SHA-SCP: A UI Element Spatial Hierarchy Aware Smartphone User Click Behavior Prediction Method

Predicting user click behavior and making relevant recommendations based on the user's historical click behavior are critical to simplifying operations and improving user experience. Modeling UI elements is essential to user click behavior prediction, while the complexity and variety of the UI make it difficult to adequately capture the information of different scales. In addition, the lack of relevant datasets also presents difficulties for such studies. In response to these challenges, we construct a fine-grained smartphone usage behavior dataset containing 3,664,325 clicks of 100 users and propose a UI element spatial hierarchy aware smartphone user click behavior prediction method (SHA-SCP). SHA-SCP builds element groups by clustering the elements according to their spatial positions and uses attention mechanisms to perceive the UI at the element level and the element group level to fully capture the information of different scales. Experiments are conducted on the fine-grained smartphone usage behavior dataset, and the results show that our method outperforms the best baseline by an average of 10.52%, 11.34%, and 10.42% in Top-1 Accuracy, Top-3 Accuracy, and Top-5 Accuracy, respectively

Miniature narrow-linewidth 1 {\mu}m Laser

Self-injection locking scheme has the potential to narrow the linewidth of lasers in a compact setup. Here, we report a narrow linewidth laser source near 1 {\mu}m by self-injection locking scheme using a Fabry-Perot (FP) hollow resonator with a high-quality factor (Q>10^8). The measured fundamental linewidth of the laser is 41 Hz, and a coarse tuning range over 5.5 nm is achieved by changing the driving current of the laser source. Meanwhile, a fine-tuning range of 373 MHz is achieved without mode hops by changing the voltage applied to the PZT on the resonator. More importantly, benefiting from the low thermal refractive noise and low thermal expansion of the FP hollow resonator, the beat-note linewidth and the frequency Allan deviation are measured to be 510.3 Hz in and 10^-11 (1s averaging time), respectively, by using a fully stabilized frequency comb as reference. Such a high-performance laser is fully integrated with a palm-sized package (52.3 mL) for field-deployable applications

Numerical simulation of thermal stratification in Lake Qiandaohu using an improved WRF-Lake model

Lake thermal stratification is important for regulating lake environments and ecosystems and is sensitive to climate change and human activity. However, numerical simulation of coupled hydrodynamics and heat transfer processes in deep lakes using one-dimensional lake models remains challenging because of the insufficient representation of key parameters. In this study, Lake Qiandaohu, a deep and warm monomictic reservoir, was used as an example to investigate thermal stratification via an improved parameterization scheme of the Weather Research and Forecast (WRF)-Lake. A comparison with in situ observations demonstrated that the default WRF-Lake model was able to simulate well the seasonal variation of the lake thermal structure. However, the simulations exhibited cold biases in lake surface water temperature (LSWT) throughout the year while generating weaker stratification in summer, thereby leading to an earlier cooling period in autumn. With an improved parameterization (i.e., via determination of initial lake water temperature profiles, light extinction coefficients, eddy diffusion coefficients and surface roughness lengths), the modified WRF-Lake model was able to better simulate LSWT and thermal stratification. Critically, employing realistic initial conditions for lake water temperature is essential for producing realistic hypolimnetic water temperatures. The use of time-dependent light extinction coefficients resulted in a deep thermocline and warm LSWT. Enlarging eddy diffusivity led to stronger mixing in summer and further influenced autumn cooling. The parameterized surface roughness lengths mitigated the excessive turbulent heat loss at the lake surface, improved the model performance in simulating LSWT, and generated a warm mixed layer. This study provides guidance on model parameterization for simulating the thermal structure of deep lakes and advances our understanding of the strength and revolution of lake thermal stratification under seasonal changes

Ocean Acidification Impairs Foraging Behavior by Interfering With Olfactory Neural Signal Transduction in Black Sea Bream, Acanthopagrus schlegelii

In recent years, ocean acidification (OA) caused by oceanic absorption of anthropogenic carbon dioxide (CO2) has drawn worldwide concern over its physiological and ecological effects on marine organisms. However, the behavioral impacts of OA and especially the underlying physiological mechanisms causing these impacts are still poorly understood in marine species. Therefore, in the present study, the effects of elevated pCO2 on foraging behavior, in vivo contents of two important neurotransmitters, and the expression of genes encoding key modulatory enzymes from the olfactory transduction pathway were investigated in the larval black sea bream. The results showed that larval sea breams (length of 4.71 ± 0.45 cm) reared in pCO2 acidified seawater (pH at 7.8 and 7.4) for 15 days tend to stall longer at their acclimated zone and swim with a significant slower velocity in a more zigzag manner toward food source, thereby taking twice the amount of time than control (pH at 8.1) to reach the food source. These findings indicate that the foraging behavior of the sea bream was significantly impaired by ocean acidification. In addition, compared to a control, significant reductions in the in vivo contents of γ-aminobutyric acid (GABA) and Acetylcholine (ACh) were detected in ocean acidification-treated sea breams. Furthermore, in the acidified experiment groups, the expression of genes encoding positive regulators, the olfaction-specific G protein (Golf) and the G-protein signaling 2 (RGS2) and negative regulators, the G protein-coupled receptor kinase (GRK) and arrestin in the olfactory transduction pathway were found to be significantly suppressed and up-regulated, respectively. Changes in neurotransmitter content and expression of olfactory transduction related genes indicate a significant disruptive effect caused by OA on olfactory neural signal transduction, which might reveal the underlying cause of the hampered foraging behavior