A locust phase change model with multiple switching states and random perturbation

Insects such as locusts and some moths can transform from a solitarious phase when they remain in loose populations and a gregarious phase, when they may swarm. Therefore, the key to effective management of outbreaks of species such as the desert locust Schistocercagregaria is early detection of when they are in the threshold state between the two phases, followed by timely control of their hopper stages before they fledge because the control of flying adult swarms is costly and often ineffective. Definitions of gregarization thresholds should assist preventive control measures and avoid treatment of areas that might not lead to gregarization. In order to better understand the effects of the threshold density which represents the gregarization threshold on the outbreak of a locust population, we developed a model of a discrete switching system. The proposed model allows us to address: (1) How frequently switching occurs from solitarious to gregarious phases and vice versa; (2) When do stable switching transients occur, the existence of which indicate that solutions with larger amplitudes can switch to a stable attractor with a value less than the switching threshold density?; and (3) How does random perturbation influence the switching pattern? Our results show that both subsystems have refuge equilibrium points, outbreak equilibrium points and bistable equilibria. Further, the outbreak equilibrium points and bistable equilibria can coexist for a wide range of parameters and can switch from one to another. This type of switching is sensitive to the intrinsic growth rate and the initial values of the locust population, and may result in locust population outbreaks and phase switching once a small perturbation occurs. Moreover, the simulation results indicate that the switching transient patterns become identical after some generations, suggesting that the evolving process of the perturbation system is not related to the initial value after some fixed number of generations for the same stochastic processes. However, the switching frequency and outbreak patterns can be significantly affected by the intensity of noise and the intrinsic growth rate of the locust population

Coupling the macroscale to the microscale in a spatiotemporal context to examine effects of spatial diffusion on disease transmission

There are many challenges to coupling the macroscale to the microscale in temporal or spatial contexts. In order to examine effects of an individual movement and spatial control measures on a disease outbreak, we developed a multiscale model and extended the semi-stochastic simulation method by linking individual movements to pathogen’s diffusion, linking the slow dynamics for disease transmission at the population level to the fast dynamics for pathogen shedding/excretion at the individual level. Numerical simulations indicate that during a disease outbreak individuals with the same infection status show the property of clustering and, in particular, individuals’ rapid movements lead to an increase in the average reproduction number R0, the final size and the peak value of the outbreak. It is interesting that a high level of aggregation the individuals’ movement results in low new infections and a small final size of the infected population. Further, we obtained that either high diffusion rate of the pathogen or frequent environmental clearance lead to a decline in the total number of infected individuals, indicating the need for control measures such as improving air circulation or environmental hygiene. We found that the level of spatial heterogeneity when implementing control greatly affects the control efficacy, and in particular, an uniform isolation strategy leads to low a final size and small peak, compared with local measures, indicating that a large-scale isolation strategy with frequent clearance of the environment is beneficial for disease control

Upper limb motor assessment for stroke with force, muscle activation and interhemispheric balance indices based on sEMG and fNIRS

IntroductionUpper limb rehabilitation assessment plays a pivotal role in the recovery process of stroke patients. The current clinical assessment tools often rely on subjective judgments of healthcare professionals. Some existing research studies have utilized physiological signals for quantitative assessments. However, most studies used single index to assess the motor functions of upper limb. The fusion of surface electromyography (sEMG) and functional near-infrared spectroscopy (fNIRS) presents an innovative approach, offering simultaneous insights into the central and peripheral nervous systems.MethodsWe concurrently collected sEMG signals and brain hemodynamic signals during bilateral elbow flexion in 15 stroke patients with subacute and chronic stages and 15 healthy control subjects. The sEMG signals were analyzed to obtain muscle synergy based indexes including synergy stability index (SSI), closeness of individual vector (CV) and closeness of time profile (CT). The fNIRS signals were calculated to extract laterality index (LI).ResultsThe primary findings were that CV, SSI and LI in posterior motor cortex (PMC) and primary motor cortex (M1) on the affected hemisphere of stroke patients were significantly lower than those in the control group (p < 0.05). Moreover, CV, SSI and LI in PMC were also significantly different between affected and unaffected upper limb movements (p < 0.05). Furthermore, a linear regression model was used to predict the value of the Fugl-Meyer score of upper limb (FMul) (R2 = 0.860, p < 0.001).DiscussionThis study established a linear regression model using force, CV, and LI features to predict FMul scale values, which suggests that the combination of force, sEMG and fNIRS hold promise as a novel method for assessing stroke rehabilitation

A general model of hormesis in biological systems and its application to pest management

Hormesis, a phenomenon whereby exposure to high levels of stressors is inhibitory but low (mild, sublethal and subtoxic) doses are stimulatory, challenges decision-making in the management of cancer, neurodegenerative diseases, nutrition and ecotoxicology. In the latter, increasing amounts of a pesticide may lead to upsurges rather than declines of pests, ecological paradoxes that are difficult to predict. Using a novel re-formulation of the Ricker population equation, we show how interactions between intervention strengths and dose timings, dose–response functions and intrinsic factors can model such paradoxes and hormesis. A model with three critical parameters revealed hormetic biphasic dose and dose timing responses, either in a J-shape or an inverted U-shape, yielding a homeostatic change or a catastrophic shift and hormetic effects in many parameter regions. Such effects were enhanced by repeated pulses of low-level stimulations within one generation at different dose timings, thereby reducing threshold levels, maximum responses and inhibition. The model provides insights into the complex dynamics of such systems and a methodology for improved experimental design and analysis, with wide-reaching implications for understanding hormetic effects in ecology and in medical and veterinary treatment decision-making. We hypothesized that the dynamics of a discrete generation pest control system can be determined by various three parameter spaces, some of which reveal the conditions for occurrence of hormesis, and confirmed this by fitting our model to both hormetic data from the literature and to a non-hormetic dataset on pesticidal control of mirid bugs in cotton

High-dose cytarabine monotherapy is superior to standard-dose cytarabine- based multiagent sequential treatment cycle for consolidation treatment in adult (14-59 years) AML patients according to European Leukemia Net 2022 risk stratification

IntroductionWe firstly investigate based on 2022 European Leukemia Net (ELN) risk stratification, whether standard-dose cytarabine based multiagent sequential chemotherapy (SDMSC) is more beneficial than high-dose cytarabine (HDAC) monotherapy in consolidation for the survival of adult acute myeloid leukemia (AML) patients.MethodsOne hundred and eighty-three AML patients with complete remission (CR) were evaluated.Results and discussionThe 3-year relapse rate was 33.4% in the HDAC group and 50.5% in the SDMSC group (p=0.066). The 3-year overall survival (OS) and event-free survival (EFS) rates in the HDAC group (69.2%, 60.7%) were significantly higher than that in the SDMSC group (50.8%, 42.1%) (p=0.025, 0.019). For patients in the intermediate risk group, the 3-year OS and EFS rates in the HDAC group (72.5%, 56.7%) were higher than that in the SDMSC group (49.1%, 38.0%) (p=0.028, 0.093). This study indicates that for young adult AML patients, HDAC consolidation achieves a higher long-term survival than SDMSC, especially for patients in the intermediate-risk group according to the 2022 ELN risk stratification

Deformation Prediction of Plate Line Rolling Forming Based on Inherent Strain Method

Inherent strain method has been widely used as a forecasting and computing method for welding deformation of large complicated structures and further applied to the research of line heating forming. Mechanical forming is a common ship-hull plate forming method, for which deformation prediction still depends mainly on elastoplastic finite element method. This paper researched the application of inherent strain method to plate line rolling forming, a common mechanical forming method, and then compared the results of inherent strain method and elastoplastic finite element method, proving the applicability of inherent strain method, providing a method for fast, accurate forecasting of distortion in plate line rolling and formation of automation equipment

Dynamic Behaviours and Bifurcation Analysis of a Filippov Ecosystem with Fear Effect

Evidences of the fear effect of the prey are well documented, which can greatly affect the dynamics of the predator-prey system. In this study, considering that the fear effect of the prey is triggered on as the density of the predator reaches and exceeds a threshold value, we develop a Filippov system of predator-prey model with the fear effect. In addition, we also include a modify factor of the growth rate of the prey when they adopt the antipredator behaviours due to the fear effect. We initially analyze the dynamics of the two subsystems, including the existence and stability of the equilibria. Utilizing the theory of the Filippov system, we discuss the sliding dynamics, i.e., the existence of sliding region and sliding equilibria. By choosing the threshold as the bifurcation parameter, we investigate the bifurcations near the regular equilibria. The solution curve has three cases: crossing the threshold curve, sliding on the threshold curve, and approaching the pseudoequilibrium. Finally, we numerically verified the existence of the global sliding bifurcation near the regular equilibrium and also the touching bifurcation

Sliding Dynamics of a Filippov Forest-Pest Model with Threshold Policy Control

A novel Filippov forest-pest system with threshold policy control (TPC) is established while an economic threshold (ET) is used to guide switching. The aim of our work is to address how to reasonably and successfully control pests by means of sliding dynamics for the Filippov system. On the basis of the above considerations, conditions for the existence and stability of equilibria of subsystems are addressed, and the sliding segments and several types of equilibria of the proposed system are defined. These equilibria include the regular/virtual equilibrium, pseudoequilibrium, boundary equilibrium, and tangent point. Further, not only are the relations between nullclines and equilibria of the Filippov system discussed, but the relations between pseudoequilibrium, nullclines, and the sliding segment are discussed. More importantly, four cases of sliding bifurcations of the Filippov system with respect to different types of equilibria of subsystems are investigated, and the corresponding biological implications concerning integrated pest management (IPM) are analyzed. Our results show that the points of intersection between nullclines are equilibria of the system, and the two endpoints of the sliding segment are on the nullclines. It is also verified that the pseudoequilibrium is the point of intersection of the sliding segment and nullclines of the Filippov system, and the pseudoequilibrium exists on the sliding segment. More interestingly, sliding dynamics analysis reveals that the Filippov system has sliding limit cycles, a bistable state and a stable refuge equilibrium point, and the optimal time and strategy for controlling pests are provided