Dynamic Mirror Research Articles

An event-triggered background-oriented schlieren technique combined with dynamic projection using dynamic mirror device

Abstract This paper reports a high-frequency event-triggered background-oriented schlieren (BOS) technique using a combination of an event-triggered camera and dynamic projection. To combine the advantages of continuous and pulsed illumination for the event-triggered camera, a novel background pattern is first developed to incorporate static and dynamic textures generated through projection utilizing a dynamic mirror device (DMD). Then, a specific post-processing algorithm is proposed to reconstruct frames with high time accuracy from event data. This technique allows for the continuous observation and capturing of flows at 4000 frames per second (FPS) with a very low cost, breaking through the short operating times of current high-frame-rate BOS. Moreover, the proposed BOS technique can visualize the flow in real-time with high temporal accuracy, a capability that is challenging to achieve with traditional BOS. To examine the proposed technique, BOS experiments were conducted on a sweeping jet actuator with various inlet pressure. The sweeping dynamics and the start-up process of the sweeping jet at various inlet pressure were visualized and investigated. It is found that the proposed event-triggered BOS can continuously visualize and record the jet flow at a resolution of 1280 × 720 pixels with an equivalent frame rate of up to 4000 FPS. The oscillation frequency of the sweeping jet was found to increase linearly with increasing inlet pressure. It reaches 117.2 Hz at an inlet pressure of 0.5 Mpa. Within the first ten milliseconds or so of start-up, the shape of the sweep was found to be symmetrical. Within the next hundred milliseconds, the jet commences to sweep and saturates. The start-up time of the sweeping jet was quantitatively measured and was observed to decrease with increased inlet pressures.

Analysing the Role of Social Media in Facilitating the Emerging Anti-Woke Sentiments

Social media has become an omnipresent force shaping cultural trends in contemporary society. Through platforms like Instagram, Twitter, and TikTok, individuals can swiftly share ideas, images, and opinions, fostering a rapid exchange of cultural influences. The accessibility and speed of information dissemination on these platforms amplify the spread of trends, from fashion and music to language and lifestyle. Social media’s influence extends beyond mere reflection, actively contributing to the creation of new cultural phenomena. It acts as a dynamic mirror, both reflecting and shaping the collective consciousness of societies worldwide, molding cultural landscapes in ways unprecedented in previous eras.

Asthma's effect on brain connectivity and cognitive decline.

To investigate the changes in dynamic voxel mirror homotopy connection (dVMHC) between cerebral hemispheres in patients with asthma. Our study was designed using a case-control method. A total of 31 subjects with BA and 31 healthy subjects with matching basic information were examined using rsfMRI. We also calculated and obtained the dVMHC value between the cerebral cortexes. Compared with the normal control group, the dVMHC of the lingual gyrus (Ling) and the calcarine sulcus (CAL), which represented the visual network (VN), increased significantly in the asthma group, while the dVMHC of the medial superior frontal gyrus (MSFG), the anterior/middle/posterior cingulate gyrus (A/M/PCG), and the supplementary motor area (SMA) of the sensorimotor network decreased significantly in the asthma group. This study showed that the ability of emotion regulation and the efficiency of visual and cognitive information processing in patients with BA was lower than in those in the HC group. The dVMHC analysis can be used to sensitively evaluate oxygen saturation, visual function changes, and attention bias caused by emotional disorders in patients with asthma, as well as to predict airway hyperresponsiveness, inflammatory progression, and dyspnea.

Design of a Dynamic Secondary Mirror Truss Adjustment Mechanism for Large Aperture Telescopes

This study focuses on the dynamic secondary mirror truss adjustment mechanism for large aperture telescopes. The relative positions between the primary and secondary mirrors have stringent requirements for large aperture optical telescopes, with an aperture of more than 2 m. Due to the large mass of the primary mirror, the secondary mirror system is designed as an adjustable mechanism with multiple degrees of freedom, dramatically impacting telescope imaging. The kinematic modeling is followed by a detailed description of the designed adjustment mechanism, and then a static and modal analysis of the designed mechanism is performed. Subsequently, a kinematic performance test of the experimental prototype is conducted. The developed mechanism can travel up to ±5 mm in the z-direction with an accuracy of 16 µm and deflection of ±0.574° in the xy-direction. It provides accuracy better than 6.4 arcseconds.

Adaptive individual residential load forecasting based on deep learning and dynamic mirror descent

With a growing penetration of renewable energy generation in the modern power networks, it has become highly challenging for network operators to balance electricity supply and demand. Residential load forecasting nowadays plays an increasingly important role in this aspect and facilitates various interactions between power networks and electricity users. While numerous research works have been proposed targeting at aggregate residential load forecasting, only a few efforts have been made towards individual residential load forecasting. The issue of volatility of individual residential load has never been addressed in forecasting. Thus, to fill this gap, this paper presents a deep learning method empowered with dynamic mirror descent for adaptive individual residential load forecasting. The proposed method is evaluated on a real-life Irish residential load dataset, and the experimental results show that it improves the prediction accuracy by 9.1% and 11.6% in the aspects of RMSE and MAE respectively in comparison with a benchmark method.

Love in Eileen Chang’s works: Distinctive and ideological

In the realm of literature, the exploration of love has perpetually fascinated both creators and readers, serving as a dynamic mirror reflecting shifts in societal norms, cultural undercurrents, and ideological tides. Across the epochs, the portrayal of love within literary works has undergone a profound evolution. In the tapestry of classical Chinese literature, characterized by draconian dogmas and entrenched male chauvinism during the feudal era, women were often relegated to subordinate roles, their experiences of love marred by silent endurance. However, a literary luminary emerged who infused new vitality into the depiction of affection – Eileen Chang. Her narratives transcended conventions, empowering individuals of all genders to articulate their emotions boldly, resist societal constraints, and challenge the forces that dictated their fates. Within the intricate weave of her prose, love ceased to be a mere sentiment; instead, it emerged as an indomitable force of defiance and liberation. This research article delves meticulously into the exquisite tapestry of love woven by Eileen Chang, casting a spotlight on its enduring essence and providing a contemporary evaluation that harmonizes with modern perspectives.

Representative Farming and Non-Farming Communities as a Dynamic Mirror of Unidimensional Poverty in Pakistan

This research examines rural and urban poverty in Pakistan on a national and provincial scale, examining its many facets. Using the HIES/PSLM data of Pakistan, which is recognized internationally, from 2013–14 to 2018–19, and two well-respected indexing approaches (FGTI for single-dimensional poverty and Alkire & Foster for multidimensional poverty), we can examine the evolution of poverty in Pakistan over the past five years. According to the findings of the time series analysis, poverty shows a mixed (rising and falling) pattern over a shorter time frame (1-2 years) and a declining trend over a longer time frame (national and provincial levels, farming, and non-farming communities) overall (at least 05 years). In Pakistan, empirical data shows that poverty has decreased by 45.1% (32.1%) among farming and non-farming communities over the past five years. The results reveal a downward trend across Pakistan's provinces, except for Baluchistan. Specific poverty declined by 46.29 percent (36.15 percent) in Punjab, 71.1 percent (75.0 percent) in KPK, and 37.0 eight percent (2.0 percent) in Sindh. Baluchistan's farming (non-farming) communities have been getting poorer, from 20.64 percent to 61.28 percent. Punjab and Sindh provinces are Sutor’s contributors to overall poverty, as seen by the decomposition of the population by the group for uni-dimensional poverty. Reduce poverty in both regions using a single-pronged approach by boosting economic growth and expanding employment options.

Blister formation in dynamic release mirror structures using femtosecond laser pulses.

Blister formation occurs when a laser pulse interacts with the underside of a polymer film on a glass substrate and is fundamental in Laser-Induced Forward Transfer (LIFT). We present a novel method of controlling blister formation using a thin metal film situated between two thin polymer films. This enables a wide range of laser pulse energies by limiting the laser penetration in the film, which allows us to exploit nonlinear interactions without transmitting high intensities that may destroy a transfer material. We study blisters using a helium ion microscope, which images their interiors, and find that laser energy deposition is primarily in the metal layer and the top polymer layer remains intact. Blister expansion is driven by laser-induced spallation of the gold film. Our work shows that this technique could be a viable platform for contaminant-free LIFT using nonlinear absorption beyond the diffraction limit.

The Role of Dynamic Core and Mirror Neuron System in Dissociative Disorder

This paper examines the current problems in understanding and conceptualizing the “personalities” of individuals with dissociate identity disorder while seeking a biological correlation of these personalities. First, the current theoretical ambiguity and potential problems regarding how we understand personalities in dissociate identity disorder are delineated by examining current international diagnostic criteria and views proposed by leading experts on the topic. The general trend is not to acknowledge each personality as having an independent sense of self, but rather a partial and fragmentary one, which does not seem to match well with its clinical manifestations. The author subsequently proposes that each personality has an independent neurological correlate, a neural network integrated as a dynamic core, as proposed by G. Edelman and G. Tononi. Although their theory is not designed to explicate personalities in dissociate identity disorder, the biological correlates of the personalities might be approximated to a coexistence of multiple dynamic cores, which was predicted by them, and partially exemplified by brain functions in split-brain experiments. The author then draws on the current understanding of the mirror neuron system discovered by G. Rizzolatti, V. Gallese, et al., which forms a basis for the understanding of how our sense of self is formed. They propose that the potential dysfunction of the mirror neuron system in a traumatic and critical situation might explain how different personalities are formed. Finally, the article discusses how these advances might be incorporated into our understanding and treatment of individuals with dissociate identity disorder.

Dynamic wavefront distortion in resonant scanners.

Dynamic mirror deformation can substantially degrade the performance of optical instruments using resonant scanners. Here, we evaluate two scanners with resonant frequencies >12kHz with low dynamic distortion. First, we tested an existing galvanometric motor with a novel, to the best of our knowledge, mirror substrate material, silicon carbide, which resonates at 13.8 kHz. This material is stiffer than conventional optical glasses and has lower manufacturing toxicity than beryllium, the stiffest material currently used for this application. Then, we tested a biaxial microelectromechanical (MEMS) scanner with the resonant axis operating at 29.4 kHz. Dynamic deformation measurements show that wavefront aberrations in the galvanometric scanner are dominated by linear oblique astigmatism (90%), while wavefront aberrations in the MEMS scanner are dominated by horizontal coma (30%) and oblique trefoil (27%). In both scanners, distortion amplitude increases linearly with deflection angle, yielding diffraction-limited performance over half of the maximum possible deflection for wavelengths longer than 450 nm and over the full deflection range for wavelengths above 850 nm. Diffraction-limited performance for shorter wavelengths or over larger fractions of the deflection range can be achieved by reducing the beam diameter at the mirror surface. The small dynamic distortion of the MEMS scanner offers a promising alternative to galvanometric resonant scanners with desirable but currently unattainably high resonant frequencies.

Combining Switchable Phase‐Change Materials and Phase‐Transition Materials for Thermally Regulated Smart Mid‐Infrared Modulators

AbstractPhase‐change materials (PCMs) and phase‐transition materials (PTMs) both show a large contrast in their respective optical properties upon switching, enabling compact optical components with diverse functionalities like sensing, thermal imaging, and data recording. However, their switching properties differ significantly, that is, the switching is non‐volatile for PCMs while volatile for PTMs. Here, new‐generation smart mid‐infrared modulators with switchable transmission, reflection, and absorption are demonstrated conceptually and experimentally, which combine one PCM (Ge3Sb2Te6 or In3SbTe2) with one PTM (VO2) as two active layers. The bottom VO2 layer is employed as a thermally regulated (modulated) dynamic mirror, facilitating the switching of transmission between “on” state (using VO2 in its semiconducting state at temperatures below its phase transition temperature Tc) and “off” state (metallic VO2 at temperatures above Tc). The PCM layer on top of the metallic VO2 layer is used either for continuously adjusting the absorption peak spectrally (by up to 1.8 µm using different phases of Ge3Sb2Te6) or for switching between absorption mode (A = 0.99 with amorphous In3SbTe2) and reflection mode (R = 0.85 with crystalline In3SbTe2). The presented concept of merging static, non‐volatile thermal switching (via PCMs) with dynamic, volatile thermal modulation (via PTMs) empowers a new generation of optical devices for smart optical switching, for example in spectrally tunable safety optical switches.

Dynamic distortion in resonant galvanometric optical scanners.

High-speed optical systems are revolutionizing biomedical imaging in microscopy, DNA sequencing, and flow cytometry, as well as numerous other applications, including data storage, display technologies, printing, and autonomous vehicles. These systems often achieve the necessary imaging or sensing speed through the use of resonant galvanometric optical scanners. Here, we show that the optical performance of these devices suffers due to the dynamic mirror distortion that arises from the variation in torque with angular displacement. In one of two scanners tested, these distortions result in a variation of signal-to-noise (Strehl) ratio by an order of magnitude across the field of view, degrading transverse resolution by more than a factor of 2. This mirror distortion could be mitigated through the use of stiffer materials, such as beryllium or silicon carbide, at the expense of surface roughness, as these cannot be polished to the same degree of smoothness as common optical glasses. The repeatability of the dynamic distortion indicates that computational and optical corrective methods are also possible.

Wafer-Level Vacuum-Packaged Translatory MEMS Actuator with Large Stroke for NIR-FT Spectrometers.

We present a wafer-level vacuum-packaged (WLVP) translatory micro-electro-mechanical system (MEMS) actuator developed for a compact near-infrared-Fourier transform spectrometer (NIR-FTS) with 800–2500 nm spectral bandwidth and signal-nose-ratio (SNR) > 1000 in the smaller bandwidth range (1200–2500 nm) for 1 s measuring time. Although monolithic, highly miniaturized MEMS NIR-FTSs exist today, we follow a classical optical FT instrumentation using a resonant MEMS mirror of 5 mm diameter with precise out-of-plane translatory oscillation for optical path-length modulation. Compared to highly miniaturized MEMS NIR-FTS, the present concept features higher optical throughput and resolution, as well as mechanical robustness and insensitivity to vibration and mechanical shock, compared to conventional FTS mirror drives. The large-stroke MEMS design uses a fully symmetrical four-pantograph suspension, avoiding problems with tilting and parasitic modes. Due to significant gas damping, a permanent vacuum of ≤3.21 Pa is required. Therefore, an MEMS design with WLVP optimization for the NIR spectral range with minimized static and dynamic mirror deformation of ≤100 nm was developed. For hermetic sealing, glass-frit bonding at elevated process temperatures of 430–440 °C was used to ensure compatibility with a qualified MEMS processes. Finally, a WLVP MEMS with a vacuum pressure of ≤0.15 Pa and Q ≥ 38,600 was realized, resulting in a stroke of 700 µm at 267 Hz for driving at 4 V in parametric resonance. The long-term stability of the 0.2 Pa interior vacuum was successfully tested using a Ne fine-leakage test and resulted in an estimated lifetime of >10 years. This meets the requirements of a compact NIR-FTS.

Embedded Digital Twins in future energy management systems: paving the way for automated grid control

Abstract Emerging real-time applications in information technology, and operational technology enable new innovative concepts to design and operate cyber-physical systems. A promising approach, which has been discovered recently as key technology by several industries is the Digital Twin (DT) concept. A DT connects the virtual representation of a physical object, system or process by available information and sensor data streams, which allows to gather new information about the system it mirrors by applying analytic functions. Thereby the DT technology can help to fill sensor data gaps, e. g., to support anomaly detection, and to predict future operating conditions and system states. This paper discusses a dynamic power system DT as a cornerstone instance of a new generation of EMS, and a prospective new EMS architecture, to support the increasingly complex operation of electric power systems. Unlike in traditional offline power system models, the parameters are updated dynamically using measurement information from the supervisory control and data acquisition (SCADA) and a wide area monitoring system (WAMS) to tune the model. This allows to derive a highly accurate virtual representation of the mirrored physical objects. A simulation engine, the Digital Dynamic Mirror (DDM) is introduced, in order to be able to reproduce the state of a reference network in real-time. The validation of the approach is carried out by a case study. In a closed loop within EMS applications, the DDM can help to assess contingency mitigation strategies, thus it can support the decision-making process under variable system conditions. The next generation of control centre Energy Management System (EMS) can benefit from this development by augmentation of the dynamic observability, and the rise of operator situation awareness.

Artificial neural network discovery of a switchable metasurface reflector.

Optical materials engineered to dynamically and selectively manipulate electromagnetic waves are essential to the future of modern optical systems. In this paper, we simulate various metasurface configurations consisting of periodic 1D bars or 2D pillars made of the ternary phase change material Ge2Sb2Te5 (GST). Dynamic switching behavior in reflectance is exploited due to a drastic refractive index change between the crystalline and amorphous states of GST. Selectivity in the reflection and transmission spectra is manipulated by tailoring the geometrical parameters of the metasurface. Due to the immense number of possible metasurface configurations, we train deep neural networks capable of exploring all possible designs within the working parameter space. The data requirements, predictive accuracy, and robustness of these neural networks are benchmarked against a ground truth by varying quality and quantity of training data. After ensuring trustworthy neural network advisory, we identify and validate optimal GST metasurface configurations best suited as dynamic switchable mirrors depending on selected light and manufacturing constraints.

Linear Modeling and Control of Comb-Actuated Resonant MEMS Mirror With Nonlinear Dynamics

This article presents a novel method to derive and identify an accurate small perturbation model of a comb-actuated resonant microelectromechanical system (MEMS) mirror with highly nonlinear dynamics. Besides the nonlinear stiffness and damping, the comb-drives add nonlinearities due to their electrostatic nature and their effect on the dynamic mirror amplitude over frequency behavior. The proposed model is based on a period to period energy conservation and applies for most nonlinearities present in an oscillator such as MEMS mirrors. It is shown that for specific nominal operation points with square wave excitation, the small perturbation model is linear for a wide range. The full dynamics of the derived linear model are parametrized by three constants, that can be estimated by the phase locked loop (PLL), performing a proposed identification method only based on phase measurements. An analysis of control laws usually applied in a PLL provides important information for the proper design of controllers to meet the desired behavior for individual applications.

Complex Valued State Space Model for Weakly Nonlinear Duffing Oscillator with Noncollocated External Disturbance

This paper proposes a slow flow model for a weakly nonlinear and parametrically driven Duffing oscillator and a complex valued state space model for the oscillator with noncollocated external disturbances. The combination of the parametrically driven duffing oscillator and noncollocated disturbances can be observed in resonant MEMS mirrors with a reinforcement structure to reduce dynamic mirror deformation. The model is based on a rational function approximation for the angular derivative of the out-of-plane comb drive capacitance, enabling qualitative analysis at large amplitudes while the stability analysis is maintained as the conventional cubic function approximation. The slow flow model is extended including a single tone noncollocated disturbance and is linearized at an equilibrium point for a small disturbance. The linearized disturbance model is reformulated by a complex valued state space model to cope with general wideband disturbances, allowing various analytic methods in traditional system theory. The simulation results demonstrate a good agreement between the proposed models and the ODE simulation, verifying the accuracy and benefits of the proposed models.

Distributed Online Convex Optimization With Time-Varying Coupled Inequality Constraints

This paper considers distributed online optimization with time-varying coupled inequality constraints. The global objective function is composed of local convex cost and regularization functions and the coupled constraint function is the sum of local convex functions. A distributed online primal-dual dynamic mirror descent algorithm is proposed to solve this problem, where the local cost, regularization, and constraint functions are held privately and revealed only after each time slot. Without assuming Slater's condition, we first derive regret and constraint violation bounds for the algorithm and show how they depend on the stepsize sequences, the accumulated dynamic variation of the comparator sequence, the number of agents, and the network connectivity. As a result, under some natural decreasing stepsize sequences, we prove that the algorithm achieves sublinear dynamic regret and constraint violation if the accumulated dynamic variation of the optimal sequence also grows sublinearly. We also prove that the algorithm achieves sublinear static regret and constraint violation under mild conditions. Assuming Slater's condition, we show that the algorithm achieves smaller bounds on the constraint violation. In addition, smaller bounds on the static regret are achieved when the objective function is strongly convex. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results.

Automated ambient recognition method based on dynamic center mirror local binary pattern: DCMLBP

Voice recognition and sound classification is a hot-topic research area in the literature and many methods have been presented. Ambient recognition is very important problem by using voices or acoustic. Especially, digital forensics examiners need an automated ambient recognition system by using acoustical voices. In this study, a novel automatic ambient recognition method is presented by using acoustic. Firstly, an acoustical voice dataset is acquired. These voices are categorized in the 8 classes and these classes are kinder garden, ferryboat, airport, café, subway, bus, traffic and walking. Then, a sequential learning method is presented for ambient recognition using acoustical voices. The proposed method consists of dynamic center mirror local binary pattern (DCMLBP) and discrete wavelet transform (DWT), neighborhood component analysis (NCA) based feature selection and classification phases. By using DWT, a sequential learning method is proposed and the proposed feature extraction method has nine levels. Experiments clearly show that the proposed DCMLBP based method has high classification accuracy, precision, geometric mean, F-score for ambient recognition. According to results, the best accuracy rate was calculated as 99.97% ± 0.07% by using support vector machine and 128 features.

Novel wide dynamic range current mirror

A novel cascode current mirror for low-voltage application with larger input dynamic range is presented. The proposed mirror circuit combines the advantages of wide input swing, wide output swing and large output resistance capability. It is suitable for low-voltage and low-power application. Simulation results show that the circuit work properly for the input current ranges of 10 [Formula: see text]A to 1 mA and bandwidth is 5.02 GHz for 1 mA DC component.