Backward Scheme Research Articles

Searchable Encryption for Conjunctive Queries with Extended Forward and Backward Privacy

Recent developments in the field of Dynamic Searchable Symmetric Encryption (DSSE) with forward and backward privacy have attracted much attention from both research and industrial communities. However, most DSSE schemes with forward and backward privacy schemes only support single keyword queries, which impedes its prevalence in practice. Although some forward and backward private DSSE schemes with expressive queries (e.g., conjunctive queries) have been introduced, their backward privacy either essentially corresponds to single keyword queries or forward privacy is not comprehensive. In addition, the deletion of many DSSE schemes is achieved by addition paired with a deletion mark (i.e., lazy deletion). To address these problems, we present two novel DSSE schemes with conjunctive queries (termed SDSSE-CQ and SDSSE-CQ-S), which achieve both forward and backward privacy. To analyze their security, we present two new levels of backward privacy (named Type-O and Type-O-, more and more secure), which give a more comprehensive understanding of the leakages of conjunctive queries in the OXT framework. Eventually, the security analysis and experimental evaluations show that the proposed schemes achieve better security with reasonable computation and communication increase.

Backward pumping Tm-doped fiber amplifier with >60% slope efficiency

Abstract In this paper, an efficient all fiber Tm-doped fiber amplifier which is backward-pumped with multi-mode laser diodes at 793 nm is reported. A maximum slope efficiency of 64.4%, a maximum output power of 35.5 W, a spectral signal to noise ratio of 66 dB and an ideal Gaussian beam profile are achieved. The results indicate that the implementation of a backward pumping scheme and strong injection of the seed power can enhance the slope efficiency, which is particularly crucial for high power fiber amplifiers at 2 μm.

Normal tissue complication probability modeling for late rectal bleeding after conventional or hypofractionated radiotherapy for prostate cancer

PurposeTo develop a single NTCP model for grade ≥ 2 late rectal bleeding (G2 LRB) after conventional or hypofractionated radiotherapy for prostate cancer. Methods and MaterialsThe development dataset consisted of prostate cancer patients (n = 656) previously randomized to conventional (39 x 2 Gy) or hypofractionated (19 x 3.4 Gy) external beam radiotherapy with N = 89 G2 LRB cases. Candidate predictors were obtained from literature. We fitted five separate logistic regression models to the data, each with one of the following dose parameters as candidate predictors in biological effective dose (BED), assuming α/β = 3 Gy: Equivalent uniform dose (EUD) with n = 0.1, EUD with n = 0.2, the relative volume receiving ≥ 111.9 Gy in BED (V111.9, the equivalent of physical V70 for a conventional schedule), minimum BED to the hottest 0.1 cm3 (D0.1cm3) or 2 cm3 (D2cm3). Previous abdominal surgery was included in every model and fractionation schedule was tested as predictor in each model. A sensitivity analysis was performed by varying the α/β-ratio, n and dose-volume cutoff. ResultsThe pre-selected candidate dosimetric predictor and previous abdominal surgery were significantly associated with the outcome in all five models. Fractionation schedule was eliminated by the backward scheme in only the EUD (n = 0.1), D0.1cm3 and D2cm3-based models. In internal validation these models showed AUC’s of 0.64, 0.60 & 0.62, respectively. The sensitivity analyses showed that EUD models with n ≥ 0.15 and / or α/β ≥ 4 Gy failed, and EUD models based on α/β = 2 Gy with n = 0.05–0.2 showed good fits as well. ConclusionsOur trial data set with different fractionation schedules offered the unique possibility to generate unbiased BED-based models. EUD (n = 0.1), D0.1cm3 and D2cm3 performed overall best in predicting G2 LRB; with α/β = 2 Gy equally good models were obtained. External validation is required to confirm our results.

Photo-induced loss of H2 from H2S, CH4, H2O and SiH4, when and why is it possible

We have explored the possibility of forming H⋅ and H2 from H2S, CH4, H2O and SiH4 in a series of ab initio calculations. The key finding is that H2S can give rise to direct photolytic ultrafast formation of H2 This finding is in agreement with the available experimental data and is a result of a directed pathway that leads toward H2 formation at easily accessible wavelengths. It arises at the (conical) intersection between the two lowest-lying electronic states. This intersection is a result of the valence orbital interaction of the two hydrogen atoms. This interaction is becoming more favorable as the S-H bonds simultaneously becomes longer. The H-S σ-σ∗ bonding interaction cannot compete with the bond formation that takes place between the hydrogens as two bonds stretch simultaneously. For oxygen this interaction it predominant. The reason is that sulfur has a higher principal quantum number and the interaction with the 1s of hydrogen therefore is less favorable. The excited states that are involved in the H2 formation from H2S could be populated by, for example, a two-photon 400 nm excitation. The other hydrides have a more entangled potential energy landscape close to the Franck-Condon region in the direction of the reaction coordinate that leads to H2 loss and as a result the direct loss of a hydrogen atom is favored. A two-photon excitation could be induced by femtosecond laser pulses that at the same time is proposed as a future platform for sensing the H2S molecules with the backward transient absorption scheme. The implication would be that both sensing and photoinduced H2 formation could be in place at the same time which justifies the use of expensive femtosecond light sources getting “two for the price of one”.

Kinematics of nonlinear waves over variable bathymetry. Part I: Numerical modelling, verification and validation

Fluid particle kinematics due to wave motion (i.e. orbital velocities and accelerations) at and beneath the free surface is involved in many coastal and ocean engineering applications, e.g. estimation of wave-induced forces on structures, sediment transport, etc. This work presents the formulations of these kinematics fields within a fully nonlinear potential flow (FNPF) approach. In this model, the velocity potential is approximated with a high-order polynomial expansion over the water column using an orthogonal basis of Chebyshev polynomials of the first kind. Using the same basis, original analytical expressions of the components of velocity and acceleration are derived in this work. The estimation of particle accelerations in the course of the simulation involves the time derivatives of the decomposition coefficients, which are computed with a high-order backward finite-difference scheme in time. The capability of the numerical model in computing the particle kinematics is first validated for regular nonlinear waves propagating over a flat bottom. The model is shown to be able to predict both the velocity and acceleration of highly nonlinear and nearly breaking waves with negligible error compared to the corresponding stream function wave solution. Then, for regular waves propagating over an uneven bottom (bar-type bottom profile), the simulated results are confronted with existing experimental data, and very good agreement is achieved up to the sixth-order harmonics for free surface elevation, velocity and acceleration.

SEDCPT: A secure and efficient Dynamic Searchable Encryption scheme with cluster padding assisted by TEE

Dynamic Searchable Symmetric Encryption (DSSE), which enables users to search and update encrypted data on an untrusted server without decryption, is a proven method when dealing with availability issues for outsourced data. However, the existing DSSE schemes suffer from forward and backward privacy problems. Although forward and backward privacy DSSE schemes can prevent these attacks, they still suffer from other challenges, such as count attacks, high communication overhead, and low computing efficiency. To solve the above problems simultaneously, we propose a secure and efficient dynamic searchable encryption scheme, which integrates a clustering algorithm, padding strategy, and trusted execution environments (TEE). The purpose of the scheme is to prevent count attacks while ensuring forward and backward privacy security. Our scheme also reduces the computing overhead and storage cost of the client by using TEE (e.g. Intel Software Guard Extension, Intel SGX) while maximizing the protection of client privacy. Furthermore, the scheme provides a secure hardware isolation environment for the cluster padding and search/update process to prevent malicious attacks from external software or super administrators. Finally, we provide corresponding security proofs and experimental evaluation which demonstrate both the security and efficiency of our scheme, respectively.

Developing deep learning-based strategies to predict the risk of hepatocellular carcinoma among patients with nonalcoholic fatty liver disease from electronic health records

ObjectiveThe accuracy of deep learning models for many disease prediction problems is affected by time-varying covariates, rare incidence, covariate imbalance and delayed diagnosis when using structured electronic health records data. The situation is further exasperated when predicting the risk of one disease on condition of another disease, such as the hepatocellular carcinoma risk among patients with nonalcoholic fatty liver disease due to slow, chronic progression, the scarce of data with both disease conditions and the sex bias of the diseases. The goal of this study is to investigate the extent to which the aforementioned issues influence deep learning performance, and then devised strategies to tackle these challenges. These strategies were applied to improve hepatocellular carcinoma risk prediction among patients with nonalcoholic fatty liver disease. MethodsWe evaluated two representative deep learning models in the task of predicting the occurrence of hepatocellular carcinoma in a cohort of patients with nonalcoholic fatty liver disease (n = 220,838) from a national EHR database. The disease prediction task was carefully formulated as a classification problem while taking censorship and the length of follow-up into consideration. ResultsWe developed a novel backward masking scheme to deal with the issue of delayed diagnosis which is very common in EHR data analysis and evaluate how the length of longitudinal information after the index date affects disease prediction. We observed that modeling time-varying covariates improved the performance of the algorithms and transfer learning mitigated reduced performance caused by the lack of data. In addition, covariate imbalance, such as sex bias in data impaired performance. Deep learning models trained on one sex and evaluated in the other sex showed reduced performance, indicating the importance of assessing covariate imbalance while preparing data for model training. ConclusionsThe strategies developed in this work can significantly improve the performance of hepatocellular carcinoma risk prediction among patients with nonalcoholic fatty liver disease. Furthermore, our novel strategies can be generalized to apply to other disease risk predictions using structured electronic health records, especially for disease risks on condition of another disease.

Exploiting Hidden Information Leakages in Backward Privacy for Dynamic Searchable Symmetric Encryption

Dynamic searchable symmetric encryption (DSSE) enables searches over encrypted data as well as data dynamics such as flexible data addition and deletion operations. A major security concern in DSSE is how to preserve forward and backward privacy, which are typically achieved by removing the linkability between the newly added data and previous queries, and between the deleted data and future queries, respectively. After information leakage types were formally defined for different levels of backward privacy (i.e., Type-I, II, III), many backward private DSSE schemes have been constructed under the definitions. However, we observed that the backward privacy can be violated by leveraging additional secondary leakage, which is typically leaked in specific constructions of schemes in spite of their theoretical guarantees. In this paper, in order to understand the security gap between the theoretical definitions and practical constructions, we conduct an in-depth analysis of the root cause for the secondary leakage, and demonstrate how it can be abused to violate Type-II backward privacy (e.g., the exposure of the deletion history) of DSSE constructions in practice. We then propose a novel Type-II backward private DSSE scheme based on Intel SGX, which is resilient to the secondary leakage abuse attack. According to the comparative analysis of our scheme with the state-of-the-art SGX-based DSSE schemes, Bunker-B (EuroSec’19) and SGX-SE1 (ACNS’20), our scheme shows higher efficiency in terms of the search latency with a negligible utility loss under the same security level (cf. Bunker-B) while showing similar efficiency with a higher security level (cf. SGX-SE1). Finally, we formally prove that our scheme guarantees Type-II backward privacy.

Simultaneous realization of high gain and low DMG of four-mode EDFA under bidirectional hybrid-mode pump.

We theoretically and experimentally verify that, the bidirectional hybrid-mode pumping scheme can address the optimization problem of trade-off between high gain and low differential modal gain (DMG) of four-mode erbium-doped fiber amplifier (4M-EDFA), in comparison with traditional both forward and backward hybrid-mode pumping scheme. It is noticed that, when the total pump power is fixed, the bidirectional hybrid-mode pumping scheme can not only achieve higher gain, but also suppress DMG due to different overlap integrals for the forward and backward pumping schemes. The bidirectional hybrid-mode pumped 4M-EDFA is developed with the forward pumping at LP02 mode and the backward pumping at LP21 mode, under a pump power ratio of 30%:70%. Thus, we can achieve an average gain of up to 21.16 dB and a low DMG of 0.43 dB at 1550 nm, and an average gain of up to 20.64 dB with a DMG of less than 1.6 dB over the C-band. In particular, the bidirectional hybrid-mode pumping scheme allows us to tailor the gain characteristics of the few-mode erbium-doped fiber amplifiers (FM-EDFAs), by adjusting the power ratio between forward and backward pumps.

The One Step Malliavin scheme: new discretization of BSDEs implemented with deep learning regressions

Abstract A novel discretization is presented for decoupled forward–backward stochastic differential equations (FBSDE) with differentiable coefficients, simultaneously solving the BSDE and its Malliavin sensitivity problem. The control process is estimated by the corresponding linear BSDE driving the trajectories of the Malliavin derivatives of the solution pair, which implies the need to provide accurate $\varGamma $ estimates. The approximation is based on a merged formulation given by the Feynman–Kac formulae and the Malliavin chain rule. The continuous time dynamics is discretized with a theta-scheme. In order to allow for an efficient numerical solution of the arising semidiscrete conditional expectations in possibly high dimensions, it is fundamental that the chosen approach admits to differentiable estimates. Two fully-implementable schemes are considered: the BCOS method as a reference in the one-dimensional framework and neural network Monte Carlo regressions in case of high-dimensional problems, similarly to the recently emerging class of Deep BSDE methods (Han et al. (2018 Solving high-dimensional partial differential equations using deep learning. Proc. Natl. Acad. Sci., 115, 8505–8510); Huré et al. (2020 Deep backward schemes for high-dimensional nonlinear PDEs. Math. Comp., 89, 1547–1579)). An error analysis is carried out to show $\mathbb{L}^2$ convergence of order $1/2$, under standard Lipschitz assumptions and additive noise in the forward diffusion. Numerical experiments are provided for a range of different semilinear equations up to $50$ dimensions, demonstrating that the proposed scheme yields a significant improvement in the control estimations.

Sweep interpolation: a cost-effective semi-Lagrangian scheme in the Global Environmental Multiscale model

Abstract. The interpolation process is the most computationally expensive step of the semi-Lagrangian (SL) approach for solving advection and is commonly used in numerical weather prediction (NWP) models. It has a significant impact on the accuracy of the solution and can potentially be the most expensive part of model integration. The sweep algorithm, which was first described by Mortezazadeh and Wang (2017), performs SL interpolation with the same computational cost as a third-order polynomial scheme but at the accuracy of the fourth order. This improvement is achieved by using two third-order backward and forward polynomial interpolation schemes in two consecutive time steps. In this paper, we present a new application of the sweep algorithm within the context of global forecasts produced with Environment Climate Change Canada's Global Environmental Multiscale (GEM) model. Results show that the SL scheme with sweep interpolation is computationally more efficient compared to a conventional SL scheme with fourth-order polynomial interpolation, especially when a very large number of passive tracers are advected. An additional advantage of this new approach is that its implementation in a chemical and weather forecast model requires minimum modifications of the interpolation weighting coefficients. An analysis of the computational performance for a set of theoretical benchmarks as well as a global ozone forecast experiment show that up to 15 % reduction in total wall clock time is achieved. Forecasting experiments using the global version of the GEM model and the new interpolation show that the sweep interpolation can perform very well in predicting ozone distribution, especially in the tropopause region, where transport processes play a significant role.

Analytical and numerical analyses of a viscous strain gradient problem involving type Ⅱ thermoelasticity

<abstract><p>In this paper, a thermoelastic problem involving a viscous strain gradient beam is considered from the analytical and numerical points of view. The so-called type Ⅱ thermal law is used to model the heat conduction and two possible dissipation mechanisms are introduced in the mechanical part, which is considered for the first time within strain gradient theory. An existence and uniqueness result is proved by using semigroup arguments, and the exponential energy decay is obtained. The lack of differentiability for the semigroup of contractions is also shown. Then, fully discrete approximations are introduced by using the finite element method and the backward time scheme, for which a discrete stability property and a priori error estimates are proved. The linear convergence is derived under suitable additional regularity conditions. Finally, some numerical simulations are presented to demonstrate the accuracy of the approximations and the behavior of the discrete energy decay.</p></abstract>

Discrete [formula omitted] remainder stability of first and second order schemes for a Volterra integro-differential equation

This work investigates the discrete L1 remainder stability of first and second order schemes for a Volterra integro-differential equation, where the backward Euler and backward difference formula schemes are applied in combination with first and second order convolution quadrature for approximating the integral term, respectively. By Hardy’s inequality and complex analysis techniques to accommodate the singularity of generating functions, we prove the long-time L1 remainder stability of numerical solutions of two schemes, which characterizes the long-time behavior of numerical solutions and indicates the preservation of asymptotically periodic stability of numerical schemes as continuous problems. Numerical experiments are performed to substantiate the theoretical analysis.

Spectral CT image reconstruction using a constrained optimization approach-An algorithm for AAPM 2022 spectral CT grand challenge and beyond.

CT reconstruction is of essential importance in medical imaging. In 2022, the American Association of Physicists in Medicine (AAPM) sponsored a Grand Challenge to investigate the challenging inverse problem of spectral CT reconstruction, with the aim of achieving the most accurate reconstruction results. The authors of this paper participated in the challenge and won as a runner-upteam. This paper reports details of our PROSPECT algorithm (Prior-based Restricted-variable Optimization for SPEctral CT) and follow-up studies regarding the algorithm's accuracy and enhancement of its convergencespeed. We formulated the reconstruction task as an optimization problem. PROSPECT employed a one-step backward iterative scheme to solve this optimization problem by allowing estimation of and correction for the difference between the actual polychromatic projection model and the monochromatic model used in the optimization problem. PROSPECT incorporated various forms of prior information derived by analyzing training data provided by the Grand Challenge to reduce the number of unknown variables. We investigated the impact of projection data precision on the resulting solution accuracy and improved convergence speed of the PROSPECT algorithm by incorporating a beam-hardening correction (BHC) step in the iterative process. We also studied the algorithm's performance under noisy projectiondata. Prior knowledge allowed a reduction of the number of unknown variables by . PROSPECT algorithm achieved the average root of mean square error (RMSE) of in the test data set provided by the Grand Challenge. Performing the reconstruction with the same algorithm but using double-precision projection data reduced RMSE to . Including the BHC step in the PROSPECT algorithm accelerated the iteration process with a 40% reduction in computationtime. PROSPECT algorithm achieved a high degree of accuracy and computationalefficiency.

Modeling strain-induced martensitic transformation in austenitic stainless steels subjected to cryogenic temperatures using incremental mean-field homogenization schemes

Austenitic stainless steels are commonly used as structural materials in high-field superconducting magnet systems because they retain high strength, ductility, and toughness at very low temperatures, and they are paramagnetic or antiferromagnetic under the Néel temperature in their fully austenitic state. However, they are susceptible to strain-induced martensitic transformation, especially at cryogenic temperatures, which modifies the material properties, induces volume changes and additional strain hardening, and leads to ferromagnetic behavior. Thus, accurate predictions of the structural performance of these materials at very low temperatures are of great interest for the conception and design of these cryo-magnetic systems. In this paper, we propose an adequate constitutive model for the evolving bi-phase material—austenite and martensite—based on a Hill-type incremental formulation. Two different versions of the model are proposed based on the linear mean-field homogenization scheme: Mori-Tanaka and Self-Consistent. Moreover, a rate-independent nonlinear mixed kinematic-isotropic hardening law is used for each phase, and the martensitic transformation is described by the nonlinear kinetic law proposed by Olson and Cohen (1975). The constitutive model is implemented in ABAQUS/Standard through a UMAT user subroutine, for which a return mapping algorithm based on the implicit backward Euler integration scheme is used and a closed-form expression of the consistent Jacobian tensor is provided. The Mori-Tanaka and Self-Consistent approaches are evaluated in terms of their ability to describe the mechanical behavior of the bi-phase aggregate by comparing the predictions of the homogenization schemes with unit-cell finite element calculations with an explicit description of the martensite inclusions and the austenite matrix. The comparison is carried out for different stress states with controlled triaxiality and Lode parameter under monotonic and cycling loading, paying special attention to the evolution of the mechanical fields in each phase. The unit-cell calculations are performed for both constant and evolving martensite volume fractions. In addition, numerical simulations of tensile tests on samples subjected to different initial temperatures are carried out for the transforming bi-phase material and the results are compared to experimental data for AISI 304L and AISI 316LN steels.

Vectorized Matrix Formulation for Sound Power Determination Through Inverse Problems and Regularization Techniques

Sound power estimation is a widely investigated research topic. Some of its state-of-the-art measurement solutions include taking velocity values on the source boundary, discrete pressure assessment on a virtual outer surface or evaluations with a sound intensity probe. The increased availability of microphone arrays proposes a new tool to obtain these results. The inverse boundary element method, the equivalent source method, the Helmholtz equation least-squares, and an approach based on the radiation resistance matrix provide vectorized formulations for estimating sound power. In this study, the results for different regularization techniques on the sound power deviation from a discrete line source are presented based on a backward reconstruction scheme from simulated sound pressure field points on four microphone arrays. Additionally, in this study, time improvement between single-frequency calculations and multi-frequency execution on multiple graphics processing units is presented. The outcome shows good accuracy and reduced computation time in graphics card implementations.

Decoupled second-order energy stable scheme for an electrohydrodynamic model with variable electrical conductivity

The motion of ions in the complex fluids widely appears in hydrodynamics, geodynamics and geophysics. Setting up suitable mathematical model, performing accurate and efficient numerical simulations are essential to understand the underlying physical principle in these phenomena. In this paper, we present a linear, second-order accurate in time, decoupled and unconditionally energy stable numerical scheme for solving an electrohydrodynamic power-law model with variable electrical conductivity. Based on a logarithm transformation for conductivity and the zero energy contribution property of the nonlinear coupling terms in the model, we derive an equivalent system by introducing a nonlocal auxiliary variable. The two-step backward differentiation scheme and the finite element method are used for the temporal and spatial discretizations, respectively. To decouple the system, the nonlocal splitting technique is employed to yield several linear subsystems, which can be solved very efficiently. Numerical simulations are carried out to demonstrate the second-order convergence in time and the unconditional energy stability. Moreover, the effects of Coulombic force and power-law fluid exponents are numerically investigated.

Stability and optimal control of age‐structured cell‐free and cell‐to‐cell transmission model of HIV

The human immunodeficiency virus (HIV) can spread more efficiently when infected CD4+ T cells directly interact with uninfected T cells. This interaction forms virological synapses, which lead to the cell‐to‐cell transmission of HIV. This study considers an age‐structured HIV infection model in which both cell‐free infection and cell‐to‐cell transmission occur. We also incorporate the proportion of T cells in latent or exposed class. Equilibrium solutions to our model are derived and then we perform the stability analysis. Optimal control problem for the drug therapy is also considered. Forward–backward scheme is used to solve the optimal control problem numerically. Numerical simulation added to study the effect of cell‐to‐cell infection. The outcomes of this work are new and complement the existing ones.

Forward and backward secure updatable ElGamal encryption scheme for cloud storage

Updatable encryption can support key/ciphertext update functionality, resist key compromise attacks, and be applicable to cloud storage. However, as a type of partitioning strategy, leakage sets or firewalls technique has been adopted by the existing updatable encryption schemes to build a relaxed security model, which forbids the adversary from querying the secret key at the challenge-equal epochs and hardly captures forward and backward security. In this paper, an enhanced security model can be built by considering a corruption oracle that allows any secret key query without requiring leakage sets. Then we utilize the indistinguishability obfuscation technique of the punctured program to construct an updatable ElGamal encryption scheme with no-directional key update and uni-directional ciphertext update. Furthermore, under the framework of the enhanced security model, the proposed scheme is proven to be IND-CPA. Finally, by comparison with the existing updatable encryption schemes, the proposed scheme eliminates leakage sets and firewalls, and can achieve both forward and backward security.

A multiphysical computational model of myocardial growth adopted to human pathological ventricular remodelling

We present a novel three-dimensional constitutive model that describes an electro-visco-elastic-growth response on the myocardium with a fully implicit staggered solution procedure for the strong electromechanical coupling. The novel formulations of the myocardium allows us to simulate and analyze the remodelling of actively contracting human ventricular heart models which consist of growing viscoelastic myocardium where the growth direction is determined based on its mechanical state at each time step. The total deformation gradient is multiplicatively decomposed into a mechanical-active part and a growth part, where the mechanical-active part is further split into elastic, viscous, and active components. Unconditional stability of time integration is ensured by a backward Euler integration scheme. With the developed model, the myocardium can experience stretch-driven longitudinal (fibre) growth and stress-driven transverse (cross-fibre) growth. To validate the developed approach, two simulations regarding pathological ventricular remodelling are implemented: two divergent types of remodelling of a left ventricular model driven by hemodynamic overloads and ventricular remodelling triggered by acute myocardial ischemia in a biventricular heart model.