Driver Intent Prediction and Collision Avoidance With Barrier Functions

For autonomous vehicles and driver assist systems,path planning and collision avoidance algorithms benefit from accurate predictions of future location of other vehicles and intent of their drivers.In the literature,the algorithms that provide driver intent belong to two categories:those that use physics based models with some type of filtering,and machine learning based approaches.In this paper we employ barrier functions(BF)to decide driver intent.BFs are typically used to prove safety by establishing forward invariance of an admissible set.Here,we decide if the“target”vehicle is violating one or more possibly fictitious(i.e.,non-physical)barrier constraints determined based on the context provided by the road geometry.The algorithm has a very small computational footprint and better false positive and negative rates than some of the alternatives.The predicted intent is then used by a control barrier function(CBF)based collision avoidance system to prevent unnecessary interventions,for either an autonomous or human-driven vehicle.

Partial function prediction of sulfate-reducing bacterial community from the rhizospheres of two typical coastal wetland plants in China

Sulfate-reducing bacteria(SRB)are ubiquitous anaerobic microorganisms that play signifi cant roles in the global biogeochemical cycle.Coastal wetlands,one of the major habitats of SRB,exhibit high sulfate-reducing activity and thus play signifi cant roles in organic carbon remineralization,benthic geochemical action,and plant-microbe interactions.Recent studies have provided credible evidence that the functional rather than the taxonomic composition of microbes responds more closely to environmental factors.Therefore,in this study,functional gene prediction based on PacBio single molecular real-time sequencing of 16S rDNA was applied to determine the sulfate-reducing and organic substrate-decomposing activities of SRB in the rhizospheres of two typical coastal wetland plants in North and South China:Zostera japonica and Scirpus mariqueter.To this end,some physicochemical characteristics of the sediments as well as the phylogenetic structure,community composition,diversity,and proportions of several functional genes of the SRB in the two plant rhizospheres were analyzed.The Z.japonic a meadow had a higher dissimilatory sulfate reduction capability than the S.mariqueter-comprising saltmarsh,owing to its larger proportion of SRB in the microbial community,larger proportions of functional genes involved in dissimilatory sulfate reduction,and the stronger ability of the SRB to degrade organic substrates completely.This study confi rmed the feasibility of applying microbial community function prediction in research on the metabolic features of SRB,which will be helpful for gaining new knowledge of the biogeochemical and ecological roles of these bacteria in coastal wetlands.

Analysis of the Protein Structure and Function of HpaG_(Xoo)

[Objective] The study was to analyze the structure and function of HpaGXoo and the relationship between the two.[Method] Some related bioinformatics analysis software on internet such as NPSA,Swiss-Model,SAPS and InterPro Scan were adopted to analyze the structure and predict its function.[Result] HpaGXoo consists of 139 amino acids,and has many alpha-helical and coiled structure,no signal peptide on N-terminal and no transmembrane structure.It locates in bacterial cytoplasm.[Conclusion] The study will lay ...

Distinct gut microbiomes in Thai patients with colorectal polyps

BACKGROUND Colorectal polyps that develop via the conventional adenoma-carcinoma sequence[e.g.,tubular adenoma(TA)]often progress to malignancy and are closely associated with changes in the composition of the gut microbiome.There is limited research concerning the microbial functions and gut microbiomes associated with colorectal polyps that arise through the serrated polyp pathway,such as hyperplastic polyps(HP).Exploration of microbiome alterations asso-ciated with HP and TA would improve the understanding of mechanisms by which specific microbes and their metabolic pathways contribute to colorectal carcinogenesis.AIM To investigate gut microbiome signatures,microbial associations,and microbial functions in HP and TA patients.METHODS Full-length 16S rRNA sequencing was used to characterize the gut microbiome in stool samples from control participants without polyps[control group(CT),n=40],patients with HP(n=52),and patients with TA(n=60).Significant differences in gut microbiome composition and functional mechanisms were identified between the CT group and patients with HP or TA.Analytical techniques in this study included differential abundance analysis,co-occurrence network analysis,and differential pathway analysis.RESULTS Colorectal cancer(CRC)-associated bacteria,including Streptococcus gallolyticus(S.gallolyticus),Bacteroides fragilis,and Clostridium symbiosum,were identified as characteristic microbial species in TA patients.Mediterraneibacter gnavus,associated with dysbiosis and gastrointestinal diseases,was significantly differentially abundant in the HP and TA groups.Functional pathway analysis revealed that HP patients exhibited enrichment in the sulfur oxidation pathway exclusively,whereas TA patients showed dominance in pathways related to secondary metabolite biosynthesis(e.g.,mevalonate);S.gallolyticus was a major contributor.Co-occurrence network and dynamic network analyses revealed co-occurrence of dysbiosis-associated bacteria in HP patients,whereas TA patients exhibited co-occurrence of CRC-associated bacteria.Furthermore,the co-occurrence of SCFA-producing bacteria was lower in TA patients than HP patients.CONCLUSION This study revealed distinct gut microbiome signatures associated with pathways of colorectal polyp development,providing insights concerning the roles of microbial species,functional pathways,and microbial interactions in colorectal carcinogenesis.

Time-stamped predictive functional control for networked control systems with random delays

The random delays in a networked control system (NCS) degrade control performance and can even destabilize the control system.To deal with this problem,the time-stamped predictive functional control (PFC) algorithm is proposed,which generalizes the standard PFC algorithm to networked control systems with random delays.The algorithm uses the time-stamp method to estimate the control delay,predicts the future outputs based on a discrete time delay state space model,and drives the control law that applies to an NCS from the idea of a PFC algorithm.A networked control system was constructed based on TrueTime simulator,with which the time-stamped PFC algorithm was compared with the standard PFC algorithm.The response curves show that the proposed algorithm has better control performance.

Effect of Bacillus amyloliquefaciens and Bacillus subtilis on fermentation, dynamics of bacterial community and their functional shifts of whole-plant corn silage

Background:Bacillus amyloliquefaciens(BA)and Bacillus subtilis(BS)are usually used as feed supplements directly or bacterial inoculants in biological feeds for animals.However,few research have reported the effects of BA and BS on fermentation characteristics and bacterial community successions of whole-plant corn silage during ensiling.If the BA and BS inoculants have positive effects on silages,then they could not only improve fermentation characteristics,but also deliver BA or BS viable cells to ruminants,which would play its probiotic effect.Therefore,the objectives of this study were to investigate the effects of BA and BS on the fermentation,chemical characteristics,bacterial community and their metabolic pathway of whole-plant corn silage.Results:Freshly chopped whole-plant corn was inoculated without or with BA and BS,respectively,and ensiled for1,3,7,14 and 60 d.Results showed that BA and BS inoculations increased lactic acid concentrations of whole-plant corn silages compared with control,and BA inoculation decreased acetic acid concentrations,whereas BS inoculation decreased fiber contents and increased crude protein(CP)content.Higher water-soluble carbohydrate contents and lower starch contents were observed in BA-and BS-inoculated silages compared with that in control.The decreased CP content and increased non-protein nitrogen content were observed in BA-inoculated silage,which was consistent with the higher amino acid metabolism abundances observed in BA-inoculated silage.In addition,it was noteworthy that BA and BS inoculations increased the metabolism of cofactors and vitamins,and decreased the relative abundances of drug resistance:antimicrobial pathways.We also found that the bacterial metabolism pathways were clearly separated into three clusters based on the ensiling times of whole-plant corn silage in the present study.There were no significant differences in bacterial community compositions among the three groups during ensiling.However,BA and BS inoculations decreased the relative abundances of undesirable bacteria such as Acetobacter and Acinetobacter.Conclusion:Our findings suggested that the BS strain was more suitable as silage inoculants than the BA strain in whole-plant corn silage in this study.

Predictive functional control based on fuzzy T-S model for HVAC systems temperature control

In heating, ventilating and air-conditioning （HVAC） systems, there exist severe nonlinearity, time-varying nature, disturbances and uncertainties. A new predictive functional control based on Takagi-Sugeno （T-S） fuzzy model was proposed to control HVAC systems. The T-S fuzzy model of stabilized controlled process was obtained using the least squares method, then on the basis of global linear predictive model from T-S fuzzy model, the process was controlled by the predictive functional controller. Especially the feedback regulation part was developed to compensate uncertainties of fuzzy predictive model. Finally simulation test results in HVAC systems control applications showed that the proposed fuzzy model predictive functional control improves tracking effect and robustness. Compared with the conventional PID controller, this control strategy has the advantages of less overshoot and shorter setting time, etc.

Adaptive predictive functional control based on Takagi-Sugeno model and its application to pH process

In order to obtain accurate prediction model and compensate for the influence of model mismatch on the control performance of the system and avoid solving nonlinear programming problem,an adaptive fuzzy predictive functional control(AFPFC) scheme for multivariable nonlinear systems was proposed.Firstly,multivariable nonlinear systems were described based on Takagi-Sugeno(T-S) fuzzy models;assuming that the antecedent parameters of T-S models were kept,the consequent parameters were identified on-line by using the weighted recursive least square(WRLS) method.Secondly,the identified T-S models were linearized to be time-varying state space model at each sampling instant.Finally,by using linear predictive control technique the analysis solution of the optimal control law of AFPFC was established.The application results for pH neutralization process show that the absolute error between the identified T-S model output and the process output is smaller than 0.015;the tracking ability of the proposed AFPFC is superior to that of non-AFPFC(NAFPFC) for pH process without disturbances,the overshoot of the effluent pH value of AFPFC with disturbances is decreased by 50% compared with that of NAFPFC;when the process parameters of AFPFC vary with time the integrated absolute error(IAE) performance index still retains to be less than 200 compared with that of NAFPFC.

Incremental multivariable predictive functional control and its application in a gas fractionation unit

The control of gas fractionation unit(GFU) in petroleum industry is very difficult due to multivariable characteristics and a large time delay.PID controllers are still applied in most industry processes.However,the traditional PID control has been proven not sufficient and capable for this particular petro-chemical process.In this work,an incremental multivariable predictive functional control(IMPFC) algorithm was proposed with less online computation,great precision and fast response.An incremental transfer function matrix model was set up through the step-response data,and predictive outputs were deduced with the theory of single-value optimization.The results show that the method can optimize the incremental control variable and reject the constraint of the incremental control variable with the positional predictive functional control algorithm,and thereby making the control variable smoother.The predictive output error and future set-point were approximated by a polynomial,which can overcome the problem under the model mismatch and make the predictive outputs track the reference trajectory.Then,the design of incremental multivariable predictive functional control was studied.Simulation and application results show that the proposed control strategy is effective and feasible to improve control performance and robustness of process.

Active disturbance rejected predictive functional control for space vehicles with RCS

Reaction control system(RCS) is a powerful and efficient actuator for space vehicles attitude control, which is typically characterized as a pulsed unilateral effector only with two states(off/on). Along with inevitable internal uncertainties and external disturbances in practice, this inherent nonlinear character always hinders space vehicles autopilot from pursuing precise tracking performance. Compared to most of pre-existing methodologies that passively suppress the uncertainties and disturbances, a design based on predictive functional control(PFC) and generalized extended state observer(GESO) is firstly proposed for three-axis RCS control system to actively reject that with no requirement for additional fuel consumption. To obtain a high fidelity predictive model on which the performance of PFC greatly depends, the nonlinear coupling multiple-input multiple-output(MIMO) flight dynamics model is parameterized as a state-dependent coefficient form. And based on that, a MIMO PFC algorithm in state space domain for a plant of arbitrary orders is deduced in this paper.The internal uncertainties and external disturbances are lumped as a total disturbance, which is estimated and cancelled timely to further enhance the robustness. The continuous control command synthesised by above controller-rejector tandem is finally modulated by pulse width pulse frequency modulator(PWPF) to on-off signals to meet RCS requirement. The robustness and feasibility of the proposed design are validated by a series of performance comparison simulations with some prominent methods in the presence of significant perturbations and disturbances, as well as measurement noise.

Predictive functional control of integrating process based on impulse response

The predictive model is built according to the characteristics of the impulse response of integrating process. In order to eliminate the permanent offset between the setpoint and the process output in the presence of the load disturbance, a novel error compensation method is proposed. Then predictive functional control of integrating process is designed. The method given generates a simple control structure, which can significandy reduce online computation. Furthermore, the tuning of the controller is fairly straightforward. Simulation results indicate that the designed control system is relatively robust to the parameters variation of the process.

Study on Ann-Based Multi-Step Prediction Model of Short-Term Climatic Variation

In the context of 1905–1995 series from Nanjing and Hangzhou, study is undertaken of estab-lishing a predictive model of annual mean temperature in 1996–2005 to come over the Changjiang (Yangtze River) delta region through mean generating function and artificial neural network in combination. Results show that the established model yields mean error of 0.45°C for their abso-lute values of annual mean temperature from 10 yearly independent samples (1986–1995) and the difference between the mean predictions and related measurements is 0.156°C. The developed model is found superior to a mean generating function regression model both in historical data fit-ting and independent sample prediction. Key words Climate trend prediction. Mean generating function (MGF) - Artificial neural network (ANN) - Annual mean temperature (AMT)

Predictive Functional Controller with a Similar Proportional Integral Optimal Regulator Structure:Comparison with Traditional Predic-tive Functional Controller and Application to Heavy Oil Coking Equipment

By extending the system's state variables,a novel predictive functional controller has been developed.The structure of this controller is similar to that of classical proportional integral(PI)optimal controller and in-cludes a control block that can perform a feed-forward control of future P-step set points.It considers both the state variables and the output errors in its cost function,which results in enhanced control performance compared with traditional state space predictive functional control(TSSPFC)methods that consider only the predictive output er-rors.The predictive functional controller(PFC)has been compared with TSSPFC in terms of tracking ability,dis-turbance rejection,and also based on its application to heavy oil coking equipment.The results obtained show the effectiveness of the controller.

Introducing atmospheric angular momentum into prediction of length of day change by generalized regression neural network model

The general regression neural network(GRNN) model was proposed to model and predict the length of day(LOD) change, which has very complicated time-varying characteristics. Meanwhile, considering that the axial atmospheric angular momentum(AAM) function is tightly correlated with the LOD changes, it was introduced into the GRNN prediction model to further improve the accuracy of prediction. Experiments with the observational data of LOD changes show that the prediction accuracy of the GRNN model is 6.1% higher than that of BP network, and after introducing AAM function, the improvement of prediction accuracy further increases to 14.7%. The results show that the GRNN with AAM function is an effective prediction method for LOD changes.

Time function of surface subsidence based on Harris model in mined-out area

The surface subsidence is a common environmental hazard in mined-out area. Based on careful analysis of the regularity of surface subsidence in mined-out area, we proposed a new time function based on Harris curve model in consideration of the shortage of current surface subsidence time functions. By analyzing the characteristics of the new time function, we found that it could meet the dynamic process, the velocity change process and the acceleration change process during surface subsidence. Then its rationality had been verified through project cases. The results show that the proposed time function model can give a good reflection of the regularity of surface subsidence in mined-out area and can accurately predict surface subsidence. And the prediction data of the model are a little greater than measured data on condition of proper measured data quantity, which is safety in the engineering. This model provides a new method for the analysis of surface subsidence in mined-out area and reference for future prediction, and it is valuable to engineering application.

Predictive functional control （PFC） and its application in chlorinated polyethylene process

The main principle and the characteristic of Predictive Functional Control (PFC) strategy are presented in this paper and the corresponding control system aid design software APC-PFC is also introduced. For a chlorinated polyethylene (CPE) process, a design scheme of cascade predictive functional control system is described and the control performance is improved obviously.

Additive predictions of aboveground stand biomass in commercial logs and harvest residues for rotation age Pinus radiata plantations in New South Wales,Australia

Two systems of additive equations were developed to predict aboveground stand level biomass in log products and harvest residue from routinely measured or predicted stand variables for Pinus radiata plantations in New South Wales,Australia.These plantations were managed under three thinning regimes or stand types before clear-felling at rotation age by cut-to-length harvesters to produce sawlogs and pulpwood.The residue material following a clear-fell operation mainly consisted of stumps,branches and treetops,short off-cut and waste sections due to stem deformity,defects,damage and breakage.One system of equations did not include dummy variables for stand types in the model specification and was intended for more general use in plantations where stand density management regimes were not the same as the stand types in our study.The other system that incorporated dummy variables was for stand type-specific applications.Both systems of equations were estimated using 61 plot-based estimates of biomass in commercial logs and residue components that were derived from systems of equations developed in situ for predicting the product and residue biomass of individual trees.To cater for all practical applications,two sets of parameters were estimated for each system of equations for predicting component and total aboveground stand biomass in fresh and dry weight respectively.The two sets of parameters for the system of equations without dummy variables were jointly estimated to improve statistical efficiency in parameter estimation.The predictive performances of the two systems of equations were benchmarked through a leave-one-plot-out cross validation procedure.They were generally superior to the performance of an alternative two-stage approach that combined an additive system for major components with an allocative system for sub-components.As using forest harvest residue biomass for bioenergy has increasingly become an integrated part of forestry,reliable estimates of product and residue biomass will assist harvest and management planning for clear-fell operations that integrate cut-to-length log production with residue harvesting.

Integrating Gene Ontology and Blast to predict gene functions

A GoBlast system was built to predict gene function by integrating Blast search and Gene Ontology (GO) annotations together. The operation system was based on Debian Linux 3.1, with Apache as the web server and Mysql database as the data storage system. FASTA files with GO annotations were taken as the sequence source for blast alignment, which were formatted by wu-formatdb program. The GoBlast system includes three Bioperl modules in Perl:a data input module, a data process module and a data output module. A GoBlast query starts with an amino acid or nucleotide sequence. It ends with an output in an html page, presenting high scoring gene products which are of a high homology to the queried sequence and listing associated GO terms beside respective gene poducts. A simple click on a GO term leads to the detailed explanation of the specific gene function. This avails gene function prediction by Blast. GoBlast can be a very useful tool for functional genome research and is available for free at http://bioq.org/goblast.

Estimation of the unfrozen water content of saturated sandstones by ultrasonic velocity

The unfrozen water content(UWC)of rocks at low temperature is an important index for evaluating the stability of the rock engineering in cold regions and artificial freezing engineering.This study addresses a new method to estimate the UWC of saturated sandstones at low temperature by using the ultrasonic velocity.Ultrasonic velocity variations can be divided into the normal temperature stage(20 to 0℃),quick phase transition stage(0 to-5℃)and slow phase transition stage(-5 to-25℃).Most increment of ultrasonic velocity is completed in the quick phase transition stage and then turns to be almost a constant in the slow phase transition stage.In addition,the UWC is also measured by using nuclear magnetic resonance(NMR)technology.It is validated that the ultrasonic velocity and UWC have a similar change law against freezing and thawing temperatures.The WE(weighted equation)model is appropriate to estimate the UWC of saturated sandstones,in which the parameters have been accurately determined rather than by data fitting.In addition,a linear relationship between UWC and ultrasonic velocity is built based on pore ice crystallization theory.It is evidenced that this linear function can be adopted to estimate the UWC at any freezing temperature by using P-wave velocity,which is simple,practical,and accurate enough compared with the WE model.

Anatomical changes in the somatosensory system after large sensory loss predict strategies to promote functional recovery after spinal cord injury

Among cases of spinal cord injury are injuries involving the dorsal column in the cervical spinal cord that interrupt the major cutaneous afferents from the hand to the cuneate nucleus（Cu）in the brainstem.Deprivation of touch and proprioceptive inputs consequently impair skilled hand use.