Lower Bound Research Articles

Mukai models and Borcherds products

abstract: Let ${\Fgn}$ be the moduli space of $n$-pointed $K3$ surfaces of genus $g$ with at worst rational double points. We establish an isomorphism between the ring of pluricanonical forms on ${\Fgn}$ and the ring of certain orthogonal modular forms, and give applications to the birational type of ${\Fgn}$. We prove that the Kodaira dimension of ${\Fgn}$ stabilizes to $19$ when $n$ is sufficiently large. Then we use explicit Borcherds products to find a lower bound of $n$ where ${\Fgn}$ has nonnegative Kodaira dimension, and compare this with an upper bound where ${\Fgn}$ is unirational or uniruled using Mukai models of $K3$ surfaces in $g\leq 20$. This reveals the exact transition point of Kodaira dimension in some~$g$.

Heritability of cerebellar subregion volumes in adolescent and young adult twins.

Twin studies have found gross cerebellar volume to be highly heritable. However, whether fine-grained regional volumes within the cerebellum are similarly heritable is still being determined. Anatomical MRI scans from two independent datasets (QTIM: Queensland Twin IMaging, N = 798, mean age 22.1 years; QTAB: Queensland Twin Adolescent Brain, N = 396, mean age 11.3 years) were combined with an optimised and automated cerebellum parcellation algorithm to segment and measure 28 cerebellar regions. We show that the heritability of regional volumetric measures varies widely across the cerebellum ( 47%-91%). Additionally, the good to excellent test-retest reliability for a subsample of QTIM participants suggests that non-genetic variance in cerebellar volumes is due primarily to unique environmental influences rather than measurement error. We also show a consistent pattern of strong associations between the volumes of homologous left and right hemisphere regions. Associations were predominantly driven by genetic effects shared between lobules, with only sparse contributions from environmental effects. These findings are consistent with similar studies of the cerebrum and provide a first approximation of the upper bound of heritability detectable by genome-wide association studies.

Repurposing of drugs against bacterial infections: A pharmacovigilance-based data mining approach.

The World Health Organization (WHO) has published a list of priority pathogens that urgently require research to develop new antibiotics. The main aim of the current study is to identify potential marketed drugs that can be repurposed against bacterial infections. A pharmacovigilance-based drug repurposing approach was used to identify potential drugs. OpenVigil 2.1 tool was used to query the FDA Adverse Event Reporting System database. The reporting odds ratio (ROR) < 1, ROR95CI upper bound <1, and no. of cases ≥30 were used for filtering and sorting of drugs. Sunburst plot was used to represent drugs in a hierarchical order using the Anatomical Therapeutic Chemical classification. Molecular docking and dynamics were performed using the Maestro and Desmond modules of Schrodinger 2023 software respectively. A total of 40 drugs with different classes were identified based on the pharmacovigilance approach which has antibacterial potential. The molecular docking results have shown energetically favored binding conformation of lisinopril against 3-deoxy-manno-octulosonate cytidylyltransferase, UDP-2,3-diacylglucosamine hydrolase, and penicillin-binding protein 3 (PBP3) of Pseudomonas aeruginosa; olmesartan, atorvastatin against lipoteichoic acids flippase LtaA and rosiglitazone and varenicline against d-alanine ligase of Staphylococcus aureus; valsartan against peptidoglycan deacetylase (SpPgdA) and atorvastatin against CDP-activated ribitol for teichoic acid precursors of Streptococcus pneumoniae. Further, molecular dynamic results have shown the stability of identified drugs in the active site of bacterial targets except lisinopril with PBP3. Lisinopril, olmesartan, atorvastatin, rosiglitazone, varenicline, and valsartan have been identified as potential drugs for repurposing against bacterial infection.

Reconfigurable Intelligent Surface Assisted Target Three-Dimensional Localization with 2-D Radar

Battlefield surveillance radar is usually 2-D radar, which cannot realize target three-dimensional localization, leading to poor resolution for the air target in the elevation dimension. Previous researchers have used the Traditional Height Finder Radar (HFR) or multiple 2-D radar networking to estimate the target three-dimensional location. However, all of them face the problems of high cost, poor real-time performance and high requirement of space–time registration. In this paper, Reconfigurable Intelligent Surfaces (RISs) with low cost are introduced into the 2-D radar to realize the target three-dimensional localization. Taking advantage of the wide beam of 2-D radar in the elevation dimension, several Unmanned Aerial Vehicles (UAVs) carrying RISs are set in the receiving beam to form multiple auxiliary measurement channels. In addition, the traditional 2-D radar measurements combined with the auxiliary channel measurements are used to realize the target three-dimensional localization by solving a nonlinear least square problem with a convex optimization method. For the proposed RIS-assisted target three-dimensional localization problem, the Cramer–Rao Lower Bound (CRLB) is derived to measure the target localization accuracy. Simulation results verify the effectiveness of the proposed 3-D localization method, and the influences of the number, the positions and the site errors of the RISs on the localization accuracy are covered.

On a sharp estimate of overlapping Schwarz methods in H(curl; Ω) and H(div; Ω)

Abstract The previously proved upper bound is $C\big(1+\frac{H^{2}}{\delta ^{2}}\big)$ for the condition number of the discrete system arising from the classical two-level overlapping Schwarz method for symmetric positive definite problems in $\boldsymbol{H}(\textbf{curl}; \varOmega )$ and $\boldsymbol{H}(\textrm{div}; \varOmega )$, where $H$ and $\delta $ are the sizes of subdomains and overlap, respectively. But all numerical results indicate that a sharper bound is $C\big (1+ \frac{H}{\delta } \big )$. In this work, we prove that the condition number is indeed bounded above by $C\big(1+\frac{H}{\delta }\big)$.

Ad Optimization Via Machine Learning: A Focus on Upper Confidence Bound and Thompson Sampling Algorithms

The objective of this project is to improve the effectiveness and efficiency of advertising on various platforms by utilizing advanced algorithms, namely the Upper Confidence Bound and Thompson Sampling Algorithm. The project aims to find a balance between exploring new advertising strategies and exploiting proven high-performing approaches. By implementing these bandit algorithms, the project aims to dynamically optimize ad placements, formats, and targeting to maximize user engagement and ad revenue. The methodology involves an iterative process of data collection, analysis, and adaptation. The initial phases include defining project objectives, understanding the target audience, and reviewing the current ad strategy. The Upper Confidence Bound algorithm enables intelligent decision-making by assigning confidence bounds to different ad strategies, allowing for efficient exploration and exploitation. On the other hand, the Thompson Sampling algorithm, rooted in Bayesian principles, dynamically adapts based on observed outcomes, striking a balance between exploration and exploitation through probabilistic reasoning. In summary, this Ads Optimization Project utilizes the power of the Upper Confidence Bound and Thompson Sampling algorithms to create a data-driven, adaptive, and user-centric approach to advertising. The ultimate goal is to achieve optimal user engagement and ad revenue.

#260 Epidemiology of immunoglobulin A nephropathy (IgAN) in Germany

Abstract Background and Aims Immunoglobulin A nephropathy (IgAN) is a rare kidney disease characterized by proteinuria, persistent micro- or macrohematuria, and arterial hypertension. It can take a variety of courses from long-term minor symptoms to rapid progressive loss of kidney function with terminal renal failure. Epidemiological measures often refer to the proportion of IgAN among patients with glomerulonephritis instead of the entire population. Therefore, we estimated the prevalence and incidence of IgAN in Germany. Method Statutory health insurance (SHI) claims data from a large German database (InGef research database) with approximately four million insurees was retrospectively analyzed. The database represents about 5% of the German population and is representative of the German demographic and clinical structure in terms of age, gender, region, morbidity, mortality, and medication usage. As there is no specific IgAN code in ICD-10-GM and coding practices vary between physicians, two algorithms with different sets of codes were developed to estimate a lower and upper bound of the 1-year prevalence and incidence from 2017-2022. The lower bound considered specific diagnosis codes which usually rely on biopsies (N00.3, N02.3, N06.3). The upper bound included a broader field of specific and unspecific codes (N00.3, N02.3, N02.5, N02.7, N02.8, N02.9, N06.3, N06.8) that are potentially used by physicians to diagnose IgAN. Identified patients were described in terms of age and gender. Results were extrapolated to the German overall population, and a trend for the upcoming five years was estimated by applying the mean prevalence and incidence from the years 2017 to 2022 to the forecasted German population for the years 2023 to 2027. Results In 2022, the 1-year prevalence of IgAN ranged from 5 (lower bound) to 38 (upper bound) per 100 000 individuals in Germany. This corresponds to approximately 4 000 and 32 200 affected patients in Germany, respectively. There was no significant change from 2017 to 2022 with mean rates ranging from 4 (lower bound) to 38 (upper bound) per 100 000 individuals in Germany. The number of prevalent patients in Germany is expected to slowly increase in the coming years due to a forecasted increasing German overall population. About 57% of the prevalent IgAN patients in 2022 were male and the mean age was 59 years for the upper bound. For the lower bound about 73% of the prevalent IgAN patients in 2022 were male and the mean age was 53. The 1-year incidence of IgAN in 2022 ranged from 0.2 (lower bound) to 0.6 (upper bound) per 100 000 individuals in Germany. Extrapolation to the German population resulted in 164 to 538 newly diagnosed IgAN patients, respectively. Both the lower and the upper bound remained stable from 2017 to 2022 with slight fluctuations and a mean incidence rate of 0.2 (lower bound) and 0.6 (upper bound) per 100 000. The trend estimation showed steady numbers of incident patients in Germany until 2027 with a minor tendency towards an increase. About 86% (lower bound) and 83% (upper bound) of the incident IgAN patients in 2022 were male and the mean age was 36 years (lower bound) and 44 years (upper bound). Conclusion Estimating the epidemiology of IgAN is challenging as physicians use different ICD codes for diagnosis. To capture the uncertainty, an upper and lower bound of the prevalence and incidence were assessed as a minimum and maximum of patient numbers. Overall, IgAN was shown to be a rare disease with a prevalence of less than 50 per 100 000 in Germany. The upper bound of the incidence rate dropped in 2020 which may be associated with the onset of the global COVID-19 pandemic in March 2020, but the rate picked up in 2021 and the lower bound did not indicate an effect caused by the pandemic. Due to the forecasted rising population in Germany until 2027, the total number of prevalent and incident IgAN patient is expected to increase slowly.

Studying the Upper Bounds of the Numbers of Zeros of Abelian Integrals by the Law of Polynomials

For the quadratic reversible systems of genus one, all of their periodic orbits are higher-order algebraic curves. When they are perturbed by polynomials of degree [Formula: see text], the numbers of zeros of their Abelian integrals will change and we study the upper bounds of these numbers by using the methods of Riccati equation and Picard–Fuchs equation. We consider both the highest and lowest degrees of polynomials, and more importantly, we consider the law of polynomials and the range of values for their variables. Consequently, some laws of the polynomials are discovered and many upper bounds are obtained, and these upper bounds are sharper than the results obtained by other techniques.

No selection lemma for empty triangles

Abstract Let P be a set of n points in general position in the plane. The Second Selection Lemma states that for any family of $$\Theta(n^3)$$ Θ ( n 3 ) triangles spanned by P, there exists a point of the plane that lies in a constant fraction of them. For families of $$\Theta(n^{3-\alpha})$$ Θ ( n 3 - α ) triangles, with $$0\le \alpha \le 1$$ 0 ≤ α ≤ 1 , there might not be a point in more than $$\Theta(n^{3-2\alpha})$$ Θ ( n 3 - 2 α ) of those triangles. An empty triangle of P is a triangle spanned by P not containing any point of P in its interior. Bárány conjectured that there exists an edge spanned by P that is incident to a super-constant number of empty triangles of P. The number of empty triangles of P might be as low as $$\Theta(n^2)$$ Θ ( n 2 ) ; in such a case, on average, every edge spanned by P is incident to a constant number of empty triangles. The conjecture of Bárány suggests that for the class of empty triangles the above upper bound might not hold. In this paper we show that, somewhat surprisingly, the above upper bound does in fact hold for empty triangles. Specifically, we show that for any integer n and real number $$0\leq \alpha \leq 1$$ 0 ≤ α ≤ 1 there exists a point set of size n with $$\Theta(n^{3-\alpha})$$ Θ ( n 3 - α ) empty triangles such that any point of the plane is only in $$O(n^{3-2\alpha})$$ O ( n 3 - 2 α ) empty triangles.

Outlier‐resistant state estimation for complex networks with random false data injection attacks under encoding–decoding mechanism

SummaryThis article focuses on the outlier‐resistant state estimation problem for discrete time‐varying complex networks (TVCNs) affected by random false data injection attacks (FDIAs) under an encoding–decoding mechanism (EDM). From the perspective of information security, a uniform‐quantization‐based EDM is employed to encrypt the transmitted data. During the data transmission process, a set of independent random variables governed by Bernoulli distribution is introduced to characterize the occurrence of random FDIAs. For the purpose of alleviating the passive impact of potential measurement outliers, a saturation structure is adopted during the estimator design. The gain matrix is given by minimizing the upper bound of estimation error covariance. According to the stochastic analysis method, it is shown that the state estimation error is bounded exponentially in mean‐square sense by providing new sufficient condition. It should be noted that we make the first attempt to develop new outlier‐resistant state estimation method with performance evolution criterion in the time‐varying perspective for TVCNs with random FDIAs under EDM. Finally, a simulation example with comparative experiment is presented to illustrate the effectiveness of the newly presented outlier‐resistant estimation algorithm.

A comparative lattice analysis of $SU(2)$ dark glueball

Abstract We study the mass and scattering cross section of $SU(2)$ glueballs as dark matter candidates using lattice simulations. We employ both naive and improved $SU(2)$ gauge actions in $3+1$ dimensions with several $\beta$ values, and adopt both the traditional Monte Carlo method and the flow-based model based on machine learning techniques to generate lattice configurations. The mass of dark scalar glueball with $J^{PC}=0^{++}$ and the NBS wave function are calculated. &amp;#xD;Using a coupling constant of $\beta=2.2$ as an illustration, we compare the dark glueball mass calculated from the configurations generated from the two methods. While consistent results can be achieved, the two methods demonstrate distinct advantages. Using the Runge-Kutta method, we extract the glueball interaction potential and two-body scattering cross section. From the observational constraints, we obtain the lower bound of the mass of scalar glueball as candidates of dark matter. Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Article funded by SCOAP3 and published under licence by Chinese Physical Society and the Institute of High Energy Physics of the Chinese Academy of Science and the Institute of Modern Physics of the Chinese Academy of Sciences and IOP Publishing Ltd.

Transitive Subtournaments of k-th Power Paley Digraphs and Improved Lower Bounds for Ramsey Numbers

Transitive Subtournaments of k-th Power Paley Digraphs and Improved Lower Bounds for Ramsey Numbers

Assessment of Organochlorine Pesticide Residue Levels in Fruits and Vegetables Sold in Federal Capital Territory (FCT), Nigeria

The study evaluated the organochlorine pesticide residue levels in fruits and vegetables sold in Federal Capital Territory, Abuja. Six samples were bought from eleven major markets across the six Area Councils of FCT, Abuja. The samples were mixed to form composite groups of the fruits and vegetables, and prepared using QuEChERS method. It was analysed using Agilent 7890 Gas Chromatography equipped with a micro-cell Electron Capture Detector (μECD). The analysis revealed that the hazard index (HI) for all the fruits and vegetables studied were well below the levels of adverse health effect for chronic exposure except for Onion in children which was 1.2287. The HI for the various fruits and vegetables in children were higher than those for the adult. For example, the HI for Tomato, Green Amaranth Leaves and Pepper all in children were 0.4485, 0.4411 and 0.3981 respectively while the HI for Tomato, Green Amaranth Leaves and Pepper all in adult were 0.1121, 0.1103 and 0.0995 respectively. The calculated cancer risk associated with the consumption of these fruits and vegetable showed values well below the upper bound of 1.0x10-6 except for Aldrin, Dieldrin, Heptachlor, Heptachlor Epoxide. a-BHC, b-BHC, and d-BHC especially in children. From the hazard index and cancer risk analysis, Aldrin and Dieldrin have been implicated as the pesticides of concern since they were present in reasonable concentrations for almost all the samples and age groups studied. The highest potential of cancer risk was found in Onions for children. Also, the total cancer risk implicated Onions (with a value of 1.2x10-4 for adult and 4.7x10-4 for children) and Pepper (with a value of 5.5x10-5 for adult and 2.2x10-4 for children) as the most contaminated foodstuffs with pesticide residues in the studied area. The order of the total cancer risk from the study was Onions &gt; Pepper &gt; Tomato &gt; Green Amaranth Leaves &gt; Fluted Pumpkin Leaves &gt; Okra for both adult and children. In conclusion it was observed that pesticide residues of Endrin, o,p'-DDE and Heptachlor in Onions, Green Amaranth Leaves and Pepper were above the Codex maximum residue level (MRL). Endrin in Onions had 858.0%, o, p'-DDE in Onions had 276.0%, o, p'-DDE in Green Amaranth Leaves had 100.8%, Heptachlor in Pepper had 168.4% and Heptachlor in Onions had 119.2%. Also, the hazard index of chronic exposure and cancer risk of children for Onions requires urgent attention as their values were well above the acceptable limit. Therefore, periodic monitoring of pesticides residues in these fruits and vegetables cannot be over emphasized, but will go a long way to prevent, control and reduce environmental pollution and health risks. Also, taking precautionary measures like proper cooking before consumption of these foodstuffs is advised.

A nonlinear disturbance observer for sliding mode control of surge in centrifugal compressors via TCV actuator

Surge is a form of dynamic instability created as an unstable pattern in the flow of fluid and can severely affect centrifugal compressor performance by causing fluctuations in flow and pressure parameters. Due to the heavy and costly damage that the surge may cause in various industrial processes such as petrochemical plants, it is necessary to design an appropriate control system to reduce the effect of this phenomenon. The problem of active surge control of a centrifugal compressor using the throttle control valve (TCV) in the presence of compressor parametric uncertainties as well as large demands on upstream and downstream loads is investigated in this work. The control objective was to design a robust control system that can stabilize the compressor over a wide operating range without knowing the upper bound for the uncertainties and load demand. The controller should also react quickly by generating a smooth control signal without saturating the control input. These objectives are achieved by designing a sliding mode controller along with a nonlinear disturbance observer. The performance of the proposed disturbance observer-based controller is evaluated under various operational and load conditions and the results are compared against fuzzy type 1, conventional sliding mode, and wavelet-based neural network robust adaptive controllers. The results show that the proposed method can tolerate large disturbances without any knowledge on the upper bound of the incident disturbance, both on the downstream pressure and upstream mass flow which is highly desirable in practice. The comparative study proves the efficacy of the proposed method using various performance measures. The study also confirms the superior robust performance and stability of the proposed method in front of matched and mismatched disturbances as well as model uncertainties especially close to the instability boundary. Although choosing a TCV actuator has made the control system design easier, the sensitivity of the control valve to flow coefficient and zero calibration under different operating ranges of the compression system is studied carefully and some recommendations for the users are provided.

Moving horizon estimation for localization of mobile robots with measurement outliers

This paper investigates the moving horizon estimation (MHE) problem of mobile robots with measurement outliers. To deal with measurement outliers, the Euclidean distance of measurement error is introduced to detect and remove abnormal data. Then, we use dimension expansion methods to preprocess the data of heterogeneous sensors, such as UWB and IMU. An MHE-based method is proposed that deals with the localization of mobile robots with measurement outliers in the presence of bounded noise. An MHE-based estimator is obtained by solving a regularized least-squares problem. We analyze the convergence of the estimation error system using the properties of norm inequalities, and an upper bound is derived for the estimation error system by using norm inequality. Finally, simulation and experiment examples are given to verify the effectiveness and applicability of the proposed approach.

Co-Axial Metrics on the Sphere and Algebraic Numbers

In this paper, we consider the following curvature equation $$\Delta u+{\rm e}^u=4\pi\biggl((\theta_0-1)\delta_0+(\theta_1-1)\delta_1 +\sum_{j=1}^{n+m}\bigl(\theta_j'-1\bigr)\delta_{t_j}\biggr)\qquad \text{in}\ \mathbb R^2,$$ $$u(x)=-2(1+\theta_\infty)\ln|x|+O(1)\qquad \text{as} \ |x|\to\infty,$$ where $\theta_0$, $\theta_1$, $\theta_\infty$, and $\theta_{j}'$ are positive non-integers for $1\le j\le n$, while $\theta_{j}'\in\mathbb{N}_{\geq 2}$ are integers for $n+1\le j\le n+m$. Geometrically, a solution $u$ gives rise to a conical metric ${\rm d}s^2=\frac12 {\rm e}^u|{\rm d}x|^2$ of curvature $1$ on the sphere, with conical singularities at $0$, $1$, $\infty$, and $t_j$, $1\le j\le n+m$, with angles $2\pi\theta_0$, $2\pi\theta_1$, $2\pi\theta_\infty$, and $2\pi\theta_{j}'$ at $0$, $1$, $\infty$, and $t_j$, respectively. The metric ${\rm d}s^2$ or the solution $u$ is called co-axial, which was introduced by Mondello and Panov, if there is a developing map $h(x)$ of $u$ such that the projective monodromy group is contained in the unit circle. The sufficient and necessary conditions in terms of angles for the existence of such metrics were obtained by Mondello-Panov (2016) and Eremenko (2020). In this paper, we fix the angles and study the locations of the singularities $t_1,\dots,t_{n+m}$. Let $A\subset\mathbb{C}^{n+m}$ be the set of those $(t_1,\dots,t_{n+m})$'s such that a co-axial metric exists, among other things we prove that (i) If $m=1$, i.e., there is only one integer $\theta_{n+1}'$ among $\theta_j'$, then $A$ is a finite set. Moreover, for the case $n=0$, we obtain a sharp bound of the cardinality of the set $A$. We apply a result due to Eremenko, Gabrielov, and Tarasov (2016) and the monodromy of hypergeometric equations to obtain such a bound. (ii) If $m\ge 2$, then $A$ is an algebraic set of dimension $\leq m-1$.

Three-Dimensional Upper Bound Solution to Estimate Soil Thrust of a Track System on Saturated Clay Slopes under Undrained Conditions

This study proposes a three-dimensional upper bound solution for estimating the soil thrust of tracked vehicles on saturated clay slopes. The present study considered block, triangular wedge, and trapezoidal wedge failure modes to formulate an upper bound solution for each. The analytical solution for soil thrust was determined as the minimum upper bound solution among those for each failure mode. This analytical solution was validated through numerical simulations that modeled track-ground interactions. Parametric studies, based on the upper bound solution, assessed the impact of track system shape, vehicle weight, undrained shear strength, and ground slope on soil thrust. The analytical solutions and parametric studies provide a rapid method for assessing vehicle operability on clay slopes and offer references for designing tracked vehicles suitable for site conditions.

Assessing the Size of the Functional Field of View in a Gaze-Contingent Search Paradigm

The functional field of view (FFV) is the part of the visual field centred around the current gaze position that the visual system can process in detail. Its size depends partly on physiological limitations, but its adaptability is largely determined by cognitive factors. For example, changes in the FFV often reflect the demands of a given task: it shrinks with high task demands and expands with easier tasks. Here, we placed an upright or inverted target among distractors. We manipulated the visibility of the search array during gaze-contingent search with small (6°), medium (12°) and large (18°) apertures. Aperture size affected performance, improving it when it increased from 6° to 12°, but not from 12° to 18°, suggesting an upper bound of the 'natural' aperture for this specific task. Furthermore, our results suggest that the FFV does not change in size in response to stimulus inversion.

A reinforcement learning-driven adaptive decomposition algorithm for multi-objective hybrid seru system scheduling considering worker transfer

The application of hybrid seru manufacturing in real-world production often necessitates the implementation of a worker transfer strategy to overcome limitations in skill levels and realize the co-optimization of production efficiency and worker workload. Therefore, this study focuses on hybrid seru system scheduling considering worker transfer (HSSWT) to minimize both the makespan and the total labor time. The presence of multiple optimization objectives and coupled subproblems results in a considerably large search space, which poses challenges that existing optimization frameworks cannot effectively address. Thus, we propose a reinforcement learning-driven adaptive decomposition algorithm (RLADA) to address this issue. First, to minimize the search space, the HSSWT is decomposed into two subproblems, each utilizing distinct search strategies to explore specific areas. Elite-driven population evolution and a lower bound-guided greedy search are proposed to solve the individual subproblems. Second, a deep Q-network has been developed to adaptively select the subproblem to optimize in each generation by dynamically dividing the objective space. Finally, to narrow the search space, the lower bound is used to filter out unpromising solutions, thereby avoiding invalid searches. Additionally, the lower bound is utilized to determine the search depth according to the optimization margin, helping to conserve computing resources. Extensive comparative results demonstrate the effectiveness of the specialized designs, and the RLADA outperforms state-of-the-art algorithms in terms of solution convergence and diversity when addressing the HSSWT.

A Method for Calculating Passive Earth Pressure Under Finite Soil Conditions Based on Upper Bound Limit Analysis

A Method for Calculating Passive Earth Pressure Under Finite Soil Conditions Based on Upper Bound Limit Analysis