The Longest Subsequence-Repeated Subsequence Problem

Motivated by computing duplication patterns in sequences, a new fundamental problem called the longest subsequence-repeated subsequence (LSRS) is proposed. Given a sequence $S$ of length $n$, a letter-repeated subsequence is a subsequence of $S$ in the form of $x_1^{d_1}x_2^{d_2}\cdots x_k^{d_k}$ with $x_i$ a subsequence of $S$, $x_j\neq x_{j+1}$ and $d_i\geq 2$ for all $i$ in $[k]$ and $j$ in $[k-1]$. We first present an $O(n^6)$ time algorithm to compute the longest cubic subsequences of all the $O(n^2)$ substrings of $S$, improving the trivial $O(n^7)$ bound. Then, an $O(n^6)$ time algorithm for computing the longest subsequence-repeated subsequence (LSRS) of $S$ is obtained. Finally we focus on two variants of this problem. We first consider the constrained version when $\Sigma$ is unbounded, each letter appears in $S$ at most $d$ times and all the letters in $\Sigma$ must appear in the solution. We show that the problem is NP-hard for $d=4$, via a reduction from a special version of SAT (which is obtained from 3-COLORING). We then show that when each letter appears in $S$ at most $d=3$ times, then the problem is solvable in $O(n^5)$ time.Comment: 16 pages, 1 figur

Combining Karhunen–Loève expansion and stochastic modeling for probabilistic delineation of well capture zones in heterogeneous aquifers

The delineation of well capture zones (WCZs), particularly for water supply wells, is of utmost importance to ensure water quality. This task requires a comprehensive understanding of the aquifer’s hydrogeological parameters for precise delineation. However, the inherent uncertainty associated with these parameters poses a significant challenge. Traditional deterministic methods bear inherent risks, emphasizing the demand for more resilient and probabilistic techniques. This study introduces a novel approach that combines the Karhunen–Loève expansion (KLE) technique with stochastic modeling to probabilistically delineate well capture zones in heterogeneous aquifers. Through numerical examples involving moderate and strong heterogeneity, the effectiveness of KLE dimension reduction and the reliability of stochastic simulations are explored. The results show that increasing the number of KL-terms significantly improves the statistical attributes of the samples. When employing more KL-terms, the statistical properties of the hydraulic conductivity field outperform those of cases with fewer KL-terms. Notably, particularly in scenarios of strong heterogeneity, achieving a convergent probabilistic WCZs map requires a greater number of KL-terms and stochastic simulations compared to cases with moderate heterogeneity

Evaluation on the psychological adjustment and countermeasures of civil servants in public emergencies

Public health emergencies are inevitable major development crises, and there are almost no omens of any emergency. The current social development would inevitably affect the psychological situation of civil servants. Grass roots civil servants have a wider range of tasks, more difficult working conditions and a more difficult environment. Under the strong social pressure, civil servants would also have negative factors such as fear and negative attitude. The mental health of grass-roots civil servants depends not only on the image and efficiency of the government, but also on creating a harmonious atmosphere and the quality of economic development. Therefore, people must pay attention to the psychological health of civil servants. It is mainly through psychological intervention and psychological adjustment to improve mental health. By analyzing the psychological characteristics of civil servants under emergencies and under pressure, and according to the importance of their coping ability under emergencies, this paper conducted corresponding psychological adjustment and psychological intervention to ensure the psychological health of civil servants, improve their ability to deal with public emergencies, and enable them to use correct and positive psychology to deal with public emergencies. It can be seen from the firefly algorithm that the prediction error value of the comprehensive quality of civil servants was declining, while the evaluation effect of the comprehensive quality was rising. The average value of the prediction error value of the comprehensive quality was about 0.49, and the average value of the evaluation effect of the comprehensive quality was about 0.73. In the whole process, the prediction error value of comprehensive quality decreased by 0.37, and the evaluation effect of comprehensive quality increased by 0.33. The comprehensive psychological quality and psychological adjustment ability of civil servants after psychological intervention were better than those before psychological intervention. The comprehensive psychological quality of civil servants after psychological intervention was 8.56% higher than that before psychological intervention, and the psychological adjustment ability was 8.47% higher than that before psychological intervention

Treatment Experience of 16 Cases in Combined with Posterior Condylar Fractures Schatzker types II and III Tibial Plateau Fracture

Objective: Exploring the treatment of combined posterior lateral approach with open reduction and internal fixation for the treatment of combined fractures of the ankle on the treatment of tibial plateau fractures with Schatzker types II and III. Method: Between April 2012 and March 2015, 16 cases of Schatkzer types II and III tibial plateau fractures were treated with T or L type limited contact dynamic compression plate (LC-DCP). Results: All 16 cases were followed-up for 12 to 36 months, with an average of 18.3 months. According to the Merchant score, 10 cases were excellent, good in 4 cases, and in 2 cases, the excellent and good rating was 87.5%. Conclusion: After treatment, anatomical reduction and stability of the posterior condyle was emphasized, and there were early functional usage and recovery of the joint functions. At the same time, the external side of the incision can be used to restore the external and rear sides to avoid replacement of the body position and improve the operation efficiency

GDNet-EEG: An attention-aware deep neural network based on group depth-wise convolution for SSVEP stimulation frequency recognition

BackgroundSteady state visually evoked potentials (SSVEPs) based early glaucoma diagnosis requires effective data processing (e.g., deep learning) to provide accurate stimulation frequency recognition. Thus, we propose a group depth-wise convolutional neural network (GDNet-EEG), a novel electroencephalography (EEG)-oriented deep learning model tailored to learn regional characteristics and network characteristics of EEG-based brain activity to perform SSVEPs-based stimulation frequency recognition.MethodGroup depth-wise convolution is proposed to extract temporal and spectral features from the EEG signal of each brain region and represent regional characteristics as diverse as possible. Furthermore, EEG attention consisting of EEG channel-wise attention and specialized network-wise attention is designed to identify essential brain regions and form significant feature maps as specialized brain functional networks. Two publicly SSVEPs datasets (large-scale benchmark and BETA dataset) and their combined dataset are utilized to validate the classification performance of our model.ResultsBased on the input sample with a signal length of 1 s, the GDNet-EEG model achieves the average classification accuracies of 84.11, 85.93, and 93.35% on the benchmark, BETA, and combination datasets, respectively. Compared with the average classification accuracies achieved by comparison baselines, the average classification accuracies of the GDNet-EEG trained on a combination dataset increased from 1.96 to 18.2%.ConclusionOur approach can be potentially suitable for providing accurate SSVEP stimulation frequency recognition and being used in early glaucoma diagnosis

Research on Protection Scheme of DC Microgrid Integrated with Fault Current Limiting Control Technology

[Introduction] With the development of new loads, such as distributed power sources and electric vehicles, DC(Direct Current) microgrids have the advantages of fewer commutation links and lower system losses than AC(Alternating Current) microgrids, and have become the current research hotspot. Due to the small coverage of the DC microgrid and access to a large amount of distributed power sources, the fault current rises quickly with a large amplitude when inter-pole short-circuit fault occurs, making it difficult to achieve differential coordination with traditional overcurrent protection used in AC distribution networks and posing a great challenge to fault localization. [Method] Therefore, in response to the characteristics of fault current in DC microgrids, the method for designing overcurrent protection setting value based on the precise control value of fault current through the integration of current limiting and protection was proposed. Combined with the reasonable capacity design of each branch, it can easily achieve differential coordination and accurately locate faults. [Result] A corresponding DC microgrid model is built on the PSCAD/EMTDC simulation platform. The proposed protection scheme is simulated and verified, and the result shows that the scheme can correctly locate the fault point and quickly remove the fault. [Conclusion] The proposed protection scheme can ensure the selectivity of overcurrent, which verifies the rationality of the scheme

AB-SIFA: SIFA with Adjacent-Byte Model

Statistical Ineffective Fault Attack (SIFA) has been a threat for implementa-tions of symmetric cryptographic primitives. Unlike Differential Fault At-tacks (DFA) which takes both correct and faulty ciphertexts, SIFA can re-cover the secret key with only correct ciphertexts. The classic SIFA is only effective on fault models with non-uniform distribution of intermediate val-ue. In this paper, we present a new fault model named adjacent-byte model, which describes a non-uniform distribution of relationship between two bytes (i.e. exclusive-or). To the best of our knowledge, it is the first time that this fault model has been proposed. We also show that the adjacent-byte faults can be induced by different fault sources and easy to reproduce. Then a new SIFA attack method called AB-SIFA on symmetric cryptography is proposed. We demonstrate the effectiveness of this new attack by simulating the attack. Finally, our attacks are applied to a software implementations of AES-128 with redundant countermeasure and a hardware AES co-processor, utilizing voltage glitches and clock glitches

An overview of emergency communication networks

In recent years, major natural disasters and public safety accidents have frequently occurred worldwide. In order to deal with various disasters and accidents using rapidly deployable, reliable, efficient, and stable emergency communication networks, all countries in the world are strengthening and improving emergency communication network construction and related technology research. Motivated by these situations, in this paper, we provide a state-of-the-art survey of the current situation and development of emergency communication networks. In this detailed investigation, our primary focus is the extensive discussion of emergency communication network technology, including satellite networks, ad hoc networks, cellular networks, and wireless private networks. Then, we explore and analyze the networks currently applied in emergency rescue, such as the 370M narrowband private network, broadband cluster network, and 5G constellation plan. We propose a broadband-narrowband integrated emergency communication network to provide an effective solution for visual dispatch of emergency rescue services. The main findings derived from the comprehensive survey on the emergency communication network are then summarized, and possible research challenges are noted. Lastly, we complete this survey by shedding new light on future directions for the emergency communication network. In the future, the emergency network will develop in the direction of intelligence, integration, popularization, and lower cost, and space-air-ground-sea integrated networks. This survey provides a reference basis for the construction of networks to mitigate major natural disasters and public safety accidents

A Skin Lipidomics Study Reveals the Therapeutic Effects of Tanshinones in a Rat Model of Acne

Tanshinone (TAN), a class of bioactive components in traditional Chinese medicinal plant Salvia miltiorrhiza, has antibacterial and anti-inflammatory effects, can enhance blood circulation, remove blood stasis, and promote wound healing. For these reasons it has been developed as a drug to treat acne. The purpose of this study was to evaluate the therapeutic effects of TAN in rats with oleic acid-induced acne and to explore its possible mechanisms of action through the identification of potential lipid biomarkers. In this study, a rat model of acne was established by applying 0.5 ml of 80% oleic acid to rats’ back skin. The potential metabolites and targets involved in the anti-acne effects of TAN were predicted using lipidomics. The results indicate that TAN has therapeutic efficacy for acne, as supported by the results of the histological analyses and biochemical index assays for interleukin (IL)-8, IL-6, IL-β and tumor necrosis factor alpha. The orthogonal projection of latent structure discriminant analysis score was used to analyze the lipidomic profiles between control and acne rats. Ninety-six potential biomarkers were identified in the skin samples of the acne rats. These biomarkers were mainly related to glycerophospholipid and sphingolipid metabolism, and the regulation of their dysfunction is thought to be a possible therapeutic mechanism of action of TAN on acne