The continuous pollution routing problem

In this paper, we presented an ε-accurate approach to conduct a continuous optimization on the pollution routing problem (PRP). First, we developed an ε-accurate inner polyhedral approximation method for the nonlinear relation between the travel time and travel speed. The approximation error was controlled within the limit of a given parameter ε, which could be as low as 0.01% in our experiments. Second, we developed two ε-accurate methods for the nonlinear fuel consumption rate (FCR) function of a fossil fuel-powered vehicle while ensuring the approximation error to be within the same parameter ε. Based on these linearization methods, we proposed an ε-accurate mathematical linear programming model for the continuous PRP (ε-CPRP for short), in which decision variables such as driving speeds, travel times, arrival/departure/waiting times, vehicle loads, and FCRs were all optimized concurrently on their continuous domains. A theoretical analysis is provided to confirm that the solutions of ε-CPRP are feasible and controlled within the predefined limit. The proposed ε-CPRP model is rigorously tested on well-known benchmark PRP instances in the literature, and has solved PRP instances optimally with up to 25 customers within reasonable CPU times. New optimal solutions of many PRP instances were reported for the first time in the experiments

Optimal mathematical programming and variable neighborhood search for k-modes categorical data clustering

The conventional k-modes algorithm and its variants have been extensively used for categorical data clustering. However, these algorithms have some drawbacks, e.g., they can be trapped into local optima and sensitive to initial clusters/modes. Our numerical experiments even showed that the k-modes algorithm could not identify the optimal clustering results for some special datasets regardless the selection of the initial centers. In this paper, we developed an integer linear programming (ILP) approach for the k-modes clustering, which is independent to the initial solution and can obtain directly the optimal results for small-sized datasets. We also developed a heuristic algorithm that implements iterative partial optimization in the ILP approach based on a framework of variable neighborhood search, known as IPO-ILP-VNS, to search for near-optimal results of medium and large sized datasets with controlled computing time. Experiments on 38 datasets, including 27 synthesized small datasets and 11 known benchmark datasets from the UCI site were carried out to test the proposed ILP approach and the IPO-ILP-VNS algorithm. The experimental results outperformed the conventional and other existing enhanced k-modes algorithms in literature, updated 9 of the UCI benchmark datasets with new and improved results

Quantitative Assessment and Grading of Hardware Trojan Threat Based on Rough Set Theory

The globalization of integrated circuit (IC) design and fabrication has given rise to severe concerns with respect to modeling strategic interaction between malicious attackers and Hardware Trojan (HT) defenders using game theory. The quantitative assessment of attacker actions has made the game very challenging. In this paper, a novel rough set theory framework is proposed to analyze HT threat. The problem is formulated as an attribute weight calculation and element assessment in an information system without decision attributes. The proposed method introduces information content in the rough set that allows calculation of the weight of both core attributes and non-core attributes. For quantitative assessment, the HT threat is characterized by the closeness coefficient. In order to allow HT defenders to use fast and effective countermeasures, a threat classification method based on the k-means algorithm is proposed, and the Best Workspace Prediction (BWP) index is used to determine the number of clusters. Statistical tests were performed on the benchmark circuits in Trust-hub in order to demonstrate the effectiveness of the proposed technique for assessing HT threat. Compared with k-means, equidistant division-based k-means, and k-means++, our method shows a significant improvement in both cluster accuracy and running time

TRPV1+ neurons alter Staphylococcus aureus skin infection outcomes by affecting macrophage polarization and neutrophil recruitment

Abstract Background The interaction between the nervous system and the immune system can affect the outcome of a bacterial infection. Staphylococcus aureus skin infection is a common infectious disease, and elucidating the relationship between the nervous system and immune system may help to improve treatment strategies. Results In this study, we found that the local release of calcitonin gene-related peptide (CGRP) increased during S. aureus skin infection, and S. aureus could promote the release of CGRP from transient receptor potential cation channel subfamily V member 1 (TRPV1+) neurons in vitro. The existence of TRPV1+ neurons inhibited the recruitment of neutrophils to the infected region and regulated the polarization of macrophages toward M2 while inhibiting polarization toward M1. This reduces the level of inflammation in the infected area, which aggravates the local infection. Furthermore, this study demonstrates that TRPV1 may be a target for the treatment of S. aureus skin infections and that botulinum neurotoxin A (BoNT/A) and BIBN4096 may reverse the inhibited inflammatory effect of CGRP, making them potential therapeutics for the treatment of skin infection in S. aureus. Conclusions In S. aureus skin infection, TRPV1+ neurons inhibit neutrophil recruitment and regulate macrophage polarization by releasing CGRP. BoNT/A and BIBN4096 may be potential therapeutic agents for S. aureus skin infection

Effects of Shizhifang on NLRP3 Inflammasome Activation and Renal Tubular Injury in Hyperuricemic Rats

Objective. Uric acid (UA) activates the NLRP3-ASC-caspase-1 axis and triggers cascade inflammatory that leads to hyperuricemic nephropathy and hyperuricemia-induced renal tubular injury. The original study aims to verify the positive effects of the traditional Chinese medicinal formula Shizhifang (SZF) on ameliorating the hyperuricemia, tubular injury, and inflammasome infiltration in the kidneys of hyperuricemic lab rats. Method. Twenty-eight male Sprague-Dawley rats were divided into four groups: control group, oxonic acid potassium (OA) model group, OA + SZF group, and OA + Allopurinol group. We evaluated the mediating effects of SZF on renal mitochondrial reactive oxygen species (ROS) and oxidative stress (OS) products, protein expression of NLRP3-ASC-caspase-1 axis, and downstream inflammatory factors IL-1β and IL-18 after 7 weeks of animals feeding. Result. SZF alleviated OA-induced hyperuricemia and inhibited OS in hyperuricemic rats (P<0.05). SZF effectively suppressed the expression of gene and protein of the NLRP3-ASC-caspase-1 axis through accommodating the ROS-TXNIP pathway (P<0.05). Conclusion. Our data suggest that SZF alleviates renal tubular injury and inflammation infiltration by inhibiting NLRP3 inflammasome activation triggered by mitochondrial ROS in the kidneys of hyperuricemic lab rats

Selective oxidative protection leads to tissue topological changes orchestrated by macrophage during ulcerative colitis

Abstract Ulcerative colitis is a chronic inflammatory bowel disorder with cellular heterogeneity. To understand the composition and spatial changes of the ulcerative colitis ecosystem, here we use imaging mass cytometry and single-cell RNA sequencing to depict the single-cell landscape of the human colon ecosystem. We find tissue topological changes featured with macrophage disappearance reaction in the ulcerative colitis region, occurring only for tissue-resident macrophages. Reactive oxygen species levels are higher in the ulcerative colitis region, but reactive oxygen species scavenging enzyme SOD2 is barely detected in resident macrophages, resulting in distinct reactive oxygen species vulnerability for inflammatory macrophages and resident macrophages. Inflammatory macrophages replace resident macrophages and cause a spatial shift of TNF production during ulcerative colitis via a cytokine production network formed with T and B cells. Our study suggests components of a mechanism for the observed macrophage disappearance reaction of resident macrophages, providing mechanistic hints for macrophage disappearance reaction in other inflammation or infection situations