Personalized Recommendation for Balancing Content Generation and Usage on Two-Sided Entertainment Platforms

Online entertainment platforms such as Youtube host a vast amount of user-generated content (UGC). The unique feature of two-sided UGC entertainment platforms is that creators’ content generation and users’ content usage can influence each other. However, traditional recommender systems often emphasize content usage but ignore content generation, leading to a misalignment between these two goals. To address the challenge, this paper proposes a prescriptive uplift framework to balance content generation and usage through personalized recommendations. Specifically, we first predict the heterogeneous treatment effects (HTEs) of recommended contents on creators’ content generation and users’ content usage, then consider these two predicted HTEs simultaneously in an optimization model to determine the recommended contents for each user. Using a large-scale real-world dataset, we demonstrate that the proposed recommendation method better balances content generation and usage and brings a 42% increase in participants’ activity compared to existing benchmark methods

Detector induced anisotropies on the angular distribution of gravitational wave sources and opportunities of constraining horizon scale anisotropies

The cosmological principle has been verified using electromagnetic (EM) observations. However its verification with high accuracy is challenging due to various foregrounds and selection effects, and possible violation of the cosmological principle has been reported in the literature. In contrast, gravitational wave (GW) observations are free of these foregrounds and related selection biases. This may enable future GW experiments to test the cosmological principle robustly with full sky distribution of millions of standard bright/dark sirens. However, the sensitivities of GW detectors are highly anisotropic, resulting in significant instrument induced anisotropies in the observed GW catalog. We investigate these instrumental effects for 3rd generation detector networks in term of multipoles $a_{\ell m}$ of the observed GW source distribution, using Monte Carlo simulations. (1) We find that the instrument induced anisotropy primarily exists at the $m=0$ modes on large scales ($\ell \lesssim 10$), with amplitude $\langle |a_{\ell 0}|^2 \rangle \sim 10^{-3}$ for two detectors (ET-CE) and $\sim 10^{-4}$ for three detectors (ET-2CE). This anisotropy is correlated with the sky distribution of signal-to-noise ratio (SNR) and localization accuracy. Such anisotropy sets a lower limit on the detectable cosmological $a_{\ell 0}$. (2) However, we find that the instrument induced anisotropy is efficiently canceled by rotation of the Earth in $m\neq 0$ components of $a_{\ell m}$. Therefore $a_{\ell m}$ ($m\neq 0$) are clean windows to detect cosmological anisotropies. (3) We investigate the capability of 3rd generation GW experiments to measure the cosmic dipole. Through Monte Carlo simulations, we find that cosmic dipole with an amplitude of $\sim 10^{-2}$ reported in the literature can be detected/ruled out by ET-CE and ET-2CE robustly, through the measurement of $a_{11}$.Comment: 7 pages, 6 figures, submitted to MNRA

Quantum Circuit AutoEncoder

Quantum autoencoder is a quantum neural network model for compressing information stored in quantum states. However, one needs to process information stored in quantum circuits for many tasks in the emerging quantum information technology. In this work, generalizing the ideas of classical and quantum autoencoder, we introduce the model of Quantum Circuit AutoEncoder (QCAE) to compress and encode information within quantum circuits. We provide a comprehensive protocol for QCAE and design a variational quantum algorithm, varQCAE, for its implementation. We theoretically analyze this model by deriving conditions for lossless compression and establishing both upper and lower bounds on its recovery fidelity. Finally, we apply varQCAE to three practical tasks and numerical results show that it can effectively (1) compress the information within quantum circuits, (2) detect anomalies in quantum circuits, and (3) mitigate the depolarizing noise in quantum devices. This suggests that our algorithm is potentially applicable to other information processing tasks for quantum circuits.Comment: 13 pages, 7 figure

Changes in the Interstitial Cells of Cajal and Immunity in Chronic Psychological Stress Rats and Therapeutic Effects of Acupuncture at the Zusanli Point (ST36)

Now, chronic psychological stress (CPS) related diseases are increasing. Many CPS patients have gastrointestinal complaints, immune suppression, and immune imbalance. Increasing evidence is indicating that acupuncture (AP) at the Zusanli point (ST36) can alleviate functional gastrointestinal disorders (FGID), immune suppression, and immune imbalance. However, few studies have investigated the potential mechanisms. In this study, CPS rat models were established, and electroacupuncture (EA) at ST36 was done for CPS rats. Daily food intake, weight, intestinal sensitivity, the morphology of interstitial cell of Cajal (ICC) in the small intestine, and serum indexes were measured. The study found that, in CPS rats, EA at ST36 could improve food intake, weight, visceral hypersensitivity, and immunity; in CPS rats, in small intestine, the morphology of ICCs was abnormal and the number was decreased, which may be part causes of gastrointestinal motility dysfunction. EA at ST36 showed useful therapeutic effects. The mechanisms may be partially related to its repairing effects on ICCs damages; in CPS rats, there were immune suppression and immune imbalance, which may be part causes of visceral hypersensitivity. EA at ST36 showed useful therapeutic effects. The mechanisms may be partially related to its regulation on immunity

Material Removal Mechanism and Force Model of Nanofluid Minimum Quantity Lubrication Grinding

Numerous researchers have developed theoretical and experimental approaches to force prediction in surface grinding under dry conditions. Nevertheless, the combined effect of material removal and plastic stacking on grinding force model has not been investigated. In addition, predominant lubricating conditions, such as flood, minimum quantity lubrication (MQL), and nanofluid minimum quantity lubrication (NMQL), have not been considered in existing force models. In this study, material removal mechanism under different lubricating conditions was researched. An improved theoretical force model that considers material removal and plastic stacking mechanisms was presented. Grain states, including cutting and ploughing, are determined by cutting efficiency (β). The influence of lubricating conditions was also considered in the proposed force model. Simulation was performed to obtain the cutting depth (a g) of each “dynamic active grain.” Parameter β was introduced to represent the plastic stacking rate and determine the force algorithms of each grain. The aggregate force was derived through the synthesis of each single-grain force. Finally, pilot experiments were conducted to test the theoretical model. Findings show that the model’s predictions were consistent with the experimental results, with average errors of 4.19% and 4.31% for the normal and tangential force components, respectively

Biological Bone Micro Grinding Temperature Field under Nanoparticle Jet Mist Cooling

Clinical neurosurgeons used micro grinding to remove bone tissues, and drip irrigation-type normal saline (NS) is used with low cooling efficiency. Osteonecrosis and irreversible thermal neural injury caused by excessively high grinding temperature are bottleneck problems in neurosurgery and have severely restricted the application of micro grinding in surgical procedures. Therefore, a nanoparticle jet mist cooling (NJMC) bio-bone micro grinding process is put forward in this chapter. The nanofluid convective heat transfer mechanism in the micro grinding zone is investigated, and heat transfer enhancement mechanism of solid nanoparticles and heat distribution mechanism in the micro grinding zone are revealed. On this basis, a temperature field model of NJMC bio-bone micro grinding is established. An experimental platform of NJMC bio-bone micro grinding is constructed, and bone micro grinding force and temperatures at different measuring points on the bone surface are measured. The results indicated that the model error of temperature field is 6.7%, theoretical analysis basically accorded with experimental results, thus certifying the correctness of the dynamic temperature field in NJMC bio-bone micro grinding

Leakage current simulations of Low Gain Avalanche Diode with improved Radiation Damage Modeling

We report precise TCAD simulations of IHEP-IME-v1 Low Gain Avalanche Diode (LGAD) calibrated by secondary ion mass spectroscopy (SIMS). Our setup allows us to evaluate the leakage current, capacitance, and breakdown voltage of LGAD, which agree with measurements' results before irradiation. And we propose an improved LGAD Radiation Damage Model (LRDM) which combines local acceptor removal with global deep energy levels. The LRDM is applied to the IHEP-IME-v1 LGAD and able to predict the leakage current well at -30 $^{\circ}$C after an irradiation fluence of $\Phi_{eq}=2.5 \times 10^{15} ~n_{eq}/cm^{2}$. The charge collection efficiency (CCE) is under development

A review on the heat and mass transfer phenomena in nanofluid coolants with special focus on automotive applications

Engineered suspensions of nanosized particles (nanofluids) are characterized by superior thermal properties. Due to the increasing need for ultrahigh performance cooling in many industries, nanofluids have been widely investigated as next-generation coolants. However, the multiscale nature of nanofluids implies nontrivial relations between their design characteristics and the resulting thermo-physical properties, which are far from being fully understood. This pronounced sensitivity is the main reason for some contradictory results among both experimental evidence and theoretical considerations presented in the literature. In this Review, the role of fundamental heat and mass transfer mechanisms governing thermo-physical properties of nanofluids is assessed, from both experimental and theoretical point of view. Starting from the characteristic nanoscale transport phenomena occurring at the particle-fluid interface, a comprehensive review of the influence of geometrical (particle shape, size and volume concentration), physical (temperature) and chemical (particle material, pH and surfactant concentration in the base fluid) parameters on the nanofluid properties was carried out. Particular focus was devoted to highlight the advantages of using nanofluids as coolants for automotive heat exchangers, and a number of design guidelines was suggested for balancing thermal conductivity and viscosity enhancement in nanofluids. This Review may contribute to a more rational design of the thermo-physical properties of particle suspensions, therefore easing the translation of nanofluid technology from small-scale research laboratories to large-scale industrial applications

Harmonizing Multi-Source Remote Sensing Images for Summer Corn Growth Monitoring

Continuous monitoring of crop growth status using time-series remote sensing image is essential for crop management and yield prediction. The growing season of summer corn in the North China Plain with the period of rain and hot, which makes the acquisition of cloud-free satellite imagery very difficult. Therefore, we focused on developing image datasets with both a high temporal resolution and medium spatial resolution by harmonizing the time-series of MOD09GA Normalized Difference Vegetation Index (NDVI) images and 30-m-resolution GF-1 WFV images using the improved Kalman filter model. The harmonized images, GF-1 images, and Landsat 8 images were then combined and used to monitor the summer corn growth from 5th June to 6th October, 2014, in three counties of Hebei Province, China, in conjunction with meteorological data and MODIS Evapotranspiration Data Set. The prediction residuals ( Δ P R K ) in NDVI between the GF-1 observations and the harmonized images was in the range of −0.2 to 0.2 with Gauss distribution. Moreover, the obtained phenological curves manifested distinctive growth features for summer corn at field scales. Changes in NDVI over time were more effectively evaluated and represented corn growth trends, when considered in conjunction with meteorological data and MODIS Evapotranspiration Data Set. We observed that the NDVI of summer corn showed a process of first decreasing and then rising in the early growing stage and discuss how the temperature and moisture of the environment changed with the growth stage. The study demonstrated that the synthesized dataset constructed using this methodology was highly accurate, with high temporal resolution and medium spatial resolution and it was possible to harmonize multi-source remote sensing imagery by the improved Kalman filter for long-term field monitoring