Mapping Network-Coordinated Stacked Gated Recurrent Units for Turbulence Prediction

Accurately predicting fluid forces acting on the sur-face of a structure is crucial in engineering design.However,this task becomes particularly challenging in turbulent flow,due to the complex and irregular changes in the flow field.In this study,we propose a novel deep learning method,named mapping net-work-coordinated stacked gated recurrent units(MSU),for pre-dicting pressure on a circular cylinder from velocity data.Specifi-cally,our coordinated learning strategy is designed to extract the most critical velocity point for prediction,a process that has not been explored before.In our experiments,MSU extracts one point from a velocity field containing 121 points and utilizes this point to accurately predict 100 pressure points on the cylinder.This method significantly reduces the workload of data measure-ment in practical engineering applications.Our experimental results demonstrate that MSU predictions are highly similar to the real turbulent data in both spatio-temporal and individual aspects.Furthermore,the comparison results show that MSU predicts more precise results,even outperforming models that use all velocity field points.Compared with state-of-the-art methods,MSU has an average improvement of more than 45%in various indicators such as root mean square error(RMSE).Through comprehensive and authoritative physical verification,we estab-lished that MSU’s prediction results closely align with pressure field data obtained in real turbulence fields.This confirmation underscores the considerable potential of MSU for practical applications in real engineering scenarios.The code is available at https://github.com/zhangzm0128/MSU.

Preoperative gastric retention in endoscopic retrograde cholangiopancreatography

We comment on the article by Jia et al,in the World Journal of Gastrointestinal Surgery.We focus mainly on the factors that impair gastric motility and cause gastric retention in the pre-operative setting of endoscopic retrograde cholan-giopancreatography(ERCP).ERCP is a complex endoscopic therapeutic proce-dure,which demands great skill from the endoscopist but also has recognized complications.Gastric retention impairs the endoscopist’s visibility but also increases the risk of complications,such as aspiration pneumonia.Therefore,identifying the factors that predispose to gastric retention alerts the endoscopists of the possible risks and enables them to take evasive action.The authors in the current study by Jia et al developed and validated a predictive model,which in-corporates five different factors,i.e.,gender,primary disease,jaundice,opioid use,and gastrointestinal obstruction,which were found to influence gastric retention.This model was shown to have a high predictive value to accurately identify pa-tients at risk for gastric retention before a therapeutic ERCP.

Mobility-Aware Adaptive Beam Tracking for Vehicles in Mm Wave Communication Networks

The millimeter wave(mm Wave)is a potential solution for high data rate communication due to its availability of large bandwidth.However,it is challenging to perform beam tracking in vehicular mm Wave communication systems due to high mobility and narrow beams.In this paper,an adaptive beam tracking algorithm is proposed to improve the network throughput performance while reducing the training signal overhead.In particular,based on the mobility prediction at base station(BS),a novel frame structure with dynamic bundled timeslot is designed.Moreover,an actor-critic reinforcement learning based algorithm is proposed to obtain the joint optimization of both beam width and the number of bundled timeslots,which makes the beam tracking adapt to the changing environment.Simulation results demonstrate that,compared with the traditional full scan and Kalman filter based beam tracking algorithms,our proposed algorithm can improve the time-averaged throughput by 11.34%and 24.86%respectively.With the newly designed frame structure,it also outperforms beam tracking with conventional frame structure,especially in scenarios with large range of vehicle speeds.

Influence of climatic conditions,topography and soil attributes on the spatial distribution of site productivity index of the species rich forests of Jalisco,Mexico

This paper presents an approach based on field data to model the spatial distribution of the site productivity index （SPI） of the diverse forest types in Jalisco, Mexico and the response in SPI to site and cli-matic conditions. A linear regression model was constructed to test the hypothesis that site and climate variables can be used to predict the SPI of the major forest types in Jalisco. SPI varied significantly with topog-raphy （elevation, aspect and slope）, soil attributes （pH, sand and silt）, climate （temperature and precipitation zones） and forest type. The most important variable in the model was forest type, which accounted for 35% of the variability in SPI. Temperature and precipitation accounted for 8 to 9% of the variability in SPI while the soil attributes accounted for less than 4% of the variability observed in SPI. No significant differences were detected between the observed and predicted SPI for the individual forest types. The linear regression model was used to develop maps of the spatial variability in predicted SPI for the individual forest types in the state. The spatial site productivity models developed in this study provides a basis for understanding the complex relationship that exists between forest productivity and site and climatic conditions in the state. Findings of this study will assist resource managers in making cost-effective decisions about the management of individual forest types in the state of Jalisco, Mexico.

Prediction and Control of Wrinkle and Fracture for Stamping Regular Polygonal Box

Based on the deformation characteristic of regular polygonal box stamped parts and the superfluous triangle material wrinkle model,the criterion of regular polygonal box stamped parts without wrinkle was deduced and used to predict and control the wrinkle limit.According to the fracture model,the criterion of regular polygonal box stamped parts without fracture was deduced and used to predict and control the fracture limit.Combining the criterion for stamping without wrinkle with that without fracture,the stamping criterion of regular polygonal box stamped parts was obtained to predict and control the stamping limit.Taken the stainless steel0Cr18Ni9(SUS304)sheet and the square box stamped part as examples,the limit diagram was given to predict and control the wrinkle,fracture and stamping limits.It is suitable for the deep drawing without flange,the deep drawing and stretching combined forming with flange and the rigid punch stretching of plane blank.The limit deep-drawing coefficient and the minimum deep-drawing coefficient can be determined,and the appropriate BHF(blank holder force)and the deep-drawing force can be chosen.These provide a reference for the technology planning,the die and mold design and the equipment determination,and a new criterion evaluating sheet stamping formability,which predicts and controls the stamping process,can be applied to the deep drawing under constant or variable BHF conditions.

Combined model based on optimized multi-variable grey model and multiple linear regression

The construction method of background value is improved in the original multi-variable grey model （MGM（1,m）） from its source of construction errors. The MGM（1,m） with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables, and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model. Finally, a combined model of the MGM（1,2） with optimized background value and the binary linear regression is constructed by an example. The results show that the model has good effects for simulation and prediction.

Predictive value of ^(18)F-fluorodeoxyglucose PET/CT for transarterial chemolipiodolization of hepatocellular carcinoma

AIM： To investigate the correlation of 18F-fluorodeoxy- glucose （18F-FDG） positron emission tomography （PET） with clinical features and the prediction of treatment response. METHODS： A total of 83 hepatocellular carcinoma （HCC） patients undergoing 18F-FDG PET before transar- terial chemolipiodolization with systemic chemo-infusion between October, 2006 and May, 2009 were retrospec-tively enrolled. The patients included 68 men and 15 women （mean age, 60 ~ 10.7 years）. The effect of 18F- FDG-monitored PET uptake on clinical features and on the evaluated treatment response was ascertained with modified Response Evaluation Criteria in Solid Tumors. The PET parameters of maximal standardized uptake value of the tumor （Tsuvmax）, the ratio of the tumor maximal standardized uptake value （SUV） to the liver maximal SUV （Tsuvmax/Lsuwax） and the ratio of tumor maximal SUV to the liver mean SUV （msuvmax/LSUVrnean） were tested as predictive factors. RESULTS： Among the 3 SUV parameters, the TSUV- =maxdLsuvmean ratio （cutoff value of 1.90） was significantly associated with tumor burden including tumor size, tu- mor number, α-fetoprotein levels and tumor stage （P 〈 0.001, P = 0.008, P = 0.011, P 〈 0.001, respectively）. The objective response rates in patients with a high SUV ratio （≥ 1.90） were significantly better than those with a low SUV ratio （〈 1.90） （P = 0.020）. The overall survival rates of patients exhibiting a low Tsuvmax/Lsu- Vmean ratio （〈 1.90） and those with a high SUV ratio （≥1.90） was 38.2 and 10.3 mo, respectively （P 〈 0.01）. However, the time to progression showed no significant difference between the groups （P = 0.15）. CONCLUSION： 18F-FDG PET can be an important predictor of HCC treatment. In particular, the Tsuvmax/ Lsuwean ratio （cutoff value of 1.90） can provide useful information in treatment prognosis for HCC patients treated with Iocoregional therapy.

Behavior Measurement Model Based on Prediction and Control of Trusted Network

In order to construct the trusted network and realize the trust of network behavior,a new multi-dimensional behavior measurement model based on prediction and control is presented.By using behavior predictive equation,individual similarity function,group similarity function,direct trust assessment function,and generalized predictive control,this model can guarantee the trust of an end user and users in its network.Compared with traditional measurement model,the model considers different characteristics of various networks.The trusted measurement policies established according to different network environments have better adaptability.By constructing trusted group,the threats to trusted group will be reduced greatly.Utilizing trusted group to restrict individuals in network can ensure the fault tolerance of trustworthiness of trusted individuals and group.The simulation shows that this scheme can support behavior measurement more efficiently than traditional ones and the model resists viruses and Trojans more efficiently than older ones.

Diffusion of Amino Acids in non-Newtonian Fluids

The amino acids are necessarily nutritious components, their diffusions in body fluid and blood that belong to typical non-Newtonian fluid are of virtual importance to control the diffusive process and help clinical treatment. In this article, a holographic interferometer has been adopted to measure the diffusivity of amino acids in non-Newtonian fluid with the use of real-time holographic interference technique. In order to prove the reliability of the experimental instrument, the diffusivities of sucrose aqueous solution at 298.15K were determined. The meas- ured result displays a satisfactory accuracy of the apparatus used. Furthermore, the diffusion coefficients of glynine, L-serine, L-threonine and L-valine in polyacrylamide （PAM） aqueous solution at 298.15K were measured, respec- tively. The experimental data were fitted by a newly proposed correlation equation based on Li＇s predictive model. The calculating results by the present model are at considerably good agreement with experimental values, and the maximum average deviation is only 0.5%.

PREDICTION OF PUMP CHARACTERISTICS ACCORDING TO GEOMETRICAL PARAMETERS OF IMPELLER AND VOLUTE CASING

The geometrical parameters of impeller or volute casing (including guide vane ofmultistage pump) have a great effect on pump characteristics, but ultimately. the pump characteris-tics are determined by the geometrical parameters of impeller and volute casing cooperatively. Inthis essay the effect of impeller and volute casing on pump characteristics will be studiedquantitatvely from the angle cf optimal matching of them.

Using the Inverse of Expected Error Variance to Determine Weights of Individual Ensemble Members： Application to Temperature Prediction

The inverse of expected error variance is utilized to determine weights of individual ensemble members based on the THORPEX （The Observing System Research and Predictability Experiment） Interactive Grand Global Ensemble （TIGGE） forecast datasets. The weights of all ensemble members are thus calculated for summer 2012, with the NCEP final operational global analysis （FNL） data as the truth. Based on the weights of all ensemble members, the variable weighted ensemble mean （VWEM） of temperature of summer 2013 is derived and compared with that from the simple equally weighted ensemble mean. The results show that VWEM has lower root-mean-square error （RMSE） as well as absolute error, and has improved the temperature prediction accuracy. The improvements are quite notable over the Tibetan Plateau and its surrounding areas; specifically, a relative improvement rate of RMSE of more than 24% in 2-m temperature is demonstrated. Moreover, the improvement rates vary slightly with the pre- diction lead-time （24-96 h）. It is suggested that the VWEM approach be employed in operational ensemble predic- tion to provide guidance for weather forecasting and climate prediction.