Animals respond to environmental threats, e.g. looming visual stimuli, with innate defensive behaviors such as escape and freezing. The key neural circuits that participate in the generation of such dimorphic defensive behaviors remain unclear. Here we show that the dimorphic behavioral patterns triggered by looming visual stimuli are mediated by parvalbumin-positive (PV+) projection neurons in mouse superior colliculus (SC). Two distinct groups of SC PV+ neurons form divergent pathways to transmit threat-relevant visual signals to neurons in the parabigeminal nucleus (PBGN) and lateral posterior thalamic nucleus (LPTN). Activations of PV+ SC-PBGN and SC-LPTN pathways mimic the dimorphic defensive behaviors. The PBGN and LPTN neurons are co-activated by looming visual stimuli. Bilateral inactivation of either nucleus results in the defensive behavior dominated by the other nucleus. Together, these data suggest that the SC orchestrates dimorphic defensive behaviors through two separate tectofugal pathways that may have interactions.
The influence of different C-doping locations in a GaN/Si structure with a GaN/AlN superlattice (SL) buffer on the material and electrical properties of GaN/Si was studied. The introduction of C doping can remarkably degrade the crystal quality of the buffer. C-doping of a top GaN buffer can introduce compressive stress into the top GaN due to the size effect, while C-doping in a SL buffer can impair the compressive stress provided from the SL buffer to the top GaN. It is found that introducing high-density carbon into the whole buffer can result in a more strain-balanced GaN/Si system with small deterioration of the 2DEG channel. Furthermore, the whole buffer C-doping method is an effective and easy way to achieve a thin buffer with low leakage current and high breakdown voltage (266 V@1 nA mm−1; 698 V@10 μA mm−1; 912 V@1 mA mm−1). By using the whole-buffer C-doping method, a 2.5 μm-thick AlGaN/GaN HFET with a breakdown voltage higher than 900 V was achieved, and the breakdown voltage per unit buffer thickness can reach 181 V μm−1.
Quantum error correction is essential for bridging the gap between the error rates of physical devices and the extremely low logical error rates required for quantum algorithms. Recent error-correction demonstrations on superconducting processors have focused primarily on the surface code, which offers a high error threshold but poses limitations for logical operations. In contrast, the color code enables much more efficient logic, although it requires more complex stabilizer measurements and decoding techniques. Measuring these stabilizers in planar architectures such as superconducting qubits is challenging, and so far, realizations of color codes have not addressed performance scaling with code size on any platform. Here, we present a comprehensive demonstration of the color code on a superconducting processor, achieving logical error suppression and performing logical operations. Scaling the code distance from three to five suppresses logical errors by a factor of $\Lambda_{3/5}$ = 1.56(4). Simulations indicate this performance is below the threshold of the color code, and furthermore that the color code may be more efficient than the surface code with modest device improvements. Using logical randomized benchmarking, we find that transversal Clifford gates add an error of only 0.0027(3), which is substantially less than the error of an idling error correction cycle. We inject magic states, a key resource for universal computation, achieving fidelities exceeding 99% with post-selection (retaining about 75% of the data). Finally, we successfully teleport logical states between distance-three color codes using lattice surgery, with teleported state fidelities between 86.5(1)% and 90.7(1)%. This work establishes the color code as a compelling research direction to realize fault-tolerant quantum computation on superconducting processors in the near future.
Inherent symmetry of a quantum system may protect its otherwise fragile states. Leveraging such protection requires testing its robustness against uncontrolled environmental interactions. Using 47 superconducting qubits, we implement the one-dimensional kicked Ising model which exhibits non-local Majorana edge modes (MEMs) with $\mathbb{Z}_2$ parity symmetry. Remarkably, we find that any multi-qubit Pauli operator overlapping with the MEMs exhibits a uniform late-time decay rate comparable to single-qubit relaxation rates, irrespective of its size or composition. This characteristic allows us to accurately reconstruct the exponentially localized spatial profiles of the MEMs. Furthermore, the MEMs are found to be resilient against certain symmetry-breaking noise owing to a prethermalization mechanism. Our work elucidates the complex interplay between noise and symmetry-protected edge modes in a solid-state environment.
Liraglutide, a glucagon-like peptide-1 (GLP-1) analog, is approved for obesity treatment, but the specific neuronal sites that contribute to its therapeutic effects remain elusive. Here, we show that GLP-1 receptor–positive (GLP-1R–positive) neurons in the lateral septum (LSGLP-1R) play a critical role in mediating the anorectic and weight-loss effects of liraglutide. LSGLP-1R neurons were robustly activated by liraglutide, and chemogenetic activation of these neurons dramatically suppressed feeding. Targeted knockdown of GLP-1 receptors within the LS, but not in the hypothalamus, substantially attenuated liraglutide's ability to inhibit feeding and lower body weight. The activity of LSGLP-1R neurons rapidly decreased during naturalistic feeding episodes, while synaptic inactivation of LSGLP-1R neurons diminished the anorexic effects triggered by liraglutide. Together, these findings offer critical insights into the functional role of LSGLP-1R neurons in the physiological regulation of energy homeostasis and delineate their instrumental role in mediating the pharmacological efficacy of liraglutide.
In this paper, the leakage path and breakdown behavior of GaN on silicon substrate were studied systematically. Three terminal breakdown voltage characteristics of the samples with various ohmic contacts spacing were evaluated. With increasing the spacing between the contacts, the breakdown voltage increased linearly first and then saturated. In order to clarify the breakdown behavior, leakage path after breakdown test was further analyzed and the breakdown behaviors were identified. Furthermore, the burnt buffer layer was observed by FIB SEM after device breakdown intuitively. It manifested that the spacing dependent breakdown characteristics of the epitaxial layer was ascribe to that different leakage paths dominated the breakdown at different spacing.
We investigated if emotion regulation can be improved through self-regulation training on non-emotional brain regions, as well as how to change the brain networks implicated in this process. During the training period, the participants were instructed to up-regulate their right dorsolateral prefrontal cortex (rDLPFC) activity according to real-time functional near-infrared spectroscopy (fNIRS) neurofeedback signals, and there was no emotional element. The results showed that the training significantly increased emotion regulation, resting-state functional connectivity (rsFC) within the emotion regulation network (ERN) and frontoparietal network (FPN), and rsFC between the ERN and amygdala; however, training did not influence the rsFC between the FPN and the amygdala. However, self-regulation training on rDLPFC significantly improved emotion regulation and generally increased the rsFCs within the networks; the rsFC between the ERN and amygdala was also selectively increased. The present study also described a safe approach that may improve emotion regulation through self-regulation training on non-emotional brain regions.
The rapid, stable, and undamaged picking of small-sized spherical fruits are one of the key technologies to improve the level of intelligent picking robots and reduce grading operations. Cherry tomatoes were selected as the research object in this work. Picking strategies of two-stage “Holding-Rotating” and finger-end grasping were determined. The end-effector was designed to separate the fruit from the stalk based on the linear motion of the constraint part and the rotating gripper. This work first studied the human hand-grasping of cherry tomatoes and designed the fingers with sinusoidal characteristics. The mathematical model of a single finger of the gripper was established. The structural parameters of the gripper were determined to meet the requirements of the grabbing range from 0 to 61.6 mm. Based on the simulation model, the constraint part was set to 6 speeds, and the fruit sizes were set to 20 mm, 30 mm, and 40 mm, respectively. When the speed was 0.08m/s, the results showed that the grabbing time was 0.5381 s, 0.387 s, and 0.2761 s, respectively, and the maximum grabbing force was 0.9717 N, 3.5077 N, and 4.0003 N now of clamping, respectively. It met the picking requirements of high speed and low loss. The criterions of two-index stability and undamaged were proposed, including the grasping index of the fixed value and the slip detection of variance to mean ratio. Therefore, the control strategy and algorithm based on two-stage and two-index for rapid, stable, and non-destructive harvesting of small fruit were proposed. The results of the picking experiment for seventy-two cherry tomatoes showed that the picking success rate was 95.82%, the average picking time was 4.86 s, the picking damage rate was 2.90%, the browning rate was 2.90% in 72 h, and the wrinkling rate was 1.49% in 72 h, which can meet the actual small spherical fruit picking requirements. The research will provide an idea for the flexible end-effectors with humanoid grasp function and provides a theoretical reference for small spherical fruit picking.
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