When Ad Is Selfie: The Effect of Selfie on the Effectiveness of Ad Endorsers in Social Media

Selfie has proliferated in social media and capture the attentions from businesses. Although selfie has been leveraged into social commerce, little literature has understood and explained the effect of selfie. To solve this gap, this paper considers the effect of selfie on the effectiveness of ad endorsers and the moderating role of product type. We interpret selfie as a form of self-disclosure and study three types of ad endorsers: celebrities, experts and typical consumers. Given the nature of selfie and ad endorsers, we hypothesize that selfie enhance the effectiveness of celebrities and typical consumers, not experts. Besides, we also hypothesize that selfie improve the effectiveness of celebrities and typical consumer for hedonic product more than for utilitarian product, and experts is good for utilitarian product. Towards hypotheses in our paper, we plan to employ lab and field experimental method to test them. Potential theoretical and practical implications have been discussed

Analysis of channel estimation error of OFDM systems in rayleigh fading

In wireless OFDM applications, since the radio channel is frequency selective and time-varying, a dynamic estimation of channel must be achieved before the demodulation of the transmitted OFDM signals. As an effective approach for solving the channel estimation problems, the pilot-assisted channel estimation technique has received considerable attention in recent years. In this paper, we investigate the channel estimation error in the existing pilot-assisted channel estimation approaches in detail, a new effective channel estimation approach with lower estimation error is proposed as well

DRL-RNP: deep reinforcement learning-based optimized RNP flight procedure execution.

The required navigation performance (RNP) procedure is one of the two basic navigation specifications for the performance-based navigation (PBN) procedure as proposed by the International Civil Aviation Organization (ICAO) through an integration of the global navigation infrastructures to improve the utilization efficiency of airspace and reduce flight delays and the dependence on ground navigation facilities. The approach stage is one of the most important and difficult stages in the whole flying. In this study, we proposed deep reinforcement learning (DRL)-based RNP procedure execution, DRL-RNP. By conducting an RNP approach procedure, the DRL algorithm was implemented, using a fixed-wing aircraft to explore a path of minimum fuel consumption with reward under windy conditions in compliance with the RNP safety specifications. The experimental results have demonstrated that the six degrees of freedom aircraft controlled by the DRL algorithm can successfully complete the RNP procedure whilst meeting the safety specifications for protection areas and obstruction clearance altitude in the whole procedure. In addition, the potential path with minimum fuel consumption can be explored effectively. Hence, the DRL method can be used not only to implement the RNP procedure with a simulated aircraft but also to help the verification and evaluation of the RNP procedure

A Case of Combining Coronary Angiography and CT Angiography to Diagnose an Acute ST Segment Elevation Myocardial Infarction and a Single Coronary Artery

Coronary artery anomalies encompass a wide spectrum of clinical presentations and pathophysiological mechanisms, exhibiting signifcant heterogeneity. The majority of coronary artery anomalies exhibit negligible clinical manifestations.. Among these anomalies, the occurrence of a single left coronary artery with congenital right coronary artery agenesis represents an exceedingly rare manifestation. This case report presents the clinical profle of a 37-year-old male patient who underwent intervention and coronary CT to confrm his acute myocardial infarction and a solitary left coronary artery. Athorough understanding of coronary variations and the identifcation of coronary lesions can enable cardiovascular physicians to adopt more personalized treatment strategies for their patients