A NOVEL EVALUATION APPROACH TO FINDING LIGHTWEIGHT MACHINE LEARNING ALGORITHMS FOR INTRUSION DETECTION IN COMPUTER NETWORK

Building practical and efficient intrusion detection systems in computer network is important in industrial areas today and machine learning technique provides a set of effective algorithms to detect network intrusion. To find out appropriate algorithms for building such kinds of systems, it is necessary to evaluate various types of machine learning algorithms based on specific criteria. In this paper, we propose a novel evaluation formula which incorporates 6 indexes into our comprehensive measurement, including precision, recall, root mean square error, training time, sample complexity and practicability, in order to find algorithms which have high detection rate, low training time, need less training samples and are easy to use like constructing, understanding and analyzing models. Detailed evaluation process is designed to get all necessary assessment indicators and 6 kinds of machine learning algorithms are evaluated. Experimental results illustrate that Logistic Regression shows the best overall performance

PSO-FNN-Based Vertical Handoff Decision Algorithm in Heterogeneous Wireless Networks

AbstractAiming at working out the problem that fuzzy logic and neural network based vertical handoff algorithm didn’t consider the load state reasonably in heterogeneous wireless networks, a PSO-FNN-based vertical handoff decision algorithm is proposed. The algorithm executes factors reinforcement learning for the fuzzy neural network (FNN) with the objective of the equal blocking probability to adapt for load state dynamically, and combined with particle swarm optimization (PSO) algorithm with global optimization capability to set initial parameters in order to improve the precision of parameter learning. The simulation results show that the PSO-FNN algorithm can balance the load of heterogeneous wireless networks effectively and decrease the blocking probability as well as handoff call blocking probability compared to sum-received signal strength (S-RSS) algorithm

Comparison of serum apolipoprotein A-I between Chinese multiple sclerosis and other related autoimmune disease

<p>Abstract</p> <p>Background</p> <p>Serum apolipoprotein (apo) A-I was considered to be an immune regulator and could suppress pro-inflammatory cytokines generated by activated T cell in some autoimmune diseases. However, the change of serum apoA-I levels in multiple sclerosis (MS) patients is unknown.</p> <p>Methods</p> <p>In the presentation we performed a study on serum apoA-I levels in the patients with MS. We enrolled some age and gender matched patients with MS, autoimmune demyelinating diseases (Guillain-Barre Syndrome and Clinically Isolated Syndrome), neuroinflammatory diseases (viral encephalitis), autoimmune connective diseases (rheumatoid arthritis and systemic lupus erythematosus) and healthy control groups, and tested their serum lipids levels: total cholesterol (TC), triglyceride (TG), high-density lipoproteins (HDL), apolipoproteinB100 (apoB100), apolipoproteinA-I (apoA-I).</p> <p>Results</p> <p>For all patients, age had no effect on serum apoA-I levels (<it>P </it>> 0.05). Meanwhile, we proved the highest serum apoA-I levels in MS patients and the lowest serum apoA-I levels in SLE patients. Serum apoA-I levels was significantly elevated in female MS patients (P = 0.033; P < 0.05).</p> <p>Conclusion</p> <p>In short we believed that patients with MS and other autoimmune demyelination had significantly decreased serum levels of apo A-I.</p

Transcriptomic and metabolomic analysis reveals the influence of carbohydrates on lignin degradation mediated by Bacillus amyloliquefaciens

IntroductionLigninolytic bacteria can secrete extracellular enzymes to depolymerize lignin into small-molecular aromatics that are subsequently metabolized and funneled into the TCA cycle. Carbohydrates, which are the preferred carbon sources of bacteria, influence the metabolism of lignin-derived aromatics through bacteria.MethodsIn this study, untargeted metabolomics and transcriptomics analyses were performed to investigate the effect of carbohydrates on lignin degradation mediated by Bacillus amyloliquefaciens MN-13, a strain with lignin-degrading activity that was isolated in our previous work.ResultsThe results demonstrated that the cell growth of the MN-13 strain and lignin removal were promoted when carbohydrates such as glucose and sodium carboxymethyl cellulose were added to an alkaline lignin-minimal salt medium (AL-MSM) culture. Metabolomics analysis showed that lignin depolymerization took place outside the cells, and the addition of glucose regulated the uptake and metabolism of lignin-derived monomers and activated the downstream metabolism process in cells. In the transcriptomics analysis, 299 DEGs were screened after 24 h of inoculation in AL-MSM with free glucose and 2 g/L glucose, respectively, accounting for 8.3% of the total amount of annotated genes. These DEGs were primarily assigned to 30 subcategories, including flagellar assembly, the PTS system, RNA degradation, glycolysis/gluconeogenesis, the TCA cycle, pyruvate metabolism, and tryptophan metabolism. These subcategories were closely associated with the cell structure, generation of cellular energy, and precursors for biosynthetic pathways, based on a − log 10 (P adjust) value in the KEGG pathway analysis.ConclusionIn summary, the addition of glucose increased lignin degradation mediated by the MN-13 strain through regulating glycolysis, TCA cycle, and central carbon metabolism

Ruminal microbiota and muscle metabolome characteristics of Tibetan plateau yaks fed different dietary protein levels

IntroductionThe dietary protein level plays a crucial role in maintaining the equilibrium of rumen microbiota in yaks. To explore the association between dietary protein levels, rumen microbiota, and muscle metabolites, we examined the rumen microbiome and muscle metabolome characteristics in yaks subjected to varying dietary protein levels.MethodsIn this study, 36 yaks were randomly assigned to three groups (n = 12 per group): low dietary protein group (LP, 12% protein concentration), medium dietary protein group (MP, 14% protein concentration), and high dietary protein group (HP, 16% protein concentration).Results16S rDNA sequencing revealed that the HP group exhibited the highest Chao1 and Observed_species indices, while the LP group demonstrated the lowest. Shannon and Simpson indices were significantly elevated in the MP group relative to the LP group (P &lt; 0.05). At the genus level, the relative abundance of Christensenellaceae_R-7_group in the HP group was notably greater than that in the LP and MP groups (P &lt; 0.05). Conversely, the relative abundance of Rikenellaceae_RC9_gut_group displayed an increasing tendency with escalating feed protein levels. Muscle metabolism analysis revealed that the content of the metabolite Uric acid was significantly higher in the LP group compared to the MP group (P &lt; 0.05). The content of the metabolite L-(+)-Arabinose was significantly increased in the MP group compared to the HP group (P &lt; 0.05), while the content of D-(-)-Glutamine and L-arginine was significantly reduced in the LP group (P &lt; 0.05). The levels of metabolites 13-HPODE, Decanoylcarnitine, Lauric acid, L-(+)-Arabinose, and Uric acid were significantly elevated in the LP group relative to the HP group (P &lt; 0.05). Furthermore, our observations disclosed correlations between rumen microbes and muscle metabolites. The relative abundance of NK4A214_group was negatively correlated with Orlistat concentration; the relative abundance of Christensenellaceae_R-7_group was positively correlated with D-(-)-Glutamine and L-arginine concentrations.DiscussionOur findings offer a foundation for comprehending the rumen microbiome of yaks subjected to different dietary protein levels and the intimately associated metabolic pathways of the yak muscle metabolome. Elucidating the rumen microbiome and muscle metabolome of yaks may facilitate the determination of dietary protein levels

Cross-correlated quantum thermometry using diamond containing dual-defect centers

The contactless temperature measurement at micro/nanoscale is vital to a broad range of fields in modern science and technology. The nitrogen vacancy (NV) center, a kind of diamond defect with unique spin-dependent photoluminescence, has been recognized as one of the most promising nanothermometers. However, this quantum thermometry technique has been prone to a number of possible perturbations, which will unavoidably degrade its actual temperature sensitivity. Here, for the first time, we have developed a cross-validated optical thermometry method using a bulk diamond sample containing both NV centers and silicon vacancy (SiV) centers. Particularly, the latter allowing all-optical method has been intrinsically immune to those influencing perturbations for the NV-based quantum thermometry, hence serving as a real-time cross validation system. As a proof-of-concept demonstration, we have shown a trustworthy temperature measurement under the influence of varying magnetic fields. This multi-modality approach allows a synchronized cross-validation of the measured temperature, which is required for micro/nanoscale quantum thermometry in complicated environments such as a living cell

Causal relationship between gut microbiota and diabetic nephropathy: a two-sample Mendelian randomization study

ObjectiveEmerging evidence has provided compelling evidence linking gut microbiota (GM) and diabetic nephropathy (DN) via the “gut-kidney” axis. But the causal relationship between them hasn’t been clarified yet. We perform a Two-Sample Mendelian randomization (MR) analysis to reveal the causal connection with GM and the development of DN, type 1 diabetes nephropathy (T1DN), type 2 diabetes nephropathy (T2DN), type 1 diabetes mellitus (T1DM), and type 2 diabetes mellitus (T2DM).MethodsWe used summary data from MiBioGen on 211 GM taxa in 18340 participants. Generalized MR analysis methods were conducted to estimate their causality on risk of DN, T1DN, T2DN, T1DM and T2DM from FinnGen. To ensure the reliability of the findings, a comprehensive set of sensitivity analyses were conducted to confirm the resilience and consistency of the results.ResultsIt was showed that Class Verrucomicrobiae [odds ratio (OR) =1.5651, 95%CI:1.1810-2.0742,PFDR=0.0018], Order Verrucomicrobiales (OR=1.5651, 95%CI: 1.1810-2.0742, PFDR=0.0018) and Family Verrucomicrobiaceae (OR=1.3956, 95%CI:1.0336-1.8844, PFDR=0.0296) had significant risk of DN. Our analysis found significant associations between GM and T2DN, including Class Verrucomimicrobiae (OR=1.8227, 95% CI: 1.2414-2.6763, PFDR=0.0139), Order Verrucomimicrobiae (OR=1.5651, 95% CI: 1.8227-2.6764, PFDR=0.0024), Rhodospirillales (OR=1.8226, 95% CI: 1.2412-2.6763, PFDR=0.0026), and Family Verrucomicroniaceae (OR=1.8226, 95% CI: 1.2412-2.6763, PFDR=0.0083). The Eubacteriumprotogenes (OR=0.4076, 95% CI: 0.2415-0.6882, PFDR=0.0021) exhibited a protection against T1DN. Sensitivity analyses confirmed that there was no significant heterogeneity and pleiotropy.ConclusionsAt the gene prediction level, we identified the specific GM that is causally linked to DN in both T1DM and T2DM patients. Moreover, we identified distinct microbial changes in T1DN that differed from those seen in T2DN, offering valuable insights into GM signatures associated with subtype of nephropathy

Ferroelectric memristor based on Pt/BiFeO3/Nb-doped SrTiO3 heterostructure

We report a continuously tunable resistive switching behavior in Pt/BiFeO₃/Nb-doped SrTiO₃ heterostructure for ferroelectric memristor application. The resistance of this memristor can be tuned up to 5 × 10⁵% by applying voltage pulses at room temperature, which exhibits excellent retention and anti-fatigue characteristics. The observed memristive behavior is attributed to the modulation effect of the ferroelectric polarization reversal on the width of depletion region and the height of potential barrier of the p-n junction formed at the BiFeO₃/Nb-doped SrTiO₃ interface.This work was supported by the National Natural Science Foundation of China (Grant Nos. 11074193 and 51132001). Q.L. and Y.L. acknowledge the support of the Australian Research Council (ARC) in the form of ARC Discovery Grants

Fe–Ga/Pb(Mg1/3Nb2/3)O3–PbTiO3 magnetoelectric laminate composites

We have found large magnetoelectric (ME) effects in long-type laminate composites of Fe–20%Ga magnetostrictive alloys and piezoelectric Pb(Mg1/3Nb2/3)O3–PbTiO3 single crystals. At lower frequencies, the ME voltage coefficient of a laminate with longitudinally magnetized and longitudinally polarized (i.e., L-L mode) layers was 1.41 V/Oe (or1.01 V/cm Oe). Near the natural resonant frequency ( ∼ 91 kHz) of the laminate, the ME voltage coefficients were found to be dramatically increased to 50.7 V/Oe (36.2 V/cm Oe)for the L-L mode. In addition, the laminate can detect a minute magnetic field as low as ∼ 2×10−12 T at resonance frequency, and ∼ 1×10−10 T at lower frequencies