Quantitative Assessment of Temporal Changes in Subaqueous Hydrothermal Activity in Active Crater Lakes During Unrest Based on a Time-Series of Lake Water Chemistry

Regular sampling of lake water has been performed at many volcanoes to assess the state of volcanic activity. However, it is not clear whether the absolute concentrations or, instead, rate of changes in concentrations are more suitable for such assessments. In this study, we show that temporal changes in concentrations of an element in lake water are described by a simple differential equation, assuming changes in lake volume and chemical processes are negligible. The time constants (63% response time for changes in the chemical concentration in lake water) have a wide range varying between 20 and 1,000 days for the studied volcanoes in Japan, meaning it takes a long time to assess volcanic activity based on the absolute concentration of an element. In order to assess the volcanic activity in a shorter time period, based on a time-series of lake element concentration data, we developed a numerical model to calculate temporal changes in the steady-state concentration, which is proportional to the elemental concentrations of the bulk hydrothermal fluid injected from subaqueous fumaroles and hot springs. We applied our method to Yugama crater lake at Kusatsu–Shirane volcano, Japan, and quantitatively evaluated temporal changes in the hydrothermal input from 1964 to 2020. As a result, we detected changes in the Cl concentrations of the bulk hydrothermal input that were associated with unrest including the phreatic eruption in 1976 and earthquake swarms in 1989–1992 and 2014–2020. The future concentration in the lake water can be predicted from the most recent steady-state concentrations. Comparing the predicted concentration curve with the concentration obtained from lake water samples, it is possible to quickly assess whether the concentration of the bulk hydrothermal input has increased/decreased or remained constant.

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Estimation and Application of Dynamic Speed-Density Relations by Using Transfer Function Models

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/1710-06 ◽

2000 ◽

Vol 1710 (1) ◽

pp. 47-57 ◽

Cited By ~ 20

Author(s):

Hossein Tavana ◽

Hani S. Mahmassani

Keyword(s):

Time Series ◽

Steady State ◽

Transfer Function ◽

Traffic Flow ◽

Traffic Engineering ◽

Series Data ◽

Flow Models ◽

Wide Range ◽

Density Relation ◽

Traffic Flow Models

Deployment of intelligent transportation systems (ITS) and availability of a vast amount of online data are opening new opportunities for researchers and practitioners. Many of the previously established methods and applications must be revisited in light of the availability of real-time data. Traffic flow models, particularly speed-density relations, lie at the core of a wide range of applications in almost all areas of traffic engineering and control. In simulation applications and continuum traffic flow models, first-order models use a steady-state or static speed-density relation, whereas higher-order models, with additional terms and parameters, are usually driven by the deviation of speed from this steady-state value. In calibrating speed-density relations using time series data, the existence of serial correlation and other dynamic effects in the data has largely been ignored in previous studies. In this study, transfer function methods (bivariate time series models) are used to specify and estimate dynamic speed-density relations from typical detector data from an advanced traffic management system control center. First the deviation of speed from an equilibrium static relation is estimated, and later the method is extended to directly estimate speed without explicit specification of an equilibrium speed-density relation. The robustness of the model temporally and spatially is investigated. In all cases considered, the method exhibits good performance and robustness in application. Furthermore, since the method is based on the use of online information, it has the capability of being adaptive and adjusting its parameters online.

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Spectroscopic Studies of Asparaginyl-tRNA Synthetase from Entamoeba histolytica

Protein and Peptide Letters ◽

10.2174/0929866526666190327122419 ◽

2019 ◽

Vol 26 (6) ◽

pp. 435-448

Author(s):

Priyanka Biswas ◽

Dillip K. Sahu ◽

Kalyanasis Sahu ◽

Rajat Banerjee

Keyword(s):

Circular Dichroism ◽

Steady State ◽

Entamoeba Histolytica ◽

Protein Concentration ◽

Trna Synthetase ◽

Solvent Exposure ◽

Steady State Fluorescence ◽

State Process ◽

Wide Range ◽

Circular Dichroïsm

Background: Aminoacyl-tRNA synthetases play an important role in catalyzing the first step in protein synthesis by attaching the appropriate amino acid to its cognate tRNA which then transported to the growing polypeptide chain. Asparaginyl-tRNA Synthetase (AsnRS) from Brugia malayi, Leishmania major, Thermus thermophilus, Trypanosoma brucei have been shown to play an important role in survival and pathogenesis. Entamoeba histolytica (Ehis) is an anaerobic eukaryotic pathogen that infects the large intestines of humans. It is a major cause of dysentery and has the potential to cause life-threatening abscesses in the liver and other organs making it the second leading cause of parasitic death after malaria. Ehis-AsnRS has not been studied in detail, except the crystal structure determined at 3 Å resolution showing that it is primarily α-helical and dimeric. It is a homodimer, with each 52 kDa monomer consisting of 451 amino acids. It has a relatively short N-terminal as compared to its human and yeast counterparts. Objective: Our study focusses to understand certain structural characteristics of Ehis-AsnRS using biophysical tools to decipher the thermodynamics of unfolding and its binding properties. Methods: Ehis-AsnRS was cloned and expressed in E. coli BL21DE3 cells. Protein purification was performed using Ni-NTA affinity chromatography, following which the protein was used for biophysical studies. Various techniques such as steady-state fluorescence, quenching, circular dichroism, differential scanning fluorimetry, isothermal calorimetry and fluorescence lifetime studies were employed for the conformational characterization of Ehis-AsnRS. Protein concentration for far-UV and near-UV circular dichroism experiments was 8 µM and 20 µM respectively, while 4 µM protein was used for the rest of the experiments. Results: The present study revealed that Ehis-AsnRS undergoes unfolding when subjected to increasing concentration of GdnHCl and the process is reversible. With increasing temperature, it retains its structural compactness up to 45ºC before it unfolds. Steady-state fluorescence, circular dichroism and hydrophobic dye binding experiments cumulatively suggest that Ehis-AsnRS undergoes a two-state transition during unfolding. Shifting of the transition mid-point with increasing protein concentration further illustrate that dissociation and unfolding processes are coupled indicating the absence of any detectable folded monomer. Conclusion: This article indicates that GdnHCl induced denaturation of Ehis-AsnRS is a two – state process and does not involve any intermediate; unfolding occurs directly from native dimer to unfolded monomer. The solvent exposure of the tryptophan residues is biphasic, indicating selective quenching. Ehis-AsnRS also exhibits a structural as well as functional stability over a wide range of pH.

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Analogy-Based Crop Yield Forecasts Based on Temporal Similarity of Leaf Area Index

Remote Sensing ◽

10.3390/rs13163069 ◽

2021 ◽

Vol 13 (16) ◽

pp. 3069

Author(s):

Yadong Liu ◽

Junhwan Kim ◽

David H. Fleisher ◽

Kwang Soo Kim

Keyword(s):

Time Series ◽

Leaf Area Index ◽

Leaf Area ◽

Crop Yield ◽

Satellite Data ◽

Growing Season ◽

Environmental Data ◽

Area Index ◽

Current Season ◽

Wide Range

Seasonal forecasts of crop yield are important components for agricultural policy decisions and farmer planning. A wide range of input data are often needed to forecast crop yield in a region where sophisticated approaches such as machine learning and process-based models are used. This requires considerable effort for data preparation in addition to identifying data sources. Here, we propose a simpler approach called the Analogy Based Crop-yield (ABC) forecast scheme to make timely and accurate prediction of regional crop yield using a minimum set of inputs. In the ABC method, a growing season from a prior long-term period, e.g., 10 years, is first identified as analogous to the current season by the use of a similarity index based on the time series leaf area index (LAI) patterns. Crop yield in the given growing season is then forecasted using the weighted yield average reported in the analogous seasons for the area of interest. The ABC approach was used to predict corn and soybean yields in the Midwestern U.S. at the county level for the period of 2017–2019. The MOD15A2H, which is a satellite data product for LAI, was used to compile inputs. The mean absolute percentage error (MAPE) of crop yield forecasts was <10% for corn and soybean in each growing season when the time series of LAI from the day of year 89 to 209 was used as inputs to the ABC approach. The prediction error for the ABC approach was comparable to results from a deep neural network model that relied on soil and weather data as well as satellite data in a previous study. These results indicate that the ABC approach allowed for crop yield forecast with a lead-time of at least two months before harvest. In particular, the ABC scheme would be useful for regions where crop yield forecasts are limited by availability of reliable environmental data.

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Identification of DC Thermal Steady-State Differential Inductance of Ferrite Power Inductors

Energies ◽

10.3390/en14133854 ◽

2021 ◽

Vol 14 (13) ◽

pp. 3854

Author(s):

Salvatore Musumeci ◽

Luigi Solimene ◽

Carlo Stefano Ragusa

Keyword(s):

Steady State ◽

Input Voltage ◽

Switching Frequency ◽

Ohmic Losses ◽

Steady State Temperature ◽

Wide Range ◽

Average Current ◽

Power Inductors ◽

Saturable Inductor ◽

Thermal Steady State

In this paper, we propose a method for the identification of the differential inductance of saturable ferrite inductors adopted in DC–DC converters, considering the influence of the operating temperature. The inductor temperature rise is caused mainly by its losses, neglecting the heating contribution by the other components forming the converter layout. When the ohmic losses caused by the average current represent the principal portion of the inductor power losses, the steady-state temperature of the component can be related to the average current value. Under this assumption, usual for saturable inductors in DC–DC converters, the presented experimental setup and characterization method allow identifying a DC thermal steady-state differential inductance profile of a ferrite inductor. The curve is obtained from experimental measurements of the inductor voltage and current waveforms, at different average current values, that lead the component to operate from the linear region of the magnetization curve up to the saturation. The obtained inductance profile can be adopted to simulate the current waveform of a saturable inductor in a DC–DC converter, providing accurate results under a wide range of switching frequency, input voltage, duty cycle, and output current values.

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Quantification of the Environmental Impacts of Highway Construction Using Remote Sensing Approach

Remote Sensing ◽

10.3390/rs13071340 ◽

2021 ◽

Vol 13 (7) ◽

pp. 1340

Author(s):

Shuailong Feng ◽

Shuguang Liu ◽

Lei Jing ◽

Yu Zhu ◽

Wende Yan ◽

...

Keyword(s):

Remote Sensing ◽

Environmental Impacts ◽

Land Surface ◽

Vegetation Index ◽

Highway Construction ◽

Temporal Changes ◽

Moisture Index ◽

Buffer Zones ◽

Wide Range ◽

Spatial And Temporal Changes

Highways provide key social and economic functions but generate a wide range of environmental consequences that are poorly quantified and understood. Here, we developed a before–during–after control-impact remote sensing (BDACI-RS) approach to quantify the spatial and temporal changes of environmental impacts during and after the construction of the Wujing Highway in China using three buffer zones (0–100 m, 100–500 m, and 500–1000 m). Results showed that land cover composition experienced large changes in the 0–100 m and 100–500 m buffers while that in the 500–1000 m buffer was relatively stable. Vegetation and moisture conditions, indicated by the normalized difference vegetation index (NDVI) and the normalized difference moisture index (NDMI), respectively, demonstrated obvious degradation–recovery trends in the 0–100 m and 100–500 m buffers, while land surface temperature (LST) experienced a progressive increase. The maximal relative changes as annual means of NDVI, NDMI, and LST were about −40%, −60%, and 12%, respectively, in the 0–100m buffer. Although the mean values of NDVI, NDMI, and LST in the 500–1000 m buffer remained relatively stable during the study period, their spatial variabilities increased significantly after highway construction. An integrated environment quality index (EQI) showed that the environmental impact of the highway manifested the most in its close proximity and faded away with distance. Our results showed that the effect distance of the highway was at least 1000 m, demonstrated from the spatial changes of the indicators (both mean and spatial variability). The approach proposed in this study can be readily applied to other regions to quantify the spatial and temporal changes of disturbances of highway systems and subsequent recovery.

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SET-VALUED PERFORMANCE APPROXIMATIONS FOR THE QUEUE GIVEN PARTIAL INFORMATION

Probability in the Engineering and Informational Sciences ◽

10.1017/s0269964820000509 ◽

2020 ◽

pp. 1-23

Author(s):

Yan Chen ◽

Ward Whitt

Keyword(s):

Steady State ◽

Decay Rate ◽

Waiting Time ◽

Partial Information ◽

Upper And Lower Bounds ◽

Interarrival Time ◽

Limited Information ◽

Wide Range ◽

The Mean ◽

Third Moment

In order to understand queueing performance given only partial information about the model, we propose determining intervals of likely values of performance measures given that limited information. We illustrate this approach for the mean steady-state waiting time in the $GI/GI/K$ queue. We start by specifying the first two moments of the interarrival-time and service-time distributions, and then consider additional information about these underlying distributions, in particular, a third moment and a Laplace transform value. As a theoretical basis, we apply extremal models yielding tight upper and lower bounds on the asymptotic decay rate of the steady-state waiting-time tail probability. We illustrate by constructing the theoretically justified intervals of values for the decay rate and the associated heuristically determined interval of values for the mean waiting times. Without extra information, the extremal models involve two-point distributions, which yield a wide range for the mean. Adding constraints on the third moment and a transform value produces three-point extremal distributions, which significantly reduce the range, producing practical levels of accuracy.

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Modelling the atmosphere of lava planet K2-141b: implications for low- and high-resolution spectroscopy

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/staa2487 ◽

2020 ◽

Vol 499 (4) ◽

pp. 4605-4612

Author(s):

T Giang Nguyen ◽

Nicolas B Cowan ◽

Agnibha Banerjee ◽

John E Moores

Keyword(s):

Steady State ◽

Ocean Circulation ◽

Scale Height ◽

High Resolution Spectroscopy ◽

Return Flow ◽

High Dispersion ◽

Magma Ocean ◽

Steady State Flow ◽

Wide Range ◽

Very High

ABSTRACT Transit searches have uncovered Earth-size planets orbiting so close to their host star that their surface should be molten, so-called lava planets. We present idealized simulations of the atmosphere of lava planet K2-141b and calculate the return flow of material via circulation in the magma ocean. We then compare how pure Na, SiO, or SiO2 atmospheres would impact future observations. The more volatile Na atmosphere is thickest followed by SiO and SiO2, as expected. Despite its low vapour pressure, we find that a SiO2 atmosphere is easier to observe via transit spectroscopy due to its greater scale height near the day–night terminator and the planetary radial velocity and acceleration are very high, facilitating high dispersion spectroscopy. The special geometry that arises from very small orbits allows for a wide range of limb observations for K2-141b. After determining the magma ocean depth, we infer that the ocean circulation required for SiO steady-state flow is only 10−4 m s−1, while the equivalent return flow for Na is several orders of magnitude greater. This suggests that a steady-state Na atmosphere cannot be sustained and that the surface will evolve over time.

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GlobSim (v1.0): deriving meteorological time series for point locations from multiple global reanalyses

Geoscientific Model Development ◽

10.5194/gmd-12-4661-2019 ◽

2019 ◽

Vol 12 (11) ◽

pp. 4661-4679 ◽

Cited By ~ 3

Author(s):

Bin Cao ◽

Xiaojing Quan ◽

Nicholas Brown ◽

Emilie Stewart-Jones ◽

Stephan Gruber

Keyword(s):

Time Series ◽

Land Surface ◽

Ground Surface ◽

Reanalysis Data ◽

Meteorological Variables ◽

Ensemble Simulations ◽

Driving Time ◽

Wide Range ◽

Global Coverage ◽

Uncertain Input

Abstract. Simulations of land-surface processes and phenomena often require driving time series of meteorological variables. Corresponding observations, however, are unavailable in most locations, even more so, when considering the duration, continuity and data quality required. Atmospheric reanalyses provide global coverage of relevant meteorological variables, but their use is largely restricted to grid-based studies. This is because technical challenges limit the ease with which reanalysis data can be applied to models at the site scale. We present the software toolkit GlobSim, which automates the downloading, interpolation and scaling of different reanalyses – currently ERA5, ERA-Interim, JRA-55 and MERRA-2 – to produce meteorological time series for user-defined point locations. The resulting data have consistent structure and units to efficiently support ensemble simulation. The utility of GlobSim is demonstrated using an application in permafrost research. We perform ensemble simulations of ground-surface temperature for 10 terrain types in a remote tundra area in northern Canada and compare the results with observations. Simulation results reproduced seasonal cycles and variation between terrain types well, demonstrating that GlobSim can support efficient land-surface simulations. Ensemble means often yielded better accuracy than individual simulations and ensemble ranges additionally provide indications of uncertainty arising from uncertain input. By improving the usability of reanalyses for research requiring time series of climate variables for point locations, GlobSim can enable a wide range of simulation studies and model evaluations that previously were impeded by technical hurdles in obtaining suitable data.

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Foslevodopa/Foscarbidopa Is Well Tolerated and Maintains Stable Levodopa and Carbidopa Exposure Following Subcutaneous Infusion

Journal of Parkinson s Disease ◽

10.3233/jpd-212813 ◽

2021 ◽

pp. 1-8

Author(s):

Matthew Rosebraugh ◽

Wei Liu ◽

Melina Neenan ◽

Maurizio F. Facheris

Keyword(s):

Steady State ◽

Phase 1 ◽

The United States ◽

Therapeutic Window ◽

Fixed Dose ◽

Advanced Parkinson’S Disease ◽

Subcutaneous Infusion ◽

Study Results ◽

Wide Range ◽

Favorable Safety

Background: Foslevodopa/foscarbidopa, formerly known as ABBV-951, is a formulation of levodopa/carbidopa prodrugs with solubility that allows for subcutaneous (SC) infusion and is in development for the treatment of motor complications for patients with advanced Parkinson’s disease (aPD). Objective: The current work characterizes the levodopa (LD) and carbidopa (CD) pharmacokinetics (PK) following SC infusions of foslevodopa/foscarbidopa delivered at four different infusion rates in PD patients. Methods: This was a Phase 1, single ascending dose, single-blind study conducted in 28 adult male and female subjects at seven sites in the United States. Foslevodopa/foscarbidopa was administered via abdominal SC infusion in PD patients over 72 hours. Patients were stratified in 4 groups and received a fixed dose of foslevodopa/foscarbidopa based on their oral daily LD intake. Serial plasma PK samples were collected to assay for LD and CD concentrations. Safety and tolerability were assessed throughout the study. Results: LD exposure quickly reached steady state and remained stable with minimal fluctuations. Foslevodopa/foscarbidopa infusion provides stable LD and CD exposures compared to oral LD/CD dosing with the average steady-state exposure ranging from 747-4660 ng/mL for the different groups. Conclusion: Foslevodopa/foscarbidopa was able to provide stable LD and CD exposures in PD patients over 72 hours via SC route of delivery with very low fluctuation in LD concentration level across a wide range of clinically relevant exposures. Foslevodopa/foscarbidopa had a favorable safety profile. The low PK fluctuation following foslevodopa/foscarbidopa infusion is expected to maintain LD exposure to treat aPD patients within a narrow therapeutic window.

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