Carbon-based interface engineering and architecture design for high-performance lithium metal anodes

Metallic lithium(Li)is considered the“Holy Grail”anode material for the nextgeneration of Li batteries with high energy density owing to the extraordinary theoretical specific capacity and the lowest negative electrochemical potential.However,owing to inhomogeneous Li-ion flux,Li anodes undergo uncontrollable Li deposition,leading to limited power output and practical applications.Carbon materials and their composites with controllable structures and properties have received extensive attention to guide the homogeneous growth of Li to achieve high-performance Li anodes.In this review,the correlation between the behavior of Li anode and the properties of carbon materials is proposed.Subsequently,we review emerging strategies for rationally designing high-performance Li anodes with carbon materials,including interface engineering(stabilizing solid electrolyte interphase layer and other functionalized interfacial layer)and architecture design of host carbon(constructing three-dimension structure,preparing hollow structure,introducing lithiophilic sites,optimizing geometric effects,and compositing with Li).Based on the insights,some prospects on critical challenges and possible future research directions in this field are concluded.It is anticipated that further innovative works on the fundamental chemistry and theoretical research of Li anodes are needed.

An Innovative K-Anonymity Privacy-Preserving Algorithm to Improve Data Availability in the Context of Big Data

The development of technologies such as big data and blockchain has brought convenience to life,but at the same time,privacy and security issues are becoming more and more prominent.The K-anonymity algorithm is an effective and low computational complexity privacy-preserving algorithm that can safeguard users’privacy by anonymizing big data.However,the algorithm currently suffers from the problem of focusing only on improving user privacy while ignoring data availability.In addition,ignoring the impact of quasi-identified attributes on sensitive attributes causes the usability of the processed data on statistical analysis to be reduced.Based on this,we propose a new K-anonymity algorithm to solve the privacy security problem in the context of big data,while guaranteeing improved data usability.Specifically,we construct a new information loss function based on the information quantity theory.Considering that different quasi-identification attributes have different impacts on sensitive attributes,we set weights for each quasi-identification attribute when designing the information loss function.In addition,to reduce information loss,we improve K-anonymity in two ways.First,we make the loss of information smaller than in the original table while guaranteeing privacy based on common artificial intelligence algorithms,i.e.,greedy algorithm and 2-means clustering algorithm.In addition,we improve the 2-means clustering algorithm by designing a mean-center method to select the initial center of mass.Meanwhile,we design the K-anonymity algorithm of this scheme based on the constructed information loss function,the improved 2-means clustering algorithm,and the greedy algorithm,which reduces the information loss.Finally,we experimentally demonstrate the effectiveness of the algorithm in improving the effect of 2-means clustering and reducing information loss.

Long-term effects of early antibiotic intervention on blood parameters,apparent nutrient digestibility, and fecal microbial fermentation profile in pigs with different dietary protein levels

Backgroud： This study aimed to determine the effects of early antibiotic intervention（EAI） on subsequent blood parameters, apparent nutrient digestibility, and fecal fermentation profile in pigs with different dietary crude protein（CP） levels. Eighteen litters of piglets（total 212） were randomly allocated to 2 groups and were fed a creep feed diet with or without in-feed antibiotics（olaquindox, oxytetracycline calcium and kitasamycin） from postnatal d 7 to d 42. On d 42, the piglets within the control or antibiotic group were mixed, respectively, and then further randomly assigned to a normal-（20%, 18%, and 14% CP from d 42 to d 77, d 77 to d 120, and d 120 to d 185,respectively） or a low-CP diet（16%, 14%, and 10% CP from d 42 to d 77, d 77 to d 120, and d 120 to d 185,respectively）, generating 4 groups. On d 77（short-term） and d 185（long-term）, serum and fecal samples were obtained for blood parameters, microbial composition and microbial metabolism analysis.Results： EAI increased（P 〈 0.05） albumin and glucose concentrations in low-CP diet on d 77, and increased（P 〈 0.05） urea concentration in normal-CP diet. On d 185, EAI increased（P 〈 0.05） globulin concentration in normal-CP diets, but decreased glucose concentration. For nutrient digestibility, EAI increased（P 〈 0.05）digestibility of CP on d 77. For fecal microbiota, the EAI as well as low-CP diet decreased（P 〈 0.05） E. coli count on d 77. For fecal metabolites, on d 77, EAI decreased（P 〈 0.05） total amines concentration but increased skatole concentration in low-CP diet. On d 185, the EAI increased（P 〈 0.05） putrescine and total amines concentrations in low-CP diets but reduced（P 〈 0.05） in the normal-CP diets. The low-CP diet decreased the concentrations of these compounds.Conclusions： Collectively, these results indicate that EAI has short-term effects on the blood parameters and fecal microbial fermentation profile. The effects of EAI varied between CP levels, which was characterized by the significant alteration of glucose and putrescine concentration.

Collaborative Pushing and Grasping of Tightly Stacked Objects via Deep Reinforcement Learning

Directly grasping the tightly stacked objects may cause collisions and result in failures,degenerating the functionality of robotic arms.Inspired by the observation that first pushing objects to a state of mutual separation and then grasping them individually can effectively increase the success rate,we devise a novel deep Q-learning framework to achieve collaborative pushing and grasping.Specifically,an efficient non-maximum suppression policy(PolicyNMS)is proposed to dynamically evaluate pushing and grasping actions by enforcing a suppression constraint on unreasonable actions.Moreover,a novel data-driven pushing reward network called PR-Net is designed to effectively assess the degree of separation or aggregation between objects.To benchmark the proposed method,we establish a dataset containing common household items dataset(CHID)in both simulation and real scenarios.Although trained using simulation data only,experiment results validate that our method generalizes well to real scenarios and achieves a 97%grasp success rate at a fast speed for object separation in the real-world environment.

Statistical delay distribution analysis on high-speed railway trains

The focus of this study is to explore the statis-tical distribution models of high-speed railway (HSR) train delays. Based on actual HSR operational data, the delay causes and their classification, delay frequency, number of affected trains, and space–time delay distributions are discussed. Eleven types of delay events are classified, and a detailed analysis of delay distribution for each classifica-tion is presented. Models of delay probability delay prob-ability distribution for each cause are proposed. Different distribution functions, including the lognormal, exponen-tial, gamma, uniform, logistic, and normal distribution, were selected to estimate and model delay patterns. The most appropriate distribution, which can approximate the delay duration corresponding to each cause, is derived. Subsequently, the Kolmogorov–Smirnov (K–S) test was used to test the goodness of fit of different train delay distribution models and the associated parameter values. The test results show that the distribution of the test data is consistent with that of the selected models. The fitting distribution models show the execution effect of the timetable and help in finding out the potential conflicts in real-time train operations.

A Simple and “Green” Method for Synthesis of Magnetic Hollow Silica Spheres and Its ⁹⁹Tc^mLabeled Targeting Studies

The magnetic hollow silica spheres (MHSS) with uniform cavity size and shell thickness were prepared by a simple and “green” method using functionalized SiO2 spheres as templates. Magnetic particles (Fe3O4) were deposited on the SiO2 surface by varying the molar ratio of [Fe2+]/[Fe3+] and the molar concentration of iron salts. The obtained magnetic hollow silica spheres exhibited a super-paramagnetic behavior at room temperature. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), and X-ray powder scattering (XRD) were applied to characterize the MHSS. Besides, their unit cell parameters are calculated according to results indexing to XRD, the MHSS sample prepared at 0.10 M iron salts and 2:1 molar ratio of [Fe2+]/[Fe3+] has a largest cell angle (β) of unit cell. Due to large hollow cavity space and super-paramagnetic characteristics, the inner amino-functionalized MHSS could be labeled with radioisotope 99Tcm to study the MHSS’s magnetic targeting distribution in vivo. These results indicate that the MHSS has potential in the magnetic targeted drug delivery system which reduces the damage to normal cells and improves the therapeutic effect of cancer.

Dispersibility, Shape and Magnetic Properties of Nano-Fe₃O₄Particles

Nano-Fe3O4 particles were prepared by a two-step microemulsion method, the influence of molar ratio of water to NP-5 (R), alkali concentration and temperature on dispersibility and shape of the nanoparticles were discussed. Magnetic studies were also carried out using VSM in this paper. It was found that the optimum preparation parameters are R = 6.0, alkali concentration = 2.5 mol.L–1, initial total iron concentration as 0.88 mol.L–1, and the temperature being 30°C, the prepared nano magnetite particles have uniform size and good dispersibility with a crystal structure belonging to cubicFe3O4 and lattice parameters of a = 8.273 ?. The results of magnetic studies show, magnetic properties of particles are influenced by dispersibility of nanoparticles which depends on size of clusters. The better dispersibility of nanoparticles leads to more ordered inner magnetic vector, and so the stronger magnetic behavior of nano-Fe3O4 particles.

Influences of SiO2/Na2O Molar Ratio on Aging and Chemical Modification of Water Glass

In this paper, the content of water glass before and after adding modifying agent was measured by Trimethylsilyl-gas-chromatography. The experimental results showed that different modulus of water glass could generate different content of mono-silicate acid and oligomeric silicate acid in water glass. After a period of storage, different modulus of water glass led to decrease of silicate content at different levels. Because higher content of Na2O in water glass tended to incur the alkaline polymerization, the occurrence of depolymerization of silicate species would lead to an increase of oligomeric silicate species, resulting in a drawback of silicate species content after a period of storage. And contrary to that, lower content of Na2O in water glass tended to incur the acidic polymerization. When the modifying agent was added to the newly made water glass, the amount of mono-silicate acid and oligomeric silicate acid also decreased. In modified water glass, the change of each silicate acid species was less than that in unmodified water glass. These results showed that the modifying agent retarded the aging of water glass. It had remarkable significance on the theory and practical application of water glass chemistry.

Lysosome-targeted carbon dots with a light-controlled nitric oxide releasing property for enhanced photodynamic therapy

The reactive oxygen species(ROS) generation efficiency is always limited by the extreme tumor microenvironment(TME), leading to unsatisfactory antitumor effects in photodynamic therapy(PDT). As a promising gas therapy molecule, nitric oxide(NO) is independent of oxygen and could even synergize ROS to enhance the therapeutic effect. However, the short half-life, instability, and uncontrollable release of exogenous NO limited the application of tumor synergistic therapy. Herein, we reported a novel kind of red-emissive carbon dots(CDs) that was capable of lysosome-targeted and light-controlled NO delivery. The CDs were synthesized by using metformin and methylene blue(MB) via a hydrothermal method.The obtained metformin-MB CDs(MMCDs) exhibited a higher1O2quantum yield and NO generation efficiency under light emitting diode(LED) light irradiation. Noteworthily, the1O2could further in situ oxidize NO into peroxynitrite anions(ONOO-), which own the higher cytotoxicity against cancer cells.Cell experiments indicate that MMCDs could destruct lysosome membrane integrity and kill almost 80%of Hep G2 cells under light irradiation while very low cytotoxicity in the dark. Moreover, MMCDs significantly decreased tumor volume and weight after phototherapy in hepatoma Hep G2-bearing mice. Our study provides a new strategy for light-controlled NO generation as well as precise lysosome-targeting for enhancement of PDT efficiency.

Indole-3-propionic Acid-aggravated CCl_(4)-induced Liver Fibrosis via the TGF-β1/Smads Signaling Pathway

Background and Aims:The pathogenesis of liver fibrosis involves liver damage,inflammation,oxidative stress,and intestinal dysfunction.Indole-3-propionic acid(IPA)has been demonstrated to have antioxidant,anti-inflammatory and anticancer activities,and a role in maintaining gut homeostasis.The current study aimed to investigate the role of IPA in carbon tetrachloride(CCl4)-induced liver fibrosis and explore the underlying mechanisms.Methods:The liver fibrosis model was established in male C57BL/6 mice by intraperitoneal injection of CCl4 twice weekly.IPA intervention was made orally(20 mg/kg daily).The degree of liver injury and fibrosis were assessed by serum alanine aminotransferase(ALT),aspartate aminotransferase(AST),and histopathology.Enzyme-linked immunosorbent assay and quantitative real-time polymerase chain reaction(qPCR)were used to detect the inflammatory cytokines.The malondialdehyde(MDA),glutathione,glutathione peroxidase,superoxide dismutase,and catalase were determined via commercial kits.Hepatocyte apoptosis was detected by terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling assay.The expression of mRNA and protein was assayed by qPCR,Western blotting,or immunohistochemical staining.Results:After IPA treatment,the ALT and AST,apoptotic cells,and pro-inflammatory factor levels were enhanced significantly.Moreover,IPA intervention up-regulated the expression of collagen I,α-smooth muscle actin,tissue inhibitor of matrix metalloproteinase-1,matrix metalloproteinase-2,transforming growth factor-β1(TGF-β1),Smad3,and phosphorylated-Smad2/3.Additionally,IPA intervention did not affect the MDA level.Attractively,the administration of IPA remodeled the gut flora structure.Conclusions:IPA aggravated CCl_(4)-induced liver damage and fibrosis by activating HSCs via the TGF-β1/Smads signaling pathway.

Degradation of 2,4-dichlorophenol catalyzed by the immobilized laccase with the carrier of Fe_3O_4@MSS–NH_2

With the Fe3O4@MSS(magnetic mesoporous silica spheres)–NH2as the carrier and the glutaraldehyde as crosslinking agent,the immobilized laccase has been prepared and characterized by XRD,IR,SEM and BET etc.Under the optimal conditions,the removal efficiency of2,4-DCP reached 88%and the removal efficiency still remained 61.5%after five cycles of operations.In virtue of GC–MS analysis,2,5-dimethoxyl-1,4-quinone,2-chlorine-1,4-dimethoxyl benzene,3,30-dichlorine-4,40-dimethoxyl biphenyl,maleic acid phenol ester,and three kinds of maleic acid,alcohol ester,and para-hydroxyl phenol ester compounds have been identified as intermediate and final degradation products of 2,4-DCP,respectively.Besides,the degradation products of 2,4-DCP have been confirmed by performing the1H-NMR and13C-NMR experiments,further demonstrating the degradation mechanism of 2,4-DCP by the immobilized laccase.

Cagelike mesoporous silica encapsulated with microcapsules for immobilized laccase and 2,4-DCP degradation

In this study,cage-like mesoporous silica was used as the carrier to immobilize laccase by a physical approach,followed by encapsulating with chitosan/alginate microcapsule membranes to form microcapsules of immobilized laccase based on layer-by-layer technology.The relationship between laccase activity recovery/leakage rate and the coating thickness was simultaneously investigated.Because the microcapsule layers have a substantial network of pores,they act as semipermeable membranes,while the laccase immobilized inside the microcapsules acts as a processing plant for degradation of2,4-dichlorophenol.The microcapsules of immobilized laccase were able to degrade 2,4-dichlorophenol within a wide range of 2,4-dichlorophenol concentration,temperature and p H,with mean degradation rate around 62%.Under the optimal conditions,the thermal stability and reusability of immobilized laccase were shown to be improved significantly,as the removal rate and degradation rate remained over 40.2% and 33.8% respectively after 6 cycles of operation.Using mass spectrometry（MS） and nuclear magnetic resonance（NMR）,diisobutyl phthalate and dibutyl phthalate were identified as the products of 2,4-dichlorophenol degradation by the microcapsules of immobilized laccase and laccase immobilized by a physical approach,respectively,further demonstrating the degradation mechanism of 2,4-dichlorophenol by microcapsule-immobilized laccase.

LAMC1, LAMA2 and LAMA3 gene polymorphisms and the risk for severe pelvic organ prolapse

Pelvic organ prolapse (POP) is the descent of the pelvic organs,including bladder, uterus, vagina and rectum, resulting in pelvic discomfort, urinary and fecal incontinence and sexual dysfunction(1)The prevalence of symptomatic POP in China is 9.56%according to a cross-sectional study involving 54,000 adult women in six provinces in the mainland of China (unpublished data). The etiology of this disorder is multifactorial, including race, age, body mass index(BMI), parity and menopause (1)The loss of the integrity of vaginal connective tissue has been demonstrated to weaken the pelvic floor support and promote the development of POP.

Supramolecular Surface Engineering of Carbon Dots Enables Matrix-Free Room Temperature Phosphorescence

Comprehensive Summary,Carbon dots(CDs)are an emerging class of nanomaterials with intriguing photophysical properties.Recently,achieving room temperature phosphorescence(RTP)for CDs has attracted considerable attention for biomedical and information applications.However,the CDs based RTP materials generally require the use of polymeric and inorganic matrix to provide the rigid environments,which remains a great challenge to obtain matrix-free CDs with RTP.Herein,a novel supramolecular strategy based on strong interparticle interactions has been developed to attain this objective,by covalent decoration of ureido-pyrimidinone(UPy,a multiple hydrogen bonding unit)on the surface of CDs.Structural characterizations validated the core-shell structure of the as-prepared CDs(EDTA-CDs)and demonstrated the successful attachment of UPy via post-modification(UPy-CDs).The presence of UPy recognition units render the strong hydrogen bonding between UPy-CDs,which stabilizes the triplet state via rigidifying effect.As a result,UPy-CDs exhibit matrix-free efficient RTP(λ_(em)=534 nm)with high brightness and long lifetime(33.6 ms)in the solid state.Owing to the dual-emission character,we further explored the application potential of UPy-CDs in information encryption and anti-counterfeiting.Overall,this work provides a new and facile strategy for achieving matrix-free phosphorescent CDs with elegant incorporation of supramolecular chemistry.

Quantum superreplication of states and gates

Although the no-cloning theorem forbids perfect replication of quantum information, it is sometimes possible to produce large numbers of replicas with vanishingly small error. This phenomenon, known as quantum superreplication, can occur for both quantum states and quantum gates. The aim of this paper is to review the central features of quantum superreplication and provide a unified view of existing results. The paper also includes new results. In particular, we show that when quantum superreplication can be achieved, it can be achieved through estimation up to an error of size O（M/N2）, where N and M are the number of input and output copies, respectively. Quantum strategies still offer an advantage for superreplication in that they allow for exponentially faster reduction of the error. Using the relation with estimation, we provide i） an alternative proof of the optimality of Heisenberg scaling in quantum metrology, ii） a strategy for estimating arbitrary unitary gates with a mean square error scaling as log N/N2, and iii） a protocol that generates O（N2） nearly perfect copies of a generic pure state U｜0） while using the corresponding gate U only N times. Finally, we point out that superreplication can be achieved using interactions among k systems, provided that k is large compared to M2/N2.

A new discrepancy for sample generation in stochastic response analyses of aerospace problems with uncertain parameters

Good distribution of samples and weights can improve the computational accuracy and efficiency in the stochastic response analyses of aerospace problems with uncertain parameters.This work proposes a new Generalized L2 Discrepancy based on a General Point(GL2D-GP)for generating samples and their corresponding weights.The proposed GL2D-GP is an extension of the existing discrepancy by introducing the non-same weights and a smaller box to measure probability errors.Minimizing the GL2D-GP can yield a weight optimization formula that generates a set of optimal non-identical weights for a given sample set.Through minimizing the GL2D-GP assigned to the set of optimal non-same weights,a new sample and weight generation method is developed.In the proposed method,the samples can be easily generated in terms of the generalized Halton formula with a series of optimal permutation vectors which are found by the intelligent evolutionary algorithm.Once the sample set is obtained,the optimal weights can be generated in terms of the weight optimization formula.Five numerical examples are presented to verify the high accuracy,efficiency,and strong robustness of the proposed sample generation method based on GL2D-GP.