Search Results (40)

This paper presents a low-power fully integrated sine signal generator for on-chip bioimpedance spectroscopy applications. The circuit is based on a relaxation oscillator, which generates a triangular signal, followed by a sixth-order Gm-C bandpass filter (BPF) that linearizes the waveform. Both blocks, designed in a 0.18 $\mathrm{\mu }$m CMOS process with 1.8 V supply, make use of a current division technique to generate low-frequency signals without requiring high-valued passive components. The relaxation oscillator features an extended frequency tuning range from 300 Hz to 300 kHz, controlled via a tuning current and a digital capacitor bank. The sine output waveform spans from 1 kHz to 50 kHz, and exhibits a −48.8 dB total harmonic distortion at 10 kHz with 18 mV amplitude. The overall system area is 0.7 ${\mathrm{mm}}^2$ and the power consumption is lower than 30 $\mathrm{\mu }$W. Full article

Linear alkylbenzene (LAB) is the main raw material used to make biodegradable detergents, and its production process is based on aromatic alkylation. HY zeolites that have undergone controlled dealumination and desilication have led industrial standards amongst solid acid catalysts because of their controllable acidity and hierarchical pore structure. Coke formation in such systems can assume a dual role, which is dependent on its condition. Though the over-deposition is known to cause deactivation by blocking the micropores, Bronsted acid-site masking, and diffusion collapse, the low-level deposition could also be done to increase the monoalkylate selectivity by the pore mouth catalysis, steric modulation, and selective suppression of secondary alkylation pathways. The critical review is done on the structural-kinetic interaction that determines the coke evolution in HY-based catalysts. In order to moderate the acid-site density and enhance hydrothermal stability, dealumination (Si/Al optimization of about 2.5 to 30–100) occurs, but to reduce deep-pore coke formation, desilication (interconnected mesopores) is created. The bimodal porosity and regulated acidity are found to be synergistic, as hierarchical HY zeolites produced through successive cycles of steam and alkaline treatments not only show LAB selectivity in excess of 90% but also exhibit much longer catalyst lifetimes. Quantitative research on the beneficial coke regime revealed that it was composed of about 36 wt% hydrogen-rich species, which were localized at the pore mouths, hence enhancing monoalkylation selectivity by 15–40%. Beyond a critical transition window (e.g., 8–12 wt.%), coke formation to condensed polyaromatic and graphitic products leads to fast deactivated coke formation, which is due to percolation limits and transport-controlled kinetics. More advanced techniques of characterization of the coke, e.g., temperature-programmed oxidation (TPO), ²⁷Al MAAS NMR, and UV-Raman spectroscopy, indicate how the coke is changed to highly structured graphitic deposits of high oxidation activation energy. Activity recovery of 85–98% is obtained in regeneration processes, including controlled oxidative calcination, microwave-based and plasma-based processes, and thermal management protocols, and it would be determined by the chemistry of the coke, its spatial distribution, and the regeneration protocols. This paper has developed a mechanistic coke control system by cross-tuning the acidity and development of an effective pore network, which led to a sustainable aromatic alkylation reaction with minimal activity loss, high selectivity, and long life. Full article

This paper develops an algebraic framework for operator matrix polynomials and demonstrates its application to control-design problems in aeroservoelastic systems. We present constructive spectral-factorization and linearization tools (block spectral divisors, companion forms and realization algorithms) that enable systematic block-pole assignment for large-scale MIMO models. Building on this theory, an adaptive block-pole placement strategy is proposed and cast in a practical implementation that augments a nominal state-feedback law with a compact neural-network compensator (single hidden layer) to handle un-modeled nonlinearities and uncertainty. The method requires state feedback and the system’s nominal model and admits Laplace-domain analysis and straightforward implementation for a two-degree-of-freedom aeroelastic wing with cubic stiffness nonlinearity and Roger aerodynamic lag is validated in MATLAB R2023a. Comprehensive simulations (Runge–Kutta 4) for different excitations and step disturbances demonstrate the approach’s advantages: compared with Eigenstructure assignment, LQR and $H_2$-control, the proposed method achieves markedly better robustness and transient performance (e.g., closed-loop ${‖\mathit{H}\left(i\omega \right)‖}_2$ ≈ 4.64, condition number χ ≈ 11.19, and reduced control efforts μ ≈ 0.41, while delivering faster transients and tighter regulation (rise time ≈ 0.35 s, settling time ≈ 1.10 s, overshoot ≈ 6.2%, steady-state error ≈ 0.9%, disturbance-rejection ≈ 92%). These results confirm that algebraic operator-polynomial techniques, combined with a compact adaptive NN augmentation, provide a well-conditioned, low-effort solution for robust control of aeroelastic systems. Full article

A bias-free antenna tuning technique that eliminates conventional DC biasing networks is presented. The tuning mechanism is based on a Light-Dependent Resistor (LDR) embedded within the antenna structure. Optical illumination is used to modulate the LDR’s resistance, thereby altering the antenna’s effective electrical length and enabling tuning of its resonant frequency and operating bands. By removing the need for bias lines, RF chokes, blocking capacitors, and control circuitry, the proposed approach minimizes parasitic effects, losses, biasing energy, and routing complexity. This makes it particularly suitable for compact and energy-constrained platforms, such as Internet of Things (IoT) devices. As proof of concept, an LDR is integrated into a ring monopole antenna, achieving tri-band operation in both high and low resistance states. In the high-resistance (OFF) state, the fabricated prototype operates across 2.1–3.1 GHz, 3.5–4 GHz, and 5–7 GHz. In the low-resistance (ON) state, the LDR bridges the two arcs of the monopole, extending the current path and shifting the lowest band to 1.36–2.35 GHz, with only minor changes to the mid and upper bands. The antenna maintains linear polarization across all bands and switching states, with measured gains reaching up to 5.3 dBi. Owing to its compact, bias-free, and low-cost architecture, the proposed design is well-suited for integration into portable wireless devices, low-power IoT nodes, and rapidly deployable communications systems where electrical biasing is impractical. Full article

This paper presents a novel control-based observer (CbO) framework for robust state and disturbance estimation in the longitudinal dynamics of fixed-wing aircraft. In this approach, the observer design problem is recast as an equivalent control problem, enabling the use of advanced control techniques for observer synthesis. Within the proposed framework, the estimation of both system states and unknown disturbance inputs is achieved by integrating disturbance rejection capabilities into the control sub-block of the observer. This integration ensures that the output mismatch between the plant and observer model is minimized, even in the presence of modeling uncertainties and external disturbances. Two observer designs are developed: (i) an ${\mathcal{H}}_{\infty }$-CbO, formulated as an ${\mathcal{H}}_{\infty }$ control problem around a linearized model at a nominal operating point, and (ii) a robust ${\mathcal{H}}_{\infty }$-CbO, which extends the design to account for significant model nonlinearities and variations by incorporating multiple operating points and optimizing for the worst-case estimation error. The longitudinal dynamics of a fixed-wing aircraft are derived and linearized to provide the basis for observer design. The performance of the proposed observers is evaluated through comprehensive simulation studies under three scenarios: operation at the nominal point, operation around neighboring points, and comparison with conventional linear observers. Simulation results demonstrate that the proposed observer offers superior robustness and accuracy in estimating both states and external disturbances, particularly in the presence of model uncertainties and varying flight conditions. Full article

This paper explores the use of a solid state transformer (SST) to mitigate the $E_{3A}$ component of a high-altitude electromagnetic pulse (HEMP) insult using external energy storage optimal control techniques. In lieu of conventional passive blocking devices or feedback-controlled energy storage devices, a novel implementation of Hamiltonian error tracking is utilized to develop a feedback control law for the variable converter ratio in an SST. The findings of the simulations performed in this paper suggest that additional energy storage is not necessary to protect an individual load from a HEMP insult. The simulations performed examine the response of a single-phase SST connected to a single voltage source on a long transmission line on the one side and a single linear resistor on the other. The control law is specifically developed for the late-time, low-frequency portion of a HEMP insult, namely the $E_{3A}$ components. The Hamiltonian error-based converter ratio control law is compared with nonlinear optimal feedforward controls to show that the HSSPFC is an external energy storage optimal controller. Full article

Background: Pinus pinea L. (stone pine) produces pine nuts of high value. Its cultivation is carried out in forests and plantations, with intensive management techniques being studied to stimulate diameter growth, which is positively related to cone production. Aims: To evaluate the effect of fertilization in a 30-year-old plantation and to understand if adult trees respond to nutritional management. Methods: A trial with completely randomized block design was established with two treatments (fertilization/control) and three repetitions. The plantation, with a density of 204 trees/ha, is located in central Chile, on a sandy-loam soil with neutral pH, medium organic matter content, and a fertility condition that limits tree development. Fertilization considered the repeated application of macro (N, P, K, S, Mg) and micronutrients (B, Fe, and Zn). Periodic measurements of height, stem and crown diameter, and cone production were made up to age 36. Cone production was evaluated using mixed generalized linear models and growth variables using ANOVA (analysis of variance). Results: Significant effects of fertilization on DBH annual growth (35% higher than the control, p < 0.001) and in cone production (3 times higher, p < 0.0001) were found. Conclusions: Fertilization is a useful practice to improve the growth and cone productivity of the species. Full article

As irrigation districts rapidly advance in terms of informatization, research on intelligent water quantity control technologies for open channels has gained increasing importance. This study aims to investigate the flow capacity and hydraulic characteristics of gates in open channels, focusing on the flow measurement and the hydraulic behavior around water-measuring structures. Although automated control in irrigation systems has achieved significant development, research on the flow characteristics near gates remains limited. To address this gap, an integrated approach combining indoor physical model experiments with theoretical analysis was used. This study explored the water surface profile, cross-sectional flow velocity distribution, vertical velocity distribution, and turbulent kinetic energy under various gate opening conditions and flow rates. The findings reveal that the water surface exhibits a sharp rise upstream of the gate, followed by a steep decline and stabilization downstream, influenced by the gate’s water-blocking effect. The flow velocities near the gate opening differ significantly in direction and magnitude from those in other cross-sections, affecting both longitudinal and vertical velocities. The turbulent kinetic energy is concentrated near the gate opening, and the turbulent kinetic energy is primarily concentrated near the sidewalls and the channel bottom; the gate’s opening size plays a crucial role in its diffusion and distribution. Linear regression analysis was utilized to fit the gate flow coefficient formula, and a comparative analysis of the measurement accuracy was conducted. The relative error between the calculated flow values and the actual measured values is within ±5%, which meets the precision requirements specified in the water measurement standards for irrigation canal systems in the irrigation district. This study pioneers an integrated approach for investigating the hydraulic characteristics of gates in open channels, merging physical model experiments with theoretical analysis. It provides novel insights into how gate openings affect water surface profiles, flow velocity distributions, and turbulent kinetic energy. This research also underscores the role of gate discharge in turbulent kinetic energy distribution, offering technical insights to enhance flow measurement accuracy and prevent sediment deposition, thereby optimizing gate applications for efficient water management. Overall, this study significantly advances the understanding of open channel flow dynamics and holds substantial significance for the refinement of water quantity control techniques in irrigation districts. Full article

This study presents a robust version of Light Cipher Block (LCB) by addressing the vulnerabilities identified in previous versions. The vulnerabilities in LCB, including a linear S-Box, improper bit shuffling, and subkey reusability, were thoroughly examined. To overcome these weaknesses, a modified version called Secure LCB is introduced, incorporating changes to the P-Box and key generation algorithm. Motivated by Gohr’s work at CRYPTO’19, this paper investigates the use of a neural distinguisher built upon a 1-dimensional convolutional neural network (1-d CNN). The deep learning model is tasked with identifying ciphertexts that have a specific, controlled difference in their inputs, as opposed to those with random input differences. The evaluation of the proposed Secure LCB using the neural distinguisher suggests that the modifications made to LCB have effectively enhanced its resistance against the neural distinguisher’s classification. This highlights the importance of addressing vulnerabilities in cryptographic systems and showcases the potential of machine learning techniques in cryptanalysis. Full article

In the context of crop breeding, plant height (PH) plays a pivotal role in determining straw and grain yield. Although extensive research has explored the genetic control of PH in wheat, there remains an opportunity for further advancements by integrating genomics with growth-related phenomics. Our study utilizes the latest genome-wide association scan (GWAS) techniques to unravel the genetic basis of temporal variation in PH across 179 Bulgarian bread wheat accessions, including landraces, tall historical, and semi-dwarf modern varieties. A GWAS was performed with phenotypic data from three growing seasons, the calculated best linear unbiased estimators, and the leveraging genotypic information from the 25K Infinium iSelect array, using three statistical methods (MLM, FarmCPU, and BLINK). Twenty-five quantitative trait loci (QTL) associated with PH were identified across fourteen chromosomes, encompassing 21 environmentally stable quantitative trait nucleotides (QTNs), and four haplotype blocks. Certain loci (17) on chromosomes 1A, 1B, 1D, 2A, 2D, 3A, 3B, 4A, 5B, 5D, and 6A remain unlinked to any known Rht (Reduced height) genes, QTL, or GWAS loci associated with PH, and represent novel regions of potential breeding significance. Notably, these loci exhibit varying effects on PH, contribute significantly to natural variance, and are expressed during seedling to reproductive stages. The haplotype block on chromosome 6A contains five QTN loci associated with reduced height and two loci promoting height. This configuration suggests a substantial impact on natural variation and holds promise for accurate marker-assisted selection. The potentially novel genomic regions harbor putative candidate gene coding for glutamine synthetase, gibberellin 2-oxidase, auxin response factor, ethylene-responsive transcription factor, and nitric oxide synthase; cell cycle-related genes, encoding cyclin, regulator of chromosome condensation (RCC1) protein, katanin p60 ATPase-containing subunit, and expansins; genes implicated in stem mechanical strength and defense mechanisms, as well as gene regulators such as transcription factors and protein kinases. These findings enrich the pool of semi-dwarfing gene resources, providing the potential to further optimize PH, improve lodging resistance, and achieve higher grain yields in bread wheat. Full article

This study introduces a novel method utilizing hyperspectral imaging for instantaneous ore-waste analysis of drill cuttings. To implement this technique, we collected samples of drill cuttings at regular depth intervals from five blast holes in an open pit gold mine and subjected them to scanning using a hyperspectral imaging system. Subsequently, we employed two distinct methods for processing the hyperspectral images. A knowledge-based method was used to estimate ore grade within each sampled interval, and a data-driven technique was employed to distinguish the ore and waste for each sample interval. Firstly, leveraging the mixed mineralogical composition of the samples, the Linear Spectral Unmixing (LSU) technique was utilized to predict ore grade for each sample. Additionally, the Gradient Boosting Classifier (GBC) was used as an efficient data-driven approach to classify ore-waste samples. Both methods rendered accurate results when they were compared with results obtained through laboratory X-ray diffraction (XRD) analysis and gold assay analysis for the same sample intervals. Adopting the proposed methodology in open pit mine operations can significantly enhance the process of grade control during blast hole drilling. This includes reducing costs, saving time, minimizing uncertainty in ore grade estimation, and establishing more precise ore-waste boundaries in resource block models. Full article

The outcomes of persistent atrial fibrillation (AF) ablation are modest with various adjunctive strategies beyond pulmonary vein isolation (PVI) yielding largely disappointing results in randomised controlled trials. Linear ablation is a commonly employed adjunct strategy but is limited by difficulty in achieving durable bidirectional block, particularly at the mitral isthmus. Epicardial connections play a role in AF initiation and perpetuation. The ligament of Marshall has been implicated as a source of AF triggers and is known to harbour sympathetic and parasympathetic nerve fibres that contribute to AF perpetuation. Ethanol infusion into the Vein of Marshall, a remnant of the superior vena cava and key component of the ligament of Marshall, may eliminate these AF triggers and can facilitate the ease of obtaining durable mitral isthmus block. While early trials have demonstrated the potential of Vein of Marshall ‘ethanolisation’ to reduce arrhythmia recurrence after persistent AF ablation, further randomised trials are needed to fully determine the potential long-term outcome benefits afforded by this technique. Full article

The paper presents a nonlinear field-oriented control technique based on the tensor product representation of the nonlinear induction machine model and the solvability of linear matrix inequalities. The nonlinear model has 32 quasi linear parameter-varying equivalent variants, and it is shown that only half of the models result in feasible controller. Two control goals are realized: torque control and speed control. The controller is a nonlinear state feedback controller completed by integral action. A new block diagram is investigated for speed control. The controller gains are designed by the solution of linear matrix inequalities to solve the Lyapunov inequality to obtain a stable and fast response and constraints on the control signal. The presented methods are verified and compared by simulations. Full article

The continued and envisioned large-scale integration of renewable energy sources as a reaction to rising global temperatures and climate change will need a readily available DC grid to increase commissioning and operating efficiency. The effective operation of these grids is predicated on the correct control of its main control points. A plethora of DC-DC converters that find use in DC microgrids act as the main control points. DC-DC converters are non-linear and can operate in different modes with completely unique characteristics. To utilise classical control techniques, laborious equivalent linear models are derived for DC-DC converters using averaging modelling schemes. The application and limitations of these modelling techniques are well captured in the available literature. The most common limitation of the available modelling schemes is that more focus is dedicated to converter attributes like order, functionality and operating mode, even when optimal power flow and voltage regulation within the DC network are of more interest. Structure-based modelling techniques like the use of basic building blocks nullify converter attributes in the modelling process which translates to modelling efficiency. In light of the merits seen with the use of basic building blocks when modelling converters in CCM, the current study extends these merits to converters operation in DCM. Similar to modelling converters in CCM, modelling techniques that are available in the literature continue to consider converter attributes in the modelling process for DCM operation. Moreover, the two modes of operation are treated as unique entities and often modelled in a non-unified manner, which compromise modelling efficiency since the same converter can operate in a different state solely based on loading. The aim is to increase modelling efficiency but also nullify operating mode in the modelling process. The same basic building blocks are now modelled as two-port networks for DCM operation and adopted based on the exact configuration of a specified converter to compute its steady-state and dynamic models. All the advantages seen when modelling converters in CCM using basic building blocks are retained and augmented when considering DCM operation. Thus, any converter with well-defined basic building blocks can be easily modelled solely based on the connection of constituent basic building blocks. Full article

This paper presents a practical study on how to improve the ${\mathscr{H}}_{\infty }$ performance and meet the input–output constraints of the two-degrees-of-freedom (DOF) flexible-joint manipulator system (FJMS) with parameter uncertainties and external disturbances. For this reason, a robust constrained moving-horizon ${\mathscr{H}}_{\infty }$ controller is designed to improve the system ${\mathscr{H}}_{\infty }$ performance while still satisfying the input–output constraints of the uncertain system. First, the uncertain controlled system model of the two-DOF FJMS is established via the Lagrange equation method, Spong’s assumption, and the linear fractional transformation (LFT) technique. Then, the control requirements and input–output constraints of the uncertain system are transformed into the linear matrix inequality (LMI) via the theory of ${\mathscr{H}}_{\infty }$ control and the full-block multiplier technique. Next, the LMI optimization problem refreshed by the current state is addressed at each sample moment with the idea of the moving-horizon control of the model predictive control (MPC), and the calculated gain is implemented to the nonlinear closed-loop system under the state feedback structure. The validity and feasibility of the designed control scheme is finally verified via the results of simulation experiments. Full article