Systemic Chemotherapy Including Ramucirumab in Combination With Pressurized Intra-Peritoneal Aerosol Chemotherapy Is a Safe Treatment Option for Peritoneal Metastasis of Gastric Cancer

BackgroundPressurized intraperitoneal aerosol chemotherapy (PIPAC) is a laparoscopic technique for local chemotherapy. It has been used for treatment of peritoneal metastasis of gastric cancer (PM GC) in combination with systemic therapy. VEGFR2 antagonist ramucirumab is a second-line therapy for GC, and has been suspected to cause wound healing disorders.MethodsThis is a retrospective single center cohort study of patients with PM GC, who received PIPAC treatment in combination with systemic chemotherapy with and without ramucirumab. Data on patients’ characteristics and their perioperative courses were collected and complication rates were compared with regard to preoperative use of ramucirumab and time between last dose of systemic therapy and PIPAC treatment.ResultsFifty patients underwent 90 PIPAC treatments for PM GC in 3 years. Overall postoperative morbidity was 11% with 6% severe complications. The mean interval between systemic therapy and PIPAC was 20 days. Neither the length of interval nor the use of ramucirumab had an effect on complication rates.ConclusionOur study suggests that addition of ramucirumab to pre-PIPAC systemic therapy, irrespective of the length of the treatment-free interval before PIPAC, does not increase the risk of postoperative complications and is therefore a safe option for treatment of PM GC.

High Order Time Series Forecasting using Fuzzy Discretization

In recent years, various methods for forecasting fuzzy time series have been presented in different areas, such as stock price, enrollments, weather, production etc. It is observed that in most of the cases, static length of intervals/equal length of interval has been used. Length of the interval has significant role on forecasting accuracy. The objective of this present study is to incorporate the idea of fuzzy discretization into interval creation and examine the effect of positional information of elements within a group or interval to the forecast. This idea outperforms the existing high order forecast methods using fixed interval. Experiments are carried on three datasets including Lahi production data, enrollment data and rainfall data which deal with a lot of uncertainty.

Evaluation of reproductive performance in sows of PresticeBlack-Pied pig - Czech genetic resource

The aim of the study was to evaluate reproductive performance in selected sows of Prestice Black-Pied pig included in Czech genetic resources and also to analyse losses of piglets and culling of sows according to parity order. The experimental work was conducted in a nucleic herd of sows registered in breeding book. A total of 88 sows were included in the observation. Findings indicate that productive parameters of Prestice Black-Pied sows are comparable to productive parameters of modern genotype sows. The results also showed that the highes conception rate after the first insemination was achieved after the second, the third and the fourth parity. Analysis of gestation length revealed that it was significantly influenced by the parity. Very highly significant difference (P<0.001) was found between the 1st and the 2nd parity and between the 1st and the 4th parity. Total numbers of piglets and numbers live-born, stillborn and reared piglets per litter increased significantly (P<0.001, P<0.01, P<0.05) up to the 4th parity, afterwards they continuously decreased. The number of stillborn piglets was the lowest at the 2nd parity, the highest at the 5th and the 6th parity (P<0.05). Length of interval was highly significantly different (P<0.01) between the 2nd and the 5th parity and significantly different (P<0.05) between the 4th and the 5th parity. Differences in the losses of piglets were not significant among parities. The most radical culling of sows was recorded after the 3rd and the 4th parity.

Time Series Forecasting with Stochastic Markov Models Based on Fuzzy Set and Grey Theory

The stochastic Markov model is combined with fuzzy set concept and grey system for improving forecasting performance. The data for model test is obtained from ACI including Hong Kong, Beijing, Taoyuan, Incheon and Narita international airport. The empirical results show that fuzzy Markov model has better predictive performance with the data with trend and intercept. For the data with random walk, grey Markov model performs better. The paper also examines the effects of transition state and length of interval on the forecasting performance with the result. Keywords: Markov model, Grey Markov model, Air cargo flow, ARIMA, MAPE.

The Research of Wind Power Fluctuation in Different Time Intervals

Power from wind turbines is mainly related to the wind speed. Due to the influence of the uncertainty of the wind, intermittent and wind farm in units of the wake, wind power has fluctuations. Based on the field measurement, it is found that t location-scale distribution is suitable to identify the probability distribution of wind power variations. By analyzing the fluctuation of a single in different time intervals, we find that the distribution of wind power fluctuation possesses a certain trend pattern. With the length of the time window increasing, the fluctuations increase and some information has been missed. We define an index to calculate the quantity of missing information and can use that to evaluate whether a certain length of interval is acceptable.