Comparative Study on Theory Model and Test Result for Dilute sulfuric Acid to Erode Concrete

AbstractIn order to find the action mechanism for dilute sulfuric acid to erode concrete, immersion test has been carried out to concrete samples for a long time. Under the premise that PH value of immersion solution is kept constant basically, acid-consuming speed of concrete sample is determined according to titer, and according to assumption of reaction boundary layer and dynamic model of chemical reaction, the theory formula that acid-consuming speed changes with time is deduced, and the action rule for sulfuric acid to erode concrete is obtained finally: course of test sample that acid-consuming speed changes with time can be divided into two phases, respectively quick erosion and stable erosion. According to analysis of immersion test data, test result and theory model are of high degree of fitting, and theory model is correct

The efficacy of upfront craniocerebral radiotherapy and epidermal growth factor receptor-tyrosine kinase inhibitors in patients with epidermal growth factor receptor-positive non-small cell lung cancer with brain metastases

The present study aims to investigate the therapeutic value of third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) combined with cranial radiotherapy (RT) in patients with EGFR-positive non-small cell lung cancer (NSCLC) and brain metastases (BMs).MethodologyThis is a retrospective study that involved 213 patients with EGFR-NSCLC and BMs, with the patients divided into two groups: the upfront cranial RT (ucRT) group (n = 96) and the non-ucRT group (n = 117). All patients were administered with osimertinib, and those in the ucRT group also underwent RT. The overall survival (OS), progression-free survival (PFS) and intracranial PFS (IPFS) of the two groups were compared.ResultsThe ucRT group manifested a markedly higher IPFS than the non-ucRT group (29.65 months vs 21.8 months; P < 0.0001). The subgroup analysis revealed that patients with oligometastases (OLOGO-BMs; 1–3 BMs) demonstrated a notably longer OS (44.5 months vs 37.3 months; P < 0.0001), PFS (32.3 months vs 20.8 months; P = 0.6884) and IPFS (37.8 months vs 22.1 months; P < 0.0001) in the ucRT group than in the non-ucRT group. However, for patients with multiple BMs, there was no significant difference in OS (27.3 months vs 34.4 months; P = 0.0710) and PFS (13.7 months vs 13.2 months; P = 0.0516) between the ucRT group and the non-ucRT group; the ucRT group exhibited a higher IPFS (26.4 months vs 21.35 months; P = 0.0028). Cox’s multivariate analysis of patients with OLOGO-BM indicated that the use of ucRT was linked to a better OS (heart rate [HR] = 0.392; 95% confidence interval [CI]: 0.178–0.863; P = 0.020) and PFS (HR = 0.558; 95% CI: 0.316–0.986; P = 0.044).ConclusionUpfront cerebral cranial stereotactic radiosurgery can improve outcomes in EGFR-positive patients with NSCLC and OLOGO-BM. However, for patients with multiple BMs, the preferable strategy may be pre-treatment with EGFR-TKIs

Simulation Analysis of Mass Concrete Temperature Field

AbstractThe cracking phenomenon of mass concrete in the foundation mat of high-rise building is a key issue concerned by the engineering. The temperature control of mass concrete has great significance in assuring the project quality. At present, the temperature control in engineering practice is mostly limited to the temperature monitor. In this paper, MIDAS finite element analytical software was used to simulate the temperature field of mass concrete in a certain high-rise building foundation, the change rules of temperature and temperature stress with the time was calculated and analyzed by finite element analysis; at the same time, simulation result was verified by the temperature measurement data. It concludes that key to temperature control of mass concrete lies in the dual control of temperature and temperature stress. The simulation analysis of finite element procedure is feasible as an auxiliary method of temperature control and management

Hierarchical Modulation with Vector Rotation for E-MBMS Transmission in LTE Systems

Enhanced Multimedia Broadcast and Multicast Service (E-MBMS) is considered of key importance for the proliferation of Long-Term Evolution (LTE) network in mobile market. Hierarchical modulation (HM), which involves a “base-layer” (BL) and an “enhancement-layer” (EL) bit streams, is a simple technique for achieving tradeoff between service quality and radio coverage. Therefore, it is appealing for MBMS. Generally, HM suffers from the severe performance degradation of the less protected EL stream. In this paper, HM with vector rotation operation introduced to EL stream is proposed, in order to improve EL's performance. With the proper interleaving in frequency domain, this operation can exploit the inherent diversity gain from the multipath channel. In this way, HM with vector rotation can effectively enhance multimedia broadcasting on quality video and coverage. The simulation results with scalable video coding (SVC) as source show the significant benefits in comparison with the conventional HM and alternative schemes

Constructing the Web of Events from Raw Data in the Web of Things

An exciting paradise of data is emerging into our daily life along with the development of the Web of Things. Nowadays, volumes of heterogeneous raw data are continuously generated and captured by trillions of smart devices like sensors, smart controls, readers and other monitoring devices, while various events occur in the physical world. It is hard for users including people and smart things to master valuable information hidden in the massive data, which is more useful and understandable than raw data for users to get the crucial points for problems-solving. Thus, how to automatically and actively extract the knowledge of events and their internal links from the big data is one key challenge for the future Web of Things. This paper proposes an effective approach to extract events and their internal links from large scale data leveraging predefined event schemas in the Web of Things, which starts with grasping the critical data for useful events by filtering data with well-defined event types in the schema. A case study in the context of smart campus is presented to show the application of proposed approach for the extraction of events and their internal semantic links

Investigation on Roles of Packing Density and Water Film Thickness in Synergistic Effects of Slag and Silica Fume

The ternary blended cement with finer slag and silica fume (SF) could improve the packing density (PD) through the filling effect. The excess water (water more than needed for filling into voids between the cement particles) can be released to improve the fresh properties and densify the microstructure which is beneficial for improving the hardened properties. To verify the hypothesis and reveal how and why (cement + slag + SF) the ternary blends could bring such advantages, the binder pastes incorporating slag and SF with various water-to-binder ratios were produced to determine the PD experimentally. To evaluate the optimum water demand (OWD) for maximum wet density, the influence of the dispersion state of the binder on PD was investigated using the wet packing density approach. The effect of PD of various binary and ternary binder systems on water film thickness (WFT), fluidity, setting time, and compressive strength development of cement paste was also investigated. The results show that the ternary blends could improve the PD and decrease the water film thickness (WFT). The enhanced PD and altered WFT are able to increase fluidity and compressive strength. The ternary blends could improve the compressive strengths by increasing PD and exerting nucleation and pozzolanic effects

Ensemble Self-Paced Learning Based on Adaptive Mixture Weighting

Self-paced learning (SPL) is a learning mechanism inspired by human and animal learning processes that gives variable weights to samples, gradually introducing simple to more complicated samples into the learning set as the “age” parameter increases. To regulate the learning process, a self-paced weighting regularization term with an “age” parameter is introduced to the learning function. Several self-paced weighting methods have been proposed, and different regularization terms might result in varied learning performance. However, on the one hand, it is difficult to select a suitable weighting method for SPL. On the other hand, it is challenging to determine the “age” parameter, and it is easy for SPL to obtain poor results as the “age” of the model increases. To solve the aforementioned difficulties, an ensemble SPL approach with an adaptive mixture weighting mechanism is proposed in this study. First, as the “age” parameter increases, a set of base classifiers is collected to produce a new data set, which is used to learn the second-level classifier. Then, the ensemble model is used to generate the final output to avoid the selection of the optimal “age” parameter. An adaptive mixture weighting method is designed to reduce the dependence of parameters on human experience. The previous methods find it difficult to determine the “age” parameters or self-paced parameters. In this paper, these parameters can be adjusted adaptively during the learning process. In comparison with the previous SPL techniques, the proposed method achieves the best results in 27 of the 32 datasets in the experiments with the adaptive parameters. The statistical tests are carried out to show that the proposed method is superior to other state-of-the-art algorithms