Fixed-time sliding-mode distributed consensus and formation control of disturbed fractional-order multi-agent systems.

In this paper, fixed-time consensus and formation control for fractional-order multi-agent systems with a dynamic virtual leader in the presence of external disturbances is investigated. Consensus is achieved in fixed-time, i.e., with a finite settling time whose upper bound is independent of the initial conditions of the agents' states. A new distributed sliding-mode control with neighborhood-based error variable is proposed to track a virtual leader in order to achieve a desired consensus in the presence of disturbances. Furthermore, the fractional Lyapunov stability theorem has been employed to prove the fixed-time stability and to estimate the upper bound of convergence. The formation of agents has also been investigated for the agents of fractional-order. Finally, several numerical simulations are provided to determine the effectiveness of the design method.

Fundamental Trade-Offs Between Power and Data Transfer in Inductive Links for Biomedical Implants.

This paper studies the fundamental trade-offs between power transfer efficiency (PTE) and spectral efficiency that occur during simultaneous power and data transfer through near-field inductive links. A mathematical analysis is used to establish the relationship between PTE and channel capacity as a function of link parameters such as coupling coefficient ( k), load resistance, and surrounding environment. The analysis predicts that the optimum trade-off between power and data transfer is particularly dependent on k, which is a monotonically-decreasing function of axial distance ( d) between the coils. Real-time adaptation of the link parameters (such as load resistance and modulation type) is proposed to automatically optimize the power-data trade-off over a wide range of distances and coupling coefficients. A bench-top prototype of such an adaptive link is demonstrated at a center frequency of 13.56 MHz. The prototype uses an ultrasound transducer to measure d with accuracy  mm, and uses this information to autonomously optimize both data rate (up to  âˆ¼ 50 Mbps) and PTE (up to  âˆ¼ 25%) as the coil-coil distance varies within the 4-15 mm range.

Impact of climate change on net primary production (NPP) in south Iran.

Climate change is a natural hazard which threatens the sustainable development of human health, food security, economic well-being, and natural resources. It also affects photosynthesis, plant respiration, and decomposition of organic matter that contribute to atmospheric carbon flow. The net primary production (NPP) is one of the main components of carbon balance. This study investigated the impact of climatic change on the net production in the Hormozgan county in south Iran. To obtain NPP, MODIS NPP product (MOD17A3) was used and future temperature and precipitation values were obtained using the HadGEM2-ES model under the RCP4.5 scenario. These values were downscaled using the LARSWG 6 statistical model, and precipitation and temperature were simulated for the RCP4.5 scenario. For further analysis, NPP was simulated based on the BIOME-BGC model and compared with the NPP data obtained from the MODIS images. Comparison of the climatic parameters of the basic (2001-2015) and future (2016-2030) periods indicated an increase in precipitation, minimum temperature, and maximum temperature of the study area and subsequently an increase in the NPP value in all biomes (averagely 17.73%) in the future. The highest NPP values were observed in the central and western parts of the region in biomes 4 (mangrove forest cover), 10 (broadleaf forest vegetation), and 6, 5, and 1 (rangeland vegetation), respectively, and the lowest values were observed in the eastern parts. Results showed that the increase in future NPP could be due to the increase in precipitation.

Vector analysis of changes in corneal astigmatism following lateral tarsal strip procedure in patients with involutional ectropion or entropion.

PURPOSE: To perform vector analysis of changes in corneal astigmatism and evaluate changes in corneal topographic parameters following the lateral tarsal strip (LTS) procedure in patients with involutional ectropion or entropion. METHODS: Nineteen eyes of 15 patients (10 eyes with ectropion and 9 eyes with entropion) were included in this prospective nonrandomized interventional case series. Corneal topographic measurements (Tomey TMS 4a topographer, Tomey Corp, Nagoya, Japan) were performed at the baseline and 3 months after the LTS procedure. Relevant changes in the topographic astigmatism magnitude or axis (defined as a change more than 0.2 D or a shift in the axis greater than 10°, respectively) were analyzed following surgery. Polar astigmatic vector analysis was performed using the Astig PLOT software to calculate surgically induced astigmatism (SIA). RESULTS: There were no significant changes in average keratometry, steep and flat meridian keratometric values, absolute cylinder, surface regularity index and surface asymmetry index after the surgery (All P > 0.05). A relevant change in the magnitude of astigmatism and an axis change greater than 10° occurred in 14 (73.6%) and 10 (52.6%) of the operated eyes, respectively. Polar vector analysis revealed that SIA was 0.47 ± 1.34 D at 91 ± 23°, indicating induction of "with the rule" astigmatism following the surgery. CONCLUSION: The LTS procedure for the correction of involutional ectropion or entropion could induce relevant changes in corneal astigmatism, sufficient to affect visual function in short term. Longer-term follow-up is required to further characterize the effect of LTS procedure on the corneal topographic features.

C-FSCV: Compressive Fast-Scan Cyclic Voltammetry for Brain Dopamine Recording.

This paper presents a novel compressive sensing framework for recording brain dopamine levels with fast-scan cyclic voltammetry (FSCV) at a carbon-fiber microelectrode. Termed compressive FSCV (C-FSCV), this approach compressively samples the measured total current in each FSCV scan and performs basic FSCV processing steps, e.g., background current averaging and subtraction, directly with compressed measurements. The resulting background-subtracted faradaic currents, which are shown to have a block-sparse representation in the discrete cosine transform domain, are next reconstructed from their compressively sampled counterparts with the block sparse Bayesian learning algorithm. Using a previously recorded dopamine dataset, consisting of electrically evoked signals recorded in the dorsal striatum of an anesthetized rat, the C-FSCV framework is shown to be efficacious in compressing and reconstructing brain dopamine dynamics and associated voltammograms with high fidelity (correlation coefficient, ), while achieving compression ratio, CR, values as high as ~ 5. Moreover, using another set of dopamine data recorded 5 minutes after administration of amphetamine (AMPH) to an ambulatory rat, C-FSCV once again compresses (CR = 5) and reconstructs the temporal pattern of dopamine release with high fidelity ( ), leading to a true-positive rate of 96.4% in detecting AMPH-induced dopamine transients.