65 research outputs found

    Modeling the Field Value Variations and Field Interactions Simultaneously for Fraud Detection

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    With the explosive growth of e-commerce, online transaction fraud has become one of the biggest challenges for e-commerce platforms. The historical behaviors of users provide rich information for digging into the users' fraud risk. While considerable efforts have been made in this direction, a long-standing challenge is how to effectively exploit internal user information and provide explainable prediction results. In fact, the value variations of same field from different events and the interactions of different fields inside one event have proven to be strong indicators for fraudulent behaviors. In this paper, we propose the Dual Importance-aware Factorization Machines (DIFM), which exploits the internal field information among users' behavior sequence from dual perspectives, i.e., field value variations and field interactions simultaneously for fraud detection. The proposed model is deployed in the risk management system of one of the world's largest e-commerce platforms, which utilize it to provide real-time transaction fraud detection. Experimental results on real industrial data from different regions in the platform clearly demonstrate that our model achieves significant improvements compared with various state-of-the-art baseline models. Moreover, the DIFM could also give an insight into the explanation of the prediction results from dual perspectives.Comment: 11 pages, 4 figure

    High-throughput UAV-based rice panicle detection and genetic mapping of heading-date-related traits

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    IntroductionRice (Oryza sativa) serves as a vital staple crop that feeds over half the world's population. Optimizing rice breeding for increasing grain yield is critical for global food security. Heading-date-related or Flowering-time-related traits, is a key factor determining yield potential. However, traditional manual phenotyping methods for these traits are time-consuming and labor-intensive.MethodHere we show that aerial imagery from unmanned aerial vehicles (UAVs), when combined with deep learning-based panicle detection, enables high-throughput phenotyping of heading-date-related traits. We systematically evaluated various state-of-the-art object detectors on rice panicle counting and identified YOLOv8-X as the optimal detector.ResultsApplying YOLOv8-X to UAV time-series images of 294 rice recombinant inbred lines (RILs) allowed accurate quantification of six heading-date-related traits. Utilizing these phenotypes, we identified quantitative trait loci (QTL), including verified loci and novel loci, associated with heading date.DiscussionOur optimized UAV phenotyping and computer vision pipeline may facilitate scalable molecular identification of heading-date-related genes and guide enhancements in rice yield and adaptation

    Deposition potential of 0.003-10 mu m ambient particles in the humidified human respiratory tract : Contribution of new particle formation events in Beijing

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    Ultrafine particles (UFPs) usually explosive growth during new particle formation (NPF) events. However, the risk of exposure to UFPs on NPF days has been ignored due to the prevalence of mass-based air quality standards. In this study, the daily deposited doses, i.e., the daily deposited particle number dose (D-PNd), mass dose (D-PMd), and surface area dose (D-PSd), of ambient particles in the human respiratory tract in Beijing were evaluated based on the particle number size distribution (3 nm-10 mu m) from June 2018 to May 2019 utilizing a Multiple-Path Particle Dosimetry Model (MPPD) after the hygroscopic growth of particles in the respiratory tract had been accounted for. Our observations showed a high frequency (72.6%) of NPF on excellent air quality days, with daily mean PM2.5 concentrations less than 35 mu g m(-3). The daily D-PNd on excellent air quality days was com-parable with that on polluted days, although the D-PMd on excellent air quality days was as low as 15.6% of that on polluted days. The D-PNd on NPF days was similar to 1.3 times that on non-NPF days. The D-PNd in respiratory tract regions decreased in the order: tracheobronchial (TB) > pulmonary (PUL) > extrathoracic (ET) on NPF days, while it was PUL > TB > ET on non-NPF days. The number of deposited nucleation mode particles, which were deposited mainly in the TB region (45%), was 2 times higher on NPF days than that on non-NPF days. Our results demonstrated that the deposition potential due to UFPs in terms of particle number concentrations is high in Beijing regardless of the aerosol mass concentration. More toxicological studies related to UFPs on NPF days, especially those targeting tracheobronchial and pulmonary impairment, are required in the future.Peer reviewe

    Hypoxic acclimatization training improves the resistance to motion sickness

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    ObjectiveVestibular provocation is one of the main causes of flight illusions, and its occurrence is closely related to the susceptibility of motion sickness (MS). However, existing training programs have limited effect in improving the resistance to motion sickness. In this study, we investigated the effects of hypoxia acclimatization training (HAT) on the resistance to motion sickness.MethodsHealthy military college students were identified as subjects according to the criteria. MS model was induced by a rotary chair. Experimental groups included control, HAT, 3D roller training (3DRT), and combined training.ResultsThe Graybiel scores were decreased in the HAT group and the 3DRT group and further decreased in the combined training group in MS induced by the rotary chair. Participants had a significant increase in blood pressure after the rotary chair test and a significant increase in the heart rate during the rotary chair test, but these changes disappeared in all three training groups. Additionally, LFn was increased, HFn was decreased, and LF/HF was increased accordingly during the rotary chair test in the control group, but the changes of these three parameters were completely opposite in the three training groups during the rotary chair test. Compared with the control group, the decreasing changes in pupillary contraction velocity (PCV) and pupillary minimum diameter (PMD) of the three training groups were smaller. In particular, the binocular PCV changes were further attenuated in the combined training group.ConclusionOur research provides a possible candidate solution for training military pilots in the resistance to motion sickness

    The effect of COVID-19 restrictions on atmospheric new particle formation in Beijing

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    During the COVID-19 lockdown, the dramatic reduction of anthropogenic emissions provided a unique opportunity to investigate the effects of reduced anthropogenic activity and primary emissions on atmospheric chemical processes and the consequent formation of secondary pollutants. Here, we utilize comprehensive observations to examine the response of atmospheric new particle formation (NPF) to the changes in the atmospheric chemical cocktail. We find that the main clustering process was unaffected by the drastically reduced traffic emissions, and the formation rate of 1.5 nm particles remained unaltered. However, particle survival probability was enhanced due to an increased particle growth rate (GR) during the lockdown period, explaining the enhanced NPF activity in earlier studies. For GR at 1.5-3 nm, sulfuric acid (SA) was the main contributor at high temperatures, whilst there were unaccounted contributing vapors at low temperatures. For GR at 3-7 and 7-15 nm, oxygenated organic molecules (OOMs) played a major role. Surprisingly, OOM composition and volatility were insensitive to the large change of atmospheric NOx concentration; instead the associated high particle growth rates and high OOM concentration during the lockdown period were mostly caused by the enhanced atmospheric oxidative capacity. Overall, our findings suggest a limited role of traffic emissions in NPF.Peer reviewe

    Methane Pyrolysis in a Hot Filament Reactor

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    An electrically heated platinum filament mounted inside a quartz tube was used as a high temperature flow reactor for methane pyrolysis. The reaction products included carbon and a mixture of hydrocarbons, mainly C1−C5 alkanes, alkenes, and benzene. The hydrocarbons were measured by gas chromatography and the carbon gravimetrically. At 1275 °C filament temperature and 100ms residence time in the hot region of the reactor, methane conversion was 19.7% and selectivity of hydrocarbon products 68%. Lowering the flow rate increased the conversion but lowered sharply the selectivity of hydrocarbon products. Coking of the filament surface gradually lowered the filament temperature and the conversion of methane. This deactivation process could be slowed by adding a few percent of oxygen to the methane feed
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