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Record W4415688782 · doi:10.3934/dcds.2025173

Existence and stability of sawtooth periodic solutions in a state-dependent switching system

2025· article· W4415688782 on OpenAlexaff
Jianshe Yu, Chunming Ju, Yufeng Wang, Kai Wang, Huaiping Zhu

Bibliographic record

VenueDiscrete and Continuous Dynamical Systems · 2025
Typearticle
Language
FieldMedicine
TopicMathematical and Theoretical Epidemiology and Ecology Models
Canadian institutionsYork University
FundersChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsSawtooth waveStability (learning theory)PopulationScalar (mathematics)Constant (computer programming)State (computer science)Stability theory

Abstract

fetched live from OpenAlex

In this paper, we investigate the existence and stability of sawtooth periodic solutions of a new scalar switching system with state dependence. We find two threshold regions for the switch, denoted as $ D_M^* $ and $ D_M^{**} $, such that every solution will eventually converge to a constant if the threshold is located in $ D_M^* $, but there exists a unique globally asymptotically stable sawtooth periodic solution if it is located in $ D_M^{**} $ under suitable conditions with the aid of the Poincaré mapping method. Furthermore, the non-existence of sawtooth periodic solutions is investigated through utilizing an ingenious contradiction argument which seems to be the first attempt. As an example, we apply our theory to show the existence of novel forms of sawtooth periodic solutions in a mosquito population suppression model.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.263
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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