Approach Angle Research Articles

Development and validation of an automatic recording microcontroller-based pendulum impact cutter

Knowledge of rice straw bunch in respect of cutting energy is the important factor for optimization of cutting elements in straw chopping system. A micro controller-based pendulum impact cutter was developed during 2019–21 at the ICAR-Central Institute of Agricultural Engineering, Bhopal, Madhya Pradesh. The system was integrated with load cell, adjustable pendulum arm and adjustable shear and approach angle (0–30 degree) during the cutting experiment. In this study, straw bunch cutting energy at the lowest point of Node 3 was examined which is just above the ground surface. Three type of blades SMS serrated, cutter bar and SMS plain blade were used to determine cutting energy. In order to determine the cutting energy requirement of straw bunch, the mechanical and physical properties of straw were determined. The results represent that the cutting force was significantly affected by blade type, shear angle and approach angle. The minimum cutting energy for SMS serrated, cutter bar and SMS plain blade was registered as 120, 189 and 243 J, respectively among all combinations of shear and approach angle. Developed recording type pendulum impact cutter was compared with the traditional method at selected combination of shear and approach angle for all the three blades and the relative error was recorded between 4–6%. It was concluded that with increasing approach angle at constant shear angle the cutting force initially decreased up to 20 degree and rapid increase from 20 to 30 degree of approach angle. Consequently, the SMS serrated blade emerges as the preferred choice for the rotary impact cutter development, showcasing the potential of this research in advancing straw chopping technology.

Overtaking collision avoidance for small autonomous uncrewed aircraft using geometric keep-out zones

Autonomous uncrewed aircraft will require collision avoidance systems (CASs) designed with autonomy in mind as they integrate into the increasingly crowded national airspace system. Current uncrewed aircraft CASs typically require a remote pilot to execute avoidance or to provide poorly defined guidance that does not benefit autonomous systems. The Path Recovery Automated Collision Avoidance System (PRACAS) re-plans flight paths to autonomously adjust for collisions using path planners and keep-out zones (KOZs), but it does not currently detect or mitigate overtaking collisions. This work investigates the effect of geometric KOZs on overtaking scenarios for autonomous uncrewed aircraft. KOZ shapes were developed by relating relative velocities and turn rates of aircraft in overtaking scenarios and were tested using PRACAS. The operational ranges for approach heading, relative velocity, and look-ahead time were then determined. The set of KOZs that were developed prevented intruder aircraft from entering the minimum separation distance of one wingspan from the mission aircraft in overtaking scenarios with look-ahead times between 5 and 12 s, relative velocities of 2–20, and approach angles between 110° and −110° measured from the heading of the main UAS. Minimum separation was maintained for low-speed encounters with relative velocities between 1.1 and 2.0 for look-ahead times between 2 and 8 s for all approach angles. With look-ahead times ranging from 5 to 8 s, overtaking collisions of all tested approach angles and relative speeds are handled with more than twice the separation required for success, showing that the KOZs developed are feasible in possible autonomous CASs.

Comparability of Outputs between Traditional and Simulation-Based Approaches to Collision Risk Modelling

Tidal stream energy is a predictable renewable energy source; however, environmental consent of developments remains a key barrier to the expansion of this industry. Uncertainty around collision risk, i.e., the risk of animals colliding with a tidal device, remains a major barrier to consent. Collision risk models are used in environmental impact assessments. Common collision risk models, like the Encounter Rate and Band Models, have limitations in accommodating new device designs and flexibility. To address this, a simulation-based approach was developed. To provide confidence in its use, it is important that the simulation-based approach is compared against the Band model and the Encounter rate model, which have been regularly used in the UK. Here, we compared collision risk estimates from the three models under the same exact conditions and one alternative condition. The results of the main scenario (where all conditions were the same) showed that the three models produced comparable results with <6% difference across all models. However, for the alternative scenario, the simulation-based approach produced a result three times higher compared to other models, which could not account for a vertical approach angle. These findings provide confidence in the simulation-based approach whilst also outlining the importance of selecting an appropriate collision risk model, tailored to the specific assessment scenario. Improved understanding and application of such models hold the key to more accurate risk evaluations in environmental impact assessments, thus facilitating the sustainable development of the tidal energy industry.

Optimizing aerogravity-assisted maneuvers at high atmospheric altitude above Venus, Earth, and Mars to control heliocentric orbits

This paper analyzes the change in the heliocentric orbital elements due to the implementation of aerogravity and powered aerogravity assist maneuvers. Three cost functions were selected to maximize the planetocentric latitude, longitude, and velocity at the end of the atmospheric flight. An optimal control problem was solved to guide a spaceplane passing above the three inner planets: Venus, Earth, and Mars. The planets were selected because they have been relevant for gravity assists, and previous studies suggest that taking advantage of their atmospheres could increase the effects of the close approach. The research aims to analyze the variation in the heliocentric orbital elements of the trajectories after performing optimal aerogravity-assists and powered aerogravity-assisted maneuvers at high atmospheric altitudes. The trajectories were calculated via nonlinear programming to find the history of the control variables: angle of attack, bank angle, and thrust. Low-fidelity gravity and atmosphere models were implemented to evaluate this proof of concept. The optimization converged for all cases, and results show that maximization of the longitude increases the duration of the atmospheric flight, increasing the turning angle by almost twice the value of a single gravity assist. Furthermore, it reduces the energy and semimajor axis in half for approach angles between 20 and 90°, saving more than 10 km/s on propulsion. Maximizing the velocity with propulsion increases the semimajor axis by more than 1.1 times the semimajor axis of the respective planet, and the optimal latitude presents a change in inclination of more than 1.0°. This maneuver could be applied to collect atmospheric samples or increase the coverage above the planet of interest. Those kinds of applications are described at the end of this paper, including a brief discussion on the maturity of this technology.

Difficulty of Identification of Official Tactile Walking Surface Indicators Using the Foot in Japan

In Japan, following an accident wherein a visually impaired was hit by a train inside a railroad crossing, the installation of tactile walking surface indicators (TWSIs) at railroad crossings have become widespread. Attention and guiding patterns as well as escort patterns have been installed in front and inside railroad crossings, respectively. However, the extent to which the latter is more discriminable than the former has not been verified. This study determined the ease of identifying the Japanese official TWSIs and both patterns using the soles of the feet. Twenty blindfolded participants used TWSIs, scanned the raised surfaces with their soles, and responded to the type of TWSIs using three-alternative forced-choice. Compared with attention and guiding, escort patterns were misidentified with subjective sureness and long identification times. In about 90% of times that attention and guiding patterns were incorrectly identified, they were misidentified as escort patterns. The escort patterns were misidentified as attention patterns in about 70% of the times in which they were misidentified. Trials with misidentification had significantly longer identification times and lower sureness (but moderate sureness) than trials with correct identification. Approach angles to TWSIs had practically no effect on the identification. When escort patterns are installed inside the railroad crossings and attention and guiding patterns are installed outside, the visually impaired may misidentify them and accidentally enter or stay at the railroad crossing. Therefore, new installation methods to effectively identify all TWSIs, especially escort patterns, or develop new TWSIs with superior ease of identification should be verified.

A new surge index with the incorporation of cyclone track approach angle information for the Bay of Bengal

A novel tropical cyclone surge potential index (TCSPI) for estimating tropical cyclone (TC) induced potential peak surge levels near the landfall locations for the entire coast of the Bay of Bengal (BoB) is presented. The proposed TCSPI incorporates parameters that are often readily available in real-time for BoB: maximum sustained wind speed (Vmax), the radius of given wind (R), translation speed (S), approach angle (θ), coastal geometry (a, b), and bathymetry information (L30). The inclusion of approach angle and associated coastal geometry information led to improvements of the TCSPI to other existing surge indices. A retrospective analysis of TCSPI using the Indian Meteorological Department (IMD) and Joint Typhoon Warning Center (JTWC) tropical cyclone (TC) best track data from 1990 to 2021 for BoB suggests that the index captures historical events reasonably well. In particular, it explains up to ∼90% of observed surge variance and up to ∼92% of those peak surge values obtained from physics-based numerical simulation using the Advanced Circulation (ADCIRC) model. Further, we utilized renowned regression-based supervised machine learning (ML) models on small data samples. The Linear Regression (LR), Regression Tree (TR), Support Vector Machine (SVM), Ensembles of Trees (EnTR), and Gaussian Process Regression (GPR) models are incorporated that can rapidly predict peak surge height across an extensive coastal region of BoB, using the same input parameter information (i.e., Vmax, R, S,L30, and θ) that have been considered in the TCSPI at the landfall time frame. Finally, the observed peak surge values associated with historical TC events in the BoB are compared with those estimated by TCSPI, ADCIRC, and ML models. The errors associated with TCSPI are comparatively less. The consideration of approach angle information in the TCSPI has improved the accuracy of the overall prediction of peak surge height associated with historical TCs by up to 17% and 19% for observed and ADCIRC-simulated peak surges, respectively. The development of such a prediction methodology can reduce the numerical computation requirements to improve the surge hazard maps, and hence, proper implementation based on surge risk is possible.

Angles of Needle Insertion for True Vocal Fold Access Via the Thyrohyoid and Cricothyroid Membranes of the Larynx

This study aims to provide an analysis of the cricothyroid and thyrohyoid membrane approaches for laryngeal injections in cadaveric vocal cords. The primary objective is to determine the optimal techniques, needle trajectories, and anatomical landmarks for accessing different regions of the vocal cords percutaneously. The study was conducted on 23 adult cadavers, consisting of 8 females and 15 males. The cadaveric larynges were mounted vertically to ensure proper anatomical positioning. Both the cricothyroid and thyrohyoid membrane approaches were utilized for reaching the vocal cords. Measurements were taken for needle trajectories, angles, and distances to determine the optimal approach for accessing the anterior, middle, and posterior thirds of the vocal cord. Through the thyrohyoid membrane approach, the anterior, middle, and posterior thirds of the vocal cords can be accessed with the optimal needle insertion coronal angles of 15.46±7.86°, 16.52±7.15° and 18.29±14.46°, and sagittal angles of 126.01±9.65°, 116.67±8.04° and 111.02±8.86° respectively at a lateral distance of 1.92±1.62mm from the midline and 8.48±2.73mm below the vertical line. From the cricothyroid membrane approach, optimal coronal and sagittal insertion angles of the anterior, middle, and posterior thirds of the vocal cord were respectively: 158.95±9.3°, 156.09±11.59°, 152.4±14.46°, 11.5±7.77°, 21.83±12.47° and 32.91±12.59°. This analysis of the cricothyroid and thyrohyoid membrane approaches in cadaveric larynges provides valuable insights for clinicians and researchers in the field of laryngology. The findings serve as a reference for optimizing laryngeal injection techniques, enhancing patient outcomes, and minimizing complications.

Analytical study of optical dielectric interfaces for sensing applications

Dynamic optical sensors, as those based on the reflectivity of isotropic dielectrical interfaces, can be useful for measuring small changes in the refractive index of fluid media. Exact and approximated explicit formulas for their sensitivity are developed. These expressions clarify the influence of each of the constructive parameters of the device, both in partial and in total reflection. It is analytically found that sensitivities are always greater when the angle of incidence approaches the angle of total reflection. It is also demonstrated that close to the critical angle for both types of reflection, the sensitivity of the p mode is greater than that of the s mode.

Visualization and characterization of experimental hydraulic fractures interacting with karst fracture-cavity distributions

Karst fracture-cavity carbonate reservoirs, in which natural cavities are connected by natural fractures to form cavity clusters in many circumstances, have become significant fields of oil and gas exploration and exploitation. Proppant fracturing is considered as the best method for exploiting carbonate reservoirs; however, previous studies primarily focused on the effects of individual types of geological formations, such as natural fractures or cavities, on fracture propagation. In this study, true-triaxial physical simulation experiments were systematically performed under four types of stress difference conditions after the accurate prefabrication of four types of different fracture-cavity distributions in artificial samples. Subsequently, the interaction mechanism between the hydraulic fractures and fracture-cavity structures was systematically analyzed in combination with the stress distribution, cross-sectional morphology of the main propagation path, and three-dimensional visualization of the overall fracture network. It was found that the propagation of hydraulic fractures near the cavity was inhibited by the stress concentration surrounding the cavity. In contrast, a natural fracture with a smaller approach angle (0° and 30°) around the cavity can alleviate the stress concentration and significantly facilitate the connection with the cavity. In addition, the hydraulic fracture crossed the natural fracture at the 45° approach angle and bypassed the cavity under higher stress difference conditions. A new stimulation effectiveness evaluation index was established based on the stimulated reservoir area (SRA), tortuosity of the hydraulic fractures (T), and connectivity index (CI) of the cavities. These findings provide new insights into the fracturing design of carbonate reservoirs.

Inadequate structural constraint on Fab approach rather than paratope elicitation limits HIV-1 MPER vaccine utility

Broadly neutralizing antibodies (bnAbs) against HIV-1 target conserved envelope (Env) epitopes to block viral replication. Here, using structural analyses, we provide evidence to explain why a vaccine targeting the membrane-proximal external region (MPER) of HIV-1 elicits antibodies with human bnAb-like paratopes paradoxically unable to bind HIV-1. Unlike in natural infection, vaccination with MPER/liposomes lacks a necessary structure-based constraint to select for antibodies with an adequate approach angle. Consequently, the resulting Abs cannot physically access the MPER crawlspace on the virion surface. By studying naturally arising Abs, we further reveal that flexibility of the human IgG3 hinge mitigates the epitope inaccessibility and additionally facilitates Env spike protein crosslinking. Our results suggest that generation of IgG3 subtype class-switched B cells is a strategy for anti-MPER bnAb induction. Moreover, the findings illustrate the need to incorporate topological features of the target epitope in immunogen design.

Proposing a method to model ship collision risk in maritime transpport based on fuzzy logic considering the influence of ship approach angle

Modeling and assessing the collision risk of ships in complex and crowded water areas plays an important role in improving marine traffic monitoring and management to enhance the safety of maritime transport. To model the collision risk assessment of ships in an area, this paper proposes a method to model ship collision risk based on fuzzy logic considering the influence of the approach angle between two ships. The method uses a hierarchical fuzzy system consisting of two fuzzy systems, fuzzy system 1 is used to calculate temporary collision risk, and fuzzy system 2 will use the output of fuzzy system 1 combined with input which is the approach angle between two ships to calculate the final collision risk. The fuzzy systems constructed in this paper are all modeled from expert knowledge allowing any officer to reference the calculation results of experts in approach situations. The paper only proposes the method, result verification can be done by simulation which will be done in further study. This model can provide an important basis for monitoring and assessing maritime collision risk and maritime risk assessment of ships for maritime administrations.

Grasping Pose Estimation for Robots Based on Convolutional Neural Networks

Robots gradually have the ability to plan grasping actions in unknown scenes by learning the manipulation of typical scenes. The grasping pose estimation method, as a kind of end-to-end method, has rapidly developed in recent years because of its good generalization. In this paper, we present a grasping pose estimation method for robots based on convolutional neural networks. In this method, a convolutional neural network model was employed, which can output the grasping success rate, approach angle, and gripper opening width for the input voxel. The grasping dataset was produced, and the model was trained in the physical simulator. A position optimization of the robotic grasping was proposed according to the distribution of the object centroid to improve the grasping success rate. An experimental platform for robot grasping was established, and 11 common everyday objects were selected for the experiments. Grasping experiments involving the eleven objects individually, multiple objects, as well as a dark environment without illumination, were performed. The results show that the method has the adaptability to grasp different geometric objects, including irregular shapes, and it is not influenced by lighting conditions. The total grasping success rate was 88.2% for the individual objects and 81.1% for the cluttered scene.

Publications reveal how socio-ecological research is implemented: Lessons from the Rhône long term socio-ecological research platform

Socio-ecological research enlists inter- and transdisciplinarity to address complex environmental issues. Yet the “socio-ecological system” concept can be interpreted in many different ways. A characterization of the diverse practices in socio-ecological research could facilitate dialogue between researchers about the possible conceptual and ethical approaches. In this study, we investigated if a detailed analysis of scientific articles would reveal the nature and course of a socio-ecological research network, and the research angle of its members. The example we used was the Rhône River Long-Term Socio-Ecological Research (LTSER) platform in France. We combined a multivariate analysis of a reading grid of publications by Rhône River LTSER researchers and a textual analysis of the scientific narratives. The publications were from a 10-year period and corresponded to those used in a recent international comparative analysis of LTSER platforms. The analysis revealed that the research was dominated by a biophysical approach, with a progressive increase in social aspects. The emergence of a transdisciplinary approach, co-constructed with operational partners, was also shown. The research conducted by the Rhône River LTSER was grounded in the context of managing a river with strong anthropic influences and interests, and the scientific approach aimed to provide knowledge for guiding decisions. Little referencfte was made in the publications to socio-ecological conceptual frameworks. Beyond the example of this LTSER platform, we identified indicators for describing the degree of inter- and transdisciplinarity and the different perceptions of socio-ecological systems. The narrative analysis revealed the angle of the research approach; this method could be used in future studies for a comparison of the diverse approaches of multiple research groups.

Performance analysis of show jumping rounds at a national pony competition

Abstract Performance analysis is utilised by coaches and athletes to identify areas to work on in training and to identify strengths in athlete performance in various sports. However, performance analysis is not commonly used within equestrian sports. The purpose of this study was to evaluate minors and their ponies competing in show jumping at a national pony competition to see if course variables affected performance. All jumping rounds were watched online. Type of faults (e.g. rails, refusals, time faults, fall of horse and or rider), type of fence (e.g. vertical, oxer), approach angle, section of the course where fault(s) occurred and round time were recorded. Spearman’s Correlation assessed if round time was correlated to total faults and a series of Kruskal-Wallis analyses determined if significant differences in faults occurred between sections of the course, where these existed, post hoc tests established where differences occurred between rounds. There was no significant difference in total faults across the 4 rounds of competition and no meaningful correlation between round time and total faults (r = 0.34; ). There were no differences between fence type and faults although more faults occurred at verticals (51.7%, n = 46 faults at verticals versus 48.3%, n = 43 at oxers; ). Faults were more likely to occur during the final quarter of the course (32.6%, n = 29) when compared to the first quarter (23.6%, n = 21; ). These results showed that faults were more likely to occur in the final quarter of a round. The information gained from this performance analysis could be beneficial to inform training or riding strategies, especially when preparing for a competition.

Staircase Recognition and Localization Using Convolutional Neural Network (CNN) for Cleaning Robot Application

Floor-cleaning robots are primarily designed to clean on a single floor, while multi-floor environments are usually not considered target applications. However, it is more efficient to have an autonomous floor-cleaning robot that can climb stairs and reach the next floors in a multi-floor building. To operate in such environments, the ability of a mobile robot to autonomously traverse staircases is very important. For this operation, staircase detection and localization are essential components for planning the traversal route on staircases. This article describes a deep learning approach using a convolutional neural network (CNN)-based robot operation system (ROS) framework for staircase detection, localization, and maneuvering of the robot to the detected stair. We present a real-time object detection framework to detect staircases in incoming images. We also localize these staircases using a contour detection algorithm to detect the target point: a point close to the center of the first step, and an angle of approach to the target point with respect to the current location of the robot. Experiments are performed with data from images captured on different types of staircases at different viewpoints/angles. The experimental results show that the presented approach can achieve an accuracy of 95% and a recall of 86.81%. A total runtime of 155 ms is taken to identify the presence of a staircase and the detection of the first step in the working environment, as well as being able to locate the target point with an accuracy of ±2 cm, ±1 degree.

Analysis of factors influencing about the effects of the liquid crystal micro fluid drive

The liquid crystal microfluid drive is a fast-growing field with potential breakthroughs. In this paper, the microdrive experimental platform and the simulation platform were designed. The influence of drive parameters (electric field strength and frequency) and material parameters (stretching elastic constant, bending elastic constant and viscosity coefficient) on the microdrive effect of liquid crystal was explored. The drive parameters mainly affect the tilt angle range of dielectric molecules. When the tilt angle of the molecule approaches 90°, 4'-(Octyloxy)-4-biphenylcarbonitrile liquid crystal material has the maximum drive speed which can reach 19 µm/s. Among the three medium materials studied, the material 4'-(Octyloxy)-4-biphenylcarbonitrile with a small viscosity coefficient, small elastic coefficient and medium dielectric anisotropy coefficient has the best drive effect. The viscosity coefficient and the dielectric coefficient have a great influence on the drive performance. This research conclusion will lay a theoretical foundation for the synthesis of medium materials driven by liquid crystal microfluid.

Influence of macroscopic natural fractures group on fractures network propagation in deep shale gas reservoir

The formation of macroscopic natural fractures in deep shale reservoirs exhibits significant variability and phenomena, such as severe fracturing fluid loss during fracturing and pressure channeling between wells occur frequently and significantly impact the fracturing effect of shale gas wells. We developed a model for the propagation of fracture networks in deep shale reservoirs, taking into account the presence of macroscopic natural fractures, and studied the sensitivity factors of macroscopic natural fractures group characteristic parameters to the stimulated reservoir volume (SRV). The influence of macroscopic natural fractures group characteristic parameters on SRV was quantitatively investigated. The SRV has a positive correlation with the distance between natural fracture groups and perforation positions, as well as the intensity of the macroscopic natural fractures group. Conversely, the density and approach angle of macroscopic natural fracture groups have a negative correlation with the SRV. The degree of correlation between the natural fracture group characteristic parameters and SRV is the distance between the natural fracture group and perforation positions > density > intensity > approach angle. Performing simulation of the propagation of fracture networks in deep shale, while taking into account the impact of macroscopic natural fractures group can enhance fracturing efficiency, lower fracture-related risks.

Variation in flight characteristics associated with entry by eagles into rotor‐swept zones of wind turbines

Automated curtailment of wind turbines can reduce fatality rates of wildlife but the resulting increased number of curtailments can reduce power generation. Tailoring curtailment criteria for each individual turbine could reduce unnecessary curtailment, yet it is unknown whether the risk to wildlife varies among turbines. We demonstrate turbine‐specific variation in the speed, altitude, approach angle and distance metrics associated with entry by eagles into rotor‐swept zones. Our results thus illustrate the potential value of turbine‐specific curtailment criteria to reduce fatality rates of wildlife at wind energy facilities.

An Encodable Scaffold for Sequence-Specific Recognition of Duplex RNA.

RNA, unlike DNA, folds into a multitude of secondary and tertiary structures. This structural diversity has impeded the development of ligands that can sequence-specifically target this biomolecule. We sought to develop ligands for double-stranded RNA (dsRNA) segments, which are ubiquitous in RNA tertiary structure. The major groove of double-stranded DNA is sequence-specifically recognized by a range of dimeric helical transcription factors, including the basic leucine zippers (bZIP) and basic helix-loop-helix (bHLH) proteins; however, such simple structural motifs are not prevalent in RNA-binding proteins. We interrogated the high-resolution structures of DNA and RNA to identify requirements for a helix fork motif to occupy dsRNA major grooves akin to dsDNA. Our analysis suggested that the rigidity and angle of approach of dimeric helices in bZIP/bHLH motifs are not ideal for the binding of dsRNA major grooves. This investigation revealed that the replacement of the leucine zipper motifs in bHLH proteins with synthetic crosslinkers would allow recognition of dsRNA. We show that a model bHLH DNA-binding motif does not bind dsRNA but can be reengineered as an RNA ligand. Based on this hypothesis, we rationally designed a miniature synthetic crosslinked helix fork (CHF) as a generalizable proteomimetic scaffold for targeting dsRNA. We evaluated several CHF constructs against a set of RNA and DNA hairpins to probe the specificity of the designed construct. Our studies reveal a new class of proteomimetics as an encodable platform for sequence-specific recognition of dsRNA.

An Encodable Scaffold for Sequence‐Specific Recognition of Duplex RNA

AbstractRNA, unlike DNA, folds into a multitude of secondary and tertiary structures. This structural diversity has impeded the development of ligands that can sequence‐specifically target this biomolecule. We sought to develop ligands for double‐stranded RNA (dsRNA) segments, which are ubiquitous in RNA tertiary structure. The major groove of double‐stranded DNA is sequence‐specifically recognized by a range of dimeric helical transcription factors, including the basic leucine zippers (bZIP) and basic helix‐loop‐helix (bHLH) proteins; however, such simple structural motifs are not prevalent in RNA‐binding proteins. We interrogated the high‐resolution structures of DNA and RNA to identify requirements for a helix fork motif to occupy dsRNA major grooves akin to dsDNA. Our analysis suggested that the rigidity and angle of approach of dimeric helices in bZIP/bHLH motifs are not ideal for the binding of dsRNA major grooves. This investigation revealed that the replacement of the leucine zipper motifs in bHLH proteins with synthetic crosslinkers would allow recognition of dsRNA. We show that a model bHLH DNA‐binding motif does not bind dsRNA but can be reengineered as an RNA ligand. Based on this hypothesis, we rationally designed a miniature synthetic crosslinked helix fork (CHF) as a generalizable proteomimetic scaffold for targeting dsRNA. We evaluated several CHF constructs against a set of RNA and DNA hairpins to probe the specificity of the designed construct. Our studies reveal a new class of proteomimetics as an encodable platform for sequence‐specific recognition of dsRNA.