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Journal articles on the topic 'Predictive adaptive response'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Nettle, Daniel, Willem E. Frankenhuis, and Ian J. Rickard. "The evolution of predictive adaptive responses in humans: response." Proceedings of the Royal Society B: Biological Sciences 281, no. 1780 (2014): 20132822. http://dx.doi.org/10.1098/rspb.2013.2822.

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2

Wells, Jonathan C. K. "Response to Gluckman et al. and Bateson: predictive adaptive responses." Trends in Endocrinology & Metabolism 19, no. 4 (2008): 112. http://dx.doi.org/10.1016/j.tem.2008.02.003.

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3

Wells, Jonathan CK. "A critical appraisal of the predictive adaptive response hypothesis." International Journal of Epidemiology 41, no. 1 (2012): 229–35. http://dx.doi.org/10.1093/ije/dyr239.

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Williams, Thomas C., and Amanda J. Drake. "Preterm birth in evolutionary context: a predictive adaptive response?" Philosophical Transactions of the Royal Society B: Biological Sciences 374, no. 1770 (2019): 20180121. http://dx.doi.org/10.1098/rstb.2018.0121.

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Preterm birth is a significant public health problem worldwide, leading to substantial mortality in the newborn period, and a considerable burden of complications longer term, for affected infants and their carers. The fact that it is so common, and rates vary between different populations, raising the question of whether in some circumstances it might be an adaptive trait. In this review, we outline some of the evolutionary explanations put forward for preterm birth. We specifically address the hypothesis of the predictive adaptive response, setting it in the context of the Developmental Orig

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Gluckman, P. D., and M. A. Hanson. "Adult disease: echoes of the past." European Journal of Endocrinology 155, suppl_1 (2006): S47—S50. http://dx.doi.org/10.1530/eje.1.02233.

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Disease occurs if an environmental challenge exceeds the ability of an individual to mount an effective adaptive response to it. Evolution has selected genomically determined traits, which are optimal for a species to survive the historical environment. However, this adaptive ability to withstand an environmental challenge varies among individuals and is itself a phenotypic characteristic: how is this determined? We argue that maternal and placental cues that constrain prenatal development, induce offspring to develop predictive adaptive responses more suited to a deprived postnatal environmen

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D., Ganga, and Ramachandran V. "Adaptive prediction model for effective electrical machine maintenance." Journal of Quality in Maintenance Engineering 26, no. 1 (2019): 166–80. http://dx.doi.org/10.1108/jqme-12-2017-0087.

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Purpose The purpose of this paper is to propose an optimal predictive model for the short-term forecast of real-time non-stationary machine variables by combining time series prediction with adaptive algorithms to minimize the error and to improve the prediction accuracy. Design/methodology/approach The proposed model is applied for prediction of speed and controller set point of three-phase induction motor operating on closed loop speed control with AC drive and PI controller. At Stage 1, the trend of the machine variables has been extracted and added to auto-regressive moving average (ARMA)

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Liu, Jiaqi. "AI-Based Epidemic Spread Prediction and Public Health Response Optimization: A Systematic Study from Data Analysis to Policy Implementation." Applied and Computational Engineering 118, no. 1 (2024): 1–7. https://doi.org/10.54254/2755-2721/2025.18470.

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The paper discusses how AI can be used to predict epidemics and improve public health responses on a wide range of critical topics from disease prediction using data to policymaking. Even conventional epidemiological models, often constrained by parameters, find it difficult to adapt to rapidly evolving disease dynamics. Our method combines machine learning (ML) and deep learning (DL) algorithms, such as long short-term memory (LSTM) and reinforcement learning (RL), to dynamically anticipate infection peaks and outbreak hotspots. Using both time-series and spatial data, the hybrid CNN-LSTM mod

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Yin, Fang Chen, Geng Sheng Ma, Ya Feng Ji, Jia Xue Yu, De Hao Gu, and Dian Hua Zhang. "Fuzzy Adaptive Direct Generalized Predictive Control Algorithm in the Application of AWC Control." Advanced Materials Research 945-949 (June 2014): 2529–32. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.2529.

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Using the characteristics of prediction model, rolling optimization and feedback correction, a AWC system based on generalized predictive control was designed, and its control performance was simulated based on a hot strip continuous mill. The results show that generalized predictive controller achieves better control effects than the normal PID on response time and steady precision with matching model; when model mismatching is caused by inaccuracy of plastic coefficient and pure delay time, the normal PID is overshot or even oscillation, but the control performance of the generalized predict

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Li, Zhaobo, Yimin Deng, and Shuanglei Sun. "Adaptive Cruise Predictive Control Based on Variable Compass Operator Pigeon-Inspired Optimization." Electronics 11, no. 9 (2022): 1377. http://dx.doi.org/10.3390/electronics11091377.

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A vehicle adaptive cruise system can control the speed and the safe distance between vehicles rapidly and effectively, which is an integral part of an intelligent driver assistance system. Adaptive cruise predictive control algorithms based on variable compass operator pigeon-inspired optimization (PIO) and PSO are proposed to improve the time response characteristics of multi-objective adaptive cruise system predictive control. Firstly, a longitudinal kinematic model of an adaptive cruise system was established and linearly discretized. Secondly, the multi-objective optimal cost function and

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Li, Zhaobo, Yimin Deng, and Shuanglei Sun. "Adaptive Cruise Predictive Control Based on Variable Compass Operator Pigeon-Inspired Optimization." Electronics 11, no. 9 (2022): 1377. http://dx.doi.org/10.3390/electronics11091377.

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A vehicle adaptive cruise system can control the speed and the safe distance between vehicles rapidly and effectively, which is an integral part of an intelligent driver assistance system. Adaptive cruise predictive control algorithms based on variable compass operator pigeon-inspired optimization (PIO) and PSO are proposed to improve the time response characteristics of multi-objective adaptive cruise system predictive control. Firstly, a longitudinal kinematic model of an adaptive cruise system was established and linearly discretized. Secondly, the multi-objective optimal cost function and

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Devevey, Godefroy, Pierre Bize, Sara Fournier, Emilie Person, and Philippe Christe. "Testing the predictive adaptive response in a host-parasite system." Functional Ecology 24, no. 1 (2010): 178–85. http://dx.doi.org/10.1111/j.1365-2435.2009.01609.x.

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Devevey, Godefroy, Pierre Bize, Sara Fournier, Emilie Person, and Philippe Christe. "Testing the predictive adaptive response in a host‐parasite system." Functional Ecology 24, no. 1 (2010): 178–85. https://doi.org/10.5281/zenodo.13513491.

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(Uploaded by Plazi for the Bat Literature Project) Summary 1. Harsh environmental conditions experienced during development can reduce the performance of the same individuals in adulthood. However, the 'predictive adaptive response' hypothesis postulates that if individuals adapt their phenotype during development to the environments where they are likely to live in the future, individuals exposed to harsh conditions in early life perform better when encountering the same harsh conditions in adulthood compared to those never exposed to these conditions before. 2. Using the common vole ( Microt

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Devevey, Godefroy, Pierre Bize, Sara Fournier, Emilie Person, and Philippe Christe. "Testing the predictive adaptive response in a host‐parasite system." Functional Ecology 24, no. 1 (2010): 178–85. https://doi.org/10.5281/zenodo.13513491.

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(Uploaded by Plazi for the Bat Literature Project) Summary 1. Harsh environmental conditions experienced during development can reduce the performance of the same individuals in adulthood. However, the 'predictive adaptive response' hypothesis postulates that if individuals adapt their phenotype during development to the environments where they are likely to live in the future, individuals exposed to harsh conditions in early life perform better when encountering the same harsh conditions in adulthood compared to those never exposed to these conditions before. 2. Using the common vole ( Microt

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Devevey, Godefroy, Pierre Bize, Sara Fournier, Emilie Person, and Philippe Christe. "Testing the predictive adaptive response in a host‐parasite system." Functional Ecology 24, no. 1 (2010): 178–85. https://doi.org/10.5281/zenodo.13513491.

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(Uploaded by Plazi for the Bat Literature Project) Summary 1. Harsh environmental conditions experienced during development can reduce the performance of the same individuals in adulthood. However, the 'predictive adaptive response' hypothesis postulates that if individuals adapt their phenotype during development to the environments where they are likely to live in the future, individuals exposed to harsh conditions in early life perform better when encountering the same harsh conditions in adulthood compared to those never exposed to these conditions before. 2. Using the common vole ( Microt

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Devevey, Godefroy, Pierre Bize, Sara Fournier, Emilie Person, and Philippe Christe. "Testing the predictive adaptive response in a host‐parasite system." Functional Ecology 24, no. 1 (2010): 178–85. https://doi.org/10.5281/zenodo.13513491.

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(Uploaded by Plazi for the Bat Literature Project) Summary 1. Harsh environmental conditions experienced during development can reduce the performance of the same individuals in adulthood. However, the 'predictive adaptive response' hypothesis postulates that if individuals adapt their phenotype during development to the environments where they are likely to live in the future, individuals exposed to harsh conditions in early life perform better when encountering the same harsh conditions in adulthood compared to those never exposed to these conditions before. 2. Using the common vole ( Microt

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Wang, Yong, Qiangang Zheng, Haibo Zhang, and Haoying Chen. "Research on predictive control of helicopter/engine based on LMS adaptive torsional vibration suppression." Journal of Low Frequency Noise, Vibration and Active Control 37, no. 4 (2018): 1151–63. http://dx.doi.org/10.1177/1461348418790495.

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In order to achieve the fast response of turboshaft engine combined with torsional vibration, a predictive controller of helicopter/engine based on the least mean square adaptive torsional vibration suppression is proposed and designed. First, in order to make up for the insufficiency of conventional notch filter on torsional vibration suppression with changeable frequency under variable rotor speed, an adaptive one based on least mean square is presented in the process of helicopter autorotation downward. Then, based on the least mean square adaptive filter, a predictive controller based on t

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17

Bateson, Patrick, Peter Gluckman, and Mark Hanson. "The biology of developmental plasticity and the Predictive Adaptive Response hypothesis." Journal of Physiology 592, no. 11 (2014): 2357–68. http://dx.doi.org/10.1113/jphysiol.2014.271460.

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18

Rickard, Ian J., and Virpi Lummaa. "The predictive adaptive response and metabolic syndrome: challenges for the hypothesis." Trends in Endocrinology & Metabolism 18, no. 3 (2007): 94–99. http://dx.doi.org/10.1016/j.tem.2007.02.004.

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19

Del Popolo Cristaldi, Fiorella, Lisa Toffoli, Gian Marco Duma, and Giovanni Mento. "Little fast, little slow, should I stay or should I go? Adapting cognitive control to local-global temporal prediction across typical development." PLOS ONE 18, no. 2 (2023): e0281417. http://dx.doi.org/10.1371/journal.pone.0281417.

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Adaptive cognitive control (CC), the ability to adjust goal-directed behavior according to changing environmental demand, can be instantiated bottom-up by implicit knowledge, including temporal predictability of task-relevant events. In S1-S2 tasks, either local (trial-by-trial hazard expectation) or global (block-by-block expectation) temporal information can induce prediction, allowing for proactive action control. Recent developmental evidence showed that adaptive CC based on global temporal prediction emerges earlier than when it is based on the local one only. However, very little is know

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20

Yamashiro, Stanley M., and Takahide Kato. "Modeling rate sensitivity of exercise transient responses to limb motion." Journal of Applied Physiology 117, no. 7 (2014): 699–705. http://dx.doi.org/10.1152/japplphysiol.00391.2014.

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Transient responses of ventilation (V̇e) to limb motion can exhibit predictive characteristics. In response to a change in limb motion, a rapid change in V̇e is commonly observed with characteristics different than during a change in workload. This rapid change has been attributed to a feed-forward or adaptive response. Rate sensitivity was explored as a specific hypothesis to explain predictive V̇e responses to limb motion. A simple model assuming an additive feed-forward summation of V̇e proportional to the rate of change of limb motion was studied. This model was able to successfully accoun

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21

Piñón, Alejandro, Antonio Favela-Contreras, Francisco Beltran-Carbajal, Camilo Lozoya, and Graciano Dieck-Assad. "Novel Strategy of Adaptive Predictive Control Based on a MIMO-ARX Model." Actuators 11, no. 1 (2022): 21. http://dx.doi.org/10.3390/act11010021.

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Many industrial processes include MIMO (multiple-input, multiple-output) systems that are difficult to control by standard commercial controllers. This paper describes a MIMO case of a class of SISO-APC (single-input, single-output adaptive predictive controller) based upon an ARX (autoregressive with exogenous variable) model. This class of SISO-APC based on ARX models has been successfully and extensively used in many industrial applications. This approach aims to minimize the barriers between the theory of predictive adaptive control and its application in the industrial environment. The pr

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22

Liao, Hong Hua. "Simulations Research on Smith Predictive Adaptive Fuzzy-PID Compound Controller in the Temperature Control System of Microchip Level PCR Instrument." Applied Mechanics and Materials 373-375 (August 2013): 1324–31. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.1324.

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Study on the temperature controlling optimization problem of a novel microchip level PCR instrument, a compound control scheme based on Smith predictive and adaptive Fuzzy-PID is presented. Because the temperature control system of microchip level PCR instrument is a time-varying, non-linear and pure time delay complex system, to achieve the different temperature zones rapid switching and the temperature precision controlling is easy to be affected by time delay factor, it may encounter problems such as large overshoot, and even poor stability in the control of system with time delay. In this

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23

Tuli, Richard, Benedick Fraass, Wensha Yang, et al. "Pretreatment [18F] FDG-PET texture analysis to predict local response of pancreatic cancer to radiotherapy." Journal of Clinical Oncology 32, no. 3_suppl (2014): 375. http://dx.doi.org/10.1200/jco.2014.32.3_suppl.375.

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375 Background: Accurate assessment of radiographic response following radiotherapy (RT) for pancreatic adenocarcinoma is challenging. Morphologic and textural features of FDG-PET have been shown to correlate with pathologic response and clinical outcomes in other solid tumors (PMID 23204495). The goal of this study was to develop a predictive algorithm derived from textural features of PET scans to predict response to RT. Methods: With IRB approval, we reviewed 10 patients with locally advanced pancreatic cancer treated with stereotactic body radiation therapy (25-30 Gy in 5 daily fractions).

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ROVEA, S. B., and RODOLFO FLESCH. "FAST ADAPTIVE GENERALIZED PREDICTIVE CONTROL FOR SYSTEMS WITH VARIABLE PARAMETERS." Journal of Engineering and Exact Sciences 5, no. 5 (2019): 0408–14. http://dx.doi.org/10.18540/jcecvl5iss5pp0408-0414.

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This paper proposes a fast predictive control structure with online model update according to process parametric variations. The proposed controller is based on the Generalized Predictive Control (GPC) algorithm, but it integrates the recursive least squares identification method with a variable forgetting factor to estimate at each iteration the parameters of a linear structure model used for multi-step ahead prediction. For a system with constraints on the process variables, the resulting optimization problem of GPC is solved using quadratic programming based on the Alternate Direction Metho

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Graczykowski, Cezary, and Rami Faraj. "Adaptive Impact Mitigation Based on Predictive Control with Equivalent Mass Identification." Sensors 23, no. 23 (2023): 9471. http://dx.doi.org/10.3390/s23239471.

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The paper presents the concept of equivalent parameter predictive control (EPPC) elaborated for semi-active fluid-based (hydraulic and pneumatic) shock absorbers equipped with controllable valves and subjected to impact excitation. The undertaken problem concerns the absorption and dissipation of the impact energy with the requirement to minimize the generated reaction force and corresponding impacting object deceleration. The development of a control strategy for a challenging problem with unknown impacting object mass and unknown changes of external and disturbance forces is proposed and dis

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Garg, Shally. "Real-Time Disaster Response with AIOps: Intelligent Infrastructure Monitoring and Optimization." International Journal of Multidisciplinary Research and Growth Evaluation. 5, no. 5 (2024): 1101–7. https://doi.org/10.54660/.ijmrge.2024.5.5.1101-1107.

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This paper explores leveraging AIOps for disaster resilience through real-time infrastructure monitoring and emergency response optimization. By integrating AI-driven predictive analytics, multi-source data (satellite, IoT, geospatial), and edge computing, AIOps can enhance decision-making during disasters. The paper highlights the importance of explainable AI (XAI) for building trust, addressing challenges like real-time data processing, scalability, and security. Future trends include autonomous response systems, deep learning for predictive management, and adaptive decision-making framework

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Montalvo, S. K., M. Arbab, Y. Gonzalez, et al. "Predictive Factors for Response to Adaptive Therapy in Thoracic Stereotactic Ablative Radiotherapy." International Journal of Radiation Oncology*Biology*Physics 117, no. 2 (2023): e43. http://dx.doi.org/10.1016/j.ijrobp.2023.06.742.

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Kommisetty, Phani Durga Nanda Kishore, Bala Maruthi Subba Rao Kuppala, Hussain Vali Buvvaji, and Venkata Rama Reddy Sabbella. "Revolutionizing Cybersecurity: Behavioral Analysis and Automated Incident Response through Predictive Analytics." International Journal of Scientific Research and Management (IJSRM) 10, no. 10 (2022): 962–79. http://dx.doi.org/10.18535/ijsrm/v10i10.ec04.

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Predictive behavioral analytics and automated response (PBAAR) concepts have the potential to revolutionize cybersecurity. The main idea of predictive behavioral analytics is to analyze, extract, and automatically apply behavioral patterns to assess whether a particular activity is malicious. To achieve this goal, simple predictive models built by domain experts need to be developed, understood, and digitally implemented in the form of a sequential approximation of the expert's descriptive models. The expert's logic will be embedded into the constructed predictive model by writing a Python fun

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Toroman, Amel, and Samir Vojić. "Adaptive car control system based on a predictive model." IOP Conference Series: Materials Science and Engineering 1208, no. 1 (2021): 012040. http://dx.doi.org/10.1088/1757-899x/1208/1/012040.

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Abstract An adaptive control is a control, which by pre-setting the parameters of the controller, enables the control of processes whose parameters are time-varying or are initially uncertain. The possibilities and benefits of adaptive control are versatile and can be best demonstrated by applying the system while driving a car, or maintaining the optimal speed and distance between cars, which is shown in this paper. As the car’s weight decreases while driving due to fuel consumption, the control algorithm has to be adapted to the changed driving conditions. Accordingly, an adaptive control sy

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Xiao, Yi’nan, Ke Wen, Yuanju Qu, Yanxi Mao, and Yang Pan. "Surface-Roughness Prediction Based on Small-Batch Workpieces for Smart Manufacturing: An Aerospace Robotic Grinding Case Study." Applied Sciences 15, no. 3 (2025): 1349. https://doi.org/10.3390/app15031349.

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Small-batch workpieces in smart manufacturing demand process parameter modeling, but existing models lack analysis across varying sample sizes and runtime conditions. This study proposes a novel surface-roughness prediction method, Response Surface Methodology-BP Neural Network (RSM-BPNN), designed for experimental data from single small-batch workpieces with varying sample sizes. First, polynomial feature transformation and selection are performed based on the proposed process parameters to improve the feature quality of input data. Second, a Dynamic Central Composite Design-Response Surface

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She, Menghua, Yaling Li, Dongbo Tu, and Yan Cai. "Computerized Adaptive Testing for Sleep Disorders." European Journal of Health Psychology 28, no. 3 (2021): 89–100. http://dx.doi.org/10.1027/2512-8442/a000076.

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Abstract. Background: As more and more people suffer from sleep disorders, the need to develop an efficient, inexpensive, and accurate assessment tool for screening sleep disorders has become more urgent. Aim: The aim of the current study was to develop a system allowing computerized adaptive testing for sleep disorders (CAT-SD). Methods: A large sample ( N = 1,304) was recruited to construct an item bank for CAT-SD and to investigate the psychometric characteristics of CAT-SD. First, analyses of unidimensionality, model fit, item fit, item discrimination parameters, and differential item func

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Jordan, Lyndon A., and Michael J. Ryan. "The sensory ecology of adaptive landscapes." Biology Letters 11, no. 5 (2015): 20141054. http://dx.doi.org/10.1098/rsbl.2014.1054.

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In complex environments, behavioural plasticity depends on the ability of an animal to integrate numerous sensory stimuli. The multidimensionality of factors interacting to shape plastic behaviour means it is difficult for both organisms and researchers to predict what constitutes an adaptive response to a given set of conditions. Although researchers may be able to map the fitness pay-offs of different behavioural strategies in changing environments, there is no guarantee that the study species will be able to perceive these pay-offs. We thus risk a disconnect between our own predictions abou

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Nettle, Daniel, Willem E. Frankenhuis, and Ian J. Rickard. "The evolution of predictive adaptive responses in human life history." Proceedings of the Royal Society B: Biological Sciences 280, no. 1766 (2013): 20131343. http://dx.doi.org/10.1098/rspb.2013.1343.

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Many studies in humans have shown that adverse experience in early life is associated with accelerated reproductive timing, and there is comparative evidence for similar effects in other animals. There are two different classes of adaptive explanation for associations between early-life adversity and accelerated reproduction, both based on the idea of predictive adaptive responses (PARs). According to external PAR hypotheses, early-life adversity provides a ‘weather forecast’ of the environmental conditions into which the individual will mature, and it is adaptive for the individual to develop

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Zhang, Junchang, Deng Zhang, and Jinjin Wan. "A New Video Tracking Algorithm Based on Multi-Complementary Features Fusion." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 37, no. 2 (2019): 323–29. http://dx.doi.org/10.1051/jnwpu/20193720323.

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In order to make full use of the diversity of sample information in the tracking process and improve the generalization ability of the tracker, this paper integrates the object model prediction results on the basis of the Staple algorithm, and applies weighted bands to the simple linearity of different predictive response results in the algorithm. To the uncertainties, a new adaptive response factor graph fusion method with weight coefficients is proposed, which effectively improves the reliability of the video target tracking algorithm. Theoretical analysis and experimental simulation show th

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WELLS, J. "Is early development in humans a predictive adaptive response anticipating the adult environment?" Trends in Ecology & Evolution 21, no. 8 (2006): 424–25. http://dx.doi.org/10.1016/j.tree.2006.05.006.

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Haddar, Mabrouk, and Boumediene Allaoua. "An efficient predictive current controller with adaptive parameter estimation in 3- inverter." International Journal of Power Electronics and Drive System (IJPEDS) 12, no. 2 (2021): 858–69. https://doi.org/10.11591/ijpeds.v12.i2.pp858-869.

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In this paper, a detail design and description of a predictive current control scheme are adopted for three-phase grid-connected two-level inverter and its application in wind energy conversion systems. Despite its advantages, the predictive current controller is very sensitive to parameter variations which could eventually affected on system stability. To solve this problem, an estimation technique proposed to identify the value of harmonic filter parameter based on Model reference adaptive system (MRAS). Lyapunov stability theory is selected to guarantee a robust adaptation and sta

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He, Defeng, Wentao He, and Xiulan Song. "Efficient predictive cruise control of autonomous vehicles with improving ride comfort and safety." Measurement and Control 53, no. 1-2 (2020): 18–28. http://dx.doi.org/10.1177/0020294019877518.

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In this paper, the adaptive cruise control problem of autonomous vehicles is considered and we propose a novel predictive cruise control approach to improve driving safety and comfort of the host vehicle. The main idea of the approach is that the predicted acceleration commands of the host vehicle are stair-likely pre-planned to satisfy their changes along the same direction within the prediction horizon. The predictive cruise controller is then computed by online solving a finite horizon constrained optimal control problem with a decision variable. Besides explicitly handling safety constrain

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Marsat, Gary, and Leonard Maler. "Preparing for the unpredictable: adaptive feedback enhances the response to unexpected communication signals." Journal of Neurophysiology 107, no. 4 (2012): 1241–46. http://dx.doi.org/10.1152/jn.00982.2011.

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To interact with the environment efficiently, the nervous system must generate expectations about redundant sensory signals and detect unexpected ones. Neural circuits can, for example, compare a prediction of the sensory signal that was generated by the nervous system with the incoming sensory input, to generate a response selective to novel stimuli. In the first-order electrosensory neurons of a gymnotiform electric fish, a negative image of low-frequency redundant communication signals is subtracted from the neural response via feedback, allowing unpredictable signals to be extracted. Here

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Elsayed, Walaa M., Maazen Alsabaan, Mohamed I. Ibrahem, and Engy El-Shafeiy. "The Potential of Deep Learning in Underwater Wireless Sensor Networks and Noise Canceling for the Effective Monitoring of Aquatic Life." Sensors 24, no. 18 (2024): 6102. http://dx.doi.org/10.3390/s24186102.

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This paper describes a revolutionary design paradigm for monitoring aquatic life. This unique methodology addresses issues such as limited memory, insufficient bandwidth, and excessive noise levels by combining two approaches to create a comprehensive predictive filtration system, as well as multiple-transfer route analysis. This work focuses on proposing a novel filtration learning approach for underwater sensor nodes. This model was created by merging two adaptive filters, the finite impulse response (FIR) and the adaptive line enhancer (ALE). The FIR integrated filter eliminates unwanted no

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Sheh Zad, Haris, Abasin Ulasyar, Adil Zohaib, and Abraiz Khattak. "Adaptive sliding mode predictive power control of three-phase AC/DC converters." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 236, no. 5 (2022): 897–912. http://dx.doi.org/10.1177/09596518221079469.

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This article presents a new adaptive sliding mode–based model predictive controller for AC/DC three-phase converters achieving better dynamic performance and stability. In the classical model predictive controller available in the literature, the model-based approach, for example, proportional–integral controller is employed for producing the active power reference for the three-phase converters. The traditional proportional–integral–based model predictive controllers consist of steady-state error and slow transient response characteristics. As a result, the DC-link voltage contains uncertaint

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Looney, Timothy. "Skin mutation burden drives adaptive immunity and response to immunotherapy." Journal for ImmunoTherapy of Cancer 13, no. 2 (2025): e011062. https://doi.org/10.1136/jitc-2024-011062.

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Numerous studies over the past century have reported an inverse correlation between lifetime solar ultraviolet radiation (UV) exposure and all-cancer incidence and mortality. For decades, this relationship was hypothesized to reflect the action of photosynthesized vitamin D, though subsequent clinical trials have failed to demonstrate the expected anti-cancer properties. Rather than a consequence of vitamin D, I hypothesize that this inverse correlation reflects the immune stimulatory action of UV-derived skin neoantigens. Over time, such UV-mediated immune education drives immune repertoire d

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Ma, Jun, Zhiyuan Bo, Zhengxiao Zhao, et al. "Machine Learning to Predict the Response to Lenvatinib Combined with Transarterial Chemoembolization for Unresectable Hepatocellular Carcinoma." Cancers 15, no. 3 (2023): 625. http://dx.doi.org/10.3390/cancers15030625.

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Background: Lenvatinib and transarterial chemoembolization (TACE) are first-line treatments for unresectable hepatocellular carcinoma (HCC), but the objective response rate (ORR) is not satisfactory. We aimed to predict the response to lenvatinib combined with TACE before treatment for unresectable HCC using machine learning (ML) algorithms based on clinical data. Methods: Patients with unresectable HCC receiving the combination therapy of lenvatinib combined with TACE from two medical centers were retrospectively collected from January 2020 to December 2021. The response to the combination th

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Blomquist, Sean M., Trisha D. Johnson, David R. Smith, et al. "Structured Decision-Making and Rapid Prototyping to Plan a Management Response to an Invasive Species." Journal of Fish and Wildlife Management 1, no. 1 (2010): 19–32. http://dx.doi.org/10.3996/jfwm-025.

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Abstract We developed components of a decision structure that could be used in an adaptive management framework for responding to invasion of hemlock woolly adelgid Adeleges tsugae on the Cumberland Plateau of northern Tennessee. Hemlock woolly adelgid, an invasive forest pest, was first detected in this area in 2007. We used a structured decision-making process to identify and refine the management problem, objectives, and alternative management actions, and to assess consequences and tradeoffs among selected management alternatives. We identified four fundamental objectives: 1) conserve the

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Kuehnle, Ryan, Holly Grace, Anundip Gill, and Kenneth Westover. "Lung cancer complete radiographic response with PULSAR." BMJ Case Reports 18, no. 6 (2025): e263887. https://doi.org/10.1136/bcr-2024-263887.

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A woman in her early 80s with a history of smoking, limited scleroderma, interstitial lung disease (ILD) and pulmonary arterial hypertension developed a right suprahilar mass, avid on positron emission tomography (PET) scan. A biopsy was not performed due to the high risk of complications and the high positive predictive value of malignancy. She was staged as IA3: cT1c N0 M0 and recommended for empiric treatment with stereotactic ablative body radiotherapy (SABR). To manage the risk of treatment-related toxicity due to ILD and the tumour’s central location, an adaptive personalised ultra-fract

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Akinola, Segun, Reddy Leelakrishna, and Vijayakumar Varadarajan. "Enhancing cardiovascular disease prediction: A hybrid machine learning approach integrating oversampling and adaptive boosting techniques." AIMS Medical Science 11, no. 2 (2024): 58–71. http://dx.doi.org/10.3934/medsci.2024005.

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<abstract> <p>This study presents a novel approach to enhance cardiovascular disease prediction using a hybrid machine learning (ML) model. Leveraging on Synthetic Minority oversampling techniques (SMOTE) and adaptive boosting (AdaBoost), we integrate these methods with prominent classifiers, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Extra Tree (ET). Focused on heart rate data as stress level indicators, our objective is to jointly predict cardiovascular disease, thereby addressing the global health challenge of early detection and accurate risk assessm

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Xia, Yina, Seong-Yoon Shin, and Hyun-Ae Lee. "Adaptive Learning in AI Agents for the Metaverse: The ALMAA Framework." Applied Sciences 14, no. 23 (2024): 11410. https://doi.org/10.3390/app142311410.

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This study investigates the adaptability of Artificial Intelligence (AI) agents in the Metaverse, focusing on their ability to enhance responsiveness, decision-making, and engagement through the proposed Adaptive Learning Model for AI Agents (ALMAA) framework. The research does not introduce new interventions to existing platforms like Epic Games or AltspaceVR but instead analyzes how their operations align with adaptive learning principles. By examining these platforms, the study demonstrates the alignment between real-world practices and theoretical constructs, offering insights into how ada

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Wei, Wentian, Lan Li, Qiyuan Li, Song Zhang, Chaoqun Fan, and Lizhe Liang. "Dynamic Weight Model Predictive Control for Longitudinal Adaptive Cruise Systems in Electric Vehicles." Applied Sciences 15, no. 12 (2025): 6715. https://doi.org/10.3390/app15126715.

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This paper proposes a dynamic weight model predictive control (DWMPC) strategy for adaptive cruise control (ACC) in pure electric vehicles, aiming to enhance robustness, energy efficiency, and ride comfort under complex traffic conditions. Unlike conventional MPC with static weights, the proposed method integrates a fuzzy inference system that evaluates driving urgency based on real-time spacing and velocity errors. The resulting emergency coefficient is mapped through a nonlinear function to dynamically adjust the velocity tracking weight in the MPC cost function. Additionally, a four-mode co

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Sulistijanti, Wellie, and Nur Khotimah. "Comparing Time Series Predictions of COVID-19 Deaths Using SARIMAX, Neural Network, and XGBoost." Asian Journal of Engineering, Social and Health 3, no. 12 (2024): 2751–58. https://doi.org/10.46799/ajesh.v3i12.481.

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Accurate and timely prediction of the development of the Covid-19 pandemic is critical to enabling adaptive responses and supporting better decision-making in pandemic management. This research aims to evaluate the effectiveness of three prediction models—SARIMAX, Neural Network, and XGBoost—in forecasting Covid-19-related deaths worldwide. Historical data from July 1 to August 15, 2020, was utilized to develop and test these models, with performance assessed using Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE). The findings reveal that the XGBoost mode

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Nardoto, Adriano, Arthur Amorim, Nelson Santana, Emilio Bueno, Lucas Encarnação, and Walbermark Santos. "Adaptive Model Predictive Control for DAB Converter Switching Losses Reduction." Energies 15, no. 18 (2022): 6628. http://dx.doi.org/10.3390/en15186628.

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The solid-state transformer is the enabling technology for the future of electric power systems. The increasing relevance of this equipment demands higher standards for efficiency and losses reduction. The dual active bridge (DAB) topology is the most usual DC-DC converter used in the solid-state transformer, and is responsible for part of its switching losses. The traditional phase-shift modulation used on DAB converters presents significant switching losses during the operation with reduced loads. The alternative Triangular and Trapezoidal Modulations have been proposed in recent literature;

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Zhang, Junhui, Qing Li, and Dapeng Chen. "Vehicle-to-vehicle based multi-objective coordinated adaptive cruise control considering platoon stability." Advances in Mechanical Engineering 10, no. 10 (2018): 168781401880271. http://dx.doi.org/10.1177/1687814018802719.

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Currently, there is a widespread concern over cooperative driving based on vehicle-to-vehicle communication due to its considerable potential to improve the increased traffic safety, efficiency, costs, and intellectualization. In this article, a multi-objective coordinated adaptive cruise control algorithm for a string of adaptive cruise control–equipped vehicles is thus proposed, which can comprehensively address issues regarding homogeneous/heterogeneous features, road capacity, in addition to driver desired response. The practical platoon stability of adaptive cruise control–equipped vehicl

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