System Dynamics Based Simulation Study On Storage and Distribution Integration of Electronic Commerce Enterprise

With the strong advocacy of national policies and the rapid development of electronic commerce, offline logistics operation has become the key to efficient and fast e-commerce. This paper will use the system dynamic method to build an integrated warehousing and distribution system of e-commerce, applying the computer simulation to analyze the change of each parameter after the target inventory and delay time have changed. Suggestions will be put forward at last: building of an info-sharing mechanism, reducing the delay time via active coordination, predicting the target inventory of distribution center on time. Through these to reduce the average cost and the possibility of short supply at distribution center, and thus guarantee the delivery quality and speed, optimize buyers’ shopping experience, form a virtuous circle and enhance the overall competence of the supply chain

A Strategy Optimization Approach for Mission Deployment in Distributed Systems

In order to increase operational efficiency, reduce delays, and/or maximize profit, almost all the organizations have split their mission into several tasks which are deployed in distributed system. However, due to distributivity, the mission is prone to be vulnerable to kinds of cyberattacks. In this paper, we propose a mission deployment scheme to optimize mission payoff in the face of different attack strategies. Using this scheme, defenders can achieve “appropriate security” and force attackers to jointly safeguard the mission situation

Data-Free Hard-Label Robustness Stealing Attack

The popularity of Machine Learning as a Service (MLaaS) has led to increased concerns about Model Stealing Attacks (MSA), which aim to craft a clone model by querying MLaaS. Currently, most research on MSA assumes that MLaaS can provide soft labels and that the attacker has a proxy dataset with a similar distribution. However, this fails to encapsulate the more practical scenario where only hard labels are returned by MLaaS and the data distribution remains elusive. Furthermore, most existing work focuses solely on stealing the model accuracy, neglecting the model robustness, while robustness is essential in security-sensitive scenarios, e.g., face-scan payment. Notably, improving model robustness often necessitates the use of expensive techniques such as adversarial training, thereby further making stealing robustness a more lucrative prospect. In response to these identified gaps, we introduce a novel Data-Free Hard-Label Robustness Stealing (DFHL-RS) attack in this paper, which enables the stealing of both model accuracy and robustness by simply querying hard labels of the target model without the help of any natural data. Comprehensive experiments demonstrate the effectiveness of our method. The clone model achieves a clean accuracy of 77.86% and a robust accuracy of 39.51% against AutoAttack, which are only 4.71% and 8.40% lower than the target model on the CIFAR-10 dataset, significantly exceeding the baselines. Our code is available at: https://github.com/LetheSec/DFHL-RS-Attack.Comment: Accepted by AAAI 202

Quantifying Long‐Term Seasonal and Regional Impacts of North American Fire Activity on Continental Boundary Layer Aerosols and Cloud Condensation Nuclei

An intimate knowledge of aerosol transport is essential in reducing the uncertainty of the impacts of aerosols on cloud development. Data sets from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement platform in the Southern Great Plains region (ARM‐SGP) and the National Aeronautics and Space Administration (NASA) Modern‐Era Retrospective Analysis for Research and Applications, version 2 (MERRA‐2), showed seasonal increases in aerosol loading and total carbon concentration during the spring and summer months (2008–2016) which was attributed to fire activity and smoke transport within North America. The monthly mean MERRA‐2 surface carbonaceous aerosol mass concentration and ARM‐SGP total carbon products were strongly correlated (R = 0.82, p < 0.01) along with a moderate correlation with the ARM‐SGP cloud condensation nuclei (NCCN) product (0.5, p ~ 0.1). The monthly mean ARM‐SGP total carbon and N_(CCN) products were strongly correlated (0.7, p ~ 0.01). An additional product denoting fire number and coverage taken from the National Interagency Fire Center (NIFC) showed a moderate correlation with the MERRA‐2 carbonaceous product (0.45, p < 0.01) during the 1981–2016 warm season months (March–September). With respect to meteorological conditions, the correlation between the NIFC fire product and MERRA‐2 850‐hPa isobaric height anomalies was lower (0.26, p ~ 0.13) due to the variability in the frequency, intensity, and number of fires in North America. An observed increase in the isobaric height anomaly during the past decade may lead to frequent synoptic ridging and drier conditions with more fires, thereby potentially impacting cloud/precipitation processes and decreasing air quality

Quantifying Long‐Term Seasonal and Regional Impacts of North American Fire Activity on Continental Boundary Layer Aerosols and Cloud Condensation Nuclei

An intimate knowledge of aerosol transport is essential in reducing the uncertainty of the impacts of aerosols on cloud development. Data sets from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement platform in the Southern Great Plains region (ARM‐SGP) and the National Aeronautics and Space Administration (NASA) Modern‐Era Retrospective Analysis for Research and Applications, version 2 (MERRA‐2), showed seasonal increases in aerosol loading and total carbon concentration during the spring and summer months (2008–2016) which was attributed to fire activity and smoke transport within North America. The monthly mean MERRA‐2 surface carbonaceous aerosol mass concentration and ARM‐SGP total carbon products were strongly correlated (R = 0.82, p < 0.01) along with a moderate correlation with the ARM‐SGP cloud condensation nuclei (NCCN) product (0.5, p ~ 0.1). The monthly mean ARM‐SGP total carbon and N_(CCN) products were strongly correlated (0.7, p ~ 0.01). An additional product denoting fire number and coverage taken from the National Interagency Fire Center (NIFC) showed a moderate correlation with the MERRA‐2 carbonaceous product (0.45, p < 0.01) during the 1981–2016 warm season months (March–September). With respect to meteorological conditions, the correlation between the NIFC fire product and MERRA‐2 850‐hPa isobaric height anomalies was lower (0.26, p ~ 0.13) due to the variability in the frequency, intensity, and number of fires in North America. An observed increase in the isobaric height anomaly during the past decade may lead to frequent synoptic ridging and drier conditions with more fires, thereby potentially impacting cloud/precipitation processes and decreasing air quality

Cutting Off the Head Ends the Conflict: A Mechanism for Interpreting and Mitigating Knowledge Conflicts in Language Models

Recently, retrieval augmentation and tool augmentation have demonstrated a remarkable capability to expand the internal memory boundaries of language models (LMs) by providing external context. However, internal memory and external context inevitably clash, leading to knowledge conflicts within LMs. In this paper, we aim to interpret the mechanism of knowledge conflicts through the lens of information flow, and then mitigate conflicts by precise interventions at the pivotal point. We find there are some attention heads with opposite effects in the later layers, where memory heads can recall knowledge from internal memory, and context heads can retrieve knowledge from external context. Moreover, we reveal that the pivotal point at which knowledge conflicts emerge in LMs is the integration of inconsistent information flows by memory heads and context heads. Inspired by the insights, we propose a novel method called Pruning Head via PatH PatcHing (PH3), which can efficiently mitigate knowledge conflicts by pruning conflicting attention heads without updating model parameters. PH3 can flexibly control eight LMs to use internal memory ($\uparrow$ 44.0%) or external context ($\uparrow$ 38.5%). Moreover, PH3 can also improve the performance of LMs on open-domain QA tasks. We also conduct extensive experiments to demonstrate the cross-model, cross-relation, and cross-format generalization of our method.Comment: 21 pages, 42 figures, 4 table

A new ring-shape high-temperature superconducting trapped-field magnet

This paper presents a new trapped-field magnet made of second-generation high-temperature superconducting (2G HTS) rings. This so-called ring-shape 2G HTS magnet has the potential to provide much stronger magnetic fields relative to existing permanent magnets. Compared to existing 2G HTS trapped- field magnets, e.g. 2G HTS bulks and stacks, this new ring-shape 2G HTS magnet is more flexible in size and can be made into magnets with large dimensions for industrial applications. Effective magnetization is the key to being able to use trapped-field magnets. Therefore, this paper focuses on the magnetization mechanism of this new magnet using both experimental and numerical methods. Unique features have been identified and quantified for this new type of HTS magnet in the field cooling and zero field cooling process. The magnetization mechanism can be understood by the interaction between shielding currents and the penetration of external magnetic fields. An accumulation in the trapped field was observed by using multiple pulse field cooling. Three types of demagnetization were studied to measure the trapped-field decay for practical applications. Our results show that this new ring-shape HTS magnet is very promising in the trapping of a high magnetic field. As a super-permanent magnet, it will have a significant impact on large-scale industrial applications, e.g. the development of HTS machines with a very high power density and HTS magnetic resonance imaging devices

MicroRNA-483 amelioration of experimental pulmonary hypertension.

Endothelial dysfunction is critically involved in the pathogenesis of pulmonary arterial hypertension (PAH) and that exogenously administered microRNA may be of therapeutic benefit. Lower levels of miR-483 were found in serum from patients with idiopathic pulmonary arterial hypertension (IPAH), particularly those with more severe disease. RNA-seq and bioinformatics analyses showed that miR-483 targets several PAH-related genes, including transforming growth factor-β (TGF-β), TGF-β receptor 2 (TGFBR2), β-catenin, connective tissue growth factor (CTGF), interleukin-1β (IL-1β), and endothelin-1 (ET-1). Overexpression of miR-483 in ECs inhibited inflammatory and fibrogenic responses, revealed by the decreased expression of TGF-β, TGFBR2, β-catenin, CTGF, IL-1β, and ET-1. In contrast, inhibition of miR-483 increased these genes in ECs. Rats with EC-specific miR-483 overexpression exhibited ameliorated pulmonary hypertension (PH) and reduced right ventricular hypertrophy on challenge with monocrotaline (MCT) or Sugen + hypoxia. A reversal effect was observed in rats that received MCT with inhaled lentivirus overexpressing miR-483. These results indicate that PAH is associated with a reduced level of miR-483 and that miR-483 might reduce experimental PH by inhibition of multiple adverse responses

Stability Improvement of DC Power Systems in an All-Electric Ship Using Hybrid SMES/Battery

As the capacity of all-electric ships (AESs) increases dramatically, the sudden changes in the system load may lead to serious problems, such as voltage fluctuations of the ship power grid, increased fuel consumption, and environmental emissions. In order to reduce the effects of system load fluctuations on system efficiency, and to maintain the bus voltage, we propose a hybrid energy storage system (HESS) for use in AESs. The HESS consists of two elements: a battery for high energy density storage and a superconducting magnetic energy storage (SMES) for high power density storage. A dynamic droop control is used to control charge/discharge prioritization. Maneuvering and pulse loads are the main sources of the sudden changes in AESs. There are several types of pulse loads, including electric weapons. These types of loads need large amounts of energy and high electrical power, which makes the HESS a promising power source. Using Simulink/MATLAB, we built a model of the AES power grid integrated with an SMES/battery to show its effectiveness in improving the quality of the power grid