Waterfront Embankment Landscape Design “Modeling after the Nature”

The concept of "modeling after the nature" was introduced into embankment landscape design,types of embankment landscapes analyzed,and landscape design concepts of urban waterfront embankment proposed,to reflect and coordinate human-nature relationship,and achieve the harmony between human society and natural environment.

Including predator presence in a refined model for assessing resistance of alfalfa cultivar to aphids

The aphid quantity ratio（AQR） is defined as the number of aphids on each cultivar divided by the number of aphids on all cultivars. AQR is based on the correlation between aphid populations and their host plants and is an important tool that has been utilized in evaluating Medicago sativa（alfalfa） cultivar resistance to aphids. However, assessment of alfalfa resistance to aphids can be confused by the presence of aphid predators, causing the assessment of plant resistance to aphids to be based on incorrect aphid population data. To refine the AQR and account for the effect of predators on aphid population assessments, we introduced a parameter ‘α＇, corresponding to the predator quantity ratio, and used αAQR as the ratio to quantify aphid populations. Populations of both aphids（4 species） and their predators（12 species） occurring in 28 M. sativa cultivars were sampled over two years at a research station near Cangzhou, Hebei Province, China. Results showed that the most suitable evaluation period was from May to June, as the aphid population was stable during this period. Compared with the AQR method, the predator population numbers based on the αAQR had a significant inverse relationship with aphid population numbers and the 28 cultivars were clustered into three classes： the resistant class, tolerant class, and susceptible class. In addition, 17 cultivars were reassigned when evaluated using αAQR. All numerical values calculated by αAQR were displayed as a Gaussian distribution, which showed that the 28 cultivars could be clustered into nine groups using a median value（±SE） of 1±0.1. Hence, ongoing alfalfa breeding trials will be assessed using the αAQR to establish a robust system that includes agronomic performance parameters in order to generalize the new method for further studies.

Study of elastic wave propagation in two phase anisotropic media by numerical modeling of pseudospectral method

When there exists anisotropy in underground media elastic parameters of the observed coordinate possibly do not coincide with that of the natural coordinate. According to the theory that the density of potential energy, dissipating energy is independent of the coordinate, the relationship of elastic parameters between two coordinates is derived for two-phase anisotropic media. Then, pseudospectral method to solve wave equations of two-phase anisotropic media is derived. At last, we use this method to simulate wave propagation in two-phase anisotropic media four types of waves are observed in the snapshots, i.e., fast P wave and slow P wave, fast S wave and slow S wave. Shear wave splitting, SV wave cusps and elastic wave reflection and transmission are also observed.

AN IMPROVED MODEL FOR COMPUTING SOLUTION DYNAMICS OF NATURAL PRODUCTS WITH ^(13)C NUCLEAR MAGNETIC RELAXATION

The fully anisotropic molecular overall tumbling model with methyl conformation jumps internal rotation among three equivalent sites is proposed,the overall tumbling rotation rates and the methyl internal rotation rates of ponicidin are computed with this model from ~C relaxation parameters.

Opinion: the use of natural hazard modeling for decision making under uncertainty

Decision making to mitigate the effects of natural hazards is a complex undertaking fraught with uncertainty. Models to describe risks associated with natural hazards have proliferated in recent years. Concurrently, there is a growing body of work focused on developing best practices for natural hazard modeling and to create structured evaluation criteria for complex environmental models. However, to our knowledge there has been less focus on the conditions where decision makers can confidently rely on results from these models. In this review we propose a preliminary set of conditions necessary for the appropriate application of modeled results to natural hazard decision making and provide relevant examples within US wildfire management programs.

Graph-based Lexicalized Reordering Models for Statistical Machine Translation

Lexicalized reordering models are very important components of phrasebased translation systems.By examining the reordering relationships between adjacent phrases,conventional methods learn these models from the word aligned bilingual corpus,while ignoring the effect of the number of adjacent bilingual phrases.In this paper,we propose a method to take the number of adjacent phrases into account for better estimation of reordering models.Instead of just checking whether there is one phrase adjacent to a given phrase,our method firstly uses a compact structure named reordering graph to represent all phrase segmentations of a parallel sentence,then the effect of the adjacent phrase number can be quantified in a forward-backward fashion,and finally incorporated into the estimation of reordering models.Experimental results on the NIST Chinese-English and WMT French-Spanish data sets show that our approach significantly outperforms the baseline method.

The Spatial Distribution Characteristics of Resident Population Growth Rate in Henan Province, China

Population is an important strategic resource for national development, a fundamental element of socio-economic development. The coordinated development of population and economy is an effective way to achieve rapid economic growth. Based on the population statistics data of counties (districts) in Henan Province, China, from 2006 to 2021. The paper firstly uses the logistic population growth mathematical model to calculate the resident population growth rate of counties (districts), then utilizes the hotspot analysis and spatial semi-variogram analysis, to research the spatial distribution characteristics of the resident population growth rate in Henan Province. The research results show that the evolution of the regional resident population in the province basically conforms to the logistic natural growth model. The resident population growth rate shows the characteristics of high in the north and low in the south, high in the center and low in the surrounding regions. The resident population growth rate is positively correlated with the level of economic development;the urban built-up areas, especially the new regions in urban planning, have a fast growth rate of resident population, which has a significant siphon effect on the population of surrounding regions. The hotspots of resident population growth rate in the province are mainly distributed in the urban built-up areas and surrounding regions of Zhengzhou, Luoyang, and Xinxiang, accounting for about 3.51% of the total area of the province. The cold spots are mainly distributed in the eastern part of the province, forming zonal distribution, which spans across Shangqiu City, Zhoukou City, and Zhumadian City, accounting for about 8.61% of the total area of the province. The area with negative growth of resident population accounts for approximately 53.47% of the total province. The spatial distribution of the growth rate of the resident population in the whole province basically conforms to the spherical model, with a small dispersion degree and a short range. In the range, there is a high degree of variability in resident population growth rate.

Improved Mechanism for Detecting Examinations Impersonations in Public Higher Learning Institutions: Case of the Mwalimu Nyerere Memorial Academy (MNMA)

Currently, most public higher learning institutions in Tanzania rely on traditional in-class examinations, requiring students to register and present identification documents for examinations eligibility verification. This system, however, is prone to impersonations due to security vulnerabilities in current students’ verification system. These vulnerabilities include weak authentication, lack of encryption, and inadequate anti-counterfeiting measures. Additionally, advanced printing technologies and online marketplaces which claim to produce convincing fake identification documents make it easy to create convincing fake identity documents. The Improved Mechanism for Detecting Impersonations (IMDIs) system detects impersonations in in-class exams by integrating QR codes and dynamic question generation based on student profiles. It consists of a mobile verification app, built with Flutter and communicating via RESTful APIs, and a web system, developed with Laravel using HTML, CSS, and JavaScript. The two components communicate through APIs, with MySQL managing the database. The mobile app and web server interact to ensure efficient verification and security during examinations. The implemented IMDIs system was validated by a mobile application which is integrated with a QR codes scanner for capturing codes embedded in student Identity Cards and linking them to a dynamic question generation model. The QG model uses natural language processing (NLP) algorithm and Question Generation (QG) techniques to create dynamic profile questions. Results show that the IMDIs system could generate four challenging profile-based questions within two seconds, allowing the verification of 200 students in 33 minutes by one operator. The IMDIs system also tracks exam-eligible students, aiding in exam attendance and integrates with a Short Message Service (SMS) to report impersonation incidents to a dedicated security officer in real-time. The IMDIs system was tested and found to be 98% secure, 100% convenient, with a 0% false rejection rate and a 2% false acceptance rate, demonstrating its security, reliability, and high performance.

Robust design of natural laminar flow supercritical airfoil by multi-objective evolution method

Abstract A transonic, high Reynolds number natural laminar flow airfoil is designed and studied. The γ-θ transition model is combined with the shear stress transport （SST） k-w turbulence model to predict the transition region for a laminar-turbulent boundary layer. The non-uniform free-form deformation （NFFD） method based on the non-uniform rational B-spline （NURBS） basis function is introduced to the airfoil parameterization. The non-dominated sorting genetic algorithm-II （NSGA-II） is used as the search algo- rithm, and the surrogate model based on the Kriging models is introduced to improve the efficiency of the optimization system. The optimization system is set up based on the above technologies, and the robust design about the uncertainty of the Mach number is carried out for NASA0412 airfoil. The optimized airfoil is analyzed and compared with the original airfoil. The results show that natural laminar flow can be achieved on a supercritical airfoil to improve the aerodynamic characteristic of airfoils.

An efficient framework for ensemble of natural disaster simulations as a service

Calculations of risk from natural disasters may require ensembles of hundreds of thousands of simulations to accurately quantify the complex relationships between the outcome of a disaster and its contributing factors.Such large ensembles cannot typically be run on a single computer due to the limited computational resources available.Cloud Computing offers an attractive alternative,with an almost unlimited capacity for computation,storage,and network bandwidth.However,there are no clear mechanisms that define how to implement these complex natural disaster ensembles on the Cloud with minimal time and resources.As such,this paper proposes a system framework with two phases of cost optimization to run the ensembles as a service over Cloud.The cost is minimized through efficient distribution of the simulations among the cost-efficient instances and intelligent choice of the instances based on pricing models.We validate the proposed framework using real Cloud environment with real wildfire ensemble scenarios under different user requirements.The experimental results give an edge to the proposed system over the bag-of-task type execution on the Clouds with less cost and better flexibility.

Study on conveyor natural frequency and time intervalfor switching off resistances

A conveyor belt driven by wound rotor motors produces dynamic tension, velocity and accelerationduring starting. The terrible situation (such as resonance) in dynamic analysis and design is that system naturalfrequencies are equal to those for switching off electric resistances. This paper analyzes and determines systemnatural frequencies based on a modeling method of receptances with the analysis of sub-systems model and of theprinciple of their addition and conveyor loop closure. It also puts forward to calculate the time interval for switching off electric resistances. The starting of one conveyor is simulated by lumped-mass-spring-model software tofurther illustrate the influence of time interval for switching off electric resistances on conveyor dynamic behavior. Two methods are also compared. The receptance model is proved to be an excellent alternative.

Improving a method for evaluating alfalfa cultivar resistance to thrips

The thrips quantity ratio（TQR） model is an important tool for evaluating crop resistance to thrips based on the correlation between thrips quantities and cultivars. Unfortunately, it is inaccurate, and the results appear significantly inconsistent when analysing the same cultivars in the same field study. To improve this model, we first studied the resistance of 28 alfalfa cultivars to thrips in Cangzhou, Hebei Province, north China. The results showed that the most suitable evaluation period was from May to June, as the thrips population was stable during this period. Second, we found that the natural enemy population was significantly positively correlated with the thrips population density（R=0.7275, P〈0.0001）, which might influence resistance estimation. Hence, we introduced a parameter ‘α＇, corresponding to the natural enemy quantity ratio, to eliminate the effect of the natural enemy using ＂αTQR＂. Using the improved method, 28 cultivars were clustered into three classes： the resistant class, sensitive class, and median class. All numerical values were calculated for αTQR displayed as a Gaussian distribution. This information showed that all data should be divided into nine groups using a median value of 1±0.1 with an equal difference of 0.1. Based on the new standard cultivars, Gongnong 1, Alfaking, Cangzhou and Algonquin were classified as highly resistant cultivars; Zhongmu 3, Gongnong 2, Zhongmu 1 and Zhongmu 2 were classified in the resistant group; Queen was classified in the moderately resistant group; Derby, WL354HQ, KRIMA, Apex, 53 HR, SARDI 5 and Farmers Treasure were classified in the median class; WL319HQ, WL343HQ and Sitel were classified as the low sensitive group; WL440 HQ and SARDI7 as the moderately sensitive group; WL168HQ and Sanditi as the sensitive group; and SARDI 10, WL363HQ, FD4, WL323 and SOCA as the highly sensitive group.

Forecasting of China's natural gas production and its policy implications

With the vigorous promotion of energy conservation and implementation of clean energy strategies,China＇s natural gas industry has entered a rapid development phase,and natural gas is playing an increasingly important role in China＇s energy structure.This paper uses a Generalized Weng model to forecast Chinese regional natural gas production,where accuracy and reasonableness compared with other predictions are enhanced by taking remaining estimated recoverable resources as a criterion.The forecast shows that China＇s natural gas production will maintain a rapid growth with peak gas of 323 billion cubic meters a year coming in 2036;in 2020,natural gas production will surpass that of oil to become a more important source of energy.Natural gas will play an important role in optimizing China＇s energy consumption structure and will be a strategic replacement of oil.This will require that exploration and development of conventional natural gas is highly valued and its industrial development to be reasonably planned.As well,full use should be made of domestic and international markets.Initiative should also be taken in the exploration and development of unconventional and deepwater gas,which shall form a complement to the development of China＇s conventional natural gas industry.

Defects and asymmetries in the visual pathway of non-human primates with natural strabismus and amblyopia

Strabismus and amblyopia are common ophthalmologic developmental diseases caused by abnormal visual experiences. However, the underlying pathogenesis and visual defects are still not fully understood. Most studies have used experimental interference to establish diseaseassociated animal models, while ignoring the natural pathophysiological mechanisms. This study was designed to investigate whether natural strabismus and amblyopia are associated with abnormal neurological defects. We screened one natural strabismic monkey(Macaca fascicularis) and one natural amblyopic monkey from hundreds of monkeys, and retrospectively analyzed one human strabismus case. Neuroimaging, behavioral,neurophysiological, neurostructural, and genovariation features were systematically evaluated using magnetic resonance imaging(MRI), behavioral tasks, flash visual evoked potentials(FVEP),electroretinogram(ERG), optical coherence tomography(OCT), and whole-genome sequencing(WGS), respectively. Results showed that the strabismic patient and natural strabismic and amblyopic monkeys exhibited similar abnormal asymmetries in brain structure, i.e., ipsilateral impaired right hemisphere. Visual behavior, visual function, retinal structure, and fundus of the monkeys were impaired. Aberrant asymmetry in binocular visual function and structure between the strabismic and amblyopic monkeys was closely related, with greater impairment of the left visual pathway.Several similar known mutant genes for strabismus and amblyopia were also identified. In conclusion,natural strabismus and amblyopia are accompanied by abnormal asymmetries of the visual system,especially visual neurophysiological and neurostructural defects. Our results suggest that future therapeutic and mechanistic studies should consider defects and asymmetries throughout the entire visual system.

Deep Semantic Structure of Natural Language

This paper presents the result of research of deep structure of natural language. The main result attained is the existence of a deterministic mathematical model that relates phonetics to associated mental images starting from the simplest linguistic units in agreement with the human response to different acoustic stimuli. Moreover, there exists two level hierarchy for natural language understanding. The first level uncovers the conceptual meaning of linguistic units, and hence forming a corresponding mental image. At the second level the operational meaning is found to suit, context, pragmatics, and world knowledge. This agrees with our knowledge about human cognition. The resulting model is parallel, hierarchical but still concise to explain the speed of natural language understanding.

A new stationary droplet evaporation model and its validation

The liquid droplet evaporation character is important for not only combustion chamber design process but also high-accuracy spray combustion simulation. In this paper, the suspended droplets＇ evaporation character was measured in a quiescent high-temperature environment by micro high-speed camera system. The gasoline and kerosene experimental results are consistent with the reference data. Methanol, common kerosene and aviation kerosene droplet evaporation characteristics, as well as their evaporation rate changing with temperature, were obtained. The evaporation rate experimental data were compared with the prediction result of Ranz-Marshall boiling temperature model（RMB）, Ranz-Marshall low-temperature model（RML）, drift flux model（DFM）, mass analogy model（MAM）, and stagnant film model（SFM）. The disparity between the experimental data and the model prediction results was mainly caused by the neglect of the natural convection effect, which was never introduced into the droplet evaporation concept. A new droplet evaporation model with consideration of natural convection buoyancy force effect was proposed in this paper. Under the experimental conditions in this paper, the calculation results of the new droplet evaporation model were agreed with the experimental data for kerosene, methanol and other fuels, with less than 20% relative deviations. The relative deviations between the new evaporation model predictions for kerosene and the experimental data from the references were within 10%.

Contributions of anthropogenic and external natural forcings to climate changes over China based on CMIP5 model simulations

Based on observations and historical simulations from the fifth phase of the Coupled Model Intercomparison Project(CMIP5) archive, the contributions of human activities(including greenhouse gases(GHGs), anthropogenic aerosols(AAs), and land use(LU)) and external natural forcings(Nat) to climate changes in China over the past 50 years were quantified. Both anthropogenic and external natural forcings account for 95%–99% of the observed temperature change from 1951–1975 to 1981–2005. In particular, the temperature changes induced by GHGs are approximately 2–3 times stronger than the observed changes, and AAs impose a significant cooling effect. The total external forcings can explain 65%–78% of the observed precipitation changes over the past 50 years, in which AAs and GHGs are the primary external forcings leading to the precipitation changes; in particular, AAs dominate the main spatial features of precipitation changes in eastern China. Human activities also dominate the long-term non-linear trends in observed temperature during the past several decades, and, in particular, GHGs, the primary warming contributor, have produced significant warming since the 1960 s. Compared to the long-term non-linear trends in observed precipitation, GHGs have largely caused the wetting changes in the arid-semiarid region since the 1970 s, whereas AAs have led to the drying changes in the humid-semihumid region; both LU and Nat can impose certain impacts on the long-term non-linear trends in precipitation. Using the optimal fingerprinting detection approach, the effects of human activities on the temperature changes can be detected and attributed in China, and the effect of GHGs can be clearly detected from the observations in humid-semihumid areas. However, the anthropogenic effects cannot be detected in the observed precipitation changes, which may be due to the uncertainties in the model simulations and to other issues. Although some results in this paper still need improvement due to uncertainties in the coupled models, this study is expected to provide the background and scientific basis for climate changes to conduct vulnerability and risk assessments of the ecological systems and water resources in the arid-semiarid region of China.

Imprecise Reliability Assessment for Heavy Numerical Control Machine Tools Against Small Sample Size Problem

Small sample size problem is one of the main problems that heavy numerical control(NC) machine tools encounter in their reliability assessment. In order to deal with the small sample size problem, many indirect reliability data such as reliability data of similar products, expert opinion, and engineers' experience are used in reliability assessment. However, the existing mathematical theories cannot simultaneously process the above reliability data of multiple types, and thus imprecise probability theory is introduced. Imprecise probability theory can simultaneously process multiple reliability data by quantifying multiple uncertainties(stochastic uncertainty,fuzzy uncertainty, epistemic uncertainty, etc.) together. Although imprecise probability theory has so many advantages, the existing natural extension models are complex and the computation result is imprecise. Therefore,they need some improvement for the better application of reliability engineering. This paper proposes an improved imprecise reliability assessment method by introducing empirical probability distributions to natural extension model, and the improved natural extension model is applied to the reliability assessment of heavy NC machine tool spindle to illustrate its effectiveness.

Performance of CH4MOD_(wetland) for the case study of different regions of natural Chinese wetland

Reliable national estimates of CH_4 emissions from natural wetlands depend on model validation based on site observations.We therefore evaluated the performance of the CH_4 MODwetlandmodel in simulating CH_4 emissions from 11 representative wetland sites in five regions of China.Model performance analysis showed that this method effectively simulates differences in the CH_4 fluxes between different sites and regions.The model efficiency for estimating the daily CH_4 fluxes in the northeastern China（NE）,Inner Mongolia and northwestern China（NW）,the North China plain and the Middle-Lower Yangtze Plain（E） and the Qinghai Tibetan Plateau（SW） was 0.51,0.20,0.52 and 0.65,respectively.The efficiency for estimating the annual mean CH_4 fluxes in southern China（S） was 0.99.Systematic negative deviation between the simulated and observed CH_4 emissions existed in all regions,especially in the NW region,which had a mean deviation（RMD） value of-36.7%.On the national scale,the root mean square error（RMSE）,the RMD,the model efficiency（EF）between the simulated and observed seasonal values were 28.7%,-7.8% and 0.93,respectively.The CH_4 emissions showed the highest sensitivity to air temperature in the NE and SW regions,and to water table depth in the E region.Based on the sensitivity analysis,future climate warming and wetting are likely to increase the wetland CH_4 emissions at different levels in all regions of China.

Constructing Damage Indices Based on Publicly Available Spatial Data:Exemplified by Earthquakes and Volcanic Eruptions in Indonesia

This article demonstrates the construction of earthquake and volcano damage indices using publicly available remote sensing sources and data on the physical characteristics of events.For earthquakes we use peak ground motion maps in conjunction with building type fragility curves to construct a local damage indicator.For volcanoes we employ volcanic ash data as a proxy for local damages.Both indices are then spatially aggregated by taking local economic exposure into account by assessing nightlight intensity derived from satellite images.We demonstrate the use of these indices with a case study of Indonesia,a country frequently exposed to earthquakes and volcanic eruptions.The results show that the indices capture the areas with the highest damage,and we provide overviews of the modeled aggregated damage for all provinces and districts in Indonesia for the time period 2004 to 2014.The indices were constructed using a combination of software programs—ArcGIS/Python,Matlab,and Stata.We also outline what potential freeware alternatives exist.Finally,for each index we highlight the assumptions and limitations that a potential practitioner needs to be aware of.