Shaping Technique Research Articles

Fabrication of a photo-crosslinkable fluoropolymer-passivated flexible neural probe and acute recording and stimulation performances in vivo

Herein, we fabricated fluorine-containing, polymer-based, flexible neural probes with fluorinated ethylene propylene (FEP) films as the substrates and photo-crosslinkable fluoropolymers as the passivation material. For fabrication, metal-free Au layer formation on the FEP film, the simultaneous photo-adhesion and photo-patterning technique, and the pulsed-laser scanning probe shaping technique were combined, followed by Au electrode surface modification. The resultant probes achieved a charge injection limit equal to 5.18 mC cm−2 by implementing iridium oxide-modified nanoporous Au (IrOx/NPG) structures. We performed simultaneous in vivo micro-stimulations of the Schaffer collateral fibres and recorded the evoked field excitatory postsynaptic potentials (fEPSPs) in the stratum radiatum layer of the hippocampal Cornu Ammonis 1 region using a single probe. Inducing the fEPSP at very low charge per pulse settings (3.2–3.6 nC/pulse) indicates the efficient charge injection capability of the IrOx/NPG electrode, thereby enabling safe, prolonged, and thrifty micro-stimulations. Furthermore, the single probe-induced and recorded long-term potentiation persisted for periods longer than 60 min following theta-burst stimulation. The materials used in this study are all biocompatible and chemically robust. The fabricated neural probes can be applied in chronic clinical trials in vivo.

Input Shaping for Flexible Systems with Non-Zero Initial Conditions

Input shaping is a finite-impulse response (FIR) filter whose coefficients are designed to produce a shaped input that avoids exciting lightly-damped modes. As a result, flexible systems can be commanded to move quickly from point to point with minimum residual vibration. However, traditional input shaping techniques assume zero initial conditions, limiting their usability for systems with non-zero initial conditions, such as, emergency stops of cranes. Besides, in practice, movement of flexible systems is often initiated when the systems are not completely stationary. In these situations, the performance of the input shaping technique deteriorates. In this paper, a modification of shaper’s impulse sequence at the beginning of the move is proposed to bring the moving flexible system to a stop before commencing movement. The modification utilizes the work and energy method to determine the distance and time as functions of the initial states for base excitation of flexible systems, rendering its application to nonlinear systems. By concatenating this modification with the existing input shapers, a novel shaper called the non-zero initial conditions zero-vibration-derivative (NI-ZVDk) input shaper is introduced. The NI-ZVDk input shaper effectively prevents the movement of flexible systems from their initial states. To demonstrate the effectiveness of the approach, a 2-mass system is utilized as a benchmark for general flexible systems with 2 degrees of freedom. Various types of motion, including pure translation, pure rotation, and combined translation-rotation, are considered. Extensive simulation results showed that, using the proposed NI-ZVDk input shaper, the flexible systems can move from non-zero initial conditions to their desired destinations with less time and less residual vibration. HIGHLIGHTS The Input Shaping (IS) technique is used to suppress residual vibrations by creating destructive interference in impulse responses This method presents a novel design modification for IS when initial conditions are non-zero This technique can be extended for use in various nonlinear vibratory systems For example, it can be used when a crane needs to stop abruptly from non-zero initial conditions without residual vibrations GRAPHICAL ABSTRACT

Simple framework for systematic high-fidelity gate operations

Semiconductor spin qubits demonstrated single-qubit gates with fidelities up to benchmarked in the single-qubit subspace. However, tomographic characterizations reveal non-negligible crosstalk errors in a larger space. Additionally, it was long thought that the two-qubit gate performance is limited by charge noise, which couples to the qubits via the exchange interaction. Here, we show that coherent error sources such as a limited bandwidth of the control signals, diabaticity errors, microwave crosstalk, and non-linear transfer functions can equally limit the fidelity. We report a simple theoretical framework for pulse optimization that relates erroneous dynamics to spectral concentration problems and allows for the reuse of existing signal shaping methods on a larger set of gate operations. We apply this framework to common gate operations for spin qubits and show that simple pulse shaping techniques can significantly improve the performance of these gate operations in the presence of such coherent error sources. The methods presented in the paper were used to demonstrate two-qubit gate fidelities with in Xue et al (2022 Nature 601 343). We also find that single and two-qubit gates can be optimized using the same pulse shape. We use analytic derivations and numerical simulations to arrive at predicted gate fidelities greater than 99.9% with duration less than, where is the difference in qubit frequencies.

Low-cost wavefront shaping via the third-order correlation of light fields.

In this Letter, inspired by the ghost imaging technique, we propose a wavefront shaping technique based on the third-order correlation of light fields (TCLF). Theoretically, we prove that if the light field fluctuation can be modeled by a complex Gaussian random process with a non-zero mean, the conjugate complex amplitude of the object and a focusing phase factor can be obtained by TCLF when using a single-point detector, which can support wavefront shaping. Experiments demonstrate that TCLF can achieve high-resolution wavefront shaping for scattered fields and scattering-assisted holography without additional operations such as optimization and phase shifting.

Congestion control analysis of optical packet switch for optical data center applications

Abstract Optical data centers serve as the backbone of modern networking, facilitating seamless connectivity for users across the globe. The connection between users and the optical data centers is established through various network topologies, which play a critical role in determining the traffic characteristics. The design and implementation of these network topologies, along with the assortment of applications hosted on optical data centers, significantly influence the flow of data within the network. The advent of cloud computing has further revolutionized optical data center operations, leading to the coexistence of a wide range of applications on different optical data center switches. As a result, the traffic characteristics observed on each optical data center switch vary significantly. This diversity in traffic patterns necessitates a comprehensive understanding of how data arrival is managed and handled by the networking infrastructure. In this paper, we explore the concept of a random traffic model for data arrival on Top of Rack (ToR) switches, which represent a crucial component of optical data center networking. In the modeling, small world model is considered. The effect of buffering and packet priorities is observed on traffic shaping. Finally, to evaluate the effectiveness of the traffic shaping techniques, we measure the packet loss performance of ToR switches and found to be as low as 10−4 even at the higher loads. Blocking performance provides valuable insights into how effectively the optical data center network manages incoming data and avoids congestion or bottlenecks.

Efficiently scanning a focus behind scattering media beyond memory effect by wavefront tilting and re-optimization.

One of the main challenges in the wavefront shaping technique is to enable controllable light propagation through scattering media. However, the scanning of the focus generated by wavefront shaping is limited to a small range determined by the optical memory effect (ME). Here, we propose and demonstrate efficiently scanning a focus behind scattering media beyond the ME region using the wavefront tilting and re-optimization (WFT&RO) method. After scanning an initial focus to a desired position by wavefront tilting, our approach utilizes the scanned focus at a new position as the "guide star" to do wavefront re-optimization, which can not only enhance the intensity of the focus to the value before scanning but also accelerate the optimization speed. Repeat such a process, we can theoretically fast scan the focus to any position beyond the ME region while maintaining a relatively uniform intensity. We experimentally demonstrate the power of the method by scanning a focus with uniform intensity values through an optical diffuser within a range that is at least 5 folds larger than the ME region. Additionally, for the case of two cascaded optical diffusers, the scanning range achieved is at least 7 folds larger than the ME region. Our method holds promising implications for applications such as imaging through media, where the ability to control light through scattering media is crucial.

Velocity range-based reward shaping technique for effective map-less navigation with LiDAR sensor and deep reinforcement learning.

In recent years, sensor components similar to human sensory functions have been rapidly developed in the hardware field, enabling the acquisition of information at a level beyond that of humans, and in the software field, artificial intelligence technology has been utilized to enable cognitive abilities and decision-making such as prediction, analysis, and judgment. These changes are being utilized in various industries and fields. In particular, new hardware and software technologies are being rapidly applied to robotics products, showing a level of performance and completeness that was previously unimaginable. In this paper, we researched the topic of establishing an optimal path plan for autonomous driving using LiDAR sensors and deep reinforcement learning in a workplace without map and grid coordinates for mobile robots, which are widely used in logistics and manufacturing sites. For this purpose, we reviewed the hardware configuration of mobile robots capable of autonomous driving, checked the characteristics of the main core sensors, and investigated the core technologies of autonomous driving. In addition, we reviewed the appropriate deep reinforcement learning algorithm to realize the autonomous driving of mobile robots, defined a deep neural network for autonomous driving data conversion, and defined a reward function for path planning. The contents investigated in this paper were built into a simulation environment to verify the autonomous path planning through experiment, and an additional reward technique "Velocity Range-based Evaluation Method" was proposed for further improvement of performance indicators required in the real field, and the effectiveness was verified. The simulation environment and detailed results of experiments are described in this paper, and it is expected as guidance and reference research for applying these technologies in the field.

The Effect of Leading-Edge Wavy Shape on the Performance of Small-Scale HAWT Rotors

The purpose of this experimental work was to investigate the role of the leading-edge wavy shape technique on the performance of small-scale HAWT fixed-pitch rotor blades operating under off-design conditions. Geometric parameters such as amplitude and wavelength were considered design variables to generate five different wavy shape blade models in order to increase the aerodynamic performance of the rotor with a diameter of 280 mm. A dedicated airfoil type S822 for small wind turbine application from the NREL Airfoil Family was chosen to fulfil both the aerodynamic and structural aspects of the blades. Rotor models were tested in a wind tunnel for different wind speeds while maintaining constant rotational speed to provide the blade-tip chord Reynolds number of 4.7 × 104. The corrected tunnel data, in terms of power coefficients and tip-speed ratios, were compared first with the literature to validate the experimental approach, and then among themselves. It was observed that for minimal sizes of tubercles, the performance of the rotor increases by about 40% compared to the RB1 baseline rotor model for a low tip-speed ratio. Conversely, for the maximum size of the tubercles, there is a marked decrease of about 51% of the rotor performance for a moderate tip-speed ratio compared to the RB1 rotor model. Among these models, specifically, the RB2 rotor model with the smallest values of amplitude and wavelength provides a 2.8% higher peak power coefficient compared to the RB1 rotor model, and at the same time preserves higher performance values for a broad range of tip-speed ratios.

Comparison between different cancer radiotherapy field shaping techniques using 6 MV and 15 MV photon energies.

Comparison between different cancer radiotherapy field shaping techniques using 6 MV and 15 MV photon energies.

Flexible generation of broadly wavelength- and OAM-tunable Laguerre-Gaussian (LG) modes from a random fiber laser.

Broadband wavelength tunable Laguerre-Gaussian (LG) mode with flexibly manipulated topological charge is greatly desired for large-capacity optical communication. However, the operating wavelengths achieved for the current LG modes are significantly restricted either by the emission spectrum of the intracavity gain medium or by the operation wavelengths of mode-conversion or modulation components. Here, broadband wavelength-tunable LG modes with a controllable topological charge are generated based on a random fiber laser (RFL) and a digital micromirror device (DMD). The RFL can produce broadly wavelength-tunable laser emissions spanning from 1044 to 1403 nm with a high spectral purity and an excellent beam quality, benefiting from the cascaded random Raman gain starting from a ytterbium fiber based active gain. A commercially available broadband DMD is then utilized to excite the LG modes with a flexibly tunable topological charge of up to 100 order through the super-pixel wavefront shaping technique. The combination of the RFL and the DMD greatly broadens the operating wavelength region of the LG modes to be achieved, which facilitates the capacity scaling-up in the orbital angular momentum multiplexed optical communication application.

Autonomous Guidance Between Quasiperiodic Orbits in Cislunar Space via Deep Reinforcement Learning

This paper investigates the use of reinforcement learning for the fuel-optimal guidance of a spacecraft during a time-free low-thrust transfer between two libration point orbits in the cislunar environment. To this aim, a deep neural network is trained via proximal policy optimization to map any spacecraft state to the optimal control action. A general-purpose reward is used to guide the network toward a fuel-optimal control law, regardless of the specific pair of libration orbits considered and without the use of any ad hoc reward shaping technique. Eventually, the learned control policies are compared with the optimal solutions provided by a direct method in two different mission scenarios, and Monte Carlo simulations are used to assess the policies’ robustness to navigation uncertainties.

US-BSF: a unified simplification of BSF model with different scattering phase functions for underwater wireless optical communication.

Underwater wireless optical communications (UWOCs) use beam shaping techniques such as the Beer-Lambert (BL) law which describes how light interacts with matter. The BL model ignores the scattering effect of UWOC, while the beam spread function (BSF) can characterize the combined effect of absorption and scattering of UWOC more accurately. The original triple-integral beam spread function (OTI-BSF) involves the Bessel function, which is very time-consuming to calculate. In addition, different seawater environments may require different scattering phase functions (SPFs) to obtain accurate modeling results compared with Henyey-Greenstein SPF (HG-SPF). So far, the BSF-based channel data generation and performance analysis in complex water environments have been time-consuming. We propose a unified simplification of BSF (US-BSF) channel based on the Gaussian mixture model, which is suitable for three commonly used SPFs. From the point of view of time consumption, our proposed US-BSF only requires an order of O(10-4) s to calculate a value on average, while the OTI-BSF requires an order of O(102) s.

Deep reinforcement learning for cooperative robots based on adaptive sentiment feedback

Human–robot cooperative tasks have gained importance with the emergence of robotics and artificial intelligence technology. In interactive reinforcement learning techniques, robots learn target tasks by receiving feedback from an experienced human trainer. However, most interactive reinforcement learning studies require a separate process to integrate the trainer’s feedback into the training dataset, making it challenging for robots to learn new tasks from humans in real-time. Furthermore, the types of feedback sentences that trainers can use are limited in previous research. To address these limitations, this paper proposes a robot teaching strategy that uses deep RL via human–robot interaction to learn table balancing tasks interactively. The proposed system employs Deep Q-Network with real-time sentiment feedback delivered through the trainer’s speech to learn cooperative tasks. We designed a novel reward function that incorporates sentiment feedback from human speech in real-time during the learning process. The paper presents an improved reward shaping technique based on subdivided feedback levels and shrinking feedback. This function serves as a guide for the robot to engage in natural interactions with humans and enables it to learn the tasks effectively. Experimental results demonstrate that the proposed interactive deep reinforcement learning model achieved a high success rate of up to 99.06%, outperforming the model without sentiment feedback.

Reference-less wavefront shaping in a Hopfield-like rough intensity landscape.

This study introduces a new digital-micromirror based binary-phase wavefront shaping technique, which allows the measurement of the full coupling matrix of a disordered medium without a reference and enables to focusing transmitted light. The coupling matrix takes on a bi-dyadic structure, similar to a Hopfield memory matrix containing two memory patterns. Sequential wavefront optimization in this configuration often stalls due to a rough intensity landscape, resulting in a non-optimal state. To overcome this issue, we propose the Complete Couplings Mapping method, which consistently reaches the theoretically expected maximum intensity.

Robust watermark based on Schur decomposition and dynamic weighting factors

Since multimedia data are now more widely distributed in digital form and easier to copy and change, copyright protection has become an essential need. One of the most common copyright protection techniques is watermarking. Invisibility and robustness are crucial aspects of watermarking; however, many of the currently used techniques simply focus more on invisibility than how robust they are. Moreover, the trade-off between invisibility and robustness is challenging. To this end, this paper proposes a novel watermark technique that efficiently overcomes the idea of a trade-off between robustness and invisibility, thereby increasing both under most attacks. Schur decomposition and a dynamic weighting factors matrix are added to the embedding process to improve the robustness of the proposed technique. Besides that, the embedding function is improved to simultaneously maximize imperceptibility and robustness. Another key contribution of the proposed approach is its use of a trajectory-based optimization algorithm rather than the more prevalent population-based algorithms to determine the optimal scaling factors. Consequently, the proposed technique rapidly identifies the best scaling factors for the embedding function. Statistical analysis is performed using the Friedman test. Experimental results show that the proposed technique outperforms other existing techniques for different sizes, shapes, and types of watermarks.

Pattern Shaping by Utilizing EBG Phase Response and Its Use in MIMO Radio Altimeter Antenna Design for Aircraft

In this study, a novel pattern shaping technique is presented and applied to the uniquely designed multiple-input multiple-output (MIMO) radio altimeter antenna, acquiring area gain. Inspired by the behavior of the perfect electric conductor, the tendency to gather a diffuse pattern is exploited to create pattern shaping. A surface with a phase response of 0° at 3.824 GHz was designed to ensure that the target radio altimeter frequency of 4.3 GHz is in the immediate vicinity of the outer phase region, where the impedance is around 166.84 Ω, transforming the diffuse pattern of the top antenna into the target conical shape. Antenna reflection values are measured as −20.072 dB at 4.344 GHz (port 1) and −27.44 dB at 4.32 GHz (port 2), while there is 6 mm between the top antenna and its reflector. At 4.32 GHz, the envelope correlation coefficient is 0.0043, the diversity gain is 9.999, and the transmission value between the opposing ports is −29.08 dB, which indicates a low mutual coupling. A MIMO antenna with a measured gain of 10.1497 dBi for port 1 and 10.5617 dBi for port 2 conforming to the design criteria of the radio altimeter is achieved.

Technological dynamics of Early Iron Age ceramics from the Heuneburg (SW Germany): A synthesis of 50 years of research

This paper addresses technological dynamics revealed through raw material analyses of Late Hallstatt (seventh–fifth centuries BCE) ceramics from the famous Heuneburg site (Herbertingen-Hundersingen, SW Germany). The study combines, for the first time, separate sets of thin-sections produced over the last 50 years in order to provide a comprehensive and consolidated characterisation of technological changes in ceramic production taking place at the site during the Hallstatt phases D1 to D3. It provides significant new insights into the relation between raw material procurement and preparation, on the one hand, and changes in ceramic typology and production methods, on the other hand (i.e. the introduction of the potter’s wheel). The results reveal a shift from a broad spectrum of fabrics tempered with grog, sand or crushed calcite in phase Hallstatt D1, to the increasing use of non-calcareous, grog or sand-tempered fabrics. The new wheel-turned pottery (appearing from phase Hallstatt D3) is exclusively produced using a non-calcareous clay, often tempered with fine sand, indicating a specialisation in raw material selection alongside the introduction of novel shaping techniques. Evidence of continuity between the fabrics used in phase Hallstatt D1 and the new wheel-turned pottery suggests craft specialists drew upon established technological knowledge to integrate the potter’s wheel. The adoption of the potter’s wheel was likely also stimulated by the increased demand for new vessels to accommodate the consumption of fermented drinks such as grape wine, fruit wine or beer.

Prediction of metal deformation due to line heating; an alternative method of mechanical bending, based on artificial neural network approach

Line heating is one of the alternative methods of forming metals and this kind of forming uses the heating torch as a source of heat input. During the process, many parameters are considered like the size of the substrate, thickness, cooling method, source power intensity, the travel speed of the power source, the sequence of heating, and so on. It is important to analyze the factors affecting the metal bending process to effectively predict the nature and final shape of a material. The present study addresses parametric research and a new prediction technique for the final shape of metal using the ANN (Artificial Neural Network) approach. The experimental data are validated using the numerical finite element method. The test setup with orthogonal arrangement L9 is used for the setup of the experimental investigation. ANN is used for model accuracy with less dependence on measured data. All steps are performed in MATLAB with different training schemes. The network takes into account three process parameters, such as metal thickness, movement speed, and the number of passes, and the multi-layered perceptron neural network is trained and tested on the data. The predictive output of the ANN model is compared to the experimental results of the final bending of a metal and shows a good fit of the predicted values of ANN to the measured data with higher values, 97% of the coefficient of determination.

Experimental and numerical investigation on the dynamic shear failure mechanism of sandstone using short beam compression specimen

In this study, a novel testing method is proposed to characterize the dynamic shear property and failure mechanism of rocks by introducing the short beam compression (SBC) specimen into the split Hopkinson pressure bar (SHPB) system. Firstly, the stress distribution of SBC specimen is comprehensively analyzed by finite element method (FEM), and the results show that the optimal notch separation ratio of SBC specimen is C/H = 0.2 to achieve successful dynamic simple-shear tests. Then, dynamic shear tests are conducted on sandstone using the SBC-SHPB method. Via careful pulse shaping technique, the dynamic force balance is guaranteed for SBC specimens, and the testing results show that the dynamic shear strength of sandstone is significantly rate-dependent. Combining the results of dynamic compression and tension tests, the failure envelopes of sandstone under different loading rates are obtained in the principle stress plane. It is found that the failure envelope of sandstone constantly expands outwards with increasing loading rate. Moreover, the energy partition of SBC specimen is quantified by virtue of high-speed digital image correlation (DIC) technique. The results show that the kinetic energy portion is non-negligible, and the shear fracture energy increases with increasing loading rate. In addition, the microscopic shear cracking mechanism of SBC specimen is analyzed by the thin section observation: the intra-granular (TG) fracture of minerals dominates the dynamic shear failure of sandstone, and the portion of TG fracture increases with increasing loading rate. This study provides a convenient and reliable method to measure the dynamic shear property and failure mechanism of rocks.

Spectrally Efficient Pulse Shaping for Beamspace Space Shift Keying in Single-RF ESPAR Systems

A novel spectrally efficient pulse shaping technique for space shift keying (SSK) in single radio frequency (single-RF) antenna systems is proposed. This technique is important since a key issue often overlooked in most single-RF systems, including SSK, is pulse shaping. The proposed pulse shaping technique is based on using an electronically steerable parasitic array radiator (ESPAR). It can avoid the bandwidth expansion arising from switching in SSK while enhancing spectral efficiency (SE) compared to conventional time-limited pulse shaping. In the proposed approach, we pulse shape the parasitic loads of the antennas in the ESPAR by using pulse shaped baseband control voltages to continuously vary the parasitic loads. This is enabled by developing an approximate linear mapping from the baseband control voltages to the ESPAR element currents. Simulation results of the proposed technique are provided, including the continuous-time ESPAR current and its power spectrum density, adjacent channel power ratio, symbol error rate (SER), SE, and energy efficiency (EE). It is shown that the proposed technique can perform spectrally efficient pulse shaping for beamspace SSK and achieve higher SE and EE than time-limited pulse shaping while maintaining the same SER.