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The total amount of sugarcane planting in China ranks third in the world, and Guangxi is the largest sugarcane planting base in China. In order to help the Guangxi government and industry better understand the annual planting distribution and scale of sugarcane in the whole region, it is convenient to optimize the planting structure and improve the efficiency of resource utilization, so as to ensure the stable development of Guangxi sugar industry. Based on the satellite-based hyperspectral image data of ' Zhuhai No.1 ', this paper carries out sugarcane recognition and area extraction, which fills the application gap of satellite-based hyperspectral image data in extracting sugarcane area in China. A globally optimized extended random walk model was used to identify and extract sugarcane by combining the spatial-spectral information of hyperspectral imagery. Firstly, the Initial probability estimation is performed using the LOR classifier, and then use the data after MNF dimensionality reduction to construct a weighted graph, and finally the probability optimization and recognition are carried out based on the extended random walk model. The results show that the spatial-spectral joint method based on extended random walk can effectively identify sugarcane, and the sugarcane recognition accuracy of 2021 year image can reach 91.4%, the misrecognition rate is 2.8%; the sugarcane recognition accuracy of 2020 year image can reach 90.5 %, the misrecognition rate is 3.1%. [ABSTRACT FROM AUTHOR]

The ongoing COVID-19 shocked financial markets globally, including China's crude oil future market, which is the third-most traded crude oil futures after WTI and Brent. As China's first crude oil futures are accessible to foreign investors, the Shanghai crude oil futures (SC) have attracted significant interest since launch at the Shanghai International Energy Exchange. The impact of COVID-19 on the new crude oil futures is an important issue for investors and policy makers. Therefore, this paper studies the short-term influence of COVID-19 pandemic on SC via multifractal analysis. We compare the market efficiency of SC before and during the pandemic with the multifractal detrended fluctuation analysis and other commonly used random walk tests. Then, we generate shuffled and surrogate data to investigate the components of multifractal nature in SC. And we examine cross-correlations between SC returns and other financial assets returns as well as SC trading volume changes by the multifractal detrended cross-correlation analysis. The results show that market efficiency of SC and its cross-correlations with other assets increase significantly after the outbreak of COVID-19. Besides that, the sources of its multifractal nature have changed since the pandemic. The findings provide evidence for the short-term impacts of COVID-19 on SC. The results may have important implications for assets allocation, investment strategies and risk monitoring. [ABSTRACT FROM AUTHOR]

The prediction of disaster risk paths can foresee the spread of disaster risk and lay a foundation for reducing or avoiding the harm of disaster risk. In this paper, we have improved the embedding layer of convolution neural network (CNN), and we literally refer to the specific CNN framework as IECNN. The IECNN model is proposed to predict the disaster risk path. Here, we first establish a disaster risk network in which each node represents two attributes: place and disaster type. The random walk paths are generated from the disaster risk network, and the structural characteristics of nodes in the disaster risk paths are considered in the improved embedding layer of IECNN. This study also applies Markov chain algorithm to calculate the probability of each disaster risk path and trains the IECNN model with the determined disaster risk paths. ROC curve, AUC, Accuracy, F1-measure, Precision, and Recall are used to evaluate the prediction model. In order to verify the feasibility and advantage of the proposed model, we use a dataset consisting of natural disasters in southwest China in the experimental section. Results of the comparative analysis display that the proposed model cannot only effectively predict the disaster risk path, but also provide the high performance in terms of every evaluation index. Moreover, some characters of disaster risk path are found and discussed. Resultantly, our results can provide an efficient way to prevent and control risk spread in disaster events. [ABSTRACT FROM AUTHOR]

This paper aims to evaluate the performances of the wavelet, Hodrick–Prescott (HP), and Baxter–King (BK) filters in extracting cyclical information and to use an appropriate method to analyze China's business cycles. First, we use a second‐order autoregression (AR (2)) and random walk, based on Monte Carlo simulation experiments, to generate the data‐generating processes (DGPs) with different frequency characteristics. Second, the HP, BK, and wavelet filters are applied to extract the cyclical components of the respective DGPs. Third, the filtering abilities of the three methods are statistically compared. The results show the following: (1) Under the condition that the DGP is low frequency (long cycle) and trend dominated, the filtering performance of the three methods will remain unsatisfactory. (2) If the DGP is high frequency (short cycle), all three methods can serve as effective methods regardless of whether they are trend dominated or cycle dominated. However, it can be seen that the BK and wavelet filters present better performance than the HP filter. (3) In other cases, better filtering performances can be observed in the wavelet. Finally, the three methods are applied to estimate China's business cycles. In conclusion, this paper argues that the wavelet can effectively replace HP and BK filters to extract cyclical components. [ABSTRACT FROM AUTHOR]

The appropriate division of underground drinking water source protection zones is a low-cost method of preventing water source pollution and ensuring a supply of safe drinking water. Based on FEFLOW, a groundwater flow model of large water sources was established for Luan River, North China. Trace lines of particle reverse migration for 100 and 1000 days were obtained by random walks. According to the trace morphology, the water sources in the riverside water source area were divided into four categories. The first- and second-grade protection areas were delimited by ArcGIS, with areas of 0.375 and 1.20 km2. The local and global sensitivity of the permeability coefficient (K) and effective porosity (ne) effects on the area of groundwater protection zones were calculated. The area of the protection zones was positively correlated with K and negatively correlated with ne. The variation in the protected zone caused by the simultaneous changes in K and ne is the same as that of ne alone, and the global sensitivity is closer to the local sensitivity of ne. This indicates that ne has a greater impact than K on the scope of groundwater protection zones. Moreover, global sensitivity is not simply a superposition of local sensitivity, and the interaction between parameters can reduce the effect of a parameter acting alone on the delineation of protection zones. This also shows that the global sensitivity is closer to the actual situation than the local sensitivity, thus providing a scientific basis for the delimitation and monitoring of water source protection zones. [ABSTRACT FROM AUTHOR]

We present a novel approach for estimating the proportional distributions of function types (i.e. functional distributions) in an urban area through learning semantics preserved embeddings of points-of-interest (POIs). Specifically, we represent POIs as low-dimensional vectors to capture (1) the spatial co-occurrence patterns of POIs and (2) the semantics conveyed by the POI hierarchical categories (i.e. categorical semantics). The proposed approach utilizes spatially explicit random walks in a POI network to learn spatial co-occurrence patterns, and a manifold learning algorithm to capture categorical semantics. The learned POI vector embeddings are then aggregated to generate regional embeddings with long short-term memory (LSTM) and attention mechanisms, to take account of the different levels of importance among the POIs in a region. Finally, a multilayer perceptron (MLP) maps regional embeddings to functional distributions. A case study in Xiamen Island, China implements and evaluates the proposed approach. The results indicate that our approach outperforms several competitive baseline models in all evaluation measures, and yields a relatively high consistency between the estimation and ground truth. In addition, a comprehensive error analysis unveils several intrinsic limitations of POI data for this task, e.g. ambiguous linkage between POIs and functions. [ABSTRACT FROM AUTHOR]

In this paper, we use the permutation entropy algorithm to derive the static and dynamic permutation entropy of commodity futures, and to evaluate the effectiveness of main products in China's commodity futures market. The intraday data of six varieties belonging to six categories in China's commodity futures market are taken as samples. We find the following: (1) The return distribution of the main varieties shows high peaks, fat tails and asymmetry, and follows the biased random walk distribution characteristics; (2) The permutation entropy of all varieties decreases significantly in the same time window, during which the price volatility of major commodity markets rises. And the time window coincides with the impact time of COVID-19 epidemic; (3) By comparing the distribution of permutation entropy of main varieties in different stages of event shock, we found that the mean value of permutation entropy decreases significantly during the process of event shock, and the price fluctuates greatly. Therefore, the significant decrease of permutation entropy is a valuable warning signal for regulators and investors. [ABSTRACT FROM AUTHOR]

Stocks markets play their financial roles of price shocks and hedging just when they are proficient. The imperative highlights of productive market are that one cannot make extraordinary profit from the stocks markets. This research investigates whether China wheat futures price can be predicted by employing artificial intelligence neural network. This would add to our knowledge whether wheat futures market is resourceful and would enable traders, sellers, and investors to improve cost-effective trading strategy. We utilize the traditional financial model to forecast the wheat futures price and acquire out of sample point estimates. We additionally assess the robustness of our outcomes by applying several alternative forecasting techniques such as artificial intelligence with one hidden layer and autoregressive integrated moving average (ARIMA) model. Furthermore, the statistical significance of our point estimation was further tested through the Mariano and Diebold test. Considering random walk forecast as the bench mark, we used a number of economic indicators, trader's expectation towards futures prices, and lagged value of futures price of wheat in order to forecast the evaluation of wheat futures price. The computable significance of out of sample estimations recommends that our ANN with one hidden layer has the best anticipating presentation among all the models considered in this exploration and has the estimating power in foreseeing wheat futures returns. Furthermore, this investigation discovers that the futures price of wheat can be predicted, and the wheat futures market of China is not productive. [ABSTRACT FROM AUTHOR]

City taxi service systems have been empirically studied by a number of data-driven methods. However, their underlying mechanisms are hard to understand because the present mathematical models neglect to explain a (whole) taxi service process that includes a pair of on-load phase and off-load phase. In this paper, by analyzing a large amount of taxi servicing data from a large city in China, we observe that the taxi service process shows different temporal and spatial features according to the on-load phase and off-load phase. Moreover, our correlation analysis results demonstrate the lack of dependence between the on-load phase and the off-load phase. Hence, we introduce two independent random walk models based on the Langevin equation to describe the underlying mechanism and to understand the temporal and spatial features of the taxi service process. Our study attempts to formulate the mathematical framework for simulating the taxi service process and better understanding of its underlying mechanism. [ABSTRACT FROM AUTHOR]

Background: Understanding potential patterns in future population levels is crucial for anticipating and planning for changing age structures, resource and health-care needs, and environmental and economic landscapes. Future fertility patterns are a key input to estimation of future population size, but they are surrounded by substantial uncertainty and diverging methodologies of estimation and forecasting, leading to important differences in global population projections. Changing population size and age structure might have profound economic, social, and geopolitical impacts in many countries. In this study, we developed novel methods for forecasting mortality, fertility, migration, and population. We also assessed potential economic and geopolitical effects of future demographic shifts.Methods: We modelled future population in reference and alternative scenarios as a function of fertility, migration, and mortality rates. We developed statistical models for completed cohort fertility at age 50 years (CCF50). Completed cohort fertility is much more stable over time than the period measure of the total fertility rate (TFR). We modelled CCF50 as a time-series random walk function of educational attainment and contraceptive met need. Age-specific fertility rates were modelled as a function of CCF50 and covariates. We modelled age-specific mortality to 2100 using underlying mortality, a risk factor scalar, and an autoregressive integrated moving average (ARIMA) model. Net migration was modelled as a function of the Socio-demographic Index, crude population growth rate, and deaths from war and natural disasters; and use of an ARIMA model. The model framework was used to develop a reference scenario and alternative scenarios based on the pace of change in educational attainment and contraceptive met need. We estimated the size of gross domestic product for each country and territory in the reference scenario. Forecast uncertainty intervals (UIs) incorporated uncertainty propagated from past data inputs, model estimation, and forecast data distributions.Findings: The global TFR in the reference scenario was forecasted to be 1·66 (95% UI 1·33-2·08) in 2100. In the reference scenario, the global population was projected to peak in 2064 at 9·73 billion (8·84-10·9) people and decline to 8·79 billion (6·83-11·8) in 2100. The reference projections for the five largest countries in 2100 were India (1·09 billion [0·72-1·71], Nigeria (791 million [594-1056]), China (732 million [456-1499]), the USA (336 million [248-456]), and Pakistan (248 million [151-427]). Findings also suggest a shifting age structure in many parts of the world, with 2·37 billion (1·91-2·87) individuals older than 65 years and 1·70 billion (1·11-2·81) individuals younger than 20 years, forecasted globally in 2100. By 2050, 151 countries were forecasted to have a TFR lower than the replacement level (TFR <2·1), and 183 were forecasted to have a TFR lower than replacement by 2100. 23 countries in the reference scenario, including Japan, Thailand, and Spain, were forecasted to have population declines greater than 50% from 2017 to 2100; China's population was forecasted to decline by 48·0% (-6·1 to 68·4). China was forecasted to become the largest economy by 2035 but in the reference scenario, the USA was forecasted to once again become the largest economy in 2098. Our alternative scenarios suggest that meeting the Sustainable Development Goals targets for education and contraceptive met need would result in a global population of 6·29 billion (4·82-8·73) in 2100 and a population of 6·88 billion (5·27-9·51) when assuming 99th percentile rates of change in these drivers.Interpretation: Our findings suggest that continued trends in female educational attainment and access to contraception will hasten declines in fertility and slow population growth. A sustained TFR lower than the replacement level in many countries, including China and India, would have economic, social, environmental, and geopolitical consequences. Policy options to adapt to continued low fertility, while sustaining and enhancing female reproductive health, will be crucial in the years to come.Funding: Bill & Melinda Gates Foundation. [ABSTRACT FROM AUTHOR]

This paper studies the effectiveness of the CSI 300 index futures markets from the perspective of information efficiency and function efficiency and examines the nonlinear dynamic characteristics of efficiency by using nonparametric methods. For information effectiveness, we find that the price of stock index futures follows a random walk. For function effectiveness, the results show that (1) the average optimal hedge ratio is 0.8702, and the average effective level reaches 86.11%. (2) The error correction mechanism is only supported by stock index futures. The error correction effect only exists in the extreme regime (only 6% of the total observed value). Most of the time (94%), both prices are subject to random walk process. There is no arbitrage trade between futures and spots. (3) Both linear and nonlinear leadership are observed in stock index futures. The nonlinear leadership is mainly reflected in stock index futures. Both leadership types are influenced by institutional changes and significant financial events and evolve over time, which indicates that stock index futures cannot play the dominant role in price discovery. In sum, we conclude that the CSI 300 stock index futures market is effective, despite the flaws in price discovery. [ABSTRACT FROM AUTHOR]

In this paper we propose a network-based Kalman filter combined generalized simulated annealing algorithm approach to decompose a group of GPS position time series into secular trend, annual and semi-annual signals as well as noise components. This approach treats east, north and vertical components of the whole network separately and estimates network-average process-noise parameters to constrain the time variability of the seasonal signals and noise components. Each coordinate component for each station is modeled in state-space model (SSM) individually. The noise components are described as the combination of flicker noise (FN), random walk noise (RWN) and observation white noise (WN). Each component, except for the trend, is allowed to variate over the time, and their amplitudes are estimated by maximization of likelihood function using a generalized simulated annealing (GSA) algorithm. The proposed approach is applied to 10 reprocessed GPS position time series from the Tectonic and Environmental Observation Network of Mainland China (CMONOC II), and its output is compared with that of ordinary maximum likelihood estimation (MLE). The results show that the proposed approach is an effective tool for the decomposition of GPS position time series. Finally, the advantages and limitations of the proposed approach are also discussed. [ABSTRACT FROM AUTHOR]

Based on the Lagrangian random walk particle tracking method and the global ocean reanalysis data, this study simulated the drift-diffusion process in ocean of microplastic particles (density less than seawater) discharged by coastal cities in China for 12 consecutive years. The results reveal that most of the microplastics (80.33%) essentially end up ashore or in the marginal seas around China, a small portion of microplastics (18.22%) enter the Sea of Japan and the Northwest Pacific Ocean via the Tsushima Strait and the Osumi-Kaikyo with the Kuroshio Tide, a very small portion of microplastics (1.45%) enter into the waters of Southeast Asian countries along with the west boundary current of South China Sea. The concentration distribution characteristics have obvious seasonal variation in the high concentration areas (the marginal seas around China and Sea of Japan). The mainly destination area of microplastics released in different cities is different. • Microplastic's transportation in ocean discharged by China's coastal cities. • Most of the microplastics (80.33%) end up ashore or in the marginal seas around China. • Two channels (18.22%, 1.45%) are exported from the marginal seas around China. • The concentration have seasonal variation in the marginal seas around China and Japan. • The microplastics's mainly destination area released in different cities is different. [ABSTRACT FROM AUTHOR]

Sustainability has been one of the key criteria of effective water exploitation. Groundwater exploitation and water-table decline at Haolebaoji water source site in the Ordos basin in NW China has drawn public attention due to concerns about potential threats to ecosystems and grazing land in the area. To better investigate the impact of production wells at Haolebaoji on the water table, an adapted algorithm called the random walk on grid method (WOG) is applied to simulate the hydraulic head in the unconfined and confined aquifers. This is the first attempt to apply WOG to a real groundwater problem. The method can not only evaluate the head values but also the contributions made by each source/sink term. One is allowed to analyze the impact of source/sink terms just as if one had an analytical solution. The head values evaluated by WOG match the values derived from the software Groundwater Modeling System (GMS). It suggests that WOG is effective and applicable in a heterogeneous aquifer with respect to practical problems, and the resultant information is useful for groundwater management. [ABSTRACT FROM AUTHOR]

In recent years, multi-source clustering has received a significant amount of attention. Several multi-source clustering methods have been developed from different perspectives. In this paper, aiming at addressing the problem of Chinese–Tibetan bilingual document clustering, a novel bilingual clustering scheme is proposed, which can well capture both the intralingua document structures and interlingua document relations. The proposed scheme consists of three major phases. Firstly, to properly combine the feature structures of documents in different languages, a bilingual graph is constructed. In the second phase, two bilingual similarity matrices are computed based on the random walk performed in the bilingual graph. Finally, the similarity based clustering methods are performed on the two bilingual similarity matrices so as to generate cluster structures for documents in each language respectively, which lead to the corresponding bilingual clustering methods. Extensive experiments conducted on two Chinese–Tibetan bilingual document sets have confirmed the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper investigates the weak form efficiency in the BRIC countries and Turkey with use of autocorrelation analysis, unit root tests, Johansen cointegration and Granger causality test. Monthly data covers the period from July 1997 to December 2013. Our findings indicate the efficiency among the stock markets in the weak form. The empirical findings indicate monthly closing prices of indices follow the random walk procedure. According to Granger causality and Johansen cointegration tests we found the long-run relationship between China and India, also China and Turkey. [ABSTRACT FROM AUTHOR]

This is a working paper which has examined the weak form of efficiency on two major stock exchanges of china that is Shanghai Stock Exchange and Shenzhen Stock Exchange. Historical index values were gathered on monthly basis for a period of 10 years (1st April 2002 to 2nd May 2013) for the Shanghai and Shenzhen Composite index. The random walk hypothesis is examined using two statistical methods, namely a serial autocorrelation test and a non-parametric runs test. In our earlier studies we have documented that Indian Stock Market (BSE) is weak form efficient whereas in this study we have concluded that Chinese stock market is not weak form efficient. [ABSTRACT FROM AUTHOR]

Blogs are arguably the most popular genre of user-generated content (UGC), which make blogs a gold mine for social science research. However, existing research on blogs has suffered from nonprobability samples collected either manually or by computerized crawling based on random walks method. The current article presents a probability sampling method for blogs, called random digit search (RDS), that is modified from the popular ‘‘random digit dialing’’ (RDD) method used in telephone surveys. The RDS method was tested in a study of Sina Blog, a popular blog service provider (BSP) in China. The results show that, while ‘‘random walks’’ sampling tends to oversample popular/active blogs, probability samples generated by RDS yield consistent and precise estimates of population parameters. Although the RDS takes advantage of the numeric identification (ID) system used on Sina Blog, the general principles may be applicable to other BSPs and many other genres of UGC. [ABSTRACT FROM PUBLISHER]

Real Gross Domestic Product (GDP) growth in China follows a random walk. Also, it has often been suggested that China 'cooks its books', that is to say that governmental officials in China manipulate economic statistics, such as GDP growth rate to present the outside world a rosy picture (Foreign Policy, 3 September 2009). If such unreliability is known to stock traders, news on GDP should not impact stock market fluctuations or their volatility. We test this hypothesis for 12 series with daily stock market returns for the years 2006 to and including 2009. [ABSTRACT FROM AUTHOR]

The paper investigates the relationship between changes in asset wealth and the trend movements of household consumption in urban China. Using the vector error correction cointegration model, we demonstrate that there is a unique long-run cointegrating relationship between household consumption, disposable income, financial wealth and housing wealth in urban China. We find that housing wealth is the only factor that restores the long-run equilibrium relationship when the cointegrated system is disturbed by an external shock. In addition, our permanent–transitory variance decomposition analysis indicates that nearly all variance in the movement of consumption is permanent, supporting the classical random walk hypothesis of consumption behavior. However, a large proportion of variance in the short-run movements of housing wealth is found to be transitory. [ABSTRACT FROM AUTHOR]

This paper empirically examines whether three East Asian stock markets, namely, those of China, Japan and South Korea, are individually and/or jointly efficient, and whether contagion exists between the cointegrated markets. While individual market efficiency is examined through testing for the random walk hypothesis, joint market efficiency is examined through testing for cointegration and contagion. The present study finds that the hypothesis of individual market efficiency is strongly rejected for the Chinese stock market, but not for the Japanese and the South Korean stock markets. However, when testing for cointegration, market efficiency is strongly rejected for all these markets. We take a simple case of contagion and find that although there is a long-term relationship among the three markets, the contagion hypothesis cannot be rejected only between Japanese and South Korean stock markets, indicating short-run portfolio diversification benefits from these two markets. [ABSTRACT FROM AUTHOR]

Regional inequality is severe in China since regional development is uneven due to various initial conditions and government policies. We employ unit root tests allowing for structural breaks to alternative inequality measures from 1952 to 2000. Empirical results indicate that (1) the regional inequality is trend stationary with structural breaks rather than following a random walk. Thus, ignoring structural changes might leads to incorrect inference and misleading policy implications; (2) the break points are associated with episodic events in Chinese economic history such as the Cultural Revolution and market reforms. This implies that the policies had a long-lasting and fundamental effect on the inequality. Resumen. La desigualdad regional en China es pronunciada debido a un desarrollo regional dispar causado por un número de condiciones iniciales y políticas gubernamentales. Empleamos pruebas de raíz unitaria que permiten rupturas estructurales ( structural breaks) en medidas de desigualdad alternativas desde 1952 al 2000. Los resultados empíricos indican que (1) la desigualdad regional es de tendencia estacionaria con rupturas estructurales en lugar de seguir un paseo aleatorio ( random walk). Por tanto, el ignorar cambios estructurales podría llevar a una inferencia incorrecta e implicaciones políticas engañosas; (2) los puntos de ruptura están asociados con acontecimientos episódicos de la historia económica china como la Revolución cultural y las reformas del mercado. Esto implica que las políticas tuvieron un efecto duradero y fundamental en la desigualdad. [ABSTRACT FROM AUTHOR]

We conjecture that the evolution process with self-avoiding random walks is the origin for the properties of urban ground bus-transport networks (BTN). In order to verify our conjecture, a toy model, which simulates the growth of urban bus-transport systems, is proposed after empirical investigation on the BTNs of four major cities in China. In current empirical and simulation research, our method combining weight and geographical topology of the BTN together allows us to study the coupling relations among the BTN's weighted quantities and underlying topological structure. Finally, the simulating results reveal that the model can reproduce most phenomena observed in real-life urban ground BTNs. [ABSTRACT FROM AUTHOR]

This study tests the random walk hypothesis for China, Hong Kong and Singapore. Using variance ratio tests, robust to heteroskedasticity and employing a recently developed bootstrap technique to customize percentiles for inference purposes it is found that Class A shares for Chinese stock exchanges and the Hong Kong equity markets are weak form efficient. However, Singapore and Class B shares for Chinese stock exchanges do not follow the random walk hypothesis, which suggests that liquidity and market capitalization may play a role in explaining results of weak form efficiency tests. [ABSTRACT FROM AUTHOR]

In this paper two different geophysical electro-magnetic techniques, long-offset time domain EM and the magnetotelluric method, are jointly inverted using a variation of Bayesian inversion called Hybrid Monte-Carlo. Long-offset time domain EM is a method that records Earth response to a controlled source square wave signal, while the magnetotelluric method records Earth response to naturally occurring electro-magnetic signals. We obtain better understanding of subsurface resistivity structures because the information they provide is complementary and joint inversion reduces the set of permissible inversion models. In most situations where long-offset time domain EM is recorded magnetotelluric data is also collected, since receiver instrumentation is shared. Hybrid Monte Carlo uses the gradient of the forward model to enable larger jumps through the solution space than are permissible using the standard Metropolis-Hastings algorithm, avoiding the pitfall of random walk behavior and giving faster convergence. The method is successfully applied to a survey area near the edge of Wuhan China. We obtain inversion results in a highly urbanized area, where the magnetotelluric method is typically compromised by background electro-magnetic noise. • HMC reduces random walks and gives faster convergence. • The joint-inversion of MT and LOTEM combines complimentary EM responses. • Problems with difficult combinations of conductors and resistor would benefit. • This is the first joint inversion of EM data using HMC. [ABSTRACT FROM AUTHOR]