Construction of a Fish-like Robot Based on High Performance Graphene/PVDF Bimorph Actuation Materials.

Smart actuators have many potential applications in various areas, so the development of novel actuation materials, with facile fabricating methods and excellent performances, are still urgent needs. In this work, a novel electromechanical bimorph actuator constituted by a graphene layer and a PVDF layer, is fabricated through a simple yet versatile solution approach. The bimorph actuator can deflect toward the graphene side under electrical stimulus, due to the differences in coefficient of thermal expansion between the two layers and the converse piezoelectric effect and electrostrictive property of the PVDF layer. Under low voltage stimulus, the actuator (length: 20 mm, width: 3 mm) can generate large actuation motion with a maximum deflection of about 14.0 mm within 0.262 s and produce high actuation stress (more than 312.7 MPa/g). The bimorph actuator also can display reversible swing behavior with long cycle life under high frequencies. on this basis, a fish-like robot that can swim at the speed of 5.02 mm/s is designed and demonstrated. The designed graphene-PVDF bimorph actuator exhibits the overall novel performance compared with many other electromechanical avtuators, and may contribute to the practical actuation applications of graphene-based materials at a macro scale

Neuro-symbolic Models for Interpretable Time Series Classification using Temporal Logic Description

Most existing Time series classification (TSC) models lack interpretability and are difficult to inspect. Interpretable machine learning models can aid in discovering patterns in data as well as give easy-to-understand insights to domain specialists. In this study, we present Neuro-Symbolic Time Series Classification (NSTSC), a neuro-symbolic model that leverages signal temporal logic (STL) and neural network (NN) to accomplish TSC tasks using multi-view data representation and expresses the model as a human-readable, interpretable formula. In NSTSC, each neuron is linked to a symbolic expression, i.e., an STL (sub)formula. The output of NSTSC is thus interpretable as an STL formula akin to natural language, describing temporal and logical relations hidden in the data. We propose an NSTSC-based classifier that adopts a decision-tree approach to learn formula structures and accomplish a multiclass TSC task. The proposed smooth activation functions for wSTL allow the model to be learned in an end-to-end fashion. We test NSTSC on a real-world wound healing dataset from mice and benchmark datasets from the UCR time-series repository, demonstrating that NSTSC achieves comparable performance with the state-of-the-art models. Furthermore, NSTSC can generate interpretable formulas that match with domain knowledge

Characteristics of Pollen from Transgenic Lines of Apple Carrying the Exogenous CpTI Gene

AbstractIt is fundamental for gene transformation and ecosystem hazard evaluation to study the pollen characteristics of transgenic plants. In this research, the characteristics of pollen from 7- or 8-year-old transgenic apple plants carrying an exogenous CpTI gene were analyzed. The results showed that there was no significant difference in terms of size, morphology, or exine ornamentation between the pollen of the transgenic plants and the non-transgenic control. However, the transgenic plants had more abnormal pollen grains. Of the 13 transgenic lines tested, 12 had a significantly lower amount of pollen and six exhibited a significantly lower germination rate when cultured in vitro. The pollen viability of three transgenic lines was determined, with two showing significantly lower viability than the control. The transgenic Gala apple pollen grains germinated normally via controlled pollination on Fuji apple stigmas. However, the pollen tubes extended relatively slowly during the middle and late development stages, and another 8h were needed to reach the ovules compared with the control. The gibberellic acid concentration in transgenic Gala apple flowers was lower than in the non-transgenic control during all development stages tested. The abscisic acid concentration in the transgenic flowers was lower during the pink stage, and higher during the ball and fully open stages. Microscopic observation of the anther structure showed no difference. The tapetum of the pollen sac wall in transgenic plants decomposed late and affected pollen grain development, which could be one of the reasons for the lower number of pollen grains and poor viability in the transgenic plants

Evaluation of IEEE802.15.4g for Environmental Observations

International audienceIEEE802.15.4g is a low-power wireless standard initially designed for Smart Utility 1 Networks, i.e. for connecting smart meters. IEEE802.15.4g operates at sub-GHz frequencies to offer 2 2-3× longer communication range compared to its 2.4 GHz counterpart. Although the standard 3 offers 3 PHYs (FSK, OFDM and O-QPSK) with numerous configurations, 2-FSK at 50 kbps is the 4 mandatory and most prevalent radio setting used. This article looks at whether IEEE802.15.4g can 5 be used to provide connectivity for outdoor deployments. We conduct range measurements using 6 the totality of the standard (all modulations with all further parametrization) in the 863-870 MHz 7 band, within four scenarios which we believe cover most low-power wireless outdoor applications: 8 line of sight, smart agriculture, urban canyon, and smart metering. We show that there are radio 9 settings that outperform the "2-FSK at 50 kbps" base setting in terms of range, throughput and 10 reliability. Results show that highly reliable communications with data rates up to 800 kbps can 11 be achieved in urban environments at 540 m between nodes, and the longest useful radio link is 12 obtained at 779 m. We discuss how IEEE802.15.4g can be used for outdoor operation, and reduce 13 the number of repeater nodes that need to be placed compared to a 2.4 GHz solution

Teaching with Uncertainty: Unleashing the Potential of Knowledge Distillation in Object Detection

Knowledge distillation (KD) is a widely adopted and effective method for compressing models in object detection tasks. Particularly, feature-based distillation methods have shown remarkable performance. Existing approaches often ignore the uncertainty in the teacher model's knowledge, which stems from data noise and imperfect training. This limits the student model's ability to learn latent knowledge, as it may overly rely on the teacher's imperfect guidance. In this paper, we propose a novel feature-based distillation paradigm with knowledge uncertainty for object detection, termed "Uncertainty Estimation-Discriminative Knowledge Extraction-Knowledge Transfer (UET)", which can seamlessly integrate with existing distillation methods. By leveraging the Monte Carlo dropout technique, we introduce knowledge uncertainty into the training process of the student model, facilitating deeper exploration of latent knowledge. Our method performs effectively during the KD process without requiring intricate structures or extensive computational resources. Extensive experiments validate the effectiveness of our proposed approach across various distillation strategies, detectors, and backbone architectures. Specifically, following our proposed paradigm, the existing FGD method achieves state-of-the-art (SoTA) performance, with ResNet50-based GFL achieving 44.1% mAP on the COCO dataset, surpassing the baselines by 3.9%

Constructive Interference in 802.15.4: A Tutorial

International audienceConstructive Interference (CI) can happen when multiple wireless devices send the same frame at the same time. If the time offset between the transmissions is less than 500 ns, a receiver will successfully decode the frame with high probability. CI can be useful for achieving low-latency communication or low-overhead flooding in a multi-hop low-power wireless network. The contribution of this article is threefold. First, we present the current state-of-the-art CI-based protocols. Second, we provide a detailed hands-on tutorial on how to implement CI-based protocols on TelosB motes, with well documented open-source code. Third, we discuss the issues and challenges of CI-based protocols, and list open issues and research directions. This article is targeted at the level of practicing engineers and advanced researchers and can serve both as a primer on CI technology and a reference to its implementation

OpenWSN & OpenMote: Demo’ing A Complete Ecosystem for the Industrial Internet of Things

International audienceThe Industrial Internet of Things (IIoT) vision relies on reliable low-power wireless technologies and a complete standardized protocol stack that brings Internet connectivity to constrained end devices. Currently IEEE802.15.4-2015 TSCH provides reliability over low-power wireless technologies and the IETF has defined a protocol stack that is suitable to constrained devices. Open-source initiatives contributing to the development of network stacks for embedded devices, and the availability of open hardware platforms that facilitate prototyping IIoT applications contributes to the adoption of IIoT technologies.To realize the IIoT vision, this demo presents the OpenWSN and OpenMote projects, which provide both an opensource software implementation of the IEEE low-power wireless technologies and the IETF protocol stack, and an open-source hardware platform that meets the requirements to prototype IIoT applications

6TiSCH Minimal Scheduling Function: Performance Evaluation

International audience6TiSCH is a standardization group within the Internet Engineering Task Force (IETF) that works on IPv6-enabled Time-slotted Channel Hopping (TSCH) networks. The 6TiSCH protocol stack, designed by the standardization work at the IETF, has direct applicability to low-power Internet of Things (IoT) use cases, including smart factory, building, infrastructure and home applications. A key component of the 6TiSCH stack is the Minimal Scheduling Function (MSF). MSF implements a traffic adaptation algorithm which allocates link-layer resources, i.e. cells in the TSCH schedule, according to the traffic load. MAX_NUMCELL is an important parameter defined in the MSF draft standard which determines the length of the running window used to measure cell usage. MSF draft standard does not recommend a value of MAX_NUMCELL to use. This paper provides recommendations on how to choose the value of MAX_NUMCELL, validated through simulation. For periodic traffic , setting MAX_NUMCELL to at least 4 times the traffic load is recommended to increase efficiency. For bursty traffic, we show that setting MAX_NUMCELL to a small value achieves a low end-to-end latency but at high communication overhead. In addition, an improved version of MSF is implemented and tested, which shows a 44% reduction in the communication overhead, considering MAX_NUMCELL = 4, while maintaining the same end-to-end latency