Discovery of 2-Naphthol from the Leaves of Actephila merrilliana as a Natural Nematicide Candidate.

To identify natural nematicides that can replace chemical nematicides, 2-naphthol with high activity against Meloidogyne incognita was isolated from Actephila merrilliana. The nematicidal activity of 2-naphthol against M. incognita was 100% at 100 µg/mL with an EC50 value of 38.00 µg/mL. Moreover, 2-naphthol had a significant negative effect on egg incubation. 2-Naphthol effectively inhibited the invasion of M. incognita into crops in both a pot experiment and field trial. In addition, the structure-activity relationship indicated that the naphthalene ring and its ß-site hydroxyl group were the key pharmacophores for the nematicidal activity of 2-naphthol. Nematodes were stimulated by 2-naphthol to produce excessive reactive oxygen species, which may be the underlying mechanism of 2-naphthol nematicidal activity. A systemic evaluation of 2-naphthol in tomato plants demonstrated that 2-naphthol remained mainly fixed in the roots after being absorbed by the crop and was not transported to the stems or leaves. Thus, 2-naphthol can be developed as a natural nematicide candidate.

From Skin Mechanics to Tactile Neural Coding: Predicting Afferent Neural Dynamics During Active Touch and Perception.

First order cutaneous neurons allow object recognition, texture discrimination, and sensorimotor feedback. Their function is well-investigated under passive stimulation while their role during active touch or sensorimotor control is understudied. To understand how human perception and sensorimotor controlling strategy depend on cutaneous neural signals under active tactile exploration, the finite element (FE) hand and Izhikevich neural dynamic model were combined to predict the cutaneous neural dynamics and the resulting perception during a discrimination test. Using in-vivo microneurography generated single afferent recordings, 75% of the data was applied for the model optimization and another 25% was used for validation. By using this integrated numerical model, the predicted tactile neural signals of the single afferent fibers agreed well with the microneurography test results, achieving the out-of-sample values of 0.94 and 0.82 for slowly adapting type I (SAI) and fast adapting type I unit (FAI) respectively. Similar discriminating capability with the human subject was achieved based on this computational model. Comparable performance with the published numerical model on predicting the cutaneous neural response under passive stimuli was also presented, ensuring the potential applicability of this multi-level numerical model in studying the human tactile sensing mechanisms during active touch. The predicted population-level 1st order afferent neural signals under active touch suggest that different coding strategies might be applied to the afferent neural signals elicited from different cutaneous neurons simultaneously.

Biomechanical Analysis of the Effect of the Finger Extensor Mechanism on Hand Grasping Performance.

Quantifying the effect of routing and topology of the inter-connected finger extensor mechanism on hand grasping performances is a long-standing research problem for the better clinical diagnosis, surgical planning and biomimetic hand development. However, it is technically demanding to measure the hand performance parameters such as the contact forces and contact area during hand manipulation. It is also difficult to replicate human hand performance through the physical hand model due to its sophisticated musculotendinous structure. In this study, an experimental validated subject-specific finite element (FE) human hand model was used for the first time to quantify the influence of different tendon topologies and material properties on hand grasping quality. It is found that the grasping quality is reduced by 15.94% and 8.54% if there are no extensor hood and lateral band respectively, and the former plays a more important role in transmitting forces and maintaining grasping qualities than the latter. Excluding extensor hood in the topology causes more reductions in hand contact pressure and contact area than omitting lateral band. 7.5% of the grasping quality is lost due to a softened tendon with half of its original Young's Modulus. Hardened extensor tendon does increase the grasping quality, but the enhancing effect tends to level off once the tendon Young's Modulus is increased by more than 50%. These results prove that the lateral band and extensor hood are critical components for maintaining grasping quality. The dexterity and grasping quality of robotic and prosthetic hands could be improved by integrating these two components. There is also no need to use very stiff tendon material as it won't help to effectively enhance the grasping quality.

Biomechanical analysis of the effect of finger joint configuration on hand grasping performance: rigid vs flexible.

Human finger joints are conventionally simplified as rigid joints in robotic hand design and biomechanical hand modelling, due to their anatomic and morphologic complexity. However, our understanding of the effect of the finger joint configuration on the resulting hand performance is still primitive. In this study, we systematically investigate the grasping performance of the hands with the conventional rigid joints and the biomechanical flexible joints based on a computational human hand model. The measured muscle electromyography (EMG) and hand kinematic data during grasping are used as inputs for the grasping simulations. The results show that the rigid joint configuration currently used in most robotic hands leads to large reductions in hand contact force, contact pressure and contact area, compared to the flexible joint configuration. The grasping quality could be reduced up to 40% and 36% by the rigid joint configuration in terms of algebraic properties of grasping matrix and finger force limit respectively. Further investigation reveals that these reductions are caused by the weak rotational stiffness of the rigid joint configuration. This study implies that robotic/prosthetic hand performance could be improved by exploiting flexible finger joint design. Hand contact parameters and grasping performance may be underestimated by the rigid joint simplification in human hand modelling.

Biology and bioinspiration of soft robotics: Actuation, sensing, and system integration.

Organisms in nature grow with senses, nervous, and actuation systems coordinated in ingenious ways to sustain metabolism and other essential life activities. The understanding of biological structures and functions guide the construction of soft robotics with unprecedented performances. However, despite the progress in soft robotics, there still remains a big gap between man-made soft robotics and natural lives in terms of autonomy, adaptability, self-repair, durability, energy efficiency, etc. Here, the actuation and sensing strategies in the natural biological world are summarized along with their man-made counterparts applied in soft robotics. The development trends of bioinspired soft robotics toward closed loop and embodiment are proposed. Challenges for obtaining autonomous soft robotics similar to natural organisms are outlined to provide a perspective in this field.

Subject-Specific Finite Element Modelling of the Human Hand Complex: Muscle-Driven Simulations and Experimental Validation.

This paper aims to develop and validate a subject-specific framework for modelling the human hand. This was achieved by combining medical image-based finite element modelling, individualized muscle force and kinematic measurements. Firstly, a subject-specific human hand finite element (FE) model was developed. The geometries of the phalanges, carpal bones, wrist bones, ligaments, tendons, subcutaneous tissue and skin were all included. The material properties were derived from in-vivo and in-vitro experiment results available in the literature. The boundary and loading conditions were defined based on the kinematic data and muscle forces of a specific subject captured from the in-vivo grasping tests. The predicted contact pressure and contact area were in good agreement with the in-vivo test results of the same subject, with the relative errors for the contact pressures all being below 20%. Finally, sensitivity analysis was performed to investigate the effects of important modelling parameters on the predictions. The results showed that contact pressure and area were sensitive to the material properties and muscle forces. This FE human hand model can be used to make a detailed and quantitative evaluation into biomechanical and neurophysiological aspects of human hand contact during daily perception and manipulation. The findings can be applied to the design of the bionic hands or neuro-prosthetics in the future.

Validation of a Low-Cost Electromyography (EMG) System via a Commercial and Accurate EMG Device: Pilot Study.

Electromyography (EMG) devices are well-suited for measuring the behaviour of muscles during an exercise or a task, and are widely used in many different research areas. Their disadvantage is that commercial systems are expensive. We designed a low-cost EMG system with enough accuracy and reliability to be used in a wide range of possible ways. The present article focuses on the validation of the low-cost system we designed, which is compared with a commercially available, accurate device. The evaluation was done by means of a set of experiments, in which volunteers performed isometric and dynamic exercises while EMG signals from the rectus femoris muscle were registered by both the proposed low-cost system and a commercial system simultaneously. Analysis and assessment of three indicators to estimate the similarity between both signals were developed. These indicated a very good result, with spearman's correlation averaging above 0.60, the energy ratio close to the 80% and the linear correlation coefficient approximating 100%. The agreement between both systems (custom and commercial) is excellent, although there are also some limitations, such as the delay of the signal (<1 s) and noise due to the hardware and assembly in the proposed system.