333 research outputs found
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 of length , a letter-repeated subsequence is a
subsequence of in the form of with
a subsequence of , and for all in
and in . We first present an time algorithm to
compute the longest cubic subsequences of all the substrings of ,
improving the trivial bound. Then, an time algorithm for
computing the longest subsequence-repeated subsequence (LSRS) of is
obtained. Finally we focus on two variants of this problem. We first consider
the constrained version when is unbounded, each letter appears in
at most times and all the letters in must appear in the solution.
We show that the problem is NP-hard for , via a reduction from a special
version of SAT (which is obtained from 3-COLORING). We then show that when each
letter appears in at most times, then the problem is solvable in
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
JNK signaling mediates acute rejection via activating autophagy of CD8+ T cells after liver transplantation in rats
BackgroundAcute rejection (AR) after liver transplantation (LT) remains an important factor affecting the prognosis of patients. CD8+ T cells are considered to be important regulatory T lymphocytes involved in AR after LT. Our previous study confirmed that autophagy mediated AR by promoting activation and proliferation of CD8+ T cells. However, the underlying mechanisms regulating autophagy in CD8+ T cells during AR remain unclear.MethodsHuman liver biopsy specimens of AR after orthotopic LT were collected to assess the relationship between JNK and CD8+ T cells autophagy. The effect of JNK inhibition on CD8+ T cells autophagy and its role in AR were further examined in rats. Besides, the underlying mechanisms how JNK regulated the autophagy of CD8+ T cells were further explored.ResultsThe expression of JNK is positive correlated with the autophagy level of CD8+ T cells in AR patients. And similar findings were obtained in rats after LT. Further, JNK inhibitor remarkably inhibited the autophagy of CD8+ T cells in rat LT recipients. In addition, administration of JNK inhibitor significantly attenuated AR injury by promoting the apoptosis and downregulating the function of CD8+ T cells. Mechanistically, JNK may activate the autophagy of CD8+ T cells through upregulating BECN1 by inhibiting the formation of Bcl-2/BECN1 complex.ConclusionJNK signaling promoted CD8+ T cells autophagy to mediate AR after LT, providing a theoretical basis for finding new drug targets for the prevention and treatment of AR after LT
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
Mechanistic analysis of loess landslide reactivation in northern Shaanxi based on coupled numerical modeling of hydrological processes and stress strain evolution: A case study of the Erzhuangkelandslide in Yan’an
The Erzhuangke landslide is a typical landslide affected by the rainy season. Rainfall changes the seepage pattern with the pre-existing landslide, weakening matric suction and soil shear strength, leading to the formation of tension cracks internally. This triggers overall sliding and localized extensive deformations. Existing studies seldom considers the interaction between the seepage field and stress field of the Erzhuangke landslide. Therefore, based on the actual engineering geological disaster scenarios, supported by on-site monitoring data and terrain physical parameters, a geometric computational model is established, and hydraulic coupled numerical simulations are conducted. By investigating variations in saturation and pore pressure within the landslide, the paper explores the rainfall infiltration patterns. It examines the impact of rainfall intensity on landslide reactivation from the perspective of stress displacement. In addition, in order to validate the accuracy and feasibility of the method, selected measurement points from the landslide are matched with corresponding positions in the numerical model. Comparative analysis is performed on displacement, soil pressure, and saturation aspects, confirming that the numerical model effectively reflects the actual situation. Through coupling numerical simulations and the study of the reactivation mechanism of the old landslide under rainfall conditions, the paper interprets field data, analyzes the reactivation process, and provides theoretical foundations and technical guidance for subsequent engineering early warning and disaster mitigation works
The potential of a targeted unilateral compound training program to reduce lower limb strength asymmetry and increase performance: a proof-of-concept in basketball
ObjectiveThis study investigates the efficacy of training methodologies aimed at mitigating asymmetries in lower limb strength and explosiveness among basketball players.MethodsThirty male university basketball athletes were enrolled in this research. Initial assessments were made regarding their physical attributes, strength, and explosiveness. Subsequently, the participants were randomly allocated into two groups: an experimental group (EG, n = 15) and a control group (CG, n = 15). Over 10 weeks, the EG engaged in a unilateral compound training regimen, incorporating resistance training exercises such as split squats, Bulgarian split squats, box step-ups, and single-leg calf raises (non-dominant leg: three sets of six repetitions; dominant leg: one set of six repetitions) and plyometric drills including lunge jumps, single-leg hops with back foot raise, single-leg lateral jumps, and single-leg continuous hopping (non-dominant leg: three sets of 12 repetitions; dominant leg: one set of 12 repetitions). The CG continued with their standard training routine. Assessments of limb asymmetry and athletic performance were conducted before and after the intervention to evaluate changes.Results1) Body morphology assessments showed limb length and circumference discrepancies of less than 3Â cm. The initial average asymmetry percentages in the single-leg countermovement jump (SLCMJ) for jump height, power, and impulse were 15.56%, 12.4%, and 4.48%, respectively. 2) Post-intervention, the EG demonstrated a significant reduction in the asymmetry percentages of SLCMJ height and power (p < 0.01), along with improvements in the isometric mid-thigh pull (IMTP) test metrics (p < 0.05). 3) The EG also showed marked enhancements in the double-leg countermovement jump (CMJ) and standing long jump (SLJ) outcomes compared to the CG (p < 0.01), as well as in squat performance (p < 0.05).ConclusionThe 10-week unilateral compound training program effectively reduced the asymmetry in lower limb strength and explosiveness among elite male university basketball players, contributing to increased maximal strength and explosiveness
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
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