about bacterial genome sequencing? There are many practical applications, such as genome-scale metabolic modeling, biosurveillance, bioforensics, and infectious disease epidemiology. In the near future, high-throughput sequencing of patient metagenomic samples could revolutionize medicine in terms of speed and accuracy of finding pathogens and knowing how to treat them.
59 BASIC BIOLOGICAL SCIENCES↗
Developing an Interactive Data Visualization Tool to Assess the Impact of Decision Support on Clinical Operations
Due to mandates from recent legislation, clinical decision support (CDS) software is being adopted by radiology practices across the country. This software provides imaging study decision support for referring providers at the point of order entry. CDS systems produce a large volume of data, providing opportunities for research and quality improvement. In order to better visualize and analyze trends in this data, an interactive data visualization dashboard was created using a commercially available data visualization platform. Following the integration of a commercially available clinical decision support product into the electronic health record, a dashboard was created using a commercially available data visualization platform (Tableau, Seattle, WA). Data generated by the CDS were exported from the data warehouse, where they were stored, into the platform. This allowed for real-time visualization of the data generated by the decision support software. The creation of the dashboard allowed the output from the CDS platform to be more easily analyzed and facilitated hypothesis generation. Integrating data visualization tools into clinical decision support tools allows for easier data analysis and can streamline research and quality improvement efforts.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
The role of renewable energy in climate stabilization: results from the EMF 27 scenarios
This paper uses the EMF27 scenarios to explore the role of renewable energy (RE) in climate change mitigation. Currently RE supplies almost 20 % of global electricity demand. Almost all EMF27 mitigation scenarios show a strong increase in renewable power production, with a substantial ramp-up of wind and solar power deployment. In many scenarios, renewables are the most important long-term mitigation option for power supply. Wind energy is competitive even without climate policy, whereas the prospects of solar photovoltaics (PV) are highly contingent on the ambitiousness of climate policy. Bioenergy is an important and versatile energy carrier; however—with the exception of low temperature heat—there is less scope for renewables other than biomass for non-electric energy supply. Despite the important role of wind and solar power in climate change mitigation scenarios with full technology availability, limiting their deployment has a relatively small effect on mitigation costs, if nuclear and carbon capture and storage (CCS)—which can serve as substitutes in low-carbon power supply—are available. Limited bioenergy availability in combination with limited wind and solar power by contrast, results in a more substantial increase in mitigation costs. While a number of robust insights emerge, the results on renewable energy deployment levels vary considerably across the models. An in-depth analysis of a subset of EMF27 reveals substantial differences in modeling approaches and parameter assumptions. To a certain degree, differences in model results can be attributed to different assumptions about technology costs, resource potentials and systems integration.
Luderer, Gunnar↗
Performance analysis of data intensive cloud systems based on data management and replication: a survey
As we delve deeper into the ‘Digital Age’, we witness an explosive growth in the volume, velocity, and variety of the data available on the Internet. For example, in 2012 about 2.5 quintillion bytes of data was created on a daily basis that originated from myriad of sources and applications including mobiledevices, sensors, individual archives, social networks, Internet of Things, enterprises, cameras, software logs, etc. Such ‘Data Explosions’ has led to one of the most challenging research issues of the current Information and Communication Technology era: how to optimally manage (e.g., store, replicated, filter, and the like) such large amount of data and identify new ways to analyze large amounts of data for unlocking information. It is clear that such large data streams cannot be managed by setting up on-premises enterprise database systems as it leads to a large up-front cost in buying and administering the hardware and software systems. Therefore, next generation data management systems must be deployed on cloud. The cloud computing paradigm provides scalable and elastic resources, such as data and services accessible over the Internet Every Cloud Service Provider must assure that data is efficiently processed and distributed in a way that does not compromise end-users’ Quality of Service (QoS) in terms of data availability, data search delay, data analysis delay, and the like. In the aforementioned perspective, data replication is used in the cloud for improving the performance (e.g., read and write delay) of applications that access data. Through replication a data intensive application or system can achieve high availability, better fault tolerance, and data recovery. In this paper, we survey data management and replication approaches (from 2007 to 2011) that are developed by both industrial and research communities. The focus of the survey is to discuss and characterize the existing approaches of data replication and management that tackle the resource usage and QoS provisioning with different levels of efficiencies. Moreover, the breakdown of both influential expressions (data replication and management) to provide different QoS attributes is deliberated. Furthermore, the performance advantages and disadvantages of data replication and management approaches in the cloud computing environments are analyzed. Open issues and future challenges related to data consistency, scalability, load balancing, processing and placement are also reported.
Malik, Saif Ur Rehman↗
Morphology, Modification and Characterisation of Electrospun Polymer Nanofiber Adsorbent Material Used in Metal Ion Removal
Among a wide range of technologies available to separate metal ions, adsorption is a major treatment technique for removing or recovering metals from aqueous solutions. Electrospun nanofiber adsorbents have attracted research consideration due to the distinctive properties such as their high surface area, high porosity and high adsorption capacity which makes nanofibers a good choice for selective metal recovery applications. Thus, the modification of electrospun nanofiber adsorbents by functionalisation with suitable ligands for selective metal extraction is a growing area of scientific research aiming to improve the selectivity of the adsorption process. This study reviews and summarises available information related to the different nanofiber modification processes for increasing adsorption efficiency, functionality and selectivity of modified nanofiber adsorbents as well as improving their durability and stability during use. The surface properties of an adsorbent is an essential control factor for its metal ion adsorption efficiency. The various techniques available for characterisation of specific properties of nanofiber adsorbents are also considered. Lastly, the recovery of the metal ions after adsorption by regenerating adsorbent materials and understanding the kinetics of nanofiber adsorption processes is summarised and recommendations made for further studies in order to address existing weaknesses of these materials.
36 MATERIALS SCIENCE↗
Feasibility of volumetric expansion of molten chlorides by conventional pushrod dilatometry
Abstract This study is a short communication on progress made in the adaptation of conventional push-rod dilatometry for the measurement of volumetric expansion of liquid salts up to 1300 K. A new crucible design is offered as a practical solution for measurement of liquid salts by this method. Proof-of-concept measurements of the volumetric expansion of sodium chloride (NaCl) are compared to the available data in literature. Measurement of the coefficient of thermal expansion (CTE) of solid NaCl compared favorably to the available data in literature, confirming both magnitude and trend. The average CTE of NaCl (solid) was $$\overline{\alpha }_{{{\text{NaCl}}\;{\text{Solid}}}} = 5.63 \cdot 10^{ - 5} {\raise0.7ex\hbox{$1$} \!\mathord{\left/ {\vphantom {1 K}}\right.\kern-\nulldelimiterspace} \!\lower0.7ex\hbox{$K$}}$$ α ¯ NaCl Solid = 5.63 · 10 - 5 1 K . The volumetric expansion of liquid NaCl was measured as $$\beta_{{{\text{NaCl}}\;{\text{Liquid}}}} \approx 3.96 \cdot 10^{ - 5} 1/K$$ β NaCl Liquid ≈ 3.96 · 10 - 5 1 / K and is essentially constant from the melt point to 1300 K. The volumetric expansion produced by this method is in reasonable agreement with the available published data and previous measurements made by the authors by neutron radiographic technique.
Parker, S. S. (ORCID:000000018597440X)↗