Fast network intrusion detection system using adaptive binning feature selection

Aiming at the problems of the low detection rate of traditional intrusion detection systems and the long training and detection time of intrusion detection systems based on deep learning,an adaptive binning feature selection algorithm using the information gain is proposed,which is combined with LightGBM to design a fast network intrusion detection system.First,the original data set is preprocessed to standardize the data;then the redundant features and noise in the original data are removed through the adaptive binning feature selection algorithm,and the original high-dimensional data are reduced to the low-dimensional data,thereby improving the accuracy of the system and reducing the training and detection time;finally,LightGBM is used for model training on the training set selected by the characteristics to train an intrusion detection system that can detect attack traffic.Through verification on the NSL-KDD data set,the proposed feature selection algorithm only takes 27.35 seconds in feature selection,which is 96.68% lower than that by the traditional algorithm.The designed intrusion detection system has an accuracy rate of 93.32% on the test set,and its training time is low.Compared with the existing network intrusion detection system,the accuracy rate of the proposed system is higher,and its model training speed is faster.     

再生砖混骨料混凝土柱的小偏心受压性能

通过小偏心受压性能试验对比研究3根的天然骨料混凝土柱和3根同强度全再生砖混骨料混凝土柱,强度分别为C25、C30和C35. 对6根柱进行加载试验,分析再生砖混骨料混凝土柱相比于同强度天然骨料混凝土柱在受力过程、破坏特征、变形能力与承载力等方面的差异. 试验发现,再生砖混骨料混凝土柱在小偏心加载至破坏的过程中,具有与天然骨料混凝土柱相似的3个受力阶段,且符合平截面假定. 与同强度的天然骨料混凝土柱相比,变形较大,但再生砖混骨料混凝土柱的极限承载力略高,原因可能在于两者轴心抗压强度的差异.     

小型预制桩基础承载特性数值模拟研究

本文建立硬化土本构模型,针对江苏省软土地区的土质条件选取数值计算参数,通过PLAXIS 2D软件对小型预制桩在的单桩水平受荷及竖向受荷进行数值模拟,得到桩身弯矩沿桩长的分布以及荷载-位移曲线,分析小型预制桩基础桩身弯矩的分布特点,并探求其在水平及竖向荷载作用下的承载特性,进而能够为小型预制桩基础工程设计以及计算方面提供一定的参考依据。     

含小水电分布式电源的配网线路串联补偿优化

以小水电接入电网为例进行分析研究,深入分析小水电给电网带来的不利影响,重点分析对变压器损耗和线路损耗这两方面的影响。最后,举例某地区小水电接入配电网进行分析研究,对丰水期的小水电加入串联补偿装置后线路电压的变化情况展开研究。     

Pharmacologic Control of CAR T Cells

Chimeric antigen receptor (CAR) therapy is a promising modality for the treatment of advanced cancers that are otherwise incurable. During the last decade, different centers worldwide have tested the anti-CD19 CAR T cells and shown clinical benefits in the treatment of B cell tumors. However, despite these encouraging results, CAR treatment has also been found to lead to serious side effects and capricious response profiles in patients. In addition, the CD19 CAR success has been difficult to reproduce for other types of malignancy. The appearance of resistant tumor variants, the lack of antigen specificity, and the occurrence of severe adverse effects due to over-stimulation of the therapeutic cells have been identified as the major impediments. This has motivated a growing interest in developing strategies to overcome these hurdles through CAR control. Among them, the combination of small molecules and approved drugs with CAR T cells has been investigated. These have been exploited to induce a synergistic anti-cancer effect but also to control the presence of the CAR T cells or tune the therapeutic activity. In the present review, we discuss opportunistic and rational approaches involving drugs featuring anti-cancer efficacy and CAR-adjustable effect.     

The Contribution of Small Vessel Disease to Neurodegeneration: Focus on Alzheimer’s Disease,Parkinson’s Disease and Multiple Sclerosis

Brain small vessel disease (SVD) refers to a variety of structural and functional changes affecting small arteries and micro vessels, and manifesting as white matter changes, microbleeds and lacunar infarcts. Growing evidence indicates that SVD might play a significant role in the neurobiology of central nervous system (CNS) neurodegenerative disorders, namely Alzheimer’s disease (AD) and Parkinson’s disease (PD), and neuroinflammatory diseases, such as multiple sclerosis (MS). These disorders share different pathophysiological pathways and molecular mechanisms (i.e., protein misfolding, derangement of cellular clearance systems, mitochondrial impairment and immune system activation) having neurodegeneration as biological outcome. In these diseases, the actual contribution of SVD to the clinical picture, and its impact on response to pharmacological treatments, is not known yet. Due to the high frequency of SVD in adult-aged patients, it is important to address this issue. In this review, we report preclinical and clinical data on the impact of SVD in AD, PD and MS, with the main aim of clarifying the predictability of SVD on clinical manifestations and treatment response.     

Small Noncoding RNAs in Knee Osteoarthritis: The Role of MicroRNAs and tRNA-Derived Fragments

Knee osteoarthritis (OA) is a degenerative knee joint disease that results from the breakdown of joint cartilage and underlying bone, affecting about 3.3% of the world’s population. As OA is a multifactorial disease, the underlying pathological process is closely associated with genetic changes in articular cartilage and bone. Many studies have focused on the role of small noncoding RNAs in OA and identified numbers of microRNAs that play important roles in regulating bone and cartilage homeostasis. The connection between other types of small noncoding RNAs, especially tRNA-derived fragments and knee osteoarthritis is still elusive. The observation that there is limited information about small RNAs different than miRNAs in knee OA was very surprising to us, especially given the fact that tRNA fragments are known to participate in a plethora of human diseases and a portion of them are even more abundant than miRNAs. Inspired by these findings, in this review we have summarized the possible involvement of microRNAs and tRNA-derived fragments in the pathology of knee osteoarthritis.     

Supramolecular Nanofibers from Collagen-Mimetic Peptides Bearing Various Aromatic Groups at N-Termini via Hierarchical Self-Assembly

Self-assembly of artificial peptides has been widely studied for constructing nanostructured materials, with numerous potential applications in the nanobiotechnology field. Herein, we report the synthesis and hierarchical self-assembly of collagen-mimetic peptides (CMPs) bearing various aromatic groups at the N-termini, including 2-naphthyl, 1-naphtyl, anthracenyl, and pyrenyl groups, into nanofibers. The CMPs (R-(GPO)_n: n > 4) formed a triple helix structure in water at 4 °C, as confirmed via CD analyses, and their conformations were more stable with increasing hydrophobicity of the terminal aromatic group and peptide chain length. The resulting pre-organized triple helical CMPs showed diverse self-assembly into highly ordered nanofibers, reflecting their slight differences in hydrophobic/hydrophilic balance and configuration of aromatic templates. TEM analysis demonstrated that 2Np-CMP_n (n = 6 and 7) and Py-CMP₆ provided well-developed natural collagen-like nanofibers and An-CMP_n (n = 5–7) self-assembled into rod-like micelle fibers. On the other hand, 2Np-CMP₅ and 1Np-CMP₆ were unable to form nanofibers under the same conditions. Furthermore, the Py-CMP₆ nanofiber was found to encapsulate a guest hydrophobic molecule, Nile red, and exhibited unique emission behavior based on the specific nanostructure. In addition to the ability of CMPs to bind small molecules, their controlled self-assembly enables their versatile utilization in drug delivery and wavelength-conversion nanomaterials.