Effects of Cations and PH on Antimicrobial Activity of Thanatin and s-Thanatin against _Escherichia coli_ ATCC25922 and _B. subtilis_ ATCC 21332

Thanatin and s-thanatin were insect antimicrobial peptides which have shown potent antimicrobial activities on a variety of microbes. In order to investigate the effect of cations and pH on the activity of these peptides against Gram-negative bacteria and Gram-positive bacteria, the antimicrobial activities of both peptides were studied in increasing concentrations of monovalent cations (K^+^ and Na^+^), divalent cations (Ca^2+^ and Mg^2+^) and H^+^. The NCCLS broth microdilution method showed that both peptides were sensitive to the presence of cations. The divalent cations showed more antagonized effect on the activity against Gram-negative bacteria than the monovalent cations, since the two peptides lost the ability to inhibit bacterial growth at a very low concentration. In addition, the activities of both peptides tested were not significantly affected by pH. Comparing to studies of other antibacterial peptide activities, our data support a hypothesis that positive ions affect the sensitivity to cation peptides

Balanced Coarsening for Multilevel Hypergraph Partitioning via Wasserstein Discrepancy

We propose a balanced coarsening scheme for multilevel hypergraph partitioning. In addition, an initial partitioning algorithm is designed to improve the quality of k-way hypergraph partitioning. By assigning vertex weights through the LPT algorithm, we generate a prior hypergraph under a relaxed balance constraint. With the prior hypergraph, we have defined the Wasserstein discrepancy to coordinate the optimal transport of coarsening process. And the optimal transport matrix is solved by Sinkhorn algorithm. Our coarsening scheme fully takes into account the minimization of connectivity metric (objective function). For the initial partitioning stage, we define a normalized cut function induced by Fiedler vector, which is theoretically proved to be a concave function. Thereby, a three-point algorithm is designed to find the best cut under the balance constraint

A Multi-Transformation Evolutionary Framework for Influence Maximization in Social Networks

Influence maximization is a crucial issue for mining the deep information of social networks, which aims to select a seed set from the network to maximize the number of influenced nodes. To evaluate the influence spread of a seed set efficiently, existing studies have proposed transformations with lower computational costs to replace the expensive Monte Carlo simulation process. These alternate transformations, based on network prior knowledge, induce different search behaviors with similar characteristics to various perspectives. Specifically, it is difficult for users to determine a suitable transformation a priori. This article proposes a multi-transformation evolutionary framework for influence maximization (MTEFIM) with convergence guarantees to exploit the potential similarities and unique advantages of alternate transformations and to avoid users manually determining the most suitable one. In MTEFIM, multiple transformations are optimized simultaneously as multiple tasks. Each transformation is assigned an evolutionary solver. Three major components of MTEFIM are conducted via: 1) estimating the potential relationship across transformations based on the degree of overlap across individuals of different populations, 2) transferring individuals across populations adaptively according to the inter-transformation relationship, and 3) selecting the final output seed set containing all the transformation's knowledge. The effectiveness of MTEFIM is validated on both benchmarks and real-world social networks. The experimental results show that MTEFIM can efficiently utilize the potentially transferable knowledge across multiple transformations to achieve highly competitive performance compared to several popular IM-specific methods. The implementation of MTEFIM can be accessed at https://github.com/xiaofangxd/MTEFIM.Comment: This work has been submitted to the IEEE Computational Intelligence Magazine for publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

InterFace:Adjustable Angular Margin Inter-class Loss for Deep Face Recognition

In the field of face recognition, it is always a hot research topic to improve the loss solution to make the face features extracted by the network have greater discriminative power. Research works in recent years has improved the discriminative power of the face model by normalizing softmax to the cosine space step by step and then adding a fixed penalty margin to reduce the intra-class distance to increase the inter-class distance. Although a great deal of previous work has been done to optimize the boundary penalty to improve the discriminative power of the model, adding a fixed margin penalty to the depth feature and the corresponding weight is not consistent with the pattern of data in the real scenario. To address this issue, in this paper, we propose a novel loss function, InterFace, releasing the constraint of adding a margin penalty only between the depth feature and the corresponding weight to push the separability of classes by adding corresponding margin penalties between the depth features and all weights. To illustrate the advantages of InterFace over a fixed penalty margin, we explained geometrically and comparisons on a set of mainstream benchmarks. From a wider perspective, our InterFace has advanced the state-of-the-art face recognition performance on five out of thirteen mainstream benchmarks. All training codes, pre-trained models, and training logs, are publicly released \footnote{$https://github.com/iamsangmeng/InterFace$}.Comment: arXiv admin note: text overlap with arXiv:2109.09416 by other author

RepBNN: towards a precise Binary Neural Network with Enhanced Feature Map via Repeating

Binary neural network (BNN) is an extreme quantization version of convolutional neural networks (CNNs) with all features and weights mapped to just 1-bit. Although BNN saves a lot of memory and computation demand to make CNN applicable on edge or mobile devices, BNN suffers the drop of network performance due to the reduced representation capability after binarization. In this paper, we propose a new replaceable and easy-to-use convolution module RepConv, which enhances feature maps through replicating input or output along channel dimension by $\beta$ times without extra cost on the number of parameters and convolutional computation. We also define a set of RepTran rules to use RepConv throughout BNN modules like binary convolution, fully connected layer and batch normalization. Experiments demonstrate that after the RepTran transformation, a set of highly cited BNNs have achieved universally better performance than the original BNN versions. For example, the Top-1 accuracy of Rep-ReCU-ResNet-20, i.e., a RepBconv enhanced ReCU-ResNet-20, reaches 88.97% on CIFAR-10, which is 1.47% higher than that of the original network. And Rep-AdamBNN-ReActNet-A achieves 71.342% Top-1 accuracy on ImageNet, a fresh state-of-the-art result of BNNs. Code and models are available at:https://github.com/imfinethanks/Rep_AdamBNN.Comment: This paper has absolutely nothing to do with repvgg, rep means repeatin

Minimal Cut Sets-Based Reliability Evaluation of the More Electric Aircraft Power System

The More Electric Aircraft (MEA) stands for the direction of aviation development in the new era, and the reliability of power systems on the MEA has attracted widespread attention. Based on the characteristics of MEA power systems, an equivalent method of electrical topology structure is presented in this article, and evaluation method is proposed which shows the reliability of the overall system with the reliability of specific nodes. Firstly, electrical topology structure of a MEA power system is converted into a network node diagram according to the proposed equivalent method. Then, the minimal path sets of specific nodes are obtained by the adjacent matrix algorithm, and the low-order minimal cut sets of disjointed are obtained. After that, the actual failure rate of components is converted to node failure rate, and the reliability of the overall system is evaluated by operational reliability indexes of specific nodes. Finally, taking the MEA A380 as an example, this paper compares and analyzes the reliability of AC loads, DC loads, and key loads to verify the validity and feasibility of the proposed evaluation method. This evaluation system can predict the weak points existing in the MEA power system, as well as providing theoretical support for maintenance schedule

Endovascular Repair of Ascending Aortic Dissection A Novel Treatment Option for Patients Judged Unfit for Direct Surgical Repair

ObjectivesThis paper sought to report the outcomes of patients who are considered unfit for urgent surgical repair of ascending aortic dissections (AADs) who were treated using a novel endovascular repair strategy.BackgroundAAD is best treated by direct surgical repair. Patients who are unable to undergo this form of treatment have poor prognoses. Previously, clinical case reports related to endovascular repair of AAD have been controversial.MethodsBetween May 2009 and January 2011, 41 consecutive patients with AAD were treated in our institution. Fifteen patients were considered poor candidates for direct surgical repair and subsequently underwent the endovascular repair.ResultsThe nature of the referral process to our tertiary care facility made the median time from aortic dissection onset to treatment 25.5 days (range: 6 to 353 days). Dissections in 5 patients (33.3%) were considered acute, and those in 10 patients (66.7%) were considered chronic. The rate of successful stent-graft deployment was 100%, and there were no major morbidities or deaths in the perioperative period. Median follow-up was 26 months (range: 16 to 35 months). One new dissection occurred in the aortic arch at 3 months and was treated with a branched endograft. Significant enlargements of true lumens and decreases of false lumens and overall thoracic aorta were noted after the procedures.ConclusionsEndovascular repair of AAD was an appropriate treatment option in patients who were considered poor candidates for traditional direct surgical repair by the clinical criteria used in our institution. A larger series of cases with longer follow-up is needed to substantiate these results

DNA methylation in the APOE genomic region is associated with cognitive function in African Americans

Abstract Background Genetic variations in apolipoprotein E (APOE) and proximal genes (PVRL2, TOMM40, and APOC1) are associated with cognitive function and dementia, particularly Alzheimer’s disease. Epigenetic mechanisms such as DNA methylation play a central role in the regulation of gene expression. Recent studies have found evidence that DNA methylation may contribute to the pathogenesis of dementia, but its association with cognitive function in populations without dementia remains unclear. Methods We assessed DNA methylation levels of 48 CpG sites in the APOE genomic region in peripheral blood leukocytes collected from 289 African Americans (mean age = 67 years) from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. Using linear regression, we examined the relationship between methylation in the APOE genomic region and multiple cognitive measures including learning, memory, processing speed, concentration, language and global cognitive function. Results We identified eight CpG sites in three genes (PVRL2, TOMM40, and APOE) that showed an inverse association between methylation level and delayed recall, a measure of memory, after adjusting for age and sex (False Discovery Rate q-value < 0.1). All eight CpGs are located in either CpG islands (CGIs) or CGI shelves, and six of them are in promoter regions. Education and APOE ε4 carrier status significantly modified the effect of methylation in cg08583001 (PVRL2) and cg22024783 (TOMM40), respectively. Together, methylation of the eight CpGs explained an additional 8.7% of the variance in delayed recall, after adjustment for age, sex, education, and APOE ε4 carrier status. Methylation was not significantly associated with any other cognitive measures. Conclusions Our results suggest that methylation levels at multiple CpGs in the APOE genomic region are inversely associated with delayed recall during normal cognitive aging, even after accounting for known genetic predictors for cognition. Our findings highlight the important role of epigenetic mechanisms in influencing cognitive performance, and suggest that changes in blood methylation may be an early indicator of individuals at risk for dementia as well as potential targets for intervention in asymptomatic populations.https://deepblue.lib.umich.edu/bitstream/2027.42/143538/1/12920_2018_Article_363.pd

Intrinsic and extrinsic epigenetic age acceleration are associated with hypertensive target organ damage in older African Americans

Abstract Background Epigenetic age acceleration, a measure of biological aging based on DNA methylation, is associated with cardiovascular mortality. However, little is known about its relationship with hypertensive target organ damage to the heart, kidneys, brain, and peripheral arteries. Methods We investigated associations between intrinsic (IEAA) or extrinsic (EEAA) epigenetic age acceleration, blood pressure, and six types of organ damage in a primarily hypertensive cohort of 1390 African Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. DNA methylation from peripheral blood leukocytes was collected at baseline (1996–2000), and measures of target organ damage were assessed in a follow-up visit (2000–2004). Linear regression with generalized estimating equations was used to test for associations between epigenetic age acceleration and target organ damage, as well as effect modification of epigenetic age by blood pressure or sex. Sequential Oligogenic Linkage Analysis Routines (SOLAR) was used to test for evidence of shared genetic and/or environmental effects between epigenetic age acceleration and organ damage pairs that were significantly associated. Results After adjustment for sex, chronological age, and time between methylation and organ damage measures, higher IEAA was associated with higher urine albumin to creatinine ratio (UACR, p = 0.004), relative wall thickness (RWT, p = 0.022), and left ventricular mass index (LVMI, p = 0.007), and with lower ankle-brachial index (ABI, p = 0.014). EEAA was associated with higher LVMI (p = 0.005). Target organ damage associations for all but IEAA with LVMI remained significant after further adjustment for blood pressure and antihypertensive use (p < 0.05). Further adjustment for diabetes attenuated the IEAA associations with UACR and RWT, and adjustment for smoking attenuated the IEAA association with ABI. No effect modification by age or sex was observed. Conclusions Measures of epigenetic age acceleration may help to better characterize the functional mechanisms underlying organ damage from cellular aging and/or hypertension. These measures may act as subclinical biomarkers for damage to the kidney, heart, and peripheral vasculature; however more research is needed to determine whether these relationships remain independent of lifestyle factors and comorbidities.https://deepblue.lib.umich.edu/bitstream/2027.42/152221/1/12920_2019_Article_585.pd