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With the development of global industry, industrial wastewater pollution has caused serious environmental problems, and the demand for green and sustainable adsorbents is increasingly strong in the society. In this article, lignin/cellulose hydrogel materials were prepared using sodium lignosulfonate and cellulose as raw materials and 0.1% acetic acid solution as a solvent. The results showed that the optimal adsorption conditions for Congo red were as follows: an adsorption time of 4 h, a pH value of 6, and an adsorption temperature of 45 °C. The adsorption process was in line with the Langmuir isothermal model and a quasi-second-order kinetic model, which belonged to single molecular layer adsorption, and the maximum adsorption capacity was 294.0 mg/g. The optimal adsorption conditions for Malachite green were as follows: an adsorption time of 4 h, a pH value of 4, and an adsorption temperature of 60 °C. The adsorption process was consistent with the Freundlich isothermal model and a pseudo-second-order kinetic model, which belonged to the chemisorption-dominated multimolecular layer adsorption with the maximum adsorption capacity of 129.8 mg/g.

Diffusion Models (DMs) have empowered great success in artificial-intelligence-generated content, especially in artwork creation, yet raising new concerns in intellectual properties and copyright. For example, infringers can make profits by imitating non-authorized human-created paintings with DMs. Recent researches suggest that various adversarial examples for diffusion models can be effective tools against these copyright infringements. However, current adversarial examples show weakness in transferability over different painting-imitating methods and robustness under straightforward adversarial defense, for example, noise purification. We surprisingly find that the transferability of adversarial examples can be significantly enhanced by exploiting a fused and modified adversarial loss term under consistent parameters. In this work, we comprehensively evaluate the cross-method transferability of adversarial examples. The experimental observation shows that our method generates more transferable adversarial examples with even stronger robustness against the simple adversarial defense., Working paper

Recently, Diffusion Models (DMs) boost a wave in AI for Art yet raise new copyright concerns, where infringers benefit from using unauthorized paintings to train DMs to generate novel paintings in a similar style. To address these emerging copyright violations, in this paper, we are the first to explore and propose to utilize adversarial examples for DMs to protect human-created artworks. Specifically, we first build a theoretical framework to define and evaluate the adversarial examples for DMs. Then, based on this framework, we design a novel algorithm, named AdvDM, which exploits a Monte-Carlo estimation of adversarial examples for DMs by optimizing upon different latent variables sampled from the reverse process of DMs. Extensive experiments show that the generated adversarial examples can effectively hinder DMs from extracting their features. Therefore, our method can be a powerful tool for human artists to protect their copyright against infringers equipped with DM-based AI-for-Art applications. The code of our method is available on GitHub: https://github.com/mist-project/mist.git., Accepted by ICML2023 (Oral)

Supplementary Material 1

Video anomaly detection under weak supervision is challenging due to the absence of frame-level annotations during the training phase. Previous work has employed graph convolution networks or self-attention mechanisms to model temporal relations, along with multiple instance learning (MIL)-based classification loss to learn discriminative features. However, most of them utilize multi-branches to capture local and global dependencies separately, leading to increased parameters and computational cost. Furthermore, the binarized constraint of the MIL-based loss only ensures coarse-grained interclass separability, ignoring fine-grained discriminability within anomalous classes. In this paper, we propose a weakly supervised anomaly detection framework that emphasizes efficient context modeling and enhanced semantic discriminability. To this end, we first construct a temporal context aggregation (TCA) module that captures complete contextual information by reusing similarity matrix and adaptive fusion. Additionally, we propose a prompt-enhanced learning (PEL) module that incorporates semantic priors into the model by utilizing knowledge-based prompts, aiming at enhancing the discriminative capacity of context features while ensuring separability between anomaly sub-classes. Furthermore, we introduce a score smoothing (SS) module in the testing phase to suppress individual bias and reduce false alarms. Extensive experiments demonstrate the effectiveness of various components of our method, which achieves competitive performance with fewer parameters and computational effort on three challenging benchmarks: the UCF-crime, XD-violence, and ShanghaiTech datasets. The detection accuracy of some anomaly sub-classes is also improved with a great margin.

We consider the SUBSET SUM problem and its important variants in this paper. In the SUBSET SUM problem, a (multi-)set $X$ of $n$ positive numbers and a target number $t$ are given, and the task is to find a subset of $X$ with the maximal sum that does not exceed $t$. It is well known that this problem is NP-hard and admits fully polynomial-time approximation schemes (FPTASs). In recent years, it has been shown that there does not exist an FPTAS of running time $\tilde\OO( 1/\epsilon^{2-\delta})$ for arbitrary small $\delta>0$ assuming ($\min$,+)-convolution conjecture~\cite{bringmann2021fine}. However, the lower bound can be bypassed if we relax the constraint such that the task is to find a subset of $X$ that can slightly exceed the threshold $t$ by $\epsilon$ times, and the sum of numbers within the subset is at least $1-\tilde\OO(\epsilon)$ times the optimal objective value that respects the constraint. Approximation schemes that may violate the constraint are also known as weak approximation schemes. For the SUBSET SUM problem, there is a randomized weak approximation scheme running in time $\tilde\OO(n+ 1/\epsilon^{5/3})$ [Mucha et al.'19]. For the special case where the target $t$ is half of the summation of all input numbers, weak approximation schemes are equivalent to approximation schemes that do not violate the constraint, and the best-known algorithm runs in $\tilde\OO(n+1/\epsilon^{{3}/{2}})$ time [Bringmann and Nakos'21].

Objective To investigate NIMA-related kinase 2 (NEK2) expression in colorectal cancer (CRC) tissues and its effect on the proliferation, migration and invasion of HCT116 cells. Methods Synthesized siRNA targeting NEK2 was transfected into HCT116 cells by lipofectamine method. CCK8 assay, FACS, wound healing assay and Transwell assay were used to detect the effects of NEK2 knockdown on cell proliferation, cell cycle distribution, migration and invasion. Western blot was carried out to detect the expression of E-cadherin, N-cadherin, CDK4 and cyclin D1. Results The expression of NEK2 in CRC tissues was significantly higher than that in adjacent normal tissues (65.0% vs. 35.0%, χ2=14.593, P < 0.01), and its level was closely related to TNM stage, lymph node metastasis and distant metastasis (all P < 0.05). NEK2 protein and mRNA levels in CRC cell lines were also significantly higher than those in normal colorectal mucosal cells (P < 0.01). After NEK2 was knocked down by siRNA, HCT116 cells were arrested in G0/G1 cycle, while cell proliferation, invasion and migration were significantly reduced (P < 0.01). NEK2 interference in HCT-116 cells led to the upregulation of E-cadherin and downregulation of N-cadherin, CDK4 and cyclin D1 at protein levels. Conclusion The high NEK2 expression is correlated with clinicopathological characteristics of CRC patients. NEK2 knockdown by siRNA could effectively inhibit the proliferation, invasion and migration abilities of colorectal cancer cells, suggesting that NEK2 plays an important role in the occurrence and development of colorectal cancer and it can be used as a potential treatment target.

Vision-language pre-training (VLP) on large-scale datasets has shown premier performance on various downstream tasks. In contrast to plenty of available benchmarks with English corpus, large-scale pre-training datasets and downstream datasets with Chinese corpus remain largely unexplored. In this work, we build a large-scale high-quality Chinese cross-modal benchmark named ZERO for the research community, which contains the currently largest public pre-training dataset ZERO-Corpus and five human-annotated fine-tuning datasets for downstream tasks. ZERO-Corpus contains 250 million images paired with 750 million text descriptions, plus two of the five fine-tuning datasets are also currently the largest ones for Chinese cross-modal downstream tasks. Along with the ZERO benchmark, we also develop a VLP framework with pre-Ranking + Ranking mechanism, boosted with target-guided Distillation and feature-guided Distillation (R2D2) for large-scale cross-modal learning. A global contrastive pre-ranking is first introduced to learn the individual representations of images and texts. These primitive representations are then fused in a fine-grained ranking manner via an image-text cross encoder and a text-image cross encoder. The target-guided distillation and feature-guided distillation are further proposed to enhance the capability of R2D2. With the ZERO-Corpus and the R2D2 VLP framework, we achieve state-of-the-art performance on twelve downstream datasets from five broad categories of tasks including image-text retrieval, image-text matching, image caption, text-to-image generation, and zero-shot image classification. The datasets, models, and codes are available at https://github.com/yuxie11/R2D2

We study a bilevel optimization problem which is a zero-sum Stackelberg game. In this problem, there are two players, a leader and a follower, who pick items from a common set. Both the leader and the follower have their own (multi-dimensional) budgets, respectively. Each item is associated with a profit, which is the same to the leader and the follower, and will consume the leader’s (follower’s) budget if it is selected by the leader (follower). The leader and the follower will select items in a sequential way: First, the leader selects items within the leader’s budget. Then the follower selects items from the remaining items within the follower’s budget. The goal of the leader is to minimize the maximum profit that the follower can obtain. Let s_A and s_B be the dimension of the leader’s and follower’s budget, respectively. A special case of our problem is the bilevel knapsack problem studied by Caprara et al. [SIAM Journal on Optimization, 2014], where s_A = s_B = 1. We consider the general problem and obtain an (s_B+ε)-approximation algorithm when s_A and s_B are both constant. In particular, if s_B = 1, our algorithm implies a PTAS for the bilevel knapsack problem, which is the first 𝒪(1)-approximation algorithm. We also complement our result by showing that there does not exist any (4/3-ε)-approximation algorithm even if s_A = 1 and s_B = 2. We also consider a variant of our problem with resource augmentation when s_A and s_B are both part of the input. We obtain an 𝒪(1)-approximation algorithm with 𝒪(1)-resource augmentation, that is, we give an algorithm that returns a solution which exceeds the given leader’s budget by 𝒪(1) times, and the objective value achieved by the solution is 𝒪(1) times the optimal objective value that respects the leader’s budget., LIPIcs, Vol. 229, 49th International Colloquium on Automata, Languages, and Programming (ICALP 2022), pages 39:1-39:19

Compression of alfalfa into briquettes is an effective way to solve the problem of storage and transportation. In the process of compression, heat is generated and the temperature is raised in the material. In fact, the appropriate temperature can improve the quality of alfalfa briquettes and reduce the energy consumption of densification. In this study, the effect of assisted vibration on the compression temperature was tested. The results showed that when the vibration frequency was below 15 Hz, the temperature at the center and side in compressed alfalfa increased slowly with compression time. When the vibration frequency was above 20 Hz, it increased first and then decreased with the increase of time. Moreover, the maximum temperature value increased remarkably when the frequency was above 20 Hz. In the same vibration frequency and compression time, the center temperature in the compressed alfalfa was higher than the side temperature. The experimental results provide a reference for the determination of reasonable vibration parameters, and explanation of the effect of vibration on reducing energy consumption.

Additional file 1: Table S1. Primers used in this study. Table S2. Promoter and terminator sequence used in this study. Figure S1. The dynamic curve of stirrer speed, temperature, dissolved oxygen, and pH overall fermentation process.

Supplementary Material 2

The ability to choose an appropriate camera view among multiple cameras plays a vital role in TV shows delivery. But it is hard to figure out the statistical pattern and apply intelligent processing due to the lack of high-quality training data. To solve this issue, we first collect a novel benchmark on this setting with four diverse scenarios including concerts, sports games, gala shows, and contests, where each scenario contains 6 synchronized tracks recorded by different cameras. It contains 88-hour raw videos that contribute to the 14-hour edited videos. Based on this benchmark, we further propose a new approach temporal and contextual transformer that utilizes clues from historical shots and other views to make shot transition decisions and predict which view to be used. Extensive experiments show that our method outperforms existing methods on the proposed multi-camera editing benchmark., Comment: Extended Abstract of ECCV 2022 Workshop on AI for Creative Video Editing and Understanding

SF6/N2 gas mixture decomposition components can reflect the operation status inside GIS, and be used for fault diagnosis and monitoring inside GIS. NF3 and N2O are the characteristic decomposition components of SF6/N2 mixed gas. In order to find a potential gas sensitivity material for the detection of NF3 and N2O. This paper investigated the adsorption properties of NF3 and N2O on Al- and Ga- doped graphene monolayers based on density functional theory. Through the analysis of adsorption distance, charge transfer, adsorption energy, energy band structure, etc., the results indicated that the adsorption effect of Al- and Ga-doped graphene to NF3 and N2O are probably good, and these nanomaterials are potential to apply for the monitoring of GIS internal faults.

Additional file 2: Table S1-S4., Figure S1-S7. Table S1. List of genes in the 3DMed 150-gene panel. Table S2. HER2 mutations identified at baseline. Table S3. Clinical response to pyrotinib according to different HER2 mutation types. Table S4. The detected molecular alterations at baseline and progression. Fig. S1. HER2 mutational map at baseline. Green: receptor L domain; red: furin-like cysteine rich region; blue: growth factor receptor domain IV; yellow: protein tyrosine kinase. Fig. S2. Survival curves of pyrotinib treated HER2-mutated NSCLC patients according to baseline characteristics. (A, B) progression-free survival (PFS) and overall survival (OS) according to the ECOG performance status. PS represents ECOG performance score. (C, D) PFS and OS of pyrotinib treated patients with or without brain metastasis. mPFS, median progression-free survival; mOS, median overall survival; HR, hazard ratio; 95%CI, 95% confidence interval. Fig. S3 Objective response rate in pre-specific subgroups. Fig. S4 Survival curves of NSCLC patients treated with pyrotinib according to previous treatment. (A, B) progression-free survival (PFS) and overall survival (OS) according to the treatment lines of pyrotinib. (C, D) PFS and OS of patients according to the prior exposures to afatinib. mPFS, median progression-free survival; mOS, median overall survival; HR, hazard ratio; 95%CI, 95% confidence interval. Fig. S5 Survival curves of pyrotinib treated NSCLC patients with different HER2 mutation. mPFS, median progression-free survival; mOS, median overall survival; HR, hazard ratio; 95%CI, 95% confidence interval. Fig. S6 Survival curves of pyrotinib treated HER2-mutated NSCLC patients according to molecular characteristics. (A, B) progression-free survival and overall survival according to HER2 amplification. (C, D) PFS and OS of pyrotinib treated patients according to the occurrence of co-mutations in other driver genes. mPFS, median progression-free survival; mOS, median overall survival; HR, hazard ratio; 95%CI, 95% confidence interval. Fig. S7 Pyrotinib resistance in a patient with HER2 and EGFR amplification. CT scans were performed at baseline (2 weeks before starting pyrotinib), best response (2 months after starting pyrotinib) and disease progression (7 months after starting pyrotinib), respectively. Mm, millimeter.

Supplementary Material 3

A diastereo- and enantioselective propargylic substitution reaction between propargylic carbonates and α-substituted nitroacetates catalyzed by a Cu-pybox complex is described. This method allows the preparation of a series of non-proteinogenic quaternary α-amino acid precursors featuring two contiguous stereogenic centers and a terminal alkyne moiety in high yields with good to excellent diastereo- and enantioselectivities in most cases. The propargylated adducts were elaborated into a diverse set of quaternary α-amino acid derivatives.

Aiming at the problem of many background interference factors in the traditional forest fire smoke monitoring video based on digital images, a detection method that can eliminate interference factors such as clouds and skylines and its specific implementation methods are proposed. The article first obtains the early forest fire smoke source detection video from close-range aerial photography of multi-rotor aircraft, and then uses the principle of multi-modal mixture Gaussian background model to establish a background model to extract the background of the early forest fire smoke video. The features of the image are high-frequency fusion, the fusion image is compared with the high-frequency energy value of the corresponding background image, if the high-frequency energy of the local area is reduced, it is determined as a suspected smoke area, and the largest connected area of suspected smoke is marked. Through the simulation experiment of the above method, the experimental results show that the method can accurately detect the smoke in the video frame image, the false detection rate is low, and the influence of related interference factors on the detection accuracy of the early forest fire smoke video image can be eliminated.

[ES] El desarrollo de las redes sociales ha traído consigo nuevas oportunidades para la comunicación de los principales fabricantes. Huawei es una de las compañías líderes en el mundo debido a su fuerza corporativa, su valor de marca y su capacidad de comunicación. Este estudio examina la estrategia de comunicación en redes sociales de Huawei a través de Facebook, Twitter y Linkedin. El significado teórico es complementar la estrategia teórica de comunicación en las redes sociales y el significado práctico es servir de referencia a otras marcas para llevar a cabo la comunicación en redes sociales, [EN] The development of social media has brought new opportunities for brand communication. Huawei is one of the leading companies in the world in terms of its corporate strength, brand value and communication capability. This study examines Huawei's social media communication strategy through Facebook, Twitter and LinkedIn. The theoretical significance is to supplement the theoretical social media communication strategy, and the practical significance is to provide reference for other companies to carry out social media communication.

With AlphaGo defeats top human players, reinforcement learning(RL) algorithms have gradually become the code-base of building stronger artificial intelligence(AI). The RL algorithm design firstly needs to adapt to the specific environment, so the designed environment guides the rapid and profound development of RL algorithms. However, the existing environments, which can be divided into real world games and customized toy environments, have obvious shortcomings. For real world games, it is designed for human entertainment, and too much difficult for most of RL researchers. For customized toy environments, there is no widely accepted unified evaluation standard for all RL algorithms. Therefore, we introduce the first virtual user-friendly environment framework for RL. In this framework, the environment can be easily configured to realize all kinds of RL tasks in the mainstream research. Then all the mainstream state-of-the-art(SOTA) RL algorithms can be conveniently evaluated and compared. Therefore, our contributions mainly includes the following aspects: 1.single configured environment for all classification of SOTA RL algorithms; 2.combined environment of more than one classification RL algorithms; 3.the evaluation standard for all kinds of RL algorithms. With all these efforts, a possibility for breeding an AI with capability of general competency in a variety of tasks is provided, and maybe it will open up a new chapter for AI., Comment: 19 pages,16 figures

Additional file 1. The primers used in this study and the structure identification of X33 AMOP.

In response to the unsafe driving of taxi drivers during the epidemic, the design and implementation of the driver's face registration and detection of whether the driver wears a mask, detection of the driver's fatigue physiological signals and multiple integration are designed. Target detection algorithm based on MobileNetV2 to realize mask detection. Combine MTCNN and Face-Net organically to realize driver's face login. The cerebellar neural network model is used to fuse the 12 fatigue monitoring signals EMG, EEG, etc. extracted by the simulated driving experiment platform to obtain a multi-integrated fatigue monitoring control model. After the fatigue driving multiple physiological indicators of the simulated driving platform, the technical model is studied and verified. It is concluded that the multiple fusion fatigue monitoring control model has higher accuracy than the traditional single signal monitoring.

Xiaoyu Wu,1 Facai Cui,1 Yu Chen,2 Ya Zhu,1 Fengzhen Liu1 1Department of Clinical Laboratory, Henan Provincial People’s Hospital, People’s Hospital of Zhengzhou University, Zhengzhou, Henan, People’s Republic of China; 2Department of Pathology, Affiliated Tumor Hospital of Zhengzhou University, Zhengzhou, Henan, People’s Republic of ChinaCorrespondence: Xiaoyu Wu Email xiaoyuwhn@163.comIntroduction: Colorectal cancer (CRC), the third most common cancer worldwide, involves a physiological and pathological long non-coding RNA (lncRNA) paradigm shift. It has been reported that the lncRNA LOXL1-AS1 affects tumor development for many kinds of cancers, but its functions and mechanisms in CRC remain unknown.Methods: Expression levels of LOXL1-AS1 and miR-708-5p within CRC tissues and cell lines were measured using qRT-PCR. The performance of gain-of-function and loss-of-function assays was aimed at examining the effects of LOXL1-AS1 and miR-708-5p; colony formation and cell viability assays were carried out to measure cell multiplication; and Transwell migration and wound-healing assays were carried out for the measurement of cell migration and invasion. Luciferase reporter assay was used to verify the interactions between LOXL1-AS1 and miR-708-5p and between miR-708-5p and the CD44-EGFR signaling pathway. Finally, expression of CD44 and EGFR proteins was measured by Western blot and immunofluorescence assays.Results: In this study, we reveal that the regulation of lncRNA LOXL1-AS1 occurs within CRC based on the correlation with poor clinical outcomes. LOXL1-AS1 knockdown along with miR-708-5p overpresentation in CRC cell lines inhibited cell multiplication, migration, and invasion. The inhibiting effect of LOXL1-AS1 knockdown on CRC was reversed by upregulating the CD44-EGFR signal pathway. From the perspective of mechanism, LOXL1-AS1 imposes sponging upon miR-708-5p and thereby promotes the CD44-EGFR signal pathway in CRC cells.Discussion: This study demonstrated that lncRNA LOXL1-AS1 enhances multiplication, migration, invasion, and progression of CRC by sponging miR-708-5p to regulate the CD44-EGFR signal pathway.Keywords: colorectal cancer, LOXL1-AS1, CD44-EGFR signal pathway, miR-708-5p, migration

With the rapid development and popularization of computer network and multimedia technology, we are continuously exposed to photographs and images. Some images are easy to be remembered, but others are ignored or quickly forgotten. Previous studies have shown that image memorability is an intrinsic property of an image, which is used to measure the degree to which an image is later remembered or forgotten. Many works have shown that visual factors that influence the image memorability, such as highly memorable visual content, image depth information. Prior research has shown that image depth information has a positive relationship with its memorability score. Based on AMNet, this paper makes few improvements and utilizes depth cues to predict the image memorability scores. In this paper, the depth cues of the images are combined with the original image features to predict the final memorability score for the given image by utilizing the late fusion methodology. Experiments conducted on public image memorability datasets evaluate the effectiveness of the proposed model.

Background LncRNAs act as functional regulators in tumor progression through interacting with various signaling pathways in multiple types of cancer. However, the effect of LINC02418 on colorectal cancer (CRC) progression and the underling mechanisms remain unclear. Methods LncRNA expression profile in CRC tissues was investigated by the TCGA database. The expressional level of LINC02418 in CRC patients was determined by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Kaplan–Meier analyses was used to investigate the correlation between LINC02418 and overall survival (OS) of CRC patients. Cell proliferative, migratory and invasive abilities were detected by CCK-8 assays, colony formation assays and trans-well assays in HCT116 and LoVo cells which were stably transduced with sh-LINC02418 or sh-NC. The binding between LINC02418 and miR-34b-5p, and the interaction between miR-34b-5p and BCL2 were determined by dual-luciferase assays. Western blot experiments were conducted to further explore the effect of miR-34b-5p on BCL2 signaling pathway. Rescue experiments were performed to uncover the role of LINC02418/miR-34b-5p/BCL2 axis in CRC progression. Results LINC02418 was upregulated in human colon cancer samples when compared with adjacent tissue, and its high expressional level correlated with poor prognosis of CRC patients. LINC02418 promoted cancer progression by enhancing tumor growth, cell mobility and invasiveness of colon cancer cells. Additionally, LINC02418 could physically bind to miR-34b-5p and subsequently affect BCL2 signaling pathway. Down-regulation of LINC02418 reduced cell proliferation, while transfection of miR-34b-5p inhibitor or BCL2 into LINC02418-silenced CRC cells significantly promoted CRC cells growth. Conclusions LINC02418 was upregulated in human CRC samples and could be used as the indicator for prediction of prognosis. LINC02418 acted as a tumor driver by negatively regulating cell apoptosis through LINC02418/miR-34b-5p/BCL2 axis in CRC.

In this paper, we propose a novel multi-variate algorithm using a triple-regression methodology to predict the airborne-pollen allergy season that can be customized for each patient in the long term. To improve the prediction accuracy, we first perform a pre-processing to integrate the historical data of pollen concentration and various inferential signals from other covariates such as the meteorological data. We then propose a novel algorithm which encompasses three-stage regressions: in Stage 1, a regression model to predict the start/end date of a airborne-pollen allergy season is trained from a feature matrix extracted from 12 time series of the covariates with a rolling window; in Stage 2, a regression model to predict the corresponding uncertainty is trained based on the feature matrix and the prediction result from Stage 1; in Stage 3, a weighted linear regression model is built upon prediction results from Stage 1 and 2. It is observed and proved that Stage 3 contributes to the improved forecasting accuracy and the reduced uncertainty of the multi-variate triple-regression algorithm. Based on different allergy sensitivity level, the triggering concentration of the pollen - the definition of the allergy season can be customized individually. In our backtesting, a mean absolute error (MAE) of 4.7 days was achieved using the algorithm. We conclude that this algorithm could be applicable in both generic and long-term forecasting problems., 4 pages, 4 figures

Nanoelectronic devices based on ferroelectric domain walls (DWs), such as memories, transistors, and rectifiers, have been demonstrated in recent years. Practical high-speed electronics, on the other hand, usually demand operation frequencies in the giga-Hertz (GHz) regime, where the effect of dipolar oscillation is important. In this work, an unexpected giant GHz conductivity on the order of 103 S/m is observed in certain BiFeO3 DWs, which is about 100,000 times greater than the carrier-induced dc conductivity of the same walls. Surprisingly, the nominal configuration of the DWs precludes the ac conduction under an excitation electric field perpendicular to the surface. Theoretical analysis shows that the inclined DWs are stressed asymmetrically near the film surface, whereas the vertical walls in a control sample are not. The resultant imbalanced polarization profile can then couple to the out-of-plane microwave fields and induce power dissipation, which is confirmed by the phase-field modeling. Since the contributions from mobile-carrier conduction and bound-charge oscillation to the ac conductivity are equivalent in a microwave circuit, the research on local structural dynamics may open a new avenue to implement DW nano-devices for RF applications.

Xiaoyu Wu,1,* Xuequan Yao,1,* Qinhong Cao,1 Zhenfeng Wu,1 Zhaojing Wang,1 Fukun Liu,1 Lizong Shen2 1Department of Surgical Oncology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China; 2Department of General Surgery, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China *These authors contributed equally to this work Background: The patients with hepatocellular carcinoma (HCC) have poor prognosis due to being diagnosed at late stage or recurrence following surgery. It’s critical to identify effective biomarkers that can improve overall diagnosis and treatment of HCC. Methods: We performed a meta-analysis of all relative studies reporting the clinicopathological significance of CDH1 hypermethylation in HCC by using Review Manager 5.2. A comprehensive literature search was performed in EMBASE, PubMed, Web of Science and Google Scholar databases. Kaplan Meier Plotter online database was used for the determination of correlation between CDH1 mRNA expression and overall survival in patients with HCC. Odds Ratios (OR) with 95% corresponding confidence intervals (CIs) were calculated. A total of 12 relevant studies were included in the meta-analysis with 981 patients. Results: The positive rate of CDH1 hypermethylation was significantly higher in HCC thanin normal liver tissue; and the pooled OR was 4.34 with 95% CI 2.50–7.56, P

Road marking is a special kind of symbol on the road surface, used to regulate the behavior of traffic participants. According to our survey, it seems that no papers has yet proposed a mature, highly practical method to detect and classify these important fine-grained markings. Deep learning techniques, especially deep neural networks, have proven to be effective in coping with a variety of computer vision tasks. Using deep neural networks to construct road marking detection systems is a practical solution.

The Ion-12SC is a sub-compact, 12.5 MeV proton su-perconducting isochronous cyclotron for commercial medical isotope production recently developed at Ionetix Corporation [1]. The machine features a patented cold steel and cryogen-free conduction cooling magnet, a low power internal cold-cathode PIG ion source, and an inter-nal liquid target [2]. It was initially designed to produce N-13 ammonia for dose on-demand cardiology applica-tions but can also be used to produce F-18, Ga-68 and other medical isotopes widely used in Positron Emission Tomography (PET). The 1st engineering prototype was completed and commissioned in September 2015, and four additional units have been completed since [3]. The first two units have been installed and operated at the University of Michigan and MIT. R efforts in physics and engineering have continued to improve machine performance, stability and reliability. These improve-ments include: 1) Water cooling added to the dummy dee to limit the operating temperature of the ion source to improve lifetime and performance, 2) Magnetic field maps, obtained with a Hall probe based mapper, were used to accurately measure the isochronism and provide information needed to compensate for any unwanted 1st harmonics and 3) Feedback based control methods ap-plied to regulate the beam intensity on target by adjusting the ion source cathode current. The C1 unit installed at the University of Michigan Medical School early this year treated ~100 patients/month with N-13 ammonia. The machines are now capable of routinely producing > 21 doses/day with > 99% availability. The Ionetix manu-facturing facility is capable of producing up to 30 ma-chines per year., Proceedings of the 10th Int. Particle Accelerator Conf., IPAC2019, Melbourne, Australia

Burning loss of graphene in the high-temperature plasma-spraying process is a critical issue, significantly limiting the remarkable performance improvement in graphene reinforced ceramic coatings. Here, we reported an effective approach to enhance the graphene retention, and thus improve the performance of plasma-sprayed alumina/graphene nanoplatelets (Al2O3/GNPs) coatings by heat treatment of agglomerated Al2O3/GNPs powders. The effect of powder heat treatment on the microstructure, GNPs retention, and electrical conductivity of Al2O3/GNPs coatings were systematically investigated. The results indicated that, with the increase in the powder heat treatment temperature, the plasma-sprayed Al2O3/GNPs coatings exhibited decreased porosity and improved adhesive strength. Thermogravimetric analysis and Raman spectra results indicated that increased GNPs retention from 12.9% to 28.4%, and further to 37.4%, as well as decreased structural defects, were obtained for the AG, AG850, and AG1280 coatings, respectively, which were fabricated by using AG powders without heat treatment, powders heat-treated at 850 °C, and powders heat-treated at 1280 °C. Moreover, the electrical conductivities of AG, AG850, and AG1280 coatings exhibited 3 orders, 4 orders, and 7 orders of magnitude higher than that of Al2O3 coating, respectively. Powder heat treatment is considered to increase the melting degree of agglomerated alumina particles, eventually leaving less thermal energy for GNPs to burn, thus, a high retention amount and structural integrity of GNPs and significantly enhanced electrical conductivity were achieved for the plasma-sprayed Al2O3/GNPs coatings.

Kinetics data for CO2 thermochemical reduction in an isothermal membrane reactor is required to identify the rate-limiting steps. Here, we report a detailed reaction kinetics study on this process supported by an La0.9Ca0.1FeO3-δ (LCF-91) membrane. The dependence of CO2 reduction rate on various operating conditions is examined such as CO2 concentration on the feed side, fuel concentrations on the sweep side and temperatures. CO2 reduction rate is proportional to the oxygen flux across the membrane, and the measured maximum fluxes are 0.191 and 0.164 μmol cm-2 s-1 with 9.5% H2 and 11.6% CO on the sweep side at 990oC, respectively. Fuel is used to maintain the chemical potential gradient across the membrane and CO is used by construction to derive the surface reaction kinetics. This membrane also exhibits stable performances for 106 hours. A resistance-network model is developed to describe the oxygen transport process and the kinetics data are parameterized using the experimental values. The model shows a transition of the rate limiting step between the surface reactions on the feed side and the sweep side depending on the operating conditions.

With the rapid expansion of the city in China, more and more old industrial buildings in cities become idle and abandoned. However, Old industrial buildings are carrying the history of a city and reflecting the urban development process so that renewal of the old industrial buildings has great value in the sense of cultural, aesthetic, ecological, economic, and sustainable development. How to reuse those buildings is worth studying. This paper, based on the principle of Adaptive Renewal and sustainable reuse, takes two typical successful cases to discuss how to reuse these old industrial buildings into culture ones in China.

Hydrogels have been widely utilized in various fields as a function of their tunable physical and biochemical properties. The unique physical properties of hydrogels, including their porosity and swelling capacity, make them favorable platforms for drug delivery. Although chitosan is the most popular natural polymer due to its biocompatibility, low toxicity, biodegradability, and other biofunctional activities, its potential commercial applications are constrained due to its poor solubility in water. Hydroxybutyl chitosan (HBCS) was synthesized in our study to improve its solubility. The HBCS hydrogel exhibited excellent thermo/pH sensitive sol-gel reversibility behavior from 4 °C to the gelation temperature. Additionally, the gelation time and temperature could be optimized by adjusting the HBCS concentration, gelation temperature, and pH value according to clinical requirements. The HBCS hydrogel had both favorable water-solubility and swellability when compared with unmodified chitosan. Moreover, the HBCS demonstrated lower hemolysis at a concentration of 1 mg/mL. The HBCS hydrogel was completely biodegraded after 8 weeks of muscle implantation and 7 weeks of subcutaneous implantation. These results demonstrated that the HBCS hydrogel with biodegradable thermo/pH sensitive sol-gel reversible properties had excellent cytocompatibility, histocompatibility, and biocompatibility as a drug carrier. As such, HBCS holds great promise for future biomedical applications.

In the management of capital assets owned by major enterprise, there exist some information disconnection including no information about equipment working conditions when bidding for them, no information about installation and debugging when the equipment was overhauled. Therefore, the paper proposes to establish a equipment management system based on BOM tree and RFID. Giving asset devices lifetime identity through RFID coding, which will be utilized throughout all procedures including planning and designing, bidding and procurement, construction building and so on. The paper develops some apps, such as engineering construction, warehouse management to realize data circulation throughout the equipment. Besides, with data analysis, the paper carries on equipment unit cost allocation and collection and supplier comprehensive evaluation, to guide equipment procurement and management, strengthen the whole process monitoring of asset operation status, improve the management level of asset lean management, and optimize the asset operation strategy of the company.

Chitosan (CS) has been reported to have utility for various potential applications in biomedicine, tissue engineering, and cosmetics, as well as in the formulation of antibacterial agents because it exhibits a variety of desirable attributes, including low-toxicity, biodegradability, excellent biocompatibility, and broad-spectrum antibacterial activity. However, the full realization of CS's biomedical applications are practically constrained by its poor solubility. The goal of the present study is to prepare hydroxybutyl chitosan (HBCS) and investigate its impacts on immunocompetence, and its antibacterial activity. In the current study, HBCS was synthesized by modifying the hydroxybutyl group on the chitosan molecule using an etherification method. The physicochemical properties of the synthesized HBCS were characterized by various methods. Results showed that hydro-soluble HBCS exhibited excellent hygroscopicity and moisture retention. It was also found that HBCS exhibited notable cytocompatibility when cultured with mouse embryo fibroblasts. HBCS was able regulate immuno-functionality and promote immunocompetence by improving phagocytosis of macrophages and reinforcing lymphocyte activity in vivo and in vitro. Moreover, HBCS was also found to inhibit L-929 cell migration, indicating the impeded migration and metastasis behaviors of fibrosarcoma cells. Additionally, HBCS displayed favorable antimicrobial functionality against both Gram-positive (Staphylococcus aureus) and Gram-negative (Escherichia coli) bacteria. This study demonstrated that HBCS could in turn lock moisture, can promote immunocompetence activity, can inhibit fibrosarcoma cell migration, and exhibits anti-bacterial functionality. Taken together, these results indicate that HBCS shows substantial promise for applications in cosmetics, biomedicine, and antibacterial therapies.

With the rapid development of the Internet, the images become the main medium of information dissemination, while the spread of pornographic images are getting more serious. Therefore, we propose a detection method of pornographic images based on a combination of global and local features. Considering the NPDI database's defective both in quality and quantity, so this paper constructs new database CUC_NSFW (Not Suitable for Work) applying data augmentation methods to improve the classification performance. Pornographic images with only exposed sensitive organs become the bottleneck of improving model recall ratio. We design a sensitive organs detection module, cascaded behind the residual network assisting the recognition of pornography images. And our method makes a good performance based on the research work of pornographic image detection

In this study, rice straw (RS) and pig manure (PM) mixtures with or without bio-pretreatment were used as the substrates and digested in a 9 L of anaerobic reactor at Organic loading rates (OLRs) of 0.4–3.1 kg COD/(m3 d). The volumetric methane production rate (VMPR), methane yield and anaerobic stability were comparatively investigated. The results showed the co-anaerobic digestion processes of RS and PM mixture after biological pretreatment were very stable at OLRs of 0.4–2.5 kg COD/(m3 d), and its optimal VMPR and methane yield could reach 0.64 L CH4/(L d) and 0.4557 L CH4/g CODremoved at OLR of 2.5 kg COD/(m3 d), which were 62.4% and 37.8% higher than those of the control under the same OLR condition. This study indicated the biological pretreatment with a cellulolytic microbial consortium own great potential in improving the methane yield and productivity of RS and PM wastes.

Chinese traditional visual culture symbols (CT-VCSs) is formed in the tradition and has the characteristic of Chinese unique ideological and cultural connotation. It is a visual cultural heritage of Chinese culture. So the research on CT-VCSs has important practical significance. In this paper, it is mainly about the recognition and classification of CT-VCSs based on machine learning. We make use of the advantages of both shallow learning and deep learning, and then we combine them together to achieve the purpose of recognition. In other words, we regard the traditional convolutional neural network as a feature extractor and extract the features of two full-connected layers as depth hierarchy features. At last, we take them into SVM with Histogram Intersection Kernel function for classification. Experimental results show that the recognition effect is very good.

A 12.5 MeV, 25 μA, proton compact superconducting cyclotron for medical isotope production has been produced. The machine is initially aimed at producing 13N ammonia for Positron Emission Tomography (PET) cardiology applications. With an ultra-compact size and cost-effective price point, this system offers clinicians unprecedented access to the preferred radiopharmaceutical isotope for cardiac PET imaging. A systems approach that carefully balanced the subsystem requirements coupled to precise beam dynamics calculations was followed. The system is designed to irradiate a liquid target internal to the cyclotron and to minimize the need for radiation shielding. The overall engineering, construction, commissioning, and experience at the first customer site will be described here., Proceedings of the 21st Int. Conf. on Cyclotrons and their Applications, Cyclotrons2016, Zurich, Switzerland

Objectives: The aim of this study was to assess the effect of the pro-inflammatory interleukin (IL)-17A in deep venous thrombosis (DVT) resolution. Materials and Methods: A total of 45 DVT patients, 30 primary deep venous insufficiencies (DVI) patients, and 18 healthy volunteers were divided into three groups: (a) Control group, (b) DVT group, and (c) DVI group. The venous blood samples of the lower extremity with DVT were collected to evaluate the expression of IL-17A in plasma. Samples of superficial venous thrombus and superficial vein without thrombosis were collected to evaluate the expression of IL-17A in tissue. Male C57/BL mice DVT model was established and was randomly divided into five groups: (1) Control group, no treatment or surgical intervention; (2) Sham group, no treatment and sham operation; (3) DVT group, each mouse intravenous (iv) injected with phosphate-buffered saline (PBS); (4) IL-17A group, each mouse was iv injected with IL-17A; and (5) IL-17A-neutralizing antibody (NA) group, each mouse was iv injected with IL17A NA. Inferior vena cava (IVC) with thrombi were collected to measure their length and weight and analysis CD31(+) endothelial cells in thrombus of internal cerebral vein. Results: Western blot suggested that the expression of IL-17A in superficial vein with thrombosis was higher than superficial vein without thrombosis from human samples (P

Nowadays, the problem of mobile digital copyright protection becomes more and more serious, the number of mobile client and small-sized system is growing. In such a situation, this paper proposed an authentication and authorization solution which based on Kerberos for tens of thousands users. This paper introduced every links of permission describe method and authentication protocol which composed the solution, and discusses the security of protocol for the man-in-the-middle attack, replay attack and password guessing attack, and analysis performance of the solution. This paper proved that the solution guarantee high safety performance on the base of lightweight.

Object detection is one of the most foundational tasks in computer vision, state-of-the-art object detection networks depend on region proposal algorithms to hypothesize object locations. Although advances like SPPnet, RCNN and Fast R-CNN have improved a lot which is widely used in the fields of object detection, exposing region proposal computation and time consuming as bottleneck. Faster-RCNN born precisely to solve this problem, is an improvement on the original R-CNN designed to speed up the detection network. So we apply the Faster R-CNN to train a detector to rank a pool of proposals for faster evaluation which have reduced the running time of the detection network and performed better.

Globalization is a historic chance for China development. Moreover, Chinese traditional Visual Cultural Symbols (VCS) is a great tag of China. Image is a carrier of VCS. With the help of machine learning, we can recognize these VCS among numerous images very well. In this paper we propose combining with several features such as SIFT, HOG, RGB, LBP to describe an image and coding these features into higher dimensional vectors. Next, the coded vectors are pooled together. Besides, we also make full use of Bag-of-Words (BOW) and Spatial Pyramid Matching (SPM) theory in order to obtain a more ideal recognition. Experiments show that it's really a feasible approach.

Chinese Traditional Visual Cultural Symbols(CT-VCSs) is the important component of Chinese ancient civilization, and it is the crystallization of Chinese culture with a history of several thousand years. So it has great significance to research CT-VCSs. In this paper, we mainly research the recognition and classification of CT-VCSs based on Convolutional neural network(CNN). We mainly use Caffenet and Alexnet in the Caffe framework, and fine-tune the existed Caffe models. Meanwhile, we also use GPU to speed up the process of training. Experimental results indicate that using CNN poses remarkable enhancement on the recognition task of CT-VCSs, and the recognition result of using Alexnet is the best.