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For disposal of scrap tyres, there have been a lot of studies done by previous researchers, but it yet remains a longstanding challenge in practice. To find a solution for this problem, the feasibility of a proposed approach in a laboratory scale was tested. The pyrolysis of scrap tyres pretreated by waste coal tar (noted as “as-pretreated” tyres) was performed in a batch reactor at atmospheric pressure. Waste coal tar was used to modify the scrap tyres to improve the pyrolysis efficiency of scrap tyres input and the quality of the product tar. The swelling behavior of scrap tyres soaked in waste coal tar at 10 °C, effect of pyrolysis temperature on the product yields, and the synergies during pyrolysis of the as-pretreated tyres and co-pyrolysis of scrap tyres/waste coal tar mixture were all investigated in detail. The results observed found that by comparison of the calculated yields and the observed experimental yields for pyrolysis products, the synergy from co-pyrolysis of scrap tyres/waste coal tar mixture boosted the gas yield without increasing the tar yield. In contrast, the synergy during pyrolysis of the as-pretreated tyres could enhance the tar yield, but reduced the gas and char yields. According to the distillation range analyses of the tar, more light fractions were found in the tar from pyrolysis of the as-pretreated tyres, in which the gasoline fraction, diesel fraction and kerosene fraction were 38.4 wt%, 46.8 wt% and 50.2 wt%, respectively. This work is expected to be helpful in further use of scrap tyres. Keywords: Scrap tyres, Waste coal tar, Pyrolysis, Synergy, Distillation range analyses

Pancreatic cancer is a severe disease that threatens human health. The hypoxic tumor microenvironment in pancreatic cancer leads to resistance to conventional therapies and helps to maintain tumor malignancy. First-line drugs present the disadvantage of systemic side effects, and a synergistic method with sonodynamic therapy (SDT) has been established as an emerging approach. In this study, we produced hypoxia-alleviating nanoplatforms (denoted as PZGI NPs) with zeolitic imidazolate frameworks-90 (ZIF-90) nanoparticles nucleating on platinum (Pt) nanoparticles and co-loaded with gemcitabine and IR780. This platform can catalyze peroxide to oxygen with loaded Pt nanoparticles to alleviate tumor hypoxia. Moreover, the loaded drugs could be quickly released in the lysosome microenvironment, which has a low pH value and high ATP level microenvironment in the mitochondria. This strategy could enhance the sensitivity of cancer cells to chemotherapy. Further, under ultrasound exposure, it could transfer the produced oxygen into a highly cytotoxic singlet oxygen for the augmented sonodynamic effect. Therefore, this multifunctional hypoxia-alleviating nanoplatform offers a promising strategy for chemo-sonodynamic therapy against pancreatic cancer.

Traditional audit data analysis algorithms have many shortcomings, such as the lack of means to mine the hidden audit clues behind the data, the difficulty of finding increasingly hidden cheating techniques caused by the electronic and networked environment, and the inability to solve the quality defects of the audited data. Correlation analysis algorithm in data mining technology is an effective means to obtain knowledge from massive data, which can complete, muffle, clean, and reduce defective data and then can analyze massive data and obtain audit trails under the guidance of expert experience or analysts. Therefore, on the basis of summarizing and analyzing previous research works, this paper expounds the research status and significance of audit data analysis and application; elaborates the development background, current status, and future challenges of correlation analysis algorithm; introduces the methods and principles of data model and its conversion and audit model construction; conducts audit data collection and cleaning; implements audit data preprocessing and its algorithm description; performs audit data analysis based on correlation analysis algorithm; analyzes the hidden node activation value and audit rule extraction in correlation analysis algorithm; proposes the application of audit data based on correlation analysis algorithm; discusses the relationship between audit data quality and audit risk; and finally compares different data mining algorithms in audit data analysis. The findings demonstrate that by analyzing association rules, the correlation analysis algorithm can determine the significance of a huge quantity of audit data and characterise the degree to which linked events would occur concurrently or sequentially in a probabilistic manner. The correlation analysis algorithm first inputs the collected audit data through preprocessing module to filter out useless data and then organizes the obtained data into a format that can be recognized by data mining algorithm and executes the correlation analysis algorithm on the sorted data; finally, the obtained hidden data is divided into normal data and suspicious data by comparing it with the pattern in the rule base. The algorithm can conduct in-depth analysis and research on the company’s accounting vouchers, account books, and a large number of financial accounting data and other data of various natures in the company’s accounting vouchers; reveal its original characteristics and internal connections; and turn it into an audit. People need more direct and useful information. The study results of this paper provide a reference for further researches on audit data analysis and application based on correlation analysis algorithm.

We present a series of programming assignments, adaptable to a range of experience levels from advanced undergraduate to PhD, to teach students design and implementation of modern NLP systems. These assignments build from the ground up and emphasize full-stack understanding of machine learning models: initially, students implement inference and gradient computation by hand, then use PyTorch to build nearly state-of-the-art neural networks using current best practices. Topics are chosen to cover a wide range of modeling and inference techniques that one might encounter, ranging from linear models suitable for industry applications to state-of-the-art deep learning models used in NLP research. The assignments are customizable, with constrained options to guide less experienced students or open-ended options giving advanced students freedom to explore. All of them can be deployed in a fully autogradable fashion, and have collectively been tested on over 300 students across several semesters.

A portion of detected breast masses might be overrated by using the Breast Imaging-Reporting and Data System ultrasonography (BI-RADS US) lexicon. A principal component regression-based contrast-enhanced ultrasound (PCR-CEUS) evaluation system was built to quantitatively illustrate whether CEUS could help radiologists to differentiate 4A masses. The PCR-CEUS evaluation system, based on principal component analysis (PCA) and logistic regression, was verified by random assignment into training and test sets and shown to reduce the data dimension and avoid collinearity in CEUS variables. This prospective study consecutively collected 238 patients with 238 4A masses confirmed pathologically. All enrolled patients accepted CEUS examination. The diagnostic performance of senior and junior radiologists, PCR-CEUS and combined methods was compared. The PCR-CEUS system had consistent diagnostic performance in both the training and test sets, with an area under the curve (AUC) of 0.831 (0.765-0.897), 0.798 (0.7034-0.892) and 0.854 (0.765-0.943) (all P0.05). The AUC of the combined diagnostic model (PCR-CEUS + Senior radiologists) was higher than that of senior radiologists, and the combined model had higher sensitivity (0.875 (0.781-0.969) vs. 0.729 (0.603-0.855)) without compromising specificity. Furthermore, the AUC and specificity of the combined model (PCR-CEUS + Junior radiologists) (0.852 (0.787-0.916)) was higher than that of junior radiologists (0.665 (0.592-0.737) (P0.00001)). PCR-CEUS demonstrated good ability in differentiating malignant BI-RADS-US 4A masses and was helpful for both senior and junior radiologists.

The aim of this study was to identify the potential and mechanisms of microbubble-mediated cavitation in promoting apoptosis and suppressing invasion in cancer cells. AsPC-1 cells were used and divided into four groups: control group, microbubble-only (MB) group, ultrasound-only (US) group and ultrasound plus microbubble (US + MB) group. Pulse ultrasound was used at a frequency of 360 kHz and a SPPA (spatial peak, pulse average) intensity of 1.4 W/cm2 for 1 min (duty rate = 50%). Then cells in the four groups were cultured for 24 h. Cell Counting Kit‑8 (Biosharp, Hefei, Anhui, China) revealed decreased cell viability in the US + MB group. Western blot confirmed that there were increased cleaved caspase‑3 and Bcl-2-associated X protein levels and decreased B‑cell lymphoma‑2 (Bcl-2) levels, as well as increased intracellular calcium ions and downregulated cleaved caspase-8, in the US + MB group. With respect to proliferation, cells in the US + MB group had lower expression of Ki67 and the weakened colony formation ability. The transwell invasion assay revealed that invasion ability could be decreased in AsPC-1 cells in the US + MB group. Further, it was found that cells in the US + MB group had lower levels of hypoxia-inducible factor-1α (HIF-1α) and vimentin and higher levels of E-cadherin compared with the other three groups. Finally, the US + MB cells had less invadopodium formation. In conclusion, these results suggest that microbubble-mediated cavitation promotes apoptosis and suppresses invasion in AsPC-1 cells.

This study aimed to identify the potential and mechanisms of microbubble-mediated cavitation in promoting apoptosis and suppressing invasion in cancer cells. AsPC-1 cells were used and divided into four groups: control group, microbubble-only (MB) group, ultrasound-only (US) group, and ultrasound combined with microbubbles (US+MB) group. Pulse ultrasound was used with a frequency of 360 kHz and an intensity of 0.7 W/cm2 for 1 min (duty rate=50%). Then cells in four groups were cultured for 24 h. Cell counting kit‑8 illustrated that US+MB could decrease cell viability. Western blot confirmed that US+MB increased cleaved Caspase‑3, Bcl-2-associated X protein (BAX), and decreased the B‑cell lymphoma‑2 (Bcl-2) levels. Besides, US+MB increased intracellular calcium ions and down-regulated cleaved Caspase-8. For proliferation ability, cells in US+MB group had a lower expression of Ki67 and the weakened colony formation ability. The transwell invasion assay showed that US+MB could decrease invasion ability in AsPC-1 cells. Further evidence showed that cells conducted with US+MB had the lower level of hypoxia-inducible factor-1α (HIF-1α) and Vimentin and the higher expression of E-cadherin than the other three groups. Finally, cells conducted with US+MB had less invadopodia formation. In conclusion, these results suggested that microbubble-mediated cavitation promoted apoptosis and suppressed invasion in AsPC-1 cells.SignificanceCancer cells have a high rate of cell division and a high rate of cell division can speed up the development of hypoxia which lead to promote cancer invasion and metastasis. Here we used microbubble-mediated cavitation to generate a mechanical shock wave which could effectively kill cancer cells through physical damage and intrinsic signaling pathway. Furthermore, effective killing of cancer cells could restrain the development of hypoxia and prevent invasion ability of cancer cells.

Tumor drug resistance (TDR) invariably leads to the failure of chemotherapy. In addition, current treatment strategies for TDR are not satisfactory due to limitations in terms of safety and feasibility. The aim of the present study was to determine whether low-intensity low-frequency ultrasound (LILFU) could improve the effect of chemotherapy and reverse TDR in gemcitabine-resistant ASPC-1 (ASPC-1/GEM) cells. The investigation focused on the association between LILFU effectiveness and the adenosine triphosphate-binding cassette (ABC) transporters and the phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT)/nuclear factor (NF)-κB signaling pathway. A Cell Counting Kit-8 assay was used to determine the appropriate acoustic intensity, half-maximal inhibitory concentration of gemcitabine (GEM) and the viability of ASPC-1/GEM cells. ASPC-1/GEM cells were divided into control, GEM, LILFU and GEM+LILFU groups. Cell proliferation was evaluated through colony formation assays, whereas cell apoptosis was detected using flow cytometry. Western blotting was used to explore the expression levels of ABC transporters and PI3K/AKT/NF-κB signaling pathway-associated proteins. Xenograft models in mice were established to identify the enhancing effect of GEM+LILFU in vivo. Immunohistochemistry was used to detect the expression levels of Ki-67 in tumor tissues. The acoustic parameter of 0.2 W/cm2 and a GEM concentration of 6.63 mg/ml were used in subsequent experiments. Following treatment with GEM+LILFU, the cell viability and proliferation ability were decreased, whereas the apoptotic rate was increased compared with the GEM group. The expression levels of ABC transporters, PI3K-P110α and NF-κB were decreased in the GEM+LILFU group. Notably, LILFU increased the effectiveness of GEM in inhibiting tumor growth, and reduced the expression levels of Ki-67 in the xenograft mouse model. LILFU improved the chemosensitivity of ASPC-1/GEM cells via inhibition of cell viability and proliferation, and promoted cell apoptosis in the GEM+LILFU group. In conclusion, LILFU may downregulate the expression levels of ABC transporters by inhibiting the PI3K-p110α/AKT/NF-κB signaling pathway, thereby reversing resistance in pancreatic cancer.

Objectives Portal vein thrombosis (PVT) is a common complication of liver cirrhosis. However, differentiation of thrombosis and tumor-in-vein (TIV) may be challenging. Contrast-enhanced ultrasound (CEUS) is an excellent method for detection of vascularization and could help in the distinction. We performed a systematic review and meta-analysis for evaluating the diagnostic value of CEUS in differentiating between PVT and TIV in hepatocellular carcinoma (HCC) patients. Methods PubMed, Embase, Cochrane Library, and Web of Science were searched up to the 5th of May 2019. The study quality was assessed by QUADAS-2 tool. Pooled sensitivity and specificity were calculated by the bivariate random effect model and hierarchical summary receiver-operating characteristic (SROC) curve was plotted. Results Seven studies including 425 participants were analyzed after screening 986 articles searched from databases. The pooled sensitivity and specificity of CEUS in diagnosing TIV were 0.94 (95%CI, 0.89–0.97) and 0.99 (95%CI, 0.80–1.00), respectively. The area under the curve (AUC) of SROC curve was 0.97 (95%CI, 0.95–0.98). The pooled sensitivity and AUC were consistent across all the subgroups of different subject numbers, country, study design, CEUS contrast agents, and diagnostic criteria. Conclusions CEUS is highly efficient in differentiating TIV from PVT and is an alternative or a substitute for CT and/or MRI. Trial registration PROSPERO registration number: CRD42019138847 Key Points • Characterization of portal vein thrombosis (PVT) vs tumor-in-vein (TIV) is critical for HCC staging. • CEUS has an excellent safety profile, provides a real-time analysis without any loss in accuracy compared with CT and MRI. • This meta-analysis demonstrates that contrast-enhanced ultrasound (CEUS) is a suitable method for the detection of PVT and distinction with TIV.

BACKGROUND Several studies demonstrated that bilirubin, a potent endogenous antioxidant, is a strong protective factor for many diabetic complications such as nephropathy, retinopathy, neuropathy, and vasculopathy. The purpose of this study was to assess the association between serum bilirubin levels and diabetic foot (DF) in Chinese patients with type 2 diabetes mellitus (T2DM). MATERIAL AND METHODS The present cross-sectional study of bilirubin levels in relation to DF was conducted in 1,269 T2DM patients with (n=578) and without (n=691) DF. Blood test results were obtained on hospital admission, including total bilirubin (T-BIL), direct bilirubin (D-BIL), and indirect bilirubin (I-BIL). Data on Wagner classification and amputation procedure in patients with DF were collected by reviewing electronic medical records. Univariate or multivariate analysis were performed to explore the association between bilirubin and DF. RESULTS Serum I-BIL levels were shown to play a protective role regarding the presence and severity of DF (OR=0.75, p=0.029 and OR=0.90, p=0.021, respectively). In addition, in a comparison of the lowest and highest tertiles of serum bilirubin concentration, the highest tertile of serum T-BIL (OR=0.51, p=0.011) and I-BIL (OR=0.28, p

In this paper, analytical stress intensity factor solutions for similar and dissimilar spot welds in lap-shear specimens under pinned and clamped loading conditions are derived. Closed-form solutions for similar welds in lap-shear specimens of equal thickness under pinned and clamped loading conditions are derived to show explicitly the effects of the clamped edges on the stress intensity factor solutions. Finite element analyses are also employed to obtain the stress intensity factor solutions for similar and dissimilar spot welds in lap-shear specimens under pinned and clamped loading conditions. Both computational and analytical solutions indicate that the clamped loading reduces the stress intensity factor solutions for the given specimen geometries by up to 7% for similar welds and by about 20% for dissimilar magnesium/steel welds.

Learning multi-hop reasoning has been a key challenge for reading comprehension models, leading to the design of datasets that explicitly focus on it. Ideally, a model should not be able to perform well on a multi-hop question answering task without doing multi-hop reasoning. In this paper, we investigate two recently proposed datasets, WikiHop and HotpotQA. First, we explore sentence-factored models for these tasks; by design, these models cannot do multi-hop reasoning, but they are still able to solve a large number of examples in both datasets. Furthermore, we find spurious correlations in the unmasked version of WikiHop, which make it easy to achieve high performance considering only the questions and answers. Finally, we investigate one key difference between these datasets, namely span-based vs. multiple-choice formulations of the QA task. Multiple-choice versions of both datasets can be easily gamed, and two models we examine only marginally exceed a baseline in this setting. Overall, while these datasets are useful testbeds, high-performing models may not be learning as much multi-hop reasoning as previously thought., Comment: NAACL 2019

The problem of representing large-scale networks with low-dimensional vectors has received considerable attention in recent years. Except the networks that include only vertices and edges, a variety of networks contain information about groups or communities. For example, on Facebook, in addition to users and the follower-followee relations between them, users can also create and join groups. However, previous studies have rarely utilized this valuable information to generate embeddings of vertices. In this paper, we investigate a novel method for learning the network embeddings with valuable group information for large-scale networks. The proposed methods take both the inner structures of the groups and the information across groups into consideration. Experimental results demonstrate that the embeddings generated by the proposed methods significantly outperform state-of-the-art network embedding methods on two different scale real-world network

In this paper, the design, analysis and fabrication of a quadruped wall-climbing robot is presented. Inspired by the climbing gaits of geckos, the robot has kinematics similar to a gecko's motion. Unlike geckos stick on the wall surface with Van del Waals force, the robot is based on electrostatic adhesion force induced by a specifically designed electrostatic adhesive footpad. By combining the bionic gait design of the gecko and the unique properties of electrostatic adhesion mechanism, the robot has advantages of light weight, low energy consumption, flexible movement and high adaptability to different wall surfaces. Climbing experiments on the surface of a high-rise glass window are demonstrated, and the robot can achieve straight climbing and turning robustly and agilely. The potential applications of this robot are reconnaissance, inspection, cleaning and repairing.

Objective: To study the effect of Tongbiling (TBL) on the proliferation of synovial fibroblast and interleukin-1 (IL-1), tumor necrosis factor-α (TNF-α) and prostaglandin E2(PGE2) secreted by synoviocytes in adjuvant arthritis (AA) rats.Methods: Synovial fibroblast was derived from culture of tissue piece. The effect of primary synoviocyte culture supernatants on the fibroblast proliferation were assayed and IL-1, TNF-α bioactivity and PGE2 content of supernatants of cultured synoviocytes were measured.Results: TBL could significantly inhibit the synovial fibroblast proliferation (P < 0.001), and down-regulate IL-1, TNF-α and PGE2 productions (P < 0. 001); indomethacin could obviously promote the synovial fibroblast proliferation (P < 0.001). It significantly inhibited PGE2 production, but further up-regulated IL-1 and TNF-α secreted by synoviocytes (P

Aim of the study TBL-II is the water extract of an anti-arthritic Chinese herbal formula Tongbiling (TBL), which has been used to treat rheumatoid arthritis (RA) for many years. We herein aimed to confirm its anti-arthritic effect and explore the potential mechanism of action on collagen-induced arthritis (CIA) in mice. Materials and methods Four weeks after the first collagen immunization, mice were treated with TBL-II orally at a lower dose of 100 mg/kg/d and higher dose of 300 mg/kg/d for 2 or 8 weeks. The severity of arthritis was evaluated by symptoms, radiological scores and histological assessment. Levels of IL-1β, IL-6, TNFα and IgG2a type anti-collagen II (CII) antibody in serum were measured by ELISA. Competitive RT-PCR and immunohistochemical analysis were used to investigate MMP-2, -3, -9 mRNA and protein expression. Results Our results revealed treatment with higher dose of TBL-II for 2 weeks attenuated significantly acute inflammation, and decreased the amounts of IL-1β and TNFα in serum; treatment for 8 weeks could obviously suppress chronic inflammation, ameliorate cartilage and bone destruction, and reduce the levels of matrix metalloproteinase (MMP)-2, -3, -9 mRNA and protein expression in joints. The levels of IgG2a type anti-CII antibody in serum were significantly reduced by treatment with higher dose of TBL-II for either 2 or 8 weeks. In contrast, treatment with lower dose of TBL-II for 8 weeks had no effect on articular destruction. Conclusions Our results suggested that TBL-II at higher dose not only ameliorated symptoms but also modified disease of CIA. TBL-II would be a potent candidate as a novel botanical drug for further investigation.