Abstract:

Organic red luminogens are seriously bound by that of the energy gap law, giving rise to severe nonradiative decay of excited state and consequently low photoluminescence quantum yield (ΦPL). Herein, two red anthraquinone-based luminogens, AQ-2DPAC and AQ-2PDPAC, are synthesized by using different linking modes between the electron donor and the electron acceptor (D-A) with or without the phenyl ring as π-bridge. Their electronic structures, thermal properties, photophysical properties, and electroluminescent properties are investigated systematically to assess the impact of the phenyl bridge on their photoluminescence properties. Both highly twisted luminogens exhibit obvious aggregation-induced emission and delayed fluorescence features, and the elongation of D-A separation distance via the introduction of phenyl bridge can simultaneously decrease singlet-triplet energy splitting, enhance fluorescence decay rate and consequently increase ΦPL. Therefore, the ΦPL of D-π-A-type AQ-2PDPAC (52%) is much larger than that of D-A-type AQ-2DPAC (19%). The organic light-emitting diode employing AQ-2PDPAC as emitter realizes a high maximum external quantum efficiency of 13.7%, and a maxima luminance of 12 260 cd·m－2.

Abstract:

Space environment can cause damage to astronauts, therefore, it is critical to monitor the physiological indicators with the purpose to study the damage mechanisms and means of protection. As a special space environments, microgravity can lead to mitochondrial dysfunction. Since mitochondrial membrane potential is an important indicator of normal mitochondria, as a result, it is meaningful to monitor mitochondrial membrane potential under simulated microgravity (SMG) quickly and easily. In this work, a mitochondria-targeting aggregation-induced emission (AIE) probe (TPE-Ph-In) is developed to monitor mitochondrial membrane potential under SMG. In order to overcome the problem of insecure cell apposition under a prolonged time of SMG, an AIE probe-hydrogel 3D imaging system is constructed by seeding the cells into Matrigel and imaging the cells with TPE-Ph-In. This work provides a new approach to investigate the cells under microgravity environment.

Abstract:

Aggregation-induced emission molecules have been widely used in the fields of biological imaging, optical waveguide and electroluminescence due to their high luminescence efficiency, but are rarely reported in the field of optical data storage. Compared with other optical storage materials, aggregation-induced emission molecules own significant developmental advantages for super-resolution optical data storage. In this study, the possible applications in super-resolution optical data storage of the aggregation-induced molecules are discussed.

Abstract:

Structural magnetic resonance imaging based autism spectrum disorder classification is important nowadays for early-stage screening and accurate diagnosis of autism spectrum disorder. However, due to the limitation of large data noise and small data volume, the predictive accuracy of structural magnetic resonance imaging based autism classification is not ideal. In this study, a new data augmentation model is proposed to improve classification accuracy without increasing training data volume. The University of Michigan sample 1 dataset of autism brain imaging data exchange I for autism study was used for training and evaluating the proposed model. 78 samples of the University of Michigan sample 1 dataset was selected randomly for performing the experiment, and the performance improved using proposed data augmentation algorithm for autism spectrum disorder classification task was calculated. Such a procedure was repeated for 500 times to collect results that are statistically significant. Based on the results, this method can stably improve classification accuracy between 10% and 20% in 494 out of 500 experiments (over 98% of the experiments). Through a comparative study of accuracy improvement and label change ratio, the problem of data label noise was explored.

Abstract:

In system-on-chip (SoC) chip, due to the differences in frequencies and activities of various functional components, uneven heat generation distribution has become a serious problem, which adversely affects the reliability and overall lifespan of the chip. To address this concern, a multi-region temperature acquisition and control system for SoC chip is designed. Firstly, the on-chip bus technology is used for distributed multi-region temperature acquisition to obtain multi-region temperature information of SoC chip. Secondly, a temperature control mechanism is designed, which can both satisfy the need of both local or global temperature control. Based on the real-time data of the temperature acquisition stage, this mechanism coordinates the underclocking, interrupt, and pulse width modulation intelligent cooling system to manage and control the temperature of the chip. Additionally, users are allowed to adjust system parameters through the master control program, which makes the system compatible with various temperature control scenarios. In this study, the experiment was carried out in a large-scale multi-core SoC platform for temperature control system. The experimental results show that the proposed temperature control system can effectively slow down the chip temperature rise rate during SoC operation. Meanwhile, the maximum temperature of the chip area is controlled within the extreme high temperature critical value set by the user within the range of ±3 ℃, indicating that the temperature control system is feasible for SoC chip temperature control.

Abstract:

The excessive glutamate-induced neuroexcitotoxicity has been widely thought as the main cause of brain cell damage in severe neurological diseases (such as ischemic stroke). Electrochemical technology is the most commonly used tool for glutamate monitoring at present. It could be applied to provide rapid and accurate assessment of the neuroexcitotoxicity for patients and animal disease models. Research advances in glutamate sensors will be important in establishing efficient therapies and brain protection strategy, and developing new drugs for severe neurological diseases. Application of nanotechnology, new enzymes, photolithography, printing, transistor technology in fabrication of glutamate sensors have greatly boosted developments in electrochemical monitoring of glutamate. In the present paper, research progress of sensing principles, design and preparation technology as well as the applications in medical studies have been reviewed, and future trends and prospective have also been discussed.

Abstract:

Thrombin-antithrombin complex (TAT) is the product of coagulation and anticoagulation balance. Its detection reflects thrombin status and can be used as an auxiliary in the diagnosis of thrombotic diseases. A chemiluminescence immunoassay method was established to analyze TAT in human plasma samples, and its analytical performance was evaluated. The TAT was used as immunogen for monoclonal antibody preparation. TAT measurement method was established using double antibody sandwich format. After the optimization of reaction, the bulk reagent concentrations of magnetic microparticle coated with antibody and acridinium labeled antibody were 0.20 g/L and 0.2 mg/L, respectively, and the sample size was 50 μL. The reaction of magnetic particle coated antibody and sample were incubated for 5 min at 37 ℃, and 5 min for subsequent reacting with the antibody labeled with acridinium. There was no cross-reaction with samples containing 0.20 mg/mL prothrombin or 0.31 mg/mL antithrombin Ⅲ. Besides, there was a high correlation (r＞0.95) between this method and TAT test kit of Sysmex. LoB is less than or equal to 0.20 ng/mL. LoD is less than or equal to 0.40 ng/mL. The linear correlation coefficient is 0.998 in the detection interval of 0.40 to 120 ng/mL, and the accuracy is within the range of ±8%. A quantitative chemiluminescence immunoassay method for TAT measurement has been established, and the performance meets customer needs for clinical utility.

Abstract:

Developing efficient Ni based hydrogenation catalysts to achieve the directional synthesis of 1,4-butanediol from 1,4-butynediol hydrogenation is the keypoint to building a high value extension industrial chain for coal based primary chemicals. Aiming at solving the problems of Raney Ni catalyst widely used at present, such as lacking support, low activity specific surface area, and poor hydrogenation selectivity, a Ni/ AC catalyst with well-developed pore structure activated carbon (AC) as support was prepared in this work, and the structure-activity relationship between catalyst structure and performance was discussed by combining characterization methods. The results showed that with the increase of Ni loading, the active nickel species exposed on the activated carbon surface increased at first and decreased later, and the hydrogenation activity also show as volcanic distribution. The 25% Ni/AC catalyst loaded with 25% Ni had the highest selectivity of 1,4-butanediol, reaching 86.2%. At this time, the selectivity of 1,4-butenediol and 2-hydroxytetrahydrofuran, the semi hydrogenation products, were 1.2% and 6.8%, respectively. Due to the highly dispersed active Ni species in this sample, a large amount of active hydrogen is provided, which promotes the hydrogenation reaction. Due to the long distance between Ni active centers and the low density of surface active H on catalysts with low Ni loading, isomerization side reactions are prone to occur to generate 2-hydroxytetrahydrofuran. At high Ni loading, the aggregation of Ni species results in the decrease of hydrogenation activity.

Abstract:

Glass through-hole adapter plate is a typical vertical transmission structure widely used in threedimensional integrated package circuits. Based on the demand of radio frequency signals for the use of smalldiameter, narrow-pitch vertical vias, glass vias with a depth-to-width ratio of 8∶1 and a minimum diameter of 25.68 μm were obtained based on a photosensitive glass substrate using ultraviolet exposure, heat treatment, and wet etching methods. The mechanism of modification of photosensitive glass during the exposure process was obtained by studying the effect of exposure amount on the through-hole preparation process of photosensitive glass through-hole preparation. The experimental results show that with the increase of exposure, the throughhole aperture increases, and the photosensitive glass modification process is a gradual modification process from the front to the back side from the surface to the inside. This provides key process support for the preparation of glass through-hole adapter plates.

Abstract:

In the research of face anti-spoofing (FAS), most related techniques are dependent to the RGB images or IR images, which lack sufficient biometric features and are vulnerable to ever-advancing presentation attacks. In this paper, a Transformer model based on combination of multiple facial regions is proposed to introduce multispectral technology into the task of facial live detection, aiming to obtain unique biological features of the real faces and increase the distinguishability from the fake faces. In the proposed model, multi-spectral images are utilized to broaden the spectral dimension for more reflection information, which can identify various materials. Besides, a spectral normalization method is preprocessed pixel by pixel to reduce the impacts of the environmental illumination variations and enhance the consistency of facial reflection features regionally. Then multiple core facial regions, like eyes, nose, mouth and cheeks, are selected as input of the deep learning model. Furthermore, a Transformer-based model is constructed to obtain both local regional features and inter association features of different facial regions, which are integrated into complete facial biometric features to achieve facial live detection. On the author''s self-built multispectral facial datasets, the results show that the proposed method achieved an accuracy of 95.72% for and a misclassification of 5.1% for live detection, which is superior to commonly used FAS models.

Abstract:

AlphaFold, which is developed by DeepMind, has made amazing advances in predicting protein structures for life sciences research. Using the vast structural predictions made possible by AlphaFold, a database of over 200 million proteins has been established. Such a database covers the complete proteomes of many organsims. This review outlines the most recent progresses in exploring protein evolution using statistical physical methods based on the AlphaFold database. Traditional protein evolution research often concentrates on the sequences or structures of proteins within the same family, using a narrow microscopic approach. With the new emergence of extensive protein structure predictions by AlphaFold, whereas, scientists can expand their horizons to include vast assortments of proteins to make parallels with all proteins in different species and extract statistical trends through macroscopic observation. By comparing the proteins with similar chain lengths in over 40 model organisms, the statistical trends in protein evolution is discovered. For organisms with higher complexity, their constituent proteins present larger radii of gyration, higher flexibility, and higher segregation of hydrophobic and hydrophilic residues in both spatial and sequence. It is also validated by statistical physics analysis that higher organismal complexity correlates with higher functional specialization of constituent proteins. The findings in these studies connect molecular evolution to organism evolution, contributing to the understanding of the origin and evolution of lives.

Abstract:

In the automatic driving systems, logarithm function has been widely used. For example, logarithm function is often used to design loss function in deep learning or convolutional neural network, which serves as the basis for the automatic driving perception system. Therefore, studying the history of invention of logarithm is of great significance to master the concept and application. This paper studies the definition of Napier""s logarithm and his three tables, analyzes two kinds of proof methods of predecessors, and puts forward new proof methods based on the exponential function. Meanwhile, this paper also analyzes Napier""s calculation method. Compared with other alternative methods, the optimization results of Napier""s interval approximation are given. The calculation by MPRF library shows that Napier""s method is more convergent to the true value.

Abstract:

Abstract: Chaos LiDAR has attracted significant attention due to its high resolution, inherent anti-interference capability, and stealth characteristics. However, the performance of chaos LiDAR in long-range target detection and imaging is quite limited by the power of chaotic light sources, sensitivity of linear detectors, and hardware bandwidth. To overcome the bottleneck of chaos LiDAR, this paper proposes the concept of Digital chaos LiDAR and conducts theoretical analysis and simulation verification. Through Monte Carlo simulation, we studied the detection probability, false probability, and detection range of Continuous-wave chaos LiDAR, Pulsed chaos LiDAR, and Digital chaos LiDAR. The simulation results show that, within the confidence interval where the detection probability is greater than 95% and the false alarm probability is less than 5%, the detection range of digital chaos LiDAR is approximately 35 times and 8 times higher than that of continuous-wave chaos LiDAR and pulsed chaos LiDAR, respectively. With the advantages of ultra-high sensitivity of single-photon detectors and digital output, digital chaos LiDAR is expected to be widely used in the field of long-range target detection and imaging.

Abstract:

The early stage of many ophthalmic diseases is usually accompanied by morphological and hemodynamic changes of microvessles. Thus, evaluation of the whole eye microvessels plays an important role in the comprehensive diagnosis of ophthalmic diseases. Due to the limited penetration depth of optical imaging techniques, especially in the case of low transmittance of the medium, it is difficult for existing optical imaging techniques to visualize the microvessels of the entire eye. For this purpose, we developed an ultrasound super-resolution imaging technique that can visualize the whole eye three-dimensional microvascular system with micron resolution. Specifically, a linear array with a central frequency of 10MHz was used to rapidly acquire multi-frame sequences, and then a super-resolution image of a slice was obtained through microbubble signal extraction, localization, tracking and center point superposition. All the acquired slices were reconstructed into three-dimensional full-eye super-resolution microvascular images. In vivo experiment demonstrates that ultrasound localization microscopy (ULM) can visualize the microvascular system of the entire eye, which is important for early diagnosis of ophthalmic diseases.

Abstract:

The coronavirus SARS-CoV-2 remains stable and highly infective in water for a long time, which makes the removal of virus from water an important approach to contain and block its spread. In this study, an antibody-engineered microrobot (AB-robot) was fabricated by using click chemistry to functionalize self-actuating Bacillus subtilis with neutralizing antibody P2C-1F11 against the SARS-CoV-2 S protein. The AB-robot can efficiently capture and remove SARS-CoV-2 from water by targeting SARS-CoV-2 S protein with P2C-1F11. The AB-robot displays rapid self-actuation capability in various aquatic media, including drinking water and tap water. And the virus clearance percentage of AB-robot in water was up to 95% against SARS-CoV-2 pseudovirus contaminant model. Moreover, scanning electron microscopy images show that a large number of virus particles were tethered to the surface of the AB-robot, further demonstrating the effective capture capability of the AB-robot. In summary, the significant contributions of both the P2C-1F11 for virus targeting and the fast microrobot motion for contacting the virus toward immediate capture and efficient removal of SARS-CoV-2 pseudovirus, which has potential application for preventing and blocking the spread of SARS-CoV-2 in water.

Abstract:

Hydrogen can selectively remove cytotoxic reactive oxygen species. The presence of hydrogen in cancer cells can affect the balance of reactive oxygen species in cancer cells, leading to apoptosis of cancer cells. In addition, hydrogen has innate advantages over drugs since it is harmless to the human body and can highly penetrate cell membranes. However, due to the diffusion of hydrogen in the body without purpose, it is difficult to achieve good curative effect by oral hydrogen-rich water and injection hydrogen-rich saline. In this paper, the mechanism of hydrogen therapy is briefly introduced, where two kinds of main nanosystems for hydrogen delivery in hydrogen therapy are introduced by enumerating some current methods of nanomaterials-based hydrogen therapy. In the end, the future of nanomaterials in cancer hydrogen therapy is prospected.

Abstract:

The flame-retardant gel polymer electrolytes present great potential for application in alkali metal batteries due to their high safety characteristics, such as good ability of dendrite inhibition, non-leakage, and non-flammability. This paper reviews the advances of flame-retardant gel polymer electrolytes in various alkali metal batteries, including lithium, sodium, aluminum, zinc, etc. The paper first discusses the flame-retardant mechanism of gel polymer electrolytes. Subsequently, the common preparation methods of flame-retardant gel polymer electrolytes are highlighted. Furthermore, the advancements of different-type flame-retardant gel polymer electrolytes in different alkali metal battery systems are symmetrically discussed. Finally, their current challenges and potential development directions are significantly proposed.

Abstract:

Logic Built In Self-Test (LBIST) is a technique in design for testability (DFT) that utilizes components of a circuit within a chip, board, or system to conduct self-testing of the digital logic circuit. LBIST plays a critical role in various applications, particularly those that are vital for life and mission, such as defense, aerospace, and autopilot systems. These applications necessitate the implementation of on-chip, on-board, or in-system self-checks to enhance the overall system reliability and enable remote diagnostics. This article first presents the commonly used LBIST classifications and describes the classic and most successful LBIST architecture used in the industry, STUMPS. Then, it summarizes the research teams and research progress at home and abroad. Then, it analyzes in detail the key technical points of LBIST such as the basic principle, timing control, deterministic self-test design, low-power design, X-tolerance, and lists mainstream LBIST business tools, the software architecture and technical characteristics of LBIST are analyzed one by one. Finally, the problems that need to be further solved in current LBIST technology are discussed and prospects are made.

Abstract:

Photonic nanojets (PNJs) are high intense, tightly focused light beams on the shadow side surface of lossless dielectric microparticles when the size of the particles is approximately equal to or slightly larger than the wavelength of the incident light. PNJs exhibit exceptional characteristics, including higher intensity than the incident light, minimum beamwidth less than the diffraction limit, propagation beyond the evanescent field region and strong backscattering. These properties make PNJs crucial in various applications such as optical signals enhancement, micro-/nano- processing and manufacturing, super-resolution optical imaging, ultra-sensitive trapping and sensing, among others. This review article begins by introducing the origins and discovery of PNJs, followed by a description of their modeling, nanojet theory, morphology features, experimental measurements, and key properties. Subsequently, it conducts a survey and discussion of several important applications of PNJs. Finally, the article concludes with a summary and prospects for the future of PNJs.

Abstract:

This is an efficient fuel-saving product based on the resonance principle，which is an external energy-saving device customized for logistics companies, transportation fleets, and individual vehicle owners. The product is designed to address the issues of improving engine thermal efficiency and reducing fuel losses. Based on the principles of wave and resonance, a pulse technology and self-vector resetting technology are proposed to improve the combustion efficiency. Mainstream brand vehicle tests have shown that the fuel efficiency of various brand vehicles has been effectively improved (6.15%-11.16%) in the testing range of 1000 km-4000 km, with the highest reaching 11.16% and the highest fuel saving per 100 kilometers being 3.29 liters. At the same time, theoretical analysis based on the design principle shows that the fuel-saving efficiency will gradually improve and eventually reach a stable optimum value after a certain adaptation period.

Abstract:

In System-on-Chip(SoC) chip, due to the differences in frequencies and activities of various functional components, uneven heat generation distribution has become a serious problem, which adversely affects the reliability and overall lifespan of the chip. To address this concern, a multi-region temperature acquisition and control system for SoC chip is designed. Firstly, the on-chip bus technology is used for distributed multi-region temperature acquisition to obtain multi-region temperature information of SoC chip. Secondly, a temperature control mechanism is designed, which can both satisfy the need of both local or global temperature control. Based on the real-time data of the temperature acquisition stage, this mechanism coordinates the underclocking, interrupt, and PWM intelligent cooling system to manage and control the temperature of the chip. Additionally, Users are allowed to adjust system parameters through the master control program, which makes the system compatible with various temperature control scenarios. In this study, the experiment was carried out in a large-scale multi-core SoC platform for temperature control system. The experimental results show that the proposed temperature control system can effectively slow down the chip temperature rise rate during SoC operation. Meanwhile, the maximum temperature of the chip area is controlled within the extreme high temperature critical value set by the user within the range of ±3℃, indicating that the temperature control system is feasible for SoC chip temperature control.

Abstract:

Structural-MRI based autism spectrum disorder classification is important nowadays for early-stage screening and accurate diagnosis of autism spectrum disorder. However, due to the limitation of large data noise and small data volume, the predictive accuracy of structural-MRI based autism classification is not ideal. In this study, a new data augmentation model is proposed to improve classification accuracy without increasing training data volume. The UM1 dataset of ABIDE I for autism study was used for training and evaluating the proposed model. 78 samples of the UM1 dataset was selected randomly for performing the experiment, and the performance improved using proposed data augmentation algorithm for ASD classification task was calculated. Such a procedure was repeated for 500 times to collect results that are statistically significant. Based on the results, this method can stably improve classification accuracy between 10% and 20% in 494 out of 500 experiments (over 98% of the experiments). Through a comparative study of accuracy improvement and label change ratio, the problem of data label noise was explored.

Abstract:

Glass through-hole adapter plate is a typical vertical transmission structure widely used in three-dimensional integrated package circuits. Based on the demand of RF signals for the use of small-diameter, narrow-pitch vertical vias, glass vias with a depth-to-width ratio of 8:1 and a minimum diameter of 25.68 μm were obtained based on a photosensitive glass substrate using UV exposure, heat treatment, and wet etching methods. The mechanism of modification of photosensitive glass during the exposure process was obtained by studying the effect of exposure amount on the through-hole preparation process of photosensitive glass through-hole preparation. The experimental results show that with the increase of exposure, the through-hole aperture increases, and the photosensitive glass modification process is a gradual modification process from the front to the back side from the surface to the inside. This provides key process support for the preparation of glass through-hole adapter plates.

Abstract:

Developing efficient Ni based hydrogenation catalysts to achieve the directional synthesis of 1,4-butanediol from 1,4-butynediol hydrogenation is the keypoint to building a high value extension industrial chain for coal based primary chemicals. Aiming at solving the problems of Raney Ni catalyst widely used at present, such as lacking support, low activity specific surface area, and poor hydrogenation selectivity, a Ni/AC catalyst with well-developed pore structure activated carbon (AC) as support was prepared in this work, and the structure-activity relationship between catalyst structure and performance was discussed by combining characterization methods. The results showed that with the increase of Ni loading, the active nickel species exposed on the activated carbon surface increased at first and decreased later, and the hydrogenation activity also show as volcanic distribution. The 25% Ni/AC catalyst loaded with 25% Ni had the highest selectivity of 1,4-butanediol, reaching 86.2%. At this time, the selectivity of 1,4-butanediol and 2-hydroxytetrahydrofuran, the semi hydrogenation products, were 1.2% and 6.8%, respectively. Due to the highly dispersed active Ni species in this sample, a large amount of active hydrogen is provided, which promotes the hydrogenation reaction. Due to the long distance between Ni active centers and the low density of surface active H on catalysts with low Ni loading, isomerization side reactions are prone to occur to generate 2-hydroxytetrahydrofuran. At high Ni loading, the aggregation of Ni species results in the decrease of hydrogenation activity.

Abstract:

The coronavirus SARS-CoV-2 remains stable and highly infective in water for a long time, which makes the removal of virus from water an important approach to contain and block its spread. In this study, an antibody-engineered microrobot (AB-robot) was fabricated by using click chemistry to functionalize self-actuating Bacillus subtilis with neutralizing antibody P2C-1F11 against the SARS-CoV-2 S protein. The AB-robot can efficiently capture and remove SARS-CoV-2 from water by targeting SARS-CoV-2 S protein with P2C-1F11. The AB-robot displays rapid self-actuation capability in various aquatic media, including drinking water and tap water. And the virus clearance percentage of AB-robot in water was up to 95% against SARS-CoV-2 pseudovirus contaminant model. Moreover, scanning electron microscopy images show that a large number of virus particles were tethered to the surface of the AB-robot, further demonstrating the effective capture capability of the AB-robot. In summary, the significant contributions of both the P2C-1F11 for virus targeting and the fast microrobot motion for contacting the virus toward immediate capture and efficient removal of SARS-CoV-2 pseudovirus, which has potential application for preventing and blocking the spread of SARS-CoV-2 in water.

Abstract:

The excessive glutamate-induced neuroexcitotoxicity has been widely thought as the main cause of brain cell damage in severe neurological diseases (such as ischemic stroke). Electrochemical technology is the most commonly used tool for glutamate monitoring at present. It could be applied to provide rapid and accurate assessment of the neuroexcitotoxicity for patients and animal disease models. Research advances in glutamate sensors will be important in establishing efficient therapies and brain protection strategy, and developing new drugs for severe neurological diseases. Application of nanotechnology, new enzymes, photolithography, printing, transistor technology in fabrication of glutamate sensors have greatly boosted developments in electrochemical monitoring of glutamate. In the present paper, research progress of sensing principles, design and preparation technology as well as the applications in medical studies have been reviewed, and future trends and prospective have also been discussed.

Abstract:

Thrombin antithrombin (TAT) complex is the product of coagulation and anticoagulation balance. Its detection reflects thrombin status and can be used as an auxiliary in the diagnosis of thrombotic diseases. A chemiluminescence immunoassay method was established to analyze TAT complex in human plasma samples, and its analytical performance were evaluated. The TAT complex was used as immunogen for antibody preparation. TAT measurement method was established using double antibody sandwich format. After the optimization of reaction, the bulk reagent concentrations of magnetic microparticle coated with antibody and acridinium labeled antibody were 0.20 mg/mL and 200 ng/mL, respectively, and the sample size was 50 μL. The reaction of magnetic particle coated antibody and sample were incubated for 5 min, and 5 min for subsequent reacting with acridine ester labeled antibody. There was no cross-reaction with samples containing 0.20 mg/mL prothrombin or 0.31 mg/mL antithrombin Ⅲ. Besides, there was a high correlation (R > 0.99) between this method and TAT test kit of Sysmex. A quantitative chemiluminescence immunoassay method for TAT measurement has been established, and the performance meets customer needs for clinical utility.

Abstract:

A thermoelectric energy conversion system could realize a direct conversion between thermal and electrical energy. The thermoelectric module composes a thermal resistance network with the hot and cold side heat exchangers within an integrated thermoelectric system. The heat transfer between the network and the heat source/sink is critical to the system performance. In this paper, we analyze the effect of external heat transfer on the system internal temperature distribution based on the coupled heat transfer relationship among different nodes in the thermal resistance network, and derive a set of analytical formulae of the system performance in practical thermal environments. Furthermore, a direct relationship between the external heat transfer conditions and the peak output power of the system is uncovered, and a general strategy for quickly designing thermoelectric energy conversion systems is proposed.

Abstract:

Major science and technology infrastructure is a "national tool" to build China into a world science and technology power. It can sustainably promote the output of major original achievements, accelerate the integration of innovation factors, and make breakthroughs in high-end industries. With the development of a new round of scientific and technological revolution and the advance of economic globalization, international competition is becoming increasingly complicated, and the development of major scientific and technological infrastructure has entered a new stage and faced new challenges. The profound change of scientific research paradigm and the rapid development of interdisciplinary integration will put forward higher requirements for the construction level of major scientific and technological infrastructure. By sorting out and analyzing the current situation of major science and technology infrastructure construction, analyzing the new development situation of big science and technology devices, as well as the challenges faced by operation and management, this paper focuses on the problems faced by major science and technology infrastructure development and management bottlenecks. To explore the development path of efficient management mechanism for big science and technology facilities in the future from three dimensions of strategy, policy and management, such as the development of appropriate measures and management policies for major science and technology infrastructure operation, the closeness between national forward-looking deployment and major national needs, the innovative organization and management mode with multi-body participation, and the open and shared international cooperation mechanism. It is of reference significance for improving the construction, operation and management level of major science and technology infrastructure, strengthening major original innovation capacity, building a powerful country in science and technology, and realizing self-reliance and self-improvement of high-level science and technology at an early date.

Abstract:

Aggregation-induced emission molecules have been widely used in the fields of biological imaging, optical waveguide and electroluminescence due to their high luminescence efficiency, but are rarely reported in the field of optical data storage. Compared with other optical storage materials, aggregation-induced emission molecules own significant developmental advantages for super-resolution optical data storage. In this study, the possible applications in super-resolution optical data storage of the aggregation-induced molecules are discussed.

Abstract:

Terahertz wave is defined as the far-infrared electromagnetic (EM) radiation between 0.1 and 10 THz. It has attracted increasing attention in both fundamental research and technological applications for its unique characteristics. In terahertz telecommunication, radar and imaging systems, terahertz antenna is key for the performance. To date, reported terahertz antennas suffer from limited phase modulation, relatively low efficiency and small beaming angle. Here we address these challenges by first designing three types of terahertz graphene antennas with the smallest size of 5 μm. We then propose a novel type of antenna with dual resonances, and achieve dynamic phase modulation within the full 2π range and meanwhile high efficiency above 20%. This performance surpasses antennas with single resonance since dual resonances alleviate the contradiction between large phase modulation range and high efficiency. We prepared terahertz graphene antennas with standard micro-fabrication processes, and experimentally obtained terahertz dynamic phase modulation of 1.03 THz with reflection efficiency above 23%, which agree with the simulation results. Making use of the phase modulation metasurfaces tuned according to continuous phase coding, we numerically realized terahertz beam steering with dynamic range of -25°~25°. We expect this work will provide a strategy for achieving large-range phase modulation and beam steering beyond the terahertz regime.

Abstract:

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to notable advancements in the pharmaceutical sector regarding the development of mRNA vaccines. These vaccines have gained considerable attention given their straightforward production process, improved safety profile compared to DNA vaccines, and efficient expression of mRNA-encoded antigens within cells. In addition, mRNA vaccines offer the advantage of not requiring transcription within the nucleus, thereby eliminating the risk of integration into the host genome. Nevertheless, mRNA vaccines also have limitations, such as possible allergy, kidney failure, and other serious side effects, or may rapidly degrade after injection or cause a cytokine storm. These factors present substantial challenges concerning the immunogenicity and delivery of mRNA vaccines. The purpose of this article is to primarily focus on the molecular design, delivery systems, and current clinical status of mRNA vaccines, aiming to provide valuable insights for future advancements in this field.

Abstract:

Chemerin, derived from tazarotenib-induced gene2 (TIG2), is an endogenous ligand for the orphan G protein-coupled receptor chemokine-like receptor 1 (CMKLR1). Chemerin/CMKLR1 signaling system plays an important role in multiple tissues and organs，and there are multiple chemerin isoforms in vivo due to the C-terminal proteolysis by several proteases. In this paper, we predicted and modeled the structure of six isoforms of chemerin by Alphafold, and modeled three active isoforms in complex with CMKLR1,to elucidate the different binding sites of different isoforms. Additionally,the known small molecule antagonist of CMKLR1, 2-(α-naphthoyl) ethyltrimethylammonium iodide (α-NETA), was also modeled to dock with CMKLR1, and the binding sites of α-NETA with CMKLR1 were analyzed. From the protein molecular structure level, our results provide: 1. The mode of interaction between active Chemerin and CMKLR1；2. The mode of interaction between α-NETA and CMKLR1. This study provides theoretical basis and experimental basis for the design of targeted drugs for CMKLR1.

Abstract:

As a representative low-level vision problem, image super resolution (SR) aims to reconstruct the high-resolution image from its low-resolution counterpart. For a long time, the analysis of SR tasks is based on the whole image, while little works observe the input partition. In this paper, we find that the restoration quality of a certain position is inseparable from its surrounding image background. This phenomenon provides us a new perspective to explain the networks by splitting the input image. We construct a new hybrid dataset, of which the foreground and background contain only one kind of texture information. And then, we prove that the similar background could benefit the network restoration. By analyzing similarity and difference between the attention mechanism and the traditional CNN network, we show that the attention structure could help the network focus on long-range effective information. Moreover, a data enhancement method to improve the network final performance and potential future works are also proposed.

Abstract:

Robots are important equipment in modern industrial manufacturing and production. As products move towards small batch, multi-variety, and flexibility, robot collaboration systems based on multi-information fusion enable high-end precision manufacturing industries. This research focuses on the precision alignment and insertion technology of a hand-eye cooperation system in the field of precision electronic component assembly. By establishing a contact state model between electronic components and heterogeneous plates, the motion characteristics of force and displacement are analyzed. A compound control algorithm integrating visual, force sense, and encoder information is proposed, combined with visual inspection and tracking technology. Component insertion comparison experiments and assembly experiments based on algorithm fusion are carried out on the electronic component assembly platform. The results show that the positioning accuracy in the alignment phase is within 0.185 pixels. The contact state judgment and adjustment algorithm in the assembly stage ensures the safe and effective assembly of components.

Abstract:

Over the past several decades，Brain-computer interfaces have made remarkable progress.In terms of the capability of implementing the technology and the functional scenarios it serves, Brain-computer interfaces technology will soon face clinical application.In this process, there will be new challenges in translating scientific achievements into commercial products.In this paper, We first introduced the characteristics of electroencephalogram, electrocortical graph, and intracortical electrical signal commonly used in Brain-computer interfaces.Then,we describe the decoding capability and the bidirectional closed-loop of information, and discuss the stability and biocompatibility problems of designing commercial brain-computer interface products.At the end of the article, we discuss the policy, fund and technical route in the industrialization development.This review aims to discuss the challenges faced by brain-computer interface technology in the process of application for the medical field, and the corresponding technical route and industrial development plan.

Abstract:

The purpose of automatic judgment document summarization is to allow computers to automatically select, extract, and compress important information from legal texts so as to reduce workload of practitioners. Currently, most summarization algorithms based on pre-trained language models have limitations on the length of the input text, so they cannot effectively summarize long texts. In this thesis, we propose a new extractive summarization algorithm, which uses a pre-trained language model to generate sentence vectors. Based on the Transformer encoder structure, the summarization task can be completed by fused information including sentence vectors, position and length of sentences. Experimental results showed that, the algorithm can effectively handle the task of summarizing long texts. In addition, the model was tested on the 2020 CAIL (Challenge of AI in Law) summarization dataset, and results showed that compared to the baseline model, the proposed model showed significant improvement in the ROUGE-1, ROUGE-2, and ROUGE-L metrics.

Abstract:

In augmented reality, virtual reality and the metaverse, three dimensional (3D) reconstruction technologies play important roles in acquiring the content information. Among them, the structured light method has been widely used due to the advantages of high precision and not being affected by the texture of the surface material on the object. Traditional structured light 3D reconstruction mainly uses digital light processing (DLP) based projectors to project coded patterns. However, the shortcomings of DLP projectors such as large size, high power, and high price limit their applications. Therefore, more 3D scanning systems start to use a micro-electro-mechanical system (MEMS) mirror as a structured light projector, which has small size, low cost, and high frame rate. In this paper, the phase-height model is proposed to complete the 3D scanning system based on MEMS mirror. To deal with the noise caused by the speckle effect, anti-noise performance of three time-phase unwrapping algorithms commonly used for MEMS mirror are experimentally compared. Results show that the multi-frequency hierarchical method and the negative exponential fitting method show better anti-noise capability and higher precision, while the multi-frequency heterodyne method shows poor anti-noise performance. This study provides a guide in choosing proper phase resolution method for MEMS based 3D scanning systems.

Abstract:

Space special environment can cause potential damage to astronauts, thus the monitoring of physiological indicators is crucial for the study of damage mechanisms and means of protection. Microgravity as one of the space special environments can lead to mitochondrial dysfunction. Meanwhile, mitochondrial membrane potential is an important indicator of normal mitochondria, it is meaningful to monitor mitochondrial membrane potential under simulated microgravity (SMG) quickly and easily. In this work, a mitochondria-targeting aggregation-induced emission (AIE) probe (TPE-Ph-In) is developed to monitor mitochondrial membrane potential under SMG. At the same time, in order to overcome the problem of insecure cell apposition under a prolonged time of SMG, an AIE probe-hydrogel 3D imaging system is constructed by seeding the cells into Matrigel and imaging the cells with TPE-Ph-In. This work provides a new method and idea to investigate the microgravity effect of cells.

Abstract:

Nowadays, with the rapid development of the Internet, more and more new applications appear gradually, the scale of network expand constantly, and the architecture of network is more and more complicated. As one of the basic technologies for enhancing network controllability, traffic classification can not only provide better QoS for ISPs, but also supervise and manage network effectively, which can ensure the security of the Internet. In this paper we review the research methods and achievements in the field of traffic classification, compare these traditional methods, and point out their advantages and disadvantages. On the other hand, for the real challenges of real-time classification of high-speed network environment, encrypted traffic classification, fine-grained traffic classification, and dynamically changed protocols classification, we describe and analyze the related research progress. Finally, we look ahead the future research direction.

Abstract:

The technology of the robot represents a national high-tech level and the degree of automation. It is helpful to develop the industry of service robots in China if we know the current situation and development trend of service robots research clearly. Recently, robotic cleaners and educational robots have been in great demand. Entertainment robots and surveillance robots are developed rapidly and the market expands quickly. Medical robots begin to enter the modern life and have played an important role in the modern surgery. To satisfy the great market and shorten the distance between China and developed countries, it is necessary to capture the development trend of the technology of service robots. R&D on service robots should focus on the integrated technologies on intelligence, modularization and network.

Abstract:

Gene is the genetic material basis. All life phenomena, like disease and death, are related to Gene. Gene sequencing is a way to read life. With the development of new generation high-throughput sequencing technology, TB or more sequence data will be generated daily. It’s more difficult to interpret these big and complex data than to acquire them. Sequence data interpretation is a critical step in current biological research and has great practical significance. It’s a great challenge for current computer systems and computing models to store, process and analysis massive high throughput sequence data. With survey, especially from BGI (Beijing Genome Institute), the current status, problems and measures taken to process high throughput sequence data will be discussed. However, the challenge is too big to be solved unless more people in different fields work together in depth for a long term.

Abstract:

This paper gives a comprehensive introduction to the status of current machine translation research and technology, and analyzes the key problems to be resolved. Finally our idea of the future trends and prospects of machine translation are put forward.

Abstract:

Automatic drive is an important application field of artificial intelligence. In this paper, a novel training strategy for self-driving vehicles was investigated based on the deep reinforcement learning model. The proposed method involves a Q-learning algorithm with filtered experience replay and pre-training with experiences from professional drivers, which accelerates the training process due to reduced exploration spaces. By resampling the input state after clustering, generalization ability of the strategy can be improved due to the individual and independent distribution of the samples. Experimental results show that, in comparison with conventional neural fitted Q-iteration algorithm, the training efficiency and controlling stability can be improved more than 90% and 30% respectively by the proposed approach. Experimental results with more complex testing tracks show that, average travel distance can be improved more than 70% in comparison with the Q-learning algorithm by the proposed method.

Abstract:

Hadoop job schedulers typically use a single resource abstraction and resources are allocated at the level of fixed-size partition of the nodes, called slots. These job schedulers ignore the different demands of jobs and fair allocation of multiple types of resources, leading to poor performance in throughput and average job completion time. This paper studies and implements a Muti-resource Fair Scheduler (MFS) in Hadoop. MFS adopts the idea of Dominant Resource Fairness (DRF). It uses a demand vector to describe demands for resources of a job and allocates resources to the job according to the demand vector. MFS uses resources more efficiently and satisfies multiple jobs with heterogeneous demands for resources. Experiment results show that MFS has higher throughput and shorter average job completion time compared to Hadoop slot-based Fair Scheduler and Capacity Scheduler.

Abstract:

With the increasing concerns of global warming and resource constraints, electric vehicles (EVs) have made great progress during the past decade. The electric driving system of EVs has dinstinct advantages, such as quick response, easy measurement , and precise control of motor torque, available flexible driving architecture, and regenerative braking, etc. Such advantages can be used to improve the performance of vehicle dynamic control. This paper presents the recent research efforts on electric vehicle dynamic control in terms of parameters estimation and dyanmic control scheme and methodology, especially focusing on the tire-road friction estimaion , novel traction control methods. The lateral dynamic control including the electrical differential control, direct yaw moment control, and the integratin chassis cotrol is proposed. Several prospects for vehicle dynamic control are proposed.

Abstract:

For the advantages of noninvasive, real-time and quantitative detection, ultrasonic transient elastography has important clinical application value. This work investigates the transient elastography in a few ways and aims to design a transient imaging system. The Displacement tracking algorithm based on correlation techniques and the parabolic interpolation algorithm is proposed to improve the accuracy. A novel match filter is designed to convolute with the estimated displacement in the time direction to boost the SNR of the displacement for a better strain image mapping. The convoluted result shows the match filter can significantly improve the strain image quality and help getting more accurate Youngs modulus estimation. The Time Gain Compensation (TGC) circuit is designed to compensate the attenuated power of the ultrasound signal. And a modified polyacrylamide gel based tissue-mimicking phantom is also developed in this paper, both indentation testing and transient elastography are used to characterize the elastic properties of this phantom. The results are almost consistent with each other.

Abstract:

With the rapid increase in numbers and scales of deep web sites on the Internet, search for data or information from deep web sites by submiting queries to and obtaining results from the backend databases has become a major means in information retrieval from the Web. This area has attracted many researchers to devote their efforts on development of technologies to make better use of information in th deep web. One challenge is searching for and integration of data from various databases in deep web. Since deep web is dominated by text data, research and development of technologies for text information retrieval from deep web have a broad application potential. In this paper, we review the state-of-the-art of deep web research in details and propose some future research directions.

Abstract:

Wireless Capsule Endoscope (WCE) is a very promising tool for the examination of the gastrointestinal (GI) tract. However, there are some problems to be solved for the existed WCE, and one key problem is the accurate localization and tracking of the WCE. Among the possible localization methods, the magnet-based localization technique has its advantages: no need for power, not much space occupation, continuously tracking ability, and no negative effect. In this paper, we present the localization method for the magnet objective inside the WCE based on the magnetic sensor array outside the human body. Through the algorithm and system design we realize real time tracking of 3D position and 2D orientation of the magnet based on the magnetic dipole model. In order to overcome the interference of the human body movement, we propose the multi-magnets’ localization method; also, the 3D positioning and 3D orientation method is proposed, which can be used to make the 3D recovery of the GI tract and the accurate computation of the physiological tissue parameters. The real experiments show that the proposed localization system can run well and obtain the accuracy with 2~3mm for the magnet.

Abstract:

Several of the top ranked supercomputers are based on the hybrid architecture consisting of a large number of CPUs and GPUs. High performance has been obtained for problems with special structures, such as FFT-based imaging processing or N-body based particle calculations. However, for the class of problems described by partial differential equations (PDEs) discretized by finite difference (or other mesh based methods such as finite element) methods, obtaining even reasonably good performance on a CPU/GPU cluster is still a challenge. In this paper, we propose and test an hybrid algorithm which matches the architecture of the cluster. The scalability of the approach is implemented by a domain decomposition method, and the GPU performance is realized by using a smoothed aggregation based algebraic multigrid method. Incomplete factorization, which performs beautifully on CPU but poorly on GPU, is completely avoided in the approach. Numerical experiments are carried out by using up to 32 CPU/GPUs for solving PDE problems discretized by FDM with up to 32 millions unknowns.

Abstract:

Effectively reducing power line interference is always an important issue in electromyography (EMG) signal recordings and analysis. In this study, four commonly used de-noising methods, including digital notch, LMS based adaptive filter, Kalman filter and S transform, which may be suitable for the reduction of power line interference in real-time EMG recordings, were chosen and their performance in reducing the power line interference from EMG signal recordings were quantitatively analyzed and compared. The pilot results of this study showed that Kalman filter presented the best whole performance in attenuating power line interference from EMG signals and S transform de-noising method illustrated the best performance when the power line interference was severe.

Abstract:

Transcranial magnetic stimulation (TMS) is a non-invasive technique that can be used for brain studying and clinical therapy. Firstly, the technology feature and application of the TMS instrument were introduced. Then several TMS coil positioning methods were evaluated and several key problems about TMS coil positioning were discussed. The aim of this study was to propose a new method for TMS coil positioning. The new method combines three aspects of quantitative information including the brain scalp, brain anatomy and brain function and has great advantages and broad application prospects.

Abstract:

This paper introduces the scientific computing grid, ScGrid, and it’s middleware SCE. ScGrid is built as one virtual supercomputer, integrating computing resource from more than 30 institutes. It provides unified,?easy to use and reliable scientific computing services. SCE is a lightweight grid middleware, which supports global job scheduling and unified data view. It provides multiple user interfaces including command line, grid portal and APIs. At present, ScGrid has been very successfully used in Chinese Academy of Sciences and widely accepted by more than 200 users.

Abstract:

Foot drop is the inability to voluntarily dorsiflex the ankle during the swing phase of gait and is usually caused by weakness and damages of the peroneal nerve. The consequences of the foot drop include the decreasing of gait quality, the limiting of mobility, the increasing of falling risk, and great increasing of energy expenditure during walking. Firstly biosignal sensors are used in the drop foot stimulator to detect foot movements. Then the surface drop foot stimulator produces a predefined stimulation profile to the peroneal nerve or tibialis anterial to elicit a dorsiflexion of the foot synchronized with the swing phase of gait to lift the foot. This paper reviewed the fundamentals and current researches of drop foot stimulators. Moreover, the development trends of the closed loop drop foot stimulator were also discussed in the paper.

Abstract:

Human action recognition acts as an important role in human machine interaction. This paper proposes a human body recognition method from depth image based on part size and position features. Random forest classifiers are trained with different parameters. Experimental results demonstrate the feasibility of proposed approach. Recognition accuracy is about 91% and the computation time is about 0.96 us per pixel.

Abstract:

Nanomaterials and nanotechnology play more and more important role in the field of new generation electronics packaging. The unique electrical, magnetic and optical properties of the nanomaterials along with their composites can enhance and improve the physical and mechanical properties of the components. Current issues of electronic packaging, especially those related to materials, are introduced and evaluated in this review. The nanomaterials, nanocomposites and nanotechnology have advantages in solving these issues and their future development direction. This review also focuses on the application of new materials such as, conductive metal particles, silica, carbon nanotubes, graphene, etc. in the high density system level packages.

Abstract:

Thirty years ago, the invention and volume shipment of IBM PC significantly enlarged the user population of computing. For the next thirty years, what is the most fundamental challenge of the computing field? What paradigm shift is needed? What is the most significant industrial problem? What are the most needed scientific breakthroughs? This article addresses these questions by discussing a dozen essential issues of computing for the masses. The most fundamental challenge is the computing market’s growth stagnation. Computing for the masses is proposed to reverse this trend and should be a fundamental future direction. It has three features of value-augmenting, affordability, and sustainability. The most basic paradigm shift is human-cyber-physical ternary computing. The most significant industrial problem is the Insecta Classis paradox. Computing for the masses needs five pillars of science support, including ternary computing science, universal compute account, efficient sea-network-cloud computing platforms, information ecosystem science, and national information accounts. This article helps outline the problem space for future computer science research, with a discussion on related transformative research projects.

Abstract:

In the past work for long time, since the computation required on object deformation and interaction is intensive, when fluid is interacted with rigid bodies, or especially with animating figure, the demand of real-time simulation and rendering could be hardly achieved. This paper presents a novel approach for generating effects simulated by fluid dynamics and interacted by the figure motions. In order to handle the interaction between fluid effect and deformed figure, firstly, the motion trajectory of character is tracked, and then the fluid dynamics is simulated by the model of Smoothed-Particle Hydrodynamics (SPH). Moreover, during the fluid simulation, an efficient algorithm for particle searching is also proposed, in virtue of parallel processing by GPU. Consequently, the simulation of 3D fluid effects with realistic character interaction can be rendered on a consumer-level PC in real-time.

Abstract:

Random Forests is an important ensemble learning method and it is widely used in data classification and nonparametric regression. In this paper, we review three main theoretical issues of random forests, i.e., the convergence theorem, the generalization error bound and the out-of-bag estimation. In the end, we present an improved Random Forests algorithm, which uses a feature weighting sampling method to sample a subset of features at each node in growing trees. The new method is suitable to solve classification problems of very high dimensional data.

Abstract:

In order to help the hearing loss children, we obtained hearing loss children’s fallible pronunciation texts and the confusing pronunciation text pairs form a good deal of hearing loss children’s audio pronunciation data. We designed a data-driven 3D talking head articulatory animation system, it was driven by the articulatory movements which were collected from a device called Electro-magnetic articulography (EMA) AG500, the system simulated Chinese articulation realistically. In that way, the hearing loss children can observe the speaker’s lips and tongue’s motions during the speaker pronouncing, which could help the hearing loss children train pronunciation and correct the fallible pronunciations. Finally, a perception test was applied to evaluate the system’s performance. The results showed that the 3D talking head system can animate both internal and external articulatory motions effectively. A modified CM model based synthesis method was used to generate the articulatory movements. The root mean square between the real articulatory movements and synthetic articulatory movements was used to measure the synthesis method, and an average value of RMS is 1.25 mm.

Abstract:

Morphological parameter measurement of Pseudosciaena Crocea plays an important role in its genetic selection and quality improvement. In this paper, an automatic detecting system which can measure the Pseudosciaena Crocea morphological parameters such as weight, length and body width was developed based on the machine vision and weighing sensor technology. The system can automatically detect the external morphology parameters by the machine vision, and get weight parameters through the weighing sensor. The mean errors of dimensional measurement and weighting are 0.28% and 0.74% respectively, which shows that the developed system can completely meet the requirements of morphological parameter measurement for Pseudosciaena Crocea. It is a new effective method to the automatic detection of fish morphology parameters.

Abstract:

In this work the thermal behavior of the LiNi1/3Co1/3Mn1/3O2 cathode material for soft packed lithium-ion power batteries during charging and discharging at different C-rate were conducted using the ARC (accelerating rate calorimeter) to provide an adiabatic environment. The overall heat generated by the lithium-ion battery during use, is partly reversible and partly irreversible, due to entropy change and joule heating, respectively. It indicates that the heating generation of lithium-ion cell is decided by the C-rate of charge and discharge. The heat is smaller at low C-rate of charge and discharge. For example, the heating generation of battery increases 7.16℃ at 0.2C-rate and the entropy change heat is clearly embodied. The joule heating is more remarkable than the entropy change during charging and discharging at high C-rate. For instance, the heating generation of cell increased 25.63℃ at 1C-rate. The heat generation of charge is less than discharge at the same C-rate. The DC inter insistence of cell at the SOC (State of Charge) of 0 to 10% increases suddenly, so the heating generation power will reach its maximum in this period during discharge. It is valuable for the design of heat dissipation in lithium-ion battery thermal management.