Nonlinear inferential multi-rate control of Kappa number at multiple locations in a continuous pulp digester

The continuous pulp digester represents a large-scale, distributed parameter system. Control of the spatial profile of degree of cooking, characterized by the Kappa number, rather than its endpoint value can effectively control properties that are dependent on the history of cooking. However, profile control of such large-scale distributed parameter systems throws up new challenges in estimation and control. We design a nonlinear model predictive controller using a multi-rate extended Kalman filter to infer and control discrete points along the Kappa number profile. Both, the plant and controller models are based on first principles. The design is tested for significant mismatches in parameters, initial state errors, and stochastic disturbances in the entering wood composition.     

Sb-Mediated Tuning of Growth- and Exciton Dynamics in Entirely Catalyst-Free GaAsSb Nanowires

Vapor-liquid-solid (VLS) growth is the mainstream method in realizing advanced semiconductor nanowires (NWs), as widely applied to many III-V compounds. It is exclusively explored also for antimony (Sb) compounds, such as the relevant GaAsSb-based NW materials, although morphological inhomogeneities, phase segregation, and limitations in the supersaturation due to Sb strongly inhibit their growth dynamics. Fundamental advances are now reported here via entirely catalyst-free GaAsSb NWs, where particularly the Sb-mediated effects on the NW growth dynamics and physical properties are investigated in this novel growth regime. Remarkably, depending on GaAsSb composition and nature of the growth surface, both surfactant and anti-surfactant action is found, as seen by transitions between growth acceleration and deceleration characteristics. For threshold Sb-contents up to 3–4%, adatom diffusion lengths are increased ≈sevenfold compared to Sb-free GaAs NWs, evidencing the significant surfactant effect. Furthermore, microstructural analysis reveals unique Sb-mediated transitions in compositional structure, as well as substantial reduction in twin defect density, ≈tenfold over only small compositional range (1.5–6% Sb), exhibiting much larger dynamics as found in VLS-type GaAsSb NWs. The effect of such extended twin-free domains is corroborated by ≈threefold increases in exciton lifetime (≈4.5 ns) due to enlarged electron-hole pair separation in these phase-pure NWs.     

Power Optimized Multiple-UAV Error-Free Network in Cognitive Environment

Many extensive UAV communication networks have used UAV cooperative control. Wireless networking services can be offered using unmanned aerial vehicles (UAVs) as aerial base stations. Not only is coverage maximization, but also better connectivity, a fundamental design challenge that must be solved. The number of applications for unmanned aerial vehicles (UAVs) operating in unlicensed bands is fast expanding as the Internet of Things (IoT) develops. Those bands, however, have become overcrowded as the number of systems that use them grows. Cognitive Radio (CR) and spectrum allocation approaches have emerged as a potential approach for resolving spectrum scarcity in wireless networks, and hence as technological solutions for future generations, from this perspective. As a result, combining CR with UAVs has the potential to give significant benefits for large-scale UAV deployment. The paper examines existing research on the subject of UAV covering and proposes a multi-UAV cognitive-based error-free model for energy-efficient communication. Coverage maximization, power control, and enhanced connection quality are the three steps of the proposed model. To satisfy the desired signal-to-noise ratio, the covering zone efficacy is investigated as a function of the distance among UAVs stationed in a specific geographic region depending on multiple deployment configurations like as rural, suburban, and urban macro deployment scenarios of the ITU-R M.2135 standard (SNR).     

Proton-Conducting Hierarchical Composite Hydrogels Producing First Soft Memcapacitors with Switchable Memory

Perpetual exigency for environment friendly clean energy and powerful soft electronics has elevated the research on hydrogels in past two decades. Hydrogels are the amplifiers of material properties using manipulation in structure–property relationship via simple, economic yet effective routes. Herein, a set of composite and hybrid hydrogels are developed by hierarchical assembling of clay nanosheets and surfactant micelles those divulge the first example of memcapacitor gels and offer exceptional proton conductivity (1.66–4.34 × 10^–2 S cm⁻¹) as a gel material. Further, Congo red, Eosin Y, and Orange G are used to hybridize one of the composites to achieve three hybrid hydrogels. Such hybridization is found to regulate the memristive function selectively from the coupled effect of memcapacitance from the composite. The composite hydrogel highlights its volatile memory with encouraging robustness under environmental conditions, established through various current–voltage (I–V) experiments. The electrochemical behaviors including the high proton conductivity are realized from impedance measurements. Material characterizations, experimental results, and in silico optimized structures rationalize composite/hybrid network formation, capacitive/memristive responses, and enhanced proton conduction in the fabricated composite superstructures. Proposed structural models demonstrate two orthogonally oriented structural encryptions to be accountable for the expressed bifunctionality in the hierarchically designed superstructures.     

Legendre wavelet method for solving variable-order nonlinear fractional optimal control problems with variable-order fractional Bolza cost

This paper deals with a numerical method for solving variable-order fractional optimal control problem with a fractional Bolza cost composed as the aggregate of a standard Mayer cost and a fractional Lagrange cost given by a variable-order Riemann–Liouville fractional integral. Using the integration by part formula and the calculus of variations, the necessary optimality conditions are derived in terms of two-point variable-order boundary value problem. Operational matrices of variable-order right and left Riemann–Liouville integration are derived, and by using them, the two-point boundary value problem is reduced into the system of algebraic equations. Additionally, the convergence analysis of the proposed method has been considered. Moreover, illustrative examples are given to demonstrate the applicability of the proposed method.     

Biochemical composition,protein quality and amino acid profile of red-toothed triggerfish (Odonus niger), an underutilised fish

The present study aims to assess the seasonal and sex-wise variations in proximate composition, amino acid profile and protein quality of Odonus niger, which will be the first report for this species. High-protein (15.15%–20.05%) and low-fat contents (0.46%–1.94%) were observed for the species studied. The highest protein was observed in September and December for male and female fishes respectively. The total essential amino acid (TEAA) content was 58.65–77.41 mg g⁻¹ (males) and 60.25–77.38 mg g⁻¹ (females) and leucine was the predominant EAA in both the sexes. The EAA index and biological value ranged between 17.50–22.56 and 7.38–12.89 for males and 18.02–22.48 and 7.94–12.80 for female fishes respectively. In male, TEAA followed Sept>Jan > Dec > Aug > Oct > Nov and in female it was Oct > Sept>Dec > Nov > Aug > Jan. The chemical score for histidine and threonine was more than the FAO recommended values. Overall, the nutritional quality of this unconventional species proved very good and comparable with other commercially important lean fishes.