In-situ AFM and quasi-in-situ studies for localized corrosion in Mg-9Al-1Fe-(Gd) alloys under 3.5 wt.% NaCl environment

Revealing the localized corrosion process of Mg alloy is considered as one of the most significant ways for improving its corrosion resistance.The reliable monitor should be high distinguishability and real-time in liquid environment.Herein,Mg-9Al-1Fe and Mg-9Al-1Fe-1Gd alloys were designed to highlight the impact of intermetallic on the corrosion behaviour.In-situ AFM with a special electrolyte circulation system and quasi-in-situ SEM observation were used to monitor the corrosion process of the designed alloys.SEM-EDS and TEM-SAED were applied to identify the intermetallic in the designed alloys,and their volta potentials were measured by SKPFM.According to the real-time and real-space in-situ AFM monitor,the corrosion process consisted of dissolution of anodicα-Mg phase,accumulation of corrosion products around cathodic phase and shedding of some fine cathodic phase.Then,the localized corrosion process of Mg alloy was revealed combined with the results of the monitor of corrosion process and Volta potential difference.

Real-World Evidence in Localized Pancreatic: Coping with Uncertainty in Unselected Populations

Background: Localized pancreatic cancer, including resectable (R), borderline resectable (BR) and locally advanced unresectable disease (LAU), is considered in clinical guidelines for diverse treatment options based on clinical trials in selected populations. Hence, exploring with real world evidence (RWE) clinicians’ preferences for treatment options and their results seems pertinent. Methods: In a set of consecutive patients with localized pancreatic cancer assisted in a third level hospital from January 2013 to December 2022, medical records, symptoms, diagnostic process, distribution between subtypes, and treatment plans, with safety and efficacy results, were assessed. Results: A total of 152 patients with localized disease were included (43.4% R, 21.0% BR, 33.6% LAU). The population characteristics exemplified differences between daily practice and clinical trials. Tumor location and symptoms were as expected. Treatment plan was conditioned by PS or comorbidities in 23.0% of patients. In patients with R disease, surgery followed by different adjuvant chemotherapy (CT) regimes was the antineoplastic treatment of choice (64.8%) with efficacy results (OS 37.5 months;95% CI 18.4 - 56.7), in the range of contemporary standards. The common use of neoadjuvant CT for BR disease (94.4%), with surgery in 50% of them, and its results (OS 30.8 months;95% CI 10.5 - 51.2) reflected current controversies of treatment recommendations and evolution in this scenario. Paliative CT with or without radiotherapy was the standard specific treatment in LAU disease (95.1%) with survival results (PFS: 10.8 months;95% CI 8.8 - 12.7. OS: 20.3 months;95% CI 13.5 - 27.2) that justify the distinct character and the specific study of this entity. Conclusion: RWE for localized pancreatic cancer aroused from the analysis of this population confirms the distinct nature of patients assisted in daily practice, as well as mirrors the complexity of decision making in clinical assumptions in which achieving stronger evidence should be paramount.

Facilitating prelithiation of silicon carbon anode by localized high-concentration electrolyte for high-rate and long-cycle lithium storage

The commercialization of silicon-based anodes is affected by their low initial Coulombic efficiency(ICE)and capacity decay,which are attributed to the formation of an unstable solid electrolyte interface(SEI)layer.Herein,a feasible and cost-effective prelithiation method under a localized highconcentration electrolyte system(LHCE)for the silicon-silica/graphite(Si-SiO_(2)/C@G)anode is designed for stabilizing the SEI layer and enhancing the ICE.The thin SiO_(2)/C layers with-NH_(2) groups covered on nano-Si surfaces are demonstrated to be beneficial to the prelithiation process by density functional theory calculations and electrochemical performance.The SEI formed under LHCE is proven to be rich in ionic conductivity,inorganic substances,and flexible organic products.Thus,faster Li+transportation across the SEI further enhances the prelithiation effect and the rate performance of Si-SiO_(2)/C@G anodes.LHCE also leads to uniform decomposition and high stability of the SEI with abundant organic components.As a result,the prepared anode shows a high reversible specific capacity of 937.5 mAh g^(-1)after 400 cycles at a current density of 1 C.NCM 811‖Li-SSGLHCE full cell achieves a high-capacity retention of 126.15 mAh g^(-1)at 1 C over 750 cycles with 84.82%ICE,indicating the great value of this strategy for Si-based anodes in large-scale applications.

Observation of flat-band localized state in a one-dimensional diamond momentum lattice of ultracold atoms

We investigated the one-dimensional diamond ladder in the momentum lattice platform. By inducing multiple twoand four-photon Bragg scatterings among specific momentum states, we achieved a flat band system based on the diamond model, precisely controlling the coupling strength and phase between individual lattice sites. Utilizing two lattice sites couplings, we generated a compact localized state associated with the flat band, which remained localized throughout the entire time evolution. We successfully realized the continuous shift of flat bands by adjusting the corresponding nearest neighbor hopping strength, enabling us to observe the complete localization process. This opens avenues for further exploration of more complex properties within flat-band systems, including investigating the robustness of flat-band localized states in disordered flat-band systems and exploring many-body localization in interacting flat-band systems.

Evolution of mechanical properties,localized corrosion resistance and microstructure of a high purity Al-Zn-Mg-Cu alloy during non-isothermal aging

The evolution of mechanical properties,localized corrosion resistance of a high purity Al-Zn-Mg-Cu alloy during non-isothermal aging(NIA)was investigated by hardness test,electrical conductivity test,tensile test,intergranular corrosion test,exfoliation corrosion test,slow strain rate tensile test and electrochemical test,and the mechanism has been discussed based on microstructure examination by optical microscopy,electron back scattered diffraction,scanning electron microscopy and scanning transmission electron microscopy.The NIA treatment includes a heating stage from 40℃to 180℃with a rate of 20℃/h and a cooling stage from 180℃to 40℃with a rate of 10℃/h.The results show that the hardness and strength increase rapidly during the heating stage of NIA since the increasing temperature favors the nucleation and the growth of strengthening precipitates and promotes the transformation of Guinier-Preston(GPI)zones toη'phase.During the cooling stage,the sizes ofη'phase increase with a little change in the number density,leading to a further slight increase of the hardness and strength.As NIA proceeds,the corroded morphology in the alloy changes from a layering feature to a wavy feature,the maximum corrosion depth decreases,and the reason has been analyzed based on the microstructural and microchemical feature of precipitates at grain boundaries and subgrain boundaries.

Iterative Subregion Correction Preconditioners with Adaptive Tolerance for Problems with Geometrically Localized Stiffness

We present a class of preconditioners for the linear systems resulting from a finite element or discontinuous Galerkin discretizations of advection-dominated problems.These preconditioners are designed to treat the case of geometrically localized stiffness,where the convergence rates of iterative methods are degraded in a localized subregion of the mesh.Slower convergence may be caused by a number of factors,including the mesh size,anisotropy,highly variable coefficients,and more challenging physics.The approach taken in this work is to correct well-known preconditioners such as the block Jacobi and the block incomplete LU(ILU)with an adaptive inner subregion iteration.The goal of these preconditioners is to reduce the number of costly global iterations by accelerating the convergence in the stiff region by iterating on the less expensive reduced problem.The tolerance for the inner iteration is adaptively chosen to minimize subregion-local work while guaranteeing global convergence rates.We present analysis showing that the convergence of these preconditioners,even when combined with an adaptively selected tolerance,is independent of discretization parameters(e.g.,the mesh size and diffusion coefficient)in the subregion.We demonstrate significant performance improvements over black-box preconditioners when applied to several model convection-diffusion problems.Finally,we present performance results of several variations of iterative subregion correction preconditioners applied to the Reynolds number 2.25×10^(6)fluid flow over the NACA 0012 airfoil,as well as massively separated flow at 30°angle of attack.

Conditional Generative Adversarial Network Enabled Localized Stress Recovery of Periodic Composites

Structural damage in heterogeneousmaterials typically originates frommicrostructures where stress concentration occurs.Therefore,evaluating the magnitude and location of localized stress distributions within microstructures under external loading is crucial.Repeating unit cells(RUCs)are commonly used to represent microstructural details and homogenize the effective response of composites.This work develops a machine learning-based micromechanics tool to accurately predict the stress distributions of extracted RUCs.The locally exact homogenization theory efficiently generates the microstructural stresses of RUCs with a wide range of parameters,including volume fraction,fiber/matrix property ratio,fiber shapes,and loading direction.Subsequently,the conditional generative adversarial network(cGAN)is employed and constructed as a surrogate model to establish the statistical correlation between these parameters and the corresponding localized stresses.The stresses predicted by cGAN are validated against the remaining true data not used for training,showing good agreement.This work demonstrates that the cGAN-based micromechanics tool effectively captures the local responses of composite RUCs.It can be used for predicting potential crack initiations starting from microstructures and evaluating the effective behavior of periodic composites.

Localized Application of Chinese Standards in Jakarta-Bandung HSR Project

Jakarta-Bandung HSR in Indonesia is the first“go global”project of China's high speed railway with a whole system,all elements and a whole industry chain,as well as the first overseas project adopting a complete set of Chinese standards.This paper sorts out the differences between relevant standards in China and Indonesia,including those in concrete raw materials,rebar standards and other main material standards,and those in external interface standards,train operation direction requirements,project approval requirements,special acceptance requirements,etc.,and summarizes the realization methods and specific achievements of localized application of Chinese standards during the implementation of Jakarta-Bandung HSR Project,to provide reference for localized application of Chinese standards in overseas projects in the future.

Regulating solid electrolyte interphases on phosphorus/carbon anodes via localized high-concentration electrolytes for potassium-ion batteries

The resourceful and inexpensive red phosphorus has emerged as a promising anode material of potassium-ion batteries(PIBs) for its large theoretical capacities and low redox potentials in the multielectron alloying/dealloying reactions,yet chronically suffering from the huge volume expansion/shrinkage with a sluggish reaction kinetics and an unsatisfactory interfacial stability against volatile electrolytes.Herein,we systematically developed a series of localized high-concentration electrolytes(LHCE) through diluting high-concentration ether electrolytes with a non-solvating fluorinated ether to regulate the formation/evolution of solid electrolyte interphases(SEI) on phosphorus/carbon(P/C) anodes for PIBs.Benefitting from the improved mechanical strength and structural stability of a robust/uniform SEI thin layer derived from a composition-optimized LHCE featured with a unique solvation structure and a superior K+migration capability,the P/C anode with noticeable pseudocapacitive behaviors could achieve a large reversible capacity of 760 mA h g^(-1)at 100 mA g^(-1),a remarkable capacity retention rate of 92.6% over 200 cycles at 800 mA g^(-1),and an exceptional rate capability of 334 mA h g^(-1)at8000 mA g^(-1).Critically,a suppressed reduction of ether solvents with a preferential decomposition of potassium salts in anion-derived interfacial reactions on P/C anode for LHCE could enable a rational construction of an outer organic-rich and inner inorganic-dominant SEI thin film with remarkable mechanical strength/flexibility to buffer huge volume variations and abundant K+diffusion channels to accelerate reaction kinetics.Additionally,the highly reversible/durable full PIBs coupling P/C anodes with annealed organic cathodes further verified an excellent practical applicability of LHCE.This encouraging work on electrolytes regulating SEI formation/evolution would advance the development of P/C anodes for high-performance PIBs.

Genome-wide investigation to assess copy number variants in the Italian local chicken population

Background Copy number variants(CNV)hold significant functional and evolutionary importance.Numerous ongoing CNV studies aim to elucidate the etiology of human diseases and gain insights into the population structure of livestock.High-density chips have enabled the detection of CNV with increased resolution,leading to the identification of even small CNV.This study aimed to identify CNV in local Italian chicken breeds and investigate their distribution across the genome.Results Copy number variants were mainly distributed across the first six chromosomes and primarily associated with loss type CNV.The majority of CNV in the investigated breeds were of types 0 and 1,and the minimum length of CNV was significantly larger than that reported in previous studies.Interestingly,a high proportion of the length of chromosome 16 was covered by copy number variation regions(CNVR),with the major histocompatibility complex being the likely cause.Among the genes identified within CNVR,only those present in at least five animals across breeds(n=95)were discussed to reduce the focus on redundant CNV.Some of these genes have been associated to functional traits in chickens.Notably,several CNVR on different chromosomes harbor genes related to muscle development,tissue-specific biological processes,heat stress resistance,and immune response.Quantitative trait loci(QTL)were also analyzed to investigate potential overlapping with the identified CNVR:54 out of the 95 gene-containing regions overlapped with 428 QTL associated to body weight and size,carcass characteristics,egg production,egg components,fat deposition,and feed intake.Conclusions The genomic phenomena reported in this study that can cause changes in the distribution of CNV within the genome over time and the comparison of these differences in CNVR of the local chicken breeds could help in preserving these genetic resources.

Present situation and prospect of immunotherapy for unresectable locally advanced esophageal cancer during peri-radiotherapy

Four major studies(Checkmate577,Keynote-590,Checkmate649 and Attraction-4)of locally advanced esophageal cancer published in 2020 have established the importance of immunotherapy,represented by anti-programmed death protein(PD)-1 in postoperative adjuvant treatment and advanced first-line treatment of locally advanced or advanced esophageal cancer and esophagogastric junction cancer,from the aspects of proof of concept,long-term survival,overall survival rate and progression-free survival.For unresectable or inoperable nonmetastatic esophageal cancer,concurrent radiotherapy and chemotherapy is the standard treatment recommended by various guidelines.Because its curative effect is still not ideal,it is necessary to explore radical radiotherapy and chemotherapy in the future,and it is considered to be promising to combine them with immunotherapeutic drugs such as anti-PD-1.This paper mainly discusses how to combine radical concurrent radiotherapy and chemotherapy with immunotherapy for unresectable local advanced esophageal cancer.

Deep brain implantable microelectrode arrays for detection and functional localization of the subthalamic nucleus in rats with Parkinson’s disease

The subthalamic nucleus(STN)is considered the best target for deep brain stimulation treatments of Parkinson’s disease(PD).It is difficult to localize the STN due to its small size and deep location.Multichannel microelectrode arrays(MEAs)can rapidly and precisely locate the STN,which is important for precise stimulation.In this paper,16-channel MEAs modified with multiwalled carbon nanotube/poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(MWCNT/PEDOT:PSS)nanocomposites were designed and fabricated,and the accurate and rapid identification of the STN in PD rats was performed using detection sites distributed at different brain depths.These results showed that nuclei in 6-hydroxydopamine hydrobromide(6-OHDA)-lesioned brains discharged more intensely than those in unlesioned brains.In addition,the MEA simultaneously acquired neural signals from both the STN and the upper or lower boundary nuclei of the STN.Moreover,higher values of spike firing rate,spike amplitude,local field potential(LFP)power,and beta oscillations were detected in the STN of the 6-OHDA-lesioned brain,and may therefore be biomarkers of STN localization.Compared with the STNs of unlesioned brains,the power spectral density of spikes and LFPs synchronously decreased in the delta band and increased in the beta band of 6-OHDA-lesioned brains.This may be a cause of sleep and motor disorders associated with PD.Overall,this work describes a new cellular-level localization and detection method and provides a tool for future studies of deep brain nuclei.

Corrigendum to“Electromagnetically induced transparency via localized surface plasmon mode-assisted hybrid cavity QED”

We would like to point out the misprinted Fig.3 in our published paper[Chin.Phys.B 32,114205(2023)].Since only orders of subfigures need to be corrected and the main results of the published paper are correct,we present the correct figure in this corrigendum.

Electromagnetically induced transparency via localized surface plasmon mode-assisted hybrid cavity QED

In recent years, most studies have focused on the perfect absorption and high-efficiency quantum memory of the onesided system, ignoring the characteristics of its optical switching contrast. Thus, the performance of all-optical switching and optical transistors is limited. Herein, we propose a localized surface plasmon(LSP) mode-assisted cavity QED system which consists of a Λ-shaped three-level quantum emitter(QE), a metal nanoparticle and a one-sided optical cavity with a fully reflected mirror. In this system, the QE coherently couples to the cavity and LSP mode respectively, which is manipulated by the control field. As a result, considerably high and stable switch contrast of 90% can be achievable due to the strong confined field of the LSP mode and perfect absorption of the optical medium. In addition, we obtain a power dependent effect between the control field and the transmitted frequency as a result of the converted dark state. We employ the Heisenberg–Langevin equation and numerical master equation formalisms to explain high switching, controllable output light and the dark state. Our system introduces an effective method to improve the performance of optical switches based on the one-sided system in quantum information storage and quantum communication.

A Novel Localized Meshless Method for Solving Transient Heat Conduction Problems in Complicated Domains

This paper first attempts to solve the transient heat conduction problem by combining the recently proposed local knot method(LKM)with the dual reciprocity method(DRM).Firstly,the temporal derivative is discretized by a finite difference scheme,and thus the governing equation of transient heat transfer is transformed into a non-homogeneous modified Helmholtz equation.Secondly,the solution of the non-homogeneous modified Helmholtz equation is decomposed into a particular solution and a homogeneous solution.And then,the DRM and LKM are used to solve the particular solution of the non-homogeneous equation and the homogeneous solution of the modified Helmholtz equation,respectively.The LKM is a recently proposed local radial basis function collocationmethod with themerits of being simple,accurate,and free ofmesh and integration.Compared with the traditional domain-type and boundary-type schemes,the present coupling algorithm could be treated as a really good alternative for the analysis of transient heat conduction on high-dimensional and complicated domains.Numerical experiments,including two-and three-dimensional heat transfer models,demonstrated the effectiveness and accuracy of the new methodology.

A review of soldering by localized heating

In recent years,the rapid development of the new energy industry has driven continuous upgrading of high-density and high-power devices.In the packaging and assembly process,the problem of differentiation of the thermal needs of different modules has become increasingly prominent,especially for small-size solder joints with high heat dissipation in high-power devices.Localized soldering is con-sidered a suitable choice to selectively heat the desired target while not affecting other heat-sensitive chips.This paper reviews several local-ized soldering processes,focusing on the size of solder joints,soldering materials,and current state of the technique.Each localized solder-ing process was discovered to have unique characteristics.The requirements for small-size solder joints are met by laser soldering,microres-istance soldering,and self-propagating soldering;however,laser soldering has difficulty meeting the requirements for large heat dissipation,microresistance soldering requires the application of pressure to joints,and self-propagating soldering requires ignition materials.However,for small-size solder junctions,selective wave soldering,microwave soldering,and ultrasonic soldering are not appropriate.Because the magnetic field can be focused on a tiny area and the output energy of induction heating is large,induction soldering can be employed as a significant trend in future research.

Unveiling localized electronic properties of ReS2 thin layers at nanoscale using Kelvin force probe microscopy combined with tip-enhanced Raman spectroscopy

Electronic properties of two-dimensional(2D) materials can be strongly modulated by localized strain. The typical spatial resolution of conventional Kelvin probe force microscopy(KPFM) is usually limited in a few hundreds of nanometers, and it is difficult to characterize localized electronic properties of 2D materials at nanoscales. Herein, tip-enhanced Raman spectroscopy(TERS) is proposed to combine with KPFM to break this restriction. TERS scan is conducted on ReS2bubbles deposited on a rough Au thin film to obtain strain distribution by using the Raman peak shift. The localized contact potential difference(CPD) is inversely calculated with a higher spatial resolution by using strain measured by TERS and CPD-strain working curve obtained using conventional KPFM and atomic force microscopy. This method enhances the spatial resolution of CPD measurements and can be potentially used to characterize localized electronic properties of 2D materials.

Assessment of earthquake location uncertainties for the design of local seismic networks

The ability to estimate earthquake source locations,along with the appraisal of relevant uncertainties,is paramount in monitoring both natural and human-induced micro-seismicity.For this purpose,a monitoring network must be designed to minimize the location errors introduced by geometrically unbalanced networks.In this study,we first review different sources of errors relevant to the localization of seismic events,how they propagate through localization algorithms,and their impact on outcomes.We then propose a quantitative method,based on a Monte Carlo approach,to estimate the uncertainty in earthquake locations that is suited to the design,optimization,and assessment of the performance of a local seismic monitoring network.To illustrate the performance of the proposed approach,we analyzed the distribution of the localization uncertainties and their related dispersion for a highly dense grid of theoretical hypocenters in both the horizontal and vertical directions using an actual monitoring network layout.The results expand,quantitatively,the qualitative indications derived from purely geometrical parameters(azimuthal gap(AG))and classical detectability maps.The proposed method enables the systematic design,optimization,and evaluation of local seismic monitoring networks,enhancing monitoring accuracy in areas proximal to hydrocarbon production,geothermal fields,underground natural gas storage,and other subsurface activities.This approach aids in the accurate estimation of earthquake source locations and their associated uncertainties,which are crucial for assessing and mitigating seismic risks,thereby enabling the implementation of proactive measures to minimize potential hazards.From an operational perspective,reliably estimating location accuracy is crucial for evaluating the position of seismogenic sources and assessing possible links between well activities and the onset of seismicity.

SNR and RSSI Based an Optimized Machine Learning Based Indoor Localization Approach:Multistory Round Building Scenario over LoRa Network

In situations when the precise position of a machine is unknown,localization becomes crucial.This research focuses on improving the position prediction accuracy over long-range(LoRa)network using an optimized machine learning-based technique.In order to increase the prediction accuracy of the reference point position on the data collected using the fingerprinting method over LoRa technology,this study proposed an optimized machine learning(ML)based algorithm.Received signal strength indicator(RSSI)data from the sensors at different positions was first gathered via an experiment through the LoRa network in a multistory round layout building.The noise factor is also taken into account,and the signal-to-noise ratio(SNR)value is recorded for every RSSI measurement.This study concludes the examination of reference point accuracy with the modified KNN method(MKNN).MKNN was created to more precisely anticipate the position of the reference point.The findings showed that MKNN outperformed other algorithms in terms of accuracy and complexity.

Survey of Indoor Localization Based on Deep Learning

This study comprehensively examines the current state of deep learning (DL) usage in indoor positioning.It emphasizes the significance and efficiency of convolutional neural networks (CNNs) and recurrent neuralnetworks (RNNs). Unlike prior studies focused on single sensor modalities like Wi-Fi or Bluetooth, this researchexplores the integration of multiple sensor modalities (e.g.,Wi-Fi, Bluetooth, Ultra-Wideband, ZigBee) to expandindoor localization methods, particularly in obstructed environments. It addresses the challenge of precise objectlocalization, introducing a novel hybrid DL approach using received signal information (RSI), Received SignalStrength (RSS), and Channel State Information (CSI) data to enhance accuracy and stability. Moreover, thestudy introduces a device-free indoor localization algorithm, offering a significant advancement with potentialobject or individual tracking applications. It recognizes the increasing importance of indoor positioning forlocation-based services. It anticipates future developments while acknowledging challenges such as multipathinterference, noise, data standardization, and scarcity of labeled data. This research contributes significantly toindoor localization technology, offering adaptability, device independence, and multifaceted DL-based solutionsfor real-world challenges and future advancements. Thus, the proposed work addresses challenges in objectlocalization precision and introduces a novel hybrid deep learning approach, contributing to advancing locationcentricservices.While deep learning-based indoor localization techniques have improved accuracy, challenges likedata noise, standardization, and availability of training data persist. However, ongoing developments are expectedto enhance indoor positioning systems to meet real-world demands.