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Programmable metasurfaces allow dynamic and real‐time control of electromagnetic (EM) waves in subwavelength resolution, holding extraordinary potentials to establish meta‐systems. Achieving independent and real‐time controls of orthogonally‐polarized EM waves via the programmable metasurface is attractive for many applications, but remains considerably challenging. Here, a polarization‐controlled dual‐programmable metasurface (PDPM) with modular control circuits is proposed, which enables a dibit encoding capability in modifying the phase profiles of x‐ and y‐polarized waves individually. The constructed extended interface circuit is able to extend the number of control interfaces from a field programmable gate array by orders of magnitude and also possesses memory function, which enhance hugely the rewritability, scalability, reliability, and stability of PDPM. As a proof‐of‐concept, a wave‐based exclusive‐OR logic gate platform for spin control of circularly‐polarized waves, a fixed‐frequency wide‐angle dual‐beam scanning system, and a dual‐polarized shared‐aperture antenna are demonstrated using a single PDPM. The proposed PDPM opens up avenues for realizing more advanced and integrated multifunctional devices and systems that have two independent polarization‐controlled signal channels, which may find many applications in future‐oriented intelligent communication, imaging, and computing technologies. A polarization‐controlled dual‐programmable metasurface that can independently control orthogonally‐polarized microwaves in real time is proposed and realized experimentally. The dual‐programmable metasurface can achieve a lot of independent control channels via only one field‐programmable gate array based on the designed extensional interface circuit, thus providing attractive functions, including wave‐based exclusive‐OR logic operation for spin control, wide‐angle dual‐beam scanning, and dual‐polarized aperture sharing.

Modular and orthogonal genetic logic gates are essential for building robust biologically based digital devices to customize cell signalling in synthetic biology. Here we constructed an orthogonal AND gate in Escherichia coli using a novel hetero-regulation module from Pseudomonas syringae . The device comprises two co-activating genes hrpR and hrpS controlled by separate promoter inputs, and a σ 54 -dependent hrpL promoter driving the output. The hrpL promoter is activated only when both genes are expressed, generating digital-like AND integration behaviour. The AND gate is demonstrated to be modular by applying new regulated promoters to the inputs, and connecting the output to a NOT gate module to produce a combinatorial NAND gate. The circuits were assembled using a parts-based engineering approach of quantitative characterization, modelling, followed by construction and testing. The results show that new genetic logic devices can be engineered predictably from novel native orthogonal biological control elements using quantitatively in-context characterized parts. Biological digital sensors require the fabrication of modular genetic logic gates. Using the Pseudomonas syringae hrp system, Wang and colleagues generate AND, NOT and NAND gates, demonstrating the ability to engineer a modular system from biological elements.

Dynamical modeling of nervous systems is of fundamental importance in many scientific fields containing the topics relative to computational neuroscience and biophysics. Many feasible mathematical models have been suggested in the explanation and prediction of some features of neural activities. Considering the special experimental findings and the computational efficiency, it is necessary to find a perfect balance between estimating biophysical functions with complete dynamics and reducing complexity when a tractable model is built. In this paper, a chemical synaptic model is reproduced by using a memristive synapse because it not only remains synaptic characteristic but also exhibits a pinched hysteresis loop and active feature locally. That is, a neuron activated by chemical synapse can produce similar firing modes as the neuron coupled by a memristive synapse, and both the chemical synapse and memristive synapse have similar field effect and biophysical properties. By calculating the one-parameter and two-parameter bifurcation as well as the Lyapunov exponent spectrum, it is confirmed that a neuron can be excited by the chemical synapse or the memristive synapse for generating chaotic firing patterns. Oscillation of the circuit composed of neuron and functional synapse is analyzed, suggesting that there exists a relation between the local activity and the edge of chaos via Hopf bifurcation. A modular circuit is designed to construct large-scale neural network. These results in this paper provide new evidences for application of memristive components and guide us to know the biophysical function of chemical synapse from physical viewpoint, in which the chemical synapse could be a kind of memristive synapse because of the same biophysical function.

This paper introduces the development history, working principle, curative effect under different output waveforms and the hardware and software design of the system. The proportional constant current output circuit is analyzed in detail. A system structure of electroacupuncture instrument based on modular design is proposed. The system structure mainly includes multi-channel electroacupuncture control module and display control module, which are connected through CAN bus. Multi-channel electroneedle control module adopts embedded processor and real-time operating system design, display control module is application level processor, running embedded Linux system design. The system has reasonable structure design and high expansibility, which is convenient for further research.

The behavior of genetic circuits is often poorly predictable. A gene’s expression level is not only determined by the intended regulators, but also affected by changes in ribosome availability imparted by expression of other genes. Here we design a quasi-integral biomolecular feedback controller that enables the expression level of any gene of interest (GOI) to adapt to changes in available ribosomes. The feedback is implemented through a synthetic small RNA (sRNA) that silences the GOI’s mRNA, and uses orthogonal extracytoplasmic function (ECF) sigma factor to sense the GOI’s translation and to actuate sRNA transcription. Without the controller, the expression level of the GOI is reduced by 50% when a resource competitor is activated. With the controller, by contrast, gene expression level is practically unaffected by the competitor. This feedback controller allows adaptation of genetic modules to variable ribosome demand and thus aids modular construction of complicated circuits. Competition for shared cellular resources often renders genetic circuits poorly predictable. Here the authors design a biomolecular quasi-integral controller that allows gene expression to adapt to variable demand in translation resources.

This paper introduces new integrated analog cells fabricated in a C035 I3T25 0.35-μm ON Semiconductor process suitable for a modular design of advanced active elements with multiple terminals and controllable features. We developed and realized five analog cells on a single integrated circuit (IC), namely a voltage differencing differential buffer, a voltage multiplier with current output in full complementary metal–oxide–semiconductor (CMOS) form, a voltage multiplier with current output with a bipolar core, a current-controlled current conveyor of the second generation with four current outputs, and a single-input and single-output adjustable current amplifier. These cells (sub-blocks of the manufactured IC device), designed to operate in a bandwidth of up to tens of MHz, can be used as a construction set for building a variety of advanced active elements, offering up to four independently adjustable internal parameters. The performances of all individual cells were verified by extensive laboratory measurements, and the obtained results were compared to simulations in the Cadence IC6 tool. The definition and assembly of a newly specified advanced active element, namely a current-controlled voltage differencing current conveyor transconductance amplifier (CC-VDCCTA), is shown as an example of modular interconnection of the selected cells. This device was implemented in a newly synthesized topology of an electronically linearly tunable quadrature oscillator. Features of this active element were verified by simulations and experimental measurements.

One of the primary ways we interact with the world is using our hands. In macaques, the circuit spanning the anterior intraparietal area, the hand area of the ventral premotor cortex, and the primary motor cortex is necessary for transforming visual information into grasping movements. However, no comprehensive model exists that links all steps of processing from vision to action. We hypothesized that a recurrent neural network mimicking the modular structure of the anatomical circuit and trained to use visual features of objects to generate the required muscle dynamics used by primates to grasp objects would give insight into the computations of the grasping circuit. Internal activity of modular networks trained with these constraints strongly resembled neural activity recorded from the grasping circuit during grasping and paralleled the similarities between brain regions. Network activity during the different phases of the task could be explained by linear dynamics for maintaining a distributed movement plan across the network in the absence of visual stimulus and then generating the required muscle kinematics based on these initial conditions in a module-specific way. These modular models also outperformed alternative models at explaining neural data, despite the absence of neural data during training, suggesting that the inputs, outputs, and architectural constraints imposed were sufficient for recapitulating processing in the grasping circuit. Finally, targeted lesioning of modules produced deficits similar to those observed in lesion studies of the grasping circuit, providing a potential model for how brain regions may coordinate during the visually guided grasping of objects.

Humans and animals can effortlessly coordinate their movements with external stimuli. This capacity indicates that sensory inputs can rapidly and flexibly reconfigure the ongoing dynamics in the neural circuits that control movements. Here, we develop a circuit-level model that coordinates movement times with expected and unexpected temporal events. The model consists of two interacting modules, a motor planning module that controls movement times and a sensory anticipation module that anticipates external events. Both modules harbor a reservoir of latent dynamics, and their interaction forms a control system whose output is adjusted adaptively to minimize timing errors. We show that the model’s output matches human behavior in a range of tasks including time interval production, periodic production, synchronization/continuation, and Bayesian time interval reproduction. These results demonstrate how recurrent interactions in a simple and modular neural circuit could create the dynamics needed to control timing behavior. We can flexibly coordinate our movements with external stimuli, but no circuit-level model exists to explain this ability. Inspired by fundamental concepts in control theory, the authors construct a modular neural circuit that captures human behavior in a wide range of temporal coordination tasks.

In response to the requirements of a satellite micro-vibration testing method, a multi-channel synchronous data acquisition system was designed based on FPGA. The system adopts a modular design philosophy, allowing flexible configuration of the number of acquisition channels by modifying program parameters and reconstructing hardware resources. Signal sampling is performed using high-precision Σ-Δ type ADCs with synchronization capabilities. The synchronization signals for each ADC and the clock signal for filters are uniformly generated by the FPGA, achieving mutual synchronization of multiple sampling channels. LVDS is chosen as the data interface to meet the bandwidth requirements. The host computer communicates with the hardware through the RS232 interface, sending control commands and retrieving LVDS-transmitted data through USB via an interface conversion circuit. The acquired data is displayed in real-time on the user interface in a graphical format. Test results indicate that the system successfully achieves the synchronous acquisition of analog voltage signals across multiple channels, making it suitable for the development of space payload equipment and ground testing devices.

Small, genetically tractable species such as larval zebrafish, Drosophila, or Caenorhabditis elegans have become key model organisms in modern neuroscience. In addition to their low maintenance costs and easy sharing of strains across labs, one key appeal is the possibility to monitor single or groups of animals in a behavioural arena while controlling the activity of select neurons using optogenetic or thermogenetic tools. However, the purchase of a commercial solution for these types of experiments, including an appropriate camera system as well as a controlled behavioural arena, can be costly. Here, we present a low-cost and modular open-source alternative called 'FlyPi'. Our design is based on a 3D-printed mainframe, a Raspberry Pi computer, and high-definition camera system as well as Arduino-based optical and thermal control circuits. Depending on the configuration, FlyPi can be assembled for well under €100 and features optional modules for light-emitting diode (LED)-based fluorescence microscopy and optogenetic stimulation as well as a Peltier-based temperature stimulator for thermogenetics. The complete version with all modules costs approximately €200 or substantially less if the user is prepared to 'shop around'. All functions of FlyPi can be controlled through a custom-written graphical user interface. To demonstrate FlyPi's capabilities, we present its use in a series of state-of-the-art neurogenetics experiments. In addition, we demonstrate FlyPi's utility as a medical diagnostic tool as well as a teaching aid at Neurogenetics courses held at several African universities. Taken together, the low cost and modular nature as well as fully open design of FlyPi make it a highly versatile tool in a range of applications, including the classroom, diagnostic centres, and research labs.