Finite-time synchronization of Markovian neural networks with proportional delays and discontinuous activations

In this paper, finite-time synchronization of neural networks (NNs) with discontinuous activation functions (DAFs), Markovian switching, and proportional delays is studied in the framework of Filippov solution. Since proportional delay is unbounded and different from infinite-time distributed delay and classical finite-time analytical techniques are not applicable anymore, new 1-norm analytical techniques are developed. Controllers with and without the sign function are designed to overcome the effects of the uncertainties induced by Filippov solutions and further synchronize the considered NNs in a finite time. By designing new Lyapunov functionals and using M-matrix method, sufficient conditions are derived to guarantee that the considered NNs realize synchronization in a settling time without introducing any free parameters. It is shown that, though the proportional delay can be unbounded, complete synchronization can still be realized, and the settling time can be explicitly estimated. Moreover, it is discovered that controllers with sign function can reduce the control gains, while controllers without the sign function can overcome chattering phenomenon. Finally, numerical simulations are given to show the effectiveness of theoretical results

Antecedents of retweeting in a (political) marketing context

Word of mouth disseminates across Twitter by means of retweeting; however the antecedents of retweeting have not received much attention. This study uses the CHAID decision tree predictive method (Kass, 1980) with readily available Twitter data, and manually coded sentiment and content data, to identify why some tweets are more likely to be retweeted than others in a (political) marketing context. The analysis includes four CHAID models: (i) using message structure variables only, (ii) source variables only, (iii) message content and sentiment variables only and (iv) a combined model using source, message structure, message content and sentiment variables. The aggregated predictive model correctly classified retweeting behavior with a 76.7% success rate. Retweeting tends to occur when the originator has a high number of Twitter followers and the sentiment of the tweet is negative, contradicting previous research (East, Hammond, & Wright, 2007; Wu, 2013) but concurring with others (Hennig-Thurau, Wiertz, & Feldhaus, 2014). Additionally, particular types of tweet content are associated with high levels of retweeting, in particular those tweets including fear appeals or expressing support for others, whilst others are associated with very low levels of retweeting, such as those mentioning the sender’s personal life. Managerial implications and research directions are presented. The study makes a methodological contribution by illustrating how CHAID predictive modelling can be used for Twitter data analysis and a theoretical contribution by providing insights into why retweeting occurs in a (political) marketing context

Biomechanical Analysis of Grafted and Nongrafted Maxillary Sinus Augmentation in the Atrophic Posterior Maxilla with Three-Dimensional Finite Element Method

This study is aimed at determining the optimal sinus augmentation approach considering the poor bone condition in the zone of atrophic posterior maxilla. A series of simplified maxillary segment models varying in residual bone height (RBH) and bone quality were established. A 10 mm standard implant combined with two types of maxillary sinus augmentation methods was applied with the RBH, which was less than 10 mm in the maxilla. The maximal equivalent von Mises (EQV) stress in residual bone was evaluated. Bone quality had an enormous impact on the stress magnitude of supporting bone. Applying sinus augmentation combined with grafts was suitable for stress distribution, and high-stiffness graft performed better than low-stiffness one. For 7 mm and 5 mm atrophic maxilla, nongrafted maxillary sinus augmentation was feasible in D3 bone. Poor bone quality was a negative factor for the implant in the region of atrophic posterior maxilla, which could be improved by grafts. Meanwhile, the choice of maxillary sinus augmentation approaches should be determined by the RBH and quality

A Real-Time Automated System for Monitoring Individual Feed Intake and Body Weight of Group-Housed Young Chickens

The feeding behavior of poultry at a young age is very likely to determine the final growth of the chicken, and can also reflect the feeding status and the health status. It is also of great significance for breeding. This paper describes the development and testing of a real-time automated system and a single passage for monitoring the individual feed intake and body weight of poultry. This system integrates an automatic feeding mechanism, an RFID reading module, a weight scale, a feed scale, and a drop weighting scale. The system uses analog circuits and digital filtering to improve the weighing accuracy, and directly measures the amount of feed falling to the ground using a high-precision weighing scale. Through the sequential opening and closing of a sliding door, group-housed chickens are separated so that the young ones are fed individually. As a result of the experiment, we learned that a young chicken grows at a rate of about 8.88 g/day, and the food conversion rate (FCR) is about 4.4, which proves that this system matches the single passage and can accurately monitor the body weight change and feeding behavior of young chickens

A Real-Time Automated System for Monitoring Individual Feed Intake and Body Weight of Group-Housed Young Chickens

The feeding behavior of poultry at a young age is very likely to determine the final growth of the chicken, and can also reflect the feeding status and the health status. It is also of great significance for breeding. This paper describes the development and testing of a real-time automated system and a single passage for monitoring the individual feed intake and body weight of poultry. This system integrates an automatic feeding mechanism, an RFID reading module, a weight scale, a feed scale, and a drop weighting scale. The system uses analog circuits and digital filtering to improve the weighing accuracy, and directly measures the amount of feed falling to the ground using a high-precision weighing scale. Through the sequential opening and closing of a sliding door, group-housed chickens are separated so that the young ones are fed individually. As a result of the experiment, we learned that a young chicken grows at a rate of about 8.88 g/day, and the food conversion rate (FCR) is about 4.4, which proves that this system matches the single passage and can accurately monitor the body weight change and feeding behavior of young chickens

The Antioxidant Phytochemical Schisandrin A Promotes Neural Cell Proliferation and Differentiation after Ischemic Brain Injury

Schisandrin A (SCH) is a natural bioactive phytonutrient that belongs to the lignan derivatives found in Schisandra chinensis fruit. This study aims to investigate the impact of SCH on promoting neural progenitor cell (NPC) regeneration for avoiding stroke ischemic injury. The promoting effect of SCH on NPCs was evaluated by photothrombotic model, immunofluorescence, cell line culture of NPCs, and Western blot assay. The results showed that neuron-specific class III beta-tubulin (Tuj1) was positive with Map2 positive nerve fibers in the ischemic area after using SCH. In addition, Nestin and SOX2 positive NPCs were significantly (p < 0.05) increased in the penumbra and core. Further analysis identified that SCH can regulate the expression level of cell division control protein 42 (Cdc42). In conclusion, our findings suggest that SCH enhanced NPCs proliferation and differentiation possible by Cdc42 to regulated cytoskeletal rearrangement and polarization of cells, which provides new hope for the late recovery of stroke

Additional file 1 of Psychometric properties and latent profile analysis of the Nursing Brand Image Scale: a methodological study in the Chinese context

Additional file 1: Appendix 1. Independent samplest-test. Appendix 2. Path analysis, average variance extracted and composite reliab. Appendix 3. Model fit. Appendix 4. Model comparisons for Multi-Group CF

Modelling soybean and maize growth and grain yield in strip intercropping systems with different row configurations

Intercropping of two or more crop species increases the efficiency of resource use and often produces a greater yield per unit land area. The relative efficiency of intercropping depends on row configuration, but there is a shortage of modelling-based evaluation of alternative intercropping options due to the inadequacy of standard process-based crop models to simulate resource capture, growth and yield formation when the canopy is spatially structured in strips. We implemented a light interception model for strip crops into the APSIM Classic model and combined it with a quasi-Bayesian approach to derive the model parameters to simulate crop growth and grain yield in maize-soybean strip intercropping. We used 4 years of field data for 5 different row configurations to derive key model parameters for simulation of light interception, LAI dynamics, biomass growth and grain yield of maize and soybean intercrops. Key model parameters (e.g. RUE, k etc.) were found to change with row-spacing and configuration, posing challenges to simulate different configurations with a single parameter set. The potential ranges of these key parameters were derived by constraining the model to observed data. The model can be potentially used to evaluate impact of planting configurations on productivity of strip intercropping systems, but the variability of key model parameters among configuration treatments calls for further in-depth research to improve modelling physiology of strip intercrops.</p