Continuous Range Research Articles

An octave tuning range quad-core VCO using a multi-mode resonator

This paper presents a novel multi-core multi-mode electric-magnetic (E-M) mixed-coupling voltage-controlled oscillator (VCO), achieving wide tuning range and phase noise optimization simultaneously through a multi-core structure. A symmetric multi-mode resonator is proposed to address the issue of differential signal mismatch caused by transformer asymmetry. An inductor ring is used to balance the inductance of each mode and its effect in each mode is analyzed in detail. A symmetrical switch network is employed for mode switching, offering advantages such as reduced parasitics and mismatch. The utilization of a varactor combined with a fixed capacitor enables electrical coupling, ensuring overlapping frequency bands even with variations in process, voltage, and temperature (PVT), and extending the tuning range. Furthermore, a switched resistor array is employed to bias the negative resistance pair and minimize the contribution of 1/f noise upconversion to the phase noise. Designed in a 40-nm complementary metal–oxide–semiconductor (CMOS) technology with a core area of 0.16 mm2, the VCO achieves a simulated continuous tuning range of 81.5%, spanning from 11.1 to 26.4 GHz. Operating at a 1.1 V supply with a power consumption of 16 mW, the phase noise at 12.15 GHz is −118.6 dBc/Hz at a 1 MHz offset, corresponding to a figure-of-merit (FoM) of 188.3 dBc/Hz and a FoMT of −206.3 dBc/Hz.

Deep reinforcement learning-aided minimum current control for the DBSRC based on harmonic analysis method

Aiming to optimize the modulation efficiency for the dual-bridge series-resonant converter (DBSRC), this paper proposes an deep reinforcement learning (DRL) aided EPS (DEPS) modulation scheme for minimum current operation based on the harmonic analysis method. Using the deep deterministic policy gradient (DDPG) algorithm as an advanced DRL algorithm, the scheme obtains the optimized modulation scheme DEPS through offline training of the agent, which can adopt the extended-phase-shift (EPS) modulation scheme and consider the zero-voltage-switching (ZVS) constraints. Thus, the trained agent of the DDPG which likes an implicit function, can provide optimal phase shift angle for the DBSRC in real-time with the minimum current and soft switching performance in the continuous operation range. Compared with the existing EPS modulation schemes using First Harmonic Approximation (FHA), the DEPS modulation scheme has similar operational efficiency and performance of the converter, while also possessing the ability to obtain modulation angles in real-time based on environmental parameters. Finally, PSIM simulation verifies the effectiveness of the proposed optimization scheme.

An effective droplet sieving method by a trapezoidal stepped microchannel

The droplet sieving process in a trapezoidal stepped microchannel was visually investigated. The sieving mechanism of the small droplet and the moving trajectory of the main droplet were studied. Three flow patterns were found in the experiment: incomplete sieving, complete sieving and main droplet loss regimes. The results show that with the increase of continuous phase superficial velocity Ut, the flow pattern evolves from incomplete sieving to complete sieving and finally to the main droplet loss regimes. The continuous phase flow rate range for the complete sieving regime increases with the growth of main droplet size. Meanwhile, the influences of droplet size and flow rate of continuous phase on the sieving process were investigated. The sieving efficiency decreases with the increase of droplet size of small droplets, whereas it is almost unaffected by the main droplet size. Under the same continuous phase flow rate of regulating channel, the higher continuous phase flow rate of the main channel would lead to lower sieving efficiency.

A computational analysis of transcribed speech of people living with dementia: The Anchise 2022 Corpus

IntroductionAutomatic linguistic analysis can provide cost-effective, valuable clues to the diagnosis of cognitive difficulties and to therapeutic practice, and hence impact positively on wellbeing. In this work, we analyzed transcribed conversations between elderly individuals living with dementia and healthcare professionals. The material came from the Anchise 2022 Corpus, a large collection of transcripts of conversations in Italian recorded in naturalistic conditions. The aim of the work was to test the effectiveness of a number of automatic analyzes in finding correlations with the progression of dementia in individuals with cognitive decline as measured by the Mini-Mental State Examination (MMSE) score, which is the only psychometric-clinical information available on the participants in the conversations. Healthy controls (HC) were not considered in this study, nor does the corpus itself include HCs. The main innovation and strength of the work consists in the high ecological validity of the language analyzed (most of the literature to date concerns controlled language experiments); in the use of Italian (there is little corpora for Italian); in the size of the analyzed data (more than 200 conversations were considered); in the adoption of a wide range of NLP methods, that span from traditional morphosyntactic investigation to deep linguistic models for conducting analyzes such as through perplexity, sentiment (polarity) and emotions. MethodsAnalyzing real-world interactions not designed with computational analysis in mind, such as is the case of the Anchise Corpus, is particularly challenging. To achieve the research goals, a wide variety of tools were employed. These included traditional morphosyntactic analysis based on digital linguistic biomarkers (DLBs), transformer-based language models, sentiment and emotion analysis, and perplexity metrics. Analyzes were conducted both on the continuous range of MMSE values and on the severe/moderate/mild categorization suggested by AIFA (Italian Medicines Agency) guidelines, based on MMSE threshold values. Results and discussionCorrelations between MMSE and individual DLBs were weak, up to 0.19 for positive, and -0.21 for negative correlation values. Nevertheless, some correlations were statistically significant and consistent with the literature, suggesting that people with a greater degree of impairment tend to show a reduced vocabulary, to have anomia, to adopt a more informal linguist register, and to display a simplified use of verbs, with a decrease in the use of participles, gerunds, subjunctive moods, modal verbs, as well as a flattening in the use of the tenses towards the present to the detriment of the past. The -0.26 inverse correlation between perplexity and MMSE suggests that perplexity captures slightly more specific linguistic information, which can complement the MMSE scores. In the categorization tasks, the classifier based on DLBs achieved an F1 score of 0.79 for binary classification between SEVERE and MILD, and 0.61 for multi-label categorization. Sentiment and emotion analyzes showed inverse trends for joy while MMSE scores suggested that less impaired individuals were less joyful, or more “negative”, than others. Considering the real-world context, this is consistent with the hypothesis of a gradual reduction in awareness in individuals affected by dementia. Finally, integrating various profiles of analysis has been proved to be effective in offering a wider picture of linguistic and communication deficits, as well as more precise data regarding the progression of dementia.

Output Characteristics of External-Cavity Mode-Hop-Free Tunable Laser Source in C+L Band

Tunable laser sources with a wide wavelength tuning range, mode-hop-free (MHF) operation, and high spectral purity are essential for applications such as high-resolution spectroscopy, coherent detection, and intelligent fiber sensing. In this paper, we present a wide-range tunable laser source that operates without mode hopping, based on external cavity feedback using a semiconductor gain chip as the laser gain medium. The wavelength, power, and spectral characteristics of the laser are experimentally measured. A wide MHF continuous wavelength tuning range from 1480 nm to 1620 nm with a side-mode suppression ratio of more than 61.65 dB is achieved. An output optical power of more than 11.14 dBm with good power stability can also be realized in the full C+L band. This proposed external-cavity tunable laser source features a narrow intrinsic linewidth and MHF tunable radiation with a maximum sweep speed of 200 nm/s, enabling practical applications such as high-resolution vector spectrum analysis.

Interactive Design of Stylized Walking Gaits for Robotic Characters

Procedural animation has seen widespread use in the design of expressive walking gaits for virtual characters. While similar tools could breathe life into robotic characters, existing techniques are largely unaware of the kinematic and dynamic constraints imposed by physical robots. In this paper, we propose a system for the artist-directed authoring of stylized bipedal walking gaits, tailored for execution on robotic characters. The artist interfaces with an interactive editing tool that generates the desired character motion in realtime, either on the physical or simulated robot, using a model-based control stack. Each walking style is encoded as a set of sample parameters which are translated into whole-body reference trajectories using the proposed procedural animation technique. In order to generalize the stylized gait over a continuous range of input velocities, we employ a phase-space blending strategy that interpolates a set of example walk cycles authored by the animator while preserving contact constraints. To demonstrate the utility of our approach, we animate gaits for a custom, free-walking robotic character, and show, with two additional in-simulation examples, how our procedural animation technique generalizes to bipeds with different degrees of freedom, proportions, and mass distributions.

Can We Still Find an Ideal Memristor?

In 1971, Chua defined an ideal memristor that links magnetic flux φ and electric charge q. In a magnetic lump with a current-carrying conductor, we found that the direct interaction between physical magnetic flux φ and physical electric charge q is memristive by nature in terms of a time-invariant φ-q curve being nonlinear, continuously differentiable and strictly monotonically increasing. Although we succeeded in demonstrating that the “ideal/real/perfect/… memristor” needs magnetism, the structure still suffers from two serious limitations: 1. a parasitic “inductor” effect and 2. bistability and dynamic sweep of a continuous resistance range. Then, we discussed how to overcome these two limitations to make a fully functioning ideal memristor with multiple or an infinite number of stable states and no parasitic inductance. We then gave a number of innovations to the current memristor structure, such as an “open” structure, nanoscale size, magnetic materials with cubic anisotropy (or even isotropy) and sequential switching of the magnetic domains. Contrary to the conjecture that “an ideal memristor may not exist or may be a purely mathematical concept”, we remain optimistic that an ideal memristor will be discovered in nature or will be made in the laboratory. Our finding of the memristive flux–charge interaction may advance the development and application of the memristor technology.

Brief intervention protocol by telephone delivered by nurses to patients with harmful alcohol use in primary health care: A feasibility trial

AimThe aim of this study is to examine the feasibility of a brief intervention protocol by telephone performed by nurses in primary health care facilities. MethodsA nonrandomized single-arm feasibility study was performed. The proposed intervention of this study is the Brief Intervention carried out by the nurse delivered by telephone, synchronously with alcohol users. The brief intervention is a motivational approach based on the FRAMES model, with its components being: Feedback, Responsibility, Advice, Menu of options, Empathy and Self-efficacy. To assess the feasibility of the protocol, we evaluated the procedure for enrolling participants, the acceptability of the protocol to participants, the satisfaction of the participants, convenience and treatment continuity. The quantitative data analysis was carried out in the R software, using descriptive statistics, categorical variables were reported by frequencies and percentages. For continuous variables, medians, means, standard deviations and range values were computed. ResultsWe followed the participants (n = 165) from baseline (T0) until 3 months (T1) and 6 months (T2) after the brief intervention. The partial effect suggests a reduction in alcohol consumption, and statistically significant differences were observed from baseline before the BI, with a decrease of 0.66 points in AUDIT scores at T1. Among the patients who completed the 3-month follow-up, 48 % reported a positive experience of receiving the brief intervention by the nurses, and 44 % reported a decrease in alcohol consumption. ConclusionsBrief intervention delivered by telephone was considered feasible and acceptable by primary health care patients, and they perceived improvement in their alcohol consumption after receiving the BI performed by nurses.

A Process Algebraic Approach to Predict and Control Uncertainty in Smart IoT Systems for Smart Cities Based on Permissible Probabilistic Equivalence.

Process algebra is one of the most suitable formal methods to model smart IoT systems for smart cities. Each IoT in the systems can be modeled as a process in algebra. In addition, the nondeterministic behavior of the systems can be predicted by defining probabilities on the choice operations in some algebra, such as PALOMA and PACSR. However, there are no practical mechanisms in algebra either to measure or control uncertainty caused by the nondeterministic behavior in terms of satisfiability of the system requirements. In our previous research, to overcome the limitation, a new process algebra called dTP-Calculus was presented to verify probabilistically the safety and security requirements of smart IoT systems: the nondeterministic behavior of the systems was defined and controlled by the static and dynamic probabilities. However, the approach required a strong assumption to handle the unsatisfied probabilistic requirements: enforcing an optimally arbitrary level of high-performance probability from the continuous range of the probability domain. In the paper, the assumption from the previous research is eliminated by defining the levels of probability from the discrete domain based on the notion of Permissible Process and System Equivalences so that satisfiability is incrementally enforced by both Permissible Process Enhancement in the process level and Permissible System Enhancement in the system level. In this way, the unsatisfied probabilistic requirements can be incrementally enforced with better-performing probabilities in the discrete steps until the final decision for satisfiability can be made. The SAVE tool suite has been developed on the ADOxx meta-modeling platform to demonstrate the effectiveness of the approach with a smart EMS (emergency medical service) system example, which is one of the most practical examples for smart cities. SAVE showed that the approach is very applicable to specify, analyze, verify, and especially, predict and control uncertainty or risks caused by the nondeterministic behavior of smart IoT systems. The approach based on dTP-Calculus and SAVE may be considered one of the most suitable formal methods and tools to model smart IoT systems for smart cities.

The effect of foot orientation modifications on knee joint biomechanics during daily activities in people with and without knee osteoarthritis

BackgroundAltered gait could influence knee joint moment magnitudes and cumulative damage over time. Gait modifications have been shown to reduce knee loading in people with knee osteoarthritis during walking, although this has not been explored in multiple daily activities. Therefore, this study investigated the effect of different foot orientations on knee loading during multiple daily activities in people with and without knee osteoarthritis. MethodsThirty people with knee osteoarthritis and twenty-nine without (control) performed walking, stair ambulation and sit-to-stand across a range of foot progression angles (neutral, toe-in, toe-out and preferred). Peak knee adduction moment, knee adduction moment impulse and knee pain were compared across a continuous range of foot orientations, between activities, and groups. FindingsIncreased foot progression angle (more toe-in) reduced 1st peak knee adduction moment across all activities in both knee osteoarthritis and control (P < 0.001). There was a greater reduction in knee adduction moment in the control group during walking and stair ambulation (P ≤ 0.006), where the knee osteoarthritis group already walked preferably less toe-out than the control group. Under preferred condition, stair descent had the greatest knee loading and knee pain compared to other activities. InterpretationAlthough increased foot progression angle (toward toe-in) appeared to be more effective in reducing knee loading for all activities, toe-in modification might not benefit stair ambulation. Future gait modification should likely be personalised to each patient considering the individual difference in preferred gait and knee alignment required to shift the loading medially or laterally.

Evolutionary stages of active to vegetated coastal transgressive dunefields in the San Matías Gulf coast, Argentina

The understanding of how active aeolian coastal dunes transform into fully vegetated forms, and the specific dune configurations that emerge, particularly within coastal dune systems, is limited. This study examines the changes in dune morphology associated with vegetation growth within transgressive dunefields in NE Patagonia, Argentina. The dunefields are located along the northern coast of the San Matías Gulf, ranging from relatively small to large, and dominantly active in the past ∼80 years. Satellite and aerial images were analyzed using GIS procedures to calculate vegetation cover changes and dune migration rates and identify different dune types and their evolutionary stages of fixation. Five stages were defined in relation to vegetation cover and dune shapes and patterns, from bare sand to fully vegetated dunes. Transverse or barchanoid ridges (sometimes with aklé [fish scale], or chaotic patterns) convert to partially vegetated sub-parabolic dunes and finish as parabolic dunes. In other cases, the dunes may convert to reticulate, aklé, or chaotic patterns, completely vegetated. Various stages span a continuous range from unvegetated to fully vegetated dunes across a wide array of timeframes. In some cases, it was possible to recognize changes from stage one to five in ∼20 years. Where the initial transverse dune is largely maintained during the stabilization process a distinctive pattern named “gusanos” (worms) was identified. The vegetated surface measured in some areas changed from 11 % to 51 % vegetation cover between 1961 and 2022, with migration rates decreasing from 9.53 m/year to zero between 1991 and 2020. The increase in vegetation growth also coincides with higher temperatures, weaker winds and decreasing grazing livestock within this Patagonia area. The recorded processes are similar to coastal dune and vegetation changes in some semiarid regions from the Southern Hemisphere between 30 and 60° S, especially in South Australia.

A comprehensive research on γ-ray and particle radiation interaction parameters of Cerium doped heavy oxide inorganic scintillators

In this study, the interaction cross sections of heavy oxide scintillators, which have a very important place in high energy physics research, with photon and particle radiation were comparatively investigated. In this context, the interaction parameters of six different Ce-doped heavy oxide scintillators were obtained using updated software. The interactions of photons with energies between 1 keV and 100 GeV with scintillators were evaluated in the light of the results produced by the Phy-X/PSD software. In addition to the continuous energy range, calculations were also made on the photon energies emitted with the highest probability of emission from sources 241Am (59.54 keV), 133Ba (356 keV), 22Na (511 and 1280 keV), 137Cs (662 keV) and 152Eu (1460 keV). Additionally, evaluations of energy absorption build-up factors valid under broad beam conditions are also included in this study. Fast neutron absorption cross sections and changes in the range (R) values for heavy particle radiation in the range of 1 keV–20 MeV were also determined with SRIM and ESTAR software. All data obtained depending on energy are explained according to the mass percentages of Lu, Gd, Hf, Y, Al and O elements in the scintillators. The highest interaction cross section for photons was obtained in the Lu2Gd2SiO5 (Ce 0.3%) scintillator (HOS2). The interaction cross section of this scintillator was obtained as 3.115 and 0.042 cm2/g at 0.1 MeV and 10 MeV photon energies, respectively. On the other hand, the highest cross-sections of the fast neutrons were observed in the scintillator (HOS5) containing GdAlO3 (Ce 1.0%) as 0.148 cm−1. This difference in neutron radiation has been explained by calculating the individual attenuation abilities of the elements in the structures. It is hoped that the data obtained will guide researchers working on the detection of different types of radiation.

Python Programming for Degree Heating Weeks Estimation using Sea Surface Temperature Data from The Google Earth Engine Dataset as Coral Bleaching Analysis Tools

Abstract This study aims to develop a program to calculate Degree Heating Weeks (DHW) using Python programming and Sea Surface Temperature (SST) data available in Google Earth Engine (GEE) datasets, e.g., HyCom, NOAA OISST v2.1, MODIS-Aqua, and NOAA Pathfinder v5.3. This study contributes to providing a DHW calculator currently unavailable on the Internet to analyze coral bleaching. This program is called PyDHW. The DHW was calculated by inputting the desired location in a polygon, a specific time range, and the SST data. The results show that Python code can extract SST from the GEE dataset according to the user’s input. This SST data is the average of the SST inside the polygon area. This program calculates and shows a graph of the DHW showing coral bleaching alert levels. All these processes were performed quickly in one run. HyCom and NOAA OISST v2.1 have a long and continuous data range. NOAA OISST v2.1 is still updated in the GEE dataset rather than the others. The MODIS-Aqua contains blank time-series data for several measurements. The NOAA Pathfinder v5.3 data shows extreme change in time series data and low temperatures with different patterns from the other SST data. However, this program is still under development and needs improvements. This program is expected to help users concerned with coral research and monitoring.

The Role of Core Sample Geometry on Countercurrent Spontaneous Imbibition: Mathematical Foundation, Examples, and Experiments Accounting for Realistic Geometries

Summary Countercurrent spontaneous imbibition (SI) experiments are among the most common multiphase experiments performed on porous rock samples. Although the samples rarely are designed to give linear flow, they are often modeled and interpreted using mathematical descriptions assuming linear flow. In this work, the goal is to derive general understanding of how imbibition into different sample geometries behaves compared with linear (1D) imbibition. Using the mathematical theory of N-volume spheres (N being the dimension), we consider core samples as N-spherical and quantify their geometry by a dimension N and length scale L. For the special cases, N=1,2,3, we obtain linear, radial, and spherical flow; however, we treat the dimension as an arbitrary real number for cases not adhering to either of these regimes. Particularly, for rectangular or cylindrical core plugs, a continuous range of dimensions is produced. Theoretical calculations of N and L of arbitrary sample shapes are derived based on relations with area per volume and derivative of area with respect to volume. They correctly produce limit cases and physically meaningful values for symmetrical, cylindrical, and rectangular geometries. The differential equation for countercurrent imbibition in N-dimensions is derived and solved with numerical examples. Also, a simplified analytical solution assuming piston-like displacement is derived to get illustrative relations between system parameters (including dimension) and recovery and front position. Predicted recovery profiles of the N-dimensional (N-D) solution overlap consistently with numerical simulations (by an alternative simulator) into cylindrical geometries with a wide range of height/diameter ratios and viscosity ratios. At early time, the saturation profiles are self-similar (look the same plotted against position divided by square root of time) and identical regardless of dimension. As long as the profiles are self-similar near the open boundary, recovery is proportional to the square root of time. For N=1, this lasts long after the front has reached the closed boundary, while for N &amp;gt;1, it can happen long before the boundary has been reached. The same time scale was applicable for all geometries, stating especially that doubling the length scale increased the time of the entire recovery profile by a factor 4. As long as recovery is proportional to square root of time, at a given time, it is also proportional to dimension over length, NL, and the time needed to reach same level of recovery is proportional to LN2. Permeability anisotropy (lower vertical than horizontal permeability) could effectively be modeled using an effective increased height, which further was captured by the dimension and length scale. Literature and in-house experimental data were matched by the model and used to validate model predictions such as the variation in time, shape of recovery curves with changes in dimension, and the importance of accounting for the dimension (geometry) during data interpretation. The model is valid for all wetting states but assumes negligible gravity and compressibility effects.

Mechanism of formation and evolution of bound states in the continuum of split-hole all-dielectric metasurface under asymmetric displacement perturbation

Bound states in the continuum (BICs) with ultra-high Q properties have attracted much attention for their perfect localization in the continuous spectral range coexisting with extended waves. In this study, breaking the traditional excitation form of structure breakage or excitation field asymmetry, a monolithic silicon nanodisk array with relative displacement generated by the complete splitting of square nanopores is proposed based on the unique electromagnetic properties of all-dielectric metamaterials. During the introduction of perturbations by asymmetric displacements of splitting holes, it is shown by numerical simulations that two BICs at different wavelengths can be realized. Combined with eigenmodes of group theory, the symmetric matching relationship between the symmetry-protected BICs and the free-space radiation during the evolution process is analytically demonstrated, and the formation mechanism and the evolution law of the BICs excited by this metasurface are deeply investigated. meanwhile, it also provides a theoretical basis for the polarization dependence of quasi-BICs excitation and the ultra-high Q factor expression of BICs. Furthermore, near-field distribution and multipole decomposition show that the field distribution and surface currents support the excitation of BIC-driven toroidal dipole and magnetic quadrupole dual modes. This study not only provides an effective reference for the stability of high-Q resonance wavelengths, but also solves the problem of the lack of universality in analyzing the resonance mechanism based on resonance phenomena, and provides solid theoretical support for the study of displacement-mediated BICs resonance excitation and evolution.

3D printing of ferromagnetic passive shims for field shaping in magnetic resonance imaging

Magnetic Resonance Imaging (MRI) often encounters image quality degradation due to magnetic field inhomogeneities. Conventional passive shimming techniques involve the manual placement of discrete magnetic materials, imposing limitations on correcting complex inhomogeneities. To overcome this, we propose a novel 3D printing method utilizing binder jetting technology to enable precise deposition of a continuous range of concentrations of ferromagnetic ink. This approach grants complete control of the magnitude of the magnetic moment within the passive shim enabling tailored corrections of B0 field inhomogeneities. By optimizing the magnetic field distribution using linear programming and an in-house written Computer-Aided Design (CAD) generation software, we printed shims with promising results in generating low spherical harmonic corrections. Experimental evaluations demonstrate feasibility of these 3D printed passive shims to induce target magnetic fields corresponding to second-order spherical harmonic, as evidenced by acquired B0 maps. The electrically insulating properties of the printed shims eliminate the risk of eddy currents and heating, thus ensuring safety. The dimensional fabrication accuracy of the printed shims surpasses previous methods, enabling more precise and localized correction of subject-specific inhomogeneities. The findings highlight the potential of binder-jetted 3D printed passive shims in MRI shimming as a versatile and efficient solution for fabricating passive shims, with the potential to enhance the quality of MRI imaging while also being applicable to other types of Magnetic Resonance systems.

Efficient Modeling of Water Adsorption in MOFs Using Interpolated Transition Matrix Monte Carlo.

With the specter of accelerating climate change, securing access to potable water has become a critical global challenge. Atmospheric water harvesting (AWH) through metal-organic frameworks (MOFs) emerges as one of the promising solutions. The standard numerical methods applied for rapid and efficient screening for optimal sorbents face significant limitations in the case of water adsorption (slow convergence and inability to overcome high energy barriers). To address these challenges, we employed grand canonical transition matrix Monte Carlo (GC-TMMC) methodology and proposed an efficient interpolation scheme that significantly reduces the number of required simulations while maintaining accuracy of the results. Through the example of water adsorption in three MOFs: MOF-303, MOF-LA2-1, and NU-1000, we show that the extrapolation of the free energy landscape allows for prediction of the adsorption properties over a continuous range of pressure and temperature. This innovative and versatile method provides rich thermodynamic information, enabling rapid, large-scale computational screening of sorbents for adsorption, applicable for a variety of sorbents and gases. As the presented methodology holds strong applicative potential, we provide alongside this paper a modified version of the RASPA2 code with a ghost swap move implementation and a Python library designed to minimize the user's input for analyzing data derived from the TMMC simulations.

Direct Power Flow Controller With Continuous Full Regulation Range

Direct Power Flow Controller With Continuous Full Regulation Range

A Reconfigurable Soft Linkage Robot via Internal "Virtual" Joints.

Traditional robots derive their capabilities of movement through rigid structural "links" and discrete actuated "joints." Alternatively, soft robots are composed of flexible materials that permit movement across a continuous range of their body and appendages and thus are not restricted in where they can bend. While trade-offs between material choices may restrain robot functionalities within a narrow spectrum, we argue that bridging the functional gaps between soft and hard robots can be achieved from a hybrid design approach that utilizes both the reconfigurability and the controllability of traditional soft and hard robot paradigms. In this study, we present a hybrid robot with soft inflated "linkages," and rigid internal joints that can be spatially reconfigured. Our method is based on the geometric pinching of an inflatable beam to form mechanical pinch-joints connecting the inflated robot linkages. Such joints are activated and controlled via internal motorized modules that can be relocated for on-demand joint-linkage configurations. We demonstrate two applications that utilize joint reconfigurations: a deployable robot manipulator and a terrestrial crawling robot with tunable gaits.

Liquid Crystal Metasurface for On‐Demand Terahertz Beam Forming Over 110° Field‐Of‐View

AbstractThe terahertz spectral region, which bridges between electronics and optics, is poised to play an important role in the development of transformative wireless communication and imaging systems with unprecedented functionality. Currently, a major challenge in terahertz technology is to develop high‐performance terahertz beam‐forming devices that can dynamically shape the terahertz radiation in a flexible manner. Existing terahertz beam‐forming devices have limited coding bits, field‐of‐view, and beam gain. Here, a reconfigurable liquid crystal‐integrated terahertz metasurface is experimentally demonstrated, with each metasurface unit cell being independently addressable. The metasurface has a 260° continuous phase tuning range with a liquid crystal layer thickness of only 1% of the free‐space wavelength. The terahertz wave diffracted from the metasurface can be steered toward a wide range of directions is shown, covering a record‐large 110° field‐of‐view with a peak gain of 25 dBi. The metasurface also features a low power consumption and sub‐second switching time. Furthermore, the formation of multiple terahertz beams is demonstrated, with the direction of each beam and the power ratio between beams adjustable on demand. The proposed liquid crystal metasurface possesses compelling prospects for future terahertz communication and imaging applications.