Refinements of Bounds for Neuman Means

We present the sharp bounds for the Neuman means SHA, SAH, SCA and SAC in terms of the arithmetic, harmonic, and contraharmonic means. Our results are the refinements or improvements of the results given by Neuman

Multi-level Monte Carlo methods with the truncated Euler-Maruyama scheme for stochastic differential equations

The truncated Euler-Maruyama method is employed together with the Multi-level Monte Carlo method to approximate expectations of some functions of solutions to stochastic differential equations (SDEs). The convergence rate and the computational cost of the approximations are proved, when the coefficients of SDEs satisfy the local Lipschitz and Khasminskii-type conditions. Numerical examples are provided to demonstrate the theoretical results

Sharp One-Parameter Mean Bounds for Yang Mean

We prove that the double inequality Jα(a,b)<U(a,b)<Jβ(a,b) holds for all a,b>0 with a≠b if and only if α≤2/(π-2)=0.8187⋯ and β≥3/2, where U(a,b)=(a-b)/[2arctan⁡((a-b)/2ab)], and Jp(a,b)=p(ap+1-bp+1)/[(p+1)(ap-bp)]  (p≠0,-1), J0(a,b)=(a-b)/(log⁡a-log⁡b), and J-1(a,b)=ab(log⁡a-log⁡b)/(a-b) are the Yang and pth one-parameter means of a and b, respectively

Evaluation of computed tomography images under deep learning in the diagnosis of severe pulmonary infection

This work aimed to explore the diagnostic value of a deep convolutional neural network (CNN) combined with computed tomography (CT) images in patients with severe pneumonia complicated with pulmonary infection. A total of 120 patients with severe pneumonia complicated by pulmonary infection admitted to the hospital were selected as research subjects and underwent CT imaging scans. The empty convolution (EC) and U-net phase were combined to construct an EC-U-net, which was applied to process the CT images. The results showed that the learning rate of the EC-U-net model decreased substantially with increasing training times until it stabilized and reached zero after 40 training times. The segmentation result of the EC-U-net model for the CT image was very similar to that of the mask image, except for some deviations in edge segmentation. The EC-U-net model exhibited a significantly smaller cross-entropy loss function (CELF) and a higher Dice coefficient than the CNN algorithm. The diagnostic accuracy of CT images based on the EC-U-net model for severe pneumonia complicated with pulmonary infection was substantially higher than that of CT images alone, while the false negative rate (FNR) and false positive rate (FPR) were substantially lower (P &lt; 0.05). Moreover, the true positive rates (TPRs) of CT images based on the EC-U-net model for patchy high-density shadows, diffuse ground glass density shadows, pleural effusion, and lung consolidation were obviously higher than those of the original CT images (P &lt; 0.05). In short, the EC-U-net model was superior to the traditional algorithm regarding the overall performance of CT image segmentation, which can be clinically applied. CT images based on the EC-U-net model can clearly display pulmonary infection lesions, improve the clinical diagnosis of severe pneumonia complicated with pulmonary infection, and help to screen early pulmonary infection and carry out symptomatic treatment

A note on the partially truncated Euler–Maruyama method

The partially truncated Euler–Maruyama (EM) method was recently proposed in our earlier paper [3] for highly nonlinear stochastic differential equations (SDEs), where the finite-time strong LT-convergence theory was established. In this note, we will point out that one condition imposed there is restrictive in the sense that this condition might force the stepsize to be so small that the partially truncated EM method would be inapplicable. In this note, we will remove this restrictive condition but still be able to establish the finite-time strong LT-convergence rate. The advantages of our new results will be highlighted by the comparisons with our earlier results in [3]

Plasmid encoding matrix protein of vesicular stomatitis viruses as an antitumor agent inhibiting rat glioma growth in situ

Aim: Oncolytic effect of vesicular stomatitis virus (VSV) has been proved previously. Aim of the study is to investigate glioma inhibition effect of Matrix (M) protein of VSV in situ. Materials and Methods: A recombinant plasmid encoding VSV M protein (PM) was genetically engineered, and then transfected into cultured C6 gliomas cells in vitro. C6 transfected with Liposome-encapsulated PM (LEPM) was implanted intracranially for tumorigenicity study. In treatment experiment, rats were sequentially established intracranial gliomas with wild-typed C6 cells, and accepted LEPM injection intravenously. Possible mechanism of M protein was studied by using Hoechst staining, PI-stained flow cytometric analysis, TUNEL staining and CD31 staining. Results: M protein can induce generous gliomas lysis in vitro. None of the rats implanted with LEPM-treated cells developed any significant tumors, whereas all rats in control group developed tumors. In treatment experiment, smaller tumor volume and prolonged survival time was found in the LEPM-treated group. Histological studies revealed that possible mechanism were apoptosis and anti-angiogenesis. Conclusion: VSV-M protein can inhibit gliomas growth in vitro and in situ, which indicates such a potential novel biotherapeutic strategy for glioma treatment.Цель: изучить способность матриксного протеина (М протеина) вируса везикулярного стоматита (ВВС) угнетать рост глиомы in situ. Материалы и методы: сконструирована рекомбинантная плазмида, кодирующая М протеин ВВС, которая затем была трансфецирована в культивированные клетки глиомы С6 in. Клетки глиомы С6, трансфецированные инкапсулированным в липосомы М протеином (ЛИМП), имплантировали интракраниально для изучения туморогенности. В эксперименте крысам с трансплантированной интракраниально глиомой С6 (исходный штамм) внутривенно вводили ЛИМП. Апоптотическое действие М протеина на опухолевые клетки изучали с применением флуоресценцентной микроскопии (окрашивание по Хехсту), проточной цитометрии (окрашивание пропидиумом йодидом), TUNEL васкуляризацию опухоли оценивали гистологически и васкуляризацию опухоли оценивали гистологически и иммуногистохимически с применением анти-CD31 моноклональных антител. 31 моноклональных антител. 31 моноклональных антител. Результаты: М протеин может индуцировать лизис клеток глиомы in. Ни у одного животного с трансплантированными клетками глиомы, обработанными ЛИМП, не возникали опухоли значительного размера, тогда как у всех крыс из контрольной группы опухоли развивались. В группе животных, которым вводили ЛИМП, опухоли были меньшего объема и отмечали увеличение продолжительности жизни животных. Показано, что М протеин проявляет антиангиогенные свойства и обладает способностью индуцировать апоптоз. Выводы: М протеин ВВС ингибирует рост глиомы in и in. На этой основе может быть разработана потенциально новая биотерапевтическая стратегия для лечения пациентов с глиомами

The partially truncated Euler-Maruyama method and its stability and boundedness

The partially truncated Euler–Maruyama (EM) method is proposed in this paper for highly nonlinear stochastic differential equations (SDEs). We will not only establish the finite-time strong Lr-convergence theory for the partially truncated EM method, but also demonstrate the real benefit of the method by showing that the method can preserve the asymptotic stability and boundedness of the underlying SDEs