LA-GRU: Building Combined Intrusion Detection Model Based on Imbalanced Learning and Gated Recurrent Unit Neural Network

The intrusion detection models (IDMs) based on machine learning play a vital role in the security protection of the network environment, and, by learning the characteristics of the network traffic, these IDMs can divide the network traffic into normal behavior or attack behavior automatically. However, existing IDMs cannot solve the imbalance of traffic distribution, while ignoring the temporal relationship within traffic, which result in the reduction of the detection performance of the IDM and increase the false alarm rate, especially for low-frequency attacks. So, in this paper, we propose a new combined IDM called LA-GRU based on a novel imbalanced learning method and gated recurrent unit (GRU) neural network. In the proposed model, a modified local adaptive synthetic minority oversampling technique (LA-SMOTE) algorithm is provided to handle imbalanced traffic, and then the GRU neural network based on deep learning theory is used to implement the anomaly detection of traffic. The experimental results evaluated on the NSL-KDD dataset confirm that, compared with the existing state-of-the-art IDMs, the proposed model not only obtains excellent overall detection performance with a low false alarm rate but also more effectively solves the learning problem of imbalanced traffic distribution

Effects of Anthropogenic Disturbances and Climate Change on Riverine Dissolved Inorganic Nitrogen Transport

Abstract Nitrogen (N) transport from land to rivers, estuaries, and coastal marine systems has been markedly altered by anthropogenic and climatic drivers over recent decades. In this study, a riverine N transport scheme considering anthropogenic N discharge and water regulation was incorporated into the Land Surface Model of the Chinese Academy of Sciences (CAS‐LSM). Seven groups of simulations using the developed model at the global scale for the period of 1981–2010 were conducted to investigate the effects of anthropogenic disturbances and climate change on riverine dissolved inorganic nitrogen (DIN) transport. It was shown that fertilization and point source pollution have enhanced the DIN fluxes in rivers across the world, especially in western Europe and eastern China. The DIN exports were significantly reduced due to retention by reservoirs and the withdrawal of surface water and groundwater, with a retention efficiency of 50–70%. Climate variability and trends increased or decreased the riverine DIN fluxes depending on the specific hydroclimatic conditions. We further analyzed the contributions of climatic and anthropogenic changes to the riverine DIN changes in four major rivers. The riverine DIN exports in the Mississippi River Basin were affected primarily by fertilization, while the changes in DIN exports of the Danube were dominated by point source pollution and water regulation. The Yangtze River in China was seriously affected by both fertilization and point source pollution, and water regulation played a significant role in reducing DIN exports. Climate variability was the primary factor explaining the interannual variability of DIN exports

Growth of Highly Oriented Ultrathin Crystalline Organic Microstripes: Effect of Alkyl Chain Length

The growth of organic semiconductor with controllable morphology is a crucial issue for achieving high-performance devices. Here we present the systematic study of the effect of the alkyl chain attached to the functional entity on controlling the growth of oriented microcrystals by dip-coating. Alkylated DTBDT-based molecules with variable chain lengths from <i>n</i>-butyl to <i>n</i>-dodecyl formed into one-dimensional micro- or nanostripe crystals at different pulling speeds. The alignment and ordering are significantly varied with alkyl chain length, as is the transistor performance. Highly uniform oriented and higher-molecular-order crystalline stripes with improved field-effect mobility can be achieved with an alkyl-chain length of around 6. We attribute this effect to the alkyl-chain-length-dependent packing, solubility, and self-assembly behavior

Survival Prediction in High-grade Osteosarcoma Using Radiomics of Diagnostic Computed Tomography

The poor 5-year survival rate in high-grade osteosarcoma (HOS) has not been increased significantly over the past 30 years. This work aimed to develop a radiomics nomogram for survival prediction at the time of diagnosis in HOS.In this retrospective study, an initial cohort of 102 HOS patients, diagnosed from January 2008 to March 2011, was used as the training cohort. Radiomics features were extracted from the pretreatment diagnostic computed tomography images. A radiomics signature was constructed with the lasso algorithm; then, a radiomics score was calculated to reflect survival probability by using the radiomics signature for each patient. A radiomics nomogram was developed by incorporating the radiomics score and clinical factors. A clinical model was constructed by using clinical factors only. The models were validated in an independent cohort comprising 48 patients diagnosed from April 2011 to April 2012. The performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. Kaplan–Meier survival analysis was performed.The radiomics nomogram showed better calibration and classification capacity than the clinical model with AUC 0.86 vs. 0.79 for the training cohort, and 0.84 vs. 0.73 for the validation cohort. Decision curve analysis demonstrated the clinical usefulness of the radiomics nomogram. A significant difference (p-value <.05; log-rank test) was observed between the survival curves of the nomogram-predicted survival and non-survival groups. The radiomics nomogram may assist clinicians in tailoring appropriate therapy

Nitroacetylacetone as a Cofuel for the Combustion Synthesis of High-Performance Indium–Gallium–Zinc Oxide Transistors

Thin-film combustion synthesis has been utilized for the fabrication of solution processed high-performance metal-oxide thin-film transistors (MOTFTs) at lower temperatures than conventional sol–gel processes. The fuel-oxidizer ensemble in the MO precursor solution/film plays an important role in achieving high-efficiency and low-residual combustion byproducts. However, unlike conventional bulk combustion, only a very limited number of thin-film fuels have been investigated. Here we report the use of an efficient new cofuel, 3-nitroacetylacetone (NAcAcH), incorporating a −NO₂ group, for the combustion synthesis of display-relevant indium–gallium–zinc-oxide (IGZO) thin films. Compared to the traditional acetylacetone (AcAcH) fuel, a higher enthalpy of combustion (988.6 vs 784.4 J/g) and a lower ignition temperature (107.8 vs 166.5 °C) are achieved for NAcAcH-based formulations. The resulting NAcAcH-derived IGZO TFTs exhibit far higher average electron mobilities (5.7 cm² V^–1 s^–1) than AcAcH-derived TFTs (2.7 cm² V^–1 s^–1). More importantly, when combining AcAcH with NAcAcH as cofuels in an optimal molar ratio of 1.5:0.5, an even larger TFT electron mobility (7.5 cm² V^–1 s^–1) and more stable devices are achieved. Comprehensive IGZO precursor/film analysis and characterization by differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), X-ray photoelectron spectroscopy (XPS), grazing incidence X-ray diffraction (GIXRD), and X-ray reflectivity (XRR) explain the basis of the film microstructure and TFT performance trends