Electrochromic-Induced Rechargeable Aqueous Batteries: An Integrated Multifunctional System for Cross-Domain Applications

Multifunctional electrochromic-induced rechargeable aqueous batteries(MERABs) integrate electrochromism and aqueous ion batteries into one platform, which is able to deliver the conversion and storage of photo-thermal-electrochemical sources.Aqueous ion batteries compensate for the drawbacks of slow kinetic reactions and unsatisfied storage capacities of electrochromic devices. On the other hand, electrochromic technology can enable dynamically regulation of solar light and heat radiation. However,MERABs still face several technical issues, including a trade-off between electrochromic and electrochemical performance, low conversion efficiency and poor service life. In this connection, novel device configuration and electrode materials, and an optimized compatibility need to be considered for multidisciplinary applications. In this review,the unique advantages, key challenges and advanced applications are elucidated in a timely and comprehensive manner. Firstly, the prerequisites for effective integration of the working mechanism and device configuration, as well as the choice of electrode materials are examined. Secondly, the latest advances in the applications of MERABs are discussed, including wearable, self-powered, integrated systems and multisystem conversion. Finally, perspectives on the current challenges and future development are outlined, highlighting the giant leap required from laboratory prototypes to large-scale production and eventual commercialization.

Discrimination and quantification of scar tissue by Mueller matrix imaging with machine learning

Scarring is one of the biggest areas of unmet need in the long-term success of glaucoma filtration surgery.Quantitative evaluation of the scar tissue and the post-operative structure with micron scale resolution facilitates development of anti-fibrosis techniques.However,the distinguishment of conjunctiva,sclera and the scar tissue in the surgical area still relies on pathologists'experience.Since polarized light imaging is sensitive to anisotropic properties of the media,it is ideal for discrimination of scar in the subconjunctival and episcleral area by characterizing small differences between proportion,organization and the orientation of the fibers.In this paper,we defined the conjunctiva,sclera,and the scar tissue as three target tissues after glaucoma filtration surgery and obtained their polarization characteristics from the tissue sections by a Mueller matrix microscope.Discrimination score based on parameters derived from Mueller matrix and machine learning was calculated and tested as a diagnostic index.As a result,the discrimination score of three target tissues showed significant difference between each other(p<0.001).The visualization of the discrimination results showed significant contrast between target tissues.This study proved that Mueller matrix imaging is effective in ocular scar discrimination and paves the way for its application on other forms of ocular fibrosis as a substitute or supplementary for clinical practice.

Deep Learning-Based Program-Wide Binary Code Similarity for Smart Contracts

Recently,security issues of smart contracts are arising great attention due to the enormous financial loss caused by vulnerability attacks.There is an increasing need to detect similar codes for hunting vulnerability with the increase of critical security issues in smart contracts.Binary similarity detection that quantitatively measures the given code diffing has been widely adopted to facilitate critical security analysis.However,due to the difference between common programs and smart contract,such as diversity of bytecode generation and highly code homogeneity,directly adopting existing graph matching and machine learning based techniques to smart contracts suffers from low accuracy,poor scalability and the limitation of binary similarity on function level.Therefore,this paper investigates graph neural network to detect smart contract binary code similarity at the program level,where we conduct instruction-level normalization to reduce the noise code for smart contract pre-processing and construct contract control flow graphs to represent smart contracts.In particular,two improved Graph Convolutional Network(GCN)and Message Passing Neural Network(MPNN)models are explored to encode the contract graphs into quantitatively vectors,which can capture the semantic information and the program-wide control flow information with temporal orders.Then we can efficiently accomplish the similarity detection by measuring the distance between two targeted contract embeddings.To evaluate the effectiveness and efficient of our proposed method,extensive experiments are performed on two real-world datasets,i.e.,smart contracts from Ethereum and Enterprise Operation System(EOS)blockchain-based platforms.The results show that our proposed approach outperforms three state-of-the-art methods by a large margin,achieving a great improvement up to 6.1%and 17.06%in accuracy.

间变性淋巴瘤激酶抑制剂不良反应管理西南专家建议(2021年版)

间变性淋巴瘤激酶(anaplastic lymphoma kinase,ALK)融合基因作为肿瘤驱动基因,对非小细胞肺癌(non-small cell lung cancer,NSCLC)的发生和发展至关重要,而靶向ALK融合基因已成为ALK阳性NSCLC患者的主要治疗手段。第一、二代ALK抑制剂(ALK inhibitor,ALKi)克唑替尼、塞瑞替尼、阿来替尼、恩沙替尼已在中国上市并广泛应用。然而,针对ALKi不良反应尚无统一的管理指导规范,在一定程度上降低甚至限制了ALKi的临床使用及患者获益。本文由四川省肿瘤学会肺癌专业委员会及四川省肿瘤性疾病医疗质量控制中心牵头,针对国内已经获批上市的ALKi,参考国内外临床研究和相关文献,并结合专家实践经验,总结出《ALKi不良反应管理专家建议(2021年版)》,以期为临床提供切实可行的ALKi不良反应的管理策略。

晚期非小细胞肺癌免疫检查点抑制剂新型生物标志物:血液PD-L1动态检测

背景免疫检查点抑制剂(immune checkpoint inhibitors,ICIs)具有良好疗效已成为恶性肿瘤治疗领域备受瞩目的翘楚。然而,仅有小部分患者获得长期临床获益。如何选择生物标志物来筛查ICIs治疗优势人群仍是一大热点。方法收集51例晚期恶性肿瘤患者的肿瘤组织和配对血样本,进行PD-L1表达的相关性分析。40例晚期非小细胞肺癌(non-small cell lung cancer,NSCLC)患者接受ICIs治疗,2个月时检测血液PD-L1(bloodPD-L1,bPD-L1)表达的动态变化,包括PD-L1 mRNA、外泌体PD-L1(exosomalPD-L1,exoPD-L1)蛋白和可溶性PD-L1(solublePD-L1,sPD-L1)。应用R软件计算最佳截断值,用于预测最佳客观缓解(best objective response,b OR)、无进展生存期(progression-free survival,PFS)和总生存期(overall survival,OS)。结果51例不同恶性肿瘤患者中,组织PD-L1(tissuePD-L1,tPD-L1)表达阳性患者的PD-L1mRNA表达水平显著升高。40例接受ICIs治疗的晚期NSCLC患者中,bPD-L1 mRNA上调≥2.04的患者b OR、PFS和OS更佳;21例接受ICIs治疗的晚期NSCLC患者中,exoPD-L1上调≥1.86的患者临床获益更大。sPD-L1动态变化与ICIs疗效无显著相关性。PD-L1 mRNA和exoPD-L1联合检测更有利于预测ICIs治疗疗效。结论bPD-L1表达与tPD-L1表达存在正相关;晚期NSCLC患者ICIs治疗初期PD-L1 mRNA和(或)exoPD-L1表达升高,可作为评估临床获益的新型生物标志物。

High-Energy Batteries:Beyond Lithium-Ion and Their Long Road to Commercialisation

Rechargeable batteries of high energy density and overall performance are becoming a critically important technology in the rapidly changing society of the twenty-first century.While lithium-ion batteries have so far been the dominant choice,numerous emerging applications call for higher capacity,better safety and lower costs while maintaining sufficient cyclability.The design space for potentially better alternatives is extremely large,with numerous new chemistries and architectures being simultaneously explored.These include other insertion ions(e.g.sodium and numerous multivalent ions),conversion electrode materials(e.g.silicon,metallic anodes,halides and chalcogens)and aqueous and solid electrolytes.However,each of these potential“beyond lithium-ion”alternatives faces numerous challenges that often lead to very poor cyclability,especially at the commercial cell level,while lithium-ion batteries continue to improve in performance and decrease in cost.This review examines fundamental principles to rationalise these numerous developments,and in each case,a brief overview is given on the advantages,advances,remaining challenges preventing cell-level implementation and the state-of-the-art of the solutions to these challenges.Finally,research and development results obtained in academia are compared to emerging commercial examples,as a commentary on the current and near-future viability of these“beyond lithium-ion”alternatives.

ia-PNCC: Noise Processing Method for Underwater Target Recognition Convolutional Neural Network

Underwater target recognition is a key technology for underwater acoustic countermeasure.How to classify and recognize underwater targets according to the noise information of underwater targets has been a hot topic in the field of underwater acoustic signals.In this paper,the deep learning model is applied to underwater target recognition.Improved anti-noise Power-Normalized Cepstral Coefficients(ia-PNCC)is proposed,based on PNCC applied to underwater noises.Multitaper and normalized Gammatone filter banks are applied to improve the anti-noise capacity.The method is combined with a convolutional neural network in order to recognize the underwater target.Experiment results show that the acoustic feature presented by ia-PNCC has lower noise and are wellsuited to underwater target recognition using a convolutional neural network.Compared with the combination of convolutional neural network with single acoustic feature,such as MFCC(Mel-scale Frequency Cepstral Coefficients)or LPCC(Linear Prediction Cepstral Coefficients),the combination of the ia-PNCC with a convolutional neural network offers better accuracy for underwater target recognition.

An integrated approach to improve the performance of lean–electrolyte lithium–sulfur batteries

While the sulfur conversion reaction kinetics in Li–S batteries is nowadays improved by the use of appropriate electrocatalysts,it remains a challenge for the batteries to perform well under the lean electrolyte condition where polysulfide shuttle,electrode passivation and the loss of electrolyte due to side reactions,are aggravated.These challenges are addressed in this study by the tandem use of a polysulfide conversion catalyst and a redox–targeting mediator in a gel sulfur cathode.Specifically,the gel cathode reduces the polysulfide mobility and hence the polysulfide shuttle and the passivation of the lithium anode by the crossover polysulfides.The redox mediator restrains the deposition of inactive sulfur species in the cathode thereby enabling the Fe–N and Co–N co–doped carbon catalyst to prolong its catalytic activity.Consequently,the integrated catalytic system is able to increase the discharge capacity of high–loading (6.8 mg cm^(-2)) lean–electrolyte (4.0μL mg^(-1)) Li–S batteries from~630 to~1316 m Ah g^(-1),concurrently with an improvement of the cycle life (600 cycles with 46%capacity retention at 1.0 m A cm^(-2)).Redox mediator assisted catalysis in a gel cathode is therefore an effective strategy to extend the application of the sulfur conversion catalyst in lean electrolyte Li–S batteries.

Insight into the structure-capacity relationship in biomass derived carbon for high-performance sodium-ion batteries

Carbonaceous materials are the most promising candidates as the anode for sodium-ion batteries (SIBs), however, they still suffer from low electric conductivity and sluggish sodium ion (Na+) reaction kinetics. Appropriate composition modulation using heteroatoms doping and structure optimization is highly desired. A basic empirical understanding of the structure-capacity relationship is also urgent in tackling the above problems. Herein, multi-functional nitrogen (N) doped carbon micro-rods with enlarged interlayer spacing are synthesized and investigated as the anode in SIBs, showing an ultra-stable capacity of 161.5 mAh g^(−1) at 2 A g^(−1) for over 5000 cycles. Experimental investigations and first-principle calculations indicate that the enlarged interlayer spacing can facilitate Na+ intercalation and N doping can guarantee the high electric conductivity and favorable electrochemical active sites. Additionally, pyridinic N is theoretically proved to be more effective to enhance Na+ adsorption than pyrrolic N due to the lower adsorption energy and stronger binding energy with Na+. Full SIBs show a high capacity and cyclability, making the biomass-derived carbon micro-rods to be a promising anode for practical SIBs applications.

The influence of irregular seafloor topography on the seismic wave field and migration imaging

One of the problems experienced in marine geophysical exploration is that the layered features in the migration imaging profile are blurred and the seismic energy reflected is weaker in the middle or lower parts. In this study we model the seismic wavefield records in the undulating seafloor when there is both a slight change and significant change in seafloor topography to analyze its influence on the seismic reflection data and migration imaging profiles. We compare and analyze the wave field records collected at the same point on the original and modified velocity models, and the cross-bonding resulting migration imaging profiles. The results show that whether the seismic reflection data collection is performed along the direction of the survey line or against the direction of the survey line, slight changes in the seafloor topography have little effect on the wave field records and the migration profile, while significant changes in the seafloor topography have great effect on both the wave field records and migration profile.

PMS-Sorting:A New Sorting Algorithm Based on Similarity

Borda sorting algorithm is a kind of improvement algorithm based on weighted position sorting algorithm,it is mainly suitable for the high duplication of search results,for the independent search results,the effect is not very good and the computing method of relative score in Borda sorting algorithm is according to the rule of the linear regressive,but position relationship cannot fully represent the correlation changes.aimed at this drawback,the new sorting algorithm is proposed in this paper,named PMS-Sorting algorithm,firstly the position score of the returned results is standardized processing,and the similarity retrieval word string with the query results is combined into the algorithm,the similarity calculation method is also improved,through the experiment,the improved algorithm is superior to traditional sorting algorithm.

Improved scheme to accelerate sparse least squares support vector regression

The pruning algorithms for sparse least squares support vector regression machine are common methods, and easily com- prehensible, but the computational burden in the training phase is heavy due to the retraining in performing the pruning process, which is not favorable for their applications. To this end, an im- proved scheme is proposed to accelerate sparse least squares support vector regression machine. A major advantage of this new scheme is based on the iterative methodology, which uses the previous training results instead of retraining, and its feasibility is strictly verified theoretically. Finally, experiments on bench- mark data sets corroborate a significant saving of the training time with the same number of support vectors and predictive accuracy compared with the original pruning algorithms, and this speedup scheme is also extended to classification problem.

Clinicopathological characterization of gastroenteropancreatic neu-roendocrine neoplasms： a retrospective study of 48 cases

Objective Gastroenteropancreatic neuroendocrine neoplasms(GEP-NENs) constitute a rare and heterogeneous group of tumors with varied biology and still constitute a diagnostic and therapeutic challenge for physicians of all specialties. In the present study, we aimed to review and study the clinicopathological characteristics of GEP-NENs applying the World Health Organization(WHO) 2010 grading criterion.Methods A total of 48 patients were enrolled in the study. The study included patients diagnosed with GEP-NENs who were treated and followed up at our Hospital from January 2013 to December 2017. Data regarding clinicopathological features of the patients were retrospectively evaluated. The expression of neuroendocrine markers was measured using the immunohistochemical Ultra Sensitive^(TM) S-P method of staining in 48 cases of primary GEP-NENs; and serum levels of neuron-specific enolase, carbohydrate an-tigen 19-9, and carcinoembryonic antigen in 36 GEP-NEN patients were measured using the electrochemiluminescence method.Results The median age at presentation was 59.3(range 48–82) years, and 39 cases(81.3%) were seen between the 5 th and 6 th decades. There was a male predilection(male: female=3:1). In 79.2% cases(38/48), tumors were hormonally nonfunctional. The most common presentation was abdominal pain, and the most frequent primary site of the tumor was the rectum, followed by the stomach(n = 15, 31.3%), colon(n = 5, 10.4%), and so on. Of the 48 tumors, 16(33.3%) were G1, 6(12.5%) cases were G2, 16(33.3%) were neuroendocrine carcinoma(NEC), and 10(20.8%) were mixed adenoneuroendocrine carcinoma(MANEC). According to the AJCC/UICC classification, 45.8%(n = 22) were diagnosed at low stage(stage I or II) while 54.2%(n = 26) were diagnosed at high stage(stage III or IV)(the majority of NEC, G3, and MANEC). A male preponderance was noted for all tumors except for G2 neoplasms, which showed no gender predilection. Thirty-nine patients underwent endoscopic biopsy. The lesions in 18.8%(n = 9) of the patients were indentified only radiologically. After the surgical procedures, 36 had at least one follow-up visit with a median follow-up duration of 5 months; the mean follow-up period was 28 ± 16 months. The oneyear and three-year survival rates were 72.2%(26/36) and 61.1%(22/36), respectively. This study did not find an effect of grade 3(G3) of tumor on the short-term clinical outcome of these patients. In the survival analysis, NEN G3, higher stage(stage III or IV) according to the AJCC/UICC classification(P < 0.05), and metastases at diagnosis(P < 0.05) were associated with poorer prognosis.Conclusion Most GEP-NENs are nonfunctional and nonspecific in presentation. The most frequent primary site of the tumor was the rectum and the commonest ages at diagnosis were the 5 th and 6 th decades. Endoscopic biopsy is the main diagnostic and histological grading method for GEP-NEN. In the survival analysis, NEN G3, a higher stage according to the AJCC/UICC classification, and metastases at diagnosis are associated with poorer prognosis.

Lossless and High Robust Watermarking of Electronic Chart for Copyright Protection

With the progression of sea exploration and offshore engineering, electronic charts have come to see widespread use in many intelligent applications. Like other digital products, electronic charts are easy to duplicate and distribute. Some watermarking solutions have proven defective to prevent copying of electronic charts because it’s as easy to forge as it is to redistribute. If the problems of copyright infringement cannot be solved, the creation of these electronic charts will be limited. The most important characteristic of electronic charts is the topological relationships among vertices, but few algorithms can control this feature. A new watermarking algorithm is here proposed as a means of copyright protection, in which the watermarks will be hosted in the electronic chart by taking into account the preservation of the topology. Sometimes, additional vertices are inserted into the middle of two adjacent vertices, sometimes not, which are governed by the value of the watermark. Experiments show that the improved algorithm is better than similar algorithms; it was found to resist geometric attacks and format exchange attacks.

Frameworked electrolytes:Ionic transport behavior and high mobility for solid state batteries

All solid-state batteries(ASSBs)are the holy grails of rechargeable batteries,where extensive searches are ongoing in the pursuit of ideal solid-state electrolytes.Nevertheless,there is still a long way off to the satisfactorily high(enough)ionic conductivity,long-term stability and especially being able to form compatible interfaces with the solid electrodes.Herein,we have explored ionic transport behavior and high mobility in the sub-nano pore networks in the framework structures.Macroscopically,the frameworked electrolyte behaves as a solid,and however in the(sub)-nano scales,the very limited number of solvent molecules in confinement makes them completely different from that in liquid electrolyte.Differentiated from a liquid-electrolyte counterpart,the interactions between the mobile ions and surrounding molecules are subject to dramatic changes,leading to a high ionic conductivity at room temperature with a low activation energy.Li+ions in the sub-nano cages of the network structure are highly mobile and diffuse rather independently,where the rate-limiting step of ions crossing cages is driven by the local concentration gradient and the electrostatic interactions between Li^(+)ions.This new class of frameworked electrolytes(FEs)with both high ionic conductivity and desirable interface with solid electrodes are demonstrated to work with Li-ion batteries,where the ASSB with LiFePO_(4)shows a highly stable electrochemical performance of over 450 cycles at 2℃ at room temperature,with an almost negligible capacity fade of 0.03‰ each cycle.In addition,the FE shows outstanding flexibility and anti-flammability,which are among the key requirements of large-scale applications.

Better engineering layered vanadium oxides for aqueous zinc‐ion batteries: Going beyond widening the interlayer spacing

Aqueous zinc‐ion batteries(ZIBs)are regarded as among the most promising candidates for large‐scale grid energy storage,owing to their high safety,low costs,and environmental friendliness.Over the past decade,vanadium oxides,which are exemplified by V2O5,have been widely developed as a class of cathode materials for ZIBs,where the relatively high theoretical capacity and structural stability are among the main considerations.However,there are considerable challenges in the construction of vanadium‐based ZIBs with high capacity,long lifespan,and excellent rate performance.Simple widenings of the interlayer spacing in the layered vanadium oxides by pre‐intercalations appear to have reached their limitations in improving the energy density and other key performance parameters of ZIBs,although various metal ions(Na+,Ca2+,and Al3+)and even organic cations/groups have been explored.Herein,we discuss the advances made more recently,and also the challenges faced by the high‐performance vanadium oxides(V2O5‐based)cathodes,where there are several strategies to improve their electrochemical performance ranging from the new structural designs down to sub‐nano‐scopic/molecular/atomic levels,including cation pre‐intercalation,structural water optimization,and defect engineering,to macroscopic structural modifications.The key principles for an optimal structural design of the V2O5‐based cathode materials for high energy density and fast‐charging aqueous ZIBs are examined,aiming at paving the way for developing energy storage designed for those large scales,high safety,and low‐cost systems.

通过表面终止化学设计实现高度可逆的锌金属阳极

锌表面自然形成的非均匀氧化层(ZnO)会与电解液发生反应形成Zn_(4)(OH)_(6)SO_(4)·xH_(2)O(ZSH)副产物,导致锌负极表面非均匀沉积,从而阻碍水性锌离子电池实际应用.为了排除氧化层分布形式的影响,本文利用表面终止化学设计策略在锌负极表面制备了一层完全氧化的ZnO层,研究发现锌负极均匀分布的ZnO层会原位演化形成致密的ZSH功能层.均匀且致密的ZSH能够有效隔绝电解液的腐蚀,从而有效提高锌负极界面的稳定性.此外,ZSH(002)晶面边缘的不饱和悬空键(如-O)更容易和Zn(H_(2)O)_(6)^(2+)结构中的锌离子形成强Zn-O键,可以促进Zn(H_(2)O)_(6)^(2+)的脱溶剂化和锌离子沿边扩散,实现了高度可逆的锌沉积行为并限制了副反应.基于此,本文提出与“表面脱水-晶体通道转移”机制明显不同的“边缘脱水-沿边缘转移”锌离子输运新机制.更重要的是,基于此组装的全电池显示出高循环稳定性(超过1000次循环)和高库仑效率(99.07%),验证了其潜在的实际应用价值.

A suture-free, shape self-adaptive and bioactive PEG-Lysozyme implant for Corneal stroma defect repair and rapid vision restoration

limitation of donor tissue shortage clinically. In addition, suturing-needed transplantation potentially causes postoperative complications. Herein, we design a PEG-Lysozyme injective hydrogel as a suture-free, shape self-adaptive, bioactive implant for corneal stroma defect repair. This implant experiences a sol-gel phase transition via an in situ amidation reaction between 4-arm-PEG-NHS and lysozyme. The physicochemical properties of PEG-Lysozyme can be tuned by the components ratio, which confers the implant mimetic corneal modulus and provides tissue adhesion to endure increased intraocular pressure. In vitro tests prove that the implant is beneficial to Human corneal epithelial cells growth and migration due to the bioactivity of lysozyme. Rabbit lamellar keratoplasty experiment demonstrates that the hydrogel can be filled into defect to form a shape-adaptive implant adhered to native stroma. The implant promotes epithelialization and stroma integrity, recovering the topology of injured cornea to normal. A newly established animal forging behavior test prove a rapid visual restoration of rabbits when use implant in a suture free manner. In general, this work provides a promising preclinical practice by applicating a self-curing, shape self-adaptive and bioactive PEG-Lysozyme implant for suture-free stroma repair.

A New Approach for Regression Analysis of Multivariate Current Status Data with Informative Censoring

Regression analysis of interval-censored failure time data has recently attracted a great deal of attention partly due to their increasing occurrences in many fields.In this paper,we discuss a type of such data,multivariate current status data,where in addition to the complex interval data structure,one also faces dependent or informative censoring.For inference,a sieve maximum likelihood estimation procedure is developed and the proposed estimators of regression parameters are shown to be asymptotically consistent and efficient.For the implementation of the method,an EM algorithm is provided,and the results from an extensive simulation study demonstrate the validity and good performance of the proposed inference procedure.For an illustration,the proposed approach is applied to a tumorigenicity experiment.

Ultra‑Stable Sodium‑Ion Battery Enabled by All‑Solid‑State Ferroelectric‑Engineered Composite Electrolytes

Symmetric Na-ion cells using the NASICON-structured electrodes could simplify the manufacturing process,reduce the cost,facilitate the recycling post-process,and thus attractive in the field of large-scale stationary energy storage.However,the long-term cycling performance of such batteries is usually poor.This investigation reveals the unavoidable side reactions between the NASICON-type Na_(3)V_(2)(PO_(4))_(3)(NVP)anode and the commercial liquid electrolyte,leading to serious capacity fading in the symmetric NVP//NVP cells.To resolve this issue,an all-solid-state composite electrolyte is used to replace the liquid electrolyte so that to overcome the side reaction and achieve high anode/electrolyte interfacial stability.The ferroelectric engineering could further improve the interfacial ion conduction,effectively reducing the electrode/electrolyte interfacial resistances.The NVP//NVP cell using the ferroelectric-engineered composite electrolyte can achieve a capacity retention of 86.4%after 650 cycles.Furthermore,the electrolyte can also be used to match the Prussianblue cathode NaxFeyFe(CN)_(6−z)·nH_(2)O(NFFCN).Outstanding long-term cycling stability has been obtained in the all-solid-state NVP//NFFCN cell over 9000 cycles at a current density of 500 mA g^(-1),with a fading rate as low as 0.005%per cycle.