Output Circuit Research Articles

Predictably manipulating photoreceptor light responses to reveal their role in downstream visual responses.

Computation in neural circuits relies on the judicious use of nonlinear circuit components. In many cases, multiple nonlinear components work collectively to control circuit outputs. Separating the contributions of these different components is difficult, and this limits our understanding of the mechanistic basis of many important computations. Here, we introduce a tool that permits the design of light stimuli that predictably alter rod and cone phototransduction currents - including stimuli that compensate for nonlinear properties such as light adaptation. This tool, based on well-established models for the rod and cone phototransduction cascade, permits the separation of nonlinearities in phototransduction from those in downstream circuits. This will allow, for example, direct tests of how adaptation in rod and cone phototransduction affects downstream visual signals and perception.

Predictably manipulating photoreceptor light responses to reveal their role in downstream visual responses

Computation in neural circuits relies on the judicious use of nonlinear circuit components. In many cases, multiple nonlinear components work collectively to control circuit outputs. Separating the contributions of these different components is difficult, and this limits our understanding of the mechanistic basis of many important computations. Here, we introduce a tool that permits the design of light stimuli that predictably alter rod and cone phototransduction currents – including stimuli that compensate for nonlinear properties such as light adaptation. This tool, based on well-established models for the rod and cone phototransduction cascade, permits the separation of nonlinearities in phototransduction from those in downstream circuits. This will allow, for example, direct tests of how adaptation in rod and cone phototransduction affects downstream visual signals and perception.

Design of a pHEMT RF mixer based on compact microstrip diplexer

Abstract This paper presents a new topology for a microwave active mixer using compact microstrip diplexer constituted from two dual-mode open loop resonators. The resonators are tuned to the radio frequency (RF) and local-oscillator (LO) frequencies, respectively, to effectively isolate the two input signals, while the diplexer output port is connected to the gate circuit of a commercial low cost GaAs pHEMT transistor. The drain circuit of the active device is connected to the load via an intermediate-frequency (IF)-modified Chebyshev low-pass filter to remove the unwanted RF and LO signals and reduce other spurious frequencies at the output of the mixer circuit. The circuit has been designed and constructed for an RF of 850 MHz, LO frequency of 1050 MHz, and an IF of 200 MHz. Experimental measurements show that the circuit provides a conversion gain of 18 dB at LO drive power of +2 dBm. It also operates satisfactorily over the RF range from 800 to 900 MHz with good image frequency rejection and stable operation.

Advanced piezoelectric fluid energy harvesters by monolithic fluid–structure–piezoelectric coupling: A full-scale finite element model

A full-scale finite element model is presented for monolithic fluid–structure interaction (FSI) simulations of thin-walled piezoelectric fluid energy harvesters (PFEHs). Unlike widely used beam/plate-based models, our model employs a solid finite element discretization to precisely represent the complex PFEH designs involving microstructured transducers and non-uniform cantilevers. These features, plus the local FSI effects, are often ignored by simplified models. We applied the Galerkin method to formulate the weak form of the mixed equation system, integrating the flow dynamics, the geometrically nonlinear cantilever, the piezoelectric components, the electrode, and the output circuit within a closed-circuit electro-mechanical coupled system. The coupling of the multiple domains is achieved through boundary-fitted discretization within a monolithic scheme, using shifted-Crank–Nicolson temporal integration. This work explored implementing piezoelectric FSI systems within the FEniCS-based TurtleFSI library, and experimented techniques such as employing penalty functions for achieving electrode components with uniform electric potentials. We investigated various advanced PFEH features, including the baseplate design, the arrangement and microstructure of the piezoelectric components, and their influence on the system's dynamic and energy output behavior. The results confirmed the model's key advantages: full-scale modeling allows the integration of complex base structures and transducer microstructures in PFEH design. Combined with monolithic FSI coupling, it offers greater versatility, supporting a wider range of fluid environments and configurations in both wind and hydropower harvesting. Additionally, the modeling strategy can be intended not only to enhance power output, but also to minimize material usage, reduce mechanical fatigue, and extend the operational lifespan of PFEH systems.

Chemical Reaction Simulator on Quantum Computers by First Quantization (II)─Basic Treatment: Implementation.

Chemical simulation is a key application area that can leverage the power of quantum computers. A chemical simulator that implements a grid-based first quantization method has promising characteristics, but an implementation fully in quantum circuits seems to have not been published. Here, we present "crsQ" (chemical reaction simulator Q), which is a quantum circuit generator that generates such a chemical simulator. The generated simulator is capable of antisymmetrization of the initial wave function and time-evolution of the wave function based on the Suzuki-Trotter decomposition. The potential energy term of the Hamiltonian is implemented using arithmetic gates, such as adders, subtractors, multipliers, dividers, and square roots. Circuit diagrams and output samples are shown. The number of qubits in the circuits scales on the order of O(η log η), where η is the number of electrons. Each component of the generated circuit was verified in unit tests. Along with this development, we designed frameworks to ease the development of large-scale circuits, namely, a temporary qubit allocation framework and an abstract syntax tree framework for arithmetic formulas. These frameworks are expected to be useful in large-scale quantum circuit generators.

The Brain's Best Kept Secret Is Its Degenerate Structure.

Degeneracy is defined as multiple sets of solutions that can produce very similar system performance. Degeneracy is seen across phylogenetic scales, in all kinds of organisms. In neuroscience, degeneracy can be seen in the constellation of biophysical properties that produce a neuron's characteristic intrinsic properties and/or the constellation of mechanisms that determine circuit outputs or behavior. Here, we present examples of degeneracy at multiple levels of organization, from single-cell behavior, small circuits, large circuits, and, in cognition, drawing conclusions from work ranging from bacteria to human cognition. Degeneracy allows the individual-to-individual variability within a population that creates potential for evolution.

Potentiation of active locomotor state by spinal-projecting serotonergic neurons.

Animals produce diverse motor actions that enable expression of context-appropriate behaviors. Neuromodulators facilitate behavioral flexibility by altering the temporal dynamics and output of neural circuits. Discrete populations of serotonergic (5-HT) neurons target circuits in the brainstem and spinal cord, but their role in the control of motor behavior is unclear. Here we define the pre- and post-synaptic organization of the spinal-projecting serotonergic system and define a role in locomotor control. We show that while forebrain-targeting 5-HT neurons decrease their activity during locomotion, subpopulations of spinal projecting neurons increase their activity in a context-dependent manner. Optogenetic activation of ventrally projecting 5-HT neurons does not trigger initiation of movement, but rather enhances the speed and duration of ongoing locomotion over extended time scales. These findings indicate that the descending serotonergic system potentiates locomotor output and demonstrate a role for serotonergic neurons in modulating the temporal dynamics of motor circuits.

Research on the influence of different organizational structures on the electrical life of sealed relays

Abstract A sealed relay is a type of power relay mainly used in fields with harsh environments, low noise requirements, or high-reliability requirements. It is used in scenarios such as vehicle loads, household appliances, industrial control, and motors. At the same time, when the input meets certain specified conditions, it is a device that can generate a jump in one or more electrical output circuits, playing a role in controlling the on/off current of the connected circuit. Power relays have been widely used in various fields due to their small size, low noise, and low power consumption advantages. This article mainly studies the electrical parameters such as arc energy, arc time, welding force, and contact burning principle of silver tin oxide electrical contact materials produced by different processes, providing a reference for the development of electrical contact materials.

Differential impact of optogenetic stimulation of direct and indirect pathways from dorsolateral and dorsomedial striatum on motor symptoms in Huntington's disease mice

The alterations in the basal ganglia circuitry are core pathological hallmark in Huntington's Disease (HD) and traditionally linked to its sever motor symptoms. Recently it was shown that optogenetic stimulation of cortical afferences to the striatum is able to reverse motor symptoms in HD mice. However, the specific contribution of the direct and indirect striatal output pathways from the dorsolateral (DLS) and dorsomedial striatum (DMS) to the motor phenotype is still not clear. Here, we aim to uncover the contributions of these striatal subcircuits to motor control in wild type (WT) and HD mice by using the symptomatic R6/1 mice. We systematically evaluated locomotion, exploratory behavior, and motor learning effects of the selective optogenetic stimulation of D1 or A2A expressing neurons (direct and indirect pathway, respectively), in DLS or DMS. Bilateral optogenetic stimulation of the direct pathway from DLS and the indirect pathway from DMS resulted in subtle locomotor enhancements, while unaltering exploratory behavior. Additionally, bilateral stimulation of the indirect pathway from the DLS improved performance in the accelerated rotarod task, suggesting a role in motor learning. In contrast, in HD mice, stimulation of these pathways did not modulate any of these behaviors. Overall, this study highlights that selective stimulation of direct and indirect pathways from DLS and DMS have subtle impact in locomotion, exploratory activity nor motor learning. The lack of responses in HD mice also suggests that strategies involving cortico-striatal circuits rather than striatal output circuits might be a better strategy for managing motor symptoms in movement disorders.

Control of spin–orbit torque-driven domain nucleation through geometry in chirally coupled magnetic tracks

The interfacial Dzyaloshinskii–Moriya interaction (DMI) can be exploited in magnetic thin films to realize lateral chirally coupled systems, providing a way to couple different sections of a magnetic racetrack and realize interconnected networks of magnetic logic gates. Here, we systematically investigate the interplay between spin–orbit torques, chiral coupling, and the device design in domain wall racetracks. We show that the current-induced domain nucleation process can be tuned between single-domain nucleation and repeated nucleation of alternate domains by changing the orientation of an in-plane patterned magnetic region within an out-of-plane magnetic racetrack. Furthermore, by combining experiments and micromagnetic simulations, we show that the combination of damping-like and field-like spin–orbit torques with DMI results in selective domain wall injection in one of two arms of a Y-shaped device depending on the current density. Such an element constitutes the basis of domain wall based demultiplexer, which is essential for distributing a single input to any one of the multiple outputs in logic circuits. Our results provide input for the design of reliable and multifunctional domain wall circuits based on chirally coupled interfaces.

МОДУЛЬНЫЕ КОДЫ С СУММИРОВАНИЕМ С ПОСЛЕДОВАТЕЛЬНОСТЬЮ ВЕСОВЫХ КОЭФФИЦИЕНТОВ, ОБРАЗУЮЩЕЙ НАТУРАЛЬНЫЙ РЯД ЧИСЕЛ ЗА ИСКЛЮЧЕНИЕМ СТЕПЕНЕЙ ДВОЙКИ

The paper presents the results of studies on the characteristics of modular weight-based sum codes, where the sequence is formed by a natural series of numbers excluding powers of two. The consideration of the studied characteristics is advisable when developing discrete systems and their diagnostic support. Catalogs of the considered codes obtained using modules M = 4, 8, 16, 32, and 64 are provided. The choice of these specific modules is due to the fact that the number of check symbols in the codewords of the considered codes is small, which minimizes structural redundancy when constructing discrete systems and their diagnostic support, resulting in self-checking, controllable, and fault-tolerant structures. Modular weight-based sum codes detect all single errors with the number of data symbols . It is also demonstrated that the considered codes detect no fewer errors than the well-known modular sum codes of single digits (classical modular sum codes). As the module value increases, the gain in the tota number of errors detected by the modular weighted codes compared to classical modular codes significantly increases. Modular weighted codes are more effective at detecting multidirectional errors of even multiplicity in data vectors containing groups of distortions {0→1, 1→0} (symmetric errors) than classical modular sum codes. However, modular weight-based sum codes are less effective in handling asymmetric errors occurring in data vectors. In an experiment with test combinational circuits, it was shown that modular weighted codes with a module M = 4 do not detect more errors occurring at circuit outputs than classical modular codes with this module. Modular weight-based sum codes and a module M = 8 have slightly better characteristics. However, a general recommendation is to use modules that are powers of two starting from M = 16. Increasing the module allows for an increase in the number of detectable errors at the outputs of benchmarks, up to 100 % coverage. Modular weight-based sum codes, with a sequence of weight coefficients forming a natural series of numbers excluding powers of two, can be effectively used in the development of discrete systems and their diagnostic support.

A modeling method for thermal steady-state simulation of the four-layer printed circuit board.

Thermal simulation of a Printed Circuit Board (PCB) can help identify potential overheating risks in the circuit. The proposed modeling method combines analytical temperature solutions and numerical approximations. Only Fourier-series analytical solutions related to the prepreg-layer surfaces need to be calculated, rather than the entire structure. Heat transfer through the lateral sides of a PCB is approximately considered as part of the compensated heat flux of the insulating-layer surface boundaries. Heat diffusion within or between metal layers is numerically approximated using the finite volume method. The core layer is treated as "thermally-thick". Temperature-dependent boundary conditions are considered through iterations. A test solver was developed based on the method. The modeling accuracy was validated by comparison with COMSOL Multiphysics for a four-layer structure with a moderate degree of discretization. Additionally, a PCB for generating DC 3.3V was designed, tested, and modeled, with the modeling results confirmed by the thermal images. The electro-thermal analysis of the distribution of electric potential and Joule heating in traces and vias was integrated into the PCB model. The layout maps of the PCB were further adjusted to reduce Joule heating in the output circuit, and the improvement on reducing the IR drop and hotspot temperature was examined.

Segregated basal ganglia output pathways correspond to genetically divergent neuronal subclasses.

The basal ganglia control multiple sensorimotor behaviors though anatomically segregated and topographically organized subcircuits with outputs to specific downstream circuits. However, it is unclear how the anatomical organization of basal ganglia output circuits relates to the molecular diversity of cell types. Here, we demonstrate that the major output nucleus of the basal ganglia, the substantia nigra pars reticulata (SNr) is comprised of transcriptomically distinct subclasses that reflect its distinct progenitor lineages. We show that these subclasses are topographically organized within SNr, project to distinct targets in the midbrain and hindbrain, and receive inputs from different striatal subregions. Finally, we show that these mouse subclasses are also identifiable in human SNr neurons, suggesting that the genetic organization of SNr is evolutionarily conserved. These findings provide a unifying logic for how the developmental specification of diverse SNr neurons relates to the anatomical organization of basal ganglia circuits controlling specialized downstream brain regions.

Multimodal Hox5 activity generates motor neuron diversity

Motor neurons (MNs) are the final output of circuits driving fundamental behaviors, such as respiration and locomotion. Hox proteins are essential in generating the MN diversity required for accomplishing these functions, but the transcriptional mechanisms that enable Hox paralogs to assign distinct MN subtype identities despite their promiscuous DNA binding motif are not well understood. Here we show that Hoxa5 modifies chromatin accessibility in all mouse spinal cervical MN subtypes and engages TALE co-factors to directly bind and regulate subtype-specific genes. We identify a paralog-specific interaction of Hoxa5 with the phrenic MN-specific transcription factor Scip and show that heterologous expression of Hoxa5 and Scip is sufficient to suppress limb-innervating MN identity. We also demonstrate that phrenic MN identity is stable after Hoxa5 downregulation and identify Klf proteins as potential regulators of phrenic MN maintenance. Our data identify multiple modes of Hoxa5 action that converge to induce and maintain MN identity.

A high gain quasi Z‐source based full‐bridge isolated DC‐DC converter with extendable structure for grid‐tied/standalone PV system

AbstractA multi‐input single‐output converter that is based on the impedance network and the standard isolated converters is presented. The topology is named quasi Z‐source full‐bridge isolated converter (qZSFBIC). The proposed topology helps to integrate various renewable power generation systems with a common three‐phase grid‐connected inverter. It was also capable of providing isolation between the input and output circuits in addition to the boost function. The integration of multiple energy sources is achieved using fewer components than conventional converters. As a result, it achieves greater conversion efficiency and has improved circuit characteristics. It offers a larger voltage control range as compared to the conventional ZSC and enhances the input‐output voltage transformation ratio. To determine whether or not the suggested converter is technically feasible, the circuit architecture, operating principle, control mechanism, and simulation results are presented. An improved proportional resonant‐second order general integrator (IPR‐SOGI) has been utilized to provide a gating signal for the voltage source inverter. The 1.5 kW, 400 V, 50 Hz model is designed to authenticate the proposed scheme with qZSFBIC. The results showed that the proposed converter offered double the time of boosting than the conventional ZSC converter and the conversion efficiency is around 89%.

A Novel Strategy for Multitype Fault Diagnosis in Photovoltaic Systems Using Multiple Regression Analysis and Support Vector Machines

This study focuses on analyzing common fault types in photovoltaic (PV) modules, employing fault diagnosis methods based on machine learning technology to enhance the accuracy and efficiency of diagnosing faults in solar power systems. Initially, we collected relevant data from the solar power system and used data analysis techniques to identify system faults, designing a human-machine monitoring interface for practical application. Furthermore, the experimental results proved that the system could accurately identify eight major types of faults, including solar panel output circuits, energy storage batteries, maximum power point tracking (MPPT) controllers, inverters, dust accumulation, loosening of mounting rack screws, damage to the mounting rack foundation, and deformation of the mounting rack structure. Particularly in the detection of dust accumulation, we developed a new method of estimating power generation from multiple regression analysis (MRA), which closely aligns the estimated power output with the actual power output, highlighting the significant impact of dust accumulation on the efficiency of solar power systems. Next, by integrating voltmeters and support vector machines (SVM) into the solar PV array modules, we are able to quickly and accurately measure and locate short-circuit and open-circuit faults in bypass diodes. Ultimately, the proposed PV fault diagnosis strategy includes diagnostics for dust accumulation and mounting frame faults, making it particularly suitable for areas with severe air pollution and frequent earthquakes, providing a comprehensive fault diagnosis solution.

Research on key circuits of high‐precision servo channel loading card for wing fatigue testing

AbstractThe key circuits of servo channel loading card with high‐precision data acquisition and output functions for wing fatigue testing are studied and improved in this paper. To solve the problem of large offset voltage in some op‐amps, non‐inverting combined amplifier circuit (NCAC) and inverting combination amplifier circuit (ICAC) are proposed by utilizing precision op‐amps combined with wide voltage and high‐power output op‐amps. In the force signal acquisition section, a non‐inverting combined zeroing filter circuit (NCZFC) is proposed to improve the precision of signal acquisition. In the excitation source output section, a non‐inverting combined excitation output circuit (NCEOC) is proposed to improve the precision of the positive excitation output; an inverting combined excitation output circuit (ICEOC) is also proposed, which improves the precision of the negative excitation output and also realizes the inversion of the input and output signals. In the servo drive output section, a non‐inverting combined voltage and current conversion circuit is proposed to improve the precision of voltage and current outputs, which has two modes of non‐inverting combined voltage output (NCVO) and non‐inverting combined current output (NCIO) modes. Simulation experiments in Multisim and actual tests have been carried out on the above improved circuits to verify the stability and precision.

Predictably manipulating photoreceptor light responses to reveal their role in downstream visual responses.

Computation in neural circuits relies on the judicious use of nonlinear circuit components. In many cases, multiple nonlinear components work collectively to control circuit outputs. Separating the contributions of these different components is difficult, and this limits our understanding of the mechanistic basis of many important computations. Here, we introduce a tool that permits the design of light stimuli that predictably alter rod and cone phototransduction currents - including stimuli that compensate for nonlinear properties such as light adaptation. This tool, based on well-established models for the rod and cone phototransduction cascade, permits the separation of nonlinearities in phototransduction from those in downstream circuits. This will allow, for example, direct tests of how adaptation in rod and cone phototransduction affects downstream visual signals and perception.

Capacitive voltage effect at a resistive sintering system container and its electrical model

Abstract The electric current activated/assisted sintering (ECAS) method enables various kinds of materials to be produced much faster and environmentally friendly compared to conventional sample production systems. The main handicap of this system is that the heating regime varies according to the material type even the chemical composition of the same type of material and causes partial melting due to the sudden current flow. Previously, the ECAS output equivalent circuit is modeled as a temperature-dependent resistor in the literature. This study shows that it is insufficient to model the ECAS output consisting of a container and two stiffs as a resistor considering experimental waveforms. We report the discovery of a capacitive effect at the output of the ECAS system that has not been reported before. We have given an equivalent electrical circuit for the ECAS system output and examined the effect’s temperature dependence. The circuit model, which consists of a parallel resistor-capacitor (R p-C) circuit in series with another resistor (R s), is suggested for the container and the stiffs. By using the experimental data, the equivalent circuit parameters are calculated by curve-fitting. The temperature dependence of the equivalent circuit parameters is also examined. Possible explanations for the capacitive effect are given. Such a model and further examining the effect may help design better ECAS systems.

Circuit firing homeostasis following synaptic perturbation ensures robust behavior.

Homeostatic regulation of excitability and synaptic transmission ensures stable neural circuit output under changing conditions. We find that pre- or postsynaptic weakening of motor neuron (MN) to muscle glutamatergic transmission in Drosophila larva has little impact on locomotion, suggesting non-synaptic compensatory mechanisms. In vivo imaging of MN to muscle synaptic transmission and MN activity both show that synaptic weakening increases activity in tonic type Ib MNs, but not in the phasic type Is MN that innervate the same muscles. Additionally, an inhibitory class of pre-MNs that innervates type Ib-but not Is-MNs decreases activity. Our experiments suggest that weakening of MN evoked synaptic release onto the muscle is compensated for by an increase in MN firing due to a combined cell-autonomous increase in excitability and decreased inhibitory central drive. Selectivity for type Ib MNs may serve to restore tonic drive while absence of firing adjustment in the convergent Is MN can maintain the contraction wave dynamics needed for locomotion.