A Study of Different Modes’ Synergy from the Perspective of Multimodal Discourse: Taking Apple Product Launch Conferences as an Example

With the development of science and technology and media information great changes have taken place in communication methods Images music gestures or written language all play important roles in daily communication besides of spoken language This study selects Apple Event 2018 as the research subject based on Halliday s Systemic Functional Linguistics Framework and Zhang Delu s modal synergy theory to analyze the selection combination relationship and multimodal application of modes in product launch conference in order to realize the interpersonal functional meaning of Halliday s Metafunction Theory under the coordination of multiple mode

Highly efficient CO2 capture with simultaneous iron and CaO recycling for the iron and steel industry

An efficient CO2 capture process has been developed by integrating calcium looping (CaL) and waste recycling technologies into iron and steel production. A key advantage of such a process is that CO2 capture is accompanied by simultaneous iron and CaO recycling from waste steel slag. High-purity CaO-based CO2 sorbents, with CaO content as high as 90 wt%, were prepared easily via acid extraction of steel slag using acetic acid. The steel slag-derived CO2 sorbents exhibited better CO2 reactivity and slower (linear) deactivation than commercial CaO during calcium looping cycles. Importantly, the recycling efficiency of iron from steel slag with an acid extraction is improved significantly due to a simultaneous increase in the recovery of iron-rich materials and the iron content of the materials recovered. High-quality iron ore with iron content of 55.1–70.6% has been recovered from waste slag in this study. Although costing nearly six times as much as naturally derived CaO in the purchase of feedstock, the final cost of the steel slag-derived, CaO-based sorbent developed is compensated by the byproducts recovered, i.e., high-purity CaO, high-quality iron ore, and acetone. This could reduce the cost of the steel slag-derived CO2 sorbent to 57.7 € t−1, appreciably lower than that of the naturally derived CaO. The proposed integrated CO2 capture process using steel slag-derived, CaO-based CO2 sorbents developed appears to be cost-effective and promising for CO2 abatement from the iron and steel industry

Inherent potential of steelmaking to contribute to decarbonisation targets via industrial carbon capture and storage

Accounting for ~8% of annual global CO2 emissions, the iron and steel industry is expected to undertake the largest contribution to industrial decarbonisation. Despite the launch of several national and regional programmes for low-carbon steelmaking, the techno-economically feasible options are still lacking. Here, based on the carbon capture and storage (CCS) strategy, we propose a new decarbonisation concept which exploits the inherent potential of the iron and steel industry through calcium-looping lime production. We find that this concept allows steel mills to reach the 2050 decarbonisation target by 2030. Moreover, only this concept is revealed to exhibit a CO2 avoidance cost (12.5–15.8 €2010/t) lower than the projected CO2 trading price in 2020, whilst the other considered options are not expected to be economically feasible until 2030. We conclude that the proposed concept is the best available option for decarbonisation of this industrial sector in the mid- to long-term

Identification of Prognostic Genes and Gene Sets for Early-Stage Non-Small Cell Lung Cancer Using Bi-Level Selection Methods

In contrast to feature selection and gene set analysis, bi-level selection is a process of selecting not only important gene sets but also important genes within those gene sets. Depending on the order of selections, a bi-level selection method can be classified into three categories – forward selection, which first selects relevant gene sets followed by the selection of relevant individual genes; backward selection which takes the reversed order; and simultaneous selection, which performs the two tasks simultaneously usually with the aids of a penalized regression model. To test the existence of subtype-specific prognostic genes for non-small cell lung cancer (NSCLC), we had previously proposed the Cox-filter method that examines the association between patients’ survival time after diagnosis with one specific gene, the disease subtypes, and their interaction terms. In this study, we further extend it to carry out forward and backward bi-level selection. Using simulations and a NSCLC application, we demonstrate that the forward selection outperforms the backward selection and other relevant algorithms in our setting. Both proposed methods are readily understandable and interpretable. Therefore, they represent useful tools for the researchers who are interested in exploring the prognostic value of gene expression data for specific subtypes or stages of a disease

Polarization State Manipulation of Electromagnetic Waves with Metamaterials and Its Applications in Nanophotonics

Polarization state is an important characteristic of electromagnetic waves. The arbitrary control of the polarization state of such wave has attracted great interest in the scientific community because of the wide range of modern optical applications that such control can afford. Recent advances in metamaterials provide an alternative method of realizing arbitrary manipulation of polarization state of electromagnetic waves in nanoscale via ultrathin, miniaturized, and easily integrable designs. In this chapter, we give a review of recent developments on polarization state manipulation of electromagnetic waves in metamaterials and discuss their applications in nanophotonics, such as polarization converter, wavefront controller, information coding, and so on

Comparing the diagnostic accuracy of five common tumour biomarkers and CA19-9 for pancreatic cancer: a protocol for a network meta-analysis of diagnostic test accuracy

Introduction: Surgical resection is the only curative treatment for patients with resectable pancreatic cancer. Unfortunately, 80%–85% of patients present with locally advanced or metastatic unresectable pancreatic cancer at the time of diagnosis. Detection of pancreatic cancer at early stages remains a great challenge due to lack of accurate detection tests. Recommendations in existing clinical practice guidelines on early diagnosis of pancreatic cancer are inconsistent and based on limited evidence. Most of them endorse measuring serum CA19-9 as a complementary test, but also state that it is not recommended for diagnosing early pancreatic cancer. There are currently no other tumour-specific markers recommended for diagnosing early pancreatic cancer. This study aims to evaluate and compare the accuracy of five common tumour biomarkers (CA242,carcino-embryonic antigen (CEA)), CA125, microRNAs and K-ras gene mutation) and CA19-9 and their combinations for diagnosing pancreatic cancer using network meta-analysis method, and to rank these tests using a superiority index. Methods and analysis: PubMed, EMBASE and the Cochrane Central Register of Controlled Trials will be searched from inception to April 2017. The search will include the above-mentioned tumour biomarkers for diagnosing pancreatic cancer, including CA19-9. The risk of bias for each study will be independently assessed as low, moderate or high using criteria adapted from the Quality Assessment of Diagnostic Accuracy Studies 2. Network meta-analysis will be performed using STATA V.12.0 and R software V.3.4.1. The competing diagnostic tests will be ranked by a superiority index. Ethics and dissemination: Ethical approval and patient consent are not required since this study is a network meta-analysis based on published studies. The results of this network meta-analysis will be submitted to a peer-reviewed journal for publication