Fast determination of meso-level mechanical parameters of PFC models

To solve the problems of blindness and inefficiency existing in the determination of meso-level mechanical parameters of particle flow code (PFC) models, we firstly designed and numerically carried out orthogonal tests on rock samples to investigate the correlations between macro-and meso-level mechanical parameters of rock-like bonded granular materials. Then based on the artificial intelligent technology, the intelligent prediction systems for nine meso-level mechanical parameters of PFC models were obtained by creating, training and testing the prediction models with the set of data got from the orthogonal tests. Lastly the prediction systems were used to predict the meso-level mechanical parameters of one kind of sandy mudstone, and according to the predicted results the macroscopic properties of the rock were obtained by numerical tests. The maximum relative error between the numerical test results and real rock properties is 3.28% which satisfies the precision requirement in engineering. It shows that this paper provides a fast and accurate method for the determination of meso-level mechanical parameters of PFC models.

Autonomous Vehicles Testing Considering Utility-Based Operable Tasks

Virtual simulation testing of Autonomous Vehicles(AVs)is gradually being accepted as a mandatory way to test the feasibility of driving strategies for AVs.Mainstream methods focus on improving testing efficiency by extracting critical scenarios from naturalistic driving datasets.However,the criticalities defined in their testing tasks are based on fixed assumptions,the obtained scenarios cannot pose a challenge to AVs with different strategies.To fill this gap,we propose an intelligent testing method based on operable testing tasks.We found that the driving behavior of Surrounding Vehicles(SVs)has a critical impact on AV,which can be used to adjust the testing task difficulty to find more challenging scenarios.To model different driving behaviors,we utilize behavioral utility functions with binary driving strategies.Further,we construct a vehicle interaction model,based on which we theoretically analyze the impact of changing the driving behaviors on the testing task difficulty.Finally,by adjusting SV’s strategies,we can generate more corner cases when testing different AVs in a finite number of simulations.

Intelligence Test

1.If you drop a white hat into the Red Sea,what does itbecome?2.What do people do in clock factories?3.Whv do seagulls live near the sea?4.A cowboy rode to an inn on Friday,stayed two nightsand 1eft on Friday.How could that be?5.Where does a bird go when it loses its tail?(Key:1.Wet.2.They make faces all day. 3.Because ifthey live near the bay they will be called bagels.4.Hishorse’s name was Friday.5.The retail store.)

English Intelligence Test

ANow,imagine(设想)there is a large live duckinside a very large bottle.

An intelligent serological SERS test toward early-stage hepatocellular carcinoma diagnosis through ultrasensitive nanobiosensing

Early or very early detection of hepatocellular carcinoma(HCC)is an effective means to resolve the low cure rates,but there currently lacks a method that fulfills clinical requirements.One of the most prospective approaches to detecting early-stage HCC is directly testing a compendium of disease-relevant biomolecules contained within human serum through surface-enhanced Raman scattering(SERS)nanobiosensing and recognizing the biomolecular patterns.We report a novel Si-based bimetallic nanoensembles-functionalized SERS substrate(its analytical enhancement factor reaches 1.47×10^(12))and introduce an ultrasensitive nanobiosensing for capturing the subtle characteristic changes in SERS spectra caused by HCC,hepatitis B,or cirrhosis.Toward early diagnosis,we created an intelligent serological test with this nanobiosensing and the deep learning algorithm to gain key biomolecular phenotypes of early-stage HCC.Using clinical samples from four target populations(normal,HCC,cirrhosis,and hepatitis B),the proof-of-principle result indicates that the test yielded a predictive accuracy of 98.75%on a held-out dataset(randomly drew 4 out of 28 samples per population).On the same held-out dataset,the sensitivity and specificity of the test were both 100%for distinguishing HCC.Such a new-concept liquid biopsy could provide an opportunity for early diagnosis of HCC.

Seguin Form Board as an intelligence tool for young children in an Indian urban slum

Objective:The present study evaluates the concurrent and predictive validity of the Seguin Form Board Test(SFBT)as an intelligence tool for children in low-and middle-income countries.Methods:In a cohort of normal children,followed up in South India,two cross-sectional analyses were done at 3 and 7 years of age on 95 children.The SFBT and Vineland Social Matu-rity Scale(VSMS)were done at 3 years of age and Malin’s Intelligence Scale for Indian Children(MISIC)and the VSMS were done at 7 years of age,and the results were compared for concurrent and predictive validity for the SFBT.Results:Intelligence quotient and social quotient had positive correlations at 3 years of age,indicating fair concurrent validity.The SFBT done at around 3 years of age had good positive cor-relation with MISIC at 7 years of age,indicating good predictive validity.Conclusion:This study shows the utility of the SFBT as a community-based intelligence tool with acceptable concurrent and predictive validity.

Validation studies of the Para DNA^(■) Intelligence System with artificial evidence items

Short tandem repeat(STR)profiling is one of the mostly used systems for forensic applications.In certain circumstances,STR profiling is time-consuming and costly,which potentially leads to delays in criminal investigations.LGC(Laboratory of the Government Chemist,UK)Forensics has developed a robust STR profiling platform called the ParaDNAVR Intelligence Test System which can provide early tactical intelligence and aid investigators in making informed decisions on sample prioritization for detection.Here,we validated the ParaDNA^(■) intelligence test for its application in forensic cases using a range of mock evidence items following guidelines set by the Scientific Working Group on DNA Analysis Methods(SWGDAM).Specifically,we tested the sensitivity and accuracy of the ParaDNA intelligence test,as well as the success rates for detecting mock samples and for use in case scenarios.Our findings demonstrate that the ParaDNA intelligence test generates useful DNA profiles,especially for samples such as blood,saliva,and semen that contain ample DNA,indicating the benefits of including ParaDNA as a prior step in forensic STR profiling pipelines.