Adaptive Graph Convolutional Network with Attention Graph Clustering for Co-saliency Detection

Co-saliency detection aims to discover the common and salient foregrounds from a group of relevant images. For this task, we present a novel adaptive graph convolutional network with attention graph clustering (GCAGC). Three major contributions have been made, and are experimentally shown to have substantial practical merits. First, we propose a graph convolutional network design to extract information cues to characterize the intra- and interimage correspondence. Second, we develop an attention graph clustering algorithm to discriminate the common objects from all the salient foreground objects in an unsupervised fashion. Third, we present a unified framework with encoder-decoder structure to jointly train and optimize the graph convolutional network, attention graph cluster, and co-saliency detection decoder in an end-to-end manner. We evaluate our proposed GCAGC method on three cosaliency detection benchmark datasets (iCoseg, Cosal2015 and COCO-SEG). Our GCAGC method obtains significant improvements over the state-of-the-arts on most of them.Comment: CVPR202

Effects of carpal tunnel syndrome on force coordination and muscle coherence during precision pinch

Carpal tunnel syndrome (CTS), caused by entrapment of the median nerve in the carpal tunnel, impairs hand function including dexterous manipulation. The purpose of this study was to investigate the effects of CTS on force coordination and muscle coherence during low-intensity sustained precision pinch while the wrist assumed different postures. Twenty subjects (10 CTS patients and 10 asymptomatic controls) participated in this study. An instrumented pinch device was used to measure the thumb and index finger forces while simultaneously collecting surface electromyographic activities of the abductor pollicis brevis (APB) and first dorsal interosseous (FDI) muscles. Subjects performed a sustained precision pinch at 10% maximum pinch force for 15 sec with the wrist stabilized at 30° extension, neutral, or 30° flexion using customized splints. The force discrepancy and the force coordination angle between the thumb and index finger forces were calculated, as well as the β-band (15-30 Hz) coherence between APB and FDI. The index finger applied greater force than the thumb (p 0.05). The directional force coordination was not significantly affected by wrist posture or CTS (p > 0.05). In general, digit force coordination during precision pinch seems to be sensitive to wrist flexion, but is not affected by CTS. The β-band muscular coherence was increased by wrist flexion for CTS patients (p < 0.05), which could be a compensatory mechanism for the flexion-induced exacerbation of CTS symptoms. This study demonstrates that wrist flexion negatively influences muscle and force coordination in CTS patients supporting the avoidance of flexion posture for symptom exacerbation and functional performance

The nestin-expressing and non-expressing neurons in rat basal forebrain display different electrophysiological properties and project to hippocampus

<p>Abstract</p> <p>Background</p> <p>Nestin-immunoreactive (nestin-ir) neurons have been identified in the medial septal/diagonal band complex (MS/DBB) of adult rat and human, but the significance of nestin expression in functional neurons is not clear. This study investigated electrophysiological properties and neurochemical phenotypes of nestin-expressing (nestin+) neurons using whole-cell recording combined with single-cell RT-PCR to explore the significance of nestin expression in functional MS/DBB neurons. The retrograde labelling and immunofluorescence were used to investigate the nestin+ neuron related circuit in the septo-hippocampal pathway.</p> <p>Results</p> <p>The results of single-cell RT-PCR showed that 87.5% (35/40) of nestin+ cells expressed choline acetyltransferase mRNA (ChAT+), only 44.3% (35/79) of ChAT+ cells expressed nestin mRNA. Furthermore, none of the nestin+ cells expressed glutamic acid decarboxylases 67 (GAD₆₇) or vesicular glutamate transporters (VGLUT) mRNA. All of the recorded nestin+ cells were excitable and demonstrated slow-firing properties, which were distinctive from those of GAD₆₇or VGLUT mRNA-positive neurons. These results show that the MS/DBB cholinergic neurons could be divided into nestin-expressing cholinergic neurons (NEChs) and nestin non-expressing cholinergic neurons (NNChs). Interestingly, NEChs had higher excitability and received stronger spontaneous excitatory synaptic inputs than NNChs. Retrograde labelling combined with choline acetyltransferase and nestin immunofluorescence showed that both of the NEChs and NNChs projected to hippocampus.</p> <p>Conclusions</p> <p>These results suggest that there are two parallel cholinergic septo-hippocampal pathways that may have different functions. The significance of nestin expressing in functional neurons has been discussed.</p

Application of improved YOLOv7-based sugarcane stem node recognition algorithm in complex environments

IntroductionSugarcane stem node detection is one of the key functions of a small intelligent sugarcane harvesting robot, but the accuracy of sugarcane stem node detection is severely degraded in complex field environments when the sugarcane is in the shadow of confusing backgrounds and other objects.MethodsTo address the problem of low accuracy of sugarcane arise node detection in complex environments, this paper proposes an improved sugarcane stem node detection model based on YOLOv7. First, the SimAM (A Simple Parameter-Free Attention Module for Convolutional Neural Networks) attention mechanism is added to solve the problem of feature loss due to the loss of image global context information in the convolution process, which improves the detection accuracy of the model in the case of image blurring; Second, the Deformable convolution Network is used to replace some of the traditional convolution layers in the original YOLOv7. Finally, a new bounding box regression loss function WIoU Loss is introduced to solve the problem of unbalanced sample quality, improve the model robustness and generalization ability, and accelerate the convergence speed of the network.ResultsThe experimental results show that the mAP of the improved algorithm model is 94.53% and the F1 value is 92.41, which are 3.43% and 2.21 respectively compared with the YOLOv7 model, and compared with the mAP of the SOTA method which is 94.1%, an improvement of 0.43% is achieved, which effectively improves the detection performance of the target detection model.DiscussionThis study provides a theoretical basis and technical support for the development of a small intelligent sugarcane harvesting robot, and may also provide a reference for the detection of other types of crops in similar environments

Assessing slope forest effect on flood process caused by a short-duration storm in a small catchment

Land use has significant impact on the hydrologic and hydraulic processes in a catchment. This work applies a hydrodynamic based numerical model to quantitatively investigate the land use effect on the flood patterns under various rainfall and terrain conditions in an ideal V-shaped catchment and a realistic catchment, indicating the land use could considerably affect the rainfall-flood process and such effect varies with the catchment terrain, land use scenario and the rainfall events. The rainfall-flood process is less sensitive for the side slope than the channel slope. For a channel slope lower than the critical value in this work, the forest located in the middle of the catchment slope could most effectively attenuate the flood peak. When the channel slope is higher than the critical one, forest located in the downstream of the catchment could most significantly mitigate the peak discharge. Moreover, the attenuation effect becomes more obvious as the rainfall becomes heavier. The fragmentation of vegetation does not reduce the flood peak in a more obvious way, compared with the integral vegetation patterns with the same area proportion. The research can help more reasonably guide the land use plan related to flood risk

Picosecond Switching of Optomagnetic Tunnel Junctions

Perpendicular magnetic tunnel junctions are one of the building blocks for spintronic memories, which allow fast nonvolatile data access, offering substantial potentials to revolutionize the mainstream computing architecture. However, conventional switching mechanisms of such devices are fundamentally hindered by spin polarized currents4, either spin transfer torque or spin orbit torque with spin precession time limitation and excessive power dissipation. These physical constraints significantly stimulate the advancement of modern spintronics. Here, we report an optomagnetic tunnel junction using a spintronic-photonic combination. This composite device incorporates an all-optically switchable Co/Gd bilayer coupled to a CoFeB/MgO-based perpendicular magnetic tunnel junction by the Ruderman-Kittel-Kasuya-Yosida interaction. A picosecond all-optical operation of the optomagnetic tunnel junction is explicitly confirmed by time-resolved measurements. Moreover, the device shows a considerable tunnel magnetoresistance and thermal stability. This proof-of-concept device represents an essential step towards ultrafast spintronic memories with THz data access, as well as ultralow power consumption.Comment: 18 pages, 3 figure

Picosecond optospintronic tunnel junctions

Perpendicular magnetic tunnel junctions (p-MTJs), as building blocks of spintronic devices, offer substantial potential for next-generation nonvolatile memory applications. However, their performance is fundamentally hindered by a subnanosecond speed limitation, due to spin-polarized-current-based mechanisms. Here, we report an optospintronic tunnel junction (OTJ) device with a picosecond switching speed, ultralow power, high magnetoresistance ratio, high thermal stability, and nonvolatility. This device incorporates an all-optically switchable Gd/Co bilayer coupled to a CoFeB/MgO-based p-MTJ, by subtle tuning of Ruderman–Kittel–Kasuya–Yosida interaction. An all-optical “writing” of the OTJ within 10 ps is experimentally demonstrated by time-resolved measurements. The device shows a reliable resistance “readout” with a relatively high tunnel magnetoresistance of 34.7%, as well as promising scaling toward the nanoscale with ultralow power consumption (<100 fJ for a 50-nm-sized bit). Our proof-of-concept demonstration of OTJ might ultimately pave the way toward a new category of integrated spintronic–photonic memory devices