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Justification of the width of the tooth spacing and the distance between the rows of teeth of the ripper for the harrower
The article substantiates the degree of immersion of working bodies in the soil and soil deformation on the basis of scientific and experimental studies of the harrowing unit used. The parameters of the harrow teeth, the qualitative performance of the technological process of the accepted parameters are also theoretically justified.
Journal Article
New multi-parameter Golay 2-complementary sequences and transforms
In this work, we develop a new unified approach to the so-called generalized Golay- Rudin-Shapiro (GRS) 2-complementary multi-parameter sequences. It is based on a new generalized iteration generating construction.
Journal Article
Gaussian Process Regression‐Based Bayesian Optimisation (G‐BO) of Model Parameters—A WRF Model Case Study of Southeast Australia Heat Extremes
In Numerical Weather Prediction (NWP) models, such as the Weather Research and Forecasting (WRF) model, parameter uncertainty in physics parameterization schemes significantly impacts model output. Our study adopts a Bayesian probabilistic approach, building on prior research that identified temperature (T) and relative humidity (Rh) as sensitive to three key WRF parameters during southeast Australia's extreme heat events. Using Gaussian process regression‐based Bayesian Optimisation (G‐BO), we accurately estimated the optimal distributions for these parameters. Results show that the default values are outside their corresponding optimal distribution bounds for two of the three parameters, suggesting the need to reconsider these default values. Additionally, the robustness of the optimal parameter distributions is validated by their application to an independent extreme heat event, not included in the optimisation process. In this test, the optimized parameters substantially improved the simulation of T and Rh, highlighting their effectiveness in enhancing simulation accuracy during extreme heat conditions. Plain Language Summary This study aims to enhance the accuracy of a numerical weather model called the Weather Research and Forecasting (WRF) model, especially for simulating extreme heat events in Southeast Australia. Typically, the accuracy of such models depends on specific settings, which are often set to default values. Our research used a method known as Gaussian process regression‐based Bayesian Optimisation (G‐BO) to determine the best range of values for these settings. We found that the default settings were not optimal. By applying G‐BO, we identified more effective values that substantially improved the model's simulations of temperature and humidity during heat extremes. This improvement was consistent even when tested on an independent extreme heat event. These advancements are vital for more accurate weather forecasting, which is essential for emergency services, electricity management, and agriculture planning during extreme heat conditions. Key Points Our study optimizes WRF model parameters for Southeast Australia heat extremes, enhancing the accuracy of the model simulation G‐BO method finds optimal parameter ranges, substantially improving the simulation of temperature and humidity Results suggest updating WRF model's default settings for better extreme heat event simulations
Journal Article
Design of linear parameter‐varying controller for morphing aircraft using inexact scheduling parameters
In this paper, the design problem of Gain‐Scheduled Output‐Feedback (GSOF) controllers using inexact scheduling parameters for morphing aircraft during the wing transition process is addressed. Both the stability of the closed‐loop system and the L2 gain performance can be guaranteed under the controller based on measured (not actual) scheduling parameters. Firstly, the linear parameter‐varying (LPV) model of morphing aircraft is established by Jacobian linearization and the additive uncertainty is introduced into the scheduling parameters. By employing non‐linear transformations, the problem is formulated as the solution to a set of parameter‐dependent linear matrix inequalities (LMI) with a single‐line search parameter. Finally, the robustness of the flight control system to the wing transition process is verified under the condition of both the uncertainty of aerodynamic parameters and of scheduling parameters.
Journal Article
Terminating q-series Summation Formulas by Two Integer Parameters
The paper systematically studies the contiguous relations of terminating 4φ3 -series. Utilizing several relations for the Ωλ,µ -series, we formulate specific identities for the terminating q-series with two integer parameters. Their limiting cases are presented in this paper. Additionally, the previous proof methods for the extension of the adjacent relation of terminating q-series are summarized and analysed.
Journal Article
On 3-parameter generalized quaternions with k-pell-lucas numbers as components
At present, numerous research studies have been conducted on Fibonacci quaternions and their generalizations. Recently, Şentürk and Ünal introduced 3-parameter generalized quaternions. This paper introduces the k-Pell-Lucas 3-parameter generalized quaternions and explores their basic properties and Binet formula. Moreover, by using the Binet formula, some generalized forms of famous sequence identities are given.
Journal Article
Land Processes Can Substantially Impact the Mean Climate State
Terrestrial processes influence the atmosphere by controlling land‐to‐atmosphere fluxes of energy, water, and carbon. Prior research has demonstrated that parameter uncertainty drives uncertainty in land surface fluxes. However, the influence of land process uncertainty on the climate system remains underexplored. Here, we quantify how assumptions about land processes impact climate using a perturbed parameter ensemble for 18 land parameters in the Community Earth System Model version 2 under preindustrial conditions. We find that an observationally‐informed range of land parameters generate biogeophysical feedbacks that significantly influence the mean climate state, largely by modifying evapotranspiration. Global mean land surface temperature ranges by 2.2°C across our ensemble (σ = 0.5°C) and precipitation changes were significant and spatially variable. Our analysis demonstrates that the impacts of land parameter uncertainty on surface fluxes propagate to the entire Earth system, and provides insights into where and how land process uncertainty influences climate. Plain Language Summary Land processes can affect climate by controlling the transfer of energy and water from the land to the atmosphere. Previous research has shown that uncertainty surrounding land processes (e.g., photosynthesis and the movement of water through soils) can drive uncertainty in land‐to‐atmosphere fluxes. However, it remains unclear how much that land uncertainty can impact climate. Here, we quantify how climate is sensitive to assumptions about land processes by varying 18 land model parameters to create an ensemble of 36 possible worlds in a global climate model. Land temperature ranges by 2.2°C across this ensemble, mostly due to changes in how much water is evaporated from the land surface. Changing land parameters also drives regionally variable changes in mean precipitation. This study highlights a large and underappreciated impact of land processes in determining the mean climate state, and provides insights into how climate is influenced by land process uncertainty. Key Points Land processes substantially impact the climatological mean state terrestrial temperature and precipitation Land parameters influence climate predominantly through changing evapotranspiration rather than through other mechanisms Warming driven by land processes activates different atmospheric feedbacks than radiatively‐driven warming
Journal Article
ON THE CENTRE-FOCUS PROBLEM IN SOME LIÉNARD SYSTEMS
A large family of planar systems of ODEs arising from Liénard equations is considered. A Liénard equation (ProQuest: ... denotes formula omitted.) is commonly used in practical problems, in particular in (electro)mechanics. It is well-known that a Liénard equation can be transformed into an autonomous planar system of ODEs of the form x′ = y - F(x), y′ = -g(x), where F′(x) = f(x). In this paper f(x) = 2α2x + 3α3x2 + 4α4x3 and g(x) = c1x + c3x3 + c5x5 + c7x7. In the parameter space (α2,α3,α4,c1,c3,c5,c7) ∈ R7 we consider the center-focus problem and find necessary conditions for the corresponding system having a center at the origin. In the parameter space (α2,α3,α4,c1,c3,c5,c7) ∈ R7 an example with a possible limit cycle and some examples with other complex dynamic behavior are presented.
Journal Article