Chaotic Characteristics of Discrete-time Linear Inclusion Dynamical Systems

In this paper, we study the chaotic behavior of a discrete-time linear inclusion.Comment: 7 pages; submitte

A robust lower order mixed finite element method for a strain gradient elasticity model

A robust nonconforming mixed finite element method is developed for a strain gradient elasticity (SGE) model. In two and three dimensional cases, a lower order $C^0$-continuous $H^2$-nonconforming finite element is constructed for the displacement field through enriching the quadratic Lagrange element with bubble functions. This together with the linear Lagrange element is exploited to discretize a mixed formulation of the SGE model. The robust discrete inf-sup condition is established. The sharp and uniform error estimates with respect to both the small size parameter and the Lam\'{e} coefficient are achieved, which is also verified by numerical results. In addition, the uniform regularity of the SGE model is derived under two reasonable assumptions.Comment: 25 page

Memory efficient location recommendation through proximity-aware representation

Sequential location recommendation plays a huge role in modern life, which can enhance user experience, bring more profit to businesses and assist in government administration. Although methods for location recommendation have evolved significantly thanks to the development of recommendation systems, there is still limited utilization of geographic information, along with the ongoing challenge of addressing data sparsity. In response, we introduce a Proximity-aware based region representation for Sequential Recommendation (PASR for short), built upon the Self-Attention Network architecture. We tackle the sparsity issue through a novel loss function employing importance sampling, which emphasizes informative negative samples during optimization. Moreover, PASR enhances the integration of geographic information by employing a self-attention-based geography encoder to the hierarchical grid and proximity grid at each GPS point. To further leverage geographic information, we utilize the proximity-aware negative samplers to enhance the quality of negative samples. We conducted evaluations using three real-world Location-Based Social Networking (LBSN) datasets, demonstrating that PASR surpasses state-of-the-art sequential location recommendation method

Intelligent model for offshore China sea fog forecasting

Accurate and timely prediction of sea fog is very important for effectively managing maritime and coastal economic activities. Given the intricate nature and inherent variability of sea fog, traditional numerical and statistical forecasting methods are often proven inadequate. This study aims to develop an advanced sea fog forecasting method embedded in a numerical weather prediction model using the Yangtze River Estuary (YRE) coastal area as a case study. Prior to training our machine learning model, we employ a time-lagged correlation analysis technique to identify key predictors and decipher the underlying mechanisms driving sea fog occurrence. In addition, we implement ensemble learning and a focal loss function to address the issue of imbalanced data, thereby enhancing the predictive ability of our model. To verify the accuracy of our method, we evaluate its performance using a comprehensive dataset spanning one year, which encompasses both weather station observations and historical forecasts. Remarkably, our machine learning-based approach surpasses the predictive performance of two conventional methods, the weather research and forecasting nonhydrostatic mesoscale model (WRF-NMM) and the algorithm developed by the National Oceanic and Atmospheric Administration (NOAA) Forecast Systems Laboratory (FSL). Specifically, in regard to predicting sea fog with a visibility of less than or equal to 1 km with a lead time of 60 hours, our methodology achieves superior results by increasing the probability of detection (POD) while simultaneously reducing the false alarm ratio (FAR).Comment: 19 pages, 9 figure

Preconditioning optimization of hydraulic fracturing in block caving of hard rock mass

Introduction: Cavability issues often arise in hard rock mines employing the block caving mining method. Hydraulic fracturing stands out as a promising pre-conditioning technology for hard rock masses, with its pre-conditioning effects dependent on variable parameters.Methods: The impact of cluster number, injection rate, and liquid volume on fracture propagation was investigated through on-site hydraulic fracturing practices. Fracturability was initially verified via true triaxial fracturing tests, and preconditioning parameters were subsequently optimized using numerical simulations. The optimized on-site construction was monitored using electromagnetic methods.Results: The study revealed a negative correlation between fracture radius and the number of clusters, gradually decreasing with an increase in cluster number. However, the fracture weakening area increased with the rise in the number of clusters. The fracture weakening area also increased with the injection rate. Additionally, the fracture radius initially increased and then decreased. Both fracture weakening area and radius increased with an increase in liquid volume. The optimized parameters were identified as four clusters, an injection rate of 4 m3/min, and a liquid volume of 500 m3.Discussion: Building upon these findings, on-site experiments were conducted and monitored using electromagnetic methods. The monitored results demonstrated that the optimized parameters effectively achieved hydraulic fracturing expansion, accomplishing the goal of weakening hard rock

Hepatic epithelioid hemangioendothelioma—a single-institution experience with 51 cases

ObjectivesThe aim of the present study was to describe the experience at a single institution in the management of hepatic epithelioid hemangioendothelioma (HEHE).MethodsWe included 51 patients with histologically confirmed HEHE. We performed log-rank (Cox–Mantel) survival analyses using Kaplan–Meier methods to test differences in survival between patients in different groups. Univariate Cox regression analyses and multivariate proportional hazards regression model were carried out to identify independent prognostic factors.ResultsDifferent imaging modalities were used to diagnose HEHE with various presentations. Liver resection (LR), liver transplantation (LT), systemic treatment (ST), and surveillance had been used in our study. A significant difference was noted between the LR group and the surveillance group with respect to mean survival (p = 0.006), as was in the LR group and the ST group (p = 0.036), and in surgical approach (LR and LT) and nonsurgical approach (ST and surveillance) (p = 0.008). The mean survival between the ST group and the surveillance group was not significantly different (p = 0.851). LR (p = 0.010) and surgical approach (p = 0.014) were favorable predictors of outcome, while macrovascular invasion (MaVI) (p = 0.037), lung metastasis (p = 0.040), and surveillance (p = 0.033) were poor prognostic factors in univariate analysis. Multivariate analysis showed that LR (p = 0.010) and surgical approach (p = 0.014) were independently associated with good OS, while surveillance (p = 0.033) was independently associated with poor OS. After adjusting for confounding factors, patients in the LR group have much better OS than those in the surveillance group (p = 0.013). However, there was no significant difference in OS between the LR group and ST group (p = 0.254), as was in the ST group and the surveillance group (p = 0.857).ConclusionsThe definitive diagnosis of HEHE was dependent on histopathology, and it was not possible to make a specific diagnosis without biopsy because the radiological findings were similar to those in some hepatic malignancies. ST was not recommended for patients who were not candidates for surgical approaches, and surgical approaches should be warranted regardless of disease stage. The retrospective nature and the small size of the data limited the generalizability of the study, designing a worldwide database that contains all data about patients with HEHE independent of their therapy, which was highly recommended

Epidemiological characteristics and drug resistance analysis of Salmonella I4, [5], 12∶I∶-in Maoming City from 2017 to 2019

Objective To understand the epidemic characteristics and drug resistance of Salmonella I4, [5], 12∶I∶-in Maoming City. Methods Salmonella I4, [5], 12∶I∶-were identified by serological method, and then antibiotic sensitivity of isolated Salmonella I4, [5], 12∶I∶-was tested by broth microdilution method. Results Among 476 strains of Salmonella from patients’ feces, 143 strains of Salmonella I4, [5], 12∶I∶-were detected, and the detection rate was 33.81%. The feces of patients were mainly from infants <3 years old, the peak period mainly occurred from June to August. The rate of resistance to doxycycline was the highest (97.90%, 140/143), followed by tetracycline (95.10%, 136/143), sulfamethoxazole (93.71%, 134/143), ampicillin (90.91%, 130/143), streptomycin (86.71%, 124/143), minocycline (83.22%, 119/143), ampicillin/sulbactam (58.74%, 84/143), chloramphenicol (58.74%, 84/143) and sulfamethoxazole/trimethoprim (53.85%, 77/143). Amikacin and meropenem were the most sensitive antibiotics, and no drug-resistant strains were found, followed by polymyxin B (99.30%, 142/143), imipenem (99.30%, 142/143), cefoxitin (97.20%, 139/143), colistin (93.01%, 133/143), ceftazidime (92.31%, 132/143), azithromycin (92.31%, 132/143), cefotaxime (81.82%, 117/143), cefepime (79.72%, 114/143) and aztreonam (79.72%, 114/143). 97 kinds of drug resistance spectrum were identified, and the multi drug resistance rate was 100.00%. Conclusion Salmonella I4, [5], 12∶I∶-infection rate in infants is high, drug resistance is serious, and it is harmful to infants. It is necessary to expand the scope of sentinel hospitals and strengthen the surveillance of Salmonella, especially Salmonella I4, [5], 12∶I∶-. Salmonella I4, [5], 12∶I∶-was more sensitive to carbapenems and the second, third and fourth generation of cephalosporins which could be used as the first choice for treatment