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Cardiovascular disease is still one of the leading causes of death in the world, and heart transplantation is the current major treatment for end-stage cardiovascular diseases. However, because of the shortage of heart donors, new sources of cardiac regenerative medicine are greatly needed. The prominent development of tissue engineering using bioactive materials has creatively laid a direct promising foundation. Whereas, how to precisely pattern a cardiac structure with complete biological function still requires technological breakthroughs. Recently, the emerging three-dimensional (3D) bioprinting technology for tissue engineering has shown great advantages in generating micro-scale cardiac tissues, which has established its impressive potential as a novel foundation for cardiovascular regeneration. Whether 3D bioprinted hearts can replace traditional heart transplantation as a novel strategy for treating cardiovascular diseases in the future is a frontier issue. In this review article, we emphasize the current knowledge and future perspectives regarding available bioinks, bioprinting strategies and the latest outcome progress in cardiac 3D bioprinting to move this promising medical approach towards potential clinical implementation., Graphical abstract Image 1, Highlights • The research progress of 3D bioprinting technology integrating biomaterials with heart cells is systematically reviewed. • The reproduction of both structure and contraction is an indispensable way for perfect heart repair and regeneration. • For the success of cardiac 3D bioprinting, the process flow of bioink should be standardized in an orderly manner. • 3D bioprinting technology is increasing the personalized utilization of biomaterials in cardiac repair and regeneration.

PurposeOur previous study showed that hepatic arterial infusion chemotherapy (HAIC) using oxaliplatin, fluorouracil, and leucovorin (FOLFOX) plus sorafenib provided a significant survival benefit over sorafenib for advanced hepatocellular carcinoma. However, it is unclear whether the survival benefit should be attributed to the synergism between HAIC and sorafenib or just HAIC alone. We aim to compare HAIC using FOLFOX plus sorafenib with HAIC alone in patients with advanced hepatocellular carcinoma.Materials and MethodsThis was a retrospective study including 225 eligible patients treated with HAIC using FOLFOX (HAIC alone group, n=126, oxaliplatin 85 mg/m², leucovorin 400 mg/m², fluorouracil bolus 400 mg/m² and 2400 mg/m² for 46 hours, every 3 weeks) alone or HAIC plus sorafenib (soraHAIC group, n=99, sorafenib 400 mg twice daily). Survival curves were calculated by the Kaplan-Meier method, and propensity-score matching was used to reduce bias.ResultsThe soraHAIC group showed a longer overall survival (12.9 [95% CI, 10.4-15.4] vs. 10.5 [95% CI, 9.5-11.5] months, HR=0.71 [95% CI, 0.53-0.96]; P=0.025), a better progression free survival (7.0 [95% CI, 5.3-8.8] vs. 5.3 [95% CI, 3.5-7.1] months, HR=0.76 [95% CI, 0.58-0.99]; P=0.046), and a higher disease control rate (RECIST 1.1: 74.8% vs. 61.1%, P=0.030) than the HAIC alone group. In multivariate analysis, soraHAIC was an independent favor factor for survival. In terms of the grade 3/4 adverse event, hand–foot skin reaction was more frequent in the soraHAIC group than the HAIC alone group. In the propensity-score matched cohorts (93 pairs), the overall survival, the progression free survival and disease control rates in the soraHAIC group were also better than those in the HAIC group (PConclusionHAIC plus sorafenib may improve overall survival and progression free survival compared with HAIC alone as initial treatment for advanced hepatocellular carcinoma.

The network language used in online chat has its commonness and characteristics. However, the level of word segmentation in the network text is not satisfactory, which puts forward a new topic for the current research on term extraction. This paper summarizes and analyzes the characteristics of the network text. Based on the conditional random field model and the combination of word tagging, the tagging set is improved, and the feature template suitable for the network text is adopted to improve the classification ability of the network text. We use the method of combining statistics and rules to recognize the Internet text named entity, normalize the text, and use CRF model to train and predict the text. Integrated with the matching rules, we modify the recognition results to achieve better results. The experimental results show that compared with the traditional text regularization and SVM classification methods, the performance of the proposed scheme is significantly improved.

This paper starts with the development status of offline literary works under the background of big data, and focuses on the online display and recommendation technology of contemporary British and American literary works, and designs and develops the design and application of its online display system. After acquiring the detailed requirement analysis, the software system is designed in detail. It adopts MVC framework and it is developed based on Java language and MYSQL. The system can provide work display, author management, work management, data management and other functional modules. It is transformed into the design and analysis of system operation process design, search engine design and data structure detailed design. Finally, according to the detailed design and implementation of the system business function verification and stress test, the effectiveness of the platform functions is proved.

BackgroundRASSF1A promoter methylation is consistent with clinicopathological data and has good accuracy in distinguishing tumors. However, the diagnostic parameters vary among previous studies. A systematic review was conducted to explore the diagnostic value of RASSF1A promoter methylation in prostate cancer.MethodsA comprehensive search of the literature in the PubMed, Medline, Cochrane Library, Embase and ISI Web of Science databases up to May 21, 2020 was performed. STATA software version 12.0 and Meta-disc version 1.4 were used to analyze the data.ResultsThe pooled sensitivity was 0.64 (95% CI 0.61–0.66), the pooled specificity was 0.80 (95% CI 0.77–0.83), the PLR was 3.82 (95% CI 1.96–7.44), and the NLR was 0.29 (95% CI 0.16–0.52). Furthermore, the pooled DOR of RASSF1A promoter methylation for prostate cancer was 13.08 (95% CI: 6.56–26.08). The area under the summary ROC curve was 0.87 (95% CI: 0.84–0.90). The results of the meta-regression suggested that heterogeneity was mainly derived from publication year. Fagan’s nomogram showed that the predictive accuracy was increased significantly by detecting RASSF1A promoter methylation for diagnosing prostate cancer.ConclusionThis meta-analysis suggests that detection of the RASSF1A promoter methylation status can be used for the diagnosis of PCa. In the future, further analyses and studies of larger sample sizes in large centers are needed to confirm our conclusion.

In order to use minimal cost to compensate signal distortion caused by fiber dispersion and carrier phase noise etc, this paper mainly puts forward 2 different self-adaption compensation algorithms in algorithm part of digital signal processing, through test and comparative analysis, it indicates that the performance of the best matching and the nature expression based on GCT is the best.

Along with the computer technology and the rapid development of communication network, wireless network sensor will be exploring new medical mode, a breakthrough in the medical field, the main monitoring and measuring the human body physiological parameters, for the human body can be all kinds of condition monitoring, data transfer to all kinds of communication terminal. Without having to leave home, monitoring their own physical condition anytime, anywhere and the test results, in the form of network transmission will be updated to medical personnel information database, doctors and patients are more closely connected on a timely base and effective communication and treatment can be easily carried out.

In the paper, an accurate and sensitive cavity attenuated phase shift spectroscopy (CAPS) sensor was used to monitor the atmospheric visibility. The CAPS system mainly includes a LED light source, a band-pass filter, an optical resonant cavity (composed of two high mirror, reflectivity is greater than 99.99%), a photoelectric detector and a lock-in amplifier. The 2L/min flow rate, the optical sensor rise and fall response time is about 15 s, so as to realize the fast measurement of visibility. An Allan variance analysis was carried out evaluating the optical system stability (and hence the maximum averaging time for the minimum detection limit) of the CAPS system. The minima (~0.1 Mm-1) in the Allan plots show the optimum average time (~100s) for optimum detection performance of the CAPS system. During this period, the extinction coefficient was correlated with PM2.5 mass (0.88), the extinction coefficient was correlated with PM10 mass (0.85). The atmospheric visibility was correlated with PM2.5 mass (0.74). The atmospheric visibility was correlated with PM10 mass (0.66).

The CAPS (Cavity Attenuated Phase shift Spectroscopy) system, which detects the extinction coefficients within a 10 nm bandpass centered at 532 nm, comprises a green LED with center wavelength in 532nm, a resonant optical cavity (36 cm length), a Photo Multiplier Tube detector, and a lock in amplifier. The square wave modulated light from the LED passes through the optical cavity and is detected as a distorted waveform which is characterized by a phase shift with respect to the initial modulation. Extinction coefficients are determined from changes in the phase shift of the distorted waveform of the square wave modulated LED light that is transmitted through the optical cavity. The performance of the CAPS system was evaluated by using measurements of the stability and response of the system. The minima (~0.1 Mm-1) in the Allan plots show the optimum average time (~100s) for optimum detection performance of the CAPS system. In the paper, it illustrates that extinction coefficient was correlated with PM2.5 mass (0.91). These figures indicate that this method has the potential to become one of the most sensitive on-line analytical techniques for extinction coefficient detection. This work aims to provide an initial validation of the CAPS extinction monitor in laboratory and field environments. Our initial results presented in this paper show that the CAPS extinction monitor is capable of providing state-of-the-art performance while dramatically reducing the complexity of optical instrumentation for directly measuring the extinction coefficients.

In the paper, an accurate and sensitive cavity attenuated phase shift spectroscopy (CAPS) system was used to monitor the atmospheric visibility coefficient in urban areas. The CAPS system, which detects the atmospheric visibility within a 10 nm bandpass centered at 532 nm, comprises a green LED with center wavelength in 532nm, a resonant optical cavity (36 cm length), a Photo Multiplier Tube detector and a lock in amplifier. The performance of the CAPS system was evaluated by measuring of the stability and response of the system. The minima (~0.06 Mm -1 ) in the Allan plots show the optimum average time(~80s) for optimum detection performance of the CAPS system. The 2L /min flow rate, the CAPS system rise and fall response time is about 15 s, so as to realize the fast measurement of visibility. By comparing the forward scatter visibility meter measurement results, the CAPS system measurement results are verified reliably, and have high precision measurement. These figures indicate that this method has the potential to become one of the most sensitive on-line analytical techniques for atmospheric visibility detection.

Tobacco smoking was one of the risk factors for upper aerodigestive tract cancer, but exclusive quantification of the impact of cigarette smoking on laryngeal cancer had not been investigated. A meta-analysis of researches that had reported quantitative estimates of cigarette smoking and risk of laryngeal cancer by March 2016 was performed. Pooled estimates of relative risks and their 95% confidence intervals were obtained and summarized. Sensitivity analysis and subgroup analysis were implemented to find out sources of research heterogeneity and the effect of potential confounders. Publication bias was investigated and corrected if found to be present through Egger’s and Begg’s test, and trim and fill algorithm. Thirty researches based on a total of 14,292 cases from three cohort and fifteen case–control studies were included and pooled estimate for the correlation between cigarette smoking and the risk of laryngeal cancer was 7.01 (95% confidence interval 5.56–8.85), with moderate heterogeneity across the researches (I 2 = 56.7%, p = 0.002). The RRs were 5.04 (95% CI 3.09–8.22) for cohort studies (p = 0.121), 7.59 (95% CI 5.86–9.82) for case–control studies (p = 0.005). The risk kept elevated within the first fifteen years of quitting smoking(RR 3.62, 95% CI 1.88–7.00) but dropped in the 16 years and more after smoking cessation(RR 1.88, 95% CI 1.16–3.05). Individuals who smoked with 40 or more pack-years had nine times the risk of laryngeal cancer(RR 9.14; 95% CI 6.24–13.39). Subjects who smoked 30 or more cigarettes a day had sevenfolds the risk of laryngeal cancer (RR 7.02; 95% CI 4.47–11.02) and who smoked 40 or more years had five times the risk versus never smokers (RR 5.76; 95% CI 3.69–8.99). Evidence of publication bias was not detected for the correlation between current cigarette smoking and risk of laryngeal cancer (p = 0.225 with Begg’s test, p = 0.317 with Egger’s test). The results demonstrated strong correlation referring to dose–response and time–response between cigarette smoking and risk of laryngeal cancer for both men and women. The probability of developing laryngeal cancer was decreased by quitting smoking, particularly among former cigarette smokers who had stopped smoking for 15 or more years. The subgroup analysis demonstrated that study type influenced the RRs estimates of the studies.

The first worldwide failure exercise (WWFE-I) indicated that the bridging micromechanics model exhibited a unique feature in calculating internal thermal stresses in the constituent fiber and resin materials of a laminated composite. Once applied to laminate strength prediction, however, the model only gave moderate correlation with the experiments. In this article, a material degradation scheme and a modified ultimate failure criterion for laminates are incorporated into the bridging model to improve its predictive capacity. Pure resin inter-layers are also introduced to simulate the effect of interfaces in between the lamina plies. With these modifications, much more accurate predictions have been obtained for the majority of the exercise problems, especially for the ultimate strengths and deformations of the multi-directional laminates. The correlation of the present theory predictions with the experiments is even better than that of any other theory predictions made in the exercise.

With the development of Web application, cross-site scripting attacks have been rapidly increasing, and the technique of those attacks is constantly updating. There has been some special advanced attacks such as the one based on encoding. In this paper we analyze two kinds of those attacks respectively based on the binary and N-ray alphabets encoding, then presents a dynamically access control method to prevent them by means of the existing detection and prevention technology of cross-site scripting attack, making up the existing approach being lack of the practicality, and the experimental results verify the feasibility and practicality of our protection mechanism.

Lacking information instruction, small and medium-sized enterprises in China, which organize as industry clusters, are suffering from high costs and production disorder. Meanwhile, equipped with informationized systems, third party logistics firms are urgently seeking new businesses to expand. Under such circumstances, we propose a 3PL-based synergy strategy model in order to satisfy the needs of the two sides. This paper outlines the structure of this model and gives a brief introduction of how this model can be implemented. Also, a preliminary MIS (Management Information System) based on SOA architecture using various information technologies is provided, which will meet the needs of the model's operation.

We performed a study to compare methods for volumetric breast density estimation in digital mammography (DM) and magnetic resonance imaging (MRI) for a high-risk population of women. DM and MRI images of the unaffected breast from 32 women with recently detected abnormalities and/or previously diagnosed breast cancer (age range 31-78 yrs, mean 50.3 yrs) were retrospectively analyzed. DM images were analyzed using QuantraTM (Hologic Inc). The MRI images were analyzed using a fuzzy-C-means segmentation algorithm on the T1 map. Both methods were compared to Cumulus (Univ. Toronto). Volumetric breast density estimates from DM and MRI are highly correlated (r=0.90, p≤0.001). The correlation between the volumetric and the area-based density measures is lower and depends on the training background of the Cumulus software user (r=0.73-84, p≤0.001). In terms of absolute values, MRI provides the lowest volumetric estimates (mean=14.63%), followed by the DM volumetric (mean=22.72%) and area-based measures (mean=29.35%). The MRI estimates of the fibroglandular volume are statistically significantly lower than the DM estimates for women with very low-density breasts (p≤0.001). We attribute these differences to potential partial volume effects in MRI and differences in the computational aspects of the image analysis methods in MRI and DM. The good correlation between the volumetric and the area-based measures, shown to correlate with breast cancer risk, suggests that both DM and MRI volumetric breast density measures can aid in breast cancer risk assessment. Further work is underway to fully-investigate the association between volumetric breast density measures and breast cancer risk.

The parenchyma tissue in the breast has a strong relation with predictive biomarkers of breast cancer. To better segment parenchyma, we perform segmentation on estimated tissue property T 1 map. To improve the estimation of tissue property (T 1 ) which is the basis for parenchyma segmentation, we present an integrated algorithm for simultaneous T 1 map estimation, T 1 map based parenchyma segmentation and group-wise registration on series of inversion recovery magnetic resonance (MR) breast images. The advantage of using this integrated algorithm is that the simultaneous T 1 map estimation (E-step) and group-wise registration (R-step) could benefit each other and jointly improve parenchyma segmentation. In particular, in E-step, T 1 map based segmentation could help perform an edge-preserving smoothing on the tentatively estimated noisy T 1 map, and could also help provide tissue probability maps to be robustly registered in R-step. Meanwhile, the improved estimation of T 1 map could help segment parenchyma in a more accurate way. In R-step, for robust registration, the group-wise registration is performed on the tissue probability maps produced in E-step, rather than the original inversion recovery MR images, since tissue probability maps are the intrinsic tissue property which is invariant to the use of different imaging parameters. The better alignment of images achieved in R-step can help improve T 1 map estimation and indirectly the T 1 map based parenchyma segmentation. By iteratively performing E-step and R-step, we can simultaneously obtain better results for T 1 map estimation,T 1 map based segmentation, group-wise registration, and finally parenchyma segmentation.

Breast density has been shown to be an independent risk factor for breast cancer. In order to segment breast parenchyma, which has been proposed as a biomarker of breast cancer risk, we present an integrated algorithm for simultaneous T1 map estimation and segmentation, using a series of magnetic resonance (MR) breast images. The advantage of using this algorithm is that the step of T1 map estimation (E-step) and the step of T1 map based tissue segmentation (S-step) can benefit each other. Since the estimated T1 map can be noisy due to the complexity of T1 estimation method, the tentative tissue segmentation results from S-step can help perform the edge-preserving smoothing on the estimated T1 map in E-step, thus removing noises and also preserving tissue boundaries. On the other hand, the improved estimation of T1 map from E-step can help segment breast tissues in a more accurate and less noisy way. Therefore, by repeating these steps, we can simultaneously obtain better results for both T1 map estimation and segmentation. Experimental results show the effectiveness of the proposed algorithm in breast tissue segmentation and parenchyma volume measurement

A sample-grating distributed Bragg reflector (SG-DBR) laser with 18 preprogrammed channels operating at 1540-1580 nm is characterized and compared for use as a source of tunable diode laser gas absorption spectroscopy. Two gases, CO and CO2, were targeted in this study by direct absorption spectroscopy and wavelength modulation spectroscopy with second-harmonic detection. In addition, the detectability of sample optical thickness is reported. Potential extensions of this research in the future are assessed using the SG-DBR diode laser as a source for tunable diode laser gas absorption spectroscopy.

Usually the quantum fluctuation characteristic of a non-degenerate optical parametric amplifier is analysed under the assumption of monochromatic pumping. However, in experiments, a driving beam with finite bandwidth is used to obtain the non-degenerate signal and idler beam amplifications. On account of that, we derive an analytical solution for the non-degenerate optical parametric amplification system with finite bandwidth laser pumping, and evaluate the associated quantum fluctuation. Finally, the application of the V1 criterion to bipartite entanglement is discussed.