Multiple Cross Research Articles

GAN-based spatial image steganography with cross feedback mechanism

Steganography has been widely used to realize covert communication with multimedia content. By simulating the competition between a generator and a discriminator in a generative adversarial network (GAN), good distortion measurement can be automatically learnt to help designing high undetectable steganography. Nevertheless, existing GAN-based steganography always uses linear convolutional neural networks to construct generators, where the modification information of pixel in deep layers cannot be real-time transmitted to the neurons of the shallow layers, resulting in a low undetectable performance due to insufficient network training. To address the problem, we propose a new GAN-based spatial steganographic scheme. Different from existing GAN-based steganography, we build multiple cross feedback channels between the contraction path and the expansion path of the generator, which allows that the down-sampling information is directly sent to the expansion layer through these feedback channels. Since the detailed information from deep layers can be captured effectively by referring to the information from cover image, the generator can finally learn a sophisticated probability map to guide high undetectable steganography. Comprehensive experimental results demonstrate that, with the same steganalyzers, our scheme is superior to existing GAN-based steganographic schemes in terms of anti-steganalysis capability.

A Rapid Detection of Haemophilus influenzae Using Multiple Cross Displacement Amplification Linked With Nanoparticle-Based Lateral Flow Biosensor.

Haemophilus influenzae is a major human pathogenic bacterium, resulting in a series of diseases, such as pneumonia, bacteremia, meningitis. However, it is hard to diagnose H. influenzae quickly. In this study, the multiple cross displacement amplification (MCDA) and nanoparticle-based lateral flow biosensor (LFB) (MCDA-LFB) were combined to detect H. influenzae, which has been proven to be reliable, rapid, and not complicated. On the basis of H. influenzae outer membrane protein P6 gene, 10 specific primers were designed. The best MCDA condition was 61°C for 1 h. The sensitivity of H. influenzae-MCD-LFB assay showed, in the pure cultures, the minimum concentration of genomic DNA templates was 100 fg. The specificity of H. influenzae-MCD-LFB assay showed only H. influenzae templates were detected, and no cross-reactivity was found in non-H. influenzae isolates and other Haemophilus species. In 56 sputum samples, with MCDA-LFB method and PCR detection, 21 samples were positive, which was in consistent with the traditional culture method. The accuracy of diagnosis of MCDA-LFB, in comparison with the traditional culture method and PCR detection, can reach 100%, indicating that the MCDA-LFB assay gains an advantage over the cultured-based method for target pathogen detection. In conclusion, the MCDA-LFB assay is suitable for the sensitive, rapid, and specific detection of H. influenzae, which might be used as a potential diagnostic tool for H. influenzae in basic and clinical laboratories.

Development of soybeans starch based tough, water resistant and mildew-proof adhesives through multiple cross linking cooperation strategy

The exploitation of the environment-friendly and renewable biomass adhesive is a promising alternative compared to petroleum-based ones in the wood industry. In this study, soybean flour (SF) was chosen as a renewable starting material for the preparation of the biomass adhesive. The soy protein structure was unfolded by the calcium hydroxide and multiple reactive groups (-COOH, –NH2, –OH, –SH) of the protein chain were exposed. Inspired by the marine mussel protein, tannic acid (TA) with many poly-catechol/pyrogallol groups was capable of interacting with protein molecules under the alkaline conditions and the strong metal coordination between Ca2+ and TA enable to reinforce the network structure of adhesive. Furthermore, the incorporation of 1,6-Hexanediol diglycidyl ether (HDE) into the pristine protein adhesive had reacted with protein molecules via chemical covalent bonds to form the stable and toughness cross-linking network. The as-obtained adhesive showed improved bonding strength and comparable water resistance. Notably, the enhanced adhesive showed an outstanding wet shear strength of 1.12 MPa, meeting China's interior furnishing requirements (≥0.7 MPa). Additionally, in contrast to unmodified adhesive, the mildew resistance of the cooperation modified adhesive was improved and the storage life extended. This research provides a novel and green way to develop a formaldehyde-free adhesive for the wood industry.

Single Multiple Cross Displacement Amplification for Rapid and Real-Time Detection of Porcine Circovirus 3.

Since 2016, a novel porcine circovirus, PCV3, has been infecting pigs, causing significant economic losses to the pig industry. In recent years, the infection rate of PCV3 has been increasing, and thus rapid and accurate detection methods for PCV3 are essential. In this study, we established a novel probe-based single multiple cross displacement amplification (P-S-MCDA) method for PCV3. The method was termed as P-S-MCDA. The P-S-MCDA uses seven primers to amplify the capsid gene, and the assay can be performed at 60°C for 30 min, greatly shortening the reaction time. The results of P-S-MCDA can not only be monitored in real time through fluorescence signals but also be determined by observing the fluorescence of the reaction tubes using a smartphone-based cassette. This method demonstrated good specificity and the same sensitivity as qPCR, with a minimum detection limit of 10 copies. In 139 clinical samples, the coincidence rate with qPCR was 100%. The P-S-MCDA can be widely applied in PCV3 detection in laboratories or in rural areas.

Scribal Experiences of Salvation – Aspects of Formation Processes in the Hezekiah-Isaiah Narratives

Abstract To this day there is no consensus about the dating and literary growth of the Hezekiah-Isaiah narratives. This paper is a contribution designed to clarify the literary history of these stories. It considers processes of innerbiblical exegesis, aspects of a text-critical analysis and facets of their absolute and relative dating. Simultaneously, observations on the multiple cross connections with other texts reveal the theological substance of the stories: Experiences of misery that appear in the older Isaiah tradition developed into a salvation-theological ideal in the Hezekiah-Isaiah narratives.

A test method for analyzing the deformation of landslide model

In order to study the overall deformation of geotechnical model conveniently, the worksite of landslide bridge foundation reinforced by the front and rear row anti-slide piles in Chenglan railway was taken as an example. On the basis of shaking tabe test of a 1/40 reduced scale model, the landslide deformation caused by vibration waves was monitored through burying self-made phosphor bronze strips in soil. Combined with the horizontal and vertical coordinates of the bending strain points on the phosphor bronze strips, the digital matrix was converted by applying Renka Cline random matrix generation method, and the two-dimensional contour plots were drawn based on it. The results showed that the two-dimensional contour plots reflected the basic law of landslide deformation reasonably, and it revealed the evolution process of landslide deformation and failure. The research conclusions were consistent with the test phenomenon, which met the basic requirements of overall deformation analysis of landslide model. This proposed method can monitor multiple cross sections and was practical for model test.

Molecular characterization of Dachengzi oil shale kerogen by multidimensional solid-state nuclear magnetic resonance spectroscopy

Solid-state nuclear magnetic resonance (SSNMR) techniques of 13C multiple cross polarization (multiCP), 13C multiCP with recoupled dipolar dephasing (multiCP/DD) and two-dimensional (2D) 1H–13C heteronuclear correlation (HETCOR) were used to characterize Dachengzi oil shale kerogen. Specific structural information was obtained from the quantitative multiCP and multiCP/DD spectra. The protonated aromatic signals distribute widely in the aromatic region and account for 24% of the total aromatic signals. The strong methylene peak in multiCP/DD spectrum indicates the long methylene chain structures. The 2D HETCOR spectra show that oxygen atoms play an important role in the connectivities between different groups. The strong peaks at the 1H/13C chemical shifts of 5/131 and 1.5/131 ppm indicate the high abundance of (–O–CH2)-aromatic and alkyl-substituted aromatic moieties. The connectivities were validated by calculating the chemical shifts of a series of relevant molecular models using quantum chemistry methods. The 13C signal assignment was completed and improved with the multidimensional SSNMR spectra. The results from SSNMR are in agreement with the fast pyrolysis study, and the appearance of (–O–CH2)-aromatic moieties indicates that the methylbenzene homologues in the pyrolysis products can originate from the cleavage of the C–O bonds in (–O–CH2)-aromatic moieties in addition to the β-scission reaction of linear alkylbenzene moieties.

Development and Application of a Multiple Cross Displacement Amplification Combined With Nanoparticle-Based Lateral Flow Biosensor Assay to Detect Candida tropicalis.

Candida tropicalis is an increasingly opportunistic pathogen that causes serious invasive candidiasis threatening a patient’s life. Traditional methods to detect C. tropicalis infection depends on time-consuming, culture-based gold-standard methods. So, we sought to establish a new method that could detect target pathogens quickly, accurately, and straightforwardly. Herein, a combination of multiple cross displacement amplification (MCDA) and lateral flow biosensors (LFB) was employed to detect C. tropicalis. In the MCDA system, 10 primers were designed to identify the specific genes of C. tropicalis and amplify the genes in an isothermal amplification device. Then, MCDA amplification reaction products could be identified visibly by color change, and all the amplification products would be tested by LFB with no special equipment. The results demonstrated that the optimal reaction condition of C. tropicalis-MCDA assay was 64°C within 30 min, and only 10 fg DNA was required in each reaction. No cross-reaction was found between C. tropicalis strains and non-C. tropicalis strains. For 300 sputum samples, the results showed that MCDA-LFB assay could rapidly and successfully detect all of the C. tropicalis-positive (28/300) samples detected by the gold-standard method. The entire procedure, including specimen processing (40 min), isothermal reaction (30 min) and result reporting (within 2 min), could be completed within 75 min. Briefly, the study results demonstrated that the detection ability of C. tropicalis-MCDA-LFB assay was better than culture methods with more simplicity, rapidity, sensitivity and specificity. Hence, MCDA-LFB strategy is an effective tool to rapidly detect C. tropicalis in clinical samples, especially in resource-poor areas.

Pain quality of thermal grill illusion is similar to that of central neuropathic pain rather than peripheral neuropathic pain.

Application of spatially interlaced innocuous warm and cool stimuli to the skin elicits illusory pain, known as the thermal grill illusion (TGI). This study aimed to discriminate the underlying mechanisms of central and peripheral neuropathic pain focusing on pain quality, which is considered to indicate the underlying mechanism(s) of pain. We compared pain qualities in central and peripheral neuropathic pain with reference to pain qualities of TGI-induced pain. Experiment 1:137 healthy participants placed their hand on eight custom-built copper bars for 60s and their pain quality was assessed by the McGill Pain Questionnaire. Experiment 2: Pain quality was evaluated in patients suffering from central and peripheral neuropathic pain (42 patients with spinal cord injury, 31 patients with stroke, 83 patients with trigeminal neuralgia and 131 patients with postherpetic neuralgia). Experiment 1: Two components of TGI-induced pain were found using principal component analysis: component 1 included aching, throbbing, heavy and burning pain, component 2 included itching, electrical-shock, numbness, and cold-freezing. Experiment 2: Multiple correspondence analysis (MCA) and cross tabulation analysis revealed specific pain qualities including aching, hot-burning, heavy, cold-freezing, numbness, and electrical-shock pain were associated with central neuropathic pain rather than peripheral neuropathic pain. We found similar qualities between TGI-induced pain in healthy participants and central neuropathic pain rather than peripheral neuropathic pain. The mechanism of TGI is more similar to the mechanism of central neuropathic pain than that of neuropathic pain.

Drug-Target Interaction Prediction Using Multi-Head Self-Attention and Graph Attention Network.

Identifying drug-target interactions (DTIs) is an important step in the process of new drug discovery and drug repositioning. Accurate predictions for DTIs can improve the efficiency in the drug discovery and development. Although rapid advances in deep learning technologies have generated various computational methods, it is still appealing to further investigate how to design efficient networks for predicting DTIs. In this study, we propose an end-to-end deep learning method (called MHSADTI) to predict DTIs based on the graph attention network and multi-head self-attention mechanism. First, the characteristics of drugs and proteins are extracted by the graph attention network and multi-head self-attention mechanism, respectively. Then, the attention scores are used to consider which amino acid subsequence in a protein is more important for the drug to predict its interactions. Finally, we predict DTIs by a fully connected layer after obtaining the feature vectors of drugs and proteins. MHSADTI takes advantage of self-attention mechanism for obtaining long-dependent contextual relationship in amino acid sequences and predicting DTI interpretability. More effective molecular characteristics are also obtained by the attention mechanism in graph attention networks. Multiple cross validation experiments are adopted to assess the performance of our MHSADTI. The experiments on four datasets, human, C.elegans, DUD-E and DrugBank show our method outperforms the state-of-the-art methods in terms of AUC, Precision, Recall, AUPR and F1-score. In addition, the case studies further demonstrate that our method can provide effective visualizations to interpret the prediction results from biological insights.

Research on optimization of the number of acoustic arrays

The reasonable number of base stations in multiple acoustic array azimuth cross location is studied. In this paper, the maximum likelihood estimation (MLE) algorithm is used to discuss the problem of increasing the number of arrays to improve the positioning accuracy, and the positioning error model is given. The experimental results show that with the increase of the number of base stations, the positioning accuracy will gradually improve, but if there are too many base stations, the improvement of positioning accuracy will gradually slow down.

RESEARCH ON RESTORING FORCE MODEL OF H-SECTION STEEL MEMBERS UNDER UNIAXIAL COMPRESSION AND BENDING CONSIDERING LOCAL BUCKLING

It is the basis of elastic-plastic time-history analysis in seismic analysis of the thin-walled frame structures that the effect of local buckling must be considered in the restoring force model. In order to obtain the moment-curvature relationship of a H-section member under cyclic bending about different axes, the hysteretic properties of uniaxial compression and bending of a thin-walled H-shaped section member were analyzed by FEM. Based on the results of tests and of parameter analysis, a restoring force model was established considering the degradation caused by local buckling and by plate interaction effect. The model is divided into two degradation models according to whether there is increased reloading stiffness in the degradation stage. The first type, the general degradation model, was used for the bending around the weak axis with buckled-web and the bending around a strong axis. The second type, increased reloading stiffness model, was used for the bending around the weak axis with unbuckled-web. The correctness of the proposed restoring force model is verified by comparing the results of tests and of numerical analyses with those of multiple cross sections with different width-thickness ratios and axial compression ratio. The comparison ensures the accuracy and applicability of the model. The model and conclusion presented show that the thin-walled H-section member has a certain ductility and energy dissipation capacity after buckling. This shows that it can be used in seismic design, and provides a design basis for the performance-based design of light steel system buildings.

Rapid Detection of Aspergillus fumigatus Using Multiple Cross Displacement Amplification Combined With Nanoparticles-Based Lateral Flow.

Aspergillus fumigatus is an opportunistic, ubiquitous, saprophytic mold which can cause infection in the lungs, nose, eyes, brain, and bones in humans, especially in immunocompromised patients. However, it is difficult to diagnose A. fumigatus infection quickly. Here, we introduce a new detection method, namely multiple cross displacement amplification (MCDA) combined with nanoparticle-based lateral flow biosensor (LFB) (MCDA-LFB), which was proved to be fast, reliable, and simple for detecting A. fumigatus. We designed a set of 10 primers targeting the gene annexin ANXC4 of A. fumigatus. The best MCDA condition is 66 °C for 35 min. The minimum concentration that can be detected by this method was 10 fg. In the case of 100 sputum samples, 20 (20%) and 15 (15%) samples were positive by MCDA-LFB and PCR method, respectively. MCDA-LFB and traditional culture method showed the same results. Compared with the culture method, the diagnostic accuracy of MCDA-LFB can reach 100%. It showed that the MCDA-LFB method has better detection ability than the PCR method. We found that the whole process could be controlled within 60 min including the preparation of DNA (20 min), MCDA reaction (35 min) and results reporting (2 min). These results show that this assay is suitable for the rapid, sensitive and specific detection of A. fumigatus in clinical samples.

Rapid, Ultrasensitive, and Highly Specific Diagnosis of COVID-19 by CRISPR-Based Detection.

Coronavirus Disease 2019 (COVID-19), which is caused by SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), has rapidly spread leading to a global pandemic. Here, we combined multiple cross displacement amplification (MCDA) with CRISPR-Cas12a-based detection to develop a novel diagnostic test (MCCD) and applied for the diagnosis of COVID-19, called COVID-19 MCCD. The MCCD protocol conducts reverse transcription MCDA (RT-MCDA) reaction for RNA templates followed by CRISPR-Cas12a/CrRNA complex detection of predefined target sequences after which degradation of a single-strand DNA (ssDNA) molecule confirms detection of the target sequence. Two MCDA primer sets and two CrRNAs were designed targeting the opening reading frame 1a/b (ORF1ab) and nucleoprotein (N) of SARS-CoV-2. The optimal conditions include two RT-MCDA reactions at 63 °C for 35 min and a CRISPR-Cas12a/CrRNA detection reaction at 37 °C for 5 min. The COVID-19 MCCD assay can be visualized on a lateral flow biosensor (LFB) and completed within 1 h including RNA extraction (15 min), RT-MCDA reaction (35 min), CRISPR-Cas12a/CrRNA detection reaction (5 min), and reporting of result (within 2 min). The COVID-19 MCCD assay is very sensitive and detects the target gene with as low as seven copies per test and does not cross-react with non-SARS-CoV-2 templates. SARS-CoV-2 was detected in 37 of 37 COVID-19 patient samples, and nonpositive results were detected from 77 non-COVID-19 patients. Therefore, the COVID-19 MCCD assay is a useful tool for the reliable and quick diagnosis of SARS-CoV-2 infection.

Multiple Cross Displacement Amplification Linked with Nanoparticles-Based Lateral Flow Biosensor in Screening of Hepatitis B Virus in Clinical Application.

BackgroundHepatitis B virus (HBV) is a common pathogen that predominantly causes severe liver disease, and remains one of a huge challenge worldwide, especially in many resource-constrained areas. Developing a low-cost, sensitive, specific, and rapid approach for screening HBV is critical for its treatment and prevention. In the current study, a novel molecular detection approach, multiple cross displacement amplification (MCDA) coupled with polymer nanoparticle-based lateral flow biosensor (MCDA-LFB), was applied for detection of HBV in blood samples.MethodsHBV standard substance and clinical donor serum samples were collected and used for the establishment and confirmation of the HBV-MCDA-LFB assay. A set of 10 MCDA primers was designed according to HBV-specific gene S. The HBV-MCDA-LFB assay conditions, including genomic template concentration, MCDA reaction temperature and time were optimized. The sensitivity and specificity of the HBV-MCDA -LFB assay were evaluated in this report. The HBV-MCDA-LFB assay was applied to detect the HBV agent from clinical samples.ResultsThe HBV-MCDA primers based on the S gene were valid for establishment of MCDA assay. The HBV-MCDA reaction with optimized conditions could be carried out at a constant temperature 64°C for 35 min. The whole process, including sample preparation (5 min), genomic template extraction (~30 min), MCDA amplification (35 min), and LFB reading (~2 min), could be completed within 80 min. The sensitivity of this assay was 5 IU per reaction. The specificity was 100% for HBV-MCDA-LFB assay.ConclusionThese results confirmed that the HBV-MCDA-LFB is a low-cost, sensitive, specific, simple, and rapid method for detecting HBV agents. This technique has great potential to develop a point-of-care testing (POCT) method in clinical practice, especially in endemic and resource-constrained regions.

Translingual and Transcultural Reflection in Study Abroad: The Case of a Vietnamese‐American Student in Guatemala

AbstractHow multilinguals reflect on and interpret their experiences abroad as they acquire an additional language has been undertheorized in study abroad research. Multilinguals navigate multiple identities, cross linguistic and social boundaries, and employ an array of resources to make meaning—that is, they engage in translingual practice. This article presents the case of Terry—a Vietnamese‐American learner of Spanish—during a 13‐week stay in Guatemala as she navigates and reflects on her sense of self. Employing translingual practice and symbolic competence as theoretical frameworks, this study examines how Terry drew on her cultural and linguistic background to understand her experiences abroad and in turn, how an abroad experience encouraged critical self‐reflection. Through a thematic analysis of interviews, course assignments, and audio‐recorded classroom observations, the findings illustrate how an abroad curriculum that emphasized structured critical reflection and local engagement encouraged Terry's development of critical translingual competence; an awareness of the symbolic significance of meaning‐making resources across contexts; and the inextricable connections among identity, language, and culture.

Comparative study of Image Classification Algorithms

This investigation analyzed five common machine learning techniques for performing image classification included Support Vector Machines (SVM), K-Nearest Neighbor (KNN), Naïve Bayes (NB), Binary Decision Tree (BDT) and Discriminant Analysis (DA). AlexNet deep learning model was utilized to fabricate these machine learning classifiers. The structure classifiers were executed and assessed by standard execution models of Accuracy (ACC), Precision (P), Sensitivity (S), Specificity (Spe) and Area Under the ROC Curve (AUC). The five strategies were assessed utilizing 2608 histopathological pictures for head and neck cancer. The examination was directed utilizing multiple times 10-overlay cross validation. For every strategy, the pre-trained AlexNet network was utilized to separate highlights from the activation layer. The outcomes outlined that, there was no contrast between the consequences of SVM and KNN. Both have the equivalent and the higher accuracy than others were 99.98 %, though 99.81%, 97.32% and 93.68% for DA, BDT and NB, separately. The current examination shows that the SVM, KNN and DA are the best techniques for classifying our dataset images.

Development and comparison of novel multiple cross displacement amplification (MCDA) assays with other nucleic acid amplification methods for SARS-CoV-2 detection

The development of alternative isothermal amplification assays including multiple cross displacement amplification (MCDA) may address speed and portability limitations of real-time PCR (rt-PCR) methods for SARS-CoV-2 detection. We developed a novel SARS-CoV-2 MCDA assay and compared its speed and sensitivity to loop-mediated isothermal amplification (LAMP) and rt-PCR. Two MCDA assays targeting SARS-CoV-2 N gene and ORF1ab were designed. The fastest time to detection and sensitivity of MCDA was compared to LAMP and rt-PCR using DNA standards and transcribed RNA. For the N gene, MCDA was faster than LAMP and rt-PCR by 10 and 20 min, respectively with fastest time to detection at 5.2 min. rt-PCR had the highest sensitivity with the limit of detection at 10 copies/µl compared with MCDA (100 copies/µl) and LAMP (500 copies/µl). For ORF1ab, MCDA and LAMP had similar speed with fastest time to detection at 9.7 and 8.4 min, respectively. LAMP was more sensitive for ORF1ab detection with 50 copies/µl compared to MCDA (500 copies/µl). In conclusion, different nucleic acid amplification methods provide different advantages. MCDA is the fastest nucleic acid amplification method for SARS-CoV-2 while rt-PCR is the most sensitive. These advantages should be considered when determining the most suitable nucleic acid amplification methods for different applications.

The Merchant Income This study discusses the factors that influence merchant income during the Covid 19 pandemic in Surabaya in 2020

Since the Covid-19 pandemic that hit the Surabaya City certainly affects the economic changes in the Surabaya City. Clearly seen from the purchasing power parity and merchant income and salary and working hour. This impact to sale and purchase of goods and service causes changes in merchant income. This study discusses the factors that influence merchant income during the Covid 19 pandemic in Surabaya in 2020. This purpose of the study is to look at the capabilities and changes in the economy from the producer side. This study took location in Surabaya Pucang Market, with concern from the merchant income, so using multiple linier regression and Cross Section data. The independent variables in the study are output selled, salary and working hour have a positive and significant effect partially and simultaneously on dependent variable is merchant income in the Pucang Market Surabaya on 2020. 
 
 Keywords: merchant income, output selled, salary, working hour.

Simultaneous detection of Streptococcuspneumoniae and prevention of carryover contamination using multiple cross displacement amplification with Antarctic thermal sensitive uracil-DNA-glycosylase and a lateral flow biosensor.

Streptococcus pneumoniae is an important clinical pathogenic bacterium that is the primary cause of meningitis, septicemia and community-acquired pneumonia. The mortality rate of pneumococcal disease is high, especially in children younger than 5-years-old. Rapid and accurate detection of S.pneumoniae is critical for clinical diagnosis. A ply gene-based multiple cross displacement amplification (MCDA) assay, amplifying DNA under 65°Cfor 40min, was established to detect S.pneumoniae. Antarctic thermal sensitive uracil-DNA-glycosylase (AUDG) was applied to prevent carryover contamination. A lateral flow biosensor (LFB) was used to indicate the MCDA results. The ply-MCDA assay could detect as low as 10 fg of S. pneumoniae DNA and 447 colony forming units (CFU)/mL of spiked sputum samples. The analytical sensitivity of the ply-MCDA assay to detect clinical specimens was 100 times higher than that of PCR. The specificity of the ply-MCDA assay was evaluated using 15 S.pneumoniae strains and 25 non-S. pneumoniae strains, which confirmed the high selectivity of the ply-MCDA assay for S.pneumoniae. The AUDG enzyme could effectively eliminate carryover contamination and thus prevented false-positive results. In conclusion, ply-AUDG-MCDA-LFB is a simple, rapid and accurate method to detect S.pneumoniae.