4,872 research outputs found

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    Assessing Atmospheric Pollution and Its Impacts on the Human Health

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    This reprint contains articles published in the Special Issue entitled "Assessing Atmospheric Pollution and Its Impacts on the Human Health" in the journal Atmosphere. The research focuses on the evaluation of atmospheric pollution by statistical methods on the one hand, and on the other hand, on the evaluation of the relationship between the level of pollution and the extent of its effect on the population's health, especially on pulmonary diseases

    Benthic communities of the lower mesophotic zone on One Tree shelf edge, southern Great Barrier Reef, Australia

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    Context: Increasing interest in mesophotic coral ecosystems has shown that reefs in deep water show considerable geomorphic and ecological variability among geographic regions. Aims: We provide the first investigation of mesophotic reefs at the southern extremity of the Great Barrier Reef (GBR) to understand the biotic gradients and habitat niches in the lower mesophotic zone. Methods: Multibeam data were used to target five benthic imagery transects collected in the lower mesophotic (80ā€“130 m) zone from the shelf edge near One Tree Island (23Ā°S, 152Ā°E) by using a single HD-SDI subsea camera. Key results: Transects supported similar benthic communities in depths of 80ā€“110 m, with the abundance of sessile benthos declining below ~110 m where the shelf break grades into the upper continental slope. Conclusions: The effect of the Capricorn Eddy may be promoting homogeneity of benthic assemblages, because it provides similar environmental conditions and potential for connectivity. Variation in benthic communities between hard and soft substrate and differing topographic relief within the study site are likely to be influenced by variation in sedimentation, including sensitivity to suspended particles. Implications: This study highlighted that the lower mesophotic region on the One Tree shelf edge supports mesophotic coral ecosystems that vary depending on depth and substrate

    Multimodal connectivity of the human basal forebrain

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    The cholinergic innervation of the cortex originates from neurons in the basal forebrain (BF) and plays a crucial role in cognitive processing. However, it is unclear how the organization of BF cholinergic neurons in the human brain is related to their functional and structural integration with the cortex. To address this, we have used high-resolution 7 Tesla diffusion and resting-state functional MRI to examine multimodal forebrain cholinergic connectivity with the neocortex in humans. Discrete parcellation analyses revealed that structural and functional parcellation broadly differentiated the anteromedial from posterolateral nuclei of BF. Next, we used gradient estimation to capture more fine-grained connectivity profile of the BF-cortical projectome and found moving from anteromedial to posterolateral BF, structural and functional gradients became progressively detethered, with the most pronounced dissimilarity localized in the nucleus basalis of Meynert (NbM). Additionally, functional but not structural connectivity with the BF grew stronger at shorter geodesic distances, with weakly myelinated transmodal cortical areas most strongly expressing this divergence. Moreover, [18F] FEOBV PET imaging was used to demonstrate that these transmodal cortical areas are also among the most densely innervated regions. This intrinsic BF cholinergic connectivity map of cortex was compared with meta-analytic connectivity map of cholinergic modulation on attention, demonstrating that patterns of brain activity evoked by directed attention are altered by pharmacological activation of acetylcholine (ACh) compared to placebo and these patterns spatially overlap with the intrinsic BF cholinergic connectivity map. Altogether, our findings provide new insights into how cholinergic signaling is organized in the human brain

    Spaceā€Scale Resolved Surface Fluxes Across a Heterogeneous, Midā€Latitude Forested Landscape

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    The Earth\u27s surface is heterogeneous at multiple scales owing to spatial variability in various properties. The atmospheric responses to these heterogeneities through fluxes of energy, water, carbon, and other scalars are scale-dependent and nonlinear. Although these exchanges can be measured using the eddy covariance technique, widely used tower-based measurement approaches suffer from spectral losses in lower frequencies when using typical averaging times. However, spatially resolved measurements such as airborne eddy covariance measurements can detect such larger scale (meso-Ī², meso-Ī³) transport. To evaluate the prevalence and magnitude of these flux contributions, we applied wavelet analysis to airborne flux measurements over a heterogeneous mid-latitude forested landscape, interspersed with open water bodies and wetlands. The measurements were made during the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors intensive field campaign. We ask, how do spatial scales of surface-atmosphere fluxes vary over heterogeneous surfaces across the day and across seasons? Measured fluxes were separated into smaller-scale turbulent and larger-scale mesoscale contributions. We found significant mesoscale contributions to sensible and latent heat fluxes through summer to autumn which would not be resolved in single-point tower measurements through traditional time-domain half-hourly Reynolds decomposition. We report scale-resolved flux transitions associated with seasonal and diurnal changes of the heterogeneous study domain. This study adds to our understanding of surface-atmospheric interactions over unstructured heterogeneities and can help inform multi-scale model-data integration of weather and climate models at a sub-grid scale

    Next Generation Traffic Signal Performance Measures: Leveraging Connected Vehicle Data

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    High-resolution connected vehicle (CV) trajectory and event data has recently become commercially available. With over 500 billion vehicle position records generated each month in the United States, these data sets provide unique opportunities to build on and expand previous advances on traffic signal performance measures and safety evaluation. This report is a synthesis of research focused on the development of CV-based performance measures. A discussion is provided on data requirements, such as acquisition, storage, and access. Subsequently, techniques to reference vehicle trajectories to relevant roadways and movements are presented. This allows for performance analyses that can range from the movement- to the system-level. A comprehensive suite of methodologies to evaluate signal performance using vehicle trajectories is then provided. Finally, uses of CV hard-braking and hard-acceleration event data to assess safety and driver behavior are discussed. To evaluate scalability and test the proposed techniques, performance measures for over 4,700 traffic signals were estimated using more than 910 million vehicle trajectories and 14 billion GPS points in all 50 states and Washington, D.C. The contents of this report will help the industry transition towards a hybrid blend of detector- and CV-based signal performance measures with rigorously defined performance measures that have been peer-reviewed by both academics and industry leaders

    Data-Driven Numerical Simulation and Optimization Using Machine Learning, and Artificial Neural Networks Methods for Drilling Dysfunction Identification and Automation

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    Providing the necessary energy supply to a growing world and market is essential to support human social development in an environmentally friendly. The energy industry is undergoing a digital transformation and rapidly adopting advanced technologies to improve safety and productivity and reduce carbon emissions. Energy companies are convinced that applying data-driven and physics-based technologies is the economical way forward. In drilling engineering, automating components of the drilling process has seen remarkable milestones with considerable efļ¬ciency gains. However, more elegant solutions are needed to plan, simulate, and optimize the drilling process for traditional and renewable energy generation. This work contributes to such efforts, speciļ¬cally in autonomous drilling optimization, real-time drilling simulation, and data-driven methods by developing: 1) a physics-based and data-driven drilling optimization and control methodologies to aid drilling operators in performing more effective decisions and optimizing the Rate of Penetration (ROP) while reducing drilling dysfunctions. 2) developing an integrated real-time drilling simulator, 3) using data-driven methodologies to identify drilling inefļ¬ciencies and improve performance. Initially, a novel drilling control systems algorithm using machine learning methods to maximize the performance of manually controlled drilling while advising was investigated. This study employs feasible non-linear control theory and data analysis to assist in data pre-analysis and evaluation. Further emphasis was spent on developing algorithms based on formation identiļ¬cation and Mechanical Speciļ¬c Energy (MSE), simulation, and validation. Initial drilling tests were performed in a lab-scale drilling rig with improved ROP and dysfunction identiļ¬cation algorithms to validate the simulated performance. Ultimately, the miniaturized drilling machine was fully automated and improved with several systems to improve performance and study the dynamic behavior while drilling by designing and implementing new control algorithms to mitigate dysfunctions and optimize the rate of penetration (ROP). Secondly, to overcome some of the current limitations faced by the industry and the need for the integration of drilling simulation models and software, in which cross-domain physics are uni-ļ¬ed within a single tool through the proposition and publication of an initial common open-source framework for drilling simulation and modeling. An open-source framework and platform that spans across technical drilling disciplines surpass what any single academic or commercial orga-nization can achieve. Subsequently, a complementary ļ¬lter for downhole orientation estimation was investigated and developed using numerical modeling simulation methods. In addition, the prospective drilling simulator components previously discussed were used to validate, visualize, and benchmark the performance of the dynamic models using prerecorded high-frequency down-hole data from horizontal wells. Lastly, machine-learning techniques were analyzed using open, and proprietary recorded well logs to identify, derive, and train supervised learning algorithms to quickly identify ongoing or incipient vibration and loading patterns that can damage drill bits and slow the drilling process. Followed by the analysis and implementation feasibility of using these trained models into a con-tained downhole tool for both geothermal and oil drilling operations was analyzed. As such, the primary objectives of this interdisciplinary work build from the milestones mentioned above; in-corporating data-driven, probabilistic, and numerical simulation methods for improved drilling dysfunction identiļ¬cation, automation, and optimization

    Annual Report 2022 - Institute of Resource Ecology

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    The Institute of Resource Ecology (IRE) is one of the ten institutes of the Helmholtz-Zentrum Dresdenā€Šā€“ā€ŠRossendorf (HZDR). Our research activities are mainly integrated into the program ā€œNuclear Waste Management, Safety and Ra-diation Research (NUSAFE)ā€ of the Helmholtz Association (HGF) and focus on the topics ā€œSafety of Nuclear Waste Disposalā€ and ā€œSafety Research for Nuclear Reactorsā€. The program NUSAFE, and therefore all work which is done at IRE, belong to the research field ā€œEnergyā€ of the HGF

    Pop-up archival tags reveal environmental influences on the vertical movements of silvertip sharks (Carcharhinus albimarginatus)

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    Vertical space use informs the ecology and management of marine species, but studies of reef-associated sharks often focus on horizontal movements. We analysed the vertical movements of silvertip sharks (Carcharhinus albimarginatus) using pop-up archival tags deployed on seven individuals in the Chagos Archipelago, central Indian Ocean. The sharks changed depth predictably with water column thermal structure, moving deeper with seasonal increases in mixed layer depth while occupying a narrow ambient water temperature range around ~27Ā°C. At shorter timescales, higher resolution data from five tags showed that silvertip shark depth varied cyclically with surface light levels, increasing during daylight and on nights around full moon. This matches the diel vertical migrations of many fish species, suggesting the sharksā€™ light-driven depth changes might relate to foraging. While most vertical movements (>98%) were within the mixed layer, deeper dives to 200-800 m occurred approximately every three days. High-resolution data from one recovered tag showed the shark ascending deep (>200 m) dives in two sharply defined phases, initially fast then slow. Analysis of dive profiles against dissolved oxygen (DO) data suggested that the shark may have ascended rapidly to escape low DO levels at depth, then reduced its ascent rate 50-80% once DO levels increased. While a small sample, the electronic tags deployed in this study revealed the silvertip sharksā€™ predictable use of mixed layer waters, narrow thermal range and apparent intolerance of hypoxic conditions. These characteristics may exacerbate the speciesā€™ vulnerability as oceanic warming and shoaling oxygen minimum zones modify vertical habitat availability

    Characterizing Allosteric Regulation and Conformational Dynamics in Staphylococcus Aureus Pyruvate Carboxylase

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    Pyruvate carboxylase (PC) produces oxaloacetate from pyruvate and bicarbonatein an ATP-dependent manner. The catalytic activity of PC places it at a pivotal intersection between catabolism and anabolism. Understanding the essential metabolic role of PC requires a more complete description of how its activity is regulated and how that regulation is manifested through changes in conformational dynamics. PC activity is regulated by the mutually exclusive binding of the allosteric activator, acetyl-CoA, and the allosteric inhibitor, L-aspartate. The binding site for acetyl- CoA has largely been identified, but the binding location for the acetyl moiety is unknown. Given that the acetyl moiety enhances the binding affinity drastically, a definition of the binding site will uncover new molecular insights regarding the allosteric mechanism. This work defines the binding site of the acetyl moiety at the biotin carboxylase dimer interface in Staphylococcus aureus PC and identifies essential residues Arg21, Lys46 and Glu418 to allosteric activation, and inhibition. Early studies on vertebrate PC reported enzyme-mediated hydrolysis of the acetyl moiety from acetyl-CoA. The complete definition of the acetyl moiety binding site offers new opportunities to understand enzyme-mediated hydrolysis. The current study confirms that microbial PC enzymes catalyze acetyl-CoA hydrolysis. Residues in the dimer interface protect against enzyme catalyzed hydrolysis of the acetyl moiety. This suggests that a secondary binding site in the carboxyltransferase domain is responsible for hydrolyzing acetyl-CoA. The regulatory mechanism that controls carrier domain translocation remains unknown. Using numerous biophysical tools, the current study demonstrates that the conformational dynamics of PC are altered by acetyl-CoA, increasing the rate of carrier domain translocation and coordinating carrier domain positioning in the tetramer. Acetyl- CoA does this by modulating the flexibility of the carboxyltransferase dimers at the corners of the tetramer. This work provides a molecular basis for both allosteric activation and inhibition and confirms that microbial PC enzymes catalyze acetyl-CoA hydrolysis. These studies provide insights into how allostery modulates the conformational dynamics of PC in a coordinated manner, lending greater insights into the metabolic role of PC at the crossroads of metabolism
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