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Infantile spasms (IS) is a neurological disorder causing mental and/or developmental retardation in many infants. Hypsarrhythmia is a typical symptom in the electroencephalography (EEG) signals with IS. Long-Term EEG/video monitoring is most frequently employed in clinical practice for IS diagnosis, from which manual screening of hypsarrhythmia is time consuming and lack of sufficient reliability. This study aims to identify potential biomarkers for automatic IS diagnosis by quantitative analysis of the EEG signals. A large cohort of 101 IS patients and 155 healthy controls (HC) were involved. Typical hypsarrhythmia and non-hypsarrhythmia EEG signals were annotated, and normal EEG were randomly picked from the HC. Root mean square (RMS), teager energy (TE), mean frequency, sample entropy (SamEn), multi-channel SamEn, multi-scale SamEn, and nonlinear correlation coefficient were computed in each sub-band of the three EEG signals, and then compared using either a one-way ANOVA or a Kruskal-Wallis test (based on their distribution) and the receiver operating characteristic (ROC) curves. The effects of infant age on these features were also investigated. For most of the employed features, significant ({p} < {0}.{05} ) differences were observed between hypsarrhythmia EEG and non-hypsarrhythmia EEG or HC, which seem to increase with increased infant age. RMS and TE produce the best classification in the delta and theta bands, while entropy features yields the best performance in the gamma band. Our study suggests RMS and TE (delta and theta bands) and entropy features (gamma band) to be promising biomarkers for automatic detection of hypsarrhythmia in long-Term EEG monitoring. The findings of our study indicate the feasibility of automated IS diagnosis using artificial intelligence.

Constacyclic codes over finite fields are a family of linear codes and contain cyclic codes as a subclass. Constacyclic codes are related to many areas of mathematics and outperform cyclic codes in several aspects. Hence, constacyclic codes are of theoretical importance. On the other hand, constacyclic codes are important in practice, as they have rich algebraic structures and may have efficient decoding algorithms. In this paper, two classes of constacyclic codes are constructed using a general construction of constacyclic codes with cyclic codes. The first class of constacyclic codes is motivated by the punctured Dilix cyclic codes and the second class is motivated by the punctured generalised Reed-Muller codes. The two classes of constacyclic codes contain optimal linear codes. The parameters of the two classes of constacyclic codes are analysed and some open problems are presented in this paper. IEEE

Large language models (LLMs) are primarily evaluated by overall performance on various text understanding and generation tasks. However, such a paradigm fails to comprehensively differentiate the fine-grained language and cognitive skills, rendering the lack of sufficient interpretation to LLMs' capabilities. In this paper, we present FAC$^2$E, a framework for Fine-grAined and Cognition-grounded LLMs' Capability Evaluation. Specifically, we formulate LLMs' evaluation in a multi-dimensional and explainable manner by dissociating the language-related capabilities and the cognition-related ones. Besides, through extracting the intermediate reasoning from LLMs, we further break down the process of applying a specific capability into three sub-steps: recalling relevant knowledge, utilizing knowledge, and solving problems. Finally, FAC$^2$E evaluates each sub-step of each fine-grained capability, providing a two-faceted diagnosis for LLMs. Utilizing FAC$^2$E, we identify a common shortfall in knowledge utilization among models and propose a straightforward, knowledge-enhanced method to mitigate this issue. Our results not only showcase promising performance enhancements but also highlight a direction for future LLM advancements., Comment: Work in Progress

Studying the generalized Hamming weights of linear codes is a significant research area within coding theory, as it provides valuable structural information about the codes and plays a crucial role in determining their performance in various applications. However, determining the generalized Hamming weights of linear codes, particularly their weight hierarchy, is generally a challenging task. In this paper, we focus on investigating the generalized Hamming weights of three classes of linear codes over finite fields. These codes are constructed by different defining sets. By analysing the intersections between the definition sets and the duals of all $r$-dimensional subspaces, we get the inequalities on the sizes of these intersections. Then constructing subspaces that reach the upper bounds of these inequalities, we successfully determine the complete weight hierarchies of these codes.

The effectiveness of anomaly signal detection can be significantly undermined by the inherent uncertainty of relying on one specified model. Under the framework of model average methods, this paper proposes a novel criterion to select the weights on aggregation of multiple models, wherein the focal loss function accounts for the classification of extremely imbalanced data. This strategy is further integrated into Random Forest algorithm by replacing the conventional voting method. We have evaluated the proposed method on benchmark datasets across various domains, including network intrusion. The findings indicate that our proposed method not only surpasses the model averaging with typical loss functions but also outstrips common anomaly detection algorithms in terms of accuracy and robustness.

For partial differential equations on domains of arbitrary shapes, existing works of neural operators attempt to learn a mapping from geometries to solutions. It often requires a large dataset of geometry-solution pairs in order to obtain a sufficiently accurate neural operator. However, for many industrial applications, e.g., engineering design optimization, it can be prohibitive to satisfy the requirement since even a single simulation may take hours or days of computation. To address this issue, we propose reference neural operators (RNO), a novel way of implementing neural operators, i.e., to learn the smooth dependence of solutions on geometric deformations. Specifically, given a reference solution, RNO can predict solutions corresponding to arbitrary deformations of the referred geometry. This approach turns out to be much more data efficient. Through extensive experiments, we show that RNO can learn the dependence across various types and different numbers of geometry objects with relatively small datasets. RNO outperforms baseline models in accuracy by a large lead and achieves up to 80% error reduction.

In this paper, several families of irreducible constacyclic codes over finite fields and their duals are studied. The weight distributions of these irreducible constacyclic codes and the parameters of their duals are settled. Several families of irreducible constacyclic codes with a few weights and several families of optimal constacyclic codes are constructed. As byproducts, a family of [2n, (n -1)/2, d = 2(vn+1)] irreducible cyclic codes over GF((q)) and a family of [(q-1)n, (n-1)/2,d =(q-1)(vn+1)] irreducible cyclic codes over GF((q)) are presented, where n is a prime such that ord(2n)(q) = (n - 1)/2 and ord((q-1)n)(q) = (n - 1)/2, respectively. The results in this paper complement earlier works on irreducible constacyclic and cyclic codes over finite fields.

Negacyclic BCH codes are a subclass of neagcyclic codes and are the best linear codes in many cases. However, there have been very few results on negacyclic BCH codes. Let q be an odd prime power and m be a positive integer. The objective of this paper is to study negacyclic BCH codes with length qm-12 and qm+12 over the finite field GF (q) and analyse their parameters. The negacyclic BCH codes presented in this paper have good parameters in general, and contain many optimal linear codes. For certain q and m, compared with cyclic codes with the same dimension and length, the negacyclic BCH codes presented in this paper have a larger minimum distance in some cases. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

RGB-D salient object detection aims to detect visually distinctive objects or regions from a pair of the RGB image and the depth image. State-of-the-art RGB-D saliency detectors are mainly based on convolutional neural networks but almost suffer from an intrinsic limitation relying on the labeled data, thus degrading detection accuracy in complex cases. In this work, we present a self-supervised self-ensembling network (S3 Net) for semi-supervised RGB-D salient object detection by leveraging the unlabeled data and exploring a self-supervised learning mechanism. To be specific, we first build a self-guided convolutional neural network (SG-CNN) as a baseline model by developing a series of three-layer cross-model feature fusion (TCF) modules to leverage complementary information among depth and RGB modalities and formulating an auxiliary task that predicts a self-supervised image rotation angle. After that, to further explore the knowledge from unlabeled data, we assign SG-CNN to a student network and a teacher network, and encourage the saliency predictions and self-supervised rotation predictions from these two networks to be consistent on the unlabeled data. Experimental results on seven widely-used benchmark datasets demonstrate that our network quantitatively and qualitatively outperforms the state-of-the-art methods. © 1999-2012 IEEE.

We previously proposed contextual spelling correction (CSC) to correct the output of end-to-end (E2E) automatic speech recognition (ASR) models with contextual information such as name, place, etc. Although CSC has achieved reasonable improvement in the biasing problem, there are still two drawbacks for further accuracy improvement. First, due to information limitation in text only hypothesis or weak performance of ASR model on rare domains, the CSC model may fail to correct phrases with similar pronunciation or anti-context cases where all biasing phrases are not present in the utterance. Second, there is a discrepancy between the training and inference of CSC. The bias list in training is randomly selected but in inference there may be more similarity between ground truth phrase and other phrases. To solve above limitations, in this paper we propose an improved non-autoregressive (NAR) spelling correction model for contextual biasing in E2E neural transducer-based ASR systems to improve the previous CSC model from two perspectives: Firstly, we incorporate acoustics information with an external attention as well as text hypotheses into CSC to better distinguish target phrase from dissimilar or irrelevant phrases. Secondly, we design a semantic aware data augmentation schema in training phrase to reduce the mismatch between training and inference to further boost the biasing accuracy. Experiments show that the improved method outperforms the baseline ASR+Biasing system by as much as 20.3% relative name recall gain and achieves stable improvement compared to the previous CSC method over different bias list name coverage ratio., Comment: Accepted by ICASSP 2023

Interplay between coding theory and combinatorial t -designs has been a hot topic for many years for combinatorialists and coding theorists. Some infinite families of cyclic codes supporting infinite families of 3-designs have been constructed in the past 50 years. However, no infinite family of negacyclic codes supporting an infinite family of 3-designs has been reported in the literature. This is the main motivation of this paper. Let q=pm , where p is an odd prime and m≥2 is an integer. The objective of this paper is to present an infinite family of cyclic codes over GF(q) supporting an infinite family of 3-designs and two infinite families of negacyclic codes over GF(q2) supporting two infinite families of 3-designs. The parameters and the weight distributions of these codes are determined. The subfield subcodes of these negacyclic codes over GF(q) are studied. Three infinite families of almost MDS codes are also presented. A constacyclic code over GF(4) supporting a 4-design and seven open problems are also presented in this paper.

We present $\textbf{$\texttt{SkillQG}$}$: a question generation framework with controllable comprehension types for assessing and improving machine reading comprehension models. Existing question generation systems widely differentiate questions by $\textit{literal}$ information such as question words and answer types to generate semantically relevant questions for a given context. However, they rarely consider the $\textit{comprehension}$ nature of questions, i.e. the different comprehension capabilities embodied by different questions. In comparison, our $\texttt{SkillQG}$ is able to tailor a fine-grained assessment and improvement to the capabilities of question answering models built on it. Specifically, we first frame the comprehension type of questions based on a hierarchical skill-based schema, then formulate $\texttt{SkillQG}$ as a skill-conditioned question generator. Furthermore, to improve the controllability of generation, we augment the input text with question focus and skill-specific knowledge, which are constructed by iteratively prompting the pre-trained language models. Empirical results demonstrate that $\texttt{SkillQG}$ outperforms baselines in terms of quality, relevance, and skill-controllability while showing a promising performance boost in downstream question answering task., Comment: Accepted at ACL 2023 Findings

BCH codes are an interesting class of cyclic codes due to their efficient encoding and decoding algorithms. In the past sixty years, a lot of progress on the study of BCH codes has been made, but little is known about the properties of their duals. Recently, in order to study the duals of BCH codes and the lower bounds on their minimum distances, a new concept called dually-BCH code was proposed by authors in \cite{GDL21}. In this paper, the lower bounds on the minimum distances of the duals of narrow-sense BCH codes with length $\frac{q^m-1}{\lambda}$ over $\mathbb{F}_q$ are developed, where $\lambda$ is a positive integer satisfying $\lambda\, |\, q-1$, or $\lambda=q^s-1$ and $s\, |\,m$. In addition, the sufficient and necessary conditions in terms of the designed distances for these codes being dually-BCH codes are presented. Many considered codes in \cite{GDL21} and \cite{Wang23} are the special cases of the codes showed in this paper. Our lower bounds on the minimum distances of the duals of BCH codes include the bounds stated in \cite{GDL21} as a special case. Several examples show that the lower bounds are good in some cases.

An $(r, \delta)$-locally repairable code ($(r, \delta)$-LRC for short) was introduced by Prakash et al. for tolerating multiple failed nodes in distributed storage systems, and has garnered significant interest among researchers. An $(r,\delta)$-LRC is called an optimal code if its parameters achieve the Singleton-like bound. In this paper, we construct three classes of $q$-ary optimal cyclic $(r,\delta)$-LRCs with new parameters by investigating the defining sets of cyclic codes. Our results generalize the related work of \cite{Chen2022,Qian2020}, and the obtained optimal cyclic $(r, \delta)$-LRCs have flexible parameters. A lot of numerical examples of optimal cyclic $(r, \delta)$-LRCs are given to show that our constructions are capable of generating new optimal cyclic $(r, \delta)$-LRCs.

The study of the generalized Hamming weight of linear codes is a significant research topic in coding theory as it conveys the structural information of the codes and determines their performance in various applications. However, determining the generalized Hamming weights of linear codes, especially the weight hierarchy, is generally challenging. In this paper, we investigate the generalized Hamming weights of a class of linear code $\C$ over $\bF_q$, which is constructed from defining sets. These defining sets are either special simplicial complexes or their complements in $\bF_q^m$. We determine the complete weight hierarchies of these codes by analyzing the maximum or minimum intersection of certain simplicial complexes and all $r$-dimensional subspaces of $\bF_q^m$, where $1\leq r\leq {\rm dim}_{\bF_q}(\C)$.

The high-density data storage technology aims to design high-capacity storage at a relatively low cost. In order to achieve this goal, symbol-pair codes were proposed by Cassuto and Blaum \cite{CB10,CB11} to handle channels that output pairs of overlapping symbols. Such a channel is called symbol-pair read channel, which introduce new concept called symbol-pair weight and minimum symbol-pair distance. In this paper, we consider the parameters of two classes of reducible cyclic codes under the symbol-pair metric. Based on the theory of cyclotomic numbers and Gaussian period over finite fields, we show the possible symbol-pair weights of these codes. Their minimum symbol-pair distances are twice the minimum Hamming distances under some conditions. Moreover, we obtain some three symbol-pair weight codes and determine their symbol-pair weight distribution. A class of MDS symbol-pair codes is also established. Among other results, we determine the values of some generalized cyclotomic numbers.

The generalized Hamming weight of linear codes is a natural generalization of the minimum Hamming distance. They convey the structural information of a linear code and determine its performance in various applications, and have become one of important research topics in coding theory. Recently, Li (IEEE Trans. Inf. Theory, 67(1): 124-129, 2021) and Li and Li (Discrete Math., 345: 112718, 2022) obtained the complete weight hierarchy of linear codes from a quadratic form over a finite field of odd characteristic by analysis of the solutions of the restricted quadratic equation in its subspace. In this paper, we further determine the complete weight hierarchy of linear codes from a quadratic form over a finite field of even characteristic by carefully studying the behavior of the quadratic form on the subspaces of this field and its dual space, and complement the results of Li and Li.

BCH codes and their dual codes are two special subclasses of cyclic codes and are the best linear codes in many cases. A lot of progress on the study of BCH cyclic codes has been made, but little is known about the minimum distances of the duals of BCH codes. Recently, a new concept called dually-BCH code was introduced to investigate the duals of BCH codes and the lower bounds on their minimum distances in \cite{GDL21}. For a prime power $q$ and an integer $m \ge 4$, let $n=\frac{q^m-1}{q+1}$ \ ($m$ even), or $n=\frac{q^m-1}{q-1}$ \ ($q>2$). In this paper, some sufficient and necessary conditions in terms of the designed distance will be given to ensure that the narrow-sense BCH codes of length $n$ are dually-BCH codes, which extended the results in \cite{GDL21}. Lower bounds on the minimum distances of their dual codes are developed for $n=\frac{q^m-1}{q+1}$ \ ($m$ even). As byproducts, we present the largest coset leader $\delta_1$ modulo $n$ being of two types, which proves a conjecture in \cite{WLP19} and partially solves an open problem in \cite{Li2017}. We also investigate the parameters of the narrow-sense BCH codes of length $n$ with design distance $\delta_1$. The BCH codes presented in this paper have good parameters in general.

Constacyclic codes over finite fields are a family of linear codes and contain cyclic codes as a subclass. Constacyclic codes are related to many areas of mathematics and outperform cyclic codes in several aspects. Hence, constacyclic codes are of theoretical importance. On the other hand, constacyclic codes are important in practice, as they have rich algebraic structures and may have efficient decoding algorithms. In this paper, two classes of constacyclic codes are constructed using a general construction of constacyclic codes with cyclic codes. The first class of constacyclic codes is motivated by the punctured Dilix cyclic codes and the second class is motivated by the punctured generalised Reed-Muller codes. The two classes of constacyclic codes contain optimal linear codes. The parameters of the two classes of constacyclic codes are analysed and some open problems are presented in this paper.

Interplay between coding theory and combinatorial $t$-designs has been a hot topic for many years for combinatorialists and coding theorists. Some infinite families of cyclic codes supporting infinite families of $3$-designs have been constructed in the past 50 years. However, no infinite family of negacyclic codes supporting an infinite family of $3$-designs has been reported in the literature. This is the main motivation of this paper. Let $q=p^m$, where $p$ is an odd prime and $m \geq 2$ is an integer. The objective of this paper is to present an infinite family of cyclic codes over $\gf(q)$ supporting an infinite family of $3$-designs and two infinite families of negacyclic codes over $\gf(q^2)$ supporting two infinite families of $3$-designs. The parameters and the weight distributions of these codes are determined. The subfield subcodes of these negacyclic codes over $\gf(q)$ are studied. Three infinite families of almost MDS codes are also presented. A constacyclic code over GF($4$) supporting a $4$-design and six open problems are also presented in this paper.

Negacyclic BCH codes are a subclass of neagcyclic codes and are the best linear codes in many cases. However, there have been very few results on negacyclic BCH codes. Let $q$ be an odd prime power and $m$ be a positive integer. The objective of this paper is to study negacyclic BCH codes with length $\frac{q^m-1}{2}$ and $\frac{q^m+1}{2}$ over the finite field $\mathbf(q)$ and analyse their parameters. The negacyclic BCH codes presented in this paper have good parameters in general, and contain many optimal linear codes. For certain $q$ and $m$, compared with cyclic codes with the same dimension and length, the negacyclic BCH codes presented in this paper have a larger minimum distance in some cases.

In this paper, several families of irreducible constacyclic codes over finite fields and their duals are studied. The weight distributions of these irreducible constacyclic codes and the parameters of their duals are settled. Several families of irreducible constacyclic codes with a few weights and several families of optimal constacyclic codes are constructed. As by-products, a family of $[2n, (n-1)/2, d \geq 2(\sqrt{n}+1)]$ irreducible cyclic codes over $\gf(q)$ and a family of $[(q-1)n, (n-1)/2, d \geq (q-1)(\sqrt{n}+1)]$ irreducible cyclic codes over $\gf(q)$ are presented, where $n$ is a prime such that $\ord_n(q)=(n-1)/2$. The results in this paper complement earlier works on irreducible constacyclic and cyclic codes over finite fields.

Existing metrics for assessing question generation not only require costly human reference but also fail to take into account the input context of generation, rendering the lack of deep understanding of the relevance between the generated questions and input contexts. As a result, they may wrongly penalize a legitimate and reasonable candidate question when it (i) involves complicated reasoning with the context or (ii) can be grounded by multiple evidences in the context. In this paper, we propose $\textbf{QRelScore}$, a context-aware $\underline{\textbf{Rel}}$evance evaluation metric for $\underline{\textbf{Q}}$uestion Generation. Based on off-the-shelf language models such as BERT and GPT2, QRelScore employs both word-level hierarchical matching and sentence-level prompt-based generation to cope with the complicated reasoning and diverse generation from multiple evidences, respectively. Compared with existing metrics, our experiments demonstrate that QRelScore is able to achieve a higher correlation with human judgments while being much more robust to adversarial samples., Comment: 16 pages, 7 figures

Machine Reading Comprehension (MRC) reveals the ability to understand a given text passage and answer questions based on it. Existing research works in MRC rely heavily on large-size models and corpus to improve the performance evaluated by metrics such as Exact Match ($EM$) and $F_1$. However, such a paradigm lacks sufficient interpretation to model capability and can not efficiently train a model with a large corpus. In this paper, we argue that a deep understanding of model capabilities and data properties can help us feed a model with appropriate training data based on its learning status. Specifically, we design an MRC capability assessment framework that assesses model capabilities in an explainable and multi-dimensional manner. Based on it, we further uncover and disentangle the connections between various data properties and model performance. Finally, to verify the effectiveness of the proposed MRC capability assessment framework, we incorporate it into a curriculum learning pipeline and devise a Capability Boundary Breakthrough Curriculum (CBBC) strategy, which performs a model capability-based training to maximize the data value and improve training efficiency. Extensive experiments demonstrate that our approach significantly improves performance, achieving up to an 11.22% / 8.71% improvement of $EM$ / $F_1$ on MRC tasks., Comment: Accepted by ACL 2022

Contextual biasing is an important and challenging task for end-to-end automatic speech recognition (ASR) systems, which aims to achieve better recognition performance by biasing the ASR system to particular context phrases such as person names, music list, proper nouns, etc. Existing methods mainly include contextual LM biasing and adding bias encoder into end-to-end ASR models. In this work, we introduce a novel approach to do contextual biasing by adding a contextual spelling correction model on top of the end-to-end ASR system. We incorporate contextual information into a sequence-to-sequence spelling correction model with a shared context encoder. Our proposed model includes two different mechanisms: autoregressive (AR) and non-autoregressive (NAR). We propose filtering algorithms to handle large-size context lists, and performance balancing mechanisms to control the biasing degree of the model. We demonstrate the proposed model is a general biasing solution which is domain-insensitive and can be adopted in different scenarios. Experiments show that the proposed method achieves as much as 51% relative word error rate (WER) reduction over ASR system and outperforms traditional biasing methods. Compared to the AR solution, the proposed NAR model reduces model size by 43.2% and speeds up inference by 2.1 times., Comment: Accepted in IEEE Transactions on Audio, Speech and Language Processing (TASLP)

This paper proposes a new "decompose-and-edit" paradigm for the text-based speech insertion task that facilitates arbitrary-length speech insertion and even full sentence generation. In the proposed paradigm, global and local factors in speech are explicitly decomposed and separately manipulated to achieve high speaker similarity and continuous prosody. Specifically, we proposed to represent the global factors by multiple tokens, which are extracted by cross-attention operation and then injected back by link-attention operation. Due to the rich representation of global factors, we manage to achieve high speaker similarity in a zero-shot manner. In addition, we introduce a prosody smoothing task to make the local prosody factor context-aware and therefore achieve satisfactory prosody continuity. We further achieve high voice quality with an adversarial training stage. In the subjective test, our method achieves state-of-the-art performance in both naturalness and similarity. Audio samples can be found at https://ydcustc.github.io/retrieverTTS-demo/., Comment: 5 pages, 1 figure, 3 tables. Accepted by Interspeech 2022

Insertion-deletion codes (insdel codes for short) are used for correcting synchronization errors in communications, and in other many interesting fields such as DNA storage, date analysis, race-track memory error correction and language processing, and have recently gained a lot of attention. To determine the insdel distances of linear codes is a very challenging problem. The half-Singleton bound on the insdel distances of linear codes due to Cheng-Guruswami-Haeupler-Li is a basic upper bound on the insertion-deletion error-correcting capabilities of linear codes. On the other hand the natural direct upper bound $d_I(\mathcal C) \leq 2d_H(\mathcal C)$ is valid for any insdel code. In this paper, for a linear insdel code $\mathcal C$ we propose a strict half-Singleton upper bound $d_I(\mathcal C) \leq 2(n-2k+1)$ if $\mathcal C$ does not contain the codeword with all 1s, and a stronger direct upper bound $d_I(\mathcal C) \leq 2(d_H(\mathcal C)-t)$ under a weak condition, where $t\geq 1$ is a positive integer determined by the generator matrix. We also give optimal linear insdel codes attaining our strict half-Singleton bound and direct upper bound, and show that the code length of optimal binary linear insdel codes with respect to the (strict) half-Singleton bound is about twice the dimension. Interestingly explicit optimal linear insdel codes attaining the (strict) half-Singleton bound, with the code length being independent of the finite field size, are given.

The rich functionalities of transition-metal oxides and their interfaces bear an enormous technological potential. Its realization in practical devices requires, however, a significant improvement of yet relatively low electron mobility in oxide materials. Recently, a mobility boost of about 2 orders of magnitude has been demonstrated at the spinel-perovskite γ-Al2O3/SrTiO3 interface compared to the paradigm perovskite-perovskite LaAlO3/SrTiO3 interface. We explore the fundamental physics behind this phenomenon from direct measurements of the momentum-resolved electronic structure of this interface using resonant soft-X-ray angle-resolved photoemission. We find an anomaly in orbital ordering of the mobile electrons in γ-Al2O3/SrTiO3 which depopulates electron states in the top SrTiO3 layer. This rearrangement of the mobile electron system pushes the electron density away from the interface, which reduces its overlap with the interfacial defects and weakens the electron-phonon interaction, both effects contributing to the mobility boost. A crystal-field analysis shows that the band order alters owing to the symmetry breaking between the spinel γ-Al2O3 and perovskite SrTiO3. Band-order engineering, exploiting the fundamental symmetry properties, emerges as another route to boost the performance of oxide devices.

The rich functionalities of transition-metal oxides and their interfaces bear an enormous technological potential. Its realization in practical devices requires, however, a significant improvement of yet relatively low electron mobility in oxide materials. Recently, a mobility boost of about 2 orders of magnitude has been demonstrated at the spinel-perovskite gamma-Al2O3/SrTiO3 interface compared to the paradigm perovskite-perovskite LaAlO3/SrTiO3 interface. We explore the fundamental physics behind this phenomenon from direct measurements of the momentum-resolved electronic structure of this interface using resonant soft-X-ray angle-resolved photoemission. We find an anomaly in orbital ordering of the mobile electrons in gamma-Al2O3/SrTiO3 which depopulates electron states in the top SrTiO3 layer. This rearrangement of the mobile electron system pushes the electron density away from the interface, which reduces its overlap with the interfacial defects and weakens the electron-phonon interaction, both effects contributing to the mobility boost. A crystal-field analysis shows that the band order alters owing to the symmetry breaking between the spinel gamma-Al2O3 and perovskite SrTiO3. Band-order engineering, exploiting the fundamental symmetry properties, emerges as another route to boost the performance of oxide devices.

The rich functionalities of transition-metal oxides and their interfaces bear an enormous technological potential. Its realization in practical devices requires, however, a significant improvement of yet relatively low electron mobility in oxide materials. Recently, a mobility boost of about 2 orders of magnitude has been demonstrated at the spinel-perovskite gamma-Al2O3/SrTiO3 interface compared to the paradigm perovskite-perovskite LaAlO3/SrTiO3 interface. We explore the fundamental physics behind this phenomenon from direct measurements of the momentum-resolved electronic structure of this interface using resonant soft-X-ray angle-resolved photoemission. We find an anomaly in orbital ordering of the mobile electrons in gamma-Al2O3/SrTiO3 which depopulates electron states in the top SrTiO3 layer. This rearrangement of the mobile electron system pushes the electron density away from the interface, which reduces its overlap with the interfacial defects and weakens the electron-phonon interaction, both effects contributing to the mobility boost. A crystal-field analysis shows that the band order alters owing to the symmetry breaking between the spinel gamma-Al2O3 and perovskite SrTiO3. Band-order engineering, exploiting the fundamental symmetry properties, emerges as another route to boost the performance of oxide devices.

The rich functionalities of transition-metal oxides and their interfaces bear an enormous technological potential. Its realization in practical devices requires, however, a significant improvement of yet relatively low electron mobility in oxide materials. Recently, a mobility boost of about 2 orders of magnitude has been demonstrated at the spinel-perovskite gamma-Al2O3/SrTiO3 interface compared to the paradigm perovskite-perovskite LaAlO3/SrTiO3 interface. We explore the fundamental physics behind this phenomenon from direct measurements of the momentum-resolved electronic structure of this interface using resonant soft-X-ray angle-resolved photoemission. We find an anomaly in orbital ordering of the mobile electrons in gamma-Al2O3/SrTiO3 which depopulates electron states in the top SrTiO3 layer. This rearrangement of the mobile electron system pushes the electron density away from the interface, which reduces its overlap with the interfacial defects and weakens the electron-phonon interaction, both effects contributing to the mobility boost. A crystal-field analysis shows that the band order alters owing to the symmetry breaking between the spinel gamma-Al2O3 and perovskite SrTiO3. Band-order engineering, exploiting the fundamental symmetry properties, emerges as another route to boost the performance of oxide devices.

The rich functionalities of transition-metal oxides and their interfaces bear an enormous technological potential. Its realization in practical devices requires, however, a significant improvement of yet relatively low electron mobility in oxide materials. Recently, a mobility boost of about 2 orders of magnitude has been demonstrated at the spinel-perovskite gamma-Al2O3/SrTiO3 interface compared to the paradigm perovskite-perovskite LaAlO3/SrTiO3 interface. We explore the fundamental physics behind this phenomenon from direct measurements of the momentum-resolved electronic structure of this interface using resonant soft-X-ray angle-resolved photoemission. We find an anomaly in orbital ordering of the mobile electrons in gamma-Al2O3/SrTiO3 which depopulates electron states in the top SrTiO3 layer. This rearrangement of the mobile electron system pushes the electron density away from the interface, which reduces its overlap with the interfacial defects and weakens the electron-phonon interaction, both effects contributing to the mobility boost. A crystal-field analysis shows that the band order alters owing to the symmetry breaking between the spinel gamma-Al2O3 and perovskite SrTiO3. Band-order engineering, exploiting the fundamental symmetry properties, emerges as another route to boost the performance of oxide devices.

Training deep models for RGB-D salient object detection (SOD) often requires a large number of labeled RGB-D images. However, RGB-D data is not easily acquired, which limits the development of RGB-D SOD techniques. To alleviate this issue, we present a Dual-Semi RGB-D Salient Object Detection Network (DS-Net) to leverage unlabeled RGB images for boosting RGB-D saliency detection. We first devise a depth decoupling convolutional neural network (DDCNN), which contains a depth estimation branch and a saliency detection branch. The depth estimation branch is trained with RGB-D images and then used to estimate the pseudo depth maps for all unlabeled RGB images to form the paired data. The saliency detection branch is used to fuse the RGB feature and depth feature to predict the RGB-D saliency. Then, the whole DDCNN is assigned as the backbone in a teacher-student framework for semi-supervised learning. Moreover, we also introduce a consistency loss on the intermediate attention and saliency maps for the unlabeled data, as well as a supervised depth and saliency loss for labeled data. Experimental results on seven widely-used benchmark datasets demonstrate that our DDCNN outperforms state-of-the-art methods both quantitatively and qualitatively. We also demonstrate that our semi-supervised DS-Net can further improve the performance, even when using an RGB image with the pseudo depth map., Comment: Accepted by IEEE TIP

[Background]: Gene and chemical therapy has become one of the rising stars in the field of molecular medicine during the last two decades. However, there are still numerous challenges in the development of efficient, targeted, and safe delivery systems that can avoid siRNA degradation and reduce the toxicity and adverse effects of chemotherapy medicine., [Results]: In this paper, a highly efficient AS1411 aptamer modified, dsDNA and MMP-2 cleavable peptide-fabricated gold nanocage vehicle, which could load doxorubicin hydrochloride (DOX) and siRNAs to achieve a combination of tumor responsive genetic therapy, chemotherapy, and photothermal treatment is presented. Our results show that this combined treatment achieved targeted gene silencing and tumor inhibition. After nearly one month of treatment with DOX-loaded Au-siRNA-PAA-AS1411 nanoparticles with one dose every three days in mice, a synergistic effect promoting the eradication of long-lived tumors was observed along with an increased survival rate of mice. The combined genetic, chemotherapeutic, and photothermal treatment group exhibited more than 90% tumor inhibition ratio (tumor signal) and a ~ 67% survival rate compared with a 30% tumor inhibition ratio and a 0% survival rate in the passive genetic treatment group., [Conclusions]: The development of nanocarriers with double-stranded DNA and MMP-2 cleavable peptides provides a new strategy for the combined delivery of gene and chemotherapy medicine. Au-siRNA-PAA-AS1411 exerts high anticancer activities on lung cancer, indicating immense potentials for clinical application.

It is well-known that cyclic codes have efficient encoding and decoding algorithms. In recent years, antiprimitive BCH codes have attracted a lot of attention. The objective of this paper is to study BCH codes of this type over finite fields and analyse their parameters. Some lower bounds on the minimum distance of antiprimitive BCH codes are given. The BCH codes presented in this paper have good parameters in general, containing many optimal linear codes. In particular, two open problems about the minimum distance of BCH codes of this type are partially solved in this paper., Comment: This manuscript was first submitted to IEEE Tran. Inf. Theory in 06, April, 2021

Based on the current-mode switching cell (CMSC), an inductive power transfer (IPT) system with dual-output is proposed in this letter. In the proposed IPT system, two CMSCs are inversely connected in series at the Rx side. Two CMSCs operate in the positive half-cycle and in the negative half-cycle of the Rx coil current, respectively. The dual output voltages can be regulated independently. The circuit structure of the CMSC is quite simple and helps to make the Rx side more compact. The control scheme is based on Rx-side real-time regulation and thereby wireless communication links are not required. Additionally, zero voltage switching (ZVS) is ensured for all switches. In order to verify the theoretical analysis, an experimental prototype with 20V/3.3A and 5V/3A outputs is fabricated, and the maximum efficiency can reach 92.8%.

It's challenging to customize transducer-based automatic speech recognition (ASR) system with context information which is dynamic and unavailable during model training. In this work, we introduce a light-weight contextual spelling correction model to correct context-related recognition errors in transducer-based ASR systems. We incorporate the context information into the spelling correction model with a shared context encoder and use a filtering algorithm to handle large-size context lists. Experiments show that the model improves baseline ASR model performance with about 50% relative word error rate reduction, which also significantly outperforms the baseline method such as contextual LM biasing. The model also shows excellent performance for out-of-vocabulary terms not seen during training., Comment: This paper has been accepted by Interspeech 2021

BCH codes are an interesting class of cyclic codes due to their efficient encoding and decoding algorithms. In many cases, BCH codes are the best linear codes. However, the dimension and minimum distance of BCH codes have been seldom solved. Until now, there have been few results on BCH codes over $\gf(q)$ with length $q^m+1$, especially when $q$ is a prime power and $m$ is even. The objective of this paper is to study BCH codes of this type over finite fields and analyse their parameters. The BCH codes presented in this paper have good parameters in general, and contain many optimal linear codes., Comment: This paper is amalgamated with another paper

It is a long-standing question to discover causal relations among a set of variables in many empirical sciences. Recently, Reinforcement Learning (RL) has achieved promising results in causal discovery from observational data. However, searching the space of directed graphs and enforcing acyclicity by implicit penalties tend to be inefficient and restrict the existing RL-based method to small scale problems. In this work, we propose a novel RL-based approach for causal discovery, by incorporating RL into the ordering-based paradigm. Specifically, we formulate the ordering search problem as a multi-step Markov decision process, implement the ordering generating process with an encoder-decoder architecture, and finally use RL to optimize the proposed model based on the reward mechanisms designed for~each ordering. A generated ordering would then be processed using variable selection to obtain the final causal graph. We analyze the consistency and computational complexity of the proposed method, and empirically show that a pretrained model can be exploited to accelerate training. Experimental results on both synthetic and real data sets shows that the proposed method achieves a much improved performance over existing RL-based method., Comment: Accepted to IJCAI'2021

Recently, a new concept called multiplicative differential cryptanalysis and the corresponding $c$-differential uniformity were introduced by Ellingsen et al.~\cite{Ellingsen2020}, and then some low differential uniformity functions were constructed. In this paper, we further study the constructions of perfect $c$-nonlinear (PcN) power functions. First, we give a necessary and sufficient condition for the Gold function to be PcN and a conjecture on all power functions to be PcN over $\gf(2^m)$. Second, several classes of PcN power functions are obtained over finite fields of odd characteristic for $c=-1$ and our theorems generalize some results in~\cite{Bartoli,Hasan,Zha2020}. Finally, the $c$-differential spectrum of a class of almost perfect $c$-nonlinear (APcN) power functions is determined., Comment: C-differential uniformity, perfect c-nonlinear function, almost perfect c-nonlinear function, differential spectrum

Two general constructions of linear codes with functions over finite fields have been extensively studied in the literature. The first one is given by $\mathcal{C}(f)=\left\{ {\rm Tr}(af(x)+bx)_{x \in \mathbb{F}_{q^m}^*}: a,b \in \mathbb{F}_{q^m} \right\}$, where $q$ is a prime power, $\bF_{q^m}^*=\bF_{q^m} \setminus \{0\}$, $\tr$ is the trace function from $\bF_{q^m}$ to $\bF_q$, and $f(x)$ is a function from $\mathbb{F}_{q^m}$ to $\mathbb{F}_{q^m}$ with $f(0)=0$. Almost bent functions, quadratic functions and some monomials on $\bF_{2^m}$ were used in the first construction, and many families of binary linear codes with few weights were obtained in the literature. This paper studies some punctured codes of these binary codes. Several families of binary linear codes with few weights and new parameters are obtained in this paper. Several families of distance-optimal binary linear codes with new parameters are also produced in this paper., Comment: Boolean function, linear code, punctured code, distance-optimal code, weight distribution

The rich functionalities of transition-metal oxides and their interfaces bear an enormous technological potential. Its realization in practical devices requires, however, a significant improvement of yet relatively low electron mobility in oxide materials. Recently, a mobility boost of about 2 orders of magnitude has been demonstrated at the spinel-perovskite gamma-Al2O3/SrTiO3 interface compared to the paradigm perovskite-perovskite LaAlO3/SrTiO3 interface. We explore the fundamental physics behind this phenomenon from direct measurements of the momentum-resolved electronic structure of this interface using resonant soft-X-ray angle-resolved photoemission. We find an anomaly in orbital ordering of the mobile electrons in gamma-Al2O3/SrTiO3 which depopulates electron states in the top SrTiO3 layer. This rearrangement of the mobile electron system pushes the electron density away from the interface, which reduces its overlap with the interfacial defects and weakens the electron-phonon interaction, both effects contributing to the mobility boost. A crystal-field analysis shows that the band order alters owing to the symmetry breaking between the spinel gamma-Al2O3 and perovskite SrTiO3. Band-order engineering, exploiting the fundamental symmetry properties, emerges as another route to boost the performance of oxide devices.

Changwu Tan,1– 3,* Xiaoqiang Wang,4,* Yuchang Wang,1– 3 Chuansen Wang,1– 3 Zhi Tang,5 Zhiping Zhang,1– 3 Jingping Liu,1– 3 Gelei Xiao1– 3 1Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan 410008, People’s Republic of China; 2Diagnosis and Treatment Center for Hydrocephalus, Xiangya Hospital, Central South University, Changsha, Hunan 410008, People’s Republic of China; 3National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan 410008, People’s Republic of China; 4Pediatric Neurological Disease Center, Xinhua Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200092, People’s Republic of China; 5Department of Neurosurgery, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan 410013, People’s Republic of China*These authors contributed equally to this workCorrespondence: Gelei XiaoDepartment of Neurosurgery, Xiangya Hospital, Central South University, Changsha, Hunan 410008, People’s Republic of ChinaTel +8613707314060Email xiaogelei@csu.edu.cnAbstract: Idiopathic normal pressure hydrocephalus (iNPH) is a rare neurological disorder with no clear prevalence factors and is a significant danger to the elderly. The intracranial glymphatic system is the internal environment that maintains brain survival and metabolism, and thus fluid exchange changes in the glymphatic system under various pathological conditions can provide important insights into the pathogenesis and differential diagnosis of many neurodegenerative diseases such as iNPH. iNPH can be diagnosed using a combination of clinical symptoms, imaging findings and history, and cerebrospinal fluid biomarkers due to the glymphatic system disorder. However, only few researchers have linked the two. Shunt surger

Jian Zhang, 1 Hongyan Zhang, 2 Jianqi Jiang, 2 Nan Cui, 2 Xiao Xue, 2 Tianying Wang, 2 Xiaoqiang Wang, 3 Yunpeng He, 2 Dongkai Wang 2 1Department of Chinese Medicine Pharmacology, School of Traditional Chinese Pharmacy, Shenyang Pharmaceutical University, Shenyang 110016, People’s Republic of China; 2Department of Pharmaceutics, School of Pharmacy, Shenyang Pharmaceutical University, Shenyang 110016, People’s Republic of China; 3Department of Pharmaceutical Chemistry, School of Pharmaceutical Engineering, Shenyang Pharmaceutical University, Shenyang 110016, People’s Republic of ChinaCorrespondence: Dongkai WangDepartment of Pharmaceutics, School of Pharmacy, Shenyang Pharmaceutical University, Shenyang 110016, People’s Republic of ChinaTel +86 24-43520529Email wangycsyphu@126.comBackground: Carbon dots (CDs) have attracted extensive attention in recent years because of their high biocompatibility and unique optical property. But they could not be well applied in the drug delivery system to enable distribution in tumor sites with their low pH sensitivity. They are barriers for drug delivery. CDs as an imaging proper were conjugated with doxorubicin (DOX) lipid-coated calcium phosphate (LCP) nanoparticle, for a pH-sensitive nanocarrier and delivery of the antitumor drugs.Materials and Methods: CDs were prepared by one-step hydrothermal treatment of citric acid and ethylenediamine. The nanoparticles were simply prepared by using microemulsion technology to form calcium phosphate (CaP) core and further coated with cationic lipids.Results: The structure was characterized by FTIR, XRD and TEM. In vitro release study revealed that DOX-CDs@LCP was pH dependent. The cytotoxicity assay demonstrated that it exhibited enhanced efficiency compared to the control group (DOX-CDs), but weaker than free DOX. The cellular uptake revealed that these pH-sensitive nanoparticles could be taken up effectively and deliver D

Jian Zhang, 1 Hongyan Zhang, 2 Jianqi Jiang, 2 Nan Cui, 2 Xiao Xue, 2 Tianying Wang, 2 Xiaoqiang Wang, 3 Yunpeng He, 2 Dongkai Wang 2 1Department of Chinese Medicine Pharmacology, School of Traditional Chinese Pharmacy, Shenyang Pharmaceutical University, Shenyang 110016, People’s Republic of China; 2Department of Pharmaceutics, School of Pharmacy, Shenyang Pharmaceutical University, Shenyang 110016, People’s Republic of China; 3Department of Pharmaceutical Chemistry, School of Pharmaceutical Engineering, Shenyang Pharmaceutical University, Shenyang 110016, People’s Republic of ChinaCorrespondence: Dongkai WangDepartment of Pharmaceutics, School of Pharmacy, Shenyang Pharmaceutical University, Shenyang 110016, People’s Republic of ChinaTel +86 24-43520529Email wangycsyphu@126.comBackground: Carbon dots (CDs) have attracted extensive attention in recent years because of their high biocompatibility and unique optical property. But they could not be well applied in the drug delivery system to enable distribution in tumor sites with their low pH sensitivity. They are barriers for drug delivery. CDs as an imaging proper were conjugated with doxorubicin (DOX) lipid-coated calcium phosphate (LCP) nanoparticle, for a pH-sensitive nanocarrier and delivery of the antitumor drugs.Materials and Methods: CDs were prepared by one-step hydrothermal treatment of citric acid and ethylenediamine. The nanoparticles were simply prepared by using microemulsion technology to form calcium phosphate (CaP) core and further coated with cationic lipids.Results: The structure was characterized by FTIR, XRD and TEM. In vitro release study revealed that DOX-CDs@LCP was pH dependent. The cytotoxicity assay demonstrated that it exhibited enhanced efficiency compared to the control group (DOX-CDs), but weaker than free DOX. The cellular uptake revealed that these pH-sensitive nanoparticles could be taken up effectively and deliver D

Graph edit distance / similarity is widely used in many tasks, such as graph similarity search, binary function analysis, and graph clustering. However, computing the exact graph edit distance (GED) or maximum common subgraph (MCS) between two graphs is known to be NP-hard. In this paper, we propose the hierarchical graph matching network (HGMN), which learns to compute graph similarity from data. HGMN is motivated by the observation that two similar graphs should also be similar when they are compressed into more compact graphs. HGMN utilizes multiple stages of hierarchical clustering to organize a graph into successively more compact graphs. At each stage, the earth mover distance (EMD) is adopted to obtain a one-to-one mapping between the nodes in two graphs (on which graph similarity is to be computed), and a correlation matrix is also derived from the embeddings of the nodes in the two graphs. The correlation matrices from all stages are used as input for a convolutional neural network (CNN), which is trained to predict graph similarity by minimizing the mean squared error (MSE). Experimental evaluation on 4 datasets in different domains and 4 performance metrics shows that HGMN consistently outperforms existing baselines in the accuracy of graph similarity approximation.

Boolean functions have very nice applications in cryptography and coding theory, which have led to a lot of research focusing on their applications. The objective of this paper is to construct binary linear codes with few weights from the defining set, which is defined by some special Boolean functions and some additional restrictions. First, we provide two general constructions of binary linear codes with three or four weights from Boolean functions with at most three Walsh transform values and determine the parameters of their dual codes. Then many classes of binary linear codes with explicit weight enumerators are obtained. Some binary linear codes and their duals obtained are optimal or almost optimal. The binary linear codes obtained in this paper may have a special interest in secret sharing schemes, association schemes, strongly regular graphs.

Let $\mathbb{F}_{p^m}$ be a finite field with $p^m$ elements, where $p$ is an odd prime and $m$ is a positive integer. Recently, \cite{Hengar} and \cite{Wang2020} determined the weight distributions of subfield codes with the form $$\mathcal{C}_f=\left\{\left(\left( {\rm Tr}_1^m(a f(x)+bx)+c\right)_{x \in \mathbb{F}_{p^m}}, {\rm Tr}_1^m(a)\right)\, : \, a,b \in \mathbb{F}_{p^m}, c \in \mathbb{F}_p\right\}$$ for $f(x)=x^2$ and $f(x)=x^{p^k+1}$, respectively, where $k$ is a nonnegative integer. In this paper, we further investigate the subfield code $\mathcal{C}_f$ for $f(x)$ being a known perfect nonlinear function over $\mathbb{F}_{p^m}$ and generalize some results in \cite{Hengar,Wang2020}. The weight distributions of the constructed codes are determined by applying the theory of quadratic forms and the properties of perfect nonlinear functions over finite fields. In addition, the parameters of the duals of these codes are also determined. Several examples show that some of our codes and their duals have the best known parameters with respect to the code tables in \cite{MGrassl}. The duals of some proposed codes are optimal with respect to the Sphere Packing bound if $p\geq 5$., Comment: Subfield code, perfect nonlinear function, quadratic form, weight distribution, Sphere Packing bound. arXiv admin note: text overlap with arXiv:1910.05461

Angle-resolved photoemission spectroscopy, visualizing the superconducting gap in k-space, plays a pivotal role in research on cuprates and other high-Tc superconducting materials. However, there has always been an imminent doubt whether this technique truly represents the intrinsic bulk spectral function, whose response can be distorted by energy- and k-dependence of the photoexcitation matrix element, and by a small photoelectron escape depth of few surface atomic layers. Here, we address this fundamental question with soft-X-ray photoemission measurements of the superconducting gap in the paradigm high-Tc cuprate Bi2Sr2CaCu2O8. We vary the matrix element by spanning a dense k-space grid, formed by the lattice superstructure, and the probing depth by changing the emission angle. The measured gap appears independent of the matrix element effects, probing depth or photoexcitation energy. This fact proves the relevance of photoemission studies for the bulk superconductivity in Bi2Sr2CaCu2O8, and calls for similar verification experiments on other high-Tc compounds, in particular more three-dimensional ones. Bi2Sr2CaCu2O8 shows an anomalously fast decay of the coherent spectral weight with photon energy, tracing back to strong electron–phonon interaction or relaxation of the lattice coherence.

DNA nanostructures have been evolving ever since the development of self-assembling DNA tile-based structures in the 1980s. DNA origami technology developed by Rothemund in 2006 simplified the synthesis process of DNA nanostructures, while simultaneously upgrading the complexity, size, and the flexibility of these structures to a great extent. DNA nanostructures possess extraordinary features, such as controllable appearance, biocompatibility, and a capacity for diverse modifications, due to which they are considered an ideal tool for cancer diagnosis and treatment. The present review describes the classification of DNA nanostructures into three categories based on their structural features and construction methods, and summarizes their performance in cancer treatment. It was established that DNA nanostructures serve as reliable carriers of chemotherapy drugs and therapeutic genes, and exhibit great compatibility with inorganic materials such as gold nanoparticles. Cancer treatment using DNA nanostructures has presented positive results in vitro as well as in vivo, and studies exploring further comparisons among the different structures are expected in future research.