The Prediction Value of the Infection Probability Score (IPS) Combined with Serum Cholinesterase and D-Dimer Detection for Infection and Survival in Critically Ill Patients

Objective: To evaluate early prediction value of IPS combined with SchE and D-dimer detection for infection and survival in critically ill patients. Methods: 199 critically ill patients admitted to the emergency intensive care unit (EICU) of our hospital from December 2018 to December 2019 were retrospectively analyzed, including 110 infection patients (infection group) and 89 non-infection patients (non-infection group). According to the survival, the infection group was divided into death group (68 cases) and survival group (42 cases). The IPS, APACHE II, SOFA and SchE, D-dimer expression levels were detected and compared;Univariate and logistic regression analysis were used to evaluate the independent prognostic factors. Results: The IPS and APACHE II of patients in the infected group were higher than those in the non-infected group, the level of SchE was lower than that in the non-infected group, and the level of D-dimer was higher than that in the non-infected group (P < 0.001). IPS, SOFA, APACHE II, SchE, D-dimer, invasive mechanical ventilation, septic shock, and ICU length of stay had significant influence on the prognosis of critically ill patients (P < 0.001). Logistic regression analysis showed that IPS (OR = 2.821, 95% CI 1.501 - 5.227), SOFA (OR = 5.078, 95% CI 3.327 - 7.690), APACHE II (OR = 14.308, 95% CI 8.901 - 21.893), SchE (OR = 0.223, 95% CI 0.165 - 0.291), D-dimer (OR = 2.10, 95% CI 1.55 - 2.85), septic shock (OR = 9.948, 95% CI 7.012 - 17.012) were independent factors affecting the prognosis of critically ill patients with infection (P < 0.001). Conclusion: IPS and D-dimer expression level in infected patients were increased and SchE decreased significantly compared with those in non-infected patients, and they significantly correlated with disease severity of infected patients and could be early prediction for prognosis.

Survival probability and ruin probability of a risk model

In this paper, a new risk model is studied in which the rate of premium income is regarded as a random variable, the arrival of insurance policies is a Poisson process and the process of claim occurring is p-thinning process. The integral representations of the survival probability are gotten. The explicit formula of the survival probability on the infinite interval is obtained in the special casc cxponential distribution.The Lundberg inequality and the common formula of the ruin probability are gotten in terms of some techniques from martingale theory.

LAPLACE TRANSFORM OF THE SURVIVAL PROBABILITY UNDER SPARRE ANDERSEN MODEL

In this paper a class of risk processes in which claims occur as a renewal process is studied. A clear expression for Laplace transform of the survival probability is well given when the claim amount distribution is Erlang distribution or mixed Erlang distribution. The expressions for moments of the time to ruin with the model above are given.

Modelling and Assessment of Survival Probability of Shock Model with Two Kinds of Shocks

The study aims at modelling and assessment of survival probability of a component experiencing two kinds of shocks namely, damage shock and fatal shock. Shocks are occurring randomly in time as events of a Poisson Process. The two cases of fixed/random threshold of components are studied. Survival probabilities of proposed models are derived. Maximum likelihood estimators (MLEs) of survival probabilities are obtained using the data from life testing experiments. Fisher information and asymptotic distribution of MLEs of parameters are obtained when a constant threshold is considered. Computation and comparison of estimators of two cases (constant threshold and random threshold) are made through simulation studies. The study recommends the consideration of threshold as a random variable.

Survival Probability of the Quantum Walk with Phase Parameters on the Two-Dimensional Trapped Lattice

We investigate the time dependence of the survival probability of quantum walks governed by Fibonacci walks with phase parameters on the trapped two-dimensional lattice. We have shown that the survival probability of the quantum walk decays with time obey to the stretched exponential law for all initial states of walkers. We have also shown that stretched exponential decay parameter β can be arranged by phase parameter combination. Obtained numerical results show that phase parameters can be used as a control parameter to determine the decay rate of the survival probability of the quantum walk.

The Survival Probability in Generalized Poisson Risk Model

In this paper we generalize the aggregated premium income process from a constant rate process to a poisson process for the classical compound Poinsson risk model,then for the generalized model and the classical compound poisson risk model ,we respectively get its survival probability in finite time period in case of exponential claim amounts.

RANDOMIZATION METHOD OF DETERMINISTIC EQUATION FOR PROBABILITY FRACTURE MECHANICS

In order to obtain any probability of survival for crack growth life, a randomization method of deterministic equation for probability fracture mechanics is presented. According to this method, the deterministic equation of fracture mechanics is randomized to stochastic equation, and the parameters of the stochastic equation are estimated by means of the statistics. Three new kinds of random models to gain the p d a/ d N Δ K curve and the γ p d a/ d N Δ K curve (confidence level probability of survival fatigue crack growth rate stress intensity factor range curve) are proposed by using this randomization method. And the p d a/ d N Δ K curves and the γ p d a/ d N Δ K curves determined by these three models are discussed and compared according to the treatment result of the experimental data from CT specimens. From examples, it is found that the three deterministic fatigue crack growth rate equations determined by these models are very near and in agreement with the traditional deterministic fatigue crack growth rate equation, and these models are effectively and easily used to treat fatigue crack growth rate data.

Factors affecting post-release survival and dispersal of reintroduced Crested Ibis(Nipponia nippon)in Tongchuan City,China

Reintroduction has become a common conservation management tool to restore endangered species in their historical range.However,many attempts have failed to establish self-sustaining populations in the wild.The success of reintroductions could be improved by varying release strategies.Therefore,it is vital to determine the factors influencing reintroduction outcomes.To better understand the post-release settlement and to optimize the release strategy of the Crested Ibis(Nipponia nippon),we quantified the effects of age,sex,acclimation duration,and the timing of release events on post-release survival and dispersal distance for the released Crested Ibis in Tongchuan City,Shaanxi Province,using a generalized linear mixed effect modeling approach.Our results indicate that 40–56.3%of the released individuals survived the first year following release.Mortality was attributable to flight collisions,starvation,disease,and unknown reasons.The post-release survival probability of ibises showed a negative association with age(estimate=-0.186;95%CI:-0.350 to-0.022;P=0.026),and post-release dispersal distance was affected by the timing of release event(estimate=0.718;95%CI:0.025 to1.253;P=0.042).However,sex and acclimation period duration did not cause detectable differences in postrelease survival probability and dispersal distance.Based on our results,optimal release strategies for establishing a reintroduced population of the Crested Ibis include:(1)release of sub-adults biased and sex ratio balanced initial groups;(2)release during the non-breeding season;and(3)food supplementation immediately after release.

Computer program of nonlinear, curved regression for ‘probacent’-probability equation in biomedicine

On the basis of experimental observations on animals, applications to clinical data on patients and theoretical statistical reasoning, the author developed a com-puter-assisted general mathematical model of the ‘probacent’-probability equation, Equation (1) and death rate (mortality probability) equation, Equation (2) derivable from Equation (1) that may be applica-ble as a general approximation method to make use-ful predictions of probable outcomes in a variety of biomedical phenomena [1-4]. Equations (1) and (2) contain a constant, γ and c, respectively. In the pre-vious studies, the author used the least maximum- difference principle to determine these constants that were expected to best fit reported data, minimizing the deviation. In this study, the author uses the method of computer-assisted least sum of squares to determine the constants, γ and c in constructing the ‘probacent’-related formulas best fitting the NCHS- reported data on survival probabilities and death rates in the US total adult population for 2001. The results of this study reveal that the method of com-puter-assisted mathematical analysis with the least sum of squares seems to be simple, more accurate, convenient and preferable than the previously used least maximum-difference principle, and better fit-ting the NCHS-reported data on survival probabili-ties and death rates in the US total adult population. The computer program of curved regression for the ‘probacent’-probability and death rate equations may be helpful in research in biomedicine.

A New Statistical Modeling Approach for Survival Analysis of Cancer Patients—Multiple Myeloma Cancer

Background: The Cox Proportional Hazard (Cox-PH) model has been a popularly used method for survival analysis of cancer data given the survival times as a function of covariates or risk factors. However, it is very seldom to see the assumptions for the application of the Cox-PH model satisfied in most of the research studies, raising questions about the effectiveness, robustness, and accuracy of the model predicting the proportion of survival times. This is because the necessary assumptions in most cases are difficult to satisfy, as well as the assessment of interaction among covariates. Methods: To further improve the therapeutic/treatment strategy for cancer diseases, we proposed a new approach to survival analysis using multiple myeloma (MM) cancer data. We first developed a data-driven nonlinear statistical model that predicts the survival times with 93% accuracy. We then performed a parametric analysis on the predicted survival times to obtain the survival function which is used in estimating the proportion of survival times. Results: The new proposed approach for survival analysis has proved to be more robust and gives better estimates of the proportion of survival than the Cox-PH model. Also, satisfying the proposed model assumptions and finding interactions among risk factors is less difficult compared to the Cox-PH model. The proposed model can predict the real values of the survival times and the identified risk factors are ranked according to the percent of contribution to the survival time. Conclusion: The new proposed nonlinear statistical model approach for survival analysis of cancer diseases is very efficient and provides an improved and innovative strategy for cancer therapeutic/treatment.

Construction of <i>k</i>-Variate Survival Functions with Emphasis on the Case <i>k</i>= 3

The purpose of this paper is to present a general universal formula for k-variate survival functions for arbitrary k = 2, 3, ..., given all the univariate marginal survival functions. This universal form of k-variate probability distributions was obtained by means of “dependence functions” named “joiners” in the text. These joiners determine all the involved stochastic dependencies between the underlying random variables. However, in order that the presented formula (the form) represents a legitimate survival function, some necessary and sufficient conditions for the joiners had to be found. Basically, finding those conditions is the main task of this paper. This task was successfully performed for the case k = 2 and the main results for the case k = 3 were formulated as Theorem 1 and Theorem 2 in Section 4. Nevertheless, the hypothetical conditions valid for the general k ≥ 4 case were also formulated in Section 3 as the (very convincing) Hypothesis. As for the sufficient conditions for both the k = 3 and k ≥ 4 cases, the full generality was not achieved since two restrictions were imposed. Firstly, we limited ourselves to the, defined in the text, “continuous cases” (when the corresponding joint density exists and is continuous), and secondly we consider positive stochastic dependencies only. Nevertheless, the class of the k-variate distributions which can be constructed is very wide. The presented method of construction by means of joiners can be considered competitive to the copula methodology. As it is suggested in the paper the possibility of building a common theory of both copulae and joiners is quite possible, and the joiners may play the role of tools within the theory of copulae, and vice versa copulae may, for example, be used for finding proper joiners. Another independent feature of the joiners methodology is the possibility of constructing many new stochastic processes including stationary and Markovian.

SAR图像中PS点的识别与选取

提出一种基于小波相位分析的永久散射体(persistent scatterer,PS)的识别与选取方法.该方法将小波理论引入到PS点识别与选取中,利用基于小波相位分析的差分干涉图滤波方法,首先对差分干涉相位图进行滤波处理,然后估算滤波后各PS候选点的噪声相位、衡量指标以及各PS点的概率,从而在兼顾各PS候选点幅度和相位的稳定性基础上实现SAR图像中PS点的有效识别与选取.理论分析和实验结果表明,该方法识别与选取的PS点是有效而且可靠的.

基于分时散射目标的非城区地形PS-InSAR监测

永久散射体(PS)在非城区的分布密度通常难以满足PS-InSAR技术的地形监测需求,导致PS-InSAR监测误差较大,而非城区通常存在一定时段内的散射目标,即分时散射目标,为此,本文提出基于分时散射目标的改进PS-InSAR算法。首先采用通过边缘保持EMD算法对SAR影像干涉对进行降噪;然后以双层K-means聚类提取非城区的分时散射目标候选集,并通过可信概率提取可靠的分时散射目标;最后通过组内加权参数迭代和组间等权融合,计算监测区的地表形变。试验结果表明,提取的分时散射目标与同位置PS点具有相近的分布特性和变化趋势,较大地提高了非城区目标点的分布密度,提高了非城区地表形变监测的精度。

Increasing the frequency of CIK cells adoptive immunotherapy may decrease risk of death in gastric cancer patients

AIM: To analyze the correlation between cytokineinduced killer (CIK) cells adoptive immunotherapy and cancer-related death in gastric cancer patients. METHODS: One hundred and fifty-six gastric cancer patients after operation at the Third Affiliated Hospital of Soochow University were enrolled in this study. Their clinical data including demographic characteristics, operation time, tumor size, pathological type and staging, tumor metastasis, outcome of chemotherapy or CIK cells adoptive immunotherapy, survival time or time of death were collected with a standard structured questionnaire. Kaplan-Meier method was used to estimate the median survival time, and the 2- and 5- year survival rates. Hazard risk (HR) and 95% confidence interval (95% CI) of CIK cells adoptive immunotherapy for gastric cancer were calculated using the two-stage time-dependent covariates Cox model. RESULTS: The survival time of gastric cancer patients was longer after CIK cells adoptive immunotherapy than after chemotherapy (χ 2 = 10.907, P = 0.001). The median survival time of gastric cancer patients was also longer after CIK cells adoptive immunotherapy than after chemotherapy (49 mo vs 27 mo, P < 0.05). The 2- and 5-year survival rates of gastric cancer patients were significantly higher after CIK cells adoptive immunotherapy than after chemotherapy (73.5% vs 52.6%, 40.4% vs 23.9%, P < 0.05). A significant difference was observed in the survival curve for patients who received CIK cells adoptive immunotherapy (0, 1-10, 11-25, and over 25 frequencies) (χ 2 = 14.534, P = 0.002). The frequencies of CIK cells adoptive immunotherapy were significantly related with the decreasing risk of death in gastric cancer patients after adjustment for sex and age of the patients, tumor stage and relapse (HR = 0.54, 95% CI: 0.36-0.80) when the first stage Cox model was used to define the subjects who remained alive beyond 36 mo as survivors. However, no correlation was observed between the frequencies of death in CIK cells adoptive immunotherapy and the risk of gastric cancer patients (HR = 1.09, 95% CI: 0.63-0.89) when the second stage Cox model was used to define the subjects who survived for more than 36 mo as survivors. CONCLUSION: The survival time of the gastric cancer patients treated with chemotherapy combined with CIK cells adoptive immunotherapy is significantly longer than that of the patients treated with chemotherapy alone and increasing the frequency of CIK cells adoptive immunotherapy seems to benefit patients more.

RWPSO与马尔科夫链的无人机航路规划

粒子群算法(PSO)是基于种群的全局搜索算法,具有原理简单,搜索稳定高效等特性,在航路规划领域被普遍运用,但是其在陷入局部最优以及收敛速度方面都存在一定的缺陷.本文针对无人机的任务权重值与生存权重值引入随机游走策略,按照一定规律改变粒子的惯性权重值,可以有效的避免上述情况发生,提升无人机在航路规划中找到最优路径的效率.另一方面,为了能够给规划的路径提供优劣性的判断标准或参考依据,需要构建适用于评估无人机飞行路径点上的生存状态概率模型,本文将随机游走粒子群算法(RWPSO)的航路规划模型与马尔科夫链生存状态随机性模型相结合,得到一个可以用来评估路径点生存概率的航路规划问题模型.仿真结果表明,基于任务权重、生存权重、任务生存权重随机游走的RWPSO算法在寻优时比PSO、量子粒子群算法(QPSO)效率更高,并成功结合马尔科夫链得到一个可以描述出无人机生存概率变化的模型.此模型框架还能够扩展应用于有辐射源、武器、电磁干扰等复杂场景中的航路与任务规划.

Complications Following Surgery for Gastric Cancer: Analysis of Prospectively Collected Data

Background and Aims: The complication rate after surgery for gastric cancer varies according to the particular definition of morbidity, so it’s necessary to report them using a standardized method, the Clavien-Dindo system. The purpose of this study was to prospectively analyze all post-gastrectomy complications in patients with gastric adenocarcinoma according to the severity grade using Clavien-Dindo system, in order to identify risk factors for postoperative complications and their prognostic significance on survival. Methods: This study is based on data from 90 consecutive patients who underwent gastrectomy for gastric neoplasia between January 2010 and February 2014 at the same unit. 15 patients were excluded (benign tumors, GISTs, missing data). Complications were categorized according to the Clavien-Dindo classification (uncomplicated patients vs patients classified ≥Grade I). The following risk factors were studied: age, BMI, sex, operation method, extent of resection, duration of surgery, transfusions, TNM staging, and lymph node ratio. Multivariate logistic regression was used to evaluate the association between risk factors and presence of complications. To assess the effect on overall survival, after selection of covariates using backward elimination, the Cox proportional hazard model was applied. Results: Among these patients, 49 (65.3%) developed complications, stratified as follows: Grade I, 6 (8%);Grade II, 24 (32%);Grade III, 6 (8%);Grade IV, 13 (17.3%). The laparoscopic technique (OR = 0.050;95% CI = 0.005 - 0.550, p = 0.0143) and no transfusions (OR = 0.219;95% CI = 0.058 - 0.827, p = 0.0251) were found to reduce the incidence of postoperative complications in the multivariate analysis. With regard to the survival analysis, lymph node ratio, malnutrition, extended resection and presence of complications were significant predictors of reduced survival in the multivariate analysis. Conclusions: Some variables can predict the risk of postoperative complications, the occurrence of which is a predictor of reduced probability of survival. In this respect it’s essential to reduce complications.

Calculation model of military aircraft suryiyability to a missile

Since missiles are main threat against aircrafts in air war,a model is proposed for calculating the aircraft survivability to a missile.The hit characteristic of aircraft to a missile is analyzed,and then Monte Carlo method is applied to generate missile detonation location according to its distribution rule.In addition,based on the analysis of fragment trajectory and critical components,the intersection point of these two is determined.Then the kill probability of critical component to a fragment can be calculated,and the aircraft survivability to a missile is obtained accordingly.Finally,the feasibility of the proposed method is demonstrated.Simulation results show that this method captures the basic effects of missile detonation locations on aircraft survivability,which may provide an effective reference to aircraft survivability research.

Shape Evolution of the Compound Nucleus in the Superheavy Element Synthesis Reaction via the BUU Model

By taking the BUU model, we simulate the superheavy element synthesis reaction. With the rotation effect being included in the BUU model, the effect of the non-centrality of the reaction ^48Ca＋^238U→^286 112 is studied. It is shown that the promising impact parameter in the synthesis process can be released from zero to a value little smaller than the radius of the smaller nucleus involved in the reaction. Meanwhile, the compound nucleus may involve rich shape phases.

On single particle breakage behavior of crushable weathered sands

This paper presents an experimental study on single particle breakage behavior of crushable weathered sands by a number of single particle uniaxial compression tests to comprehensively investigate the characteristics of single particle breakage,the probability of survival of single particle,and the effects of particle size and weathering on single particle strengths.The behavior of single particle under uniaxial compression falls into the mixed five phases:damage by chipping,elastic deformation,fragmentation by partial fracture,breakage by splitting,and the residuals,demonstrating the complexity and variability of the tensile strengths of single particles.The behavior of single particle breakage was quantified herein by the initial fracture and failure strengths of single particle.The probability of survival decreased as the characteristic stresses increased.An increase in the particle size or weathering number of single particle resulted in a reduction in the probability of survival of single particle.For a given probability of survival,the difference in the initial fracture characteristic stress and failure characteristic stress decreased with increasing particle size but showed a complex change with increasing weathering number.The probability of survival showed greater variability for the normalized initial fracture characteristic stress than for the normalized failure characteristic stress,implying that the initial fracture stresses of single particles diverged more than the failure stresses of the particles.The average initial fracture and failure characteristic stresses,and the initial fracture and failure characteristic stresses corresponding to 1/e(37%)survival of single particles decreased while increasing particle size or weathering number,but the decrease showed a sharper rate for smaller single particles with a lower weathering number.The ln-ln coordinates showed a linear representation of the failure characteristic stress and particle size,verifying the applicability of Weibull theory to single particle breakage.However,weathering resulted in downward translation and slight rotation of the linear relation of the failure characteristic stress and particle size in the ln-ln coordinates.

Solution of the Fuzzy Equation <i>A + X = B</i>Using the Method of Superimposition

Fuzzy equations were solved by using different standard methods. One of the well-known methods is the method of α-cut. The method of superimposition of sets has been used to define arithmetic operations of fuzzy numbers. In this article, it has been shown that the fuzzy equation , where A, X, B are fuzzy numbers can be solved by using the method of superimposition of sets. It has also been shown that the method gives same result as the method of α-cut.