Two-step Scheme Research Articles

The SPES Laser Ion Source: Time Structure and Laser Enhancement Measurements with Sm+ beam

A two-step resonance photo-ionization scheme has been used to ionize samarium atoms in the SPES tantalum hot-cavity ion source. The effect of the ion load on the ion beam time structure and the laser enhancement of the ion yield has been studied at different ion source temperatures. Generally, the introduction of more positive ions (ion load) affects negatively the overall confinement of the laser ions inside the volume of the ion source. Possible enhancement of the laser ion confinement through the introduction of neutrals is observed as well. The ion load is also observed to affect the confinement in the transfer line much more than in the hot cavity. Measurement of the time structure with inverted polarity of the cavity DC heating supply confirmed the significance of the longitudinal potential for ion extraction. The laser enhancements of the ion yield are found to be sensitive to the ion load at low operating temperature of the ion source i.e. 1800°C, whereas at 2050°C and 2200°C, they are relatively stable till an ion load value of 1.2 µA.

Hemisynthesis and cytotoxic evaluation of manoyl oxide analogs from sclareol: effect of two tertiary hydroxyls & Heck coupling on cytotoxicity

Sclareol, a bioactive diterpene alcohol isolated from Salvia sclarea, was subjected to structural modification and cytotoxic evaluation. Boron-Heck-coupled analogs of manoyl oxide were prepared from sclareol in a two-step reaction scheme. In the first step manoyl oxide was prepared from sclareol using cerium (IV) ammonium nitrate. Further the structural modification of manoyl oxide via Palladium (II) catalysed Boron-Heck coupling reaction produced a new series of compounds. All the synthesised compounds were screened for in vitro cytotoxic evaluation against four cancer cell lines HCT-116, MCF-7, MDA-MB231and MDA-MB468. The results showed that manoyl oxide is less active than sclareol. Sclareol shows an IC50 of 2.0 µM compared to manoyl oxide with an IC50 of 50 µM against the MCF-7 cell line. From the results it was inferred that the presence of two tertiary hydroxyls in sclareol are necessary for its cytotoxic activity and Heck coupled analogs are more active than sclareol and manoyl oxide.

Toward static and transient stress-constrained topology optimization for shell-infill structures

This paper contributes to a stress-constrained topology optimization approach for the design of shell-infill structures. Based on the density method, we utilize the two-step filtering and projection scheme and local volume constraint for generating the shell and non-uniform infills, respectively. The topology optimization formulation is defined as a Robust Minimum Compliance problem with Volume and Stress constraints (RMCVS), where the robust method is used to eliminate undesired topological characteristics. We globalize the static and transient stress constraints through the p-norm function, and tailor material interpolation and stress relaxation schemes for both cases, respectively, to avoid numerical difficulties. Sensitivity analysis is provided, and the derivatives of the objective function and constraints with respect to the design variable fields are derived. We then validate the suggested method through several 2D and 3D benchmarks. The results illustrate that the method is robust to generate various shell-infill structures while limiting the maximum static and transient stress.

Relativistic coupled cluster study on the spectroscopic and radiative properties of the KFr molecule and modeling of the transport properties of potassium–francium dilute gas medium

The KFr diatomic molecule represents a promising candidate for photoassociation and indirect laser cooling. It has not yet been investigated experimentally and remains the only representative of the family of alkali-metal diatomics, which is scarcely researched theoretically. The potential energy curves of the states belonging to the three lowest dissociation limits of the KFr molecule are calculated using the Fock-space relativistic coupled cluster theory for the first time. Properties and parameters, such as electronic term energies, equilibrium internuclear distances, transition and permanent dipole moments, sequences of vibrational energies, harmonic vibrational frequencies, Franck–Condon factors, and radiative lifetimes (including bound and free transitions), are predicted. We analyzed and evaluated the probabilities of the two-step schemes (optical cycles) for the transfer process of the KFr molecules from excited vibronic states to the ground vibronic state. The transport properties (diffusion, viscosity, and thermal conductivity coefficients) of two-component dilute gas media of potassium and francium atoms as functions of the translation temperature up to 3000 K are also calculated. The data obtained would be useful for laser cooling and spectral experiments with KFr molecules.

Complexin has a dual synaptic function as checkpoint protein in vesicle priming and as a promoter of vesicle fusion

The presynaptic SNARE-complex regulator complexin (Cplx) enhances the fusogenicity of primed synaptic vesicles (SVs). Consequently, Cplx deletion impairs action potential-evoked transmitter release. Conversely, though, Cplx loss enhances spontaneous and delayed asynchronous release at certain synapse types. Using electrophysiology and kinetic modeling, we show that such seemingly contradictory transmitter release phenotypes seen upon Cplx deletion can be explained by an additional of Cplx in the control of SV priming, where its ablation facilitates the generation of a "faulty" SV fusion apparatus. Supporting this notion, a sequential two-step priming scheme, featuring reduced vesicle fusogenicity and increased transition rates into the faulty primed state, reproduces all aberrations of transmitter release modes and short-term synaptic plasticity seen upon Cplx loss. Accordingly, we propose a dual presynaptic function for the SNARE-complex interactor Cplx, one as a "checkpoint" protein that guarantees the proper assembly of the fusion machinery during vesicle priming, and one in boosting vesicle fusogenicity.

Updating to Optimal Parametric Values by Memory-Dependent Methods: Iterative Schemes of Fractional Type for Solving Nonlinear Equations

In the paper, two nonlinear variants of the Newton method are developed for solving nonlinear equations. The derivative-free nonlinear fractional type of the one-step iterative scheme of a fourth-order convergence contains three parameters, whose optimal values are obtained by a memory-dependent updating method. Then, as the extensions of a one-step linear fractional type method, we explore the fractional types of two- and three-step iterative schemes, which possess sixth- and twelfth-order convergences when the parameters’ values are optimal; the efficiency indexes are 6 and 123, respectively. An extra variable is supplemented into the second-degree Newton polynomial for the data interpolation of the two-step iterative scheme of fractional type, and a relaxation factor is accelerated by the memory-dependent method. Three memory-dependent updating methods are developed in the three-step iterative schemes of linear fractional type, whose performances are greatly strengthened. In the three-step iterative scheme, when the first step involves using the nonlinear fractional type model, the order of convergence is raised to sixteen. The efficiency index also increases to 163, and a third-degree Newton polynomial is taken to update the values of optimal parameters.

Target Development towards First Production of High-Molar- Activity 44gSc and 47Sc by Mass Separation at CERN-MEDICIS.

The radionuclides 43Sc, 44g/mSc, and 47Sc can be produced cost-effectively in sufficient yield for medical research and applications by irradiating natTi and natV target materials with protons. Maximizing the production yield of the therapeutic 47Sc in the highest cross section energy range of 24-70 MeV results in the co-production of long-lived, high-γ-ray-energy 46Sc and 48Sc contaminants if one does not use enriched target materials. Mass separation can be used to obtain high molar activity and isotopically pure Sc radionuclides from natural target materials; however, suitable operational conditions to obtain relevant activity released from irradiated natTi and natV have not yet been established at CERN-MEDICIS and ISOLDE. The objective of this work was to develop target units for the production, release, and purification of Sc radionuclides by mass separation as well as to investigate target materials for the mass separation that are compatible with high-yield Sc radionuclide production in the 9-70 MeV proton energy range. In this study, the in-target production yield obtained at MEDICIS with 1.4 GeV protons is compared with the production yield that can be reached with commercially available cyclotrons. The thick-target materials were irradiated at MEDICIS and comprised of metallic natTi, natV metallic foils, and natTiC pellets. The produced radionuclides were subsequently released, ionized, and extracted from various target and ion source units and mass separated. Mono-atomic Sc laser and molecule ionization with forced-electron-beam-induced arc-discharge ion sources were investigated. Sc radionuclide production in thick natTi and natV targets at MEDICIS is equivalent to low- to medium-energy cyclotron-irradiated targets at medically relevant yields, furthermore benefiting from the mass separation possibility. A two-step laser resonance ionization scheme was used to obtain mono-atomic Sc ion beams. Sc radionuclide release from irradiated target units most effectively could be promoted by volatile scandium fluoride formation. Thus, isotopically pure 44g/mSc, 46Sc, and 47Sc were obtained as mono-atomic and molecular ScF 2+ ion beams and collected for the first time at CERN-MEDICIS. Among all the investigated target materials, natTiC is the most suitable target material for Sc mass separation as molecular halide beams, due to high possible operating temperatures and sustained release.

Trace Silicon Determination in Biological Samples by Inductively Coupled Plasma Mass Spectrometry (ICP-MS): Insight into the Volatility of Silicon Species in Hydrofluoric Acid Digests for Optimal Sample Preparation and Introduction to ICP-MS

A method for the determination of trace levels of silicon from biological materials by inductively coupled plasma mass spectrometry (ICP-MS) has been developed. The volatility of water-soluble silicon species, hexafluorosilicic acid (H2SiF6), and sodium metasilicate (Na2SiO3) was investigated by evaporating respective solutions (50 µg/mL silicon) in HNO3), nitric acid + hydrochloric acid (HNO3 + HCl), and nitric acid + hydrochloric acid + hydrofluoric acid (HNO3 + HCl + HF) at 120 °C on a hot-block to near dryness. The loss of silicon from H2SiF6 solutions was substantial (>99%) regardless of the digestion medium. Losses were also substantial (>98%) for metasilicate solutions heated in HNO3 + HCl + HF, while no significant loss occurred in HNO3 or HNO3 + HCl. These results show that H2SiF6 species were highly volatile and potential losses could confound accuracy at trace level determinations by ICP-MS if digestates prepared in HF are heated to eliminate HF. Among the various matrices comprising major elements, sodium appeared to be effective in reducing silicon loss from H2SiF6 solutions. Excess sodium chloride (NaCl) matrix provided better stability, improving silicon recoveries by up to about 80% in evaporated HF digestates of soil and mine waste samples, but losses could not be fully prevented. To safely remove excess acids and circumvent the adverse effects of excess HF (e.g., risk of high Si background signals), a two-step digestion scheme was adopted for the preparation of biological samples containing trace silicon levels. A closed-vessel digestion was performed either in 4 mL of concentrated HNO3 and 1 mL of concentrated HCl or 4 mL of concentrated HNO3, 1 mL of concentrated HCl and 1 mL of concentrated HClO4 on a hot plate at 140 °C. Digestates were then evaporated to incipient dryness at 120 °C to remove the acids. A second closed-vessel digestion was carried out to dissolve silicates in 0.5 mL of concentrated HNO3 and 0.5 mL of concentrated HF at 130 °C. After digestion, digestates were diluted to 10 mL. The solution containing about 5% HNO3 and 5% HF was directly analyzed by ICP-MS equipped with an HF-inert sample introduction system. The limit of detection was about 110 µg/L for 28Si when using the Kinetic Energy Discrimination (KED) mode. The method was used to determine silicon in various plant and tissue certified reference materials. Data were acquired for 28Si using KED and standard (STD) modes, and 74Ge and 103Rh as internal standard elements. There was not any significant difference between the accuracy and precision of the results obtained with 74Ge and 103Rh within the same measurement mode. Precision, calculated as relative standard deviation for four replicate analyses, varied from 5.3 (tomato leaves) to 21% (peach leaves) for plant and from 2.2 (oyster tissue) to 33% (bovine liver) for tissue SRM/CRMs. Poor precision was attributed to material heterogeneity and the large particle size distribution. An analysis of lung tissue samples from those with occupational exposure to silica dust revealed that tissues possessed substantial levels of water-soluble silicates, but the most silicon was present in the particulate matter fraction.

Accounting for spatial distribution in mean-field homogenization of particulate composites

Several analytical mean-field homogenization methods, which take into account the particle volume fraction, shape and orientation are readily available to estimate the effective properties of particulate composites. Models have also been proposed to account for the spatial distribution of the particles. The classical Ponte-Castañeda and Willis (PCW) model is based on a parametrization of the statistical distribution law, while the Interaction Direct Derivative (IDD) model associates a matrix cell to each inclusion, representative of close interactions. In the literature, the use of the IDD is commonly reduced to the particular case of the classical Mori and Tanaka (MT) scheme or to the aforementioned PCW model. The present study introduces an original approach to calibrate the IDD model, for 2D linear conductivity, based on representative images of the microstructure. The links between the models and the range of validity of the IDD model are discussed. Besides, an “IDD-based” PCW model and a two-step scheme are proposed for situations where the IDD estimate is inconsistent (lack of major symmetry). Finally, an image analysis method using Voronoï diagrams is implemented to define the cells associated to each inclusion and supply the models. The method is validated by comparisons between the obtained IDD and PCW estimates, the Mori–Tanaka (MT) model and benchmark full-field numerical simulations. Accounting for the inclusion distribution is seen to lead to better estimates, both qualitatively (by capturing anisotropic behaviors due to the sole distribution) and quantitatively. Possible extensions to elastic composites are discussed.

Optimisation of sugar and solid biofuel co-production from almond tree prunings by acid pretreatment and enzymatic hydrolysis.

Almond pruning biomass is an important agricultural residue that has been scarcely studied for the co-production of sugars and solid biofuels. In this work, the production of monosaccharides from almond prunings was optimised by a two-step process scheme: pretreatment with dilute sulphuric acid (0.025M, at 185.9-214.1℃ for 0.8-9.2min) followed by enzyme saccharification of the pretreated cellulose. The application of a response surface methodology enabled the mathematical modelling of the process, establishing pretreatment conditions to maximise both the amount of sugar in the acid prehydrolysate (23.4kg/100kg raw material, at 195.7℃ for 3.5min) and the enzymatic digestibility of the pretreated cellulose (45.4%, at 210.0℃ for 8.0min). The highest overall sugar yield (36.8kg/100kg raw material, equivalent to 64.3% of all sugars in the feedstock) was obtained with a pretreatment carried out at 197.0℃ for 4.0min. Under these conditions, moreover, the final solids showed better properties for thermochemical utilisation (22.0MJ/kg heating value, 0.87% ash content, and 72.1mg/g moisture adsorption capacity) compared to those of the original prunings.

Strategy to improve synaptic behavior of ion-actuated synaptic transistors—the use of ion blocking layer to improve state retention

Synaptic transistors (STs) with a gate/electrolyte/channel stack, where mobile ions are electrically driven across the solid electrolyte, have been considered as analog weight elements for neuromorphic computing. The current (ID) between the source and drain in the ST is analogously updated by gate voltage (VG) pulses, enabling high pattern recognition accuracy in neuromorphic systems; however, the governing physical mechanisms of the ST are not fully understood yet. Our previous physics-based simulation study showed that ion movement in the electrolyte, rather than the electrochemical reactions that occur in the channel, plays an important role in switching. In this study, we experimentally explore the properties of the HfOx electrolyte and show that by tuning the density of oxygen vacancies, it can assume the dual role of electrolyte and channel. We demonstrate analog synaptic behavior using a novel ST with a two-layer stack of CuOx/HfOx, where the CuOx is the gate and Cu ion reservoir, and the HfOx is the electrolyte and channel. To improve state retention and linearity, we introduce a Cu ion transport barrier in the form of a dense and stoichiometric Al2O3 layer. The CuOx/Al2O3/HfOx exhibits excellent state retention and improved potentiation and depression response. Energy dispersive spectroscopy mapping following potentiation confirms the role of the Al2O3 layer in confining the Cu ions in the HfOx layer. We also show that a two-step programming scheme can further enhance synaptic response and demonstrate high recognition accuracy on the Fashion-MNIST dataset in simulation.

Vertically averaged and moment equations: New derivation, efficient numerical solution and comparison with other physical approximations for modeling non-hydrostatic free surface flows

Efficient modeling of flow physics is a prerequisite for a reliable computation of free-surface environmental flows. Non-hydrostatic flows are often present in shallow water environments, making the task challenging. In this work, we use the method of weighted residuals for modeling non-hydrostatic free surface flows in a depth-averaged framework. In particular, we focus on the Vertically Averaged and Moment (VAM) equations model. First, a new derivation of the model is presented using expansions of the field variables in sigma-coordinates with Legendre polynomials basis. Second, an efficient two-step numerical scheme is proposed: the first step corresponds to solving the hyperbolic part with a second-order path-conservative PVM scheme. Then, in a second step, non-hydrostatic terms are corrected by solving a linear Poisson-like system using an iterative method, thereby resulting in an accurate and efficient algorithm. The computational effort is similar to the one required for the well-known Serre-Green-Naghdi (SGN) system, while the results are largely improved. Finally, the physical aspects of the model are compared to the SGN system and a multilayer model, demonstrating that VAM is comparable in physical accuracy to a two-layer model.

Enhancing the Assimilation of SWOT Simulated Observations Using a Multi-Scale 4DVAR Method in Regional Ocean Modeling System

This paper presents an innovative approach to enhance the assimilation of high-resolution simulated observations, specifically targeting Surface Water Ocean Topography (SWOT) Ka-band Radar Interferometer Sea Surface Height (SSH) products, within the Regional Ocean Modeling System (ROMS). Responding to the demand for improved assimilation techniques, we developed a multi-scale Four-Dimensional Variational Data Assimilation (4DVAR) system, building upon validated fine-scale correction capabilities from prior studies. The multi-scale strategy was extended to the ROMS-4DVAR system, providing a comprehensive solution for assimilating high-resolution observations. Leveraging the Observing System Simulation Experiment (OSSE) framework, we conducted a twin experiment comprising a nature run and a free run case. Subsequently, synthetic SWOT SSH measurements were decomposed, considering the model configuration resolution. These components, derived from dense SSH observations, were integrated into a two-step 4DVAR assimilation scheme. The first cycle targets large-scale features for model field correction, and the updated analysis serves as the background for the second assimilation step, addressing fine-scale observation components. Comparisons with the primitive ROMS-4DVAR using a single-scale scheme highlight the superiority of the multi-scale strategy in reducing gaps between the model and the SSH observations. The Root Mean Squared Error (RMSE) is halved, and the Mean Absolute Percentage Error (MAPE) decreases from 2.237% to 0.93%. The two-step assimilation procedure ensures comprehensive multi-scale updates in the SSH field simulation, enhancing fine-scale features in the analysis fields. The quantification of three-dimensional-model dynamic fields further validates the efficiency and superiority of the multi-scale 4DVAR approach, offering a robust methodology for assimilating high-resolution observations within the ROMS.

Obtaining morphometric standards of drone wings of separate populations of honey bees (Apis mellifera) in Ukraine

Today, there are no systematic studies on the wing phenotypes of drone populations of the honeybee widespread in Ukraine. Considering that drone genomes are haploid, this allows one to establish the correspondence between the phenotype and the drone genome, thereby roughly determining the queen's genome in the part responsible for the wing phenotype. This partially compensates for the lack of resources among domestic scientists to conduct genetic research on bees. The aim of the study was to examine the wings of drones from several apiaries in the Kharkiv, Sumy, Poltava, and Zhytomyr regions, identify typical phenotypes, and attempt their taxonomic identification. Using discriminant analysis, 4640 drone wings were classified into three clusters. A two-step scheme for forming significantly different phenotype clusters of wings was proposed. Initially, based on the similarity of Euclidean distances and Mahalanobis distances (<2.6) between clusters, three groups were obtained, which, for refinement, underwent a second classification. As a result, average values and confidence intervals of eight morphometric traits were established: Ci, Dbi, Disc.sh, Pci, Ri, Ci.3, Ci.2.1, Ci.2.2 for the three wing groups. It is suggested to accept the trait values of these groups as reference data: one as a local population of the A. m. carnica subspecies, and the other two as regional standards for Ukrainian bees. Based on the obtained standards, a significant presence of A. m. carnica subspecies bees was established in all studied apiaries, except for the apiary with the status of a breeding ground for Ukrainian steppe bees (Kuzemin village, Sumy region), where such presence is minimal. This fact indicates the need for special measures to reproduce and expand the ranges of existence of local populations of Ukrainian steppe bees. The example of creating local and regional morphometric standards provided in this work is specifically designed to address this issue.

New Memory-Updating Methods in Two-Step Newton’s Variants for Solving Nonlinear Equations with High Efficiency Index

In the paper, we iteratively solve a scalar nonlinear equation f(x)=0, where f∈C(I,R),x∈I⊂R, and I includes at least one real root r. Three novel two-step iterative schemes equipped with memory updating methods are developed; they are variants of the fixed-point Newton method. A triple data interpolation is carried out by the two-degree Newton polynomial, which is used to update the values of f′(r) and f″(r). The relaxation factor in the supplementary variable is accelerated by imposing an extra condition on the interpolant. The new memory method (NMM) can raise the efficiency index (E.I.) significantly. We apply the NMM to five existing fourth-order iterative methods, and the computed order of convergence (COC) and E.I. are evaluated by numerical tests. When the relaxation factor acceleration technique is combined with the modified Dzˇunic´’s memory method, the value of E.I. is much larger than that predicted by the paper [Kung, H.T.; Traub, J.F. J. Assoc. Comput. Machinery 1974, 21]. for the iterative method without memory.

A Facile Surface Modification Scheme for Medical-Grade Titanium and Polypropylene Using a Novel Mussel-Inspired Biomimetic Polymer with Cationic Quaternary Ammonium Functionalities for Antibacterial Application.

Medical device-associated infection remains a critical problem in the healthcare setting. Different clinical- or device-related methods have been attempted to reduce the infection rate. Among these approaches, creating a surface with bactericidal cationic functionality has been proposed. To do so, a sophisticated multi-step chemical procedure would be needed. Instead, a simple immersion approach was utilized in this investigation to render the titanium and polypropylene surface with the quaternary ammonium functionality by using a mussel-inspired novel lab-synthesized biomimetic catechol-terminated polymer, PQA-C8. The chemical oxidants, CuSO4/H2O2, as well as dopamine, were added into the novel PQA-C8 polymer immersion solution for one-step surface modification. Additionally, a two-step immersion scheme, in which the polypropylene substrate was first immersed in the dopamine solution and then in the PQA-C8 solution, was also attempted. Surface analysis results indicated the surface characteristics of the modified substrates were affected by the immersion solution formulation as well as the procedure utilized. The antibacterial assay has shown the titanium substrates modified by the one-step dopamine + PQA-C8 mixtures with the oxidants added and the polypropylene modified by the two-step scheme exhibited bacterial reduction percentages greater than 90% against both Gram-positive S. aureus and Gram-negative E. coli and these antibacterial substrates were non-cytotoxic.

The use of complex structure splines in roadway design

Objectives. The aim of the work is to develop the theory of spline-approximation of a sequence of points on a plane for using compound splines with a complex structure. In contrast to a simple spline (e.g., polynomial), a compound spline contains repeating bundles of several elements. Such problems typically arise in the design of traces for railroads and highways. The plan (projection on the horizontal plane) of such a trace is a curve consisting of a repeating bundle of elements “line + clothoid + circle + clothoid ...,” which ensures continuity not only of curve and tangent but also of curvature. The number of spline elements, which is unknown, should be determined in the process of solving the design problem. An algorithm for solving the problem with respect to the spline, which consists of arcs conjugated by straight lines, was implemented and published in an earlier work. The approximating spline in the general case is a multivalued function, whose ordinates may be limited. Another significant factor that complicates the problem is the presence of clothoids that are not expressed analytically (in a formula). The algorithm for determining the number of elements of a spline with clothoids and constructing an initial approximation was also published earlier. The present work considers the next stage of solving the spline approximation problem: optimization using a nonlinear programming spline obtained at the first stage by means of the dynamic programming method.Methods. A new mathematical model in the form of a modified Lagrange function is used together with a special nonlinear programming algorithm to optimize spline parameters. In this case, it is possible to calculate the derivatives of the objective function by the spline parameters in the absence of its analytical expression through these parameters.Results. A mathematical model and algorithm for optimization of compound spline parameters comprising arcs of circles conjugated by clothoids and lines have been developed.Conclusions. The previously proposed two-step scheme for designing paths of linear structures is also suitable for the utilization of compound splines with clothoids.

A two-step passenger flow anomaly detection scheme based on machine learning methods

Subway is an important transportation means for residents due to its large volume, punctuality and environmental friendliness. However, weather factors, sports events, concerts and some unexpected events can lead to a surge or abnormality in passenger flow, which brings enormous pressure to the management of stations and passenger flow guidance. Inspired by this, this paper formulates the abnormal passenger flows into different categories in terms of the characteristics and periodical trends, and proposes a two-step abnormal detection scheme to identify the anomalies and their type, and locate abnormal positions. First, two abnormal passenger flows recognition methods based on Jensen–Shannon divergence, dynamic time warping, and density-based spatial clustering of applications with noise are established to identify the station-level abnormal passenger flow. Then, a triple standard deviation algorithm based on sliding window is further proposed to identify the abnormal type and position. Real-world smart card data of the Beijing subway in China, and the manual mutation data of the real data are employed to evaluate effectiveness of our framework. The results show that our two-step scheme is superior to the state-of-the-art algorithms, which can detect out and locate abnormal passenger flows with various characteristics. On more mutation data, this paper discusses the performances on various anomalies of different types of stations in depth, which further indicates our framework is robust and effective in practice.

A Security Enhanced Android Unlock Scheme Based on Pinch-to-Zoom for Smart Devices

With the rapid development of information technology, mobile phones especially smartphones have become a basic and important personal device to assist and facilitate an individual’s daily life. Due to the convenience, an individual is very likely to store various personal information on smartphones, including healthcare record, ID card manifold, family photos, private video clips, etc. This may pose a big challenge on data security and privacy. To mitigate such risk, one commonly used security solution is phone unlock pattern, where Android unlock pattern should be the most widely used one on Android devices. However, Android unlock scheme is known to be not secure under various adversarial scenarios. In the literature, there is a trend of combining the unlock scheme with touch biometric. In this work, we follow this trend and develop ZoomPass, a security-enhanced Android unlock scheme by analyzing solely zoom behavior from individuals. It is a two-step scheme that requires an individual to select two dots and perform a pinch-to-zoom action for each dot. To evaluate the scheme performance, we conduct a user study with 100 participants and found that our scheme can reach good performance in both usability and security.

Two-step homogenization of spatiotemporal metasurfaces using an eigenmode-based approach

Metamaterials are a fascinating class of photonic materials since they allow us to control optical responses (largely) at will. Besides being an intellectual challenge, adding time variations into spatial metamaterials increases the degrees of freedom to tune their effective response, which motivates their exploration. However, to exploit such materials in the future design of functional devices, we may wish to treat them at the effective level to avoid considering all the mesoscopic details. To permit such effective treatment, we describe here an eigenmode-based approach to homogenize spatiotemporal metamaterials composed of a periodic arrangement of scatterers made from a time-varying material. Practically, we consider the periodic arrangement of spheres within one layer. In our two-step homogenization scheme, we first temporally homogenize that metasurface using the eigenmodes of the bulk time-varying material. Following this, we perform spatial homogenization by inverting the Fresnel coefficients of a slab made from a stationary material. These steps effectively describe the optical response of the spatiotemporal metasurface as a homogeneous slab. We validate our results by comparing the optical observables, i.e., reflectivity and transmissivity, of the metasurface with those of the homogenized slab, and we assess the limitations of the homogenization.