记忆成像

感知和理解大规模动态场景需要高性能的成像系统。传统的成像系统通过简单地通过拼接相机提高像素分辨率来追求更高的性能,而牺牲了庞大的系统。此外,它们严格遵循前馈路径,即它们的像素级感知独立于语义理解。不同的是,人类视觉系统在前馈和反馈两种通路上都具有优势:前馈通路从视觉输入中提取物体表征(称为记忆印痕),而在反馈通路中,相关的印痕被重新激活以产生关于物体的假设。受此启发,我们提出了一种双通道成像机制,称为刻痕驱动摄像。我们从抽象场景的整体表示开始,它与本地细节双向关联,由实例级印痕驱动。从技术上讲,整个系统的工作原理是在兴奋-抑制和联想状态之间交替进行。在前一种状态下,像素级细节被动态整合或抑制,以加强实例级印记。在关联状态下,空间和时间上一致的内容在其印痕的驱动下被合成,以获得未来场景出色的录像质量。联想状态通过综合由其印痕驱动的空间和时间上一致的内容,作为未来场景的成像。大量的仿真和实验结果表明,该系统彻底改变了传统的录像模式,在多目标大场景的录像中显示出巨大的潜力。

CNN-Based Intelligent Safety Surveillance in Green IoT Applications

Safety surveillance is considered one of the most important factors in many constructing industries for green internet of things(IoT)applications.However,traditional safety monitoring methods require a lot of labor source.In this paper,we propose intelligent safety surveillance(ISS)method using a convolutional neural network(CNN),which is an autosupervised method to detect workers whether or not wearing helmets.First,to train the CNN-based ISS model,the labeled datasets mainly come from two aspects:1)our labeled datasets with the full labeled on both helmet and pedestrian;2)public labeled datasets with the parts labeled either on the helmet or pedestrian.To fully take advantage of all datasets,we redesign CNN structure of network and loss functions based on YOLOv3.Then,we test our proposed ISS method based on the specific detection evaluation metrics.Finally,experimental results are given to show that our proposed ISS method enables the model to fully learn the labeled information from all datasets.When the threshold of intersection over union(IoU)between the predicted box and ground truth is set to 0.5,the average precision of pedestrians and helmets can reach 0.864 and 0.891,respectively.

电聚合制备分子印迹电极及其特异性表征

本实验设计以邻苯二胺为功能单体,以双酚A为目标分子,采用简单快速的电聚合方法,制备了对双酚A具有特异性识别能力的分子印迹电极。采用差分脉冲伏安法和石英晶体微天平对印迹电极的特异识别性能进行表征。结果表明,印迹电极对双酚A表现出较高的特异性识别能力。与非印迹电极相比,识别能力提高一个数量级。同时,该电极对100倍浓度的阿特拉津、17β-雌二醇的信号响应仅为十分之一,表明该电极在复杂体系中具有良好的抗干扰能力。此外,该实验方案目标分子选择灵活,能制备针对不同目标分子的印迹电极,可满足自主设计实验的需求。通过该创新实验,可以有效帮助学生深入了解分子间的相互作用,体验在分子层次设计材料的过程。

Maggot homogenate is associated with neural regeneration and wound healing in the rat

BACKGROUND：Live delivery limits the clinical application of maggot therapy. To date in China, there are no in vivo reports regarding wound healing mechanisms of maggot therapy or the effects of maggot homogenate on wound nerve regeneration.OBJECTIVE：To avoid complications due to the use of live maggots, an aseptic maggot homogenate was applied. Substance P （SP） and gene protein product 9.5 expression in a cutaneous wound was analyzed to explore possible mechanisms of neural regeneration and wound healing in the rat.DESIGN, TIME AND SETTING：A random grouping and controlled animal study was performed at the laboratory of the Department of Orthopedic Surgery, First Affiliated Hospital, Dalian Medical University from August 2008 to April 2009.MATERIALS：Live maggots were cultured and provided by the laboratory of the Department of Orthopedic Surgery of the First Affiliated Hospital, Dalian Medical University, China.METHODS：A total of 48 adult rats were selected and two acute, full-thickness wounds （round, 1.5 cm diameter） were created on the back of each rat. The two wounds were randomly assigned to homogenate product and control groups. Following two-step disinfection of maggots, a homogenate was produced from 10 maggots and applied to the wound area in the homogenate product group, while the wounds in the control group were treated with normal saline alone.MAIN OUTCOME MEASURES：On days 1,3, 7, 10, 14, and 21 following injury, the wound tissue was excised. Histological examination of the wound was observed by hematoxylin and eosin staining or Masson＇s Trichrome staining. SP and protein gene product 9.5 expressions were examined by immunohistochemistry to evaluate wound neural regeneration.RESULTS：On days 7, 10, and 14, the rate of wound healing was significantly greater in the homogenate product group compared with the control group （P 〈 0.05）, and homogenate healing was better than that seen in the control group. On days 3, 7, and 10, SP expression in cells and regenerative nerves was significantly greater in the homogenate product group compared with the control group （P 〈 0.05）. On days 7 and 10, protein gene product 9.5 expression was detected in the regenerative nerve, and expression level was significantly greater in the homogenate product group compared with the control group （P 〈 0.05）.CONCLUSION：Maggot homogenate resulted in upregulated SP and protein gene product 9.5 expressions, thereby promoting neural regeneration and wound healing.

Ultrasonic Wireless Communication Through Metal Barriers

Ultrasound can be used as a carrier to realize wireless communication to and from a metal-enclosed space,which has the characteristics such as immunity to the electromagnetic shielding effect and non-destructive penetration of metal obstacles.This paper firstly reviews the previous studies in the field of ultrasonic wireless communication through metal barriers,and summarizes their achievements and the existing problems.Secondly,an overview of the research methods involved in studying the characteristic of acoustic-electric channel is presented,and the principles are introduced for the actual measurement method,equivalent circuit method,ABCD parameter method,finite element analysis method and time-domain finite difference method.Then,an overview of the communication algorithms are presented such as orthogonal frequency division multiplexing(OFDM),single-carrier frequency domain equalization and multiple input multiple output OFDM.Finally,the potential future study are proposed in light of the trend of development and unsolved problems.

Photonic neuromorphic architecture for tens-of-task lifelong learning

Scalable,high-capacity,and low-power computing architecture is the primary assurance for increasingly manifold and large-scale machine learning tasks.Traditional electronic artificial agents by conventional power-hungry processors have faced the issues of energy and scaling walls,hindering them from the sustainable performance improvement and iterative multi-task learning.Referring to another modality of light,photonic computing has been progressively applied in high-efficient neuromorphic systems.Here,we innovate a reconfigurable lifelong-learning optical neural network(L2 ONN),for highly-integrated tens-of-task machine intelligence with elaborated algorithm-hardware codesign.Benefiting from the inherent sparsity and parallelism in massive photonic connections,L2 ONN learns each single task by adaptively activating sparse photonic neuron connections in the coherent light field,while incrementally acquiring expertise on various tasks by gradually enlarging the activation.The multi-task optical features are parallelly processed by multi-spectrum representations allocated with different wavelengths.Extensive evaluations on freespace and on-chip architectures confirm that for the first time,L2 ONN avoided the catastrophic forgetting issue of photonic computing,owning versatile skills on challenging tens-of-tasks(vision classification,voice recognition,medical diagnosis,etc.)with a single model.Particularly,L2 ONN achieves more than an order of magnitude higher efficiency than the representative electronic artificial neural networks,and 14×larger capacity than existing optical neural networks while maintaining competitive performance on each individual task.The proposed photonic neuromorphic architecture points out a new form of lifelong learning scheme,permitting terminal/edge AI systems with light-speed efficiency and unprecedented scalability.

VEGF-B prevents excessive angiogenesis by inhibiting FGF2/FGFR1 pathway

Although VEGF-B was discovered as a VEGF-A homolog a long time ago,the angiogenic effect of VEGF-B remains poorly understood with limited and diverse findings from different groups.Notwithstanding,drugs that inhibit VEGF-B together with other VEGF family members are being used to treat patients with various neovascular diseases.It is therefore critical to have a better understanding of the angiogenic effect of VEGF-B and the underlying mechanisms.Using comprehensive in vitro and in vivo methods and models,we reveal here for the first time an unexpected and surprising function of VEGF-B as an endogenous inhibitor of angiogenesis by inhibiting the FGF2/FGFR1 pathway when the latter is abundantly expressed.Mechanistically,we unveil that VEGF-B binds to FGFR1,induces FGFR1/VEGFR1 complex formation,and suppresses FGF2-induced Erk activation,and inhibits FGF2-driven angiogenesis and tumor growth.Our work uncovers a previously unrecognized novel function of VEGF-B in tethering the FGF2/FGFR1 pathway.Given the anti-angiogenic nature of VEGF-B under conditions of high FGF2/FGFR1 levels,caution is warranted when modulating VEGF-B activity to treat neovascular diseases.

Carbonaceous ceramic nanofibrous aerogels for high-temperature thermal superinsulation

Ultralight ceramic aerogels are attractive thermal superinsulating materials,but display a formidable tradeoff between low and high temperature thermal conductivity(κ)due to their low-density features.Embedding carbon species as infrared opacifier in ultralight ceramic aerogels can substantially reduce the thermal radiation heat transfer without compromising the ultralow solid conduction.However,the oxidation resistance of embedded carbon species still remains inadequate to prevent thermal etching at high temperatures.Herein,we report a carbonaceous design and synthesis of ceramic nanofibrous aerogels with amorphous carbon embedded in the yttrium-stabilized zircon nanofibers to achieve a high-temperature thermal superinsulating performance with robust thermomechanical stability.The aerogels display one of the lowestκof 95 mW·m^(−1)·K^(-1)at 1,000℃in air among ultralight material family,as well as robust mechanical flexibility with up to 95%compressive strain,30%non-linear fracture strain,and 99%bending strain,and high thermal stability with ultralow strength degradation less than 1%after sharp thermal shocks(240℃·s^(-1))and working temperature up to 1,200℃.The combined high-temperature thermal superinsulating and thermomechanical properties offer an attractive material system for robust thermal insulation under extreme conditions.

Numerical study of elbow erosion due to sand particles under annular flow considering liquid entrainment

Sand particle erosion is always a challenge in natural gas production.In particular,the erosion in gas-liquid-solid annular flow is more complicated.In this study,a three-phase flow numerical model that couples the volume of fluid multiphase flow model and the discrete phase model was developed for prediction of erosion in annular flow.The ability of the numerical model to simulate the gas-liquid annular flow is validated through comparison with the experimental data.On the basis of the above numerical model,the phase distribution in the pipe was analyzed.The liquid entrainment behavior was reasonably simulated through the numerical model,which guaranteed the accuracy of predicting the particle erosion.Additionally,four erosion prediction models were used for the erosion calculation,among them,the Zhang et al.erosion model predicted the realistic results.Through the analysis of the particle trajectory and the particle impact behavior on the elbow,the cushion effect of the liquid film on the particles and the erosion morphology generation at the elbow were revealed.

Production analysis in shale gas reservoirs based on fracturing-enhanced permeability areas

Hydraulic fracturing has been widely applied in shale gas exploitation because it improves the permeability of the rock matrix.Fracturing stimulation parameters such as the pumping rate, the fracturing sequence, and the fracture spacing significantly influence the distribution of the stimulated reservoir volume(SRV). In this research, we built a numerical model that incorporates the hydraulic fracturing process and predicts gas production. The simulation of fracture propagation is based on the extended finite element method(XFEM), which helps to calculate aspects of the fractures and the SRV; we imported the results into a production analysis model as the initial conditions for production prediction. Using the model, we investigated the effects of some key parameters such as rock cohesion, fracture spacing, pumping rate, and fracturing sequence on the shale gas production.Our results proved that the SRV was distributed in the vicinity of the main fractures, and the SRVs were connected between the fractures in a small fracture spacing. We obtained optimal spacing by analyzing the production increment. High pumping-rate treatment greatly changes the in-situ stress around the hydraulic fractures and enlarges the field of SRV. Simultaneous fracturing treatment improves the flow conductivity of formation more than sequential fracturing. This study provides insights into the hydraulic fracturing design for economical production.

Antitumor mechanism of Se-containing polysaccharide,a novel organic selenium compound

Recent studies on the inhibition of tumor growth by Se-containing polysaccharide were reviewed.Meanwhile,the possible molecular mechanisms of the inhibition of tumor cell growth through antioxidation,induction of tumor cell apoptosis,blockade of cell cycle,and enhancement of immunity by Se-containing polysaccharide were proposed.In the end,the potential application of Se-containing polysaccharide in the prevention and treatment of tumor was elucidated.

Epidemic modeling for the resurgence of COVID-19 in Chinese local communities

COVID-19 is a constantly challenging global health issue due to its strong intensity,rapid mutation and high infectiousness.The new Delta and Omicron variants have triggered massive outbreaks worldwide.Even China,which has done a good job in outbreak prevention,is still heavily affected by the virus.The long-term fight against multiple COVID-19 outbreaks is ongoing.In this study,we propose an SEIQR model that considers the incubation period and quarantine measurement.We verified our model using actual outbreak data from four Chinese cities.Numerical simulations show that a five-day delay results in a double resurgence scale.Our model can be used as a tool to understand the spread of the virus quantitatively and provide a reference for policymaking accordingly.