Demonstrating Path-Independent Anyonic Braiding on a Modular Superconducting Quantum Processor.

Anyons, exotic quasiparticles in two-dimensional space exhibiting nontrivial exchange statistics, play a crucial role in universal topological quantum computing. One notable proposal to manifest the fractional statistics of anyons is the toric code model; however, scaling up its size through quantum simulation poses a serious challenge because of its highly entangled ground state. In this Letter, we demonstrate that a modular superconducting quantum processor enables hardware-pragmatic implementation of the toric code model. Through in-parallel control across separate modules, we generate a 10-qubit toric code ground state in four steps and realize six distinct braiding paths to benchmark the performance of anyonic statistics. The path independence of the anyonic braiding statistics is verified by correlation measurements in an efficient and scalable fashion. Our modular approach, serving as a hardware embodiment of the toric code model, offers a promising avenue toward scalable simulation of topological phases, paving the way for quantum simulation in a distributed fashion.

Cognitive impairment in Alzheimer's disease FAD4T mouse model: Synaptic loss facilitated by activated microglia via C1qA.

Alzheimer's disease (AD) is a chronic and progressive neurodegenerative disorder characterized by cognitive dysfunction. The connection between neuroinflammation and abnormal synaptic function in AD is recognized, but the underlying mechanisms remain unclear. In this study, we utilized a mouse model of AD, FAD4T mice aged 6-7 months, to investigate the molecular changes affecting cognitive impairment. Behavior tests showed that FAD4T mice exhibited impaired spatial memory compared with their wild-type littermates. Immunofluorescence staining revealed the presence of Aß plaques and abnormal glial cell activation as well as changes in microglial morphology in the cortex and hippocampus of FAD4T mice. Synaptic function was impaired in FAD4T mice. Patch clamp recordings of hippocampal neurons revealed reduced amplitude of miniature excitatory postsynaptic currents. Additionally, Golgi staining showed decreased dendritic spine density in the cortex and hippocampus of FAD4T mice, indicating aberrant synapse morphology. Moreover, hippocampal PSD-95 and NMDAR1 protein levels decreased in FAD4T mice. RNA-seq analysis revealed elevated expression of immune system and proinflammatory genes, including increased C1qA protein and mRNA levels, as well as higher expression of TNF-α and IL-18. Taken together, our findings suggest that excessive microglia activation mediated by complement factor C1qA may contribute to aberrant synaptic pruning, resulting in synapse loss and disrupted synaptic transmission, ultimately leading to AD pathogenesis and behavioral impairments in the FAD4T mouse model. Our study provides valuable insights into the underlying mechanisms of cognitive impairments and preliminarily explores a potentially effective treatment approach targeting on C1qA for AD.

Construction of metal-organic framework/cellulose nanofibers-based hybrid membranes and their ion transport property for efficient osmotic energy conversion.

The development of advanced nanofluidic membranes with better ion selectivity, efficient energy conversion and high output power density remains challenging. Herein, we prepared nanofluidic hybrid membranes based on TEMPO oxidized cellulose nanofibers (T-CNF) and manganese-based metal organic framework (MOF) using a simple in situ synthesis method. Incorporated T-CNF endows the MOF/T-CNF hybrid membrane with a high cation selectivity up to 0.93. Nanoporous MOF in three-dimensional interconnected nanochannels provides massive ion transport pathways. High transmembrane ion flux and low ion permeation energy barrier are correlated with a superior energy conversion efficiency (36 %) in MOF/T-CNF hybrid membrane. When operating under 50-fold salinity gradient by mixing simulated seawater and river water, the MOF/T-CNF hybrid membrane achieves a maximum power density value of 1.87 W m-2. About 5-fold increase in output power density was achieved compared to pure T-CNF membrane. The integration of natural nanofibers with high charge density and nanoporous MOF materials is demonstrated an effective and novel strategy for the enhancement of output power density of nanofluidic membranes, showing the great potential of MOF/T-CNF hybrid membranes as efficient nanofluidic osmotic energy generators.

Design of metallic phase WS2/cellulose nanofibers composite membranes for light-boosted osmotic energy conversion.

Osmotic energy reserves in estuaries, coupled with the ubiquitous solar energy, could be harnessed through emerging nanofluidic membranes to reduce the energy crisis. Herein, we mixed WS2 with high concentration of metal phase and cellulose nanofiber (CNF) to fabricate composite membranes by vacuum filtration. Incorporated CNF as space charge donors increases the ion flux through the enlarged interlayer spacing in the WS2/CNF composite membrane. By simulating seawater and river water, the power density of the composite membrane reached to 1.99 W m-2. Furthermore, due to the photoelectric characteristics of WS2, the composite membrane exhibits photoresponsivity, which generated a photocurrent of 177 nA through illumination. Taking the advantage of the optoelectronic properties of the composite membrane, the power density under illumination is twice than that of the dark state. Based on the results, this material design strategy can enhance the ion transport in nanofluidic membranes for efficient generation of clean energy.

A Multimodel Fusion Method for Cardiovascular Disease Detection Using ECG.

Objective. Electrocardiogram (ECG) is an important diagnostic tool that has been the subject of much research in recent years. Owing to a lack of well-labeled ECG record databases, most of this work has focused on heartbeat arrhythmia detection based on ECG signal quality. Approach. A record quality filter was designed to judge ECG signal quality, and a random forest method, a multilayer perceptron, and a residual neural network (RESNET)-based convolutional neural network were implemented to provide baselines for ECG record classification according to three different principles. A new multimodel method was constructed by fusing the random forest and RESNET approaches. Main Results. Owing to its ability to combine discriminative human-crafted features with RESNET deep features, the proposed new method showed over 88% classification accuracy and yielded the best results in comparison with alternative methods. Significance. A new multimodel fusion method was presented for abnormal cardiovascular detection based on ECG data. The experimental results show that separable convolution and multiscale convolution are vital for ECG record classification and are effective for use with one-dimensional ECG sequences.

Video Text Tracking With a Spatio-Temporal Complementary Model.

Text tracking is to track multiple texts in a video, and construct a trajectory for each text. Existing methods tackle this task by utilizing the tracking-by-detection framework, i.e., detecting the text instances in each frame and associating the corresponding text instances in consecutive frames. We argue that the tracking accuracy of this paradigm is severely limited in more complex scenarios, e.g., owing to motion blur, etc., the missed detection of text instances causes the break of the text trajectory. In addition, different text instances with similar appearance are easily confused, leading to the incorrect association of the text instances. To this end, a novel spatio-temporal complementary text tracking model is proposed in this paper. We leverage a Siamese Complementary Module to fully exploit the continuity characteristic of the text instances in the temporal dimension, which effectively alleviates the missed detection of the text instances, and hence ensures the completeness of each text trajectory. We further integrate the semantic cues and the visual cues of the text instance into a unified representation via a text similarity learning network, which supplies a high discriminative power in the presence of text instances with similar appearance, and thus avoids the mis-association between them. Our method achieves state-of-the-art performance on several public benchmarks. The source code is available at https://github.com/lsabrinax/VideoTextSCM.

Single probe PCR melting curve analysis MTHFR C677T SNP sites.

BACKGROUND: The detection and analysis of methylene tetrahydrofolate reductase (MTHFR) C677T single nucleotide polymorphism (SNP) from blood samples is time-consuming and costly. We aimed to establish a method to detect these SNPs by direct whole blood PCR and without DNA extraction. METHODS: Probes modified by different fluorescent groups on the same sequence were designed. Various MTHFR genotypes from direct blood PCR experiments were used to verify the similarity of the obtained and sequencing results. The SNP sites adjacent to the MTHFR C677T SNP were used to verify whether the method can accurately distinguish these sites. RESULTS: The ROX probe was found to be the most suitable for this study. We tested 291 samples with 1 µL whole blood as a template, and obtained 126, 43, and 122 cases of C677C, C677T, and C677 C/T genotypes, respectively. The melting curve was consistent with the sequencing results. The detection limit was approximately 1000 white blood cells/µL. Through PCR and the melting curve method, the adjacent sites were accurately distinguished. CONCLUSION: We established a reliable, simple, rapid, and low-cost direct blood PCR method for the detection of MTHFR C677T SNPs. This could also be used as a potential diagnostic tool for a variety of diseases.

Molecular Dynamics Study of Binary Nanodroplet Evaporation on a Heated Homogeneous Substrate.

The evaporation mechanism of miscible binary nanodroplets from heated homogeneous surfaces was studied by molecular dynamics simulations, which has never been studied before. The binary droplets contain a hydrophilic component (type-2 particles) and a hydrophobic component (type-3 particles). It is shown that liquid-liquid interaction strength (ε23) and hydrophilic particle number fraction (φ) have great influence on the surface tension, wetting characteristics, evaporation patterns, evaporation rate, and local mass flux. It is observed that when ε23 ≥ 1, or φ ≈ 0.5, the evaporation mode is the constant-contact-angle mode. Otherwise, it is the mixed mode. We found that the evaporation rate becomes faster when φ and ε23 increase. The droplets become more hydrophilic when φ increases, which promotes heat transfer efficiency between the liquid-solid interface. Besides, a larger ε23 promotes the heat transfer inside the droplet. The mass transfer to the vapor phase occurs preferentially in the vicinity of TPCL (three phase contact line) in the hydrophilic systems (θ < θc), where θc is the critical contact angle, while in most hydrophobic systems (θ > θc), the mass flux close to the TPCL is suppressed. We found that θc ∈ (102°-106°), which is different from the theoretical one, θc = 90°. The discrepancy is attributed to the existence of the adsorption layer near the TPCL.

Pinning-Depinning Mechanism of the Contact Line during Evaporation of Nanodroplets on Heated Heterogeneous Surfaces: A Molecular Dynamics Simulation.

Droplet evaporation on heterogeneous or patterned surfaces has numerous potential applications, for example, inkjet printing. The effect of surface heterogeneities on the evaporation of a nanometer-sized cylindrical droplet on a solid surface is studied using molecular dynamics simulations of Lennard-Jones particles. Different heterogeneities of the surface were achieved through alternating stripes of equal width but two chemical types, which lead to different contact angles. The evaporation induced by the heated substrate instead of the isothermal evaporation is investigated. It is found that the whole evaporation process is generally dominated by the nonuniform evaporation effect. However, at the initial moment, the volume expansion and local evaporation effects play important roles. From the nanoscale point of view, the slow movement of the contact line during the pinning process is observed, which is different from the macroscopic stationary pinning. Particularly, we found that the speed of the contact line may be not only affected by the intrinsic energy barrier between the two adjacent stripes ( u) but also relevant to the evaporation rate. Generally speaking, the larger the intrinsic energy barrier, the slower the movement of the contact line. At the specified temperature, when u is less than a critical energy barrier ( u*), the speed of the contact line would increase with the evaporate rate. When u > u*, the speed of the contact line is determined only by u and no longer affected by the evaporation rate at different stages (the first stick and the second stick).

Identification of pulmonary nodules via CT images with hierarchical fully convolutional networks.

Lung cancer is one of the most diagnosable forms of cancer worldwide. The early diagnoses of pulmonary nodules in computed tomography (CT) chest scans are crucial for potential patients. Recent researches have showed that the methods based on deep learning have made a significant progress for the medical diagnoses. However, the achievements on identification of pulmonary nodules are not yet satisfactory enough to be adopted in clinical practice. It is largely caused by either the existence of many false positives or the heavy time of processing. With the development of fully convolutional networks (FCNs), in this study, we proposed a new method of identifying the pulmonary nodules. The method segments the suspected nodules from their environments and then removes the false positives. Especially, it optimizes the network architecture for the identification of nodules rapidly and accurately. In order to remove the false positives, the suspected nodules are reduced using the 2D models. Furthermore, according to the significant differences between nodules and non-nodules in 3D shapes, the false positives are eliminated by integrating into the 3D models and classified via 3D CNNs. The experiments on 1000 patients indicate that our proposed method achieved 97.78% sensitivity rate for segmentation and 90.1% accuracy rate for detection. The maximum response time was less than 30 s and the average time was about 15 s. Graphical Abstract This paper has proposed a new method of identifying the pulmonary nodules. The method segments the suspected nodules from CT images and removes the false positives. As shown in the above, the proposed approach consists of three stages. In stage I, raw data are filtered and normalized. The clean normalized data are then segmented in stage II to extract the suspected nodular lesions through 2D FCNs. Stage III is to remove some false positives generated at stage II via 3D CNNs and outputs the final results. The experiments on 1000 patients indicate that our proposed method has achieved 97.78% sensitivity rate for segmentation and 90.1% accuracy rate for detection. The maximum response time was less than 30 s and the average time was about 15 s.

[Effectiveness of modified method for cup ear deformity].

OBJECTIVE: To introduce a modified method to correct type I and type II cup ear and to evaluate the effectiveness. METHODS: Between May 2006 and November 2011, 23 patients with type I or type II cup ear (27 ears, type I in 6 ears and type II in 21 ears according to Tanzer's criteria) were treated. There were 14 males and 9 females with an average age of 10 years (range, 7-16 years). The unilateral ear was involved in 19 cases and bilateral ears in 4 cases. The main clinical manifestations included the flat helix and scapha and ptosis of upper 1/3 auricle. The arc incision was adopted in the auriculocephalic angle, elevation of the dis-clothing-like flap in the front and rear of the auricular cartilage, relocation of the craniofacial initiation site of the scapha and the cavity of auricular concha, correction of deformational auricular cartilage and reconstruction of smooth helix, antihelix, superior and inferior antihelix crus. RESULTS: All the incisions healed by first intention without any hematoma, postoperative infection, or flap necrosis. All patients were followed up 9 months-6 years (median, 36 months). No auricle ptosis, deformity contour, or atrophy was observed. The structure of the helix, scapha, and antihelix were clear, natural, and excellent. The scars at the local site were limited and unconspicuous. CONCLUSION: Modified method can almost correct all the anatomic defects of cup ear. It is an ideal method to treat type I and type II cup ear.