Vibrational Resonance and Electrical Activity Behavior of a Fractional-Order FitzHugh–Nagumo Neuron System

Making use of the numerical simulation method, the phenomenon of vibrational resonance and electrical activity behavior of a fractional-order FitzHugh–Nagumo neuron system excited by two-frequency periodic signals are investigated. Based on the definition and properties of the Caputo fractional derivative, the fractional L1 algorithm is applied to numerically simulate the phenomenon of vibrational resonance in the neuron system. Compared with the integer-order neuron model, the fractional-order neuron model can relax the requirement for the amplitude of the high-frequency signal and induce the phenomenon of vibrational resonance by selecting the appropriate fractional exponent. By introducing the time-delay feedback, it can be found that the vibrational resonance will occur with periods in the fractional-order neuron system, i.e., the amplitude of the low-frequency response periodically changes with the time-delay feedback. The weak low-frequency signal in the system can be significantly enhanced by selecting the appropriate time-delay parameter and the fractional exponent. In addition, the original integer-order model is extended to the fractional-order model, and the neuron system will exhibit rich dynamical behaviors, which provide a broader understanding of the neuron system.

Identifying regional variation in place visit behavior during a global pandemic

The emergence of the SARS-CoV-2 virus in 2019 lead to a global pandemic that altered the activity behavior of most people on our planet. While government regulations and public concern modified visitation patterns to places of interest, little research has examined the nuanced changes in the length of time someone spends at a place, nor the regional variability of these changes. In this work, we examine place visit duration in four major U.S. cities, identify which place types saw the largest and smallest changes, and quantify variation between cities. Furthermore, we identify socio-economic and demographic factors that contribute to changes in visit duration and demonstrate the varying influence of these factors by region. The results of our analysis indicate that the pandemic's impact on visiting behavior varies between cities, though there are commonalities found in certain types of places. Our findings suggest that places of interest within lower income communities experienced less change in visit duration than others. An increase in the percentage of younger, Black or Hispanic populations within a community also resulted in a smaller decrease in visit duration than in other communities. These findings offer insight into the factors that contribute to changes in visiting behavior and the resilience of communities to a global pandemic.

Effectiveness of additional resistance and balance training and telephone support program in exercise-based cardiac rehabilitation on quality of life and physical activity: Randomized control trial

Objectives To evaluate 20 days and 3 months follow-up effectiveness of cardiac rehabilitation (CR) enhanced by resistance/balance training and telephone-support program compared to usual CR care in improving quality of life, clinical course and physical activity behavior. Design Single-centre randomized controlled trial. Setting Inpatient CR clinic Subjects 116 (76.1 ± 6.7 years, 50% male) patients 14.5 ± 5.9 days after valve surgery/intervention were randomized to intervention group (IG, n = 60) or control group (CG, n = 56). Intervention Additional resistance/balance training (3 days/week) during phase-II CR and telephone-support program during 3-month follow-up. CG patients were provided with usual CR care. Main measures Short Form 36 Health Survey scales, European Quality of Life 5 Dimensions 3 Level Version QoL index, visual analog scale, clinical course, and physical activity behavior assessed with standardized questionnaires. Results IG reported statistically significant higher mental component score (48.5 ± 6.91 vs. 40.3 ± 11.21 at the baseline, 50.8 ± 9.76 vs. 42.6 ± 9.82 after 20 days, 49.4 ± 8.45 vs. 40.5 ± 8.9 after 12 weeks follow up), general health (48.6 ± 3.17 vs. 45.0 ± 2.95 at the baseline, 53.6 ± 3.02 vs. 43.8 ± 2.55 after 20 days, 53.2 ± 3.11 vs. 44.2 ± 3.07 after 12 weeks) and role limitations due to emotional problems (48.5 ± 15.2 vs. 27.7 ± 11.5 at the baseline, 72.7 ± 12.6 vs. 30.5 ± 11.2 after 20 days, 66.6 ± 14.2 vs. 36.1 ± 11.2 after 12 weeks) in all three assessments ( p < 0.05). CG patients had more documented hospital admissions (4 (8%) vs 10 (25%), p = 0.027), atrial fibrillation paroxysms (3 (6.0%) vs. 10 (35.0%), p = 0.011) and blood pressure swings (13 (26%) vs. 20 (50%), p = 0.019). IG patients chose more different physical activities (1.7 ± 0.7 vs. 1.25 ± 0.63, p = 0.002), spent more time being physical active every day (195.6 ± 78.6 vs. 157.29 ± 78.8, p = 0.002) Conclusions The addition of resistance/balance exercises and telephone-support program 12 weeks after to the CR could linked to higher physical activity levels and fewer clinical complications but did not lead to a significant improvement in quality of life.

Prediction of Enterprise Economic Activity Behavior Based on Neural Network and ARIMA Hybrid Model

Enterprise economy refers to the comprehensive situation reflected in the gross product, production scale, total production and efficiency, technological content, marketing means, and so on; under certain social conditions, enterprises use resources obtained by law to engage in economic activities. Under the guidance of consciousness or culture, enterprises use “legally obtained resources” to promote economic development. Enterprise economy is affected by manpower, capital, management, operation, policy, and other aspects. In the context of the rapid development of big data in the current era, this paper proposes a prediction model of enterprise economic activity behavior based on neural network and ARIMA by investigating a variety of artificial intelligence models and verifies its feasibility. Commodity circulation enterprises have a more urgent demand for the development of business audit due to their operation characteristics. Therefore, this paper takes commodity circulation enterprises as representatives and predicts business audit in the big data environment based on the model proposed in this paper.

Let’s build an app for that

The promotion of physical activity behavior change among adults with cancer is a research priority. Within this field, increasing attention is being devoted to the use of health technology, which includes mobile phones and applications, or apps, to support and deliver physical activity behavior change interventions. While building a mobile app is a popular proposal among exercise oncology researchers, little practical information exists on how this process should be done or what considerations researchers should take in collaboration with participants and industry. The present article provides an overview of recent experiences with app development in exercise oncology and outlines several recommendations for future research. Methods and Results: After forming an interdisciplinary team of researchers, industry partners, and exercise oncology program participants, an iterative, user-centered app improvement process was followed to collect feedback and make meaningful changes to an existing mobile health app for its use in exercise oncology. Participant feedback was summarized and addressed collaboratively via open discussion and detailed action plans. Changes made include enhanced introductory materials for the app and improvements to usability and personalization. Some requests remain to be addressed in future updates. Two challenges identified during the app improvement process were balancing the unique needs and priorities of all parties, as well as addressing the variable feedback from a variable population of adults with cancer. Conclusions and significance: A multidisciplinary participant-oriented app improvement process led to meaningful updates to the mobile application of interest, preparing researchers to carry out an evaluation of its effectiveness within exercise oncology. Furthermore, based on lessons learned, the research team present key recommendations to consider in future mobile app research before, during, and after the development process.