Rapid Switching Research Articles

Orthogonal limited-angle CT reconstruction method based on anisotropic self-guided image filtering

Computed tomography (CT) reconstruction from incomplete projection data is significant for reducing radiation dose or scanning time. In this work, we investigate a special sampling strategy, which performs two limited-angle scans. We call it orthogonal limited-angle sampling. The X-ray source trajectory covers two limited-angle ranges, and the angle bisectors of the two angular ranges are orthogonal. This sampling method avoids rapid switching of tube voltage in few-view sampling, and reduces data correlation of projections in limited-angle sampling. It has the potential to become a practical imaging strategy. Then we propose a new reconstruction model based on anisotropic self-guided image filtering (ASGIF) and present an algorithm to solve this model. We construct adaptive weights to guide image reconstruction using the gradient information of reconstructed image itself. Additionally, since the shading artifacts are related to the scanning angular ranges and distributed in two orthogonal directions, anisotropic image filtering is used to preserve image edges. Experiments on a digital phantom and real CT data demonstrate that ASGIF method can effectively suppress shading artifacts and preserve image edges, outperforming other competing methods.

Quasi-Simultaneous Identification of Polar and Neutral Lipids in Mass Spectrometry by kHz Switching of Electrospray and Plasma Ionization.

The identification of polar and neutral lipid species as biomarkers in complex biological samples is a key task in clinical and life sciences. Electrospray and plasma-based ionization techniques are necessary to cover the full range of lipidomes, owing to their limited molecular polarity ranges. However, combining both to generate hybrid spectra is difficult without averaging spectra, as electrospray and plasma sources operate under vastly different conditions. Their electric fields also interfere, resulting in a mutual destabilization of the ionization processes. Herein, a heated nanoelectrospray is combined with a flexible microtube plasma using a rapid (kHz range) switching process (heated nESI-sFμTP) to generate quasi-simultaneous ionization. This approach loads the ion trap with polar and less-polar ions during each injection cycle, generating hybrid spectra without averaging it. The performance of the quasi-simultaneous approach is investigated in positive ion mode, comparing it with conventional ion sources through the analysis of complex lipid liver and heart samples. While no improvements are observed in negative ion mode, the novel quasi-simultaneous approach shows great potential for analyzing complex samples in positive ion mode. The combined heated nESI-sFμTP exceeds the molecular polarity range of individual sources, offering excellent ionization efficiency and MS2 capabilities.

Minute-Level Room-Temperature Switching and Long Cycle Stability of Thermochromic Inorganic Perovskite Smart Windows.

Perovskite smart windows (PSWs) are widely investigated owing to excellent thermochromic properties, while restricted by poor transition performance and cycle stability. Herein, dimethyl sulfoxide vapor is utilized as an induction reagent for rapid reversible switching at room temperature between the colored and bleached phases. To obtain PSWs with different optical properties and transition performance, red CsPbIBr2, yellow Rb0.5Cs0.5PbIBr2 and brown CsSn0.1Pb0.9IBr2 are prepared through alloying. The perovskites can exhibit reversible switching at 27.4-34.3°C within 1.9-5.1min. Even after 100 cycles, they exhibit remarkable stability of luminous transmittance (retention ≥97.4%) and transition time (retention ≥97.6%). Experimental characterization proves that the reversible switching occurs between colored three-dimension perovskite phase and bleached zero-dimension perovskite phase. In the field test (air temperature=21.6-26.5°C), model houses with PSWs exhibit a maximum indoor temperature drop of 4.2°C. Furthermore, they exhibit considerable temperature modulation ability up to 7.9°C under a solar simulator (temperature of the control model house=60°C). The decrease in the luminous transmittance of the PSWs after 20 days is 2.9%, indicating excellent long-term stability. This study offers PSWs with prominent transition performance and long cycle stability.

Schwinger particle production: Rapid switch off of the external field versus dynamical assistance

Schwinger particle production: Rapid switch off of the external field versus dynamical assistance

Redox Dependent Color Modulating Copper(I) Complex for Flexible Electrochromic Device

AbstractPursuing the development of eco‐friendly, cost‐effective and flexible materials that offer high‐color contrast and low power consumption is a promising approach for advancing the next‐generation optoelectronic devices. Herein, we report the synthesis of a heteroleptic copper(I) complex [Xantphos‐Cu‐cmdf]PF6 (C1), in high yield, using Xantphos and cmdf ligands. The complex has high thermal stability and displays low‐energy absorption between 360 and 470 nm due to the metal‐to‐ligand charge transfer (MLCT) transition. The electrochemical analysis confirmed the electrochromic properties of C1. A bilayer electrochromic device (ECD) incorporating P3HT and C1 demonstrated excellent color modulation (45 %) and rapid switching times (less than one second). Furthermore, the flexible ECD utilizing C1 showed superior performance compared to its solid‐state counterpart, with high efficiency (~200 cm2/C), color modulation (69 %) and sub‐second switching times. The high coloration efficiency and fast switching time of the ECDs developed from stable and cost‐effective Cu(I) complex, C1, make it a promising candidate for real‐world electrochromic applications.

Wave transformation in transmission lines with rapid connection and disconnection of reactive elements

Rapid switching of transmission line parameters has emerged as a way to manipulate signals and as a testbed for various electromagnetic processes in time-varying media, including metamaterials. In general, the switching results in wave reflection and transmission similar to that for a spatial interface but at new frequencies. Here, various realizations of parameter switching are studied: connection and disconnection of reactive elements (capacitors and inductors) in series and in parallel. The temporal boundary conditions for the current and voltage distributions are derived rigorously based on the telegrapher’s equations that explicitly model additional elements, instead of taking the equivalent values. It is shown that the temporal boundary conditions depend not only on the parameter values before and after switching but on its specific realization. Connecting or disconnecting reactive elements always involves energy losses. When new elements are added, two types of losses are identified. The first type is related to the creation of static magnetic and electric fields in the elements after switching. The second type is related to a very rapid energy dissipation during switching even for a vanishingly small resistivity in the line. When elements are removed, their energy is also removed from the waves. The effects of finite switching times are discussed. This study defines some serious constraints in using switchable transmission lines for the realization of photonic time crystals and efficient wave manipulation without externally added energy. The results are also applicable to wave propagation phenomena in other media with time-varying parameters.

A shared alarmone-GTP switch underlies triggered and spontaneous persistence.

Persisters describe phenotypically switched cells refractory to antibiotic killing in a genetically susceptible population, while preserving the ability to resume growth when antibiotics are discontinued1,2. Since its proposal 70 years ago, great strides were made to build the framework regarding persistence, including defining triggered, spontaneous and antibiotic-induced persisters. However, challenges remain in characterizing the molecular determinants underlying the phenotypic switch into persistence3. Here we document triggered, spontaneous and antibiotic-induced persistence in a Gram-positive bacterium, all through a common switch involving the alarmone (p)ppGpp and each stemming from a different alarmone synthesis pathway. Starvation-triggered persistence is mediated by Rel synthetase, and spontaneous persistence is through self-amplification via allosteric enzyme activation of alarmone synthetases Rel and SasB, whereas lethal and sublethal concentrations of cell wall antibiotics induce alarmones through an antibiotic-induced alarmone synthetase SasA, consequently enabling adaptive persistence that promotes survival. (p)ppGpp accumulation promotes persistence by depleting intracellular GTP and antagonizing its action. We developed a fluorescent GTP reporter to visualize rare events of persister formation in wild type bacteria, revealing a rapid switch from growth to dormancy in single cells as their GTP levels drop beneath a threshold. While a modest drop of GTP in bulk population slows down growth and promotes antibiotic tolerance, (p)ppGpp drives persistence by allowing the switch-like dynamics to drop GTP beneath the persister threshold in single cells. Persistence through alarmone-GTP antagonism is likely a widespread mechanism to survive antibiotics in Gram positive bacteria and possibly beyond.

A sticky Poisson Hidden Markov Model for solving the problem of over-segmentation and rapid state switching in cortical datasets.

The application of hidden Markov models (HMMs) to neural data has uncovered hidden states and signatures of neural dynamics that are relevant for sensory and cognitive processes. However, training an HMM on cortical data requires a careful handling of model selection, since models with more numerous hidden states generally have a higher likelihood on new (unseen) data. A potentially related problem is the occurrence of very rapid state switching after decoding the data with an HMM. The first problem can lead to overfitting and over-segmentation of the data. The second problem is due to intermediate-to-low self-transition probabilities and is at odds with many reports that hidden states in cortex tend to last from hundred of milliseconds to seconds. Here, we show that we can alleviate both problems by regularizing a Poisson-HMM during training so as to enforce large self-transition probabilities. We call this algorithm the 'sticky Poisson-HMM' (sPHMM). When used together with the Bayesian Information Criterion for model selection, the sPHMM successfully eliminates rapid state switching, outperforming an alternative strategy based on an HMM with a large prior on the self-transition probabilities. The sPHMM also captures the ground truth in surrogate datasets built to resemble the statistical properties of the experimental data.

Dynamic FeOx/FeWOx nanocomposite memristor for neuromorphic and reservoir computing.

Memristors are crucial in computing due to their potential for miniaturization, energy efficiency, and rapid switching, making them particularly suited for advanced applications such as neuromorphic computing and in-memory operations. However, these tasks often require different operational modes-volatile or nonvolatile. This study introduces a forming-free Ag/FeOx/FeWOx/Pt nanocomposite memristor capable of both operational modes, achieved through compliance current (CC) adjustment and structural engineering. Volatile switching occurs at low CC levels (<500 μA), transitioning to nonvolatile at higher levels (mA). Operating at extremely low voltages (<0.2 V), this memristor exhibits excellent uniformity, data retention, and multilevel switching, making it highly suitable for high-density data storage. The memristor successfully mimics fundamental biological synapse functions, exhibiting potentiation, depression, and spike-rate dependent plasticity (SRDP). It effectively emulates transitions from short-term memory (STM) to long-term memory (LTM) by varying pulse characteristics. Leveraging its volatile switching and STM features, the memristor proves ideal for reservoir computing (RC), where it can emulate dynamic reservoirs for sequence data classification. A physical RC system, implemented using digits 0 to 9, achieved a recognition rate of 93.4% in off-chip training with a deep neural network (DNN), confirming the memristor's effectiveness. Overall, the dual-mode switching capability of the Ag/FeOx/FeWOx/Pt memristor enhances its potential for AI applications, particularly in temporal and sequential data processing.

The role of fear and dopamine-striatal pathways in grooming.

Fear is a fundamental emotion that triggers rapid and automatic behavioral response. Fear is known to suppress reward-seeking behaviors, interrupt previous activities to prioritize defensive responses and lead to rapid switch to defensive reactions. Dopamine (DA) plays a complicated role in the choice and performance of actions and it has a potential interaction of innate actions with the presence of fear. Here, in a series of experiments we explore the role of the different DA striatal pathways in mediating grooming, an innate behavior comprised of a structured sequence of repetitive actions, with or without the presence of fear. Using chemogenetics, we specifically inhibited the DA pathways projecting to the dorsolateral striatum (DLS), dorsomedial striatum (DMS), and ventral striatum (VS), while mice were engaged in a behavioral paradigm inducing grooming during the presentation of a fear related cue. We found that fear related cues consistently reduced grooming proportions and shortened induced grooming bouts, regardless of DA manipulation, indicating prioritization of freezing behavior in fearful contexts. This also suggests that fear responses may be mediated through pathways independent of DA-based action selection. The role of DA, however, varies depending on the specific striatal pathway. Inhibiting DLS DA input delayed grooming initiation and reduced grooming when competing with freezing. In contrast, DMS DA input had no effect on grooming, while inhibition of VS mesolimbic DA input increased grooming proportions and duration. These findings underscore the distinct and sometimes opposing roles of different DA-striatal pathways in modulating innate behaviors. We discuss potential implications of this duality in DA function for both theoretical and clinical fields.

Probing sensorimotor memory through the human speech-audiomotor system.

Our knowledge of human sensorimotor learning and memory is predominantly based on the visuospatial workspace and limb movements. Humans also have a remarkable ability to produce and perceive speech sounds. We asked whether the human speech-auditory system could serve as a model to characterize the retention of sensorimotor memory in a workspace that is functionally independent of the visuospatial one. Using adaptation to altered auditory feedback, we investigated the durability of a newly acquired speech-acoustical memory (8- and 24-h delay), its sensitivity to the manner of acquisition (abrupt vs. gradual perturbation), and factors affecting memory retrieval. We observed extensive retention of learning (∼70%) but found no evidence for offline gains. The speech-acoustical memory was insensitive to the manner of its acquisition. To assess factors affecting memory retrieval, tests were first done in the absence of auditory feedback (with masking noise). Under these conditions, it appeared there was no memory for prior learning as if after an overnight delay, speakers had returned to their habitual speech production modes. However, when speech was reintroduced, resulting in speech error feedback, speakers returned immediately to their fully adapted state. This rapid switch shows that the two modes of speech production (adapted and habitual) can coexist in parallel in sensorimotor memory. The findings demonstrate extensive persistence of speech-acoustical memory and reveal context-specific memory retrieval processes in speech-motor learning. We conclude that the human speech-auditory system can be used to characterize sensorimotor memory in a workspace that is distinct from the visuospatial workspace.NEW & NOTEWORTHY There is extensive retention of speech-motor learning. Two parallel modes exist in speech motor memory, one with access to everyday habitual speech and the other with access to newly learned speech-acoustical maps. The availability of speech error feedback triggers a switch between these two modes. Properties of sensorimotor memory in the human speech-auditory system are behaviorally similar to, but functionally independent of, their visuospatial counterparts.

Systematic Analysis of Memristor Theory, manufacture and application status

Research into memristor technology has gained significant momentum because of its ability to revolutionize storage and neuromorphic computing. Memristors are two-terminal devices that retain an electrical resistance state based on prior voltage applications, embodying a nonlinear element suited for future electronic systems. Because they have low energy requirements, rapid switching capabilities, and ability to store multiple states, memristors are well-positioned to significantly influence the development of cutting-edge memory solutions and serve as artificial synapses within neuromorphic computing systems. This paper provides an exploration of recent advancements of the memristor technology, focusing on material composition, switching mechanisms, and their applications such as non-volatile memory, reconfigurable logic gates, and neuromorphic computing systems. By analyzing materials such as binary oxides, perovskites, and two-dimensional compounds, the review delves into how these materials enhance performance characteristics like speed, endurance, and energy efficiency. The discussion underscores the transformative potential of memristors in shaping next-generation computing architectures, making them a cornerstone of future innovations in both digital and analog computing.

Photoswitchable Diazocine Derivative for Adenosine A3 Receptor Activation in Psoriasis.

Incorporating photoisomerizable moieties within drugs offers the possibility of rapid and reversible light-dependent switching between active and inactive configurations. Here, we developed a photoswitchable adenosine A3 receptor (A3R) agonist that confers optical control on this G protein-coupled receptor through noninvasive topical skin irradiation in an animal model of psoriasis. This was achieved by covalently bonding an adenosine-5'-methyluronamide moiety to a diazocine photochrome, whose singular photoswitching properties facilitated repeated interconversion between a thermally stable, biologically inactive Z agonist form and a photoinduced, pharmacologically active E configuration. As a result, our photoswitchable agonist allowed the precise modulation of A3R function both in vitro and in vivo, which led to a clear light-controlled pharmacotherapeutic effect on mouse skin lesions. This breakthrough not only demonstrates the potential of diazocine photoswitches for in vivo photopharmacology but also paves the way for the development of new strategies for skin-related diseases that require localized and temporally controlled drug action.

Dynamics of β-cardiac myosin between the super-relaxed and disordered-relaxed states.

The super-relaxed (SRX) state of myosin ATPase activity is critical for striated muscle function, and its dysregulation is linked to cardiomyopathies. It is unclear whether the SRX state exchanges readily with the disordered-relaxed (DRX) state, and whether the SRX state directly corresponds to the folded back interacting-head motif (IHM). Using recombinant β-cardiac heavy meromyosin (HMM) and subfragment 1 (S1), which cannot form the IHM, we show that the SRX and DRX populations are in rapid equilibrium, dependent on myosin head-tail interactions. Some mutations which cause hypertrophic (HCM) or dilated (DCM) cardiomyopathies alter the SRX-DRX equilibrium, but not all mutations. The cardiac myosin inhibitor mavacamten slows nucleotide release by an equal factor for both HMM and S1, thus only indirectly influencing the occupancy time of the SRX state. These findings suggest that purified myosins undergo rapid switching between SRX and DRX states, refining our understanding of cardiomyopathy mechanisms.

A power‐saving control voltage‐retention circuit for fast‐locking phase‐locked loops with sleep mode

AbstractThis study proposes a voltage‐retention circuit (VRC) for a low‐power phase‐locked loop (PLL) designed for mobile interfaces. The PLL, incorporating the proposed scheme, supports the sleep mode to achieve low power consumption and fast switching between the sleep and active modes. To facilitate rapid switching between these modes, the proposed VRC stores the filter information from the previous input during sleep mode, ensuring quick settling upon reactivation. The VRC comprises a resistor‐steering digital‐to‐analog converter (DAC), a comparator, and a counter. During the active mode, the circuit adjusts the DAC using the comparator and counter to track the loop‐filter voltage, and it holds the tracked voltage value during the sleep mode. The proposed circuit, designed using a 65‐nm CMOS process, demonstrates 54% improved settling time compared to conventional circuits. Additionally, it reduces power consumption during sleep mode by 88%.

Performance Evaluation of Solar PV Integrated with Custom Power Device under Various Load Conditions

The non-linear properties and rapid switching of power electronic equipment are the primary causes of power quality issues in power systems, particularly in the power distribution systems. The widespread use of delicate equipment, which continuously pollutes the environment, is making power quality problems worse. The increasing integration of renewable energy sources into the generation mix and the decarburization of the economy have created new challenges for smart grid technology, requiring creative solutions such as energy storage systems and smart transformers. This article describes a solar photovoltaic integrated unified power quality conditioner (UPQC) that uses a deep learning method based on neural networks and a novel compensating technique. Here, two Deep Neural Network algorithms are used, one in the solar PV system to obtain the maximum power under various irradiance situations, and the other to manage the UPQC under various load conditions. When compared to the conventional UPQC based on PQ Theory, DNN-UPQC produces superior results in terms of reducing total harmonic distortion. This iterative strategy, which is focused on soft computing, provides faster convergence to the target condition while maintaining the updating weight within a predetermined limit. PV-based UPQC has been connected individually to reduce voltage sag, swell, and unbalance in variable load conditions. The system's dynamic and steady state performance are assessed by modelling it with a MATLAB-Simulink in different load condition.

Effect of Annealing Temperature on Morphology and Electrochromic Performance of Electrodeposited WO₃ Thin Films

The purpose of this study was to investigate the effect of annealing temperature on the structural, morphological, and electrochemical properties of tungsten trioxide (WO3) films, fabricated via electrodeposition and annealed at 50 °C, 250 °C, and 450 °C. Structural analysis using X-ray diffraction (XRD) revealed temperature-induced modifications, transitioning from amorphous to crystalline phases. Morphological studies by field emission scanning electron microscopy (FESEM) demonstrated an increase in grain size with temperature (31 nm, 48 nm, and 53 nm) and the formation of cracks at higher annealing temperatures. Electrochemical characterization showed that the WO3 film annealed at 250 °C exhibited superior redox activity, enhanced ion diffusion, and excellent reversibility. Optical studies highlighted its exceptional performance, with 79.35% optical modulation, a coloration efficiency of 97.91 cm2/C, and rapid switching times (9.8 s for coloration and 7.5 s for bleaching). Furthermore, long-term cycling tests confirmed minimal degradation after 5000 cycles, demonstrating durability. This work provides a comprehensive understanding of the annealing temperature’s impact on WO3 films and underscores the novelty of achieving optimal electrochromic (EC) performance through temperature tuning, advancing the design of energy-efficient smart materials.

Ultrasensitive and Breathable Hydrogel Fiber‐Based Strain Sensors Enabled by Customized Crack Design for Wireless Sign Language Recognition

AbstractWearable strain sensors, capable of continuously detecting human movements, hold great application prospects in sign language gesture recognition to alleviate the daily communication barriers of the deaf and mute community. However, the unsatisfactory strain sensing performance (such as low sensitivity, narrow detection range, etc.) and wearing discomfort severely hinder their practical application. Here, high‐performance breathable hydrogel strain sensors are proposed by introducing an adjustable localized crack in a closed‐loop connected hydrogel fiber encapsulated by porous elastomer films. Upon loading/unloading of external strain, the dynamic opening/closing of the pre‐cut crack causes a rapid switching in the hydrogel conductive path, resulting in sharp changes in resistance and a high sensitivity. Consequently, the hydrogel‐based crack‐effect strain sensor exhibits a superb sensitivity (GF up to 3930), a broad detection range (from 0.02% to 80%), fast response/recovery time (78/52 ms), repeatability, and structural stability. Based on the capability to accurately detect various strains across the full range of human movements, a wireless sign language recognition system is developed to achieve a high recognition accuracy of 98.1% by encoding and decoding various sign language gestures with the assistance of machine learning, providing a robust platform for efficient sign language intelligibility and barrier‐free communication.

Multi-objective grey wolf optimizer based on reinforcement learning for distributed hybrid flowshop scheduling towards mass personalized manufacturing

As an emerging production paradigm, mass personalized manufacturing (MPM) realizes personalized product customization under the premise of ensuring large-scale production. In this paradigm, the rapid switching of the type and quantity of manufacturing tasks increases the difficulty of scheduling. Hence, this paper proposes the distributed hybrid flowshop scheduling problem with an order modularization and tasks assigning method (DHFSP-OMTA), where heterogeneous customer orders are decomposed into standard and personalized production tasks and assigned to different factories. Meantime, towards MPM, a novel mixed integer linear programming model is established to minimize the makespan and total energy consumption simultaneously. Considering the high complexity of DHFSP-OMTA, a multi-objective grey wolf optimizer based on reinforcement learning (MOGWO-RL) is designed. This paper contains the following three improvements. Firstly, the variable tasks splitting method combines two initial heuristic-rule to produce a high-quality population. Secondly, a variable neighborhood search based on reinforcement learning is designed to improve the search quality and jump out of the local optimum. Thirdly, an efficient merging batches method is presented to save transportation energy consumption. The advantages of the proposed algorithm are verified on 18 modified test instances based on the Taillard benchmark with the MPM feature. The results show that MOGWO-RL has the best effectiveness and stability of all comparison algorithms. Therefore, it can be used as a novel method to solve MPM’s scheduling problem.

High-Performance Electrochromic Devices Composed of Niobium Tungsten Oxide Films

Electrochromic technology plays a pivotal role in various industries, offering significant benefits in energy efficiency and sustainability. By efficiently modulating sunlight, it reduces dependence on traditional climate control systems, thus decreasing overall energy consumption. Among electrochromic materials, tungsten oxide (WO3) is highly favored for its outstanding stability and superior optical modulation amplitude. However, the escalating demands of commercial applications necessitate enhancements in electrochromic performance, achievable through doping or composite designs. This study investigates the electrochromic characteristics of novel niobium tungsten oxide (Nb18W16O93) thin films, employing a gel electrolyte and examining their structural, optical, and electrochemical attributes. Compared to pure WO3, the Nb18W16O93-based electrochromic device exhibited a significant optical modulation of 55.1% in the visible spectrum and 31.3% in the near-infrared region. The gel-based device not only provides safety benefits over liquid electrolytes by mitigating leakage risks but also features rapid switching response times, with a coloration duration of 3.9 s and a bleaching interval of 3.6 s. Moreover, the device showcases exceptional long-term stability, retaining a ΔT of nearly 72% after 10,000 cycles.