Unbiased Delayed Feedback Label Correction for Conversion Rate Prediction

Conversion rate prediction is critical to many online applications such as digital display advertising. To capture dynamic data distribution, industrial systems often require retraining models on recent data daily or weekly. However, the delay of conversion behavior usually leads to incorrect labeling, which is called delayed feedback problem. Existing work may fail to introduce the correct information about false negative samples due to data sparsity and dynamic data distribution. To directly introduce the correct feedback label information, we propose an Unbiased delayed feedback Label Correction framework (ULC), which uses an auxiliary model to correct labels for observed negative feedback samples. Firstly, we theoretically prove that the label-corrected loss is an unbiased estimate of the oracle loss using true labels. Then, as there are no ready training data for label correction, counterfactual labeling is used to construct artificial training data. Furthermore, since counterfactual labeling utilizes only partial training data, we design an embedding-based alternative training method to enhance performance. Comparative experiments on both public and private datasets and detailed analyses show that our proposed approach effectively alleviates the delayed feedback problem and consistently outperforms the previous state-of-the-art methods.Comment: accepted by KDD 202

The relationship between polycystic ovary syndrome and insulin resistance from 1983 to 2022: A bibliometric analysis

BackgroundPolycystic ovary syndrome (PCOS) is a common clinical disease often associated with insulin resistance (IR). The interaction between PCOS and IR will promote the progress of PCOS and the risk of related complications, harm women's physical and mental health, and increase the social and economic burden.Materials and MethodsPCOS IR-related works of literature were retrieved through the Web of Science Core Collection (WoSCC) Database and imported into VOSviewer and CiteSpace, respectively, in plain text format to conduct the literature visualization analysis of authors, countries, institutions, highly cited works of literature, and keywords, aiming to reveal the hot spots and trends of PCOS IR fields.ResultsA total of 7,244 articles were retrieved from 1900 to 2022. Among them, the United States has made the largest contribution. Diamanti-Kandarakis E was the author with the most publications, and the University of Athens was the institution with most publications. Keyword analysis showed that PCOS interacts with IR mainly through sex-hormone binding globulin, luteinizing hormone, insulin-like growth factor, oxidative stress, and other mechanisms. In addition, the complications of PCOS complicated with IR are also the focus of researchers' attention.ConclusionsThrough bibliometric analysis, this paper obtains the research hotspot and trend of PCOS IR fields, which can provide a reference for subsequent research

Fabrication and Properties of Cu-SiC-GNP composites

Based on the unique structure and excellent properties of graphene, the graphene nanoplates (GNP) were added to the traditional Cu-SiC composites. In this study, planetary ball milling, cold pressing and sintering were utilised to fabricate the Cu-SiC-GNP composites, which might be a route of the efficient industrial manufacturing of Cu-SiC-GNP composites. As for a new material, processing parameters of Cu-SiC-GNP needed to be investigated first. At the beginning of study, the as-received copper and Cu-SiC-GNP milled for 2 h were used to find an appropriate sintering temperature. Morphology, density and hardness were all employed and analysed. The connection of grains for Cu and Cu-SiC-GNP tended to increase while the ratio of pore and void inclined to decrease. Considering both curves of density vs. sintering temperature and curves of microhardness vs. sintering temperature, the best sintering temperature for these two kinds of materials was 800 degrees C. Furthermore, it was found that sintering of Cu-SiC-GNP composites was harder because of the addition of SiC and GNP with higher melting points..

The Impact of the Digital Economy on CO2 Emissions: A Theoretical and Empirical Analysis

Since the Industrial Revolution, human activities have led to the emission of a lot of greenhouse gases, such as carbon dioxide, sharply increasing the concentration of greenhouse gases in the atmosphere and resulting in serious global warming. With the rapid development of computer technology, the digital economy is gradually becoming the engine of economic growth. As a new economic mode, how the digital economy affects the environment is worth studying. In this paper, we introduced the digital economy into the Solow growth model as technological progress and conducted fixed-effects regressions based on the global panel data of 190 countries from 2005 to 2016. We found an inverted U-shaped, non-linear relationship between CO2 emissions and the digital economy, which supports the environmental Kuznets curve (EKC) hypothesis. We suggest that governments need to not only adopt hedging policies to reduce CO2 emissions caused by the digital economy in the early stage but also promote the development of the digital economy to achieve the goal of global collaborative environmental protection

Effect of Revegetation in Extremely Degraded Grassland on Carbon Density in Alpine Permafrost Regions

Revegetation has been proposed as an effective approach to restoring the extremely degraded grassland in the Qinghai–Tibetan Plateau (QTP). However, little is known about the effect of revegetation on ecosystem carbon density (ECD), especially in alpine permafrost regions. We compared aboveground biomass carbon density (ABCD), belowground biomass carbon density (BBCD), soil organic carbon density (SOCD), and ECD in intact alpine meadow, extremely degraded, and revegetated grasslands, as well as their influencing factors. Our results indicated that (1) ABCD, BBCD, SOCD, and ECD were significantly lower in extremely degraded grassland than in intact alpine meadow; (2) ABCD, SOCD, and ECD in revegetated grassland significantly increased by 93.46%, 16.88%, and 19.22%, respectively; (3) stepwise regression indicated that BBCD was mainly influenced by soil special gravity, and SOCD and ECD were controlled by freeze–thaw strength and soil temperature, respectively. This study provides a comprehensive survey of ECD and basic data for assessing ecosystem service functions in revegetated grassland of the alpine permafrost regions in the QTP

A cross‐layer anti‐jamming method in satellite Internet

Abstract In view of the diverse jamming environment, the single‐level anti‐jamming method faces some challenges such as poor timeliness, high cost and poor effect. In this paper, routing delay, cost overhead and diversified jamming threats are comprehensively considered. In addition, a cross‐layer anti‐jamming method is proposed in the scenario of busy satellite Internet communication. The proposed cross‐layer anti‐jamming method involves two levels: link‐layer anti‐jamming based on path repair and network‐layer anti‐jamming based on path reconstruction. On the one hand, the channel is selected based on the improved Q‐learning anti‐jamming algorithm to confront common jamming. On the other hand, the route from the source to the destination node is selected based on the cross‐layer anti‐jamming algorithm to confront high‐intensity jamming. Finally, the simulation results show that, compared with other anti‐jamming algorithms, the proposed algorithm can achieve higher efficiency, lower cost, and more robust anti‐jamming routing

Using the InVEST Model to Assess the Impacts of Climate and Land Use Changes on Water Yield in the Upstream Regions of the Shule River Basin

Water yield is a key ecosystem function index, directly impacting the sustainable development of the basin economy and ecosystem. Climate and land use/land cover (LULC) changes are the main driving factors affecting water yield. In the context of global climate change, assessing the impacts of climate and LULC changes on water yield in the alpine regions of the Qinghai–Tibet Plateau (QTP) is essential for formulating rational management and development strategies for water resources. On the basis of the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, we simulated and analyzed the spatiotemporal variations and the impacts of LULC and climate changes on water yield from 2001 to 2019 in the upstream regions of the Shule River Basin (USRB) on the northeastern margin of the QTP. Three scenarios were designed in the InVEST model to clearly analyze the contributions of climate and LULC changes on the variation of water yield. The first scenario integrated climate and LULC change into the model according to the actual conditions. The second scenario was simulation without LULC change, and the third scenario was without climate change. The results showed that (1) the InVEST model had a good performance in estimating water yield (coefficient of determination (R2) = 0.986; root mean square error (RMSE) = 3.012, p < 0.05); (2) the water yield significantly increased in the temporal scale from 2001 to 2019, especially in the high altitude of the marginal regions (accounting for 32.01%), while the northwest regions significantly decreased and accounted for only 8.39% (p < 0.05); (3) the spatial distribution of water yield increased from the middle low-altitude regions to the marginal high-altitude regions; and (4) through the analysis of the three scenarios, the impact of climate change on water yield was 90.56%, while that of LULC change was only 9.44%. This study reveals that climate warming has a positive impact on water yield, which will provide valuable references for the integrated assessment and management of water resources in the Shule River Basin

Optical and Electrical Properties of Ag-Doped In 2

Ag-doped In2S3 (In2S3:Ag) thin films have been deposited onto glass substrates by a thermal evaporation method. Ag concentration is varied from 0 at.% to 4.78 at.%. The structural, optical, and electrical properties are characterized using X-ray diffraction (XRD), spectrophotometer, and Hall measurement system, respectively. The XRD analysis confirms the existence of In2S3 and AgIn5S8 phases. With the increase of the Ag concentration, the band gap of the films is decreased gradually from 2.82 eV to 2.69 eV and the resistivity drastically is decreased from ~103 to 5.478×10-2 Ω·cm

Nanowire dimer optical antenna brightens the surface defects of silicon

Plasmonic hot spots located between metallic dimer nanostructures have been utilized comprehensively to achieve efficient light emission. However, different from the enhancement occurred in the plasmonic hot spot, the investigation of light emission off the hot spot on submicron scale remains challenge. In this work, we have constructed a plasmonic nanowire dimer (NWD) system to brighten the light emission of the surface defects of silicon off the hot spot on the submicron scale. The NWD can trap light through plasmonic gap, then, the excited emitter on the submicron scale can radiate light efficiently by coupling with the dipole gap plasmonic mode. Furthermore, the coupling of dipole plasmonic mode with the emitters can be tuned by changing the gap size, and then photoluminescence emission was drastically enhanced up to 126 folds. Theoretical simulations reveal the photoluminescence enhancement arises from the combination of the NWD’s high radiation efficiency, Purcell enhancement, efficient redirection of the emitted photoluminescence and the excitation enhancement. In this study, the photoluminescence signal can be effectively enhanced by placing nano-antenna patch on the detected low-quantum-efficiency emitters, which may open up a pathway toward controlling plasmonic gap mode enhanced light emission off the hot spot on submicron scale