FinalMLP: An Enhanced Two-Stream MLP Model for CTR Prediction

Click-through rate (CTR) prediction is one of the fundamental tasks for online advertising and recommendation. While multi-layer perceptron (MLP) serves as a core component in many deep CTR prediction models, it has been widely recognized that applying a vanilla MLP network alone is inefficient in learning multiplicative feature interactions. As such, many two-stream interaction models (e.g., DeepFM and DCN) have been proposed by integrating an MLP network with another dedicated network for enhanced CTR prediction. As the MLP stream learns feature interactions implicitly, existing research focuses mainly on enhancing explicit feature interactions in the complementary stream. In contrast, our empirical study shows that a well-tuned two-stream MLP model that simply combines two MLPs can even achieve surprisingly good performance, which has never been reported before by existing work. Based on this observation, we further propose feature gating and interaction aggregation layers that can be easily plugged to make an enhanced two-stream MLP model, FinalMLP. In this way, it not only enables differentiated feature inputs but also effectively fuses stream-level interactions across two streams. Our evaluation results on four open benchmark datasets as well as an online A/B test in our industrial system show that FinalMLP achieves better performance than many sophisticated two-stream CTR models. Our source code will be available at MindSpore/models.Comment: Accepted by AAAI 2023. Code available at https://xpai.github.io/FinalML

Regress 3D human pose from 2D skeleton with kinematics knowledge

3D human pose estimation is a hot topic in the field of computer vision. It provides data support for tasks such as pose recognition, human tracking and action recognition. Therefore, it is widely applied in the fields of advanced human-computer interaction, intelligent monitoring and so on. Estimating 3D human pose from a single 2D image is an ill-posed problem and is likely to cause low prediction accuracy, due to the problems of self-occlusion and depth ambiguity. This paper developed two types of human kinematics to improve the estimation accuracy. First, taking the 2D human body skeleton sequence obtained by the 2D human body pose detector as input, a temporal convolutional network is proposed to develop the movement periodicity in temporal domain. Second, geometrical prior knowledge is introduced into the model to constrain the estimated pose to fit the general kinematics knowledge. The experiments are tested on Human3.6M and MPII (Max Planck Institut Informatik) Human Pose (MPI-INF-3DHP) datasets, and the proposed model shows better generalization ability compared with the baseline and the state-of-the-art models

Emission accounting and drivers in 2004 EU accession countries

The ten countries that joined the European Union (EU) in 2004 (Cyprus, Czechia, Estonia, Hungary, Lithuania, Latvia, Malta, Poland, Slovakia, and Slovenia) have experienced faster economic growth and slower declines in energy consumption than traditional EU members. As designing of low-carbon policies requires accurate CO2 emission accounting, this study describes the evolving trajectories of CO2 emissions from 2005 to 2017 of 2004 EU accession members by providing detailed emission inventories by 28 types of energy and 47 socioeconomic sectors. We further quantify the contributions of four socioeconomic drivers (i.e., economic growth, energy structure, carbon intensity, and energy intensity) to the emission changes. The results show that the total CO2 emissions of the ten countries decreased by 7.50% from 2010 (506.81 Mt) to 2016 (468.78 Mt), which is lower than the average decline rate of other EU members (10.52%). Although the effect of economic growth contributed the most to emission increase (15.44%), it is completely offset by the decline in carbon intensity (-18.82%). We also discuss potential roadmaps towards carbon neutrality by designing 33 scenarios based on the European Union Low-Carbon Development Map 2050. We find that carbon neutrality cannot be achieved unless the share of renewable energy sources reaches 60% and more than half of existing coal and gas power plants are upgraded to Carbon Capture Storage (CCS) technology. These changes require the implementation of both short-term and long-term strategies

Who buys new energy vehicles in china? Assessing social-psychological predictors of purchasing awareness, intention, and policy

This paper investigates the salience of social-psychological factors in explaining why drivers purchase (or fail to purchase) New Energy Vehicles (NEVs)—including hybrid electric vehicles, battery electric vehicles, and fuel cell electric vehicles—in China. A questionnaire measuring six dimensions (including attitudes, subjective norms, perceived behavioral control, personal norms, low-carbon awareness and policy) was distributed in Tianjin, where aggressive policy incentives for NEVs exist yet adoption rates remain low. Correlation analysis and hierarchical multiple regression analyses are applied data collected through 811 valid questionnaires. We present three main findings. First, there is an “awareness-behavior gap” whereby low-carbon awareness has a moderating effect on purchasing behavior via psychological factors. Second, subjective norms has a stronger influence on intention to purchase New Energy Vehicles than other social-psychological factors. Third, acceptability of government policies has positive significant impact on adoption of New Energy Vehicles, which can provide reference potential template for other countries whose market for New Energy Vehicles is also in an early stage

Preventive effects of sodium hyaluronate combined with pelvic floor neuromuscular electrical stimulation on the intrauterine adhesions in women after abortion

The aim of this study was to investigate the clinical efficacy of combining pelvic floor neuromuscular stimulation treatment (NMES) with sodium hyaluronate in preventing intrauterine adhesions (IUA) following abortion. A total of 140 women who underwent artificial abortion were enrolled. The control group received only an intrauterine injection of sodium hyaluronate post-surgery, while the observation group received both the injection and daily pelvic floor NMES treatments, beginning on the day after the abortion. Monthly follow-ups on menstrual conditions were conducted for six months post-surgery. Fasting venous blood samples from both groups were collected on the second day post-abortion and the day after treatment. Transvaginal color Doppler ultrasound was used on the second day post-abortion and the 15th day post the first menstrual cycle to measure endometrial thickness, and the pulsatility and resistance indices of the endometrial spiral arteries. Over the six-month follow-up, the combination therapy group exhibited a notably lower IUA incidence compared to the control group (2.8% vs. 15.7%). Furthermore, combined treatment significantly expedited post-abortion menstrual recovery, reduced vaginal bleeding volume and duration (P < 0.001). It also increased endometrial thickness and reduced the endometrial spiral artery's pulsatility and resistance indices (P < 0.05). In addition, lower serum tumor necrosis factor alpha (TNF-α) and higher interleukin-10 (IL-10) were found in the observation group compared to the control group (P < 0.05). The combination therapy offers significant advantages in preventing and reducing IUA after abortion, resulting in a substantial reduction in IUA occurrence

Integration of spatial justice into navigating the combat on illegal, unreported and unregulated fishing in ocean and coastal areas

As a geographical dimension of justice, spatial justice is characterized by the interplay of social justice and heterogeneous spaces, including the ocean. Despite the generous contribution of ocean to humankind, concerns over aquatic spatial justice are disproportionately lacking. Among the core disruptors of ocean justice, illegal, unreported and unregulated (IUU) fishing imposes a major threat to global fisheries governance. The synthesis of spatial analysis and justice perspective can generate new insights to help understand and potentially address IUU fishing. To examine the spatial (in)justices concerning IUU fishing, we first propose a novel tripartite framework that envisions space as a form of opportunity, society and rights to externalize its socio-environmental implications. Then we integrate productive, distributive and consumptive justices to examine the spatial variations of IUU stakeholders along the fish value chain, and use stakeholder analysis to investigate spatial powers and conflicts regarding both a micro scale of fish communities, and a macro scale of states (coastal state, flag state, port state and market state) and supernational players (regional fisheries management organizations and marine protected areas). It is discovered that certain regions provide greater spatial benefits that stimulate IUU behaviors; IUU misconducts cause spatial differentiation and spatial deprivation that disrupt social orders in fish communities; space can empower stakeholders’ inclusive and proper engagement into the place-based management process against IUU fishing. Since the spatialized vision has been increasingly highlighted in marine fisheries management, it is suggested to intervene in the world ocean by leveraging spatial knowledge, managing spatial conflicts and facilitating spatial action, in order to promote spatial justice and better combat IUU fishing globally

Greenhouse gas emissions from municipal wastewater treatment facilities in China from 2006 to 2019

Wastewater treatment plants (WWTPs) alleviate water pollution but also induce resource consumption and environmental impacts especially greenhouse gas (GHG) emissions. Mitigating GHG emissions of WWTPs can contribute to achieving carbon neutrality in China. But there is still a lack of a high-resolution and time-series GHG emission inventories of WWTPs in China. In this study, we construct a firm-level emission inventory of WWTPs for CH4, N2O and CO2 emissions from different wastewater treatment processes, energy consumption and effluent discharge for the time-period from 2006 to 2019. We aim to develop a transparent, verifiable and comparable WWTP GHG emission inventory to support GHG mitigation of WWTPs in China