New Set Of Parameters Research Articles

Search for duplicates of showers in the IAU MDC database

Context. The meteor shower database of the IAU Meteor Data Center (MDC) is used by the whole community of meteor astronomers. Observers submit both new and known meteor shower parameters to the MDC. Two types of problems may arise during the submission process: If a new observation of an already-known meteor shower is submitted as the discovery of a new shower, a duplicate shower will appear in the MDC. If the submission of a new set of parameters for an existing shower is incorrect, a false duplicate of a known meteor shower will appear in the MDC. The MDC database contains such duplicates and false duplicates, so it is desirable to detect them among the streams already in the database and those delivered to the database as new streams. Aims. We aim to develop a method for objective detection of duplicates among meteor showers and to apply it to the MDC. The method will also enable us to verify whether various sets of parameters of the same shower are compatible and thus reveal the false duplicates. Methods. We suggest two methods based on cluster analyses and two similarity functions among geocentric and heliocentric shower parameters collected in the MDC. Results. We obtained a number of results of varying significance. Seven new showers represented by two or more parameter sets were discovered, revealing the duplicates we searched for. We found full agreement between our results and those reported in the MDC database for 30 showers. The multiple sets of parameters defining these showers are correct since they were identified as duplicates. For 20 showers, the same duplicates as given in the MDC were found only by one method. We found 27 showers for which the number of parameter sets found by both methods is close to the corresponding number in the MDC database. However, we found 56 showers listed in the MDC by more than one set of parameters for which no duplicates were found by either of the applied methods. These showers have false duplicates among their sets of parameters. Conclusions. The obtained results confirm the effectiveness of the proposed approach of identifying duplicates. We have shown that in order to detect and verify duplicate meteor showers, it is possible to apply the objective proposal instead of the subjective approach used so far. We consider the identification of 83 problematic cases in the MDC database, among which at least some duplicates were misclassified, to be a particularly important result. The correction of these cases will significantly improve the content of the MDC database.

An approach to classify areas for appropriate rainfall-runoff risk management: A case study in Drevenica basin, Slovakia

Best management practices for landscapes include adapting them to rainfall extremes that have an impact on surface runoff. A critical profile (CP) is a location where a path of concentrated surface runoff might enter an inhabited area causing potential damage, e.g. by flooding, water erosion and torrential mudflows. Critical profiles have been determined using modified methodological guidelines for identifying critical points by the T.G. Masaryk Water Research Institute in Prague, 2009. In the model watershed Drevenica (117.27 km2), 27 profiles have been identified, where concentrated flow paths and the boundaries of built-up areas intersect. Four of the profiles have contributing areas of 0.3–10 km2, average slope ≥ 3.5% and the share of arable land ≥40% as well as the critical conditions indicator according to the methodological guidelines and have been verified in terrain. Surveys and analysis also pointed out that another three profiles have indications of erosion runoff during rainfalls of varying intensity. By modifications of the original thresholds, these profiles have been included as critical. The lower threshold for contributing area was reduced to 0.2 km2. A new set of parameters was added by the authors, namely the proportion of land with higher soil erosion risk levels (SERL) 2 to 5, exceeding 20% and threshold surface runoff volume ≥ 6000 m3. Critical profiles with their contributing areas are prime candidates for multi-functional ecological engineering measures.

Solar Wind Energy Budget Dilemma During Substorms Induced by Interplanetary Shocks

AbstractInterplanetary (IP) shocks can trigger substorms when they interact the magnetosphere. In study of Hajra and Tsurutani (2018, https://doi.org/10.1016/0032-0633(77)90001-0), they reported a shock‐induced substorm event where the energy dissipation exceeded the energy input ( parameter). In this study, we examined 198 IP shock‐induced substorms from 1995 to 2021 and found 32 underpowered events where the energy dissipation exceeded the energy input calculated from IP shock sheath parameters. We also found underpowered events using other newly developed energy functions. To resolve this dilemma, we introduce the concept of dual compressions of the interplanetary magnetic field by both the IP shock and the bow shock, respectively. Based on in situ observations in the magnetosheath, we obtained a set of new parameters from the dual compressions. The stronger magnetic field resulting from the double compressions reconnects the geomagnetic field, leading to an increased input of energy into the magnetosphere. This new energy input is generally sufficient to balance the energy dissipation.

The 2023 GOLD Report: Updated Guidelines for Inhaled Pharmacological Therapy in Patients with Stable COPD.

Over the past 22years, annual GOLD Reports have documented important changes in guidance and recommendations for uniformly treating patients with chronic obstructive pulmonary disease (COPD) with the goal of improving outcomes in patients suffering from this condition. The most recent GOLD Report, released in 2023, shows continued refinement in several areas, including more precise definitions of COPD and exacerbations of COPD, a new set of parameters to assess exacerbation severity, an updated COPD assessment tool, updated guidelines for initial and follow-up treatment, new information regarding the association between pharmacological triple therapy and reduction in mortality, and new discussions of inhaler device choice and adherence to COPD medications. Whereas we do not address all of the new or updated material in GOLD's 2023 Report, we summarize key changes in GOLD's recommendations regarding inhalation therapy for stable COPD and frame these changes in the context of previous GOLD recommendations.

Estimating the Size of Clustered Hidden Populations

Abstract Successive sampling population size estimation (SS-PSE) is a method used by government agencies, aid organizations, and researchers around the world to estimate the size of hidden populations using data from respondent-driven sampling surveys. SS-PSE addresses a specific need in estimation, since many countries rely on having accurate size estimates to plan and allocate finite resources to address the needs of hidden populations. However, SS-PSE relies on several assumptions, one of which requires the underlying social network of the hidden population to be fully connected. We propose two modifications to SS-PSE for estimating the size of hidden populations whose underlying social network is composed of disjoint clusters. The first method is a theoretically straightforward extension of SS-PSE, but it relies on prior information that may be difficult to obtain in practice. The second method extends the Bayesian SS-PSE model by introducing a new set of parameters that allow for clustered estimation without requiring the additional prior information. After providing theoretical justification for both novel methods, we then assess their performance using simulations and apply the Clustered SS-PSE method to a population of internally displaced persons in Bamako, Mali.

Center of Pressure Behavior in Response to Unexpected Base of Support Shifting: A New Objective Tool for Dynamic Balance Assessment.

The translation of the base of support represents a promising approach for the objective assessment of dynamic balance control. Therefore, this study aimed to present a servo-controlled, electrically driven movable plate and a new set of parameters based on the center-of-pressure (CoP) trajectory. Twenty subjects were assessed on a force platform screwed over a movable plate that could combine the following settings: direction (forward (FW) and backward (BW)), displacement (25 mm, 50 mm, and 100 mm), and ramp rate (100 mm/s and 200 mm/s). The subjects underwent two sets of 12 trials randomly combining the plate settings. From the CoP trajectory of the 2.5 s time window after the perturbation, the 95% confidence-interval ellipse (Area95) and the CoP mean velocity (Unit Path) were calculated. Within the same time window, the first peak (FP), the maximal oscillations (ΔCoPMax), and the standard deviation (PPV) of the CoP anterior-posterior trajectory were calculated. The plate direction (p < 0.01), ramp rate (p < 0.001), and displacement (p < 0.01) affected the Area95, FP, and ΔCoPMax, while the Unit Path and PPV were influenced only by the ramp rate (p < 0.001) and displacement (p < 0.001). The servo-controlled, electrically driven movable plate and the CoP-related parameters presented in this study represent a new promising objective tool for dynamic balance assessment.

The SPIDER Pulse Plant Configuration Environment

At the ITER Neutral Beam Test Facility, the Source for the Production of Ions of Deuterium Extracted from Radio frequency plasma (SPIDER) has been in operation since 2018 aiming at prototyping the heating and diagnostic neutral beam appliances in view of the ITER demanding requirements for plasma burning conditions and instabilities control. For the sake of safety, machine protection and efficiency it is necessary to follow an accurate planning strategy and approval action of the experiment parameter settings. Although the initial tools available for the SPIDER integrated commissioning and early campaigns offered the basic functionality to perform the necessary tasks, there were a set of relevant issues that were identified as needing improvements for an efficient and safe configuration environment. Namely, the fact that there were no tools indicating the parameters change since the previous pulse, or the lack of a comparison tool between a new set of parameters and a previous setup, demanded a tedious and error prone verification of all parameters in the sequence. Moreover, several verifications should be automated according to the machine safety limits, increasing the safety check by human and automated machine (algorithmic) validation. This contribution depicts (i) the approval sequence designed for SPIDER safe operation; (ii) the configuration environment requirements according to the SPIDER pulse preparation procedure; (iii) the decision of the development tools used for implementation and design; (iv) the implementation details and preliminary tests of the global environment.

Parameterization and validation of a new AMBER force field for an oxovanadium (IV) complex with therapeutic potential implications in Alzheimer's disease

The scarcity of efficient force fields to describe metal complexes may be a problem for new advances in medicinal chemistry. Thus, the development of force fields for these compounds can be valuable for the scientific community, especially when it comes to molecules that show interesting outputs regarding potential treating of diseases. Vanadium complexes, for instance, have shown promising results towards therapeutics of Alzheimer's Disease, most notably the bis(maltolato)oxovanadium (IV). Therefore, the mainly goal of this work is to develop and validate a new set of parameters for this vanadium complex from a minimum energy structure, obtained by DFT calculations, where great results of the new force field are found when confronted with experimental and quantum reference values. Moreover, the new force field showed to be quite effective to describe the molecule of under study whilst GAFF could not describe it effectively. In addition, a case study points out hydrogen bonds in the vanadium complex-PTP1B system.

Joint longitudinal model-based meta-analysis of FEV1 and exacerbation rate in randomized COPD trials.

Model-based meta-analysis (MBMA) is an approach that integrates relevant summary level data from heterogeneously designed randomized controlled trials (RCTs). This study not only evaluated the predictability of a published MBMA for forced expiratory volume in one second (FEV1) and its link to annual exacerbation rate in patients with chronic obstructive pulmonary disease (COPD) but also included data from new RCTs. A comparative effectiveness analysis across all drugs was also performed. Aggregated level data were collected from RCTs published between July 2013 and November 2020 (n = 132 references comprising 156 studies) and combined with data used in the legacy MBMA (published RCTs up to July 2013 - n = 142). The augmented data (n = 298) were used to evaluate the predictive performance of the published MBMA using goodness-of-fit plots for assessment. Furthermore, the model was extended including drugs that were not available before July 2013, estimating a new set of parameters. The legacy MBMA model predicted the post-2013 FEV1 data well, and new estimated parameters were similar to those of drugs in the same class. However, the exacerbation model overpredicted the post-2013 mean annual exacerbation rate data. Inclusion of year when the study started on the pre-treatment placebo rate improved the model predictive performance perhaps explaining potential improvements in the disease management over time. The addition of new data to the legacy COPD MBMA enabled a more robust model with increased predictability performance for both endpoints FEV1 and mean annual exacerbation rate.

Armature Design Recommendations Based on Action Parameters

Force resolution over a C-armature reveals a large Lorentz force that acts to push the armature into rails. Large contact forces lead to a multitude of problems and efficiency losses. This article introduces a set of new parameters called action parameters (APs): armature action and action constant. These parameters optimize armature–rail (A/R) contact force to desired levels and improve muzzle velocity and launcher efficiency. The kinetic energy increases by 7.56 times for the case considered in this article. However, issues regarding loss of compliance and contact force fluctuations arising from optimizing C-armature unveil the need to develop a new armature design. It is recommended that the new armature should have a monolithic design, mechanical load carrying capacity, compliance, and a short current path. Such a hybrid armature design is proposed, and the design process is described.

GAFF-AIC: reoptimisation of the GAFF force field for realistic densities and viscosities in aromatic isocyanates

ABSTRACT Molecular mechanical force field methods, which help to investigate material properties beyond molecular scales, describe the intra- and intermolecular interactions of molecules assuming a classical force field comprised of several terms. Force fields should accurately describe the energy interactions of all moleculer elements to, eventually, accurately reproduce macromolecular properties of that materials. In the case of aromatic isocyanates, general purpose force fields failed to properly account for molecular interactions and, consequently, at the prediction of macromolecular properties of isocyanate-based materials. The present study presents a new force field based on the General AMBER Force Field (GAFF), namely GAFF-AIC, which shows improved results for the prediction of macromolecular properties, in particular density and viscosities, of materials based on aromatic isocyanates. For that, a new set of parameters for intramolecular and intermolecular interactions has been optimised by means of a least square fitting. It is shown that GAFF-AIC is able to accurately reproduce the experimental density and viscosity of liquid 1-naphtyl isocyanate. Moreover, these newly proposed force field parameters were evaluated to see how efficient they were at predicting the liquid densities and viscosities for several considered aromatic isocyanates, resulting in an accurate estimation that is in excellent agreement with experimental results.

Coarse-Grained Modeling of the SARS-CoV-2 Spike Glycoprotein by Physics-Informed Machine Learning

Coarse-grained (CG) modeling has defined a well-established approach to accessing greater space and time scales inaccessible to the computationally expensive all-atomic (AA) molecular dynamics (MD) simulations. Popular methods of CG follow a bottom-up architecture to match properties of fine-grained or experimental data whose development is a daunting challenge for requiring the derivation of a new set of parameters in potential calculation. We proposed a novel physics-informed machine learning (PIML) framework for a CG model and applied it, as a verification, for modeling the SARS-CoV-2 spike glycoprotein. The PIML in the proposed framework employs a force-matching scheme with which we determined the force-field parameters. Our PIML framework defines its trainable parameters as the CG force-field parameters and predicts the instantaneous forces on each CG bead, learning the force field parameters to best match the predicted forces with the reference forces. Using the learned interaction parameters, CGMD validation simulations reach the microsecond time scale with stability, at a simulation speed 40,000 times faster than the conventional AAMD. Compared with the traditional iterative approach, our framework matches the AA reference structure with better accuracy. The improved efficiency enhances the timeliness of research and development in producing long-term simulations of SARS-CoV-2 and opens avenues to help illuminate protein mechanisms and predict its environmental changes.

Optimizing the placement of numerical relativity simulations using a mismatch predicting neural network

Gravitational wave observations from merging compact objects are becoming commonplace, and as detectors improve and gravitational wave sources become more varied, it is increasingly important to have dense and expansive template banks of predicted gravitational waveforms. Since numerical relativity is the only way to fully solve the nonlinear merger regime of general relativity for comparably massed systems, numerical relativity simulations are critical for gravitational wave detection and analysis. These simulations are computationally expensive, with each simulation placing one point within the high dimensional parameter space of binary black hole coalescences. This makes it important to have a method of placing new simulations in ways that use our computational resources optimally while ensuring sufficient coverage of the parameter space. Accomplishing this requires predicting the impact of a new set of parameters before performing the simulation. To this effect, this paper introduces a neural network to predict the mismatch between the gravitational waves of two binary systems. Using this network, we then show how we can propose new numerical relativity simulations that will provide the most benefit. We also use the network to identify gaps in existing public catalogs and identify degeneracies in the binary black hole parameter space.

Polar Codes for Module-LWE Public Key Encryption: The Case of Kyber

In modern society, the Internet is one of the most used means of communication. Thus, secure information transfer is inevitably of major importance. Computers nowadays use encryption methods based on arithmetic operations to turn messages into ciphertexts that are practically impossible for an attacker to reverse-engineer using a classical computer. Lately, it has been proven that this is possible in a post-quantum setting where quantum computers of considerable size are available to attackers. With the advance of technology of quantum computers, it is now more necessary than ever before to construct encryption schemes that cannot be broken either using a classical or a quantum computer. The National Institute of Technology and Standards (NIST) has orchestrated a competition, and numerous encryption schemes have been proposed. The NIST has identified one algorithm to be standardized for the post-quantum era. This algorithm is called CRYSTALS-Kyber and is based on module learning with errors (MLWE). This paper investigates how to apply error correcting codes in order to create some excess decryption failure rate (DFR) and to take advantage of that in order to re-tune Kyber’s parameters in the pursuit of higher security. By applying Polar Codes, Kyber’s security was managed to be increased by 54.4% under a new set of parameters, while keeping the decryption failure rate well below the upper acceptable bound set by the NIST.

Development of a new force field for the family of primary aliphatic amines using the three steps systematic parameterization procedure

The applicability of the three steps systematic parametrization procedure (3SSPP) to develop a force field for primary amines was evaluated in the present work. Previous simulations of primary amines show that current force fields (FF) can underestimate some experimental values under room conditions. Therefore, we propose a new set of parameters, for an united atom (UA) model, that can be used for short and long amines which predict correctly thermodynamic and dynamical properties. Following the 3SSPP methodology, the partial charges are chosen to match the experimental dielectric constant whereas the Lennard-Jones (LJ) parameters, ε and σ, are fitted to reproduce the surface tension at the vapor-liquid interface and the liquid density, respectively. Simulations were initially conducted for the propylamine molecule by introducing three different types of carbon atoms, Cα and Cβ, with electric charges, and Cn, without charge. Then, modifying the charges of the carbons and using the transferable LJ parameters, the new set of constants for long amines were found. The results show good agreement for the experimental dielectric constant and mass density with a percentage error less than 1% surface tension the error is up to 4% ethylamine, the new charges were obtained from a fitting function calculated from the long amines results. For these molecules, the values of the dielectric constant and the surface tension present errors of the order of 10% with the experimental data. Miscibility of the amines was also tested with the new parameters and the results show reasonable agreement with experiments.

Solubility of CO2 in Aqueous Formic Acid Solutions and the Effect of NaCl Addition: A Molecular Simulation Study.

There is a growing interest in the development of routes to produce formic acid from CO2, such as the electrochemical reduction of CO2 to formic acid. The solubility of CO2 in the electrolyte influences the production rate of formic acid. Here, the dependence of the CO2 solubility in aqueous HCOOH solutions with electrolytes on the composition and the NaCl concentration was studied by Continuous Fractional Component Monte Carlo simulations at 298.15 K and 1 bar. The chemical potentials of CO2, H2O, and HCOOH were obtained directly from single simulations, enabling the calculation of Henry coefficients and subsequently considering salting in or salting out effects. As the force fields for HCOOH and H2O may not be compatible due to the presence of strong hydrogen bonds, the Gibbs-Duhem integration test was used to test this compatibility. The combination of the OPLS/AA force field with a new set of parameters, in combination with the SPC/E force field for water, was selected. It was found that the solubility of CO2 decreases with increasing NaCl concentration in the solution and increases with the increase of HCOOH concentration. This continues up to a certain concentration of HCOOH in the solution, after which the CO2 solubility is high and the NaCl concentration has no significant effect.

A new approach to pollution vulnerability assessment in aquifers using K-means analysis

The most used methods to evaluate the vulnerability to contamination of aquifers are based on overlay index maps, such us DRASTIC, GOD and AVI. These methods assign weighting and rating values to hydrogeological characteristics, introducing subjectivity in the evaluation. In this research, a new methodology is proposed to eliminate some of that subjectivity. The methodology evaluates the vulnerability to contamination of a detrital aquifer using K-means cluster analysis with a new set of parameters. The set is composed of some parameters extracted from these methods, as well as other new ones that have a significant influence on the movement of contaminants. Application of the Principal Components Analysis (PCA) technique before using K-means cluster allowed the selection of the most relevant parameters. To validate the methodology, this was applied to a detrital aquifer located at central Spain (the so-called “Aluviales Jarama-Tajuña” aquifer) with a significant agricultural development. To compare the traditional methods of vulnerability assessment with the K-means cluster, nitrate concentration was used as a pollution indicator. Thus, 23 groundwater quality samples were used to correlate (Spearman´s correlation coefficient) the vulnerability values with nitrate concentration to validate the most suitable method. The results showed that GOD and AVI were not appropriate methods to evaluate the vulnerability of the aquifer, because they have negative or very low correlation with nitrate concentration (− 0.5 and 0.01, respectively). This is due to the use of very few variables that do not represent relevant features for the vulnerability assessment. Alternatively, DRASTIC and K-means cluster analysis obtained higher Spearman´s correlation coefficients (0.34 and 0.48, respectively). The relevant features selected by PCA analysis to use in the K-means low-dimensional analysis were depth of groundwater (D), net recharge (R), and land use (L). The new proposed method grouped data in three clusters that represent low vulnerability (35.9% of the study area), moderate (41.4%) and high vulnerability (22.7%). K-means increases the Spearman’s correlation by 14% with respect to the most approximate conventional method (DRASTIC). Therefore, the results obtained confirm the advantage of joint application of PCA and K-Means analysis, which represents a novel approach for the assessment of groundwater vulnerability in detrital aquifers.

Parameterized Tropical Cyclone Precipitation Model for Catastrophe Risk Assessment in China

Abstract Inland flooding and mudslides from tropical cyclone (TC) rainstorms are among the most destructive natural hazards in China, resulting in considerable direct economic losses and large numbers of fatalities. In this paper, a TC precipitation model (TCPM) is improved by incorporating the effects of complex terrain through a set of new parameters (e.g., slope, roughness, and attenuation distance) for a more accurate assessment of TC rainfall hazards in China. Moreover, by introducing parameterized spiral rainbands, the model could more accurately capture the intensity of extreme precipitation. The model comprehensively considers dynamic and thermodynamic precipitation factors and is adept at capturing the climate characteristics of TC precipitation and the probability distribution of extreme TC precipitation in China. The model is verified by providing two comparisons. One is analysis including detailed results of three typical TC cases, and the other uses empirical cumulative distribution functions for extreme observations and simulations of historical landfalling TCs in China during the period 1960–2018. The comparisons reveal that the TCPM shows impressive performance for strong TCs with heavy precipitation within 200–300 km of the TC center. Moreover, both the modeled extreme hourly and total TC precipitation probability distributions are consistent with the observations. However, the model needs to be further improved for TCs with dispersive or long-distance precipitation. Significance Statement In this paper, an optimized and physics-based model for the simulation of tropical cyclone precipitation is described and used to estimate the risk of TC rainfall hazards in China. The work is innovative in that it considers the effect of complex terrain from three perspectives, including slope, roughness, and attenuation distance. The simulations demonstrated that the model is adept at capturing the main climate characteristics of TC precipitation and the probability distribution of extreme TC precipitation in China, which is simple to run several hundred thousand times, with bright application prospects in catastrophe risk assessment.

Accurate Description of Solvent-Exposed Salt Bridges with a Non-polarizable Force Field Incorporating Solvent Effects.

The strength of salt bridges resulting from the interaction of cations and anions is modulated by their environment. However, polarization of the solvent molecules by the charged moieties makes the accurate description of cation-anion interactions in an aqueous solution by means of a pairwise additive potential energy function and classical combination rules particularly challenging. In this contribution, aiming at improving the representation of solvent-exposed salt-bridge interactions with an all-atom non-polarizable force field, we put forth here a parametrization strategy. First, the interaction of a cation and an anion is characterized by hybrid quantum mechanical/molecular mechanics (QM/MM) potential of mean force (PMF) calculations, whereby constantly exchanging solvent molecules around the ions are treated at the quantum mechanical level. The Lennard-Jones (LJ) parameters describing the salt-bridge ion pairs are then optimized to match the reference QM/MM PMFs through the so-called nonbonded FIX, or NBFIX, feature of the CHARMM force field. We apply the new set of parameters, coined CHARMM36m-SBFIX, to the calculation of association constants for the ammonium-acetate and guanidinium-acetate complexes, the osmotic pressures for glycine zwitterions, guanidinium, and acetate ions, and to the simulation of both folded and intrinsically disordered proteins. Our findings indicate that CHARMM36m-SBFIX improves the description of solvent-exposed salt-bridge interactions, both structurally and thermodynamically. However, application of this force field to the standard binding free-energy calculation of a protein-ligand complex featuring solvent-excluded salt-bridge interactions leads to a poor reproduction of the experimental value, suggesting that the parameters optimized in an aqueous solution cannot be readily transferred to describe solvent-excluded salt-bridge interactions. Put together, owing to their sensitivity to the environment, modeling salt-bridge interactions by means of a single, universal set of LJ parameters remains a daunting theoretical challenge.

On the Configurations of Closed Kinematic Chains in Three-dimensional Space

A kinematic chain in three-dimensional Euclidean space consists of $n$ links that are connected by spherical joints. Such a chain is said to be within a closed configuration when its link lengths form a closed polygonal chain in three dimensions. We investigate the space of configurations, described in terms of joint angles of its spherical joints, that satisfy the the loop closure constraint, meaning that the kinematic chain is closed. In special cases, we can find a new set of parameters that describe the diagonal lengths (the distance of the joints from the origin) of the configuration space by a simple domain, namely a cube of dimension $n-3$. We expect that the new findings can be applied to various problems such as motion planning for closed kinematic chains or singularity analysis of their configuration spaces. To demonstrate the practical feasibility of the new method, we present numerical examples.