Oscillation Criteria for Fourth-Order Nonlinear Dynamic Equations on Time Scales

We establish some new oscillation criteria for nonlinear dynamic equation of the form on an arbitrary time scale with , where are positive rd-continuous functions. An example illustrating the importance of our result is included

Efficient and Accurate Co-Visible Region Localization with Matching Key-Points Crop (MKPC): A Two-Stage Pipeline for Enhancing Image Matching Performance

Image matching is a classic and fundamental task in computer vision. In this paper, under the hypothesis that the areas outside the co-visible regions carry little information, we propose a matching key-points crop (MKPC) algorithm. The MKPC locates, proposes and crops the critical regions, which are the co-visible areas with great efficiency and accuracy. Furthermore, building upon MKPC, we propose a general two-stage pipeline for image matching, which is compatible to any image matching models or combinations. We experimented with plugging SuperPoint + SuperGlue into the two-stage pipeline, whose results show that our method enhances the performance for outdoor pose estimations. What's more, in a fair comparative condition, our method outperforms the SOTA on Image Matching Challenge 2022 Benchmark, which represents the hardest outdoor benchmark of image matching currently.Comment: 9 pages with 6 figures. Many experiments have not yet been conducted, the theoretical sections are rather concise, and the references are not adequately comprehensive. This version of the paper is being released to make this work public, and code will also be published soon. We will continue to conduct additional experiments and periodically update the pape

Global Behavior of the Difference Equation x

We study the following difference equation xn+1=(p+xn-1)/(qxn+xn-1), n=0,1,…, where p,q∈(0,+∞) and the initial conditions x-1,x0∈(0,+∞). We show that every positive solution of the above equation either converges to a finite limit or to a two cycle, which confirms that the Conjecture 6.10.4 proposed by Kulenović and Ladas (2002) is true

The effects of solvent extraction on nanoporosity of marine-continental coal and mudstone

Coal and organic-rich mudstone develop massive nanopores, which control the storage of adsorbed and free gas, as well as fluid flows. Generation and retention of bitumen and hydrocarbons of oil window reservoirs add more uncertainty to the nanoporosity. Solvent extraction is a traditional way to regain unobstructed pore networks but may cause additional effects due to interactions with rocks, such as solvent adsorbing on clay surfaces or absorbing in kerogens. Selected marine-continental coal and mudstone in Eastern Ordos Basin were studied to investigate how pore structures are affected by these in-situ-sorptive compounds (namely residual bitumen and hydrocarbons) and altered by solvent extractions. Solvent extraction was performed to obtain bitumen-free subsamples. Organic petrology, bulk geochemical analyses and gas chromatography were used to characterize the samples and the extracts. Low-pressure argon and carbon dioxide adsorptions were utilized to characterize the nanopore structures of the samples before and after extraction. The samples, both coal and mudstone, are in oil windows, with vitrinite reflectance ranging from 0.807 to 1.135%. The coals are strongly affected by marine organic input, except for the sample C-4; the mudstones are sourced by either marine or terrestrial organic input, or their mixture. As for the coals affected by marine organic input, residual bitumen and hydrocarbons occupying or blocking pores <10 nm becomes weak with thermal maturation. Bitumen derived from terrestrial organic matter mainly affects small pores, since coal asphaltene molecules are much smaller than petroleum asphaltene molecules. The mudstone M-2 with high extract production showed an increase of nanopores after extraction, due to the exposure of the filled or blocked pores. However, most transitional mudstones saw decreases of the pores because pore shrinkage caused by solvents adsorbing on and swelling clay minerals (mainly kaolinite and illite/smectite mixed layers) counteracts the released pore spaces. Solvent extractions on the coals significantly increased the micropores <0.6 nm, since the heat of sorption of alkanes reaches the peak in the pores within 0.4–0.5 nm. By contrast, solvent extractions on the mudstones decreased the micropores ∼0.35 nm, which is perhaps caused by evaporative drying of solvent displacing residual water in clay

Constructing quantum dots@flake g-C3N4 isotype heterojunctions for enhanced visible-light-driven NADH regeneration and enzymatic hydrogenation

The authors thank the financial support from National Natural Science Funds of China (21406163, 91534126, 21621004), Tianjin Research Program of Application Foundation and Advanced Technology (15JCQNJC10000), Open Funding Project of the National Key Laboratory of Biochemical Engineering (2015KF-03), and the Program of Introducing Talents of Discipline to Universities (B06006). X.W. also acknowledges financial support from The Carnegie Trust for the Universities of Scotland (70265) and The Royal Society (RG150001 and IE150611).Peer reviewedPostprin

a deep learning model to recognize food contaminating beetle species based on elytra fragments

Abstract Insect pests are often associated with food contamination and public health risks. Accurate and timely species-specific identification of pests is a key step to scale impacts, trace back the contamination process and promptly set intervention measures, which usually have serious economic impact. The current procedure involves visual inspection by human analysts of pest fragments recovered from food samples, a time-consuming and error-prone process. Deep Learning models have been widely applied for image recognition, outperforming other machine learning algorithms; however only few studies have applied deep learning for food contamination detection. In this paper, we describe our solution for automatic identification of 15 storage product beetle species frequently detected in food inspection. Our approach is based on a convolutional neural network trained on a dataset of 6900 microscopic images of elytra fragments, obtaining an overall accuracy of 83.8% in cross validation. Notably, the classification performance is obtained without the need of designing and selecting domain specific image features, thus demonstrating the promising prospects of Deep Learning models in detecting food contamination

YXQ-EQ Induces Apoptosis and Inhibits Signaling Pathways Important for Metastasis in Non-Small Cell Lung Carcinoma Cells

Background/Aims: Lung cancer is one of the most prevalent malignancies in the world. The 5-year survival rate for non-small cell lung cancer (NSCLC) patients is only approximately 15%, with metastasis as the primary cause of death. This study was aimed to investigate cytotoxic effect of external qi of Yan Xin Qigong (YXQ-EQ) toward human lung adenocarcinoma A549 cells as well as its effect on signaling pathways promoting migration, invasion and epithelial-to-mesenchymal transition (EMT) in A549 cells. Methods: Cytotoxic effect of YXQ-EQ was evaluated using MTS [3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium, inner salt] and cologenic assays. Apoptosis of treated cells was determined by Annexin V/propidium iodide staining and flow cytometry analysis, while cell migration and invasion were determined using transwell assays and EMT was assessed by morphological changes in cells. Protein expression and phosphorylation were examined by immunoblot analyses. Results: YXQ-EQ induced apoptosis in A549 cells, resulting in a pronounced reduction in viability and clonogenic formation. This was associated with inhibition of phosphorylation of AKT and ERK1/2 and reduced expression of anti-apoptotic proteins BCL-xL, XIAP and survivin. Furthermore, YXQ-EQ inhibited EGF/EGFR signaling and EGF mediated migration and invasion of A549 cells. While TGF-β1 induced phosphorylation of SMAD2/3 and EMT in A549 cells, YXQ-EQ suppressed TGF-β/SMAD signaling and induced cell death in these cells in the presence of TGF-β1. Conclusion: Our findings suggest that YXQ-EQ could exert anti-lung cancer effects via inhibiting signaling pathways that are important for NSCLC cell survival and NSCLC metastasis

Iron accumulation in the ventral tegmental area in Parkinson's disease

IntroductionThe ventral tegmental area (VTA) is less affected compared to substantia nigra pars compacta (SNc) in Parkinson's disease (PD). This study aimed to quantitatively evaluate iron content in the VTA across different stages of PD in order to help explain the selective loss of dopamine neurons in PD.MethodsQuantitative susceptibility mapping (QSM) data were obtained from 101 PD patients, 35 idiopathic rapid eye movement sleep behavior disorder (RBD) patients, and 62 healthy controls (HCs). The mean QSM values in the VTA and SNc were calculated and compared among the groups.ResultsBoth RBD and PD patients had increased iron values in the bilateral SNc compared with HCs. RBD and PD patients in the Hoehn–Yahr (H &amp; Y) stage 1 did not show elevated iron values in the VTA, while PD patients with more than 1.5 H &amp; Y staging had increased iron values in bilateral VTA compared to HCs.DiscussionThis study shows that there is no increased iron accumulation in the VTA during the prodromal and early clinical stages of PD, but iron deposition increases significantly as the disease becomes more severe