Beyond Spacetime Geometry—The Death of Philosophy and Its Quantum Reincarnation

Contrary to the “end” and “death” assertions on philosophy, this paper predicts an equilibrium-based and harmony-centered scientific reincarnation of philosophy. Logically, the reincarnation is backed by a formal system and a background independent geometry that transcends spacetime. Physically, it is supported by definable quantum causality and bipolar logical unifications of matter and antimatter, particle and wave, big bang and black hole, relativity and quantum entanglement. Philosophically, it is distinguished from Western metaphysics and dialectics as well as the Dao of Laozi. It is named a quantum reincarnation for its central claim that YinYang bipolar quantum entanglement is the source of causality for the Being of beings following the 2nd law of thermodynamics. Thus, it presents a modest unification of science and philosophy for their reciprocal interaction (Note: Equilibrium subsumes non-equilibrium and quasi—equilibrium as local non-equilibriums can form global equilibrium or quasi-equilibrium).

Hybrid Estimation of State and Input for Linear Discrete Time-varying Systems： A Game Theory Approach

为线性分离变化时间的系统的 H 混合评价问题在这份报纸被调查，在估计的信号是状态和输入的线性联合的地方。设计目的从骚乱要求最坏的精力获得到是的评价错误不到规定水平。混合评价问题的最佳的答案是僵绳点一二播放器零和微分游戏。根据微分比赛途径，为混合评价问题的必要、足够的可解决的条件以一个 Riccati 微分方程的答案被提供。而且，如果可解决的条件满足，一个可能的评估者被建议。评估者被印射矩阵的一个获得矩阵和产量描绘，在后者反映在未知输入和输出评价错误之间的内部关系的地方。最后，一个数字例子被提供说明建议途径。

Simulation on the Models of Small Scale Passive Acoustic Sensor Arrays Based on Time-Delay Estimation Method

The passive acoustic localization with planar sensor array is introduced. Based on a method to eliminate the influence of effective sound velocity in passive detection, a new five-sensors solid array and its localization model are put forward. The factors that influence the precision of the localization are analyzed. Considering the errors from the factors synchronously, the simulation compares the solid array with the planar array. It can be proved that the five-sensor solid array is better than the four-sensor planar array in the estimation of bearing elements.

Locating the position of objects in non-line-of-sight based on time delay estimation

Non-line-of-sight imaging detection is to detect hidden objects by indirect light and intermediary surface（diffuser）.It has very important significance in indirect access to an object or dangerous object detection, such as medical treatment and rescue. An approach to locating the positions of hidden objects is proposed based on time delay estimation. The time delays between the received signals and the source signal can be obtained by correlation analysis, and then the positions of hidden objects will be located. Compared with earlier systems and methods, the proposed approach has some modifications and provides significant improvements, such as quick data acquisition, simple system structure and low cost, and can locate the positions of hidden objects as well： this technology lays a good foundation for developing a practical system that can be used in real applications.

Impact of the Time Scale of Model Sensitivity Response on Coupled Model Parameter Estimation

That a model has sensitivity responses to parameter uncertainties is a key concept in implementing model parameter es- timation using filtering theory and methodology. Depending on the nature of associated physics and characteristic variability of the fluid in a coupled system, the response time scales of a model to parameters can be different, from hourly to decadal. Unlike state estimation, where the update frequency is usually linked with observational frequency, the update frequency for parameter estimation must be associated with the time scale of the model sensitivity response to the parameter being esti- mated. Here, with a simple coupled model, the impact of model sensitivity response time scales on coupled model parameter estimation is studied. The model includes characteristic synoptic to decadal scales by coupling a long-term varying deep ocean with a slow-varying upper ocean forced by a chaotic atmosphere. Results show that, using the update frequency deter- mined by the model sensitivity response time scale, both the reliability and quality of parameter estimation can be improved significantly, and thus the estimated parameters make the model more consistent with the observation. These simple model results provide a guideline for when real observations are used to optimize the parameters in a coupled general circulation model for improving climate analysis and prediction initialization.

Hybrid Estimation of State and Input for Linear Continuous Time-varying Systems:A Game Theory Approach

The H∞ hybrid estimation problem for linear continuous time-varying systems is in-vestigated in this paper, where estimated signals are linear combination of state and input. Designobjective requires the worst-case energy gain from disturbance to estimation error be less than a pre-scribed level. Optimal solution of the hybrid estimation problem is the saddle point of a two-playerzero sum di?erential game. Based on the di?erential game approach, necessary and su?cient solvableconditions for the hybrid estimation problem are provided in terms of solutions to a Riccati di?e-rential equation. Moreover, one possible estimator is proposed if the solvable conditions are satisfied.The estimator is characterized by a gain matrix and an output mapping matrix that re?ects theinternal relations between the unknown input and output estimation error. Both state and unknowninputs estimation are realized by the proposed estimator. Thus, the results in this paper are alsocapable of dealing with fault diagnosis problems of linear time-varying systems. At last, a numericalexample is provided to illustrate the proposed approach.

A Non-Destructive Time Series Model for the Estimation of Cherry Coffee Production

Coffee plays a key role in the generation of rural employment in Colombia.More than 785,000 workers are directly employed in this activity,which represents the 26%of all jobs in the agricultural sector.Colombian coffee growers estimate the production of cherry coffee with the main aim of planning the required activities,and resources(number of workers,required infrastructures),anticipating negotiations,estimating,price,and foreseeing losses of coffee production in a specific territory.These important processes can be affected by several factors that are not easy to predict(e.g.,weather variability,diseases,or plagues.).In this paper,we propose a non-destructive time series model,based on weather and crop management information,that estimate coffee production allowing coffee growers to improve their management of agricultural activities such as flowering calendars,harvesting seasons,definition of irrigation methods,nutrition calendars,and programming the times of concentration of production to define the amount of personnel needed for harvesting.The combination of time series and machine learning algorithms based on regression trees(XGBOOST,TR and RF)provides very positive results for the test dataset collected in real conditions for more than a year.The best results were obtained by the XGBOOST model(MAE=0.03;RMSE=0.01),and a difference of approximately 0.57%absolute to the main harvest of 2018.

EFFECTS OF ORIGINAL PHASE AND TIME-DELAY ON THE HF CHANNEL PARAMETER ESTIMATION

It is proposed firstly that the original phase and the time-delay are the main factors which affect the measuring resolution of the multitone complex envelope method. The effects of these factors are analysed and checked by the computer simulation. Finally, three possible ways to eliminate these effects are given.

SUBSAMPLE TIME DELAY ESTIMATION BASED ON PHASE SPECTRUM OF BAND LIMITED STOCHASTIC SIGNALS

The accuracy of conventional time delay estimation （TDE） algorithms is limited by the sampling interval. A novel algorithm of subsample TDE suitable for widehand signals is presented to improve the accuracy. This algorithm applies periodogram and parabolic interpolation to the cross correlation spectrum of band limited stochastic signals, and can obtain a continuous time delay estimator. Simulations are carried out to compare the performance of the proposed algorithm with that of other subsample TDE algorithms. Results show that the proposed algorithm outperforms other algorithms and reachs the Cramer-Rao lower bound （CRLB） at a high signal- to-noise ratio. For the wideband characteristic and the randomness of the transmitting signal, the proposed algo- rithm is suitable for the low probability of intercept radars.

THE LARGE TIME BEHAVIOR OF SPECTRAL APPROXIMATION FOR A CLASS OF PSEUDOPARABOLIC VISCOUS DIFFUSION EQUATION

The asymptotic behavior of the solutions to a class of pseudoparabolic viscous diffusion equation with periodic initial condition is studied by using the spectral method. The semidiscrete Fourier approximate solution of the problem is constructed and the error estimation between spectral approximate solution and exact solution on large time is also obtained. The existence of the approximate attractor AN and the upper semicontinuity d（AN,A） → 0 are proved.

Estimation of the amount of erosion at unconformities in the last stage of the Eocene Sanduo period in the Subei Basin,China

Strata erosion is a widespread phenomenon in sedimentary basins. The generation, migration, and accumulation of hydrocarbon is influenced by the scale of erosion, so estimating the amount of erosion is essential in the analysis of oil and gas bearing basins. According to the geological features in the Subei Basin and the actual data, using the integrated method, we estimated the level of erosion at the unconformities caused by the Sanduo event. By using the mudstone interval transit time method and the vitrinite reflectance method on data from typical wells, it can be concluded that the Gaoyou, Jinhu, and Hongze depressions suffered strong strata erosion from the late Eocene to Oligocene, and the total strata erosion thickness was 300–1,100 m. Different tectonic units in the same depression have extremely uneven erosion intensity: the low convex regions have the maximum erosion thickness, amounting to 800–1,100 m; the slope regions have an erosion thickness of generally 600–800 m; the erosion thickness of the slope-hollow transition zone is 300–500 m. For the whole basin, we used the strata thickness trend analysis method combined with the interval transit time and vitrinite reflectance methods to estimate the erosion thickness in the Sanduo period. The results show that the most severe erosion of the Sanduo event in the Subei Basin is between 1,000 m to 1,200 m, mainly located in depressions around the Jianhu Uplift; the deep hollow area has the least erosion, generally about 300–600 m, and the erosion in the slope area is about 600–900 m. Compared with the northern part, the southern part has relatively little erosion. It is also proved that the Sanduo movement has heterogeneous intensity, and the western region has greater intensity than the eastern region.

Distributed Dynamic Load in Structural Dynamics by the Impulse-Based Force Estimation Algorithm

This paper proposes a novel approach for identifying distributed dynamic loads in the time domain.Using polynomial andmodal analysis,the load is transformed intomodal space for coefficient identification.This allows the distributed dynamic load with a two-dimensional form in terms of time and space to be simultaneously identified in the form of modal force,thereby achieving dimensionality reduction.The Impulse-based Force Estimation Algorithm is proposed to identify dynamic loads in the time domain.Firstly,the algorithm establishes a recursion scheme based on convolution integral,enabling it to identify loads with a long history and rapidly changing forms over time.Secondly,the algorithm introduces moving mean and polynomial fitting to detrend,enhancing its applicability in load estimation.The aforementioned methodology successfully accomplishes the reconstruction of distributed,instead of centralized,dynamic loads on the continuum in the time domain by utilizing acceleration response.To validate the effectiveness of the method,computational and experimental verification were conducted.

A modified time domain interpolation method for LS channel estimation in OFDM systems

A modified time domain interpolation method is proposed for orthogonal frequency division multiplexing(OFDM)systems to address the problem that time domain interpolation in the least square(LS)channel estimation method based on comb-type pilots cannot choose the pilot spacing flexibly.Firstly,the estimated channel frequency response(CFR)at pilot positions in the frequency domain is obtained by LS channel estimation based on comb-type pilots,and the estimated channel impulse response(CIR)in the time domain is obtained by linear interpolation and inverse fast Fourier transform(IFFT).Secondly,the error of the estimated CIR obtained by linear interpolation is analyzed by theoretical deduction,and a method for correcting it is proposed.Finally,an estimated CFR at all subcarrier positions in the frequency domain is obtained by performing zero padding in the time domain and fast Fourier transform(FFT)on the modified CIR.The simulation results suggest that the proposed method gives similar performance to time domain interpolation,yet it does not need to meet the condition of time domain interpolation that the number of subcarriers must be an integral multiple of pilot spacing to use it.The proposed method allows for flexible pilot spacing,reducing the number of pilots and the consumption of subcarriers used for channel estimation.

Intelligent recognition and information extraction of radar complex jamming based on time-frequency features

In modern war,radar countermeasure is becoming increasingly fierce,and the enemy jamming time and pattern are changing more randomly.It is challenging for the radar to efficiently identify jamming and obtain precise parameter information,particularly in low signal-to-noise ratio(SNR)situations.In this paper,an approach to intelligent recognition and complex jamming parameter estimate based on joint time-frequency distribution features is proposed to address this challenging issue.Firstly,a joint algorithm based on YOLOv5 convolutional neural networks(CNNs)is proposed,which is used to achieve the jamming signal classification and preliminary parameter estimation.Furthermore,an accurate jamming key parameters estimation algorithm is constructed by comprehensively utilizing chi-square statistical test,feature region search,position regression,spectrum interpolation,etc.,which realizes the accurate estimation of jamming carrier frequency,relative delay,Doppler frequency shift,and other parameters.Finally,the approach has improved performance for complex jamming recognition and parameter estimation under low SNR,and the recognition rate can reach 98%under−15 dB SNR,according to simulation and real data verification results.

Impacts of sampling design on the abundance estimation of Portunus trituberculatus using crab pots

Fishery-independent surveys can provide high-quality data and support fishery assessment and management.Optimization of sampling design is crucial to increase the quality of fishery surveys.Crab pots are important fishing gears used to catch crabs.We analyzed the impacts of sampling design of crab pots on the abundance of Portunus trituberculatus in the Changjiang(Yangtze)River estuary to the Hangzhou Bay and its adjacent waters in East China Sea.The crab pots were cylindrical,240 mm in height and 600 mm in diameter of the iron ring.Our sampling designs(including fixed-station sampling,simple random sampling,stratified fixed-station sampling,and stratified random sampling),three number of stations(9,16,and 24),and three numbers of crab pots(500,1000,and 3000)were simulated and compared with the“true”abundance that obtained from bottom trawl surveys in the study area in 2007.The scenarios with 16 stations were set in stratification as a control group for comparison with unstratified designs.Results show that simple random sampling can obtain more stable results than fixed-station sampling in the abundance estimation of P.trituberculatus.In addition,stratified sampling resulted in more accurate abundance than unstratified sampling.The accuracy of the simulated results improved with the increase of the number of stations.No remarkable differences in the results were found among the scenarios of different number of crab pots at each station.However,resource-intensive areas exerted great impacts on simulation results.Thus,prior information or pre-survey results about resource abundance and density distribution are necessary.This study may serve as a reference for future sampling designs of crab pots of P.trituberculatus and other species.

Adaptive sliding mode control of modular self-reconfigurable spacecraft with time-delay estimation

The reconstruction control of modular self-reconfigurable spacecraft (MSRS) is addressed using an adaptive sliding mode control (ASMC) scheme based on time-delay estimation (TDE) technology. In contrast to the ground, the base of the MSRS is floating when assembled in orbit, resulting in a strong dynamic coupling effect. A TED-based ASMC technique with exponential reaching law is designed to achieve high-precision coordinated control between the spacecraft base and the robotic arm. TDE technology is used by the controller to compensate for coupling terms and uncertainties, while ASMC can augment and improve TDE’s robustness. To suppress TDE errors and eliminate chattering, a new adaptive law is created to modify gain parameters online, ensuring quick dynamic response and high tracking accuracy. The Lyapunov approach shows that the tracking errors are uniformly ultimately bounded (UUB). Finally, the on-orbit assembly process of MSRS is simulated to validate the efficacy of the proposed control scheme. The simulation results show that the proposed control method can accurately complete the target module’s on-orbit assembly, with minimal perturbations to the spacecraft’s attitude. Meanwhile, it has a high level of robustness and can effectively eliminate chattering.

On the Ontology of Taiwan Residents Films in the Post Declare Martial Law Ended Period

In addition to describing the social reality of Taiwan’s political and economic chaos, Taiwan’s films after the lifting of martial law also try to explore the ultimate significance of human existence, showing the color of ontology. Under the influence of postmodern culture, Taiwan films adopt non-linear narrative methods such as fragmented, time countercurrent or psychological time, emphasizing people’s instant experience and expressing modern people’s anxiety and social absurdity. In addition, the film highlights the gridding and deformed space, so as to highlight the interpersonal alienation and survival dilemma of modern cities. Taiwan Residents films also reflect the impermanence of fate, the nothingness of existence, and the absurdity of society through the death of characters. It is also coupled with the existential view of “living to death” and “others are hell”.

Evaluation of floating car technologies for travel time estimation

Travel times have been traditionally estimated from data collected by roadway sensors. Recently, new tech- nologies, such as cell phone tracking, license plate matching, automatic vehicle identifications and video detection, are employed for this purpose. In this study, the data collected by TRANSMIT readers, Bluetooth sensors, and INRIX are assessed by comparing each to the ＂ground truth＂ travel times collected by probe vehicles carrying GPS-based naviga- tion devices. Travel times of probe vehicles traveling on the study segment of 1-287 in New Jersey were collected in 2009. Statistical measures, such as standard deviation, average absolute speed error, and speed error bias, were used to make an in-depth analysis. The accuracy of each travel time estimation method is analyzed. The data collected by Bluetooth sensors and the TRANSMIT readers seem more consistent with the ground true data, and slightly outperform the data reported by 1NRIX. This study established a procedure for analyzing the accuracy of floating car data （FCD） collected by different technologies.

Parameter estimation of LFM signals based on time reversal

In this paper,parameter estimation of linear frequency modulation(LFM)signals containing additive white Gaussian noise is studied.Because the center frequency estimation of an LFM signal is affected by the error propagation effect,resulting in a higher signal to noise ratio(SNR)threshold,a parameter estimation method for LFM signals based on time reversal is proposed.The proposed method avoids SNR loss in the process of estimating the frequency,thus reducing the SNR threshold.The simulation results show that the threshold is reduced by 5 dB compared with the discrete polynomial transform(DPT)method,and the root-mean-square error(RMSE)of the proposed estimator is close to the Cramer-Rao lower bound(CRLB).

Normothermic regional perfusion mobile teams in controlled donation after circulatory death pathway: Evidence and peculiarities

To facilitate the implementation of controlled donation after circulatory death(cDCD)programs even in hospitals not equipped with a local Extracorporeal Membrane Oxygenation(ECMO)team(Spokes),some countries and Italian Regions have launched a local cDCD network with a ECMO mobile team who move from Hub hospitals to Spokes for normothermic regional perfusion(NRP)implantation in the setting of a cDCD pathway.While ECMO teams have been clearly defined by the Extracorporeal Life Support Organization,regarding composition,responsibilities and training programs,no clear,widely accepted indications are to date available for NRP teams.Although existing NRP mobile networks were developed due to the urgent need to increase the number of cDCDs,there is now the necessity for transplantation medicine to identify the peculiarities and responsibility of a NRP team for all those centers launching a cDCD pathway.Thus,in the present manuscript we summarized the character-istics of an ECMO mobile team,highlighting similarities and differences with the NRP mobile team.We also assessed existing evidence on NRP teams with the goal of identifying the characteristic and essential features of an NRP mobile team for a cDCD program,especially for those centers who are starting the program.Differences were identified between the mobile ECMO team and NRP mobile team.The common essential feature for both mobile teams is high skills and experience to reduce complications and,in the case of cDCD,to reduce the total warm ischemic time.Dedicated training programs should be developed for the launch of de novo NRP teams.