From Sequential to Parallel Growth of Cities： Theory and Evidence from Canada

This paper examines city growth patterns and the corresponding city size distribution evolution over long periods of time using a simple New Economic Geography(NEG) model and urban population data from Canada. The main findings are twofold. First, there is a transition from sequential to parallel growth of cities over long periods of time: city growth shows a sequential mode in the stage of rapid urbanization, i.e., the cities with the best development conditions will take the lead in growth, after which the cities with higher ranks will become the fastest-growing cities; in the late stage of urbanization, city growth converges according to Gibrat′s law, and exhibits a parallel growth pattern. Second, city size distribution is found to have persistent structural characteristics: the city system is self-organized into multiple discrete size groups; city growth shows club convergence characteristics, and the cities with similar development conditions eventually converge to a similar size. The results will not only enhance our understanding of urbanization process, but will also provide a timely and clear policy reference for promoting the healthy urbanization of developing countries.

Controlling factors on the charging process of oil and gas in the eastern main sub-sag of the Baiyun Sag,Zhujiang River(Pearl River)Mouth Basin

The eastern main sub-sag(E-MSS)of the Baiyun Sag was the main zone for gas exploration in the deep-water area of the Zhujiang River(Pearl River)Mouth Basin at its early exploration stage,but the main goal of searching gas in this area was broken through by the successful exploration of the W3-2 and H34B volatile oil reservoirs,which provides a new insight for exploration of the Paleogene oil reservoirs in the E-MSS.Nevertheless,it is not clear on the distribution of“gas accumulated in the upper layer,oil accumulated in the lower layer”(Gas_(upper)-Oil_(lower))under the high heat flow,different source-rock beds,multi-stages of oil and gas charge,and multi-fluid phases,and not yet a definite understanding of the genetic relationship and formation mechanism among volatile oil,light oil and condensate gas reservoirs,and the migration and sequential charge model of oil and gas.These puzzles directly lead to the lack of a clear direction for oil exploration and drilling zone in this area.In this work,the PVT fluid phase,the origin of crude oil and condensate,the secondary alteration of oil and gas reservoirs,the evolution sequence of oil and gas formation,the phase state of oil and gas migration,and the configuration of fault activity were analyzed,which established the migration and accumulation model of Gas_(upper)-Oil_(lower)cocontrolled by source and heat,and fractionation controlled by facies in the E-MSS.Meanwhile,the fractionation evolution model among common black reservoirs,volatile reservoirs,condensate reservoirs and gas reservoirs is discussed,which proposed that the distribution pattern of Gas_(upper)-Oil_(lower)in the E-MSS is controlled by the generation attribute of oil and gas from source rocks,the difference of thermal evolution,and the fractionation controlled by phases after mixing the oil and gas.Overall,we suggest that residual oil reservoirs should be found in the lower strata of the discovered gas reservoirs in the oil-source fault and diapir-developed areas,while volatile oil reservoirs should be found in the deeper strata near the sag with no oil-source fault area.

On Spatial Distribution Pattern of Broccoli Clubroot Disease and and the Sampling Technique

[Objective] To further improve the prediction and forecast and continuous control ability of broccoli clubroot disease. [Methods] The spatial distribution pattern of diseased or infected plants was analyzed using the least square method, fre- quency distribution, aggregation index, m＊-m regression analysis and Taylor＇s pow- er law model. [Result] The field distribution of broccoli plants with clubroot disease tended to be aggregated distribution, m＇-m regression analysis showed that the el- ementary composition of the spatial distribution of diseased or infected plants was individual colony, the individuals attracted each other; the disease had obvious dis- ease focus in the field, and the individual colony showed uniform distribution pattern in the field. Taylor＇s power law showed that the spatial pattern of individual dis- eased or infected plant with clubroot disease tended to be uniform distribution with the increase of the density. On the basis of this, Iwao optimal theoretical sampling model and sequential sampling model were established, namely N =273.954 1/m- 59.698 5, To （N）=0.368 4N±1.926 8√N, respectively, it meant that when surveying N plants, if the accumulative incidence rate exceeded upper bound, the field can be set as control object; if the accumulative incidence rate didn＇t reach lower bound, it can be set as uncontrol field; if the accumulative incidence rate was between upper bound and lower bound, it should be surveyed continuously until the maximum sample size （mo=0.368 4） appeared, that was, the disease incidence was 15%, so the sampling number should be 684 plants. [Conclusion] The research results had very important instructive meaning for disease control.

The Method for Optimum Estimation of COVID-19 Variant Type Virus Infection Status Analysis by the Multivariate Analysis Considering the Environmental Variability Impact in Japan

Currently, the estimated value of the effective reproduction number (ERN), which is an index for grasping the COVID-19 infection status, is used for important planning and evaluation of infection prevention measures. Since ERN in the Sequential SIR model fluctuates in multiple dimensions due to changes in the surrounding environment, it is difficult to set the appropriate accuracy of the uncertainty region of the estimated data. The challenge in this study is to build a mathematical model of infectious disease according to the characteristics and data characteristics of the infectious disease and select an appropriate estimation method. Highly accurate quantitative research that analyzes the validity of “how infectious diseases prevail” from an academic point of view is the key to prediction and estimation in appropriate infection situation analysis. In this study, we adopted a statistical multivariate analysis method (T method) that enables evaluation and prediction of important factors related to ERN estimation and analysis of phenomena that change in real time (time series analysis). It was clarified that it is possible to estimate with higher accuracy by applying the T method to the estimated value of ERN by the current SIR mathematical model.

On the Characterization and Fault Identification of Sequentially t-Diagnosable System Under PMC Model

Sequential diagnosis is a very useful strategy for system-level fault identification because of its lower cost of hardware.In this paper,the characterization of sequentially t-diagnosable system is given,and a tmiversal algorithm to seek faulty units in the system is developed.

The molecular and evolutionary basis of reproductive isolation in plants

Reproductive isolation is defined as processes that prevent individuals of different populations from mating, survival or producing fertile offspring. Reproductive isolation is critical for driving speciation and maintaining species identity, which has been a fundamental concern in evolutionary biology. In plants,reproductive isolation can be divided into prezygotic and postzygotic reproductive barriers, according to its occurrence at different developmental stages. Postzygotic reproductive isolation caused by reduced fitness in hybrids is frequently observed in plants, which hinders gene flow between divergent populations and has substantial effects on genetic differentiation and speciation, and thus is a major obstacle for utilization of heterosis in hybrid crops. During the past decade, China has made tremendous progress in molecular and evolutionary basis of prezygotic and postzygotic reproductive barriers in plants. Present understandings in reproductive isolation especially with new data in the last several years well support three evolutionary genetic models, which represent a general mechanism underlying genomic differentiation and speciation. The updated understanding will offer new approaches for the development of wide-compatibility or neutral varieties, which facilitate breeding of hybrid rice as well as other hybrid crops.

Development of a key-variable-based parallel HVAC energy predictive model

Building heating,ventilation,and air conditioning(HVAC)systems consume large amounts of energy,and precise energy prediction is necessary for developing various energy-efficiency strategies.Energy prediction using data-driven models has received increasing attention in recent years.Typically,two types of driven models are used for building energy prediction:sequential and parallel predictive models.The latter uses the historical energy of the target building as training data to predict future energy consumption.However,for newly built buildings or buildings without historical data records,the energy can be estimated using the parallel model,which employs the energy data of similar buildings as training data.The second predictive model is seldom studied because the model input feature is difficult to identify and collect.Herein,we propose a novel key-variable-based parallel HVAC energy predictive model.This model has informative input features(including meteorological data,occupancy activity,and key variables representing building and system characteristics)and a simple architecture.A general key-variable screening toolkit which was more versatile and flexible than present parametric analysis tools was developed to facilitate the selection of key variables for the parallel HVAC energy predictive model.A case study is conducted to screen the key variables of hotel buildings in eastern China,based on which a parallel chiller energy predictive model is trained and tested.The average cross-test error measured in terms of the coefficient of variation of the root mean square error(CV-RMSE)and normalized mean bias error(NMBE)of the parallel chiller energy predictive model is approximately 16%and 8.3%,which is acceptable for energy prediction without using historical energy data of the target building.

Hierarchically Clustered HMM for Protein Sequence Motif Extraction with Variable Length

Protein sequence motifs extraction is an important field of bioinformatics since its relevance to the structural analysis. Two major problems are related to this field：（1） searching the motifs within the same protein family; and（2） assuming a window size for the motifs search. This work proposes the Hierarchically Clustered Hidden Markov Model（HC-HMM） approach, which represents the behavior and structure of proteins in terms of a Hidden Markov Model chain and hierarchically clusters each chain by minimizing distance between two given chains＇ structure and behavior. It is well known that HMM can be utilized for clustering, however, methods for clustering on Hidden Markov Models themselves are rarely studied. In this paper, we developed a hierarchical clustering based algorithm for HMMs to discover protein sequence motifs that transcend family boundaries with no assumption on the length of the motif. This paper carefully examines the effectiveness of this approach for motif extraction on 2593 proteins that share no more than 25% sequence identity. Many interesting motifs are generated.Three example motifs generated by the HC-HMM approach are analyzed and visualized with their tertiary structure.We believe the proposed method provides a unique protein sequence motif extraction strategy. The related data mining fields using Hidden Markova Model may also benefit from this clustering on HMM themselves approach.

Rotorcraft flight endurance estimation based on a new battery discharge model

To avoid the numerical complexities of the battery discharge law of electric-powered rotorcrafts,this study uses the Kriging method to model the discharge characteristics of Li-Po batteries under standard conditions.A linear current compensation term and an ambient temperature compensation term based on radial basis functions are then applied to the trained Kriging model,leading to the complete discharged capacity-terminal voltage model.Using an orthogonal experimental design and a sequential method,the coefficients of the current and ambient temperature compensation terms are determined through robust optimization.An endurance calculation model for electric-powered rotorcrafts is then established,based on the battery discharge model,through numerical integration.Laboratory tests show that the maximum relative error of the proposed discharged capacity-terminal voltage model at detection points is 0.0086,and that of the rotorcraft endurance calculation model is 0.0195,thus verifying their accuracy.A flight test further demonstrates the applicability of the proposed endurance model to general electric-powered rotorcrafts.

Judging the Normativity of PAF Based on TFN and NAN

The normativity of workers'actions during producing has a great impact on the quality of the products and the safety of the operation process.Previous studies mainly focused on the normativity of each single producing action instead of considering the normativity of continuous producing actions,which is defined as producing action flow(PAF)in this paper,during operation process.For this issue,a normativity judging method based on two-LSTM fusion network(TFN)and normativity-aware attention network(NAN)is proposed.First,TFN is designed to detect and recognize the producing actions based on skeleton sequences of a worker during complete operation process,and PAF data in sequential form are obtained.Then.NAN is built to allocate difTerent levels of attention to each producing action within the sequence of PAF.and by this means,an efficient normativity judging is conducted.The combustor surface cleaning(CSC)process of rocket engine is taken as the experimental case,and the CSC-Action2D dataset is established for evaluation.Experiment results show the high performance of TFN and NAN.demonstrating the effectiveness of the proposed method for PAF normativity judging.