Enormously large tippers observed in southwest China: can realistic 3-D EM modeling reproduce them?

Abstract: Vertical magnetic transfer functions (tippers) estimated at a global/continental net of geomagnetic observatories/sites can be used to image the electrical conductivity structure of the Earth's crust and upper mantle (down to around 200 km). We estimated tippers at 54 geomagnetic observatories across China, aiming eventually to invert them in terms of subsurface three-dimensional (3-D) conductivity distribution. Strikingly, we obtained enormously large tippers at three inland observatories in southwest China. Large tippers are often observed at coastal/island observatories due to high conductivity contrasts between resistive bedrock and conductive seawater. However, tippers at those inland observatories appeared to be a few times larger than coastal/island tippers. As far as we know, such large tippers (reaching value 3) were never reported in any region worldwide. We perform electromagnetic simulations in 3-D conductivity models mimicking the geological setting and demonstrate that enormously large tippers are feasible and can be attributed to a current channeling effect.

A Review of Subsurface Electrical Conductivity Anomalies in Magnetotelluric Imaging.

After 70 years of development, magnetotelluric (MT), a remote sensing technique for subsurface electrical resistivity imaging, has been widely applied in resource exploration and the deep tectonic evolution of the Earth. The electrical resistivity anomalies and their quantitative interpretation are closely related to or even controlled by the interconnected high-conductivity phases, which are frequently associated with tectonic activity. Based on representative electrical resistivity studies mainly of the deep crust and mantle, we reviewed principal electrical conduction mechanisms, generally used conductivity mixing models, and potential causes of high-conductivity including the saline fluid, partial melting, graphite, sulfide, and hydrogen in nominally anhydrous minerals, and the general methods to infer the water content of the upper mantle through electrical anomaly revealed by MT.

First report of alternate hosts of willow rust disease caused by Melampsora ferrinii in China.

Corydalis acuminata Franch., C. edulis Maxim. and C. racemosa (Thunb.) Pers. of family Papaveraceae are rich in multiple alkaloids and widely used as Chinese medicinal herbs, for treating cough, pruritus, sores tinea and snake venom (Zhang et al. 2008, Iranshahy et al. 2014). In April 2021, orange rust pustules were observed on C. acuminata, C. edulis and C. racemosa in Shaanxi Province (34°4'56'' N, 108°2'9'' E, alt. 770 m), China. Samples were collected and voucher specimens were preserved in the Herbarium Mycologicum Academiae Sinicae (nos. HMAS249947-HMAS249949), China. Consequent geospatial investigations revealed that diseased plants can be observed at an altitude of 400-1000 m, and show an incidence from 40% to 80% varied by altitude. Spermogonia epiphyllous, subcuticular, densely grouped, oval or round, 0.14-0.36 × 0.09-0.30 mm, pale orange-yellow, and type 3 of Cummins and Hiratsuka (1963). Aecia mostly hypophyllous, subepidermal without peridia, Caeoma-type, erumpent, densely grouped, oval or round, 0.27-0.85 × 0.15-0.43 mm, and orange-yellow; hyaline peridial cells produced in a periphery of the sorus under the ruptured epidermis of host plants. Aeciospores globoid or broadly ellipsoid, catenulate with intercalary cells, 15.7-20.1 × 10.8-15.7 µm, yellow to pale orange; walls hyaline, verrucose, 1.7-3.1 µm thick. This fungus was morphologically identified as Melampsora (Melampsoraceae). The rDNA-28S and the internal transcribed spacer (ITS) regions were amplified using primers NL1/NL4 and ITS1/ITS4 (Ji et al. 2020; Wang et al. 2020). Bi-directional sequences were assembled and deposited in GenBank (accession nos. MW990091-MW990093 and MW996576-MW996578). Phylogenetic trees were constructed with the ITS+rDNA-28S dataset based on maximum-likelihood (ML), maximum-parsimony (MP) and Bayesian Inference (BI). ML and MP bootstrap values were calculated by bootstrap analyses of 1,000 replicates using MEGA-X (Kumar et al. 2018), while BI posterior probabilities (Bpps) were calculated using MrBayes ver. 3.1.2 (Ji et al. 2020; Wang et al. 2020). Phylogenetic analyses grouped our specimens and Melampsora ferrinii Toome & Aime into one clade, highly supported by bootstrap values of ML, MP, and Bpps of 100%/100%/1. Inoculations were conducted with 1-year-old plants of original host, Salix babylonica L. (Toome & Aime 2015). Aeciospores suspension with a concentration of 106 spores/ml were sprayed on 20 healthy leaves, with another 20 healthy leaves sprayed with sterile water as the control. The inoculated plants were kept in darkness at 20-25 °C for 2 days and then transferred into greenhouse at 23°C with 16 h light per day. After 8-10 days of inoculation, yellow pustules of uredinia appeared on abaxial surfaces of the inoculated leaves, which were identical to Toome & Aime (2015) reported, while the control leaves remained healthy. Inoculations with the same method were conducted by spraying urediniospores, and the same rust symptoms developed after 8 days. Genus Corydalis was verified as the alternate host of M. chelidonii-pierotii Tak. Matsumoto, M. coleosporioides Dietel, M. idesiae Miyabe and M. yezoensis Miyabe & T. Matsumoto (Shinyama & Yamaoka 2012; Okane et al. 2014; Yamaoka & Okane 2019), and C. incisa (Thunb.) Pers. was speculated as the potential alternate host of M. ferrinii (Toome & Aime 2015). Based on morphology, phylogeny and pathogenicity, we firstly report M. ferrinii in mainland China and verify C. acuminata, C. edulis and C. racemosa instead of C. incisa as its alternate hosts.

Patch Matching and Dense CRF-Based Co-Refinement for Building Change Detection from Bi-Temporal Aerial Images.

The identification and monitoring of buildings from remotely sensed imagery are of considerable value for urbanization monitoring. Two outstanding issues in the detection of changes in buildings with composite structures and relief displacements are heterogeneous appearances and positional inconsistencies. In this paper, a novel patch-based matching approach is developed using densely connected conditional random field (CRF) optimization to detect building changes from bi-temporal aerial images. First, the bi-temporal aerial images are combined to obtain change information using an object-oriented technique, and then semantic segmentation based on a deep convolutional neural network is used to extract building areas. With the change information and extracted buildings, a graph-cuts-based segmentation algorithm is applied to generate the bi-temporal changed building proposals. Next, in the bi-temporal changed building proposals, corner and edge information are integrated for feature detection through a phase congruency (PC) model, and the structural feature descriptor, called the histogram of orientated PC, is used to perform patch-based roof matching. We determined the final change in buildings by gathering matched roof and bi-temporal changed building proposals using co-refinement based on CRF, which were further classified as "newly built," "demolished", or "changed". Experiments were conducted with two typical datasets covering complex urban scenes with diverse building types. The results confirm the effectiveness and generality of the proposed algorithm, with more than 85% and 90% in overall accuracy and completeness, respectively.

Building Change Detection from Bi-Temporal Dense-Matching Point Clouds and Aerial Images.

In this work, a novel building change detection method from bi-temporal dense-matching point clouds and aerial images is proposed to address two major problems, namely, the robust acquisition of the changed objects above ground and the automatic classification of changed objects into buildings or non-buildings. For the acquisition of changed objects above ground, the change detection problem is converted into a binary classification, in which the changed area above ground is regarded as the foreground and the other area as the background. For the gridded points of each period, the graph cuts algorithm is adopted to classify the points into foreground and background, followed by the region-growing algorithm to form candidate changed building objects. A novel structural feature that was extracted from aerial images is constructed to classify the candidate changed building objects into buildings and non-buildings. The changed building objects are further classified as "newly built", "taller", "demolished", and "lower" by combining the classification and the digital surface models of two periods. Finally, three typical areas from a large dataset are used to validate the proposed method. Numerous experiments demonstrate the effectiveness of the proposed algorithm.

Construction of a camelid VHH yeast two-hybrid library and the selection of VHH against haemagglutinin-neuraminidase protein of the Newcastle disease virus.

BACKGROUND: Newcastle disease (ND), which is caused by the Newcastle disease virus (NDV), is one of the most important avian diseases in poultry. Since its discovery in 1926, ND has caused great economic losses to the world poultry industry and remains a threat to chickens and wild birds. Although a stringent vaccination policy is widely adopted to control ND, ND outbreaks still occur, and virulent NDV is sporadically isolated from chickens and wild birds. To study the pathogenesis of ND and provide tools to prevent its prevalence, novel antibody fragments should be developed. The variable domains of the heavy chain of the heavy-chain antibodies (VHH) are the smallest naturally occurring antibodies derived from camelid heavy-chain antibodies. The comparatively small size, high affinity, high solubility, low immunogenicity and ability to bind epitopes inaccessible to conventional antibodies of VHH make them ideal candidates for a considerable number of therapeutic and biotechnological applications. However, an anti-NDV VHH has not been reported to date. RESULTS: In this study, a VHH yeast two-hybrid library was constructed from NDV vaccine immunized C. bactrianus, and seven VHH fragments to the haemagglutinin-neuraminidase (HN) protein of NDV were successfully screened and characterized for the first time. These selected VHH clones were all expressed as soluble protein in E. coli. ELISA, dot blot, immunocytochemistry and pull down results showed that the screened VHHs could interact with NDV virion, among which five had neutralizing activity. In addition, the seven VHHs could inhibit the haemagglutination activity of different NDV strains. CONCLUSIONS: We constructed an NDV-immunized VHH yeast two-hybrid library and screened and characterized seven VHHs targeting NDV HN protein for the first time. The seven VHHs may have great potential for NDV diagnosis, pathogenesis and therapeutics.

Generalized modeling of spontaneous imbibition based on Hagen-Poiseuille flow in tortuous capillaries with variably shaped apertures.

Spontaneous imbibition of wetting liquids in porous media is a ubiquitous natural phenomenon which has received much attention in a wide variety of fields over several decades. Many traditional and recently presented capillary-driven flow models are derived based on Hagen-Poiseuille (H-P) flow in cylindrical capillaries. However, some limitations of these models have motivated modifications by taking into account different geometrical factors. In this work, a more generalized spontaneous imbibition model is developed by considering the different sizes and shapes of pores, the tortuosity of imbibition streamlines in random porous media, and the initial wetting-phase saturation. The interrelationships of accumulated imbibition weight, imbibition rate and gas recovery and the properties of the porous media, wetting liquids, and their interactions are derived analytically. A theoretical analysis and comparison denote that the presented equations can generalize several traditional and newly developed models from the literature. The proposed model was evaluated using previously published data for spontaneous imbibition measured in various natural and engineered materials including different rock types, fibrous materials, and silica glass. The test results show that the generalized model can be used to characterize the spontaneous imbibition behavior of many different porous media and that pore shape cannot always be assumed to be cylindrical.

High-precision image aided inertial navigation with known features: observability analysis and performance evaluation.

A high-precision image-aided inertial navigation system (INS) is proposed as an alternative to the carrier-phase-based differential Global Navigation Satellite Systems (CDGNSSs) when satellite-based navigation systems are unavailable. In this paper, the image/INS integrated algorithm is modeled by a tightly-coupled iterative extended Kalman filter (IEKF). Tightly-coupled integration ensures that the integrated system is reliable, even if few known feature points (i.e., less than three) are observed in the images. A new global observability analysis of this tightly-coupled integration is presented to guarantee that the system is observable under the necessary conditions. The analysis conclusions were verified by simulations and field tests. The field tests also indicate that high-precision position (centimeter-level) and attitude (half-degree-level)-integrated solutions can be achieved in a global reference.

Electroacupuncture at ST36 modulates the intestinal microecology and may help repair the intestinal barrier in the rat model of severe acute pancreatitis.

Severe acute pancreatitis (SAP) onset and development are closely associated with intestinal barrier injury. Evidence from clinical practice and research has shown that electroacupuncture (EA) at the Zusanli (ST36) acupoint can improve intestinal barrier function and abdominal symptoms in patients with SAP; however, the specific mechanisms of action remain unclear. This study aimed to observe the changes in the intestinal microbiota and metabolites in SAP rats and to explore the effect of EA at ST36 on intestinal barrier injury in SAP rats. 16S rRNA gene sequencing combined with microbial diversity analysis, short-chain fatty acids (SCFAs)-targeted metabolomics, immunohistochemistry, immunofluorescence, western blotting, and other techniques were used to explore the mechanism of EA at bilateral ST36 acupoints on SAP-related intestinal barrier injury. Our results showed that EA at ST36 could repair intestinal barrier injury by modulating intestinal microecology, thereby reducing intestinal inflammation, restoring intestinal function, and ultimately alleviating the prognosis of SAP. Our study provides new insights into the mechanisms and treatment of intestinal barrier injury in patients with SAP from the perspectives of microbiota and SCFAs regulation.

[Electroacupuncture for acute exacerbation of chronic obstructive pulmonary disease complicated with gastrointestinal dysfunction: a randomized controlled trial].

OBJECTIVE: To observe the clinical effect of electroacupuncture (EA) for acute exacerbation of chronic obstructive pulmonary disease (AECOPD) complicated with gastrointestinal dysfunction. METHODS: A total of 100 patients with AECOPD complicated with gastrointestinal dysfunction were randomly divided into an EA group (50 cases, 2 cases dropped off, 1 case excluded) and a medication group (50 cases). Both groups were treated with symptomatic and supportive treatment such as low flow oxygen, nebulized inhalation of short-acting ß2 agonist (SABA) or short-acting muscarinic antagonist (SAMA) combined with inhaled corticosteroid (ICS). The EA group was treated with EA at Zusanli (ST 36), Yinlingquan (SP 9), Zhongwan (CV 12), Shuifen (CV 9), Tianshu (ST 25), Chize (LU 5) and Lieque (LU 7), with discontinuous wave, 2 Hz in frequency, 30 min each time, once a day. In the medication group, oral mosapride citrate tablets were given, 3 times a day, 5 mg each time. Both groups were treated for 5 d. Before and after treatment, the gastrointestinal symptom rating scale (GSRS) score was observe, serum procalcitonin (PCT), C-reactive protein (CRP), and plasma oxygenation index (PaO2/FiO2) were detected, and patient satisfaction degree was evaluated in the two groups. RESULTS: Compared with before treatment, except for diarrhea dimension in the medication group, the total scores and each dimension scores of GSRS were decreased (P<0.05), serum PCT and CRP were decreased (P<0.05), plasma PaO2/FiO2 was increased (P<0.05) in the two groups after treatment. After treatment, in the EA group, the total score and abdominal pain, dyspepsia, constipation and diarrhea scores of GSRS were lower than those in the medication group (P<0.05), meanwhile serum PCT and CRP were lower and plasma PaO2/FiO2 was higher than those in the medication group (P<0.05). The improvement of gastrointestinal symptoms, life quality and overall satisfaction degree in the EA group were superior to those in the medication group (P<0.05). CONCLUSION: EA could improve the symptoms of patients with AECOPD complicated with gastrointestinal dysfunction, reduce inflammatory response, improve oxygenation and patient satisfaction degree.

Analysis of the driving role and impact of road construction on carbon stock.

Road construction will have a large impact on the ecosystem in the road area, and carbon stock, as an important indicator to measure the scale and quantity of primary productivity of the ecosystem, will also change, but the specific pattern is not clear. It is important to study the impact of road construction on carbon stock for regional ecosystem protection and sustainable economic and social development. Based on the InVEST model, this paper quantifies the spatial and temporal changes of carbon stocks in Jinhua, Zhejiang Province, from 2002 to 2017, using remote sensing image classification data land cover types as model driving data, geodetector, trend analysis, and buffer zone analysis methods, explores the driving effect of road construction on carbon stocks, and analyzes the spatial and temporal impacts of road construction on carbon stocks within the buffer zone. Results indicate that the total carbon stock in the Jinhua area showed a decreasing trend during the 16 years, decreasing by about 8.58 × 106 t. The spatial changes in the areas with higher carbon stocks were not significant. The explanatory power of road network density on carbon stock reaches 37%, and the anisotropic effect of road construction on carbon stock is strong and had a significant driving effect on carbon storage reduction. The new highway construction will accelerate the rate of carbon stock decline in the buffer zone, and the spatial situation is generally "the farther away from the highway, the higher the carbon stock."

Automatic Detection of Small Sample Apple Surface Defects Using ASDINet.

The appearance quality of apples directly affects their price. To realize apple grading automatically, it is necessary to find an effective method for detecting apple surface defects. Aiming at the problem of a low recognition rate in apple surface defect detection under small sample conditions, we designed an apple surface defect detection network (ASDINet) suitable for small sample learning. The self-developed apple sorting system collected RGB images of 50 apple samples for model verification, including non-defective and defective apples (rot, disease, lacerations, and mechanical damage). First, a segmentation network (AU-Net) with a stronger ability to capture small details was designed, and a Dep-conv module that could expand the feature capacity of the receptive field was inserted in its down-sampling path. Among them, the number of convolutional layers in the single-layer convolutional module was positively correlated with the network depth. Next, to achieve real-time segmentation, we replaced the flooding of feature maps with mask output in the 13th layer of the network. Finally, we designed a global decision module (GDM) with global properties, which inserted the global spatial domain attention mechanism (GSAM) and performed fast prediction on abnormal images through the input of masks. In the comparison experiment with state-of-the-art models, our network achieved an AP of 98.8%, and a 97.75% F1-score, which were higher than those of most of the state-of-the-art networks; the detection speed reached 39ms per frame, achieving accuracy-easy deployment and substantial trade-offs that are in line with actual production needs. In the data sensitivity experiment, the ASDINet achieved results that met the production needs under the training of 42 defective pictures. In addition, we also discussed the effect of the ASDINet in actual production, and the test results showed that our proposed network demonstrated excellent performance consistent with the theory in actual production.

Asymmetric Weighted Logistic Metric Learning for Hyperspectral Target Detection.

Traditional target detection methods assume that the background spectrum is subject to the Gaussian distribution, which may only perform well under certain conditions. In addition, traditional target detection methods suffer from the problem of the unbalanced number of target and background samples. To solve these problems, this study presents a novel target detection method based on asymmetric weighted logistic metric learning (AWLML). We first construct a logistic metric-learning approach as an objective function with a positive semidefinite constraint to learn the metric matrix from a set of labeled samples. Then, an asymmetric weighted strategy is provided to emphasize the unbalance between the number of target and background samples. Finally, an accelerated proximal gradient method is applied to identify the global minimum value. Extensive experiments on three challenging hyperspectral datasets demonstrate that the proposed AWLML algorithm improves the state-of-the-art target detection performance.

Construction and Evaluation of a Nomogram to Predict Gallstone Disease Based on Body Composition.

Purpose: We aimed to analyze the body composition characteristics of gallstone disease (GD) patients with bioelectrical impedance analysis (BIA) and to construct a nomogram to predict GD based on body composition. Methods: Patients with or without symptomatic cholecystolithiasis or choledocholithiasis diagnosed in Inner Mongolia People's Hospital from July 2020 to December 2021 were selected as the case group, and healthy subjects during the same period were selected as the control group. The body composition of the two groups was determined by BIA. The risk predictors for GD were extracted to construct a nomogram based on regression analysis. ROC curves were used to evaluate the predictive power of the nomogram, and calibration curves were drawn to evaluate the consistency of the model. The bootstrap method was used to verify the model and evaluate the generalizability of the model. Results: A total of 1000 individuals were recruited for the study, including 500 GD cases and 500 controls, to evaluate body composition. Multivariate logistic regression analysis showed that sex (OR = 2.292, 95% CI: 1.436-3.660), BMI (OR = 1.828, 95% CI: 1.738-1.929), body fat percentage (BFP) (OR = 1.904, 95% CI: 1.811-2.205) and waist circumference (WC) (OR = 1.934, 95% CI: 1.899-1.972) were risk predictors of GD. The AUC was 0.770 (95% CI: 0.741-0.799). The calibration curve showed that the C-index was 0.767. The prediction model was validated internally with 1000 bootstrap resamples. The accurate value was 0.72, and the kappa value was 0.43. All of the indices indicated that the model was well constructed and could be used to predict the incidence of GD. Conclusion: A nomogram model of gallstone disease based on sex, BMI, BFP and WC was constructed with good discrimination, calibration and generalizability and can be used for the noninvasive and convenient prediction of gallstone disease in the general population.

Transcutaneous electrical acupoint stimulation combined with electroacupuncture promotes rapid recovery after abdominal surgery: Study protocol for a randomized controlled trial.

Introduction: The most frequent complications after abdominal surgery include a decrease or loss of appetite, abdominal distension, abdominal pain caused by reduced gastrointestinal motility, anal arrest with intestinal distension and defecation, and nausea and vomiting due to anesthetic and opioid analgesic administration. These complications severely affect postoperative recovery, prolong hospital stay, and increase the financial burden. The objective of this study is to investigate the efficacy and safety of three acupoint stimulation modalities (electroacupuncture [EA], transcutaneous electrical acupoint stimulation [TEAS], and transcutaneous acupoint electrical stimulation combined with EA [TEAS+EA]), and two EA instrument waveforms (continuous wave and dilatational wave) for rapid recovery after abdominal surgery. Methods and analysis: A total of 560 patients will be recruited and randomly allocated to receive one of the following seven interventions: continuous wave EA, continuous wave TEAS, continuous wave TEAS + EA, dilatational wave EA, dilatational wave TEAS, dilatational wave TEAS + EA, and a control. For this study, continuous waves at 2 Hz, and dilatational waves at 2/50 Hz would be selected. The points to be stimulated by EA are the bilateral Neiguan (PC6), Hegu (LI6), Zusanli (ST36), Shangjuxu (ST37), and Xiajuxu (ST39), and TEAS would stimulate the bilateral Liangmen (ST21) and Daheng (SP15). The control group will neither receive EA nor TEAS. All patients will undergo an enhanced recovery plan after surgery and be provided with standardized perioperative management. Treatment will start on the first postoperative day and be administered once daily in the morning until the patient regains spontaneous bowel movements and can tolerate oral intake of solid food. The primary outcome is a composite of time to first defecation and time to tolerance of a solid diet. Secondary outcomes include time to first exhaustion; time of first defecation; time of tolerance of a solid diet; time to the first ambulation; length of hospital stay from surgery to discharge; visual analog scale score for postoperative daily pain, nausea, and vomiting; incidence of postoperative complications; and treatment acceptability. Discussion: This study will compare the efficacy and safety of three acupoint stimulation methods and two EA instrument waveforms for rapid recovery after abdominal surgery. Trial Registration: Chinese Clinical Trial Registry (http://www.chictr.org.cn), ChiCTR2100043883.

Inversion of high-amplitude magnetic total field anomaly: an application to the Mengku iron-ore deposit, northwest China.

In magnetic prospecting, the total field anomaly formula that represents the projection of the magnetic anomaly vector on the geomagnetic field is widely used because it simplifies the calculation of forward modelling and inversion of magnetic data. However, the projection anomaly yields errors relative to the true observed magnetic anomaly, especially for high-amplitude magnetic anomalies such as in iron orebody and unexploded ordnance prospecting. In this study, we analyse the difference between the projection anomaly and observed modulus difference anomaly with physical parameters, and propose to directly invert for the modulus difference anomaly by constructing a nonlinear matrix equation between the model corrections and data corrections. The inversion is then implemented using a preconditioned conjugate gradient algorithm. Synthetic and field magnetic data were used to test the inversion method. Comparison of the two types of total field anomalies shows that the error of the projection anomaly increased with increasing total-field magnetic anomaly. When the total-field magnetic anomaly was < 5,000 nT, the difference between the projection anomaly and modulus difference anomaly results can be ignored. For high-amplitude magnetic anomalies, the modulus difference anomaly inversion produced more accurate representations of both the shape and location of the magnetic sources.

Complex Inversion of MRT Signals under Different Loop Configurations for Groundwater Exploration.

Surface nuclear magnetic resonance (SNMR) is a relatively new geophysical method for non-invasive groundwater exploration and aquifer characterization. Conventional SNMR surveys based on one-dimensional (1-D) inversion of amplitude data recorded only using coincident loops provide limited or distorted groundwater distribution information, especially in regions with strong lateral heterogeneity and complicated hydrological environments. The simplistic approach limits the applicability and efficiency of SNMR, which was therefore made more effective in this study using a sophisticated signal response formulation. The elliptical polarization parameters of the excitation magnetic fields and 2-D sensitivity kernels (including real and imaginary parts) of three commonly used loop configurations were first calculated. After all the individual complex signals of five simulated measurement series along a profile were incorporated. The 2-D magnetic resonance tomography (MRT) complex inversion scheme was then used to perform high resolution tomography of synthetic models under the three loop configurations, taking full advantage of the different sensitivity distributions offered by the different loop configurations and the high sensitivity of the imaginary parts of signals to deep structures. Contrast analyses of the tomographic results showed that the complex inversions significantly decreased model ambiguities and increased depth resolution even with artificial noise added. Coincident loop measurements usually gave the best vertical resolution, and separated loops provided better lateral resolution. However, various factors would influence phase data, meaning that the complex inversion of field data is neither very reliable nor very common at present.