Resilient performance of self-centering hybrid rocking walls with curved interface under pseudo-static loading

Frame and rocking wall(FRW)structures have excellent resilient performance during earthquakes.However,the concrete at interfacial corners of rocking walls(RWs)is easily crushed due to local extreme compression during the rocking process.An innovative RW with a curved interface is proposed to prevent interfacial corners from producing local damage,enhancing its earthquake resilient performance(ERP).The precast wall panel with a curved interface is assembled into an integral self-centering hybrid rocking wall(SCRW)by two post-tensioned unbonded prestressed tendons.Moreover,two ordinary energy dissipation steel rebars and two shear reinforcements are arranged to increase the energy dissipation capacity and lateral resistance.Two SCRW specimens and one monolithic reinforced concrete(RC)shear wall(SW)were tested under pseudo-static loading to compare the ERPs of the proposed SCRW and the SW,focusing on studying the effect of the curved interface on the SCRW.The key resilient performance of rocking effects,failure modes,and hysteretic properties of the SCRW were explored.The results show that nonlinear deformations of the SCRW are concentrated along the interface between the SCRW and the foundation,avoiding damage within the SCRW.The restoring force provided by the prestressed tendons can effectively realize self-centering capacity with small residual deformation,and the resilient performance of the SCRW is better than that of monolithic SW.In addition,the curved interface of the SCRW makes the rocking center change and move inward,partially relieving the stress concentration and crush of concrete.The rocking range of the rocking center is about 41.4%of the width of the SCRW.

An Extrapolated Parallel Subgradient Projection Algorithm with Centering Technique for the Convex Feasibility Problem

In this paper,we present an extrapolated parallel subgradient projection method with the centering technique for the convex feasibility problem,the algorithm improves the convergence by reason of using centering techniques which reduce the oscillation of the corresponding sequence.To prove the convergence in a simply way,we transmit the parallel algorithm in the original space to a sequential one in a newly constructed product space.Thus,the convergence of the parallel algorithm is derived with the help of the sequential one under some suitable conditions.Numerical results show that the new algorithm has better convergence than the existing algorithms.

Could Sequential Residual Centering Resolve Low Sensitivity in Moderated Regression? Simulations and Cancer Symptom Clusters

Multicollinearity constitutes shared variation among predictors that inflates standard errors of regression coefficients. Several years ago, it was proven that the common practice of mean centering in moderated regression cannot alleviate multicollinearity among variables comprising an interaction, but merely masks it. Residual centering (orthogonalizing) is unacceptable because it biases parameters for predictors from which the interaction derives, thus precluding interpretation of moderator effects. I propose and validate residual centering in sequential re-estimations of a moderated regression—sequential residual centering (SRC)—by revealing unbiased multicollinearity conditioning across the interaction and its related terms. Across simulations, SRC reduces variance inflation factors (VIF) regardless of distribution shape or pattern of regression coefficients across predictors. For any predictor, the reduced VIF is used to derive a lower standard error of its regression coefficient. A cancer sample illustrates SRC, which allows unbiased interpretations of symptom clusters. SRC can be applied efficiently to alleviate multicollinearity after data collection and shows promise for advancing synergistic frontiers of research.

GRAPHICAL COMPUTING METHOD ON FOUR-BAR LINKAGE(1)——Inflexion Circle,Focal Axis,Ball's Point,Centering-point Curve and Circling-point Curve For Four ISPs,Coupler Curves Based on Ball's Points——

By means of programs GTMPAC based- on generalized triangle method,analysis and synthesis of mechanism design in accordance with absolutely graphicalmethod( absolutely germetrical method) are developed.In this paper,we make aspecial study about centering- point curve and circling- point curve and couplercurves based on Ball’s points.

Local Curvature and Centering Effects in Nonlinear Regression Models

The effects of centering response and explanatory variables as a way of simplifying fitted linear models in the presence of correlation are reviewed and extended to include nonlinear models, common in many biological and economic applications. In a nonlinear model, the use of a local approximation can modify the effect of centering. Even in the presence of uncorrelated explanatory variables, centering may affect linear approximations and related test statistics. An approach to assessing this effect in relation to intrinsic curvature is developed and applied. Mis-specification bias of linear versus nonlinear models also reflects this centering effect.

怡化全面启动Call Centering服务系统

本刊讯日前，怡化启动了自主研发的Call Center服务系统，致力让银行更好地了解设备运行状况，提供一站式怏捷的技术支持和售后服务，实现准确高效运营。该系统在YH—CRM客户关系管理信息平台的基础上，

A self-centering and stiffness-controlled MEMS accelerometer

This paper presents a high-performance MEMS accelerometer with a DC/AC electrostatic stiffness tuning capability based on double-sided parallel plates(DSPPs).DC and AC electrostatic tuning enable the adjustment of the effective stiffness and the calibration of the geometric offset of the proof mass,respectively.A dynamical model of the proposed accelerometer was developed considering both DC/AC electrostatic tuning and the temperature effect.Based on the dynamical model,a self-centering closed loop is proposed for pulling the reference position of the forceto-rebalance(FTR)to the geometric center of DSPP.The self-centering accelerometer operates at the optimal reference position by eliminating the temperature drift of the readout circuit and nulling the net electrostatic tuning forces.The stiffness closed-loop is also incorporated to prevent the pull-in instability of the tuned low-stiffness accelerometer under a dramatic temperature variation.Real-time adjustments of the reference position and the DC tuning voltage are utilized to compensate for the residue temperature drift of the proposed accelerometer.As a result,a novel controlling approach composed of a self-centering closed loop,stiffness-closed loop,and temperature drift compensation is achieved for the accelerometer,realizing a temperature drift coefficient(TDC)of approximately 7μg/℃ and an Allan bias instability of less than 1μg.

Insights into ionic association boosting water oxidation activity and dynamic stability

There have been reports about Fe ions boosting oxygen evolution reaction(OER)activity of Ni-based catalysts in alkaline conditions,while the origin and reason for the enhancement remains elusive.Herein,we attempt to identify the activity improvement and discover that Ni sites act as a host to attract Fe(Ⅲ)to form Fe(Ni)(Ⅲ)binary centres,which serve as the dynamic sites to promote OER activity and stability by cyclical formation of intermediates(Fe(Ⅲ)→Fe(Ni)(Ⅲ)→Fe(Ni)-OH→Fe(Ni)-O→Fe(Ni)OOH→Fe(Ⅲ))at the electrode/electrolyte interface to emit O_(2).Additionally,some ions(Co(Ⅱ),Ni(Ⅱ),and Cr(Ⅲ))can also be the active sites to catalyze the OER process on a variety of electrodes.The Fe(Ⅲ)-catalyzed overall water-splitting electrolyzer comprising bare Ni foam as the anode and Pt/Ni-Mo as the cathode demonstrates robust stability for 1600 h at 1000 mA cm^(-2)@~1.75 V.The results provide insights into the ioncatalyzed effects boosting OER performance.

Activating d^(10)electronic configuration to regulate p-band centers as efficient active sites for solar energy conversion into H_(2)by surface atomic arrangement

Relationship between the activity for photocatalytic H_(2)O overall splitting(HOS)and the electron occupancy on d orbits of the active component in photocatalysts shows volcanic diagram,and specially the d^(10)electronic configuration in valley bottom exhibits inert activity,which seriously fetters the development of catalytic materials with great potentials.Herein,In d^(10)electronic configuration of In_(2)O_(3)was activated by phosphorus atoms replacing its lattice oxygen to regulate the collocation of the ascended In 5p-band(Inɛ5p)and descended O 2p-band(Oɛ2p)centers as efficient active sites for chemisorption to*OH and*H during forward HOS,respectively,along with a declined In 4d-band center(Inɛ4d)to inhibit its backward reaction.A stable STH efficiency of 2.23%under AM 1.5 G irradiation at 65°C has been obtained over the activated d^(10)electronic configuration with a lowered activation energy for H_(2)evolution,verified by femtosecond transient absorption spectroscopy,in situ diffuse reflectance infrared Fourier transform spectroscopy and theoretical calculations of dynamics.These findings devote to activating d^(10)electronic configuration for resolving the reaction energy barrier and dynamical bottleneck of forward HOS,which expands the exploration of high-efficiency catalytic materials.

Introducing hydroxyl groups to tailor the d-band center of Ir atom through side anchoring for boosted ORR and HER

Tuning the coordination atoms of central metal is an effective means to improve the electrocatalytic activity of atomic catalysts.Herein,iridium(Ir) is proposed to be asymmetrically anchored by sp-N and pyridinic N of hydrogen-substituted graphdiyne(HsGDY),and coordinated with OH as an Ir atomic catalyst(Ir_(1)-N-HsGDY).The electron structures,especially the d-band center of Ir atom,are optimized by these specific coordination atoms.Thus,the as-synthesized Ir_(1)-N-HsGDY exhibits excellent electrocatalytic performances for oxygen reduction and hydrogen evolution reactions in both acidic and alkaline media.Benefiting from the unique structure of HsGDY,IrN_(2)(OH)_(3) has been developed and demonstrated to act as the active site in these electrochemical reactions.All those indicate the fresh role of the sp-N in graphdiyne in producing a new anchor way and contributing to promote the electrocatalytic activity,showing a new strategy to design novel electrochemical catalysts.

In-situ construction of abundant active centers on hierarchically porous carbon electrode toward high-performance phosphate electrosorption: Synergistic effect of electric field and capture sites

Phosphate removal is crucial for eutrophication control and water quality improvement.Electro-assisted adsorption,an eco-friendly elec-trosorption process,exhibited a promising potential for wastewater treatment.However,there are few works focused on phosphate electro-sorption,and reported electrodes cannot attach satisfactory removal capacities and rates.Herein,electro-assisted adsorption of phosphate via in-situ construction of La active centers on hierarchically porous carbon(LaPC)has been originally demonstrated.The resulted LaPC composite not only possessed a hierarchically porous structure with uniformly dispersed La active sites,but also provided good conductivity for interfacial electron transfer.The LaPC electrode achieved an ultrahigh phosphate electrosorption capability of 462.01 mg g^(-1) at 1 V,outperforming most existing electrodes.The superior phosphate removal performance originates from abundant active centers formed by the coupling of electricfield and capture sites.Besides,the stability and selectivity toward phosphate capture were maintained well even under comprehensive conditions.Moreover,a series of kinetics and isotherms models were employed to validate the electrosorption process.This work demonstrates a deep understanding and promotes a new level of phosphate electrosorption.

Cortical hem signaling center: functions, development, and potential implications for evolution and brain disorders

Development of the telencephalon relies upon several signaling centers-localized cellular populations that supply secreted factors to pattern the cortical neuroepithelium.One such signaling center is the cortical hem,which arises during embryonic development at the telencephalic dorsal midline,adjacent to the choroid plexus and hippocampal primordium(Figure 1A).While the cortical hem has also been described in reptiles and birds,most of our knowledge about the developmental roles of the cortical hem is derived from the analysis in mice.The cortical hem produces several types of secreted molecules,including wingless-related integration site(Wnt)and bone morphogenetic(Bmp)proteins.The cortical hem is particularly important for the development of the hippocampus,which is involved in learning and memory,and the neocortex,which is the most complex brain region that mediates multiple types of behavior and higher cognitive functions(Mangale et al.,2008;Dal-Valle-Anton and Borrell,2022).

Preparing highly entangled states of nanodiamond rotation and NV center spin

A nanodiamond with an embedded nitrogen-vacancy(NV)center is one of the experimental systems that can be coherently manipulated within current technologies.Entanglement between NV center electron spin and mechanical rotation of the nanodiamond plays a fundamental role in building a quantum network connecting these microscopic and mesoscopic degrees of motions.Here we present a protocol to asymptotically prepare a highly entangled state of the total quantum angular momentum and electron spin by adiabatically boosting the external magnetic field.

An Adaptive Congestion Control Optimization Strategy in SDN-Based Data Centers

The traffic within data centers exhibits bursts and unpredictable patterns.This rapid growth in network traffic has two consequences:it surpasses the inherent capacity of the network’s link bandwidth and creates an imbalanced network load.Consequently,persistent overload situations eventually result in network congestion.The Software Defined Network(SDN)technology is employed in data centers as a network architecture to enhance performance.This paper introduces an adaptive congestion control strategy,named DA-DCTCP,for SDN-based Data Centers.It incorporates Explicit Congestion Notification(ECN)and Round-Trip Time(RTT)to establish congestion awareness and an ECN marking model.To mitigate incorrect congestion caused by abrupt flows,an appropriate ECN marking is selected based on the queue length and its growth slope,and the congestion window(CWND)is adjusted by calculating RTT.Simultaneously,the marking threshold for queue length is continuously adapted using the current queue length of the switch as a parameter to accommodate changes in data centers.The evaluation conducted through Mininet simulations demonstrates that DA-DCTCP yields advantages in terms of throughput,flow completion time(FCT),latency,and resistance against packet loss.These benefits contribute to reducing data center congestion,enhancing the stability of data transmission,and improving throughput.

Design of compact integrated diamond nitrogen-vacancy center quantum probe

An integrated quantum probe for magnetic field imaging is proposed,where the nitrogen–vacancy(NV)center fixed at the fiber tip is located on the periphery of flexible ring resonator.Using flexible polyimide(PI)as the substrate medium,we design a circular microstrip antenna,which can achieve a bandwidth of 140 MHz at Zeeman splitting frequency of 2.87 GHz,specifically suitable for NV center experiments.Subsequently,this antenna is seamlessly fixed at a three-dimensional-printed cylindrical support,allowing the optical fiber tip to extend out of a dedicated aperture.To mitigate errors originating from processing,precise tuning within a narrow range can be achieved by adjusting the conformal amplitude.Finally,we image the microwave magnetic field around the integrated probe with high resolution,and determine the suitable area for placing the fiber tip(SAP).

A new monitoring index for ecological vulnerability and its application in the Yellow River Basin,China from 2000 to 2022

The ecological environment of the Yellow River Basin has become more fragile under the combined action of natural and manmade activities.However,the change mechanisms of ecological vulnerability in different sub-regions and periods vary,and the reasons for this variability are yet to be explained.Thus,in this study,we proposed a new remote sensing ecological vulnerability index by considering moisture,heat,greenness,dryness,land degradation,and social economy indicators and then analyzed and disclosed the spatial and temporal change patterns of ecological vulnerability of the Yellow River Basin,China from 2000 to 2022 and its driving mechanisms.The results showed that the newly proposed remote sensing ecological vulnerability index had a high accuracy,at 86.36%,which indicated a higher applicability in the Yellow River Basin.From 2000 to 2022,the average remote sensing ecological vulnerability index of the Yellow River Basin was 1.03,denoting moderate vulnerability level.The intensive vulnerability area was the most widely distributed,which was mostly located in the northern part of Shaanxi Province and the eastern part of Shanxi Province.From 2000 to 2022,the ecological vulnerability in the Yellow showed an overall stable trend,while that of the central and eastern regions showed an obvious trend of improvement.The gravity center of ecological vulnerability migrated southwest,indicating that the aggravation of ecological vulnerability in the southwestern regions was more severe than in the northeastern regions of the basin.The dominant single factor of changes in ecological vulnerability shifted from normalized difference vegetation index(NDVI)to temperature from 2000 to 2022,and the interaction factors shifted from temperature∩NDVI to temperature∩precipitation,which indicated that the global climate change exerted a more significant impact on regional ecosystems.The above results could provide decision support for the ecological protection and restoration of the Yellow River Basin.

Performance Prediction Based Workload Scheduling in Co-Located Cluster

Cloud service providers generally co-locate online services and batch jobs onto the same computer cluster,where the resources can be pooled in order to maximize data center resource utilization.Due to resource competition between batch jobs and online services,co-location frequently impairs the performance of online services.This study presents a quality of service(QoS)prediction-based schedulingmodel(QPSM)for co-locatedworkloads.The performance prediction of QPSM consists of two parts:the prediction of an online service’s QoS anomaly based on XGBoost and the prediction of the completion time of an offline batch job based on randomforest.On-line service QoS anomaly prediction is used to evaluate the influence of batch jobmix on on-line service performance,and batch job completion time prediction is utilized to reduce the total waiting time of batch jobs.When the same number of batch jobs are scheduled in experiments using typical test sets such as CloudSuite,the scheduling time required by QPSM is reduced by about 6 h on average compared with the first-come,first-served strategy and by about 11 h compared with the random scheduling strategy.Compared with the non-co-located situation,QPSM can improve CPU resource utilization by 12.15% and memory resource utilization by 5.7% on average.Experiments show that the QPSM scheduling strategy proposed in this study can effectively guarantee the quality of online services and further improve cluster resource utilization.

Micron-sized fiber diamond probe for quantum precision measurement of microwave magnetic field

We present a quantitative measurement of the horizontal component of the microwave magnetic field of a coplanar waveguide using a quantum diamond probe in fiber format.The measurement results are compared in detail with simulation,showing a good consistence.Further simulation shows fiber diamond probe brings negligible disturbance to the field under measurement compared to bulk diamond.This method will find important applications ranging from electromagnetic compatibility test and failure analysis of high frequency and high complexity integrated circuits.

Building Fe atom–cluster composite sites using a site occupation strategy to boost electrochemical oxygen reduction

The high-temperature pyrolysis process for preparing M–N–C single-atom catalyst usually results in high heterogeneity in product structure concurrently contains multiscale metal phases from single atoms(SAs),atomic clusters to nanoparticles.Therefore,understanding the interactions among these components,especially the synergistic effects between single atomic sites and cluster sites,is crucial for improving the oxygen reduction reaction(ORR)activity of M–N–C catalysts.Accordingly,herein,we constructed a model catalyst composed of both atomically dispersed FeN4 SA sites and adjacent Fe clusters through a site occupation strategy.We found that the Fe clusters can optimize the adsorption strength of oxygen reduction intermediates on FeN4 SA sites by introducing electron-withdrawing–OH ligands and decreasing the d-band center of the Fe center.The as-developed catalyst exhibits encouraging ORR activity with halfwave potentials(E1/2)of 0.831 and 0.905 V in acidic and alkaline media,respectively.Moreover,the catalyst also represents excellent durability exceeding that of Fe–N–C SA catalyst.The practical application of Fe(Cd)–CNx catalyst is further validated by its superior activity and stability in a metalair battery device.Our work exhibits the great potential of synergistic effects between multiphase metal species for improvements of singleatom site catalysts.

Dynamic Routing of Multiple QoS-Required Flows in Cloud-Edge Autonomous Multi-Domain Data Center Networks

The 6th generation mobile networks(6G)network is a kind of multi-network interconnection and multi-scenario coexistence network,where multiple network domains break the original fixed boundaries to form connections and convergence.In this paper,with the optimization objective of maximizing network utility while ensuring flows performance-centric weighted fairness,this paper designs a reinforcement learning-based cloud-edge autonomous multi-domain data center network architecture that achieves single-domain autonomy and multi-domain collaboration.Due to the conflict between the utility of different flows,the bandwidth fairness allocation problem for various types of flows is formulated by considering different defined reward functions.Regarding the tradeoff between fairness and utility,this paper deals with the corresponding reward functions for the cases where the flows undergo abrupt changes and smooth changes in the flows.In addition,to accommodate the Quality of Service(QoS)requirements for multiple types of flows,this paper proposes a multi-domain autonomous routing algorithm called LSTM+MADDPG.Introducing a Long Short-Term Memory(LSTM)layer in the actor and critic networks,more information about temporal continuity is added,further enhancing the adaptive ability changes in the dynamic network environment.The LSTM+MADDPG algorithm is compared with the latest reinforcement learning algorithm by conducting experiments on real network topology and traffic traces,and the experimental results show that LSTM+MADDPG improves the delay convergence speed by 14.6%and delays the start moment of packet loss by 18.2%compared with other algorithms.