AFPN: Asymptotic Feature Pyramid Network for Object Detection

Multi-scale features are of great importance in encoding objects with scale variance in object detection tasks. A common strategy for multi-scale feature extraction is adopting the classic top-down and bottom-up feature pyramid networks. However, these approaches suffer from the loss or degradation of feature information, impairing the fusion effect of non-adjacent levels. This paper proposes an asymptotic feature pyramid network (AFPN) to support direct interaction at non-adjacent levels. AFPN is initiated by fusing two adjacent low-level features and asymptotically incorporates higher-level features into the fusion process. In this way, the larger semantic gap between non-adjacent levels can be avoided. Given the potential for multi-object information conflicts to arise during feature fusion at each spatial location, adaptive spatial fusion operation is further utilized to mitigate these inconsistencies. We incorporate the proposed AFPN into both two-stage and one-stage object detection frameworks and evaluate with the MS-COCO 2017 validation and test datasets. Experimental evaluation shows that our method achieves more competitive results than other state-of-the-art feature pyramid networks. The code is available at \href{https://github.com/gyyang23/AFPN}{https://github.com/gyyang23/AFPN}

Study on the Emission Characteristics in Renewable Energy Combustion under Different Working Conditions of Marine Two-Stroke Diesel Engine

In this paper, MAN 6S35ME-B9 two-stroke diesel engine is taken as the research object. By constructing a detailed combustion reaction mechanism including CH4, C4H10O, nitrides and other substances, CHEMKIN-PRO is used to simulate the same fuel mixing ratio and excess air coefficient. Under the condition of 1.5, the temperature, NO mole fraction and NH3 mole fraction in the reactor change and study the factors affecting the pollutant emission of marine diesel engine with the crank angle under different working conditions. The simulation shows that with the decrease of diesel engine speed, the maximum temperature of combustion reaction and the temperature at exhaust opening are obviously reduced. At the same time, mole fraction of NO and NH3 decreases with the decrease of rotational speed, and there is no nitride production in the combustion reaction at 25%

Synergistic Influence of Local Climate Zones and Wind Speeds on the Urban Heat Island and Heat Waves in the Megacity of Beijing, China

Large-scale modifications to urban underlying surfaces owing to rapid urbanization have led to stronger urban heat island (UHI) effects and more frequent urban heat wave (HW) events. Based on observations of automatic weather stations in Beijing during the summers of 2014–2020, we studied the interaction between HW events and the UHI effect. Results showed that the UHI intensity (UHII) was significantly aggravated (by 0.55°C) during HW periods compared to non-heat wave (NHW) periods. Considering the strong impact of unfavorable weather conditions and altered land use on the urban thermal environment, we evaluated the modulation of HW events and the UHI effect by wind speed and local climatic zones (LCZs). Wind speeds in urban areas were weakened due to the obstruction of dense high-rise buildings, which favored the occurrence of HW events. In detail, 35 HW events occurred over the LCZ1 of a dense high-rise building area under low wind speed conditions, which was much higher than that in other LCZ types and under high wind speed conditions (< 30 HW events). The latent heat flux in rural areas has increased more due to the presence of sufficient water availability and more vegetation, while the increase in heat flux in urban areas is mainly in the form of sensible heat flux, resulting in stronger UHI effect during HW periods. Compared to NHW periods, lower boundary layer and wind speed in the HW events weakened the convective mixing of air, further expanding the temperature gap between urban and rural areas. Note that LCZP type with its high-density vegetation and water bodies in the urban park area generally exhibited, was found to have a mitigating effect on the UHI, whilst at the same time increasing the frequency and duration of HW events during HW periods. Synergies between HWs and the UHI amplify both the spatial and temporal coverage of high-temperature events, which in turn exposes urban residents to additional heat stress and seriously threatens their health. The findings have important implications for HWs and UHII forecasts, as well as for scientific guidance on decision-making to improve the thermal environment and to adjust the energy structure

Impulsiveness indirectly affects suicidal ideation through depression and simultaneously moderates the indirect effect: A moderated mediation path model

ObjectiveThis study aims to investigate the indirect effect of impulsiveness on suicidal ideation through depression and the moderating effect of impulsiveness on the indirect effect in an integrated path model.MethodsSelf-rating depression scale (SDS), Barratt impulsiveness scale-11th version (BIS-11), and self-rating idea of suicide scale (SIOSS) were applied. A moderated mediation path model was established including impulsiveness, depression, and suicidal ideation as observed variables.ResultsThe main results revealed that the moderated mediation path model fit well in describing the relationships among impulsiveness, depression, and suicidal ideation. The indirect effect of impulsiveness mediated by depression and the moderating effect of impulsiveness on suicidal ideation was significant. Multiple comparisons showed that the indirect effects under different conditions of impulsiveness had statistical differences. The higher the impulsiveness was, the stronger the predictive effect of depression on suicidal ideation was.ConclusionsThe present study confirms that people who have impulsive traits are riskier to generate suicidal thoughts because they are more likely to suffer from depression and that people who are depressive have even higher risk to develop suicidal thoughts when they simultaneously have impulsive traits. In clinical and health care work, when considering depression to prevent suicidal ideation, impulsiveness needs to be monitored throughout the process of premorbid and onset stages of depression

DeepBurning-MixQ: An Open Source Mixed-Precision Neural Network Accelerator Design Framework for FPGAs

Mixed-precision neural networks (MPNNs) that enable the use of just enough data width for a deep learning task promise significant advantages of both inference accuracy and computing overhead. FPGAs with fine-grained reconfiguration capability can adapt the processing with distinct data width and models, and hence, can theoretically unleash the potential of MPNNs. Nevertheless, commodity DPUs on FPGAs mostly emphasize generality and have limited support for MPNNs especially the ones with lower data width. In addition, primitive DSPs in FPGAs usually have much larger data width than that is required by MPNNs and haven't been sufficiently co-explored with MPNNs yet. To this end, we propose an open source MPNN accelerator design framework specifically tailored for FPGAs. In this framework, we have a systematic DSP-packing algorithm to pack multiple lower data width MACs in a single primitive DSP and enable efficient implementation of MPNNs. Meanwhile, we take DSP packing efficiency into consideration with MPNN quantization within a unified neural network architecture search (NAS) framework such that it can be aware of the DSP overhead during quantization and optimize the MPNN performance and accuracy concurrently. Finally, we have the optimized MPNN fine-tuned to a fully pipelined neural network accelerator template based on HLS and make best use of available resources for higher performance. Our experiments reveal the resulting accelerators produced by the proposed framework can achieve overwhelming advantages in terms of performance, resource utilization, and inference accuracy for MPNNs when compared with both handcrafted counterparts and prior hardware-aware neural network accelerators on FPGAs.Comment: Accepted by 2023 IEEE/ACM International Conference on Computer-Aided Design (ICCAD

Adversarial behaviours in mixing coins under incomplete information

Criminals can launder crypto-currencies through mixing coins, whose original purpose is preservation of privacy in the presence of traceability. Therefore, it is essential to elaborately design mixing polices to achieve both privacy and anti-money laundering. Existing work on mixing policies relies on the knowledge of a blacklist. However, these policies are paralysed under the scenario where the blacklist is unknown or evolving. In this paper, we regard the above scenario as games under incomplete information where parties put down a deposit for the quality of coins, which is suitably managed by a smart contract in case of mixing bad coins. We extend the poison and haircut policies to incomplete information games, where the blacklist is updated after mixing. We prove the existence of equilibria for the improved polices, while it is known that there is no equilibria in the original poison and haircut policies, where blacklist is public known. Furthermore, we propose a seminal suicide policy: the one who mixes more bad coins will be punished by not having the deposit refunded. Thus, parties have no incentives to launder money by leveraging mixing coins. In effect, all three policies contrast money laundering while preserving privacy under incomplete information. Finally, we simulate and verify the validity of these policies

Influence of Group Cognitive Behavioral Therapy on Pregnancy Outcomes among Pregnant Women with Gestational Diabetes Mellitus: a Propensity Score Matching Study

Background Gestational diabetes mellitus (GDM) is a common complication during pregnancy. However, the adherence to individualized medical nutrition therapy (IMNT) alone among GDM women is poor and the impact of group cognitive behavioral therapy (GCBT) on their pregnancy outcomes remains unclear. Objective To examine the impact of GCBT on the pregnancy outcomes of women with GDM, and to provide reference for improving pregnancy outcomes and developing effective gestational diabetes management programme. Methods A total of 878 pregnant women with GDM who delivered and received IMNT in our hospital from 2020 to 2021 were retrospectively selected as the study subjects and divided into the observation group including 141 pregnant women with GDM who received GCBT and the control group including 737 pregnant women with GDM who did not receive GCBT. The differences in pregnancy outcomes of pregnant women with GDM between the two groups before and after propensity score matching were analyzed. Results There were 134 pregnant women with GDM in the observation group and 256 pregnant women with GDM in the control group after 1∶2 propensity score matching. The proportion of pregnant women with GDM who gained normal weight in the observation group (50.7%, 68/134) was higher than that in the control group (37.5%, 96/256) (P<0.05) . The gestational weeks of delivery of pregnant women with GDM in the observation group (39.0±1.1) were longer than those in the control group (38.5±1.7) (P<0.05) . Additionally, the proportions of preterm infants (3.7%) , macrosomia (1.5%) , and low birth weight infants (2.2%) were lower than those in the control group (10.5%, 5.9%, and 9.0%, respectively) (P<0.05) . Conclusions GCBT can help reduce the risk of the delivery of preterm infants, low birth weight infants, and macrosomia in pregnant women with GDM, providing a reference for the establishment of a multidisciplinary management model for GDM

An Initial Value Calibration Method for the Wheel Force Transducer Based on Memetic Optimization Framework

Some initial values of the wheel force transducer (WFT) change after being mounted in the vehicle. The traditional static calibration is inadequate to fully obtain these initial values. Aiming to this problem, an online initial value calibration method is proposed. The method does not require any additional calibration equipment or manual operation and just requires the vehicle mounted with the WFT to be driven on a flat road with constant speed. In this way, an initial value mode is constructed and then converted to an optimization problem. To solve this problem and acquire the right initial value, an improved Memetic framework based on particle swarm optimization (PSO) and Levenberg-Marquardt (LM) is adopted. To verify the effect of the proposed method, the real WFT data is used and the comparative test is carried out. The experiment result shows that the proposed method is superior to the traditional one and can improve the measurement accuracy effectively

Responses of carbon exchange characteristics to meteorological factors, phenology, and extreme events in a rubber plantation of Danzhou, Hainan: evidence based on multi-year data

IntroductionOn Hainan Island, a rubber plantation that occupies a large swath of land plays an important role in the regional carbon budget. However, the carbon exchange of the rubber plantation is poorly understood.MethodsIn this study, using the eddy covariance methods we measured carbon metrics in the rubber plantation for 13 years from 2010 to 2022.ResultsWe clarified that the rubber plantation is a carbon sink and the annual net ecosystem exchange (NEE), ecosystem respiration, and gross primary production were −911.89 ± 135.37, 1,528.04 ± 253.50, and 2,439.93 ± 259.63 gC·m−2·a−1, respectively. Carbon fluxes differed between interannual years; specifically, rainy season fluxes were nearly double dry season fluxes. Radiation explained 46% of the variation for NEE in rainy season, and temperature explained 36% of the variation for NEE in the dry season. LAI explained the highest proportion of the monthly variation in NEE (R2 = 0.72, p < 0.001), indicating that when hydrothermal conditions are sufficient phenology may be the primary factor controlling carbon sequestration of rubber plantation. Due to climate change, there is an increasing probability of extreme climate events, such as typhoons, heat waves, and drought. Thus, we compared NEE before and after such events and results show extreme climate events reduce carbon uptake in the rubber plantation. We found that typhoons reduced NEE to varying degrees on different timescales. Heat waves generally decreased NEE during the day but recovered quickly and increased carbon uptake if there was sufficient precipitation. Drought reduced carbon uptake and continued to decrease even after precipitation.DiscussionEstimating the carbon sink capacity of the rubber plantation and studying the response to regional environmental changes are important for both applied research (carbon sink research and market trading, sink enhancement, and emission reduction, etc.) and basic research (land use change, phenology change, etc.)

How to achieve bidirectional zero-knowledge authentication?

Due to the completeness, reliability and zero-knowledge nature, the zero-knowledge proof is widely used to designed various protocols, including zero-knowledge authentication protocols. However, the existing zero-knowledge proof scheme cannot realize bidirectional authentication. In this paper, we design a series of bidirectional zero-knowledge protocols based on two new flavors of operations applicable to multiplicative cyclic group. The two notions are formally defined in this paper. We also provide some formal definitions and properties for the two notions. According to our definitions, any bounded polynomial function defined on multiplicative cyclic group has duality and mirror. Based on the two operations, we introduce and formally define dual commitment scheme and mirror commitment scheme. Besides, we provide two efficient constructions for dual commitment and mirror commitment respectively based on CDH assumption and RSA assumption, and named DCCDH, DCRSA, MCCDH and MCRSA respectively. We also provide the extended version supporting multiple messages in the appendix. Then, we design some efficient non-interactive as well as interactive zero-knowledge authentication protocols based on these commitments. The protocols allow two participants to submit commitments to each other so that they can achieve mutual zero-knowledge authentication only a communication initialization needed. Moreovere , similar to other commitment schemes, our schemes also can be widely used to construction of other schemes for cryptography, such as, verifiable secret sharing, zero-knowledge sets, credentials and content extraction signatures