On or off topic? Understanding the effects of issue-related political targeted ads.

Whilst data-driven strategies are allegedly prevalent in political campaigns, evidence regarding their actual effectiveness is scarce. This study investigates, from an individual perspective, the effect of issue congruency in political ads on immediate responses and voting behaviors. To reach our goal, we combined different types of data collection: mobile experience sampling method (mESM), panel survey, and content analysis. The combined approach allowed us to effectively study targeted ads within the cross-device and cross-platform environment. The results showed that voters perceive online political ads that are about a topic that they care about as more interesting, informative, and persuasive regardless of their partisanship. This positive ad perception subsequently leads to a higher probability of voting for the promoted party in the ad. We also found that an ad discussing a topic in line with the receiver's concerns positively affects the evaluation of the promoted party in the ad only when the party is already favored by the voter. Taken together, this study provides insights into the conditional effectiveness of data-driven strategies in political campaigns.

MRI-Based Artificial Intelligence in Rectal Cancer.

Rectal cancer (RC) accounts for approximately one-third of colorectal cancer (CRC), with death rates increasing in patients younger than 50 years old. Magnetic resonance imaging (MRI) is routinely performed for tumor evaluation. However, the semantic features from images alone remain insufficient to guide treatment decisions. Functional MRIs are useful for revealing microstructural and functional abnormalities and nevertheless have low or modest repeatability and reproducibility. Therefore, during the preoperative evaluation and follow-up treatment of patients with RC, novel noninvasive imaging markers are needed to describe tumor characteristics to guide treatment strategies and achieve individualized diagnosis and treatment. In recent years, the development of artificial intelligence (AI) has created new tools for RC evaluation based on MRI. In this review, we summarize the research progress of AI in the evaluation of staging, prediction of high-risk factors, genotyping, response to therapy, recurrence, metastasis, prognosis, and segmentation with RC. We further discuss the challenges of clinical application, including improvement in imaging, model performance, and the biological meaning of features, which may also be major development directions in the future. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

Engineering Mechanical Compliance of an Organic Compound toward Flexible Crystal Lasing Media.

Recently, organic crystals with mechanical flexibility have been emerging as a hot research topic due to their great potentials in flexible optoelectronics. However, organic crystals exhibiting elastic bending or plastic bending are relatively rare. In this study, we proposed a strategy to improve the probability of crystal flexibility as well as to regulate the mechanical properties by controlling polymorphism. Three different emissive organic polymorphs Cry-G, Cry-Y, and Cry-O with elastic, plastic, and brittle natures, respectively, were obtained by fine-tuning crystallization conditions of a diaryl ß-diketone compound. Cry-G was found to transduce light and amplify the self-waveguided emission efficiently along the crystal body in the elastically bent state, demonstrating its multifunctional applications in flexible optical devices. This study is of great scientific significance not only to engineer mechanical compliance of organic crystals but also to highlight the utility of "crystal flexibility".