Opportunistic Wiretapping/Jamming: A New Attack Model in Millimeter-Wave Wireless Networks

While the millimeter-wave (mmWave) communication is robust against the conventional wiretapping attack due to its short transmission range and directivity, this paper proposes a new opportunistic wiretapping and jamming (OWJ) attack model in mmWave wireless networks. With OWJ, an eavesdropper can opportunistically conduct wiretapping or jamming to initiate a more hazardous attack based on the instantaneous costs of wiretapping and jamming. We also provide three realizations of the OWJ attack, which are mainly determined by the cost models relevant to distance, path loss and received power, respectively. To understand the impact of the new attack on mmWave network security, we first develop novel approximation techniques to characterize the irregular distributions of wiretappers, jammers and interferers under three OWJ realizations. With the help of the results of node distributions, we then derive analytical expressions for the secrecy transmission capacity to depict the network security performance under OWJ. Finally, we provide extensive numerical results to illustrate the effect of OWJ and to demonstrate that the new attack can more significantly degrade the network security performance than the pure wiretapping or jamming attack

Uni-QSAR: an Auto-ML Tool for Molecular Property Prediction

Recently deep learning based quantitative structure-activity relationship (QSAR) models has shown surpassing performance than traditional methods for property prediction tasks in drug discovery. However, most DL based QSAR models are restricted to limited labeled data to achieve better performance, and also are sensitive to model scale and hyper-parameters. In this paper, we propose Uni-QSAR, a powerful Auto-ML tool for molecule property prediction tasks. Uni-QSAR combines molecular representation learning (MRL) of 1D sequential tokens, 2D topology graphs, and 3D conformers with pretraining models to leverage rich representation from large-scale unlabeled data. Without any manual fine-tuning or model selection, Uni-QSAR outperforms SOTA in 21/22 tasks of the Therapeutic Data Commons (TDC) benchmark under designed parallel workflow, with an average performance improvement of 6.09\%. Furthermore, we demonstrate the practical usefulness of Uni-QSAR in drug discovery domains

Water Balance Analysis of Hulun Lake, a Semi-Arid UNESCO Wetland, Using Multi-Source Data

Hulun Lake is the largest lake in northeastern China, and its basin is located in China and Mongolia. This research aims to analyze the dynamic changes in the water volume of Hulun Lake and to estimate the groundwater recharge of the lake during the past 60 years. Multi-source data were used, and water-level-data-interpolation extrapolation, water-balance equations, and other methods were applied. The proportion of the contribution of each component to the quantity of water in Hulun Lake during the last 60 years was accurately calculated. Evaporation loss was the main component in the water loss in Hulun Lake. In the last 60 years, the average annual runoff into the lake was about 1.202 billion m3, and it was the factor with the largest variation range and the leading factor affecting the changes in the quantity of water in Hulun Lake. There was groundwater recharge in Hulun Lake for a long period, and the average annual groundwater recharge was about 776 million m3 (excluding leakage). The contribution ratio of the river water, groundwater, and precipitation to the recharging of Hulun Lake was about 5:3:2. The changes in the quantity of water in Hulun Lake are affected by climate change and human activities in China and Mongolia, especially those in Mongolia

Evidence for the contribution of COMT gene Val158/108Met polymorphism (rs4680) to working memory training-related prefrontal plasticity.

BackgroundGenetic factors have been suggested to affect the efficacy of working memory training. However, few studies have attempted to identify the relevant genes.MethodsIn this study, we first performed a randomized controlled trial (RCT) to identify brain regions that were specifically affected by working memory training. Sixty undergraduate students were randomly assigned to either the adaptive training group (N = 30) or the active control group (N = 30). Both groups were trained for 20 sessions during 4 weeks and received fMRI scans before and after the training. Afterward, we combined the data from the 30 participants in the RCT study who received adaptive training with data from 71 additional participants who also received the same adaptive training but were not part of the RCT study (total N = 101) to test the contribution of the COMT Val158/108Met polymorphism to the interindividual difference in the training effect within the identified brain regions.ResultsIn the RCT study, we found that the adaptive training significantly decreased brain activation in the left prefrontal cortex (TFCE-FWE corrected p = .030). In the genetic study, we found that compared with the Val allele homozygotes, the Met allele carriers' brain activation decreased more after the training at the left prefrontal cortex (TFCE-FWE corrected p = .025).ConclusionsThis study provided evidence for the neural effect of a visual-spatial span training and suggested that genetic factors such as the COMT Val158/108Met polymorphism may have to be considered in future studies of such training

Analytical solution of the nitracline with the evolution of subsurface chlorophyll maximum in stratified water columns

In a stratified water column, the nitracline is a layer where the nitrate concentration increases below the nutrient-depleted upper layer, exhibiting a strong vertical gradient in the euphotic zone. The subsurface chlorophyll maximum layer (SCML) forms near the bottom of the euphotic zone, acting as a trap to diminish the upward nutrient supply. Depth and steepness of the nitracline are important measurable parameters related to the vertical transport of nitrate into the euphotic zone. The correlation between the SCML and the nitracline has been widely reported in the literature, but the analytic solution for the relationship between them is not well established. By incorporating a piecewise function for the approximate Gaussian vertical profile of chlorophyll, we derive analytical solutions of a specified nutrient-phytoplankton model. The model is well suited to explain basic dependencies between a nitracline and an SCML. The analytical solution shows that the nitracline depth is deeper than the depth of the SCML, shoaling with an increase in the light attenuation coefficient and with a decrease in surface light intensity. The inverse proportional relationship between the light level at the nitracline depth and the maximum rate of new primary production is derived. Analytic solutions also show that a thinner SCML corresponds to a steeper nitracline. The nitracline steepness is positively related to the light attenuation coefficient but independent of surface light intensity. The derived equations of the nitracline in relation to the SCML provide further insight into the important role of the nitracline in marine pelagic ecosystems

Inhibition of HSP90 attenuates porcine reproductive and respiratory syndrome virus production in vitro

BACKGROUND: Porcine reproductive and respiratory syndrome virus (PRRSV) infection leads to substantial economic losses to the swine industry worldwide. However, no effective countermeasures exist to combat this virus infection so far. The most common antiviral strategy relies on directly inhibiting viral proteins. However, this strategy invariably leads to the emergence of drug resistance due to the error-prone nature of viral ploymerase. Targeting cellular proteins required for viral infection for developing new generation of antivirals is gaining concern. Recently, heat shock protein 90 (HSP90) was found to be an important host factor for the replication of multiple viruses and the inhibition of HSP90 showed significant antiviral effects. It is thought that the inhibition of HSP90 could be a promising broad-range antiviral approach. However, the effects of HSP90 inhibition on PRRSV infection have not been evaluated. In the current research, we tried to inhibit HSP90 and test whether the inhibition affect PRRSV infection. METHODS: We inhibit the function of HSP90 with two inhibitors, geldanamycin (GA) and 17- allylamono-demethoxygeldanamycin (17-AAG), and down-regulated the expression of endogenous HSP90 with specific small-interfering RNAs (siRNAs). Cell viability was measured with alamarBlue. The protein level of viral N was determined by western blotting and indirect immunofluorescence (IFA). Besides, IFA was employed to examine the level of viral double-stranded RNA (dsRNA). The viral RNA copy number and the level of IFN-β mRNA were determined by quantitative real-time PCR (qRT-PCR). RESULTS: Our results indicated that both HSP90 inhibitors showed strong anti-PRRSV activity. They could reduce viral production by preventing the viral RNA synthesis. These inhibitory effects were not due to the activation of innate interferon response. In addition, we observed that individual knockdown targeting HSP90α or HSP90β did not show dramatic inhibitory effect. Combined knockdown of these two isoforms was required to reduce viral infection. CONCLUSIONS: Our results shed light on the possibility of developing potential therapeutics targeting HSP90 against PRRSV infection

Direct Observation of Enhanced Raman Scattering on Nano-Sized ZrO2 Substrate: Charge-Transfer Contribution

Direct observation of the surface-enhanced Raman scattering (SERS) of molecules adsorbed on nano-sized zirconia (ZrO2) substrates was first reported without the need for the addition of metal particles. It was found that ZrO2 nanoparticles can exhibit unprecedented Raman signal enhancements on the order of 103 for the probe molecule 4-mercaptobenzoic acid (4-MBA). The dramatic effect of the calcination temperature on the ZrO2 nanoparticles was also investigated. The ZrO2 nanoparticles with the particle diameter of 10.5 nm, which were prepared by calcination at a temperature of 500°C, have the highest SERS activity. A comparison between the experimental and calculation results indicates that charge transfer (CT) effects dominate the surface enhancement. The plentiful surface state of ZrO2 active substrate that is beneficial to CT resonance occurs between molecules and ZrO2 to produce a SERS effect. The CT process depends, to a large extent, on the intrinsic properties of the modifying molecules and the surface properties of the ZrO2. This is a new SERS phenomenon for ZrO2 that will expand the application of ZrO2 to microanalysis and is beneficial for studying the basic properties of both ZrO2 and SERS

KIAA1199 promotes migration and invasion by Wnt/β-catenin pathway and MMPs mediated EMT progression and serves as a poor prognosis marker in gastric cancer

Background KIAA1199 was upregulated in diverse cancers, but the association of KIAA1199 with gastric cancer (GC), the biological role of KIAA1199 in GC cells and the related molecular mechanisms remain to be elucidated. Methods KIAA1199 expression was analysed by reverse transcription-polymerase chain reaction assay (RT-PCR) and immunohistochemistry (IHC) in GC patient tissue. The small hairpin RNA (shRNA) was applied for the knockdown of endogenous KIAA1199 in NCI-N87 and AGS cells. MTT, colony formation, scratch wounding migration, transwell chamber migration and invasion assays were employed respectively to investigate the role of KIAA1199 in GC cells. The potential signaling pathway of KIAA1199 induced migration and invasion was detected. Results KIAA1199 was upregulated in GC tissue and was an essential independent marker for poor prognosis. Knockdown KIAA1199 suppressed the proliferation, migration and invasion in GC cells. KIAA1199 stimulated the Wnt/β-catenin signaling pathway and the enzymatic activity of matrix metalloproteinase (MMP) family members and thus accelerated the epithelial-to-mesenchymal transition (EMT) progression in GC cells. Conclusion These findings demonstrated that KIAA1199 was upregulated in GC tissue and associated with worse clinical outcomes in GC, and KIAA1199 acted as an oncogene by promoting migration and invasion through the enhancement of Wnt/β-catenin signaling pathway and MMPs mediated EMT progression in GC cell

Converting Redox Signaling to Apoptotic Activities by Stress-Responsive Regulators HSF1 and NRF2 in Fenretinide Treated Cancer Cells

BACKGROUND: Pharmacological intervention of redox balance in cancer cells often results in oxidative stress-mediated apoptosis, attracting much attention for the development of a new generation of targeted therapy in cancer. However, little is known about mechanisms underlying the conversion from oxidative signaling to downstream activities leading cells to death. METHODOLOGY/PRINCIPAL FINDINGS: We here report a systematic detection of transcriptome changes in response to oxidative signals generated in leukemia cells upon fenretinide treatment, implicating the occurrence of numerous stress-responsive events during the fenretinide induced apoptosis, such as redox response, endoplasmic reticulum stress/unfolded protein response, translational repression and proteasome activation. Moreover, the configuration of these relevant events is primarily orchestrated by stress responsive transcription factors, as typically highlighted by NF-E2-related factor-2 (NRF2) and heat shock factor 1 (HSF1). Several lines of evidence suggest that the coordinated regulation of these transcription factors and thus their downstream genes are involved in converting oxidative signaling into downstream stress-responsive events regulating pro-apoptotic and apoptotic activities at the temporal and spatial levels, typifying oxidative stress-mediated programmed death rather than survival in cancer cells. CONCLUSIONS/SIGNIFICANCE: This study provides a roadmap for understanding oxidative stress-mediated apoptosis in cancer cells, which may be further developed into more sophisticated therapeutic protocols, as implicated by synergistic induction of cell apoptosis using proteasome inhibitors with fenretinide