Search

The increased availability of ultrahigh-dimensional biomarker data and the high demand of identifying biomarkers importantly related to survival outcomes made feature screening methods commonplace in the analysis of cancer genome data. When survival outcomes include endpoints of overall survival (OS) and time-to-progression (TTP), a high concordance is typically found in both endpoints in cancer studies, namely, patients' OS would most likely be extended when tumour progression is delayed. Existing screening procedures are often performed on a single survival endpoint only and may result in biased selection of features for OS in ignorance of disease progression. We propose a novel feature screening method by incorporating information of TTP into the selection of important biomarker predictors for more accurate inference of OS subsequent to disease progression. The proposal is based on the rank of correlation between individual features and the conditional distribution of OS given observations of TTP. It is advantageous for its flexible model nature, which requires no marginal model assumption for each endpoint, and its minimal computational cost for implementation. Theoretical results show its ranking consistency, sure screening and false rate control properties. Simulation results demonstrate that the proposed screener leads to more accurate feature selection than the method without considering the prior observations of disease progression. An application to breast cancer genome data illustrates its practical utility and facilitates disease classification using selected biomarker predictors. Ministry of Education (MOE) Xiang’s research was partially supported by the Singapore Ministry of Education Academic Research Fund Tier 1 Grant (RG98/20) and Tier 2 Grant (MOE-T2EP20121-0004), and Peng’s research was partially supported by the National Key R&D Program of China (Nos. 2021YFA1000100 and 2021YFA1000101) and the National Natural Science Foundation of China (NSFC grant no. 92046005).

Cryptanalysts have been looking for differential characteristics in ciphers for decades and it remains unclear how the subkey values and more generally the Markov assumption impacts exactly their probability estimation. There were theoretical efforts considering some simple linear relationships between differential characteristics and subkey values, but the community has not yet explored many possible nonlinear dependencies one can find in differential characteristics. Meanwhile, the overwhelming majority of cryptanalysis works still assume complete independence between the cipher rounds. We give here a practical framework and a corresponding tool to investigate all such linear or nonlinear effects and we show that they can have an important impact on the security analysis of many ciphers. Surprisingly, this invalidates many differential characteristics that appeared in the literature in the past years: we have checked differential characteristics from 8 articles (4 each for both SKINNY and GIFT) and most of these published paths are impossible or working only for a very small proportion of the key space. We applied our method to SKINNY and GIFT, but we expect more impossibilities for other ciphers. To showcase our advances in the dependencies analysis, in the case of SKINNY we are able to obtain a more accurate probability distribution of a differential characteristic with respect to the keys (with practical verification when it is computationally feasible). Our work indicates that newly proposed differential characteristics should now come with an analysis of how the key values and the Markov assumption might or might not affect/invalidate them. In this direction, more constructively, we include a proof of concept of how one can incorporate additional constraints into Constraint Programming so that the search for differential characteristics can avoid (to a large extent) differential characteristics that are actually impossible due to dependency issues our tool detected. Published version

Implementation-based attacks are major concerns for modern cryptography. For symmetric-key cryptography, a significant amount of exploration has taken place in this regard for primitives such as block ciphers. Concerning symmetric-key operating modes, such as Authenticated Encryption with Associated Data (AEAD), the state-of-the-art mainly addresses the passive Side-Channel Attacks (SCA) in the form of leakage resilient cryptography. So far, only a handful of work address Fault Attacks (FA) in the context of AEADs concerning the fundamental properties – integrity and confidentiality. In this paper, we address this gap by exploring mode-level issues arising due to FAs. We emphasize that FAs can be fatal even in cases where the adversary does not aim to extract the long-term secret, but rather tries to violate the basic security requirements (integrity and confidentiality). Notably, we show novel integrity attack examples on state-of-the-art AEAD constructions and even on a prior fault-resilient AEAD construction called SIV$. On the constructive side, we first present new security notions of fault-resilience, for PRF (frPRF), MAC (frMAC) and AEAD (frAE), the latter can be seen as an improved version of the notion introduced by Fischlin and Gunther at CT-RSA’20. Then, we propose new constructions to turn a frPRF into a fault-resilient MAC frMAC (hash-then-frPRF) and into a fault-resilient AEAD frAE (MAC-then-Encrypt-then-MAC or MEM). Nanyang Technological University Published version This work was supported by a joint Wallenberg AI, Autonomous Systems and SoftwareProgram-Nanyang Technological Universy (WASP-NTU) grant.

This paper establishes a general analytical framework for classical and impulse stochastic control problems in the presence of model uncertainty. We consider a set of dominated models, which are induced by the measures equivalent to that of a reference model. The state process under the reference model is a multidimensional Markov process with multidimensional Brownian motion, controlled by continuous and impulse control variates. We propose quasi-variational inequalities (QVI) associated with the value function of the control problem and prove a verification theorem for the solution to the QVI. With the relative entropy constraints and piecewise linear intervention penalty, we show that the QVI can be degenerated to the non-robust case and it can be solved via the solution to a free boundary problem. To illustrate the tractability of the proposed framework, we apply it to a linear-quadratic setting, which covers a broad class of problems including robust mean-reverting inventory controls. Ministry of Education (MOE) Chi Seng Pun gratefully acknowledges Ministry of Education (MOE), AcRF Tier 2 grant (Reference No: MOE2017-T2-1-044) for the funding of this research.

In this paper, we develop an efficient Hermite spectral-Galerkin method for nonlocal diffusion equations in unbounded domains. We show that the use of the Hermite basis can de-convolute the troublesome convolutional operations involved in the nonlocal Laplacian. As a result, the “stiffness” matrix can be fast computed and assembled via the four-point stable recursive algorithm with O(N2) arithmetic operations. Moreover, the singular factor in a typical kernel function can be fully absorbed by the basis. With the aid of Fourier analysis, we can prove the convergence of the scheme. We demonstrate that the recursive computation of the entries of the stiffness matrix can be extended to the two-dimensional nonlocal Laplacian using the isotropic Hermite functions as basis functions. We provide ample numerical results to illustrate the accuracy and efficiency of the proposed algorithms.

It is quite common that a nonlinear partial differential equation (PDE) admits multiple distinct solutions and each solution may carry a unique physical meaning. One typical approach for finding multiple solutions is to use the Newton method with different initial guesses that ideally fall into the basins of attraction confining the solutions. In this paper, we propose a fast and accurate numerical method for multiple solutions comprised of three ingredients: (i) a well-designed spectral-Galerkin discretization of the underlying PDE leading to a nonlinear algebraic system (NLAS) with multiple solutions; (ii) an effective deflation technique to eliminate a known (founded) solution from the other unknown solutions leading to deflated NLAS; and (iii) a viable nonlinear least-squares and trust-region (LSTR) method for solving the NLAS and the deflated NLAS to find the multiple solutions sequentially one by one. We demonstrate through ample examples of differential equations and comparison with relevant existing approaches that the spectral LSTR-Deflation method has the merits: (i) it is quite flexible in choosing initial values, even starting from the same initial guess for finding all multiple solutions; (ii) it guarantees high-order accuracy; and (iii) it is quite fast to locate multiple distinct solutions and explore new solutions which are not reported in literature. Ministry of Education (MOE) L. Li: This work of this author is partially supported by the Science Foundations of Hunan Province (Nos: 2020JJ5464, 20C1595). L-L. Wang: The research of this author is partially supported by Singapore MOE AcRF Tier 1 Grant: RG15/21.

Linear codes have widespread applications in data storage systems. There are two major contributions in this paper. We first propose infinite families of optimal or distance-optimal linear codes over Fp constructed from projective spaces.Moreover, a necessary and sufficient condition for such linear codes to be Griesmer codes is presented. Secondly, as an application in data storage systems, we investigate the locality of the linear codes constructed. Furthermore, we show that these linear codes are alphabet-optimal locally repairable codes with locality 2. Nanyang Technological University Submitted/Accepted version This work was supported by NTU Research Grant 04INS000047C230GRT01.

Let A,B be subsets of a finite abelian group G. Suppose that A+B does not contain a unique sum, i.e., there is no g∈G with a unique representation g=a+b, a∈A, b∈B. From such sets A,B, sparse linear systems over the rational numbers arise. We obtain a new determinant bound on invertible submatrices of the coefficient matrices of these linear systems. Under the condition that |A|+|B| is small compared to the order of G, these bounds provide essential information on the Smith Normal Form of these coefficient matrices. We use this information to prove that A and B admit coset partitions whose parts have properties resembling those of A and B. As a consequence, we improve previously known sufficient conditions for the existence of unique sums in A+B and show how our structural results can be used to classify sets A and B for which A+B does not contain a unique sum when |A|+|B| is relatively small. Our method also can be applied to subsets of abelian groups which have no unique differences. Ministry of Education (MOE) This research is supported by the Ministry of Education, Singapore, under its Academic Research Fund Tier 1 (RG27/18).

We consider oblivious transfer protocols performed over binary symmetric channels in a malicious setting where parties will actively cheat if they can. We provide constructions purely based on coding theory that achieve an explicit positive rate, the essential ingredient being the existence of linear codes whose Schur products are asymptotically good. National Research Foundation (NRF) The work of Frédérique Oggier was supported by the Singapore National Research Foundation under Research Grant NRF-RF2009-07.

A Π 1 0 \Pi ^{0}_{1} class P P is thin if every Π 1 0 \Pi ^{0}_{1} subclass Q Q of P P is the intersection of P P with some clopen set. In 1993, Cenzer, Downey, Jockusch and Shore initiated the study of Turing degrees of members of thin Π 1 0 \Pi ^{0}_{1} classes, and proved that degrees containing no members of thin Π 1 0 \Pi ^{0}_{1} classes can be recursively enumerable, and can be minimal degree below 0 ′ \mathbf {0}’ . In this paper, we work on this topic in terms of genericity, and prove that all 2-generic degrees contain no members of thin Π 1 0 \Pi ^{0}_{1} classes. In contrast to this, we show that all 1-generic degrees below 0 ′ \mathbf {0}’ contain members of thin Π 1 0 \Pi ^{0}_{1} classes.

An edge labeling of a connected graph $G = (V,E)$ is said to be local antimagic if it is a bijection $f : E \to \{1, . . . , |E|\}$ such that for any pair of adjacent vertices $x$ and $y$, $f^+(x) \ne f^+(y)$, where the induced vertex label $f^+(x) = \sum f(e)$, with $e$ ranging over all the edges incident to $x$. The local antimagic chromatic number of $G$, denoted by $\chi_{la}(G)$, is the minimum number of distinct induced vertex labels over all local antimagic labelings of $G$. In this paper, we first show that a $d$-leg spider graph has $d+1\le \chi_{la}\le d+2$. We then obtain many sufficient conditions such that both the values are attainable. Finally, we show that each 3-leg spider has $\chi_{la} = 4$ if not all legs are of odd length. We conjecture that almost all $d$-leg spiders of size $q$ that satisfies $d(d+1) \le 2(2q-1)$ with each leg length at least 2 has $\chi_{la} = d+1$., Comment: 25 pages

We present an algorithm for the numerical solution of nonlinear parabolic partial differential equations. This algorithm extends the classical Feynman–Kac formula to fully nonlinear partial differential equations, by using random trees that carry information on nonlinearities on their branches. It applies to functional, non-polynomial nonlinearities that are not treated by standard branching arguments, and deals with derivative terms of arbitrary orders. A Monte Carlo numerical implementation is provided. Ministry of Education (MOE) This research is supported by the Ministry of Education, Singapore, under its Tier 2 Grant MOE-T2EP20120-0005.

We show that the maximum cardinality of an equiangular line system in 17 dimensions is 48, thereby solving a longstanding open problem. Furthermore, by giving an explicit construction, we improve the lower bound on the maximum cardinality of an equiangular line system in 18 dimensions to 57., 39 pages. Contains tables referenced in the journal version. arXiv admin note: text overlap with arXiv:2002.08085

The latent monkeypox outbreak has become the most emergent public health challenge globally. This study was conducted to assess the acceptability, and willingness to take and pay for a hypothetical Monkeypox vaccine among the Vietnamese general public as well as investigate preference for individual vaccine attributes. Published version This work was funded by Vingroup Joint Stock Company (Vingroup JSC), Vingroup and supported by Vingroup Innovation Foundation (VINIF) under project code VINIF.2020.COVID-19.DA03, and ActionAid Vietnam.

This paper incorporates Bayesian estimation and optimization into a portfolio selection framework, particularly for high-dimensional portfolios in which the number of assets is larger than the number of observations. We leverage a constrained \ell 1 minimization approach, called the linear programming optimal (LPO) portfolio, to directly estimate effective parameters appearing in the optimal portfolio. We propose two refinements for the LPO strategy. First, we explore improved Bayesian estimates, instead of sample estimates, of the covariance matrix of asset returns. Second, we introduce Bayesian optimization (BO) to replace traditional grid-search cross-validation (CV) in tuning hyperparameters of the LPO strategy. We further propose modifications in the BO algorithm by (1) taking into account the time-dependent nature of financial problems and (2) extending the commonly used expected improvement acquisition function to include a tunable trade-off with the improvement's variance. Allowing a general case of noisy observations, we theoretically derive the sublinear convergence rate of BO under the newly proposed EIVar and thus our algorithm has no regret. Our empirical studies confirm that the adjusted BO results in portfolios with higher out-of-sample Sharpe ratio, certainty equivalent, and lower turnover compared to those tuned with CV. This superior performance is achieved with a significant reduction in time elapsed, thus also addressing time-consuming issues of CV. Furthermore, LPO with Bayesian estimates outperforms the original proposal of LPO, as well as the benchmark equally weighted and plugin strategies. Ministry of Education (MOE) This work was funded by the Ministry of Education, Singapore (MOE2017-T2-1-044).

Bayesian inverse problems for inferring the unknown forcing and initial condition of Navier-Stokes equation play important roles in many practi-cal areas. The computation cost of sampling the posterior probability measure can be exceedingly high. We develop the Finite Element Multilevel Markov Chain Monte Carlo (FE-MLMCMC) sampling method for approximating ex-pectation with respect to the posterior probability measure of quantities of interest for a model problem of Navier-Stokes equation in the two dimensional periodic torus. We first consider the case where the forcing and the initial condition are bounded for all the realizations and depend linearly on a countable set of random variables which are uniformly distributed in a compact interval. We establish the essentially optimal convergence rate of the method and verify it numerically. The method follows from that developed in V. H. Hoang, Ch. Schwab and A. M. Stuart, Inverse problems, vol. 29, 2013 for inferring the coefficients of linear elliptic forward equations under the uniform prior probability measure. In the case of the Gaussian prior probability measure, numerical re-sults, using the MLMCMC method developed for the Gaussian prior in V. H. Hoang, J. H. Quek and Ch. Schwab, Inverse problems, vol. 36, 2020, indicate the essentially optimal convergence rates. However, a rigorous theory for the MLMCMC sampling procedure is not available, due to the non-integrability with respect to the Gaussian prior of the theoretical finite element errors of the forward solvers that are available in the literature.

Automated methods have become crucial components when searching for distinguishers against symmetric-key cryptographic primitives. While MILP and SAT solvers are among the most popular tools to model ciphers and perform cryptanalysis, other methods with different performance profiles are appearing. In this article, we explore the use of Constraint Programming (CP) for differential cryptanalysis on the Ascon authenticated encryption family (first choice of the CAESAR lightweight applications portfolio and current finalist of the NIST LWC competition) and its internal permutation. We first present a search methodology for finding differential characteristics for Ascon with CP, which can easily find the best differential characteristics already reported by the Ascon designers. This shows the capability of CP in generating easily good differential results compared to dedicated search heuristics. Based on our tool, we also parametrize the search strategies in CP to generate other differential characteristics with the goal of forming limited-birthday distinguishers for 4, 5, 6 and 7 rounds and rectangle attacks for 4 and 5 rounds of the Ascon internal permutation. We propose a categorization of the distinguishers into black-box and non-black-box to better differentiate them as they are often useful in different contexts. We also obtained limited-birthday distinguishers which represent currently the best known distinguishers for 4, 5 and 6 rounds under the category of non-black-box distinguishers. Leveraging again our tool, we have generated forgery attacks against both reduced-rounds Ascon-128 and Ascon-128A, improving over the best reported results at the time of writing. Finally, using the best differential characteristic we have found for 2 rounds, we could also improve a recent attack on round-reduced Ascon-HAsh. Agency for Science, Technology and Research (A*STAR) Published version The authors are supported by the Temasek Laboratories.

Ultrahigh-dimensional gene features are often collected in modern cancer studies in which the number of gene features p is extremely larger than sample size n. While gene expression patterns have been shown to be related to patients' survival in microarray-based gene expression studies, one has to deal with the challenges of ultrahigh-dimensional genetic predictors for survival predicting and genetic understanding of the disease in precision medicine. The problem becomes more complicated when two types of survival endpoints, distant metastasis-free survival and overall survival, are of interest in the study and outcome data can be subject to semi-competing risks due to the fact that distant metastasis-free survival is possibly censored by overall survival but not vice versa. Our focus in this paper is to extract important features, which have great impacts on both distant metastasis-free survival and overall survival jointly, from massive gene expression data in the semi-competing risks setting. We propose a model-free screening method based on the ranking of the correlation between gene features and the joint survival function of two endpoints. The method accounts for the relationship between two endpoints in a simply defined utility measure that is easy to understand and calculate. We show its favorable theoretical properties such as the sure screening and ranking consistency, and evaluate its finite sample performance through extensive simulation studies. Finally, an application to classifying breast cancer data clearly demonstrates the utility of the proposed method in practice. Ministry of Education (MOE) Submitted/Accepted version Xiang’s research was supported by the Singapore Ministry of Education Academic Research Fund Tier 1 grant RG98/20 and Peng’s research was supported by National Natural Science Foundation of China (NSFC Grant No. 92046005).

Although social distancing can effectively contain the spread of infectious diseases by reducing social interactions, it may have economic effects. Crises such as the COVID-19 pandemic create dilemmas for policymakers because the long-term implementation of restrictive social distancing policies may cause massive economic damage and ultimately harm healthcare systems. This paper proposes an epidemic control framework that policymakers can use as a data-driven decision support tool for setting efficient social distancing targets. The framework addresses three aspects of the COVID-19 pandemic that are related to social distancing or community mobility data: modeling, financial implications, and policy-making. Thus, we explore the COVID-19 pandemic and concurrent economic situation as functions of historical pandemic data and mobility control. This approach allows us to formulate an efficient social distancing policy as a stochastic feedback control problem that minimizes the aggregated risks of disease transmission and economic volatility. We further demonstrate the use of a deep learning algorithm to solve this control problem. Finally, by applying our framework to U.S. data, we empirically examine the efficiency of the U.S. social distancing policy. H.Y. Wong acknowledges the Research Matching Grant (RMG project code: 8601495) received from the Research Grants Council of Hong Kong.

Reservoir computing systems are constructed using a driven dynamical system in which external inputs can alter the evolving states of a system. These paradigms are used in information processing, machine learning, and computation. A fundamental question that needs to be addressed in this framework is the statistical relationship between the input and the system states. This paper provides conditions that guarantee the existence and uniqueness of asymptotically invariant measures for driven systems and shows that their dependence on the input process is continuous when the set of input and output processes are endowed with the Wasserstein distance. The main tool in these developments is the characterization of those invariant measures as fixed points of naturally defined Foias operators that appear in this context and which have been profusely studied in the paper. Those fixed points are obtained by imposing a newly introduced stochastic state contractivity on the driven system that is readily verifiable in examples. Stochastic state contractivity can be satisfied by systems that are not state-contractive, which is a need typically evoked to guarantee the echo state property in reservoir computing. As a result, it may actually be satisfied even if the echo state property is not present., 33 pages, 5 figures

Topological data analysis has recently found applications in various areas of science, such as computer vision and understanding of protein folding. However, applications of topological data analysis to natural language processing remain under-researched. This study applies topological data analysis to a particular natural language processing task: fake news detection. We have found that deep learning models are more accurate in this task than topological data analysis. However, assembling a deep learning model with topological data analysis significantly improves the model’s accuracy if the available training set is very small. Published version

A scatterplot is often the graph of choice for displaying the relationship between two variables. Scatterplots are useful for exploratory analysis, but can do much more than just identifying correlations. As data sets get larger and more complex, relying solely on “eye power” alone may cause us to miss interesting associations, or worse, make wrong interpretations. We show that by combining scatterplots with statistical and logical reasoning (the sliding window and two-axis median bisection), we may identify interesting associations in a case study of Graduate Record Examination admission versus graduation outcomes, and whether low detectability of proteins in a biological sample are truly associated with low abundance. Due to subjective visual interpretability, we recommend graphing the data using a multitude of visual variables and graph types before concluding the absence of an association. Finally, even if associations are demonstrable, developing causal models that could explain the observed fuzziness and lack of apparent correlations in the scatterplot are helpful for better decision-making and interpretation. Ministry of Education (MOE) This work is supported by the Ministry of Education, Singapore, under its Academic Research Fund Tier-1 (RG35/20) to WWBG. This work is also supported in part by a Singapore Ministry of Education Tier-2 Grant (MOE2019-T21-042) to LW and WWBG.

This paper studies stochastic linear-quadratic control with a time-inconsistent objective and worst-case drift disturbance. We allow the agent to introduce disturbances to reflect her uncertainty about the drift coefficient of the controlled state process. We adopt a two-step equilibrium control approach to characterize the robust time-consistent controls, which can preserve the order of preference. Under a general framework allowing random parameters, we derive a sufficient condition for equilibrium controls using the forward-backward stochastic differential equation approach. We also provide analytical solutions to mean-variance portfolio problems for various settings. Our empirical studies confirm the improvement in portfolio’s performance in terms of out-of-sample Sharpe ratio by incorporating with robustness. Ministry of Education (MOE) Bingyan Han is supported by UIC Start-up Research Fund (Reference No: R72021109). Chi Seng Pun gratefully acknowledges the Ministry of Education (MOE), AcRF Tier 2 Grant (Reference No: MOE2017-T2-1-044) for the funding of this research. Hoi Ying Wong acknowledges the support from the Research Grants Council of Hong Kong via GRF 14303915.

In this paper, we design a truly exact perfect absorbing layer (PAL) for domain truncation of the two-dimensional Helmholtz equation in an unbounded domain with bounded scatterers. This technique is based on a complex compression coordinate transformation in polar coordinates and a judicious substitution of the unknown field in the artificial layer. Compared with the widely used perfectly matched layer (PML) methods, the distinctive features of PAL lie in that (i) it is truly exact in the sense that the PAL-solution is identical to the original solution in the bounded domain reduced by the truncation layer; (ii) with the substitution, the PAL-equation is free of singular coefficients and the substituted unknown field is essentially nonoscillatory in the layer; and (iii) the construction is valid for general star-shaped domain truncation. By formulating the variational formulation in Cartesian coordinates, the implementation of this technique using standard spectral-element or finite-element methods can be made easy as a usual coding practice. We provide ample numerical examples to demonstrate that this method is highly accurate and robust for very high wavenumbers and thin layers. It outperforms the classical PML and the recently advocated PML using unbounded absorbing functions. Moreover, it can fix some flaws of the PML approach. Ministry of Education (MOE) Published version The work of the first author was partially supported by the Strategic Priority Research Program of Chinese Academy of Sciences grant XDA25010402. The work of the second author was partially supported by Singapore MOE AcRF Tier 2 Grants MOE2018-T2-1-059 and MOE2017-T2- 2-144.

Thermodynamic resources, beyond their well-known usefulness in work extraction and other thermodynamic tasks, are often important also in tasks that are not evidently thermodynamic. Here we develop a framework for identifying such resources in diverse applications of bosonic continuous-variable systems. Introducing the class of bosonic linear thermal operations to model operationally-feasible processes, we apply this model to identify uniquely quantum properties of bosonic states that refine classical notions of thermodynamic resourcefulness. Among these are (1) a suite of temperature-like quantities generalizing the equilibrium temperature to quantum, non-equilibrium scenarios; (2) signal-to-noise ratios quantifying a system's capacity to carry information in phase-space displacement; and (3) well-established non-classicality measures quantifying the resolution in sensing and parameter estimation tasks., 9 pages (6 figures), 4-page supplemental material

COFB is a lightweight Authenticated Encryption with Associated Data (AEAD) mode based on block ciphers. It was proposed in CHES 2017 and is the basis for GIFT-COFB, a finalist in the NIST lightweight standardization project. It comes with provable security results that guarantee its security up to the birthday bound in the nonce-respecting model. However, the designers offer multiple versions of the analysis with different details and the implications of attacks against the scheme are not discussed deeply. In this article, we look at a group of possible forgery and privacy attacks against COFB. We show that the security for both forgery and privacy is bounded by the number of forgery attempts. We show the existence of forgery and privacy attacks with success probability qd/2n/2, given qd forgery attempts. In particular, we show an attack with 2n/2 attempts using only a single known-plaintext encryption query against COFB. While these attacks do not contradict the claims made by the designers of GIFT-COFB, they show its limitations in terms of the number of forgery attempts. They also show that, while COFB generates a 128-bit tag, it behaves in a very similar manner to an AEAD scheme with 64-bit tag. As a result of independent interest, our analysis provides a contradiction to the main theorem of Journal of Cryptology volume 33, pages 703–741 (2020), which includes an improved security proof of COFB compared to the CHES 2017 version. Finally, we discuss the term nqd/2n/2 that appears in the security proof of GIFT-COFB and CHES 2017, showing why there is a security gap between the provable results and the attacks. We emphasize that the results in this article do not threaten the security of GIFT-COFB in the scope of the NIST lightweight cryptography requirements or the claims made by the designers in the specification document of the design. Nanyang Technological University Published version This work was funded under the MALEC project, Temasek Laboratories NTU grant DSOCL17101.

We show that there is a cuppable c.e. degree, all of whose cupping partners are high. In particular, not all cuppable degrees are ${\operatorname {\mathrm {low}}}_3$-cuppable, or indeed ${\operatorname {\mathrm {low}}}_n$ cuppable for any n, refuting a conjecture by Li. On the other hand, we show that one cannot improve highness to superhighness. We also show that the ${\operatorname {\mathrm {low}}}_2$-cuppable degrees coincide with the array computable-cuppable degrees, giving a full understanding of the latter class.

We study computable Polish spaces and Polish groups up to homeomorphism. We prove a natural effective analogy of Stone duality, and we also develop an effective definability technique which works up to homeomorphism. As an application, we show that there is a $\Delta ^0_2$ Polish space not homeomorphic to a computable one. We apply our techniques to build, for any computable ordinal $\alpha $, an effectively closed set not homeomorphic to any $0^{(\alpha )}$-computable Polish space; this answers a question of Nies. We also prove analogous results for compact Polish groups and locally path-connected spaces.

We propose a general greedy algorithm for binary de Bruijn sequences, called Generalized Prefer-Opposite Algorithm, and its modifications. By identifying specific feedback functions and initial states, we demonstrate that most previously-known greedy algorithms that generate binary de Bruijn sequences are particular cases of our algorithm. Nanyang Technological University Accepted version Nanyang Technological University Grant M4080456 supports the research carried out by M. F. Ezerman and A. A. Fahreza.

We study a family of optimal control problems under a set of controlled-loss constraints holding at different deterministic dates. The characterization of the associated value function by a Hamilton-Jacobi-Bellman equation usually calls for additional strong assumptions on the dynamics of the processes involved and the set of constraints. To treat this problem in absence of those assumptions, we first convert it into a state-constrained stochastic target problem and then apply a level-set approach. With this approach, the state constraints can be managed through an exact penalization technique. Accepted version Authors are grateful to the Young Investigator Training Program and Association of Bank Foundations. This is a post-peer-review, pre-copyedit version of an article published in Journal of Optimization Theory and Applications. The final authenticated version is available online at: http://dx.doi.org/10.1007/s10957-020-01724-8

In this paper, we present a compact design for the code based signature called LEDAsig with side channel resistance. Existing implementations concentrate on the high-speed feature while few of them have considerations on area or power efficiency which are particularly decisive for low-cost or power constrained IoT applications. We propose an area-efficient FPGA architecture for systematically rotating the QC-LDGM codes amongst the block RAMs with read-first mode. Additionally, the side channel vulnerability of LEDAsig is carefully examined, and protective masking schemes are introduced accordingly to safeguard our design from power analysis attacks. Effectiveness of these schemes is verified on SAKURA-G FPGA board. Up till now, the design presented in this work is the most compact one and also the first side-channel secure one addressing first-order and (univariate) second-order differential power analysis for the code based signature schemes in the open literature. We show for instance that our first-order (second-order) protected implementation can sign a signature in 117 (203) ms on a Xilinx Spartan-6 FPGA, occupying only 622 (1142) slices, and therefore is a prospective candidate for post-quantum signature schemes in low-resource settings. Agency for Science, Technology and Research (A*STAR) Ministry of Education (MOE) This work was supported in part by the CityU Internal under Grant 9678187, in part by the Singapore Ministry of Education under Grant MOE2016-T2-2-014(S) and in part by A*Star, Singapore, under Grant SERC A19E3b0099.

Holographic representations of data encode information in packets of equal importance that enable progressive recovery. The quality of recovered data improves as more and more packets become available. This progressive recovery of the information is independent of the order in which packets become available. Such representations are ideally suited for distributed storage and for the transmission of data packets over networks with unpredictable delays and or erasures. Several methods for holographic representations of signals and images have been proposed over the years and multiple description information theory also deals with such representations. Surprisingly, however, these methods had not been considered in the classical framework of optimal least-squares estimation theory, until very recently. We develop a least-squares approach to the design of holographic representation for stochastic data vectors, relying on the framework widely used in modeling signals and images., Comment: 22 pages with 6 figures

This paper contributes to the general program which aims to eliminate an unbounded search from proofs and procedures in computable structure theory. A countable structure in a finite language is punctual if its domain is ω \omega and its operations and relations are primitive recursive. A function f f is punctual if both f f and f − 1 f^{-1} are primitive recursive. We prove that there exists a countable rigid algebraic structure which has exactly two punctual presentations, up to punctual isomorphism.

In this paper, we present a lightweight hardware design for a recently proposed quantum-safe key encapsulation mechanism based on QC-LDPC codes called LEDAkem, which has been admitted as a round-2 candidate to the NIST post-quantum standardization project. Existing implementations focus on high speed while few of them take into account area or power efficiency, which are particularly decisive for low-cost or power constrained IoT applications. The solution we propose aims at maximizing the metric of area efficiency by rotating the QC-LDPC code representations amongst the block RAMs in digit level. Moreover, optimized parallelized computing techniques, lazy accumulation and block partition are exploited to improve key decapsulation in terms of area and timing efficiency. We show for instance that our area-optimized implementation for 128-bit security requires 6.82× 1056.82×105 cycles and 2.26× 1062.26×106 cycles to encapsulate and decapsulate a shared secret, respectively. The area-optimized design uses only 39 slices (3 percent of the available logic) and 809 slices (39 percent of the available logic) for key encapsulation and key decapsulation respectively, on a small-size low-end Xilinx Spartan-6 FPGA. Ministry of Education (MOE) National Research Foundation (NRF) This work was partially supported by Singapore Ministry of Education under Research Grant MOE2016-T2-2-014(S) and the National Research Foundation, Prime Ministers Office, Singapore under its Strategic Capability Research Centres Funding Initiative.

In recent years, blockchain has received increasing attention and numerous applications have emerged from this technology. A renowned Blockchain application is the cryptocurrency Bitcoin, that has not only been effectively solving the double-spending problem but also it can confirm the legitimacy of transactional records without relying on a centralized system to do so. Therefore, any application using Blockchain technology as the base architecture ensures that the contents of its data are tamper-proof. This paper uses the decentralized Blockchain technology approach to ensure that consumers do not fully rely on the merchants to determine if products are genuine. We describe a decentralized Blockchain system with products anti-counterfeiting, in that way manufacturers can use this system to provide genuine products without having to manage direct-operated stores, which can significantly reduce the cost of product quality assurance. Ministry of Education (MOE) National Research Foundation (NRF) Published version The work of Jinhua Ma and Xin Chen was supported by the National Natural Science Foundation of China under Grant 61872089,Grant 61902070, and Grant 61972094. The work of Shih-Ya Lin and Hung-Min Sun was supported by the Ministry of Science and Technology of the Republic of China under Grant MOST 106-2221-E-007-026-MY3, Grant MOST 107-2221-E-007-015-MY3, and Grant MOST 108-2218E001-001. The work of Huaxiong Wang was supported by the National Research Foundation, Prime Minister’sOffice, Singapore under its Strategic Capability Research Centres Funding Initiative and Singapore Ministry of Education under Research Grant MOE2016-T2-2-014(S).

A robust positioning pattern is a large array that allows a mobile device to locate its position by reading a possibly corrupted small window around it. In this paper, we provide constructions of binary positioning patterns, equipped with efficient locating algorithms, that are robust to a constant number of errors and have redundancy within a constant factor of optimality. Furthermore, we modify our constructions to correct rank errors and obtain binary positioning patterns robust to any errors of rank less than a constant number. Additionally, we construct $q$-ary robust positioning sequences robust to a large number of errors, some of which have length attaining the upper bound. Our construction of binary positioning sequences that are robust to a constant number of errors has the least known redundancy amongst those explicit constructions with efficient locating algorithms. On the other hand, for binary robust positioning arrays, our construction is the first explicit construction whose redundancy is within a constant factor of optimality. The locating algorithms accompanying both constructions run in time cubic in sequence length or array dimension., Comment: Extended Version of SODA 2019 Paper

The Moho discontinuity plays an important role in crustal growth and evolution. In this study, we delineate the Moho geometry in southern California by jointly using local Moho-reflected waves PmP and teleseismic Moho-converted waves Ps. To well constrain the Moho geometry, we have developed a two-stage process to pick PmP waves and have created a reliable PmP travel time data set with a total of 10,192 picks. We have also extracted 38,648 high-quality P-wave receiver functions (RFs). The Moho depth is initially estimated via the common conversion point (CCP) stacking of RFs and then refined by inverting the PmP travel time data in a community velocity model (CVM-H, version 15.1.1). The newly built Moho geometry is generally consistent with the California Moho Model version 1.0 (CMM-1.0), that is, a shallow Moho beneath the Salton Trough (23 km), a uniformly shallow Moho beneath the Mojave Desert and the Basin and Range (34 km). However, our Moho model reveals some new features different from the CMM–1.0, such as a deep Moho (∼34 km) beneath the northern end of the central and western Transverse Ranges, consistent with the observation of deep seismicities due to a thick brittle crust there. We also find a gradual transition from the lower crust to the uppermost mantle beneath the western Peninsular Ranges, leading to the rareness of pickable PmP waves as well as weak Moho-converted signals there. Ministry of Education (MOE) National Research Foundation (NRF) Published version This research is partly funded by the National Research Foundation Singapore and the Singapore Ministry of Education under the Research Centers of Excellence Initiative (Project Code Number: 04MNS001953A620). T. Li and P. Tong are also partly supported by Singapore MOE AcRF Tier-2 Grant (04MNP002073C230).

We present an algorithm for the numerical solution of ordinary differential equations by random enumeration of the Butcher trees used in the implementation of the Runge–Kutta method. Our Monte Carlo scheme allows for the direct numerical evaluation of an ODE solution at any given time within a certain interval, without iteration through multiple time steps. In particular, this approach does not involve a discretization step size, and it does not require the truncation of Taylor series. Ministry of Education (MOE) This research is supported by the Ministry of Education, Singapore, under its Tier 2 Grant MOE-T2EP20120-0005.

This paper studies mean–variance portfolio selection problem subject to proportional transaction costs and no-shorting constraint. We do not impose any distributional assumptions on the asset returns. By adopting dynamic programming, duality theory, and a comparison approach, we manage to derive a semi-closed form solution of the optimal dynamic investment policy with the boundaries of buying, no-transaction, selling, and liquidation regions. Numerically, we illustrate the properties of the optimal policy by depicting the corresponding efficient frontiers under different rates of transaction costs and initial wealth allocations. We find that the efficient frontier is distorted due to the transaction cost incurred. We also examine how the width of the no-transaction region varies with different transaction cost rates. Empirically, we show that our transaction-cost-aware policy outperforms the transaction-cost-unaware policy in a realistic trading environment that incurs transaction costs. Ministry of Education (MOE) Chi Seng Pun gratefully acknowledges Ministry of Education (MOE), AcRF Tier 2 grant (Reference No: MOE2017-T2-1-044) for the funding of this research.

Let Q⊆Rm, K⊆Rn be open sets, p,q∈N, 1≤r

The need for clean water is expected to substantially increase while further reductions of water availability in sufficient quantity and quality are projected owing to climate change and anthropogenic activities. Accordingly, the debate on water security has recently intensi fied and reached the intergovernmental arena. Industry is, in particular, one of the largest (non-consumptive) water users, accountable for massive toxic wastewater discharges and facing stringent and costly environmental oversight. However, the management of reservoirs is intricate and operational research must be further expanded to design tools that enhance water security while improving operators' profi tability. We therefore consider a game-theoretic framework to study the strategies adopted by a large group of similar producers sharing a water reservoir for their manufacturing activities. Each operator faces random demand for its outputs and chooses the optimal time to invest in a technology that ends its reliance on the reservoir. This technology introduces cost saving opportunities for the operator and benefi ts for the environment. Each producer therefore solves a so-called optimal stopping problem, and all problems are coupled through the reservoir level. We formulate the problem of finding a Nash equilibrium as a mean-fi eld game (MFG) of optimal stopping. We then apply the model to the paper milling industry, an extensive water user facing a tightening of environmental regulations. This paper provides fresh insights into how to rethink the problem of technological change and water management, by offering an innovative application of operational research that builds on recent mathematical developments made in MFG theory. Published version

Efficient thermal transportation in compact heat density gadgets is a prevailing issue to be addressed. The flow of a mono nanofluid (SiO2/Kerosene oil) and hybrid nanofluid (TiO2 + SiO2/Kerosene oil) is studied in context of Riga wedge. The basic purpose of this work pertains to improve thermal conductivity of base liquid with inclusions of nano-entities. The hybrid nanofluid flow over Riga wedge is new aspect of this work. The concentration of new species is assumed to constitute the base liquid to be non-Newtonian. The fundamental formulation of the concentration laws of mass, momentum and energy involve partial derivatives. The associated boundary conditions are taken in to account. Similarity variables are utilized to transform the leading set of equations into ordinary differential form. Shooting procedure combined with Runge-Kutta method is harnessed to attain numerical outcomes. The computational process is run in matlab script. It is seen that the velocity component f′(η) goes upward with exceeding inputs of modified Hartmann number Mh and it slows down when non-dimensional material parameter αh takes large values. Also, Nusselt number - θ′(0) is enhanced with developing values of Eckert number Ec and Biot number Bi. Published version This Research was supported by Taif University Researchers Supporting Project Number (TURSP-2020/217), Taif University, Taif, Saudi Arabia.

We study the rank weight hierarchy, thus in particular the minimum rank distance, of polynomial codes over the finite field $\FF_{q^m}$, $q$ a prime power, $m \geq 2$. We assume that polynomials involved are squarefree. We establish the rank weight hierarchy of $[n,n-1]$ constacyclic codes. We characterize polynomial codes of $r$th rank weight $r$, and in particular of irst rank or minimum rank distance 1. Finally, we provide a refinement of the Singleton bound, from which we show that cyclic codes cannot be MRD (maximum rank distance) codes, but constacyclic codes can be. National Research Foundation (NRF) Submitted/Accepted version The early stage of this research by J. Ducoat and F. Oggier was supported by the Singapore National Research Foundation under Research Grant NRF-RF2009-07.

We investigate equiangular lines in finite orthogonal geometries, focusing specifically on equiangular tight frames (ETFs). In parallel with the known correspondence between real ETFs and strongly regular graphs (SRGs) that satisfy certain parameter constraints, we prove that ETFs in finite orthogonal geometries are closely aligned with a modular generalization of SRGs. The constraints in our finite field setting are weaker, and all but 18 known SRG parameters on v≤1300 vertices satisfy at least one of them. Applying our results to triangular graphs, we deduce that Gerzon's bound is attained in finite orthogonal geometries of infinitely many dimensions. We also demonstrate connections with real ETFs, and derive necessary conditions for ETFs in finite orthogonal geometries. As an application, we show that Gerzon's bound cannot be attained in a finite orthogonal geometry of dimension 5. Ministry of Education (MOE) GRWG was partially supported by the Singapore Ministry of Education Academic Research Fund (Tier 1); grant numbers: RG29/18 and RG21/20. JJ was supported by NSF DMS 1830066. DGM was partially supported by AFOSR FA9550-18-1-0107 and NSF DMS 1829955.

We present the wave equation-based adjoint tomography of northeastern Japan using common-source double-difference travel-time data. More than 30,000 high-quality first P-wave arrivals from 117 local earthquakes recorded by 713 seismic stations are included in the inversion, generating more than 350,000 double-difference travel times of first P-wave arrivals. In comparison with commonly used travel-time data, the common-source double-difference travel times are insensitive to source parameters and source-side structures but place enhanced constraints on receiver-side structures. As a result, these robust double-difference travel times generate a reliable VP model down to a depth of 120 km. Our inversion results clearly show crustal low-velocity anomalies beneath the volcanic arc. The subducting Pacific slab is illuminated as a landward-dipping high-velocity anomaly, and the arc magmatism in the mantle wedge is shown as low-velocity anomalies. Thanks to the newly operated Seafloor Observation Network (S-net), prominent high-velocity bodies are detected in the fore-arc mantle wedge at depths of 30-60 km. These abnormal high-VP bodies indicate a low degree of serpentinization in the fore-arc mantle wedge at low temperatures, correlating well with the previous finding that the uppermost mantle in the Kuril and Tohoku fore-arc is cold and dry.Our inversion results reveal reliable tectonic features in the subduction zone beneath northeastern Japan, suggesting thatwave equation-based common-source double- difference travel-time adjoint tomography is an effective and robust method to illuminate detailed structures of the crust and uppermost mantle. Ministry of Education (MOE) This work is supported by the Minister of Education, Singapore, under its MOE AcRF Tier-2 Grant (04MNP002073C230). This work is also supported by the National Natural Science Foundation of China (Grant Numbers 11871297 and U1839206), the National Key Research and Development Program of China on Monitoring, Early Warning and Prevention of Major Natural Disaster (Grant Number 2017YFC1500301), and Tsinghua University Initiative Scientific Research Program.

We propose and analyze a class of temporal up to fourth-order unconditionally structure-preserving single-step methods for Allen–Cahn-type semilinear parabolic equations. We first revisit some up to second-order exponential time different Runge–Kutta (ETDRK) schemes, and provide unified proofs for the unconditionally maximum-principle-preserving and mass-conserving properties. Noting that the stabilized ETDRK schemes belong to a special class of parametric Runge–Kutta schemes, we introduce the stabilized integrating factor Runge–Kutta (sIFRK) formulation to construct new high-order parametric single-step methods, and propose two strategies to eliminate the exponential effects of sIFRK: (1) a recursive approximation; (2) a combination of exponential and linear functions. Together with the nonnegativity of coefficients and non-decreasing of abscissas, the resulting two families of improved stabilized integrating factor Runge–Kutta (isIFRK) schemes can unconditionally preserve the maximum-principle and conserve the mass. The order conditions, linear stability and convergence in the l∞-norm are analyzed rigorously. We demonstrate that the proposed framework, which is explicit and free of limiters or cut-off post-processing, offers a simple, practical, and effective approach to developing high-order unconditionally structure-preserving algorithms. Comparisons with traditional schemes demonstrate the necessity of developing high-order unconditionally structure-preserving schemes. A series of numerical experiments verify theoretical results of proposed isIFRK schemes. This work was supported by the Natural Science Foundation of China (No. 11901577, 11971481, 12071481), Natural Science Foundation of Hunan (No. 2020JJ5652), Defense Science Foundation of China (No. 2021-JCJQ-JJ0523), National Key R&D Program of China (No. SQ2020YFA0709803), National Key Project (No. GJXM92579) and Research Fund of National University of Defense Technology (No. ZK19-37, ZZKY-JJ-21-01).

Protein-protein interactions (PPIs) are involved in almost all biological processes in the cell. Understanding protein-protein interactions holds the key for the understanding of biological functions, diseases and the development of therapeutics. Recently, artificial intelligence (AI) models have demonstrated great power in PPIs. However, a key issue for all AI-based PPI models is efficient molecular representations and featurization. Here, we propose Hom-complex-based PPI representation, and Hom-complex-based machine learning models for the prediction of PPI binding affinity changes upon mutation, for the first time. In our model, various Hom complexes Hom(G1, G) can be generated for the graph representation G of protein-protein complex by using different graphs G1, which reveal G1-related inner connections within the graph representation G of protein-protein complex. Further, for a specific graph G1, a series of nested Hom complexes are generated to give a multiscale characterization of the PPIs. Its persistent homology and persistent Euler characteristic are used as molecular descriptors and further combined with the machine learning model, in particular, gradient boosting tree (GBT). We systematically test our model on the two most-commonly used data sets, that is, SKEMPI and AB-Bind. It has been found that our model outperforms all the existing models as far as we know, which demonstrates the great potential of our model for the analysis of PPIs. Our model can be used for the analysis and design of efficient antibodies for SARS-CoV-2. Ministry of Education (MOE) Nanyang Technological University This work was supported in part by Nanyang Technological University Startup Grant M4081842 and Singapore Ministry of Education Academic Research fund Tier 1 RG109/19, MOET2EP20120-0013, and MOE-T2EP20220-0010. The first author was supported by Nankai Zhide foundation. The second author was supported by Natural Science Foundation of China (NSFC Grant No. 11221091, 11271062, 11571184). The third author was supported by Natural Science Foundation of China (NSFC Grant No. 11971144), High-level Scientific Research Foundation of Hebei Province and the start-up research fund from BIMSA.

Hodge theory reveals the deep intrinsic relations of differential forms and provides a bridge between differential geometry, algebraic topology, and functional analysis. Here we use Hodge Laplacian and Hodge decomposition models to analyze biomolecular structures. Different from traditional graph-based methods, biomolecular structures are represented as simplicial complexes, which can be viewed as a generalization of graph models to their higher-dimensional counterparts. Hodge Laplacian matrices at different dimensions can be generated from the simplicial complex. The spectral information of these matrices can be used to study intrinsic topological information of biomolecular structures. Essentially, the number (or multiplicity) of k-th dimensional zero eigenvalues is equivalent to the k-th Betti number, i.e., the number of k-th dimensional homology groups. The associated eigenvectors indicate the homological generators, i.e., circles or holes within the molecular-based simplicial complex. Furthermore, Hodge decomposition-based HodgeRank model is used to characterize the folding or compactness of the molecular structures, in particular, the topological associated domain (TAD) in high-throughput chromosome conformation capture (Hi-C) data. Mathematically, molecular structures are represented in simplicial complexes with certain edge flows. The HodgeRank-based average/total inconsistency (AI/TI) is used for the quantitative measurements of the folding or compactness of TADs. This is the first quantitative measurement for TAD regions, as far as we know. Ministry of Education (MOE) Nanyang Technological University Published version This work was supported in part by Nanyang Technological University Startup Grant M4081842 and Singapore Ministry of Education Academic Research fund Tier 1 RG109/19 and Tier 2 MOE-T2EP20120-0013 and MOE-T2EP20220-0010.

A (t,n)-threshold scheme with secure secret reconstruction, or a (t,n)-SSR scheme for short, is a (t,n)-threshold scheme against the outside adversary who has no valid share, but can impersonate a participant to take part in the secret reconstruction phase. We point out that previous bivariate polynomial-based (t,n)-SSR schemes, such as those of Harn et al. (Information Sciences 2020), are insecure, which is because the outside adversary may obtain the secret by solving a system of [Formula presented] linear equations. We revise Harn et al. scheme and get a secure (t,n)-SSR scheme based on a symmetric bivariate polynomial for the first time, where t⩽n⩽2t-1. To increase the range of n for a given t, we construct a secure (t,n)-SSR scheme based on an asymmetric bivariate polynomial for the first time, where n⩾t. We find that the share sizes of our schemes are the same or almost the same as other existing insecure (t,n)-SSR schemes based on bivariate polynomials. Moreover, our asymmetric bivariate polynomial-based (t,n)-SSR scheme is more easy to be constructed compared to the Chinese Remainder Theorem-based (t,n)-SSR scheme with the stringent condition on moduli, and their share sizes are almost the same. Ministry of Education (MOE) The work of Jian Ding and Changlu Lin was supported in part by National Natural Science Foundation of China under Grant Nos. U1705264 and 61572132, in part by Natural Science Foundation of Fujian Province under Grant No. 2019J01275, in part by Guangxi Key Laboratory of Trusted Software under Grant No. KX202039, and in part by University Natural Science Research Project of Anhui Province under Grant No. KJ2020A0779. The work of Pinhui Ke was supported by National Natural Science Foundation of China under Grant Nos. 61772292 and 61772476. The work of Huaxiong Wang was supported by the Singapore Ministry of Education under Grant Nos. RG12/19 and RG21/18 (S).

The three-dimensional (3D) chromosomal structure plays an essential role in all DNA-templated processes, including gene transcription, DNA replication and other cellular processes. Although developing chromosome conformation capture (3C) methods, such as Hi-C, which can generate chromosomal contact data characterized genome-wide chromosomal structural properties, understanding 3D genomic nature-based on Hi-C data remains lacking. Here, we propose a persistent spectral simplicial complex (PerSpectSC) model to describe Hi-C data for the first time. Specifically, a filtration process is introduced to generate a series of nested simplicial complexes at different scales. For each of these simplicial complexes, its spectral information can be calculated from the corresponding Hodge Laplacian matrix. PerSpectSC model describes the persistence and variation of the spectral information of the nested simplicial complexes during the filtration process. Different from all previous models, our PerSpectSC-based features provide a quantitative global-scale characterization of chromosome structures and topology. Our descriptors can successfully classify cell types and also cellular differentiation stages for all the 24 types of chromosomes simultaneously. In particular, persistent minimum best characterizes cell types and Dim (1) persistent multiplicity best characterizes cellular differentiation. These results demonstrate the great potential of our PerSpectSC-based models in polymeric data analysis. Ministry of Education (MOE) Nanyang Technological University Nanyang Technological University Startup Grant (grant no. M4081842.110); Singapore Ministry of Education Academic Research fund (grant nos. Tier 1 RG109/19, Tier 2 MOE2018-T2-1-033, Tier 2 MOE-T2EP20120-0013); National Natural Science Foundation of China (grant no. 31971180); China Scholarship Council (grant no. 201906540026).