Mathematical Biosciences and Engineering最新文献_第5页

A close look at the viral reduction rate in target cell limited models. 在靶细胞有限模型中仔细观察病毒减少率。

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2026-04-13 DOI: 10.3934/mbe.2026053

Lifeng Han, Jiang Liu, Ye Yuan, Shiqian Zhang, Hao Zhu, Ye Xiong

引用次数: 0

Addressing domain shift via imbalance-aware domain adaptation in embryo development assessment. 通过不平衡感知领域适应解决胚胎发育评估中的领域转移。

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2026-04-10 DOI: 10.3934/mbe.2026051

Lei Li, Xinglin Zhang, Jun Liang, Mengqian Huang, Tao Chen

{"title":"Addressing domain shift via imbalance-aware domain adaptation in embryo development assessment.","authors":"Lei Li, Xinglin Zhang, Jun Liang, Mengqian Huang, Tao Chen","doi":"10.3934/mbe.2026051","DOIUrl":"10.3934/mbe.2026051","url":null,"abstract":"Deep learning models in medical imaging face dual challenges: domain shift, where models perform poorly when deployed in settings different from their training environment, and class imbalance, where certain disease conditions are naturally underrepresented. We have presented imbalance-aware domain adaptation (IADA), a novel framework that simultaneously tackles both challenges through three key components: (1) adaptive feature learning with class-specific attention mechanisms, (2) balanced domain alignment with dynamic weighting, and (3) adaptive threshold optimization. Our theoretical analysis established convergence guarantees and complexity bounds. Through extensive experiments on embryo development assessment across four imaging modalities, IADA demonstrated significant improvements over existing methods, achieving up to 25.19% higher accuracy while maintaining balanced performance across classes. In challenging scenarios with low-quality imaging systems, IADA showed robust generalization with AUC improvements of up to 12.56%. These results demonstrate IADA's potential for developing reliable and equitable medical imaging systems for diverse clinical settings. The code is publicly available at https://github.com/yinghemedical/imbalance-aware_domain_adaptation.","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":"23 5","pages":"1375-1401"},"PeriodicalIF":2.6,"publicationDate":"2026-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147942796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effect of drug resistance on an HIV epidemic in heterogeneous populations. 耐药性对异质人群中HIV流行的影响

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2026-04-07 DOI: 10.3934/mbe.2026050

Roberto A Saenz

{"title":"Effect of drug resistance on an HIV epidemic in heterogeneous populations.","authors":"Roberto A Saenz","doi":"10.3934/mbe.2026050","DOIUrl":"10.3934/mbe.2026050","url":null,"abstract":"The emergence of drug resistance (DR) may impair the control of the human immunodeficiency virus (HIV) epidemic. We analyze the transmission and drug-resistance dynamics of HIV using a stochastic model in combination with Monte Carlo simulations, which considers population heterogeneity, set in terms of the set-point viral load (SPVL) distribution. In our modeling framework, once a SPVL is sampled, it determines the transmission rate and survival time for each new infected individual. On the other hand, DR emergence randomly occurs with a fixed probability in an individual receiving antiretroviral therapy (ART). In addition, we implicitly assume that the SPVL serves as a proxy for the replication pressure and resistance risk, as the DR fitness-cost proportionally reduces the SPVL in our model (an assumption motivated by modeling convenience instead of an actual biological mechanism present in the DR dynamics). Finally, we simplify the dynamics by assuming no ART regimen switching in cases of treatment failure (which we assumed to be only due to DR). Our results show that for a high treatment coverage, DR causes a higher stationary infection prevalence in populations with moderate-to-high mean viral loads. Moreover, DR could produce more infections for greater ART coverage, especially when treatment is administered early after contagion; however, an earlier initiation of ART allows for the possibility of epidemic extinction. Additionally, we evaluate the effect on the epidemic dynamics of other parameters, such as the probability of DR emergence and the relative fitness of the DR strain. Overall, our analysis contributes to the understanding of drug resistance evolution in situations where ART is inadequately managed.","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":"23 5","pages":"1356-1374"},"PeriodicalIF":2.6,"publicationDate":"2026-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147943507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A personal overview of epidemic models for mosquito-borne infections. 蚊媒感染流行模型的个人概述。

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2026-04-02 DOI: 10.3934/mbe.2026047

Andrea Pugliese, Simone De Reggi

引用次数: 0

Imitation dynamics in vaccination under partial and temporary immune protection. 局部和暂时性免疫保护下疫苗接种的模仿动力学。

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2026-04-02 DOI: 10.3934/mbe.2026048

Paulo Doutor, Ricardo Castelhano, Maria do Céu Soares, Bob Kooi

{"title":"Imitation dynamics in vaccination under partial and temporary immune protection.","authors":"Paulo Doutor, Ricardo Castelhano, Maria do Céu Soares, Bob Kooi","doi":"10.3934/mbe.2026048","DOIUrl":"10.3934/mbe.2026048","url":null,"abstract":"Vaccination has been the most effective strategy to contain and control infectious disease epidemics. Over the past decades, its success and the consequent herd immunity changed public perceptions on the disease and vaccination's expected costs which, in some cases, resulted in vaccine hesitancy. This work extends the classical SIR model by incorporating both temporary and partial immunity, along with individual vaccination decisions driven by an imitation dynamics approach based on perceived expected costs. Our methodology relied on the stability analysis of the equilibria and the investigation of bifurcation phenomena within the model. To this end, we employed classical local asymptotic techniques, complemented by numerical continuation methods and the computation of Lyapunov exponents. The analysis of the model revealed an interplay between incomplete immune protection and imitation parameters, with rich dynamics involving oscillatory and chaotic behavior for low waning immunity rates and/or high protection against reinfection, and for high social-learning rate. Furthermore, exploring temporary immunity led to the conclusion that for diseases with shorter immunity periods and for vaccines with high relative expected cost, people will rapidly decline any vaccination efforts. These findings emphasize the importance of human behavior for a population in an epidemic landscape, and may provide insight on how to adapt and improve public health interventions.","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":"23 5","pages":"1315-1339"},"PeriodicalIF":2.6,"publicationDate":"2026-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147943465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Oscillations in marine and insect populations with delayed density-dependence. 具有延迟密度依赖性的海洋和昆虫种群的振荡。

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2026-04-02 DOI: 10.3934/mbe.2026049

Thomas Erneux, Yang Kuang

引用次数: 0

CNN-based estimation of series resistance in photovoltaic cells from electroluminescence images with application to output power prediction. 基于cnn的光伏电池电致发光图像串联电阻估计及其输出功率预测应用。

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2026-04-01 DOI: 10.3934/mbe.2026046

Hector Felipe Mateo-Romero, Jose Ignacio Morales Aragonés, Luis Hernández-Callejo, Miguel Ángel González-Rebollo, Valentín Cardeñoso-Payo, Victor Alonso-Gómez, Mario Carbonó delaRosa, Ginés García Mateos

{"title":"CNN-based estimation of series resistance in photovoltaic cells from electroluminescence images with application to output power prediction.","authors":"Hector Felipe Mateo-Romero, Jose Ignacio Morales Aragonés, Luis Hernández-Callejo, Miguel Ángel González-Rebollo, Valentín Cardeñoso-Payo, Victor Alonso-Gómez, Mario Carbonó delaRosa, Ginés García Mateos","doi":"10.3934/mbe.2026046","DOIUrl":"https://doi.org/10.3934/mbe.2026046","url":null,"abstract":"The estimation of series resistance in photovoltaic (PV) cells is a crucial parameter that significantly influences their efficiency and overall performance. This study proposes a novel methodology to predict the slope of the current-voltage (Ⅰ-Ⅴ) curve of a PV cell in the first quadrant, where this slope (the electrical conductance) is directly associated with the series resistance of the cell. By leveraging artificial intelligence techniques, a convolutional neural network model has been developed to estimate this slope from electroluminescence (EL) images of the cells. The model was trained on a dataset consisting of EL images of PV cells with artificially induced defects, together with the corresponding slope values derived from the cells' Ⅰ-Ⅴ curves. Furthermore, this work presents a second model that combines the slope information and EL images to improve the prediction of the maximum power point (MPP) of a PV cell, surpassing previous approaches that rely solely on EL imagery. Both models demonstrated low error rates across multiple evaluation metrics, evidencing their accuracy and robustness. Additionally, comparative analysis with other machine learning methods highlights the competitive performance of the proposed approaches. These contributions provide promising tools for enhancing the assessment and diagnosis of PV cell efficiency and reliability, potentially leading to improved performance and increased longevity of photovoltaic systems.","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":"23 5","pages":"1269-1288"},"PeriodicalIF":2.6,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147942937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cost-effectiveness and optimal control analysis of an SIR-P model for rodent-transmitted infection in agricultural environments. 农业环境鼠类传播感染SIR-P模型的成本效益和最优控制分析。

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2026-03-31 DOI: 10.3934/mbe.2026045

Mahmoud Moustafa

{"title":"Cost-effectiveness and optimal control analysis of an SIR-P model for rodent-transmitted infection in agricultural environments.","authors":"Mahmoud Moustafa","doi":"10.3934/mbe.2026045","DOIUrl":"10.3934/mbe.2026045","url":null,"abstract":"Rodent populations in agricultural environments serve as critical reservoirs for zoonotic diseases, posing significant risks to food security and public health. Transmission in these settings is complex, thereby occurring through both direct rodent-to-rodent contacts and indirect exposures to environmental contamination. In this paper, we formulate and analyze a deterministic model that integrates rodent population dynamics with an environmental pathogen compartment. To identify resource-efficient mitigation policies, we develop an optimal control framework that incorporates three time-dependent interventions: contact prevention, environmental sanitation, and treatment. By applying Pontryagin's Maximum Principle, we derive the Hamiltonian, the adjoint system, and the characterization of the optimal controls, and subsequently solve the optimality system using a forward-backward sweep algorithm. We evaluate the epidemiological impact and economic viability of seven distinct intervention strategies using the Average Cost-Effectiveness Ratio (ACER) and the Incremental Cost-Effectiveness Ratio (ICER). Numerical simulations demonstrate that while the full combination of controls yields the maximum reduction in infection, the prevention-only strategy emerges as the most economically attractive option under restricted budgets. These findings suggest that prioritizing contact-reduction measures provides the most cost-effective basis for disease management, while integrated sanitation and treatments should be scaled based on resource availability. This study provides a quantitative framework that may assist agricultural stakeholders in developing resource-efficient control policies.","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":"23 5","pages":"1251-1268"},"PeriodicalIF":2.6,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147943328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Global well-posedness and pattern formation in a predator-prey reaction-diffusion system with prey-taxis. 具有猎物趋向性的捕食者-猎物反应-扩散系统的全局适定性和模式形成。

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2026-03-31 DOI: 10.3934/mbe.2026044

Mohamed Hafdane, Nossaiba Baba, Saida Khiyar

{"title":"Global well-posedness and pattern formation in a predator-prey reaction-diffusion system with prey-taxis.","authors":"Mohamed Hafdane, Nossaiba Baba, Saida Khiyar","doi":"10.3934/mbe.2026044","DOIUrl":"https://doi.org/10.3934/mbe.2026044","url":null,"abstract":"This paper investigates a spatiotemporal predator-prey model that incorporates the Allee effect, the fear effect, prey-taxis, and harvesting within a Beddington-DeAngelis functional framework. The model captures the combined influence of biological interactions, behavioral responses, and harvesting activities on population dynamics in a spatially heterogeneous environment. The global existence, positivity, and boundedness of classical solutions are first established under appropriate parameter conditions. The existence and local stability of homogeneous steady states are then analyzed, and the conditions for diffusion-driven instability are derived to characterize the onset of spatial patterns. Using weakly nonlinear analysis, amplitude equations are developed to describe the modulation of spatial modes near the bifurcation threshold. Numerical investigations are conducted to complement the theoretical analysis: bifurcation diagrams are employed to examine the effects of biological parameters such as the Allee threshold ($ beta $), fear intensity ($ gamma $), and conversion efficiency ($ varepsilon $), while spatiotemporal simulations are performed to visualize different scenarios and demonstrate the impact of prey-taxis on pattern formation and population organization.","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":"23 5","pages":"1203-1250"},"PeriodicalIF":2.6,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147943489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparing Bayesian and frequentist inference in biological models: A comparative analysis of accuracy, uncertainty, and identifiability. 比较贝叶斯和频率推理在生物模型：准确性，不确定性和可识别性的比较分析。

IF 2.6 4区工程技术

Mathematical Biosciences and Engineering Pub Date : 2026-03-30 DOI: 10.3934/mbe.2026043

Mohammed A Y Mohammed, Hamed Karami, Gerardo Chowell

{"title":"Comparing Bayesian and frequentist inference in biological models: A comparative analysis of accuracy, uncertainty, and identifiability.","authors":"Mohammed A Y Mohammed, Hamed Karami, Gerardo Chowell","doi":"10.3934/mbe.2026043","DOIUrl":"10.3934/mbe.2026043","url":null,"abstract":"Mathematical models are widely used to study ecological and epidemiological systems, but the accuracy of the resulting inferences and forecasts depends on the estimation framework. This study compares Bayesian and frequentist approaches across three biological models using four datasets: The Lotka-Volterra predator-prey system, a generalized logistic model (GLM) applied to lung injury and mpox data, and the susceptible-exposed-infected (reported and unreported)-recovered (SEIUR) epidemic model for COVID-19. To ensure a fair comparison, both approaches were implemented with a normal error structure. We first examined the structural identifiability to determine which parameters can be recovered in principle. We then evaluated practical identifiability and fitting performance using four metrics: Mean absolute error, mean squared error, prediction interval coverage, and the weighted interval score. For the Lotka-Volterra model, we studied three types of observations: Prey only, predator only, and both species together. The frequentist workflow, implemented through QuantDiffForecast, uses nonlinear least squares and parametric bootstraping to quantify uncertainty. The Bayesian workflow, implemented through BayesianFitForecast, uses Hamiltonian Monte Carlo sampling to obtain posterior distributions and diagnostic measures. Our results show that frequentist inference performs well when the system comprises fully observed data, as in the GLM or in the Lotka-Volterra model when both species are observed. Bayesian inference performs better when uncertainty is high and observations are limited or indirect, as seen in the SEIUR epidemic model. The identifiability analysis helps explain these differences by showing how observability shapes the reliability of parameter recovery and uncertainty quantification.","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":"23 5","pages":"1156-1202"},"PeriodicalIF":2.6,"publicationDate":"2026-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147943313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0