Ape+: A Faster Ape with Static Model Guided Exploration

Ape is the state-of-the-art Android GUI testing tool, which implements a dynamic model internally to guide the testing process. At the time of writing, Ape was one of the most effective Android testing tools. Ape’s interactions with Android devices partially rely on private APIs, which made it difficult to support newer Android versions. Aiming to solve this problem, we adopted Appium as the interaction layer. However, the introduction of Appium distorted Ape into a server-client structure, which brought a huge overhead and severely affected the efficiency. Besides, Ape naturally tries to test all widgets. Neverthe- less, in scenarios where an application only needs to be partially tested, such strategy limits the effectiveness due to the inability to prioritize activities of interest. In this study, we introduce Ape+, which boosts the efficiency of Ape but avoids using private Android APIs. We reconstruct Ape as a monolithic on-device testing tool by re- placing Appium, the communication layer between Ape and the device, with UiAutomator. We solved technical challenges, such as supporting drag function and fetching current ac- tivity names, and experiments show that efficiency improvements among the applications are between 10% to 40% compare to Ape with Appium. We also analyze different static analyses tools to find the one whose static model is informative enough to bring extra knowledge to Ape for activity prioritization. Using in- strumentation, we improve the accuracy of widget matching, which is an essential step to bridge the gap between the dynamic model and the static one and combine both synergis- tically. We also introduce a priority decay strategy to mitigate false information produced by static analysis, and a path finding algorithm to help Ape+ navigate between activities using both models. Our experiments show, for two selected applications with informative models, Ape+ is able to cover every activity 37% and 57% faster. We believe that Ape+ is a decent testbed with maintainability and extensibility for conducting research on automated Android GUI testing in the future

A comment on "Ab initio calculations of pressure-dependence of high-order elastic constants using finite deformations approach" by I. Mosyagin, A.V. Lugovskoy, O.M. Krasilnikov, Yu.Kh. Vekilov, S.I. Simak and I.A. Abrikosov

Recently, I. Mosyagin, A.V. Lugovskoy, O.M. Krasilnikov, Yu.Kh. Vekilov, S.I. Simak and I.A. Abrikosov in the paper: "Ab initio calculations of pressure-dependence of high-order elastic constants using finite deformations approach"[Computer Physics Communications 220 (2017) 2030] presented a description of a technique for ab initio calculations of the pressure dependence of second- and third-order elastic constants. Unfortunately, the work contains serious and fundamental flaws in the field of finite-deformation solid mechanics.Comment: 3 pages, 0 figure

The transition from incoherent to coherent random laser in defect waveguide based on organic/inorganic hybrid laser dye

This paper systematically demonstrated a variety of experimental phenomena of random lasers (RLs) of N,N′-di-(3-(isobutyl polyhedral oligomeric silsesquioxanes)propyl) perylene diimide (DPP) organic/inorganic hybrid laser dye, which is composed of perylene diimide (PDI) as gain media and polyhedral oligomeric silsesquioxanes (POSS) as scattering media at a mole ratio of 1:2. In this work, we observe the transition from incoherent RL in the DPP-doped solutions and polymer membrane systems using dip-coating method to coherent RL in the polymer membrane system with defect waveguide using semi-polymerization (SP) coating method. Meanwhile, we found that the hybrid dye-DPP has a long lasing lifetime compared with the traditional laser dyes, which indicates that the POSS group can suppress the photo-bleaching effect to extend the working life of laser dyes

Efficient and ultra-stable perovskite light-emitting diodes

Perovskite light-emitting diodes (PeLEDs) have emerged as a strong contender for next-generation display and information technologies. However, similar to perovskite solar cells, the poor operational stability remains the main obstacle toward commercial applications. Here we demonstrate ultra-stable and efficient PeLEDs with extraordinary operational lifetimes (T50) of 1.0x10^4 h, 2.8x10^4 h, 5.4x10^5 h, and 1.9x10^6 h at initial radiance (or current densities) of 3.7 W/sr/m2 (~5 mA/cm2), 2.1 W/sr/m2 (~3.2 mA/cm2), 0.42 W/sr/m2 (~1.1 mA/cm2), and 0.21 W/sr/m2 (~0.7 mA/cm2) respectively, and external quantum efficiencies of up to 22.8%. Key to this breakthrough is the introduction of a dipolar molecular stabilizer, which serves two critical roles simultaneously. First, it prevents the detrimental transformation and decomposition of the alpha-phase FAPbI3 perovskite, by inhibiting the formation of lead and iodide intermediates. Secondly, hysteresis-free device operation and microscopic luminescence imaging experiments reveal substantially suppressed ion migration in the emissive perovskite. The record-long PeLED lifespans are encouraging, as they now satisfy the stability requirement for commercial organic LEDs (OLEDs). These results remove the critical concern that halide perovskite devices may be intrinsically unstable, paving the path toward industrial applications.Comment: This is a preprint of the paper prior to peer review. New and updated results may be available in the final version from the publishe

Social Integration and Residence Intention of Foreigners in Western China: Evidence from Xi’an

Since “Belt and Road Initiative” (BRI) of 2014, the number of foreigners in China has increased rapidly and China has become an importing country for immigrants, a change ongoing since the beginning of the 21st century. To respond to the rapidly increasing number of foreigners in China, the government frequently revised the immigration policies and issued new regulations for foreigners. However, scholars understand very little about how the foreigners perceive their integration into Chinese society or decide to pursue long-term residency or lawful permanent resident status. While some pioneering studies touch on this, with samples from the coastal megacities, no empirical evidence has been collected from smaller, inner cities. Three new findings about the foreigners in Xi’an, a major city in western China, fill this literature gap. First, the level of subjective social integration is largely influenced by the local networks. Second, the level of objective social integration depends largely on local and hometown networks. Third, the intention to obtain long-term and permanent residency in China is more evident in those foreigners who come from countries covered by the BRI and who consider China to be a better place to live than their home country

Predicting liposome formulations by the integrated machine learning and molecular modeling approaches

Liposome is one of the most widely used carriers for drug delivery because of the great biocompatibility and biodegradability. Due to the complex formulation components and preparation process, formulation screening mostly relies on trial-and-error process with low efficiency. Here liposome formulation prediction models have been built by machine learning (ML) approaches. The important parameters of liposomes, including size, polydispersity index (PDI), zeta potential and encapsulation, are predicted individually by optimal ML algorithm, while the formulation features are also ranked to provide important guidance for formulation design. The analysis of key parameter reveals that drug molecules with logS [-3, -6], molecular complexity [500, 1000] and XLogP3 (≥2) are priority for preparing liposome with higher encapsulation. In addition, naproxen (NAP) and palmatine HCl (PAL) represented the insoluble and water-soluble molecules are prepared as liposome formulations to validate prediction ability. The consistency between predicted and experimental value verifies the satisfied accuracy of ML models. As the drug properties are critical for liposome particles, the molecular interactions and dynamics of NAP and PAL liposome are further investigated by coarse-grained molecular dynamics simulations. The modeling structure reveals that NAP molecules could distribute into lipid layer, while most PAL molecules aggregate in the inner aqueous phase of liposome. The completely different physical state of NAP and PAL confirms the importance of drug properties for liposome formulations. In summary, the general prediction models are built to predict liposome formulations, and the impacts of key factors are analyzed by combing ML with molecular modeling. The availability and rationality of these intelligent prediction systems have been proved in this study, which could be applied for liposome formulation development in the future