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This preliminary study investigated whether direct measurement of head rotation improves prediction of mild traumatic brain injury (mTBI). Although many studies have implicated rotation as a primary cause of mTBI, regulatory safety standards use 3 degree-of-freedom (3DOF) translation-only kinematic criteria to predict injury. Direct 6DOF measurements of human head rotation (3DOF) and translation (3DOF) have not been previously available to examine whether additional DOFs improve injury prediction. We measured head impacts in American football, boxing, and mixed martial arts using 6DOF instrumented mouthguards, and predicted clinician-diagnosed injury using 12 existing kinematic criteria and 6 existing brain finite element (FE) criteria. Among 513 measured impacts were the first two 6DOF measurements of clinically diagnosed mTBI. For this dataset, 6DOF criteria were the most predictive of injury, more than 3DOF translation-only and 3DOF rotation-only criteria. Peak principal strain in the corpus callosum, a 6DOF FE criteria, was the strongest predictor, followed by two criteria that included rotation measurements, peak rotational acceleration magnitude and Head Impact Power (HIP). These results suggest head rotation measurements may improve injury prediction. However, more 6DOF data is needed to confirm this evaluation of existing injury criteria, and to develop new criteria that considers directional sensitivity to injury.

In this paper, a novel semi-quantum key distribution (SQKD) protocol is designed based on single photons in both polarization and spatial-mode degrees of freedom, which allows to establish a raw key between one quantum communicant and one classical communicant. The proposed SQKD protocol only adopts one kind of quantum state as the initial quantum resource. The detailed security analysis shows that it can resist Eve’s active attacks, such as the intercept-resend attack, the measure-resend attack, the Trojan horse attack and the entangle-measure attack. The proposed SQKD protocol only needs single photons in both polarization and spatial-mode degrees of freedom as quantum resource and employs single-photon measurements. Thus, it has excellent feasibility, since the preparation and the measurement of a single photon in both polarization and spatial-mode degrees of freedom can be easily acheived with present quantum technologies.

With the rapid development of the manufacturing industry, industrial automation equipment represented by computer numerical control (CNC) machine tools has put forward higher and higher requirements for the machining accuracy of parts. Compared with the multi-axis serial platform solution, the parallel platform solution is theoretically more suitable for high-precision machining equipment. There are many parallel platform solutions, but not one can provide a common physical platform to test the effectiveness of a variety of control algorithms. To achieve the goals, this paper is based on the Stewart six degrees of freedom parallel platform, and it mainly studies the platform construction. This study completed the mechanical structure design of the parallel platform. Based on the microprogrammed control unit (MCU) + pre-driver chip + three-phase full bridge solution, we have completed the circuit design of the motor driver. We wrote the program of MCU to drive six parallel robotic arms as well as the program of the parallel platform control center on the PC, and we completed the system joint debugging. The closed-loop control effect of the parallel platform workspace pose is realized.

We proposed a novel jaw movement tracking method that can measure in six degrees of freedom. The magnetic field generated by a permanent magnet paired with a small, low-power-consumption Hall effect magnetic sensor is used to estimate the relative distance between two objects—in this instance, the lower and upper jaws. By installing a microelectromechanical system (MEMS) orientation sensor in the device, we developed a mouthpiece-type sensing device that can measure voluntary mandibular movements in three-dimensional orientation and position. An evaluation of individuals wearing this device demonstrated its ability to measure mandibular movement with an accuracy of approximately 3 mm. Using the movement recording feature with six degrees of freedom also enabled the evaluation of an individual’s jaw movements over time in three dimensions. In this method, all sensors are built onto the mouthpiece and the sensing is completed in the oral cavity. It does not require the fixation of a large-scale device to the head or of a jig to the teeth, unlike existing mandibular movement tracking devices. These novel features are expected to increase the accessibility of routine measurements of natural jaw movement, unrestricted by an individual’s physiological movement and posture.

In order to increase the capacity of quantum communication, several quantum dialogue (QD) protocols, including this work, are based on single photons in both polarization and spatial-mode degrees of freedom (PSDF). Some of them use seven or four composite unitary operations to implement a QD protocol, while this work adopts a mere two single unitary operations to do. Most importantly, their information-theoretical efficiencies are generally only 50%, yet that of this work is up to 66.67%. The analyses show that the proposed QD protocol is safe without information leakage. It does not adopt auxiliary photons either and simply needs single photons in PSDF, whose preparation and measurement can be easily implemented with current technology. So, it is not only of great feasibility in practice, but also simple and efficient.

For real-time detection scenarios such as battlefield reconnaissance and surveillance, where high positioning accuracy is required and receiving station resources are limited, we propose an innovative distributed aerial target localization method with low degrees of freedom. This method is based on a hybrid measurement approach. First, a measurement model is established using the spatial geometric relationship between the distributed node network configuration and the target, with angle of arrival (AOA) and time difference of arrival (TDOA) measurements employed to estimate partial target parameters. Then, frequency difference of arrival (FDOA) measurements are utilized to enhance the accuracy of parameter estimation. Finally, using inter-node measurements, a pseudo-linear system of equations is constructed to complete the three-node aerial target localization. The method uses satellites as radiation sources to transmit signals, with unmanned aerial vehicles (UAVs) acting as receiving station nodes to capture the signals. It effectively utilizes hybrid measurement information, enabling aerial target localization with only three receiving stations. Simulation results validate the significant advantages of the proposed algorithm in enhancing localization accuracy, reducing system costs, and optimizing resource allocation. This technology not only provides an efficient and practical localization solution for battlefield reconnaissance and surveillance systems but also offers robust technical support and broad application prospects for the future development of unmanned systems, intelligent surveillance, and emergency rescue.

Thumb degree-of-freedom (DOF) allocation in anthropomorphic robot hands involves a trade-off between functional mobility and mechanical-control complexity. This study presents a controlled multi-metric framework for comparing recurring thumb DOF configurations under common palm geometry, non-thumb finger structure, reference frames, Denavit–Hartenberg kinematics, and sampling assumptions. Five literature-derived thumb configurations, namely 3-1-1, 2-2-1, 2-1-1, 2-0-1, and 1-1-1, were evaluated to determine which thumb DOFs should be preserved when kinematic complexity is reduced. The theoretical evaluation included Kapandji Opposition Test reachability, opposition alignment, workspace volume, workspace compactness, cylindrical grasp opportunity, and Jacobian-based dexterity. A targeted experimental validation of the 2-1-1 and 2-0-1 prototypes was then performed on a tendon-driven test bench. The results showed that qualitatively similar thumb configurations are quantitatively unequal: several designs achieved identical Kapandji scores but differed substantially in workspace, alignment, dexterity, and grasp feasibility. Overall, 3-1-1 achieved the strongest overall capability, while 2-2-1 emerged as the strongest reduced-complexity alternative and achieved the best mean dexterity. Retaining two active carpometacarpal DOFs preserved a large share of dexterous function, whereas metacarpophalangeal fixation maintained selected cylindrical grasps but narrowed the feasible task boundary.

Insect‐scale crawling robots can navigate confined environments mainly for passive tasks such as search, rescue, and surveillance. Adding actuated degrees of freedom to manipulate the environment can substantially expand the range of tasks that the insect‐scale robot can perform, which is, however, prohibitive due to the added volume and weight. Herein, a miniature rotary electrostatic clutch is presented such that it enables reconfigurable motion by selectively distributing the power of a single motor while embedded at multiple joints. In order to facilitate a compact clutch with a large locking torque, cutting patterns in the electrostatic clutch layer are incorporated. The segmented layer allows large out‐of‐plane displacement, thereby increasing the contact area between layers during engagement. Therefore, compact (20 mm), lightweight (0.4 g) clutches achieve a locking torque of 83.4 mNm, 4 times larger than a clutch without the pattern. Adding a single motor, seven clutches, and four clutch‐layer pairs enables independent drive of six additional joints without significantly increasing size or mass. This approach allows insect‐scale robots to perform variety tasks such as object manipulation, obstacle negotiation, and shape transformation. This method offers an efficient way to embed multiple actuated degrees of freedom in miniature robots, therefore enhancing their mobility and functionality. Insect‐scale crawling robots can traverse confined environments; nevertheless, their functionalities are predominantly restricted to sensing because of challenges in integrating actuated degrees of freedom. Herein, a miniature rotary electrostatic clutch is presented by incorporating cutting patterns in the clutch layer. The clutches are inserted at several joints to create a small robot with six independent joints for manipulation and reconfiguration.

The seven-degree-of-freedom space manipulator, characterized by its redundant and aspheric wrist structure, is extensively used in space missions due to its exceptional dexterity and multi-joint capabilities. However, the non-spherical wrist structure presents challenges in solving inverse kinematics, as it cannot decouple joints using the Pieper criterion, unlike spherical wrist structures. To address this issue, this paper presents a closed-form analytical method for solving the inverse kinematics of seven-degree-of-freedom aspheric wrist space manipulators. The method begins by identifying the redundant joint through comparing the volumes of the workspace with different joints fixed. The redundant joint angle is then treated as a parametric joint angle, enabling the derivation of closed-form expressions for the non-parametric joint angles using screw theory. The optimal solution branch is identified through a comparative analysis of various self-motion manifold branches. Additionally, a hybrid approach, combining analytical and numerical methods, is proposed to optimize the parametric joint angle for a trajectory tracking task. Simulation results confirm the effectiveness of the proposed method.

The kinetostatic compliance method (KCM) models protein molecules as nanomechanisms consisting of numerous rigid peptide plane linkages. These linkages articulate with respect to each other through changes in the molecule dihedral angles, resulting in a kinematic mechanism with hyper degrees of freedom. Within the KCM framework, nonlinear interatomic forces drive protein folding by guiding the molecule’s dihedral angle vector towards its lowest energy state in a kinetostatic manner. This paper proposes a numerical integrator that is well suited to KCM-based protein folding and overcomes the limitations of traditional explicit Euler methods with fixed step size. Our proposed integration scheme is based on pseudo-transient continuation with an adaptive step size updating rule that can efficiently compute protein folding pathways, namely, the transient three-dimensional configurations of protein molecules during folding. Numerical simulations utilizing the KCM approach on protein backbones confirm the effectiveness of the proposed integrator.