G protein-coupled receptors (GPCR) represent the single most important drug targets for medical therapy, and information from genome sequencing and genomic data bases has substantially accelerated their discovery. The lack of a systematic approach either to identify the function of a new GPCR or to associate it with a cognate ligand has added to the growing number of orphan receptors. In this work we provide a novel approach to this problem using a ␤-arrestin2/green fluorescent protein conjugate (␤arr2-GFP). It provides a real-time and single cell based assay to monitor GPCR activation and GPCR-G protein-coupled receptor kinase or GPCR-arrestin interactions. Confocal microscopy demonstrates the translocation of ␤arr2-GFP to more than 15 different ligand-activated GPCRs. These data clearly support the common hypothesis that the ␤-arrestin binding of an activated receptor is a convergent step of GPCR signaling, increase by 5-fold the number of GPCRs known to interact with ␤-arrestins, demonstrate that the cytosol is the predominant reservoir of biologically active ␤-arrestins, and provide the first direct demonstration of the critical importance of G protein-coupled receptor kinase phosphorylation to the biological regulation of ␤-arrestin activity and GPCR signal transduction in living cells. The use of ␤arr2-GFP as a biosensor to recognize the activation of pharmacologically distinct GPCRs should accelerate the identification of orphan receptors and permit the optical study of their signal transduction biology intractable to ordinary biochemical methods.The G protein-coupled receptor (GPCR) 1 superfamily is growing rapidly (1-3), creating many new orphan receptors whose properties remain undefined (4 -6). 2 Currently characterized GPCRs display many distinct pharmacologies. For example, they interact with a vast array of ligands and generate intracellular signals by multiple second messenger pathways (4,8,9). Based on work with rhodopsin and the ␤ 2 -adrenergic receptor (␤ 2 AR), it has been postulated that members of the GPCR superfamily desensitize via a common mechanism involving the arresting proteins visual arrestin, ␤-arrestin1 and ␤-arrestin2 (10 -13). However, mainly due to the inherent difficulties of examining the interaction of the components mediating desensitization in their native environment or the need for purified reconstituted systems, this has not been clearly established for many GPCRs. Biochemical studies indicate that arrestins regulate GPCR signal transduction (desensitization) by binding agonist-activated receptors that have been phosphorylated by G protein-coupled receptor kinases (GRKs) (12). While the functional source of arrestin molecules targeted to receptors remains unknown, it is apparent that arrestin binding terminates signaling by interdicting receptor interaction with G proteins (12).To characterize the interaction between ␤-arrestin and different GPCRs and to assess the contribution of GRKs to this process, we examined using confocal microscopy how a green fluorescent protein...

We develop a state-of-the-art fraud prediction model using a machine learning approach. We demonstrate the value of combining domain knowledge and machine learning methods in model building. We select our model input based on existing accounting theories, but we differ from prior accounting research by using raw accounting numbers rather than financial ratios.We employ one of the most powerful machine learning methods, ensemble learning, rather than the commonly used method of logistic regression. To assess the performance of fraud prediction models, we introduce a new performance evaluation metric commonly used in ranking problems that is more appropriate for the fraud prediction task. Starting with an identical set of theory-motivated raw accounting numbers, we show that our new fraud prediction model outperforms two benchmark models by a large margin: the Dechow et al. logistic regression model based on financial ratios, and the Cecchini et al. support-vector-machine model with a financial kernel that maps raw accounting numbers into a broader set of ratios. JEL codes: C53; M41

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This work presents a wrinkled Platinum (wPt) strain sensor with tunable strain sensitivity for applications in wearable health monitoring. These stretchable sensors show a dynamic range of up to 185% strain and gauge factor (GF) of 42. This is believed to be the highest reported GF of any metal thin film strain sensor over a physiologically relevant dynamic range to date. Importantly, sensitivity and dynamic range are tunable to the application by adjusting wPt film thickness. Performance is reliable over 1000 cycles with low hysteresis after sensor conditioning. The possibility of using such a sensor for real-time respiratory monitoring by measuring chest wall displacement and correlating with lung volume is demonstrated.

TianQin is a planned space-based gravitational wave (GW) observatory consisting of three Earth-orbiting satellites with an orbital radius of about $10^5 \, {\rm km}$. The satellites will form an equilateral triangle constellation the plane of which is nearly perpendicular to the ecliptic plane. TianQin aims to detect GWs between $10^{-4} \, {\rm Hz}$ and $1 \, {\rm Hz}$ that can be generated by a wide variety of important astrophysical and cosmological sources, including the inspiral of Galactic ultra-compact binaries, the inspiral of stellar-mass black hole binaries, extreme mass ratio inspirals, the merger of massive black hole binaries, and possibly the energetic processes in the very early universe and exotic sources such as cosmic strings. In order to start science operations around 2035, a roadmap called the 0123 plan is being used to bring the key technologies of TianQin to maturity, supported by the construction of a series of research facilities on the ground. Two major projects of the 0123 plan are being carried out. In this process, the team has created a new-generation $17 \, {\rm cm}$ single-body hollow corner-cube retro-reflector which was launched with the QueQiao satellite on 21 May 2018; a new laser-ranging station equipped with a $1.2 \, {\rm m}$ telescope has been constructed and the station has successfully ranged to all five retro-reflectors on the Moon; and the TianQin-1 experimental satellite was launched on 20 December 2019—the first-round result shows that the satellite has exceeded all of its mission requirements.

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