Flexible multichannel electrodes for acute recording in nonhuman primates.

Flexible electrodes have demonstrated better biocompatibility than rigid electrodes in relieving tissue encapsulation and long-term recording. Nonhuman primates are closer to humans in their brains' structural and functional properties, thus making them more suitable than rodents as animal models for potential clinical usage. However, the application of flexible electrodes on nonhuman primates has rarely been reported. In the present study, a flexible multichannel electrode array for nonhuman primates was developed and implemented for extracellular recording in behaving monkeys. To minimize the window of durotomy for reducing possible risks, a guide-tube-compatible implantation solution was designed to deliver the flexible electrodes through the dura into the cortex. The proposed structure for inserting flexible electrodes was characterized ex vivo and validated in vivo. Furthermore, acute recording of multichannel flexible electrodes for the primates was performed. The results showed that the flexible electrodes and implantation method used in this study meet the needs of extracellular recording in nonhuman primates. Task-related neuronal activities with a high signal-to-noise ratio of spikes demonstrated that our whole device is currently a minimally invasive and clinically viable approach for extracellular recording.

Boron Nitride/Polyurethane Composites with Good Thermal Conductivity and Flexibility.

Thermal insulating composites are indispensable in electronic applications; however, their poor thermal conductivity and flexibility have become bottlenecks for improving device operations. Hexagonal boron nitride (BN) has excellent thermal conductivity and insulating properties and is an ideal filler for preparing thermally insulating polymer composites. In this study, we report a method to fabricate BN/polyurethane (PU) composites using an improved nonsolvent-induced phase separation method with binary solvents to improve the thermal performance and flexibility of PU. The stress and strain of BN60/PU are 7.52 ± 0.87 MPa and 707.34 ± 38.34%, respectively. As prepared, BN60/PU composites with unordered BN exhibited high thermal conductivity and a volume resistivity of 0.653 W/(m·K) and 23.9 × 1012 Ω·cm, which are 218.71 and 39.77% higher than that of pure PU, respectively. Moreover, these composite films demonstrated a thermal diffusion ability and maintained good integrity after 1000 bending cycles, demonstrating good mechanical and thermal reliability for practical use. Our findings provide a practical route for the production of flexible materials for efficient thermal management.

Fabrication of Silane-Grafted Cellulose Nanocrystals and Their Effects on the Structural, Thermal, Mechanical, and Hysteretic Behavior of Thermoplastic Polyurethane.

Reinforcement of polymer nanocomposites can be achieved by the selection of the appropriate fabrication method, surface modification, and orientation of the filler. Herein, we present a nonsolvent-induced phase separation method with ternary solvents to prepare thermoplastic polyurethane (TPU) composite films with excellent mechanical properties using 3-Glycidyloxypropyltrimethoxysilane-modified cellulose nanocrystals (GLCNCs). ATR-IR and SEM analyses of the GLCNCs confirmed that GL was successfully coated on the surface of the nanocrystals. The incorporation of GLCNCs in TPU resulted in the enhancement of the tensile strain and toughness of pure TPU owing to the enhanced interfacial interactions between them. The GLCNC-TPU composite film had tensile strain and toughness values of 1740.42% and 90.01 MJ/m3, respectively. Additionally, GLCNC-TPU exhibited a good elastic recovery rate. CNCs were readily aligned along the fiber axis after the spinning and drawing of the composites into fibers, which further improved the mechanical properties of the composites. The stress, strain, and toughness of the GLCNC-TPU composite fiber increased by 72.60%, 10.25%, and 103.61%, respectively, compared to those of the pure TPU film. This study demonstrates a facile and effective strategy for fabricating mechanically enhanced TPU composites.

Implantable intracortical microelectrodes: reviewing the present with a focus on the future.

Implantable intracortical microelectrodes can record a neuron's rapidly changing action potentials (spikes). In vivo neural activity recording methods often have either high temporal or spatial resolution, but not both. There is an increasing need to record more neurons over a longer duration in vivo. However, there remain many challenges to overcome before achieving long-term, stable, high-quality recordings and realizing comprehensive, accurate brain activity analysis. Based on the vision of an idealized implantable microelectrode device, the performance requirements for microelectrodes are divided into four aspects, including recording quality, recording stability, recording throughput, and multifunctionality, which are presented in order of importance. The challenges and current possible solutions for implantable microelectrodes are given from the perspective of each aspect. The current developments in microelectrode technology are analyzed and summarized.

A High-Precision Method for 100-Day-Old Classification of Chickens in Edge Computing Scenarios Based on Federated Computing.

Due to the booming development of computer vision technology and artificial intelligence algorithms, it has become more feasible to implement artificial rearing of animals in real production scenarios. Improving the accuracy of day-age detection of chickens is one of the examples and is of great importance for chicken rearing. This paper focuses on the problem of classifying the age of chickens within 100 days. Due to the huge amount of data and the different computing power of different devices in practical application scenarios, it is important to maximize the computing power of edge computing devices without sacrificing accuracy. This paper proposes a high-precision federated learning-based model that can be applied to edge computing scenarios. In order to accommodate different computing power in different scenarios, this paper proposes a dual-ended adaptive federated learning framework; in order to adapt to low computing power scenarios, this paper performs lightweighting operations on the mainstream model; and in order to verify the effectiveness of the model, this paper conducts a number of targeted experiments. Compared with AlexNet, VGG, ResNet and GoogLeNet, this model improves the classification accuracy to 96.1%, which is 14.4% better than the baseline model and improves the Recall and Precision by 14.8% and 14.2%, respectively. In addition, by lightening the network, our methods reduce the inference latency and transmission latency by 24.4 ms and 10.5 ms, respectively. Finally, this model is deployed in a real-world application and an application is developed based on the wechat SDK.

Compact and low-loss TM-pass polarizer based on a hybrid plasmonic waveguide with a semiround arch Si core.

A compact and low loss TM-pass polarizer based on a hybrid plasmonic waveguide (HPW) has been demonstrated. By introducing the hollow HPW with a semiround arch (SRA) Si core, the unwanted TE mode can be effectively cut off and the TM mode can pass through by hybrid plasmonic mode with excellent transmission characteristics. The hollow structure realizes lower index with n=1 due to the air region, and the SRA construction effectively suppresses the energy loss of the TM mode caused by the corner effect. Thus, TM modes pass through with negligible loss and exhibit the characteristic of strong mode limitation. By optimizing the width of metal, the width of the HPW, and the length of the tapered mode converter, an optimum performance with a high polarization extinction ratio of 67.87 dB and a low insert loss of 0.029 dB at the work wavelength=1550nm is achieved. Detailed analysis also proves that the proposed polarizer has a compact size of only 7 µm and a great fabrication tolerance. This work offers a simple and effective scheme of polarization control on-chip.

Focusing characteristics of cylindrical vector beams through a multi-focal all-dielectric grating lens.

A novel, to the best of our knowledge, type of multi-focal all-dielectric grating lens is proposed in this work, and focusing characteristics of cylindrical vector beams through the lens are investigated in detail. Based on the negative refraction mechanism of negative-first-order diffraction and Fermat's principle, a multi-focal lens is designed. By analyzing the diffraction effect of the grating, the essential factor that affects the focus quality is found. Through a two-step optimization process, secondary foci and the focal displacement of primary foci caused by high-order diffractions are overcome, and the quality of the focal field is significantly improved. This work provides a reference for micro-lens design for focus modulation, and the research results also have potential applications in the fields of light-field manipulation and optical tweezers.