Charge State Information Research Articles

Research on Capacity Configuration and Optimal Operation of Microgrid Energy Storage under Demand Management

In order to reduce the energy consumption cost, considering the influence of the correlation of photovoltaic output, load demand and peak valley TOU price in different periods on the optical storage capacity configuration, the system operation strategy and capacity configuration principle are determined based on the peak valley TOU price and energy storage charge state information and the actual size of photovoltaic output and load.Integrated with the historical load, time of use electricity price, state of charge, charge discharge power and other constraints of the energy storage system, the minimum objective function is utilized to optimize the output power of energy storage.The effectiveness of the model is verified by an example. The sensitivity analysis shows that different demand tariff rules affect the user demand declaration strategy. The energy storage system planning selects the light storage combination with appropriate capacity according to the demand tariff rules and the change of energy storage investment cost, which has practical engineering value.

Extracting Charge and Mass Information from Highly Congested Mass Spectra Using Fourier-Domain Harmonics

Native mass spectra of large, polydisperse biomolecules with repeated subunits, such as lipoprotein Nanodiscs, can often be challenging to analyze by conventional methods. The presence of tens of closely spaced, overlapping peaks in these mass spectra can make charge state, total mass, or subunit mass determinations difficult to measure by traditional methods. Recently, we introduced a Fourier Transform-based algorithm that can be used to deconvolve highly congested mass spectra for polydisperse ion populations with repeated subunits and facilitate identification of the charge states, subunit mass, charge-state-specific, and total mass distributions present in the ion population. Here, we extend this method by investigating the advantages of using overtone peaks in the Fourier spectrum, particularly for mass spectra with low signal-to-noise and poor resolution. This method is illustrated for lipoprotein Nanodisc mass spectra acquired on three common platforms, including the first reported native mass spectrum of empty "large" Nanodiscs assembled with MSP1E3D1 and over 300 noncovalently associated lipids. It is shown that overtone peaks contain nearly identical stoichiometry and charge state information to fundamental peaks but can be significantly better resolved, resulting in more reliable reconstruction of charge-state-specific mass spectra and peak width characterization. We further demonstrate how these parameters can be used to improve results from Bayesian spectral fitting algorithms, such as UniDec. Graphical Abstract ᅟ.

Context-Aware Abnormality Monitoring Service for Care-Needing Persons Using a Probabilistic Model

Background/Objectives: Care-needing persons usually have routine life patterns in their visiting places and routes. Probabilistic models are useful tools to capture the inherent patterns for care-needing persons from a collection of data and to make inference for uncertain situation. Methods/Statistical Analysis: A dynamic Bayesian network model is proposed to capture the traveling patterns for care-needing person. A collection of traveling data having location, date, and battery charge state information is used to train the dynamic Bayesian network model, in which the training travel data are preprocessed to filter out noises using a smoothing filter. The model makes probabilistic inference for the latent random variables on the fly with respect to the arriving captured sensor data. To conduct the probabilistic inference, the Rao-Blackwellized particle filter is used for fast execution. To take protective steps at potentially abnormal situations, the context-based service rules are defined that specify what to do in which situations the care-needing person is. Findings: The situations of interest are evaluated based on the deviation of the inferred probability distribution from the trained ones regarding the latent random variables. The service rules enable to realize value-added services such abnormal state alerting, abnormality notification to stakeholders, and situational information collection at abnormal states for future forensic or tracking. A real data set has been collected from a young student and the proposed method has been trained and tested in an implemented prototype system for young child care. In the experiments for a 6 weeks data set, the method detected all new test routes successfully when the deviation distance is greater than about 20 meters due to the limited precision of the GPS sensors. Improvements/Applications: The proposed model can be applied to context-aware abnormality service for care-needing persons like young children, mentally ill or disabled persons, and elderly persons are exposed to various dangers in daily life.

Detecting low-level synthesis impurities in modified phosphorothioate oligonucleotides using liquid chromatography–high resolution mass spectrometry

Oligonucleotide phosphorothioatediesters (phosphorothioate oligonucleotides), in which one of the non-bridging oxygen atoms at each phosphorus center is replaced by a sulfur atom, are now one of the most popular oligonucleotide modifications due to their ease of chemical synthesis and advantageous pharmacokinetic properties. Despite significant progress in the solid-phase oligomerization chemistry used in the manufacturing of these oligonucleotides, multiple classes of low-level impurities always accompany synthetic oligonucleotides. Liquid chromatography–mass spectrometry has emerged as a powerful technique for the identification of these synthesis impurities. However, impurity profiling, where the entire complement of low-level synthetic impurities is identified in a single analysis, is more challenging. Here we present an LC–MS method based the use of high resolution-mass spectrometry, specifically Fourier transform ion cyclotron resonance mass spectrometry (FTICRMS or FTMS). The optimal LC–FTMS conditions, including the stationary phase and mobile phases for the separation and identification of phosphorothioate oligonucleotides, were found. The characteristics of FTMS enable charge state determination from single m/z values of low-level impurities. Charge state information then enables more accurate modeling of the detected isotopic distribution for identification of the chemical composition of the detected impurity. Using this approach, a number of phosphorothioate impurities can be detected by LC–FTMS including failure sequences carrying 3′-terminal phosphate monoester and 3′-terminal phosphorothioate monoester, incomplete backbone sulfurization and desulfurization products, high molecular weight impurities, and chloral, isobutyryl, and N3 (2-cyanoethyl) adducts of the full-length product. When compared with low resolution LC–MS, ∼60% more impurities can be identified when charge state and isotopic distribution information is available and used for impurity profiling.

Analysis of a sequence of energetic ion and magnetic field events upstream from the Saturnian magnetosphere

The existence of energetic particle events to ∼200 R S upstream and ∼1300 R S downstream of Saturn was established during the Voyager 1, 2 flybys in 1980 and 1981, respectively. The origin of the events could not be determined with certainty because of lack of particle charge state and species measurements at lower (<300 keV) energies, which dominate the spectra. High sensitivity observations of energetic ion directional intensities, energy spectra, and ion composition were obtained by the Ion and Neutral Camera (INCA) of the Magnetospheric IMaging Instrument (MIMI) complement, with a geometry factor of ∼2.5 cm 2 sr and some capability of separating light (H, He) and heavier (C, N, O) ion groups (henceforth referred to as ‘hydrogen’ and ‘oxygen’, respectively). Charge state information was provided where possible by the Charge-Energy-Mass Spectrometer (CHEMS) over the range ∼3–235 keV per charge, and magnetic field (IMF) data by the MAG instrument on Cassini. The observations revealed the presence of distinct upstream bursts of energetic hydrogen and oxygen ions whenever the IMF connected the spacecraft to the planetary bow shock to distances >80 R S. The events exhibited the following characteristics: (1) hydrogen ion bursts are observed in the energy range 3–220 keV (and occasionally to E>220 keV) and oxygen ion bursts in the energy range 32 to ∼700 keV. (2) Pitch angle distributions are initially anisotropic with ions moving away from the bow shock along the IMF, but tend to isotropize as the event progresses in time. (3) The duration of the ion bursts is several minutes up to 4 h. (4) The event examined in this study contains significant fluxes of singly charged oxygen. (5) Ion bursts are accompanied by distinct diamagnetic field depressions with β>10, and exhibit wave structures consistent with ion cyclotron waves for O + and O ++. Given the magnetic field configuration during the detection of the events and that energetic ions trapped within the magnetosphere of Saturn are H +, H 2 + and various water products including O +, O ++, we conclude that O-rich upstream events must be particles leaking from Saturn's magnetosphere under favorable IMF conditions. The spectral evolution of the upstream events and their anisotropy characteristics are discussed in the context of current models.

Characteristic signatures of energetic ions upstream from the Kronian magnetosphere as revealed by Cassini/MIMI

AbstractWe present unique observations obtained by the Magnetospheric Imaging Instrument (MIMI) on the Cassini spacecraft, of the energetic ion population in the environment upstream from the dawn-to-noon sector of the Kronian magnetosphere during the approach phase and subsequent several orbits of the Cassini spacecraft around the planet. High sensitivity observations of energetic ion directional intensities, energy spectra, and ion composition were obtained by the Ion and Neutral Camera (INCA) of the MIMI instrument complement with a geometry factor of ~2.5 cm2sr. Charge state information was provided by the Charge-Energy-Mass-Spectrometer (CHEMS) over the range ~3 to 220 keV per charge. The observations revealed the presence of distinct upstream bursts of energetic hydrogen and oxygen ions up to distances of ~135 RS. The observations are presented and their theoretical implications are addressed.

Charger: Combination of Signal Processing and Statistical Learning Algorithms for Precursor Charge-State Determination from Electron-Transfer Dissociation Spectra

Tandem mass spectrometry in combination with liquid chromatography has emerged as a powerful tool for characterization of complex protein mixtures in a high-throughput manner. One of the bioinformatics challenges posed by the mass spectral data analysis is the determination of precursor charge when unit mass resolution is used for detecting fragment ions. The charge-state information is used to filter database sequences before they are correlated to experimental data. In the absence of the accurate charge state, several charge states are assumed. This dramatically increases database search times. To address this problem, we have developed an approach for charge-state determination of peptides from their tandem mass spectra obtained in fragmentations via electron-transfer dissociation (ETD) reactions. Protein analysis by ETD is thought to enhance the range of amino acid sequences that can be analyzed by mass spectrometry-based proteomics. One example is the improved capability to characterize phosphorylated peptides. Our approach to charge-state determination uses a combination of signal processing and statistical machine learning. The signal processing employs correlation and convolution analyses to determine precursor masses and charge states of peptides. We discuss applicability of these methods to spectra of different charge states. We note that in our applications correlation analysis outperforms the convolution in determining peptide charge states. The correlation analysis is best suited for spectra with prevalence of complementary ions. It is highly specific but is dependent on quality of spectra. The linear discriminant analysis (LDA) approach uses a number of other spectral features to predict charge states. We train LDA classifier on a set of manually curated spectral data from a mixture of proteins of known identity. There are over 5000 spectra in the training set. A number of features, pertinent to spectra of peptides obtained via ETD reactions, have been used in the training. The loading coefficients of LDA indicate the relative importance of different features for charge-state determination. We have applied our model to a test data set generated from a mixture of 49 proteins. We search the spectra with and without use of the charge-state determination. The charge-state determination helps to significantly save the database search times. We discuss the cost associated with the possible misclassification of charge states.

Resonant Tunneling Charge Detection and Dephasing

We analyze the properties of charge detection and dephasing of a charge qubit through a resonant tunneling detector. The resonant tunneling detector is modeled as a one-dimensional double barrier delta-function potential with its barrier height being sensitive to the charge state of the qubit. The dephasing and the measurement rates show quasi-periodic oscillations as a function of the energy of the incident electron. We show that there exists a phase-sensitive contribution to dephasing, even for a detector with perfect mirror symmetry, which is not observed in a non-resonant detector. We demonstrate that this behavior originates from the abrupt phase change in the reection amplitude, which is not sensitive to the transmission probability, but retains the charge state information.

State and prospects of solar-heliospheric energetic particle research

Energetic particle populations are important constituents of solar, circumplanetary, interplanetary and distant heliospheric plasma structures, and at the same time provide valuable tools for testing models of galactic and universal acceleration and propagation processes. Although both the maximum energies and the variety of plasma processes are restricted by the relatively small size and energy supply of the solar system, these limitations are partly compensated by the superior spatial, temporal, directional and charge state information available for these particles. Both in situ and remote sensing observations contribute to our understanding. Recent advances in these fields will be reviewed, and the expected impact of current and future missions discussed.

Evaluation of Crown Ether Complexation for Elemental Electrospray Mass Spectrometry

Formation of various solvent clusters under mild source conditions and the loss of charge state information and lack of sensitivity under harsh source conditions are the major problems encountered ...

Charge states of solar energetic particles using the geomagnetic cutoff technique: SAMPEX measurements in the 6 November 1997 solar particle event

We report on the ionization states of ∼0.5–50 MeV/nucleon ions in the 6 November 1997 solar particle event using instrumentation on the SAMPEX satellite and the geomagnetic cutoff technique. Using the geomagnetic cutoffs of ∼10 MeV 4He and ∼20 MeV protons, we infer the ionization states of ∼0.5–50 MeV/nucleon C‐Fe by measuring their latitude distributions. The geomagnetic cutoff method extends the measurement of ionization states beyond 10 MeV/nucleon, where charge state information is inaccessible with present electrostatic deflection techniques. In contrast to an increase of the Fe charge state observed above ∼20 MeV/nucleon in events in late 1992, we find in the 6 November 1997 event that Si &amp; Fe charge states increased dramatically across 0.5–50 MeV/nucleon. While the origin of this newly discovered energy dependence is unknown, such significant event to event variations of solar particle charge states should be considered in models of acceleration and transport processes.