An effective Denial of Service Attack Detection Method in Wireless Mesh Networks

AbstractIn order to detect the DoS attack (Denial-of-Service attack) when wireless mesh networks adopt AODV routing protocol of Ad Hoc networks. Such technologies as an end-to-end authentication, utilization rate of cache memory, two pre-assumed threshold value and distributed voting are used in this paper to detect DoS attacker, which is on the basic of hierarchical topology structure in wireless mesh networks. Through performance analysis in theory and simulations experiment, the scheme would improve the flexibility and accuracy of DoS attack detection, and would obviously improve its security in wireless mesh networks

Panoptic Video Scene Graph Generation

Towards building comprehensive real-world visual perception systems, we propose and study a new problem called panoptic scene graph generation (PVSG). PVSG relates to the existing video scene graph generation (VidSGG) problem, which focuses on temporal interactions between humans and objects grounded with bounding boxes in videos. However, the limitation of bounding boxes in detecting non-rigid objects and backgrounds often causes VidSGG to miss key details crucial for comprehensive video understanding. In contrast, PVSG requires nodes in scene graphs to be grounded by more precise, pixel-level segmentation masks, which facilitate holistic scene understanding. To advance research in this new area, we contribute the PVSG dataset, which consists of 400 videos (289 third-person + 111 egocentric videos) with a total of 150K frames labeled with panoptic segmentation masks as well as fine, temporal scene graphs. We also provide a variety of baseline methods and share useful design practices for future work.Comment: Accepted to CVPR 2023. Project Page: https://jingkang50.github.io/PVSG/. Codebase: https://github.com/LilyDaytoy/OpenPVSG. We provide 400 long videos with frame-level panoptic segmentation, scene graph, dense captions, and QA annotation

Intrathecal Injection of Spironolactone Attenuates Radicular Pain by Inhibition of Spinal Microglia Activation in a Rat Model

Microglia might play an important role in nociceptive processing and hyperalgesia by neuroinflammatory process. Mineralocorticoid receptor (MR) expressed on microglia might play a central role in the modulation of microglia activity. However the roles of microglia and MR in radicular pain were not well understood. This study sought to investigate whether selective MR antagonist spironolactone develop antinociceptive effects on radicular pain by inhibition neuroinflammation induced by spinal microglia activation.Radicular pain was produced by chronic compression of the dorsal root ganglia with SURGIFLO™. The expression of microglia, interleukin beta (IL-1β), interleukin 6 (IL-6), tumor necrosis factor alpha (TNF-α), NR1 subunit of the NMDA receptor (t-NR1), and NR1 subunit phosphorylated at Ser896 (p-NR1) were also markedly up-regulated. Intrathecal injection of spironolactone significantly attenuated pain behaviors as well as the expression of microglia, IL-1β, TNF-α, t-NR1, and p-NR1, whereas the production of IL-6 wasn't affected.These results suggest that intrathecal delivery spironolactone has therapeutic effects on radicular pain in rats. Decreasing the activation of glial cells, the production of proinflammatory cytokines and down-regulating the expression and phosphorylation of NMDA receptors in the spinal dorsal horn and dorsal root ganglia are the main mechanisms contributing to its beneficial effects

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Infrared Stripe Correction Algorithm Based on Wavelet Analysis and Gradient Equalization

In the uncooled infrared imaging systems, owing to the non-uniformity of the amplifier in the readout circuit, the infrared image has obvious stripe noise, which greatly affects its quality. In this study, the generation mechanism of stripe noise is analyzed, and a new stripe correction algorithm based on wavelet analysis and gradient equalization is proposed, according to the single-direction distribution of the fixed image noise of infrared focal plane array. The raw infrared image is transformed by a wavelet transform, and the cumulative histogram of the vertical component is convolved by a Gaussian operator with a one-dimensional matrix, in order to achieve gradient equalization in the horizontal direction. In addition, the stripe noise is further separated from the edge texture by a guided filter. The algorithm is verified by simulating noised image and real infrared image, and the comparison experiment and qualitative and quantitative analysis with the current advanced algorithm show that the correction result of the algorithm in this paper is not only mild in visual effect, but also that the structural similarity (SSIM) and peak signal-to-noise ratio (PSNR) indexes can get the best result. It is shown that this algorithm can effectively remove stripe noise without losing details, and the correction performance of this method is better than the most advanced method

A Cross-Scale Framework for Modelling Chloride Ions Diffusion in C-S-H: Combined Effects of Slip, Electric Double Layer and Ion Correlation

Water and chloride ions within pores of cementitious materials plays a crucial role in the damage processes of cement pastes, particularly in the binding material comprising calcium-silicate-hydrates (C-S-H). The migration mechanism of water and chloride ions restricted in C-S-H nanopores is complicated due to the presence of interfacial effects. The special mechanical properties of the solid–liquid interface determine the importance of boundary slip and Electric Double Layer (EDL) and ion diversity in pore solutions determines the difference of the EDL and the stability of water film slip. A cross-scale model covering slip effects, time-varying of EDL and ion correlation needs to be developed so that the interfacial effects concentrated at the pore scale can be extended to affect the overall diffusivity of C-S-H. The statistics of pore size distribution and fractal dimension were used to quantitatively compare the similarities between model and C-S-H structure, thus proving the reliability of cross-scale reconstructed C-S-H transmission model. The results show that the slip effect is the dominant factor affecting the diffusion ability of C-S-H, the contribution of the slip effect is up to 60% and the contribution rate of EDL time-varying only up to about 15%. Moreover, the slip effect is sensitive to both ion correlation and C-S-H inhomogeneity and EDL time-varying is almost insensitive to ion correlation changes. This quantification provides a necessary benchmark for understanding the destructiveness of cement-based materials in the salt rich environment and provides new insights into improving the durability of concrete by changing the solid–liquid interface on the micro-nanoscale

Sonum: Software-Defined Synergetic Sampling Approach and Optimal Network Utilization Mechanism for Long Flow in a Data Center Network

Long flow detection and load balancing are crucial techniques for data center running and management. However, both of them have been independently studied in previous studies. In this paper, we propose a complete solution called Sonum, which can complete long flow detection and scheduling at the same time. Sonum consists of a software-defined synergetic sampling approach and an optimal network utilization mechanism. Sonum detects long flows through consolidating and processing sampling information from multiple switches. Compared with the existing prime solution, the missed detection rate of Sonum is reduced by 2.3%–5.1%. After obtaining the long flow information, Sonum minimizes the potential packet loss rate as the optimization target and then translates load balancing into an optimization problem of arranging a minimum packet loss path for long flows. This paper also introduces a heuristic algorithm for solving this optimization problem. The experimental results show that Sonum outperforms ECMP and Hedera in terms of network throughput and flow completion time

Machine-Learning-Assisted Identification of Steam Channeling after Cyclic Steam Stimulation in Heavy-Oil Reservoirs

Cyclic steam stimulation (CSS) is one efficient technology for enhancing heavy-oil recovery. However, after multiple cycles, steam channeling severely limits the thermal recovery because high-temperature steam preferentially breaks through to the producers. To solve the issues of steam breakthrough, it is essentially important and necessary to recognize steam channeling. In this work, a machine-learning-assisted identification model, based on a random-forest ensemble algorithm, is developed to predict the occurrence of steam channeling during steam huff-and-puff processes. The set of feature attributes is constructed based on the permeability ratio, steam quality, and steam-injection speed, which provides the reference for the construction of the training-sample set, steam-channeling reconstruction set, and prediction set. Based on the realistic data, the Pearson correlation coefficient is implemented to confirm the linear correlation among different characteristics; thus, the dimension reduction of the characteristic parameters is achieved. The random oversampling method is adopted to treat the unbalanced training-sample set. Our results show that this model can accurately describe the current state of steam channeling and predict steam propagation in the following cycles

Enhancement Study of Ice Storage Performance in Circular Tank with Finned Tube

Combined experimental and numerical studies are conducted to study ice storage performance of an ice storage tank with finned tube. Axially arranged fins on the refrigerant tube are applied to enhance the solidification. The evolution of the solid−liquid interface and the variation of temperature of the typical position is examined. The effect of natural convection is discussed in detail. In addition, the effects of refrigerant temperature and initial water temperature on the ice storage performance are analyzed. The results indicate that the ice storage performance is enhanced by the metal fins remarkably. The defection of poor heat transfer after ice is formed can be solved by applying fins in ice storage devices. Natural convection leads to unnecessary mixing of water with different temperatures, lessening the cooling energy stored and acting as a disadvantage during solidification. Decreasing the refrigerant temperature and initial water temperature is beneficial for ice storage

Immunogenicity and Safety of COVID-19 Vaccines among People Living with HIV: A Systematic Review and Meta-Analysis

Background: The immunogenicity and safety of COVID-19 vaccines among people living with human immunodeficiency virus (PLWH) are unclear. We aimed to evaluate the immunogenicity and safety of COVID-19 vaccines among PLWH. Methods: We systematically searched PubMed, EMBASE, and Web of Science from 1 January 2020 to 28 April 2022 and included observational studies, randomized clinical trials, and non-randomized clinical trials reporting extractable data about the immunogenicity and safety of COVID-19 vaccines among PLWH. Results: A total of 34 eligible studies covering 4517 PLWH were included. The pooled seroconversion rates among PLWH after the first and second doses were 67.51% (95% confident interval (CI) 49.09–85.93%) and 96.65% (95%CI 95.56–97.75%), respectively. The seroconversion was similar between PLWH and healthy controls after the first (risk ratio (RR) = 0.89, 95%CI 0.76–1.04) and the second (RR = 0.97, 95%CI 0.93–1.00) dose. Moreover, the geometric mean titer (GMT) showed no significant difference between PLWH and healthy controls after the first dose (standardized mean difference (SMD) = 0.30, 95%CI -1.11, 1.70) and the second dose (SMD = -0.06, 95%CI -0.18, 0.05). Additionally, the pooled incidence rates of total adverse events among PLWH after the first and the second dose were 46.55% (95%CI 28.29–64.82%) and 30.96% (95%CI 13.23–48.70%), respectively. There was no significant difference in risks of total adverse events between PLWH and healthy controls after the first (RR = 0.86, 95%CI 0.67–1.10) and the second (RR = 0.88, 95%CI 0.68–1.14) dose. Conclusions: The available evidence suggested that the immunogenicity and safety of COVID-19 vaccines among PLWH were acceptable. There was no significant difference in the seroconversion rates and incidence rates of adverse events of COVID-19 vaccines between PLWH and healthy controls