The present study is the concern of Hergé's Tintin au Congo Enunciative reading. Tintin au Congo works as an illustrative sample if we consider its artistic nature (lines which constitute drawings ...expressing movements) of the strip cartoon of developing a plot that is able to be translated into a literary work. The enunciative setting in a strip cartoon sets characters in couples (transmitters - recipients) who make use of different vignettes as an excellent communicative frame. The spatial setting takes the form of places under images printings. The temporal setting and the modal particles are placed in balloons. In fact, Tintin au Congo is a speaking work. The ingredients which animate it (pictures and texts) provoke more particular attention then what is the concern of the literary work.
Roy is humanely and professionally committed in ways that are unmatched by any other non-Palestinian scholar' - Edward W. Said Gaza, the centre of Palestinian nationalism and resistance to the ...occupation, is the linchpin of the Israeli-Palestinian conflict and the key to its resolution. Since 2005, Israel has deepened the isolation of the territory, severing it almost completely from its most vital connections to the West Bank, Israel and beyond, and has deliberately shattered its economy, transforming Palestinians from a people with political rights into a humanitarian problem. Sara Roy unpacks this process, looking at US foreign policy towards the Palestinians, as well as analysing the trajectory of Israeli policy toward Gaza, which became a series of punitive approaches meant not only to contain the Hamas regime but weaken Gazan society. Roy also reflects on Gaza's ruination from a Jewish perspective and discusses the connections between Gaza's history and her own as a child of Holocaust survivors. This book, a follow up from the renowned Failing Peace, comes from one of the world's most acclaimed writers on the region.
The stable operation of strip rolling mill is the key factor to ensure the stability of product quality. The design capability of existing domestic imported and self-developed strip rolling mills ...cannot be fully developed, and the frequent occurrence of mill vibration and operation instability problems seriously restrict the equipment capacity and the production of high-end strip products. The vibration prediction analysis method for hot strip mill based on eXtreme gradient boosting (XGBoost) and Bayesian optimization (BO) is proposed. First, an XGBoost prediction model is developed based on a self-built data set to construct a complex functional relationship between process parameters and rolling mill vibration. Second, the important hyperparameters and parameters of XGBoost are optimized using Bayesian optimization algorithm to improve the prediction accuracy, computational efficiency, and stability of the model. Third, a comprehensive comparison is made between the prediction model in this paper and other well-known machine learning benchmark models. Finally, the prediction results of the model are interpreted using the SHapley Additive exPlanations (SHAP) method. The proposed model outperforms existing models in terms of prediction accuracy, computational speed and stability. At the same time, the degree of influence of each feature on rolling mill vibration is also obtained.
Gold immunochromatographic strip (GICS) has become a popular membrane-based diagnostic tool in a variety of settings due to its sensitivity, simplicity and rapidness. This paper aimed to develop a ...framework of automatic image inspection to further improve the sensitivity as well as the quantitative performance of the GICS systems. As one of the latest methodologies in machine learning, the deep belief network (DBN) is applied, for the first time, to quantitative analysis of GICS images with hope to segment the test and control lines with a high accuracy. It is remarkable that the exploited DBN is capable of simultaneously learning three proposed features including intensity, distance and difference to distinguish the test and control lines from the region of interest that are obtained by preprocessing the GICS images. Several indices are proposed to evaluate the proposed method. The experiment results show the feasibility and effectiveness of the DBN in the sense that it provides a robust image processing methodology for quantitative analysis of GICS.
Here, we report a simple fluorescent strip sensor based on aptamer-quantum dots technology that can meet toxin monitoring demands using ochratoxin A (OTA) as a model toxin. The limit of the detection ...(LOD) for the fluorescent strip was 1.9 ng mL(-1), while the time needed for the detection is only 10 min; this conforms to the standards of World Health Organization (WHO) or better. Overall functional parameters are also better than the analogous characteristics of gold nanoparticle strips. High selectivity was maintained as well, making them suitable for the samples with complex solution composition.
The strip-shaped interferences in aeromagnetic data pose great adverse effects on data interpretation. In literature, a number of methods have been proposed to deal with this problem. However, ...existing methods still have some limitations. Inspired by the ability of deep learning techniques to extract features from data, this study presents a novel convolutional neural network (CNN)-based method to eliminate the strip-shaped interferences in aeromagnetic data. The proposed method uses the U-Net structure to establish the whole network. The use of up-down sampling and skip connection enables the network to extract multiscale strip-shaped interferences with complex distribution and morphological characteristics. The basic theoretical formulas of the network and its architecture are presented, along with the construction method of the training dataset. Afterward, the presented method is tested on several synthetic examples and real aeromagnetic data collected in Jining, Inner Mongolia, and is compared with the conventional directional cosine filter to display its advantage in accuracy. The results demonstrate that the presented method can eliminate the strip-shaped interferences in aeromagnetic data effectively while preserving the features due to the real geological sources without any subjective parameters.
The study described here is aimed at illuminating deformation mechanism involved in Twin-roll Thin Strip Casting Process (TRSC) with respect to high-permeability 6.5 wt.% Si electrical strip ...(6.5 wt.% Si strip) in terms of crystal plasticity (CP) theory, and a Visco-plastic Self-consistent model (VPSC) was utilized to explore the deformation mechanism by applying crystallographic orientation (OR) analysis. Results underscore that the activation of overall potential single slip system with regard to studied 6.5 wt.% Si strip including {110} , {112} as well as {123} can contribute to the OR conversion from Cube texture to Rotated-Cube texture, α-fiber texture as well as γ-fiber texture, while with different evolution rate during deformation. The potential multi-slip system of {112} +{123} with average number of activated slip system per grain ~9.1–9.4, and multi-slip system of {110} +{112} +{123} with average number of activated slip system per grain ~10.4–10.8 are identified to be the predominant slip systems during deformation by comparing to the actual OR features obtained from TRSC-processed 6.5 wt.% Si strip. The CP-based method proposed in present study is deemed as a reference to investigate deformation behavior involved in the other semi-solid forming process.
Deep learning algorithms have gained widespread usage in defect detection systems. However, existing methods are not satisfied for large-scale applications on surface defect detection of strip steel. ...In this paper, we propose a precise and efficient detection model, named CABF-YOLO, based on the YOLOX for strip steel surface defects. Firstly, we introduce the Triplet Convolutional Coordinate Attention (TCCA) module in the backbone of the YOLOX. By factorizing the pooling operation, the TCCA module can accurately capture cross-channel features to identify the location information of defects. Secondly, we design a novel Bidirectional Fusion (BF) strategy in the neck of the YOLOX. The BF strategy enhances the fusion of low-level and high-level semantic information to obtain fine-grained information. Lastly, the original bounding box loss function is replaced by the EIoU loss function. In the EIoU loss function, the penalty term is redefined to consider the overlap area, central point, and side length of the required regressions to accelerate the convergence rate and localization accuracy. On the benchmark NEU-DET dataset and GC10-DET dataset, the experimental results show that the CABF-YOLO achieves superior performance compared with other comparison models and satisfies the real-time detection requirement of industrial production.
Avian leukemia is an infectious tumorous disease of chickens caused by subgroup A of the avian leukemia virus (ALV-A), which mainly causes long-term viremia, slow growth, immune suppression, ...decreased production performance, multi-tissue tumors, and even death. The infection rate of this disease is very high in chicken herds in China, causing huge economic losses to the poultry industry every year. We successfully expressed the specific antigen protein of ALV (P27) through recombinant protein technology and screened a pair of highly sensitive monoclonal antibodies (mAbs) through mouse immunity, cell fusion, and antibody pairing. Based on this pair of antibodies, we established a dual antibody sandwich ELISA and gold nanoparticle immunochromatographic strip (AuNP-ICS) detection method. In addition, the parameters of the dual antibody sandwich ELISA and AuNP-ICS were optimized under different reaction conditions, which resulted in the minimum detection limits of 0.2 ng mL
−1
and 1.53 ng ml
−1
, respectively. Commonly available ELISA and AuNP-ICS products on the market were compared, and we found that our established immune rapid chromatography had higher sensitivity. This established AuNP-ICS had no cross-reactivity with Influenza A (H1N1), Influenza A (H9N2), respiratory syncytial virus (RSV), varicella-zoster virus (VZV),
Listeria monocytogenes
listeriolysin (LLO), and
Staphylococcal enterotoxin
SED or SEC. Finally, the established AuNP-ICS was used to analyze 35 egg samples, and the results showed 5 positive samples and 30 negative samples. The AuNP-ICS rapid detection method established by our group had good specificity, high sensitivity, and convenience, and could be applied to the clinical sample detection of ALV-A.
A gold nanoparticle-based immunochromatographic test strip for the detection of avian leukosis virus P27 antigen in egg white samples.
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