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At least 1,567 records · Page 87

The relationship between urinary selenium levels and risk of gestational diabetes mellitus: A nested case–control study

Background Selenium (Se) is an essential trace element for the human body. Serum Se and urinary Se are also biomarkers to assess Se exposure status. However, studies focusing on the association between urinary Se and the risk of gestational diabetes mellitus (GDM) are rare. Objective To investigate the association between urinary Se and the risk of GDM. Methods A nested case–control study based on a prospective birth cohort in Wuhan, China, which focuses on the effects of prenatal environmental factors exposure on pregnant women and children’s health was conducted. Two hundred and twenty-six cases and 452 controls were included. Maternal urine samples were collected before GDM diagnosis, and the urinary Se levels were determined. We assessed the association of urinary Se with GDM by conditional logistic regression with maternal urinary Se level as a categorical variable, and estimated the association between Se and glucose levels by multiple linear regression. The potential modifier roles of maternal age and fetal sex have also been assessed. Results Lower urinary level of Se was significantly associated with a higher risk of GDM (OR = 2.35 for the tertile 1, 95% CI:1.36-4.06; adjusted OR = 1.79 for the tertile 2, 95%CI:1.09-2.95; p for trend = 0.01). Fetal sex had an interaction with Se in the association with GDM. The association was more pronounced among pregnant women with female fetuses than with male fetuses. Discussion Our study suggested a significant negative association between urinary Se and the risk of GDM, and this association may vary depending on the fetal sex.

Liu, Yuanxia↗

Clinical effects of 3D printing-assisted posterolateral incision in the treatment of ankle fractures involving the posterior malleolus

Objective To explore the clinical outcomes of a 3D printing-assisted posterolateral approach for the treatment of ankle fractures involving the posterior malleolus. Methods A total of 51 patients with ankle fractures involving the posterior malleolus admitted to our hospital from January 2018 to December 2019 were selected. The patients were divided into 3D printing group (28 cases) and control group (23 cases). 3D printing was performed for ankle fractures, followed by printing of a solid model and simulation of the operation on the 3D model. The operation was then performed according to the preoperative plan, including open reduction and internal fixation via the posterolateral approach with the patient in the prone position. Routine x-ray and CT examinations of the ankle joint were performed, and ankle function was evaluated using the American Foot and Ankle Surgery Association (AOFAS) ankle-hindfoot score. Results All patients underwent x-ray and CT examinations. All fractures healed clinically, without loss of reduction or failure of internal fixation. Good clinical effects were achieved in both groups of patients. The operation time, intraoperative blood loss and intraoperative fluoroscopy frequency in the 3D printing group were significantly less than those in the control group ( p < 0.05). There was no significant difference between the two groups in the anatomical reduction rate of fractures or the incidence of surgical complications ( p > 0.05). Conclusion The 3D printing-assisted posterolateral approach is effective in the treatment of ankle fractures involving the posterior malleolus. The approach can be well planned before the operation, is simple to perform, yields good fracture reduction and fixation, and has good prospects for clinical application.

Zheng, Hongming↗

Duration of Contagion of Foot-And-Mouth Disease Virus in Infected Live Pigs and Carcasses

Data-driven modeling of incursions of high-consequence, transboundary pathogens of animals is a critical component of veterinary preparedness. However, simplifying assumptions and excessive use of proxy measures to compensate for gaps in available data may compromise modeled outcomes. The current investigation was prospectively designed to address two major gaps in current knowledge of foot-and-mouth disease virus (FMDV) pathogenesis in pigs: the end (duration) of the infectious period and the viability of FMDV in decaying carcasses. By serial exposure of sentinel groups of pigs to the same group of donor pigs infected by FMDV A24 Cruzeiro, it was demonstrated that infected pigs transmitted disease at 10 days post infection (dpi), but not at 15 dpi. Assuming a latent period of 1 day, this would result in a conservative estimate of an infectious duration of 9 days, which is considerably longer than suggested by a previous report from an experiment performed in cattle. Airborne contagion was diminished within two days of removal of infected pigs from isolation rooms. FMDV in muscle was inactivated within 7 days in carcasses stored at 4°C. By contrast, FMDV infectivity in vesicle epithelium harvested from intact carcasses stored under similar conditions remained remarkably high until the study termination at 11 weeks post mortem. The output from this study consists of experimentally determined data on contagion associated with FMDV-infected pigs. This information may be utilized to update parameterization of models used for foot-and-mouth disease outbreak simulations involving areas of substantial pig production.

59 BASIC BIOLOGICAL SCIENCES↗

Performance Evaluation of Weather@home2 Simulations over West African Region

Weather and climate forecasting, using climate models, have become essential tools and life-savers in the West African region; in spite of the fact that climate models do not fully comply with attributes of forecast qualities—RASAP: reliability, association, skill, accuracy, and precision. The objective of this paper is to quantitatively evaluate, in comparison to CRU and ERA5 datasets, the RASAP compliance-level of the weather@home2 modeling system (w@h2). Findings from some statistical evaluations show that, to a moderately significant extent, w@h2 model provides useful information during the monsoon seasons; skills to capture the Little Dry Season over the Guinea zone; predictive skills for the onset season; ability to reproduce all the annual characteristics of the surface maximum air temperature over the region; as well as skill to detect heat waves that usually ravage West Africa during the boreal spring. The model displays traces of attributes that are needed for seasonal climate predictions and applications. Deficiencies in the quantitative reproducibility point to the facts that the model does provide a reliability akin to that of regional climate models. This paper further furnishes a prospective user with information on whether the model might be “useful or not” for a particular application.

West Africa↗

Quantitative Evaluation of CO 2 Storage Potential in the Offshore Atlantic Lower Cretaceous Strata, Southeastern United States

The geological storage of CO 2 in the Earth’s subsurface has the potential to significantly offset greenhouse gas emissions for safe, economical, and acceptable public use. Due to legal advantages and vast resource capacity, offshore CO 2 storage provides an attractive alternative to onshore options. Although offshore Lower Cretaceous reservoirs have a vast expected storage capacity, there is a limited quantitative assessment of the offshore storage resource in the southeastern United States. This work is part of the Southeast Offshore Storage Resource Assessment (SOSRA) project, which presents a high-quality potential geological repository for CO 2 in the Mid- and South Atlantic Planning Areas. This is the first comprehensive investigation and quantitative assessment of CO 2 storage potential for the Lower Cretaceous section of the outer continental shelf that includes the Southeast Georgia Embayment and most of the Blake Plateau. An interpretation of 200,000 km of legacy industrial 2D seismic reflection profiles and geophysical well logs (i.e., TRANSCO 1005-1-1, COST GE-1, and EXXON 564-1) were utilized to create structure and thickness maps for the potential reservoirs and seals. We identified and assessed three target reservoirs isolated by seals based on their effective porosity values. The CO 2 storage capacity of these reservoirs was theoretically calculated using the DOE-NETL equation for saline formations. The prospective storage resources are estimated between 450 and 4700 Mt of CO 2 , with an offshore geological efficiency factor of dolomite between 2% and 3.6% at the formation scale.

03 NATURAL GAS↗

Atmospheric Drivers of Wind Turbine Blade Leading Edge Erosion: Review and Recommendations for Future Research

Leading edge erosion (LEE) of wind turbine blades causes decreased aerodynamic performance leading to lower power production and revenue and increased operations and maintenance costs. LEE is caused primarily by materials stresses when hydrometeors (rain and hail) impact on rotating blades. The kinetic energy transferred by these impacts is a function of the precipitation intensity, droplet size distributions (DSD), hydrometeor phase and the wind turbine rotational speed which in turn depends on the wind speed at hub-height. Hence, there is a need to better understand the hydrometeor properties and the joint probability distributions of precipitation and wind speeds at prospective and operating wind farms in order to quantify the potential for LEE and the financial efficacy of LEE mitigation measures. However, there are relatively few observational datasets of hydrometeor DSD available for such locations. Here, we analyze six observational datasets from spatially dispersed locations and compare them with existing literature and assumed DSD used in laboratory experiments of material fatigue. We show that the so-called Best DSD being recommended for use in whirling arm experiments does not represent the observational data. Neither does the Marshall Palmer approximation. We also use these data to derive and compare joint probability distributions of drivers of LEE; precipitation intensity (and phase) and wind speed. We further review and summarize observational metrologies for hydrometeor DSD, provide information regarding measurement uncertainty in the parameters of critical importance to kinetic energy transfer and closure of data sets from different instruments. A series of recommendations are made about research needed to evolve towards the required fidelity for a priori estimates of LEE potential.

17 WIND ENERGY↗

Nuclear-Driven Integrated Energy Systems: A State-of-the-Art Review

Because of the growing concerns regarding climate change and energy sustainability, a transition toward a modern energy sector that reduces environmental effects while promoting social and economic growth has gained traction in recent years. Sustainable energy solutions, which include renewable and low-carbon sources such as nuclear energy and natural gas, could minimize emissions of greenhouse gases, enhance air and water quality, and encourage energy independence. Yet, the shift to a sustainable energy industry is fraught with difficulties, including governmental and regulatory obstacles, technological and economic limits, and societal acceptability hurdles. Addressing these issues would necessitate the development of long-term, durable, and cost-effective energy systems containing nuclear energy and associated with the generation of both electricity and other by-products required by industry. Integrated energy systems (IES) are a novel way to maximize the use of various energy resources and technologies in order to deliver dependable, efficient, and sustainable energy services. IES entail the integration of various energy systems, such as electricity, heating, cooling, and transportation, in respect to energy sustainability and a system’s resilience and flexibility. Their development and implementation require the cooperation of several parties, including energy providers and policymakers. This study provides a state-of-the-art literature review of the most creative nuclear-driven hybrid energy system applications and methodologies, from which the research challenges and prospects for effective IES implementation emerge.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Polymeric Membranes for H2S and CO2 Removal from Natural Gas for Hydrogen Production: A Review

Natural gas, an important source of hydrogen, is expected to be crucial in the transition to a hydrogen-based economy. The landscape of the gas processing industry is set to change in the near future with the development of highly acidic sour gas wells. Natural gas purification constitutes a major share of the gas separation membrane market, and the shift to low-quality sour gas wells has been mirrored in the trends of membrane material research. Purification also constitutes the major portion of the cost of natural gas, posing implications for the cost of hydrogen production. This review provides an update on the current state of research regarding polymeric membranes for H2S removal, along with CO2 separation, from natural gas that is used for hydrogen production via steam methane reforming. The challenges of adapting polymeric membranes to ternary H2S/CO2/CH4 separations are discussed in detail. Key polymeric materials are highlighted, and the prospects for their application in H2S removal from natural gas are evaluated. Finally, the growing interest in H2 production from H2S is discussed. Advances in the membrane industry and the emergence of new membrane materials may significantly improve the commercial viability of such processes.

Rao, Shraavya↗

Towards an Energy Future with Ubiquitous Electric Vehicles: Barriers and Opportunities

The electrification of personal transportation holds great potential for lowering greenhouse gas emissions and reducing climate change. The promise of electric vehicles (EVs) to serve these goals has resulted in a broad range of supporting policies aimed at encouraging widespread EV adoption at both the state and federal levels in the United States and around the world. While the EV revolution and prospects of a world with ubiquitous EVs are impacting various industries and many aspects of daily life, strategic interactions between the power grid and EVs are crucial for a successful energy transition. However, managing the interplay between EVs and the power grid remains a challenge. Motivated by that tension, this paper surveys a variety of solutions, policies, and incentives that are focused on effectively managing EV charging behaviors. The paper’s objective is to explore these tools to ensure that EV owners have ultimate control over their personal vehicles while simultaneously allowing the power grid to mitigate adverse network impacts. Furthermore, this paper examines the role of charging infrastructure technology and its strategic placement in facilitating the seamless integration of EVs into the grid. Additionally, the paper highlights financial mechanisms associated with EV integration and discusses the consequences of these mechanisms.

25 ENERGY STORAGE↗

Hydrogen and the Global Energy Transition—Path to Sustainability and Adoption across All Economic Sectors

This perspective article delves into the critical role of hydrogen as a sustainable energy carrier in the context of the ongoing global energy transition. Hydrogen, with its potential to decarbonize various sectors, has emerged as a key player in achieving decarbonization and energy sustainability goals. This article provides an overview of the current state of hydrogen technology, its production methods, and its applications across diverse industries. By exploring the challenges and opportunities associated with hydrogen integration, we aim to shed light on the pathways toward achieving a sustainable hydrogen economy. Additionally, the article underscores the need for collaborative efforts among policymakers, industries, and researchers to overcome existing hurdles and unlock the full potential of hydrogen in the transition to a low-carbon future. Through a balanced analysis of the present landscape and future prospects, this perspective article aims to contribute valuable insights to the discourse surrounding hydrogen’s role in the global energy transition.

08 HYDROGEN↗

Qualification and Quantification of Porosity at the Top of the Fuel Pins in Metallic Fuels Using Image Processing

Approximately 130,000 metal fuel pins were irradiated in the Experimental Breeder Reactor II (EBR-II) during its 30 years of operation to develop and characterize existing and prospective fuels. For many of the metal fuel irradiation experiments, neutron radiography imaging was performed to characterize fuel behavior, such as fuel axial expansion. While several fuel expansion results obtained from neutron radiography imaging have been published, the analysis of neutron radiography for the purpose of describing statistical properties of porous matter formed on top of the fuel pins, also referred to as fluff in previous publications, is significantly less represented in the literature with just a single paper so far. This study aims to validate and augment results reported in previous publications using automated image processing. The paper describes the statistical properties of the porous matter in terms of nine parameters derived from radiography images and correlates those parameters with such fuel properties as composition, expansion, temperature, and burnup. The reported results are based on 1097 fuel pins of eight different fuel compositions. For three major fuel types, U-10Zr, U-8Pu-10Zr, and U-19Pu-10Zr, a clear negative correlation is found between the Pu content and five parameters describing the amount of porous matter generated. The parameters describing granularity properties, however, showed either negative correlation or nonlinear dependency from fuel composition. The parameters describing the amount showed a positive correlation with fuel axial expansion, while granularity parameters showed a negative correlation with axial expansion. The dependency on cladding temperature was found to be weak. A positive correlation is demonstrated for volume parameters and fuel burnup. In general, reported results confirm and validate findings published in previous studies using a much larger number of pins and automated processing techniques, which easily lend themselves to reproducibility, thus avoiding subjective bias.

36 MATERIALS SCIENCE↗

LES and RANS Spray Combustion Analysis of OME 3-5 and n-Dodecane

Clean-burning oxygenated and synthetic fuels derived from renewable power, so-called e-fuels, are a promising pathway to decarbonize compression–ignition engines. Polyoxymethylene dimethyl ethers (PODEs or OMEs) are one candidate of such fuels with good prospects. Their lack of carbon-to-carbon bonds and high concentration of chemically bound oxygen effectively negate the emergence of polycyclic aromatic hydrocarbons (PAHs) and even their precursors like acetylene (C 2 H 2 ), enabling soot-free combustion without the soot-NO x trade-off common for diesel engines. The differences in the spray combustion process for OMEs and diesel-like reference fuels like n-dodecane and their potential implications on engine applications include discrepancies in the observed ignition delay, the stabilized flame lift-off location, and significant deviations in high-temperature flame morphology. For CFD simulations, the accurate modeling and prediction of these differences between OMEs and n-dodecane proved challenging. This study investigates the spray combustion process of an OME 3 − 5 mixture and n-dodecane with advanced optical diagnostics, Reynolds-Averaged Navier–Stokes (RANS), and Large-Eddy Simulations (LESs) within a constant-volume vessel. Cool-flame and high-temperature combustion were measured simultaneously via high-speed (50 kHz) imaging with formaldehyde (CH 2 O) planar laser-induced fluorescence (PLIF) representing the former and line-of-sight OH* chemiluminescence the latter. Both RANS and LES simulations accurately describe the cool-flame development process with the formation of CH 2 O. However, CH 2 O consumption and the onset of high-temperature reactions, signaled by the rise of OH* levels, show significant deviations between RANS, LES, and experiments as well as between n-dodecane and OME. A focus is set on the quality of the simulated results compared to the experimentally observed spatial distribution of OH*, especially in OME fuel-rich regions. The influence of the turbulence modeling is investigated for the two distinct ambient temperatures of 900 K and 1200 K within the Engine Combustion Network Spray A setup. The capabilities and limitations of the RANS simulations are demonstrated with the initial cool-flame propagation and periodic oscillations of CH 2 O formation/consumption during the quasi-steady combustion period captured by the LES.

CFD↗

Advancements in Manufacturing of High-Performance Perovskite Solar Cells and Modules Using Printing Technologies

Perovskite photovoltaic technology carries immense opportunity for the solar industries because of its remarkable efficiency and prospect for cost-effective production. However, the successful deployment of perovskite solar modules (PSMs) in the solar market necessitates tackling stability-based obstacles, scalability, and environmental considerations. This paper unveils a comprehensive examination of the cutting-edge advancements in the manufacturing of perovskite solar cells (PSCs) and modules, with an emphasis on high-speed, large-area printing. The paper underscores the substantial progress achieved in printed PSCs and PSMs, demonstrating promising electrical performance and long-term device durability. This review paper categorizes printing techniques compatible with large-area high-speed manufacturing into three distinct families: blade coating, slot die coating, and screen printing, as these common printing practices offer precise control, scalability, cost-effectiveness, high resolution, and efficient material usage. Additionally, this paper presents an in-depth investigation and comparison of superior PSCs and PSMs fabricated by printing on power conversion efficiency (PCE), stability, and scalability.

14 SOLAR ENERGY↗

Gamma-ray Spectroscopy in Low-Power Nuclear Research Reactors

Gamma-ray spectroscopy is an effective technique for radioactive material characterization, routine inventory verification, nuclear safeguards, health physics, and source search scenarios. Gamma-ray spectrometers typically cannot be operated in the immediate vicinity of nuclear reactors due to their high flux fields and their resulting inability to resolve individual pulses. Low-power reactor facilities offer the possibility to study reactor gamma-ray fields, a domain of experiments hitherto poorly explored. In this work, we present gamma-ray spectroscopy experiments performed with various detectors in two reactors: The EPFL zero-power research reactor CROCUS, and the neutron beam facility at the Ohio State University Research Reactor (OSURR). We employed inorganic scintillators (CeBr3), organic scintillators (trans-stilbene and organic glass), and high-purity germanium semiconductors (HPGe) to cover a range of typical—and new—instruments used in gamma-ray spectroscopy. The aim of this study is to provide a guideline for reactor users regarding detector performance, observed responses, and therefore available information in the reactor photon fields up to 2 MeV. The results indicate several future prospects, such as the online (at criticality) monitoring of fission products (like Xe, I, and La), dual-particle sensitive experiments, and code validation opportunities.

Pakari, Oskari V. (ORCID:0000000337048190)↗

Identification and Classification of Fungal GPCR Gene Families

G protein-coupled receptors (GPCRs) are transmembrane proteins crucial for signal transduction in eukaryotes, responding to diverse extracellular signals. Researchers have found and systematically summarized 14 distinct types of GPCRs in fungi but their distribution among numerous fungal species remained largely unexamined. Additionally, three families of mammalian homologs (Rhodopsin, Glutamate, and Frizzled) have been found in previous studies, but they are not included in the systematic classification of fungal GPCRs. Our study establishes a unified classification of 17 GPCR classes in fungi, combining 14 fungal and 3 mammalian previously recognized groups, and classifies 28,294 GPCRs across 1357 fungal species, significantly expanding the scale of GPCRs in fungi and demonstrating their broader distribution. We found that mammalian homologs are notably more prevalent in Early Diverging Fungi (EDF), whereas the previous 14 classes are predominantly found in Ascomycota and Basidiomycota. The most abundant class detected in fungi was Pth11-like GPCRs, exclusively found in Pezizomycotina and involved in fungal pathogenicity. Our analysis suggested that Pezizomycotina ancestor possessed an extensive array of Pth11-like GPCRs, but over time, some species underwent considerable reductions in these GPCRs in conjunction with genome contractions. Utilizing a custom-built convolutional neural network (CNN) for the identification of fungal GPCRs, we identified several putative novel fungal GPCRs. Predicted interactions between these prospective new GPCRs and G-alpha proteins, as simulated by AlphaFold Multimer, provided additional support for their functional relevance. In conclusion, our work defines the first large-scale, unified classification of fungal GPCRs, reveals lineage-specific expansions and contractions, and uncovers previously unrecognized GPCR candidates with potential functional roles in fungal signaling.

G protein-coupled receptors↗

Deep-Learning-Based Segmentation of Keyhole in In-Situ X-ray Imaging of Laser Powder Bed Fusion

In laser powder bed fusion processes, keyholes are the gaseous cavities formed where laser interacts with metal, and their morphologies play an important role in defect formation and the final product quality. The in-situ X-ray imaging technique can monitor the keyhole dynamics from the side and capture keyhole shapes in the X-ray image stream. Keyhole shapes in X-ray images are then often labeled by humans for analysis, which increasingly involves attempting to correlate keyhole shapes with defects using machine learning. However, such labeling is tedious, time-consuming, error-prone, and cannot be scaled to large data sets. To use keyhole shapes more readily as the input to machine learning methods, an automatic tool to identify keyhole regions is desirable. In this paper, a deep-learning-based computer vision tool that can automatically segment keyhole shapes out of X-ray images is presented. The pipeline contains a filtering method and an implementation of the BASNet deep learning model to semantically segment the keyhole morphologies out of X-ray images. The presented tool shows promising average accuracy of 91.24% for keyhole area, and 92.81% for boundary shape, for a range of test dataset conditions in Al6061 (and one AliSi10Mg) alloys, with 300 training images/labels and 100 testing images for each trial. Prospective users may apply the presently trained tool or a retrained version following the approach used here to automatically label keyhole shapes in large image sets.

36 MATERIALS SCIENCE↗

Resurgence of Electron Quantum Tunneling Sensors

Quantum tunneling sensors are typically ultra-sensitive devices that have been specifically designed to convert a stimulus into an electronic signal using the wondrous principles of quantum mechanical tunneling. In the early 1990s, William Kaiser developed one of the first micromachined quantum tunneling sensors as part of his work with the NASA Jet Propulsion Laboratory. Since then, there have been scattered attempts at utilizing this phenomenon for the development of a variety of physical and chemical sensors. Although these devices demonstrate unique characteristics, such as high sensitivity, the principle of quantum tunneling often acts as a double-edged sword and is responsible for certain drawbacks of this sensor family. In this review, we briefly explain the underlying working principles of quantum tunneling and how they are used to design miniaturized quantum tunneling sensors. We then proceed to describe an overview of the various attempts at developing such sensors. Next, we discuss their current necessity and recent resurgence. Finally, we describe various advantages and shortcomings of these sensors and end this review with an insight into the potential of this technology and prospects.

Banerjee, Aishwaryadev↗

Is Genetic Engineering a Route to Enhance Microalgae-Mediated Bioremediation of Heavy Metal-Containing Effluents?

Contamination of the biosphere by heavy metals has been rising, due to accelerated anthropogenic activities, and is nowadays, a matter of serious global concern. Removal of such inorganic pollutants from aquatic environments via biological processes has earned great popularity, for its cost-effectiveness and high efficiency, compared to conventional physicochemical methods. Among candidate organisms, microalgae offer several competitive advantages; phycoremediation has even been claimed as the next generation of wastewater treatment technologies. Furthermore, integration of microalgae-mediated wastewater treatment and bioenergy production adds favorably to the economic feasibility of the former process—with energy security coming along with environmental sustainability. However, poor biomass productivity under abiotic stress conditions has hindered the large-scale deployment of microalgae. Recent advances encompassing molecular tools for genome editing, together with the advent of multiomics technologies and computational approaches, have permitted the design of tailor-made microalgal cell factories, which encompass multiple beneficial traits, while circumventing those associated with the bioaccumulation of unfavorable chemicals. Previous studies unfolded several routes through which genetic engineering-mediated improvements appear feasible (encompassing sequestration/uptake capacity and specificity for heavy metals); they can be categorized as metal transportation, chelation, or biotransformation, with regulation of metal- and oxidative stress response, as well as cell surface engineering playing a crucial role therein. This review covers the state-of-the-art metal stress mitigation mechanisms prevalent in microalgae, and discusses putative and tested metabolic engineering approaches, aimed at further improvement of those biological processes. Finally, current research gaps and future prospects arising from use of transgenic microalgae for heavy metal phycoremediation are reviewed.

Ranjbar, Saeed (ORCID:0000000256518605)↗