In this paper, we study the classification and evolution of bifurcation curves of semipositone problem with Minkowski-curvature operator{−(u′/1−u′2)′=λf(u), in (−L,L),u(−L)=u(L)=0,where λ,L>0, ...f∈C2(0,∞), and the following conditions (H1)–(H2) hold:(H1)there exists β>0 such that (β−u)f(u)<0 for u>0 and u≠β.(H2)Let F(u)≡∫0uf(t)dt. Then F:0,∞)⟶R is continuous and differentiable for u>0. And there exists η>0 such that (η−u)F(u)<0 for u>0 and u≠η. Notice that we allow f(0+)=−∞. In particular, we further obtain the exact shapes of the bifurcation curve as f is convex or concave. Finally, we apply these results in several problems.
Stress-induced neuroinflammation was considered to play a critical role in the pathogenesis of depression. Transcutaneous auricular vagus nerve stimulation (taVNS) is a relatively non-invasive ...alternative treatment for patients suffering from major depressive disorder. The anti-inflammatory signal of vagus nerve is mediated by α7 nicotinic acetylcholine receptor (α7nAchR), and the hippocampus, the region with the most distribution of α7nAchR, regulates emotions. Here, we investigated the role of α7nAchR mediating hippocampal neuroinflammation in taVNS antidepressant effect though homozygous α7nAChR (-/-) gene knockout and α7nAchR antagonist (methyllycaconitine, MLA).
There were control, model, taVNS, α7nAChR(-/-) + taVNS, hippocampus (Hi) MLA + taVNS and Hi saline + taVNS groups. We used the chronic unpredicted mild stress (CUMS) method to establish depressive model rats for 42 days, excepting control group. After the successful modeling, except the control and model, the rats in the other groups were given taVNS, which was applied through an electroacupuncture apparatus at the auricular concha (2/15 Hz, 2 mA, 30 min/days) for 21 days. Behavioral tests were conducted at baseline, after modeling and after taVNS intervention, including sucrose preference test (SPT), open field test (OFT) and forced swimming test (FST). These tests are widely used to evaluate depression-like behavior in rats. The samples were taken after experiment, the expressions of α7nAchR, NF-κB p65, IL-1β and the morphology of microglia were detected.
Depression-like behavior and hippocampal neuroinflammation in CUMS model rats were manifested by down-regulated expression of α7nAchR, up-regulated expression of NF-κB p65 and IL-1β, and the morphology of microglia was in amoebic-like activated state. TaVNS could significantly reverse the above-mentioned phenomena, but had rare improvement effect for α7nAChR(-/-) rats and Hi MLA rats.
The antidepressant effect of taVNS is related to hippocampal α7nAchR/NF-κB signal pathway.
Adversarial robustness of deep neural networks has been actively investigated. However, most existing defense approaches are limited to a specific type of adversarial perturbations. Specifically, ...they often fail to offer resistance to multiple attack types simultaneously, i.e., they lack multi-perturbation robustness. Furthermore, compared to image recognition problems, the adversarial robustness of video recognition models is relatively unexplored. While several studies have proposed how to generate adversarial videos, only a handful of approaches about defense strategies have been published in the literature. In this paper, we propose one of the first defense strategies against multiple types of adversarial videos for video recognition. The proposed method, referred to as MultiBN, performs adversarial training on multiple adversarial video types using multiple independent batch normalization (BN) layers with a learning-based BN selection module. With a multiple BN structure, each BN brach is responsible for learning the distribution of a single perturbation type and thus provides more precise distribution estimations. This mechanism benefits dealing with multiple perturbation types. The BN selection module detects the attack type of an input video and sends it to the corresponding BN branch, making MultiBN fully automatic and allowing end-to-end training. Compared to present adversarial training approaches, the proposed MultiBN exhibits stronger multi-perturbation robustness against different and even unforeseen adversarial video types, ranging from Lp-bounded attacks and physically realizable attacks. This holds true on different datasets and target models. Moreover, we conduct an extensive analysis to study the properties of the multiple BN structure.
Multi-label learning paradigm, which aims at dealing with data associated with potential multiple labels, has attracted a great deal of attention in machine intelligent community. In this paper, we ...propose a novel multi-label twin support vector machine (MLTSVM) for multi-label classification. MLTSVM determines multiple nonparallel hyperplanes to capture the multi-label information embedded in data, which is a useful promotion of twin support vector machine (TWSVM) for multi-label classification. To speed up the training procedure, an efficient successive overrelaxation (SOR) algorithm is developed for solving the involved quadratic programming problems (QPPs) in MLTSVM. Extensive experimental results on both synthetic and real-world multi-label datasets confirm the feasibility and effectiveness of the proposed MLTSVM.
•The first nonparallel hyperplane SVM (MLTSVM) classifier applied in multi-label learning is proposed.•The multi-label information of the dataset can be effectively captured by multiple nonparallel hyperplanes.•The ambiguity of the predicting procedure is avoided by the effective decision function.•An efficient SOR algorithm is applied to solve the proposed MLTSVM.•Experimental results confirm the feasibility and superiority of the proposed MLTSVM.
The hotel industry is essential for tourism. With the rapid expansion of the internet, consumers only search for their desired keywords on the website when they trying to find a hotel to stay, ...causing the relevant hotel information would appear. To quickly respond to the changing market and consumer habits, each hotel must focus on its website information and information quality. This study proposes a novel methodology that uses rough set theory (RST), principal component analysis, t-Distributed Stochastic Neighbor Embedding (t-SNE), and attribute performance visualization to explore the relationship between hotel star ratings and hotel website information quality. The collected data are based on the star-rated hotels of the Taiwanstay website, and the checklists of hotel website services are used to obtain the relevant attributes data. The results show that there are significant differences in information quality between hotels below two stars and those above four stars. The information quality provided by the higher star hotels was more detailed than that offered by low-star hotels. Based on the attribute performance matrix, the one-star and two-star hotels have advantage attributes in their landscape, reply time, restaurant information, social media, and compensation. Furthermore, the three-five star hotels have advantage attributes in their operational support, compensation, restaurant information, traffic information, and room information. These results could be provided to the stakeholders as a reference.
Non-parallel hyperplane classifiers have attracted many attention due to their wider applicability than parallel hyperplane classifiers, and it accelerates the training speed through separately ...training of each hyperplane. However, it does not consider the correlation relationship among the non-parallel hyperplanes. In addition, since these non-parallel hyperplanes are built on the same training data, there may exist correlation among them due to redundancy of the data. In this paper, we investigate the decorrelation problem of non-parallel hyperplane classifiers. We integrate non-parallel hyperplanes into a unified model and explore this relationship through a joint classifier learning approach. Taking the twin support vector machine as an example, a novel decorrelation regularization term is added into the joint problem. Additionally, an effective alternating optimization algorithm has been introduced to address this nonconvex problem. To evaluate the proposed method, a series of experiments are conducted on binary and multi-class classification datasets from the benchmark database repository. Experimental results compared to several parallel and non-parallel hyperplane based classifiers demonstrate the effectiveness of the proposed method.
•A unified non-parallel SVM with decorrelation TWJCL for multi-class classification is proposed.•Compared to JCL, TWJCL achieves decorrelation in each binary classification.•Experiments show TWJCL has low correlation coefficient and good classification performance.
In this paper, we study the classification and evolution of bifurcation curves of positive solutions for the one-dimensional Minkowski-curvature problem{−(u′/1−u′2)′=λf(u), in (−L,L),u(−L)=u(L)=0, ...where λ,L>0, f∈C0,∞)∩C2(0,∞) and f(u)>0 for u≥0. Furthermore, we show that, for sufficiently large L>0, the bifurcation curve SL may have arbitrarily many turning points. Finally, we apply these results to obtain the global bifurcation diagrams for Ambrosetti–Brezis–Cerami problem, Liouville–Bratu–Gelfand problem and perturbed Gelfand problem with the Minkowski-curvature operator, respectively. Moreover, we will make two lists which show the different properties of bifurcation curves for Minkowski-curvature problems, corresponding semilinear problems and corresponding prescribed curvature problems.
Abstract
Tumor cells have long been recognized as a relative contraindication to hyperbaric oxygen treatment (HBOT) since HBOT might enhance progressive cancer growth. However, in an oxygen deficit ...condition, tumor cells are more progressive and can be metastatic. HBOT increasing in oxygen partial pressure may benefit tumor suppression. In this study, we investigated the effects of HBOT on solid tumors, such as lung cancer. Non-small cell human lung carcinoma A549-cell-transferred severe combined immunodeficiency mice (SCID) mice were selected as an in vivo model to detect the potential mechanism of HBOT in lung tumors. HBOT not only improved tumor hypoxia but also suppressed tumor growth in murine xenograft tumor models. Platelet endothelial cell adhesion molecule (PECAM-1/CD31) was significantly increased after HBOT. Immunostaining of cleaved caspase-3 was demonstrated and apoptotic tumor cells with nuclear debris were aggregated starting on the 14th-day after HBOT. In vitro
,
HBOT suppressed the growth of A549 cells in a time-dependent manner and immediately downregulated the expression of p53 protein after HBOT in A549 cells. Furthermore, HBOT-reduced p53 protein could be rescued by a proteasome degradation inhibitor, but not an autophagy inhibitor in A549 cells. Our results demonstrated that HBOT improved tissue angiogenesis, tumor hypoxia and increased tumor apoptosis to lung cancer cells in murine xenograft tumor models, through modifying the tumor hypoxic microenvironment. HBOT will merit further cancer therapy as an adjuvant treatment for solid tumors, such as lung cancer.
The inedible parts of nuts and stone fruits are low‐cost and lignin‐rich feedstock for more sustainable production of aromatic chemicals in comparison with the agricultural and forestry residues. ...However, the depolymerization performances on food‐related biomass remains unclear, owing to the broad physicochemical variations from the edible parts of the fruits and plant species. In this study, the monomer production potentials of ten major fruit and nutshell biomass were investigated with comprehensive numerical information derived from instrumental analysis, such as plant cell wall chemical compositions, syringyl/guaiacyl (S/G ratios, and contents of lignin substructure linkages (β‐O‐4, β–β, β‐5). A standardized one‐pot reductive catalytic fractionation (RCF) process was applied to benchmark the monomer yields, and the results were statistically analyzed. Among all the tested biomass, mango endocarp provided the highest monolignol yields of 37.1 % per dry substrates. Positive S‐lignin (70–84 %) resulted in higher monomer yield mainly due to more cleavable β‐O‐4 linkages and less condensed C−C linkages. Strong positive relationships were identified between β‐O‐4 and S‐lignin and between β‐5 and G‐lignin. The analytical, numerical, and experimental results of this study shed lights to process design of lignin‐first biorefinery in food‐processing industries and waste management works.
This study explores the monomer production potential of fruit and nutshell biomass for sustainable aromatic chemical production. Mango endocarp exhibits the highest monolignol yield, attributed to positive S‐lignin and specific linkages. The findings inform lignin‐first biorefinery design in food‐processing industries and waste management.
PDF
