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Background: Surgical procedures for proximal gastric cancer remain a highly debated topic. Total gastrectomy (TG) is widely accepted as a standard radical surgery. However, subtotal esophagectomy, proximal gastrectomy (PG) or even subtotal gastrectomy, when a small upper portion of the stomach can technically be preserved, are alternatives in current clinical practice. Methods: Using a cohort of the PGSAS NEXT trial, consisting of 1909 patients responding to a questionnaire sent to 70 institutions between July 2018 and December 2019, gastrectomy type, reconstruction method, and furthermore the remnant stomach size and the anti-reflux procedures for PG were evaluated. Results: TG was the procedure most commonly performed (63.0%), followed by PG (33.4%). Roux-en-Y was preferentially employed following TG irrespective of esophageal tumor invasion, while jejunal pouch was adopted in 8.5% of cases with an abdominal esophageal stump. Esophagogastrostomy was most commonly selected after PG, followed by the double-tract method. The former was preferentially employed for larger remnant stomachs (≧3/4), while being used slightly less often for tumors with as compared to those without esophageal invasion in cases with a remnant stomach 2/3 the size of the original stomach. Application of the double-tract method gradually increased as the remnant stomach size decreased. Anti-reflux procedures following esophagogastrostomy varied markedly. Conclusions: TG is the mainstream and PG remains an alternative in current Japanese clinical practice for proximal gastric cancer. Remnant stomach size and esophageal stump location appear to influence the choice of reconstruction method following PG.

As global warming intensifies, the damage caused by drought cannot be disregarded. Traditional drought monitoring is often carried out with monthly resolution, which fails to monitor the sub-monthly climatic event. The GRACE-based drought severity index (DSI) is a drought index based on terrestrial water storage anomalies (TWSA) observed by the gravity recovery and climate experiment (GRACE) satellite. DSI has the ability to monitor drought effectively, and it is in good consistency with other drought monitoring methods. However, the temporal resolution of DSI is limited by that of GRACE observations, so it is necessary to obtain TWSA with a higher temporal resolution to calculate DSI. We use a statistical method to reconstruct the TWSA, which adopts precipitation and temperature to obtain TWSA on a daily resolution. This statistical method needs to be combined with the time series decomposition method, and then the parameters are simulated by the Markov chain Monte Carlo (MCMC) procedure. In this study, we use this TWSA reconstruction method to obtain high-quality TWSA at daily time resolution. The correlation coefficient between CSR–TWSA and the reconstructed TWSA is 0.97, the Nash–Sutcliffe efficiency is 0.93, and the root mean square error is 16.57. The quality of the reconstructed daily TWSA is evaluated, and the DSI on a daily resolution is calculated to analyze the drought phenomenon in the Pearl River basin (PRB). The results show that the TWSA reconstructed by this method has high consistency with other daily publicly available TWSA products and TWSA provided by the Center for Space Research (CSR), which proves the feasibility of this method. The correlation between DSI based on reconstructed daily TWSA, SPI, and SPEI is greater than 0.65, which is feasible for drought monitoring. From 2003 to 2021, the DSI recorded six drought events in the PRB, and the recorded drought is more consistent with SPI-6 and SPEI-6. There was a drought event from 27 May 2011 to 12 October 2011, and this drought event had the lowest DSI minimum (minimum DSI = −1.76) recorded among the six drought events. The drought monitored by the DSI is in line with government announcements. This study provides a method to analyze drought events at a higher temporal resolution, and this method is also applicable in other areas. [ABSTRACT FROM AUTHOR]

Surgical procedures for proximal gastric cancer remain a highly debated topic. Total gastrectomy (TG) is widely accepted as a standard radical surgery. However, subtotal esophagectomy, proximal gastrectomy (PG) or even subtotal gastrectomy, when a small upper portion of the stomach can technically be preserved, are alternatives in current clinical practice. Using a cohort of the PGSAS NEXT trial, consisting of 1909 patients responding to a questionnaire sent to 70 institutions between July 2018 and December 2019, gastrectomy type, reconstruction method, and furthermore the remnant stomach size and the anti-reflux procedures for PG were evaluated. TG was the procedure most commonly performed (63.0%), followed by PG (33.4%). Roux-en-Y was preferentially employed following TG irrespective of esophageal tumor invasion, while jejunal pouch was adopted in 8.5% of cases with an abdominal esophageal stump. Esophagogastrostomy was most commonly selected after PG, followed by the double-tract method. The former was preferentially employed for larger remnant stomachs (≧3/4), while being used slightly less often for tumors with as compared to those without esophageal invasion in cases with a remnant stomach 2/3 the size of the original stomach. Application of the double-tract method gradually increased as the remnant stomach size decreased. Anti-reflux procedures following esophagogastrostomy varied markedly. TG is the mainstream and PG remains an alternative in current Japanese clinical practice for proximal gastric cancer. Remnant stomach size and esophageal stump location appear to influence the choice of reconstruction method following PG. [ABSTRACT FROM AUTHOR]

Catalyst utilization is an important determinant of proton exchange membrane fuel cell performance, and increasing the catalyst utilization is one of the most critical approaches to reducing the catalyst loading in PEMFC. 4-phase stochastic reconstruction method based on the variable-resolution Quartet Structure Generation Set (QSGS) algorithm is utilized to elucidate the influence of different parameters of electrode preparation, including the porosity, the dispersion degree of carbon agglomerate, ionomer content, and carbon support size, on the catalyst utilization in the catalyst layer. It was found that there exist optimal values for the porosity, dispersion degree of carbon agglomerate, ionomer content, and carbon support sizes in CLs and any deviations from these optimal values would lead to transport issues of electron, proton and mass within CLs. Taking electron, proton and mass transport into consideration simultaneously, the optimal Pt utilization is 46.55% among 48 cases in this investigation, taken at the carbon support diameter of 40 nm, the porosity of 0.4, the agglomerate spatial density of 25 μm−3 and I/C at 0.7. The selection of porosity, ultrasonic dispersion technique and ionomer content for conventional electrode preparation requires compromises on mass, electron and proton transport, leading to catalyst utilization in CLs hardly exceeding 50%. Therefore, the next generation of catalyst layer design and preparation technology is desired.

Introduction: This paper proposes a five-layer fully connected neural network for predicting radiation parameters in a radiation space based on detector readings.Methods: The network is trained and tested using gamma flux values from individual detector positions as input, and is used to predict the gamma radiation field in 3D space under different source term distributions. The method is evaluated using the mean percentage change error (PCT) for the test set under different source term distributions.Results: The results show that the neural network method can accurately predict radiation parameters with an average PCT error range of 0.53% to 3.11%, within the given measurement input error range of ± 10%. The method also demonstrates its ability to directly reconstruct the 3D radiation field with some simple source terms.Discussion: The proposed method has practical value in real operations within radiation spaces, and can be used to improve the accuracy and efficiency of predicting radiation parameters. Further research could explore the use of more complex source term distributions and the integration of other types of sensors for improved accuracy.

• A novel model combining variate-centric Transformer with large kernel temporal convolution was proposed. • Variate-centric Transformer was proposed to make self-attention acts on variables. • Large kernel temporal convolution was used to learn causal temporal information. • Experiments of microreactor process were conducted, which made algorithms be tested in real-world data. Fault detection and diagnosis (FDD) is an essential tool to ensure safety in chemical industries, and nowadays, many reconstruction-based deep learning methods are active in fault detection. However, many algorithms still suffer from not ideal actual performance. Inspired by the core mechanism of Transformer and large kernel convolution, this paper proposes a novel model combining variate-centric Transformer with large kernel temporal convolution. Variate-centric Transformer depends on self-attention to capture the multivariate correlations of input data, and large kernel temporal convolution collects period information to summarize temporal features. A benchmark dataset Tennessee Eastman process (TEP) and experiment data from the microreactor process are used to test the performance of fault detection. Compared with other reconstruction-based methods, results demonstrate that our model achieves a higher fault detection rate and a lower detection latency, and shows a significant potential for process safety. [ABSTRACT FROM AUTHOR]

As global warming intensifies, the damage caused by drought cannot be disregarded. Traditional drought monitoring is often carried out with monthly resolution, which fails to monitor the sub-monthly climatic event. The GRACE-based drought severity index (DSI) is a drought index based on terrestrial water storage anomalies (TWSA) observed by the gravity recovery and climate experiment (GRACE) satellite. DSI has the ability to monitor drought effectively, and it is in good consistency with other drought monitoring methods. However, the temporal resolution of DSI is limited by that of GRACE observations, so it is necessary to obtain TWSA with a higher temporal resolution to calculate DSI. We use a statistical method to reconstruct the TWSA, which adopts precipitation and temperature to obtain TWSA on a daily resolution. This statistical method needs to be combined with the time series decomposition method, and then the parameters are simulated by the Markov chain Monte Carlo (MCMC) procedure. In this study, we use this TWSA reconstruction method to obtain high-quality TWSA at daily time resolution. The correlation coefficient between CSR–TWSA and the reconstructed TWSA is 0.97, the Nash–Sutcliffe efficiency is 0.93, and the root mean square error is 16.57. The quality of the reconstructed daily TWSA is evaluated, and the DSI on a daily resolution is calculated to analyze the drought phenomenon in the Pearl River basin (PRB). The results show that the TWSA reconstructed by this method has high consistency with other daily publicly available TWSA products and TWSA provided by the Center for Space Research (CSR), which proves the feasibility of this method. The correlation between DSI based on reconstructed daily TWSA, SPI, and SPEI is greater than 0.65, which is feasible for drought monitoring. From 2003 to 2021, the DSI recorded six drought events in the PRB, and the recorded drought is more consistent with SPI-6 and SPEI-6. There was a drought event from 27 May 2011 to 12 October 2011, and this drought event had the lowest DSI minimum (minimum DSI = −1.76) recorded among the six drought events. The drought monitored by the DSI is in line with government announcements. This study provides a method to analyze drought events at a higher temporal resolution, and this method is also applicable in other areas.

The brightness temperature reconstruction of synthetic aperture interferometric radiometers (SAIRs) is an underdetermined and ill-posed inverse problem. The classical Hilbert-space regularization methods have often the disadvantages of the oversmoothness effects and the oscillations. In this article, an adaptive Lp reconstruction method in Lebesgue spaces is introduced to obtain the accurate brightness temperature map in SAIRs. The proposed approach can adaptively adjust the exponent p between 1.2 and 2 according to the region of the map to be reconstructed. The experimental results show that the Lp reconstruction method can effectively reduce oversmoothness and Gibbs oscillations, and better improve the accuracy of the inverse results, compared to the traditional minimum-norm and band-limited regularization methods.

This paper presents the application of the edge reversal method for a further accurate evaluation of the three-dimensional tool geometry of a single-point diamond tool with an atomic force microscope (AFM). In the edge reversal method, the tip radius of an AFM probe, which ranges from a few nm to several-ten nm, can be evaluated quantitatively by using measured AFM profile data of a tool cutting edge and an indentation mark generated by the tool cutting edge. The AFM tip radius obtained by the edge reversal method is utilized in this paper to reconstruct the three-dimensional profile of the cutting edge of a single-point diamond tool from the AFM data, which is obtained in measurement as the convolution of the tool edge profile and the shape of AFM tool tip. The validity of the obtained AFM tip radius in the edge reversal method is verified by employing it for the compensation of the AFM image of a two-dimensional (2D) grating artifact. Finally, the reconstruction of the three-dimensional profile of the cutting edge of a single-point diamond tool is carried out, and the cutting edge radius and the nose radius of the tool are evaluated quantitatively based on the reconstructed three-dimensional (3D) profile of the cutting tool. [ABSTRACT FROM AUTHOR]

Abstract Proximal gastrectomy (PG) is one of the function‐preserving surgical methods for the treatment of upper gastric cancer. Favorable postoperative results have been reported in comparison with total gastrectomy. However, because there are challenges, such as postoperative reflux esophagitis, anastomotic stenosis, and residual food, appropriate selection of a reconstruction method is crucial. Some methods include esophagogastric anastomosis, including simple esophagogastrostomy, tube‐like stomach esophagogastrostomy, side overlap with fundoplication by Yamashita, and double‐flap technique, and reconstruction using the small intestine, including double‐tract methods, jejunal interposition, and jejunal pouch interposition. However, standard reconstruction methods are yet to be established. PG has also been employed in early gastric cancer of the upper third of the stomach, and indications have also been extended to esophagogastric junction cancer, which has shown an increase in recent years. Although many retrospective studies have revealed the functional benefits or oncological safety of PG, the characteristics of each surgical procedure should be understood so that an appropriate reconstruction method, with a reflux prevention mechanism and minimal postoperative injury, can be selected.

As a mesoscale phenomenon of the ocean, the ocean front can directly affect the structural characteristics of sound speed profiles and further affect the acoustic propagation characteristics of the sea area. In this paper, we use the fuzzy C-means (FCM) algorithm to cluster the surface sound speed in the sea area of the Kuroshio Extension (KE) and detect the frontal zone of Kuroshio Extension (KEF). At the same time, the sound speed profile (SSP) is used instead of the temperature profile to establish the model of the sound speed field in the front area of the Kuroshio Extension and to improve the theoretical model of the ocean front. Compared with the actual ocean front calculated by reanalysis data, the root means square error (RSME) of the transmission loss (TL) calculated by the model is controlled below 6 dB, which proves the validity of the model. Finally, we propose the melt function in the model to forecast the depth change of the acoustic convergence area. Compared with the actual calculation result based on reanalysis data, the root means square error (RSME) of the depth forecasting after the frontal zone is 43.3 m. This reconstruction method does not rely on the high spatial resolution data of the whole sea depth and can be of referential significance to acoustic detection in the ocean front environment. [ABSTRACT FROM AUTHOR]

We identify two issues with the reverse regression approach as implemented in several classic reconstructions of past climate fluctuations from dendroclimatologcical data series. First, instead of estimating the causal relationship between the proxy, which is measured with significant error, as function of climate and formally inverting the relationship, most papers estimate the inverted relationship directly. This leads to biased coefficients and reconstructions with artificially low variance. Second, we show that inversion of the relationship is often done incorrectly when the underlying causal relationship is dynamic in nature. We show analytically as well as using Monte Carlo experiments and actual tree ring data, that the reverse regression method results in biased coefficients, reconstructions with artificially low variance and overly smooth reconstructions. We further demonstrate that correct application of the inverse regression method is preferred. However, if the measurement error in the tree ring index is significant, neither method provides reliable reconstructions.

Fatigue cracking in welded joints is a critical problem in bridge engineering, especially for aging long-span steel bridges. The crack size and density are increasing gradually with the bridge aging process, where the crack interaction will accelerate the crack propagation or even short cracks merging into a long crack. However, the mechanism underlying the coupled propagation behavior of multiple cracks remains unclear. In this study, the coupling effect of multiple cracks was investigated based on numerical simulations. Subsequently, the numerical result was verified by a full-scale segmental fatigue experiment. In order to overcome the time-consuming iterative computations, the back propagation (BP) neural network was utilized to predict the effective coupling spacing between multiple cracks. Finally, a new crack reconstruction method was proposed to simplify crack merging processes. Results indicate that the coupled propagation behavior is significantly impacted by the effective crack spacing. The coupling effect is more significant at the near-end point compared to other feature points. In addition, the cracks with similar sizes have greater coupled effect, which is the worst-case scenario for the multiple fatigue crack problem. The experimental study demonstrates that the growth rate of the near-end point is 1.53 times that of the far-end point and pre-made cracks merge together successfully. By utilizing the BP neural network, the relative error of predicted effective spacing of two cracks is 3.52%. Compared to existing design specifications, the new reconstruction method provides a more reliable result for the fatigue life prediction of the welding seam with multiple fatigue cracks. • Sensitive parameters for multiple crack coupling effects were investigated. • The coupling effect has a significant effect on the near-end point of the crack. • The coupling effect and effective spacing increase with crack shape ratio and size. • A crack reconstruction method is proposed based on the BP neural network. [ABSTRACT FROM AUTHOR]

Among many parameters characterizing atmospheric aerosols, aerosol mass extinction efficiency (MEE) is important for understanding the optical properties of aerosols. MEE is expressed as a function of the refractive indices (i.e., composition) and size distributions of aerosol particles. Aerosol MEE is often considered as a size-independent constant that depends only on the chemical composition of aerosol particles. The famous Malm's reconstruction equation and subsequent revised methods express the extinction coefficient as a function of aerosol mass concentration and MEE. However, the used constant MEE does not take into account the effect of the size distribution of polydispersed chemical composition. Thus, a simplified expression of size-dependent MEE is required for accurate and conventional calculations of the aerosol extinction coefficient and also other optical properties. In this study, a simple parameterization of MEE of polydispersed aerosol particles was developed. The geometric volume–mean diameters of up to 10 µm with lognormal size distributions and varying geometric standard deviations were used to represent the sizes of various aerosol particles (i.e., ammonium sulfate and nitrate, elemental carbon, and sea salt). Integrating representations of separate small mode and large mode particles using a harmonic mean-type approximation generated the flexible and convenient parameterizations of MEE that can be readily used to process in situ observations and adopted in large-scale numerical models. The calculated MEE and the simple forcing efficiency using the method developed in this study showed high correlations with those calculated using the Mie theory without losing accuracy. [ABSTRACT FROM AUTHOR]

Driven by sintering kinetics, stochastically distributed voids exist inevitably in nano‑silver sintered joints to affect their electrical, mechanical and thermal properties, reliability, etc. In this paper, a holistic approach including both void morphology characterization and reconstruction stages is developed for the reconstruction of Stochastically Distributed Void Morphologies (SDVMs) in nano‑silver sintered joints. A set of dispersion parameters, including area A, distance l, angle α, and aspect ratio δ, are firstly proposed for quantitatively characterizing the voids dispersion features of the SDVMs. Then on the basis of the characterization results, a reconstruction approach is developed based on the random medium theory and similarity comparison algorithm. The applicability and validity of the proposed voids dispersion characterization and SDVM reconstruction methods are verified through numerical and experimental case studies, respectively. And effects on the dispersion features of the SDVMs by such as autocorrelation function parameters and the sintering pressure are also investigated via the comparative discussions on the cumulative distribution function (cdf) curves of all dispersion parameters.

Proximal gastrectomy (PG) is one of the function‐preserving surgical methods for the treatment of upper gastric cancer. Favorable postoperative results have been reported in comparison with total gastrectomy. However, because there are challenges, such as postoperative reflux esophagitis, anastomotic stenosis, and residual food, appropriate selection of a reconstruction method is crucial. Some methods include esophagogastric anastomosis, including simple esophagogastrostomy, tube‐like stomach esophagogastrostomy, side overlap with fundoplication by Yamashita, and double‐flap technique, and reconstruction using the small intestine, including double‐tract methods, jejunal interposition, and jejunal pouch interposition. However, standard reconstruction methods are yet to be established. PG has also been employed in early gastric cancer of the upper third of the stomach, and indications have also been extended to esophagogastric junction cancer, which has shown an increase in recent years. Although many retrospective studies have revealed the functional benefits or oncological safety of PG, the characteristics of each surgical procedure should be understood so that an appropriate reconstruction method, with a reflux prevention mechanism and minimal postoperative injury, can be selected. [ABSTRACT FROM AUTHOR]

In this study, a tomography reconstruction problem of binary images is considered on the isometric grid. On this grid, the triangle pixels have two types of orientations, accordingly, the authors call them delta or nabla shape pixels. The proposed reconstruction method uses data of projections of three natural directions. They are the lane directions of the triangular tessellation (these directions are somewhat analogous to row/column directions on the rectangular grids). The projection ray, penetrating through a grid lane, now not passing through the middle of pixels (i.e. through the middle line of triangle shape pixels), as usually taken, but little bit shifted from the middle parallel to the lane. This method provides the exact information about the number of nabla and delta shape triangle pixels in each lane of the image. This additional information is included in the reconstruction process to improve the quality of reconstruction. They formulate the suggested model into an energy‐minimisation problem and apply a gradient‐based approach for its minimisation. They show and analyse various experimental results on test images. The presented approach shows both better quality reconstructions and shorter running time than the earlier approaches. [ABSTRACT FROM AUTHOR]

As a mesoscale phenomenon of the ocean, the ocean front can directly affect the structural characteristics of sound speed profiles and further affect the acoustic propagation characteristics of the sea area. In this paper, we use the fuzzy C-means (FCM) algorithm to cluster the surface sound speed in the sea area of the Kuroshio Extension (KE) and detect the frontal zone of Kuroshio Extension (KEF). At the same time, the sound speed profile (SSP) is used instead of the temperature profile to establish the model of the sound speed field in the front area of the Kuroshio Extension and to improve the theoretical model of the ocean front. Compared with the actual ocean front calculated by reanalysis data, the root means square error (RSME) of the transmission loss (TL) calculated by the model is controlled below 6 dB, which proves the validity of the model. Finally, we propose the melt function in the model to forecast the depth change of the acoustic convergence area. Compared with the actual calculation result based on reanalysis data, the root means square error (RSME) of the depth forecasting after the frontal zone is 43.3 m. This reconstruction method does not rely on the high spatial resolution data of the whole sea depth and can be of referential significance to acoustic detection in the ocean front environment.

Polyamide 6 (PA6) is able to absorb water from the surrounding air and bond to it by forming hydrogen bonds between the carbonamide groups of its molecular chains. Diffusion processes cause locally different water concentrations in the (component) cross-section during the sorption process, resulting in locally different mechanical properties due to the water-induced plasticisation effect. However, the water content of PA6 is usually specified as an integral value, so no information about a local water distribution within a component is provided. This paper shows a method to characterise moisture distributions within PA6 samples using low-energy computer tomography (CT) techniques and comparing the reconstructed results with a developed finite elements (FE) modelling method based on Fick’s diffusion laws with concentration-dependent diffusion coefficients. For this purpose, the ageing of the samples at two different water bath temperatures as well as at different integral water contents are considered. The results obtained by CT reconstruction and FE modelling are in very good agreement, so that the concentration distributions by water sorption of PA6 calculated by FEM can be regarded as validated.

Ultrasound computed tomography (USCT) systems based on capacitive micromachined ultrasonic transducer (CMUT) arrays have a wide range of application prospects. For this paper, a high-precision image reconstruction method based on the propagation path of ultrasound in breast tissue are designed for the CMUT ring array; that is, time-reversal algorithms and FBP algorithms are respectively used to reconstruct sound speed distribution and acoustic attenuation distribution. The feasibility of this reconstruction method is verified by numerical simulation and breast model experiments. According to reconstruction results, sound speed distribution reconstruction deviation can be reduced by 53.15% through a time-reversal algorithm based on wave propagation theory. The attenuation coefficient distribution reconstruction deviation can be reduced by 61.53% through FBP based on ray propagation theory. The research results in this paper will provide key technological support for a new generation of ultrasound computed tomography systems.

This paper presents a systematic structure and a control strategy for the electric vehicle charging station. The system uses a three-phase three-level neutral point clamped (NPC) rectifier to drive multiple three-phase three-level NPC converters to provide electric energy for electric vehicles. This topology can realize the single-phase AC mode, three-phase AC mode, and DC mode by adding some switches to meet different charging requirements. In the case of multiple electric vehicles charging simultaneously, a system optimization control algorithm is adopted to minimize DC-bus current fluctuation by analyzing and reconstructing the DC-bus current in various charging modes. This algorithm uses the genetic algorithm (ga) as the core of computing and reduces the number of change parameter variables within a limited range. The DC-bus current fluctuation is still minimal. The charging station system structure and the proposed system-level optimization control algorithm can improve the DC-side current stability through model calculation and simulation verification.

Synthetic aperture imaging radiometers (SAIRs) are powerful passive microwave systems for high-resolution imaging by use of synthetic aperture technique. However, the ill-posed inverse problem for SAIRs makes it difficult to reconstruct the high-precision brightness temperature map. The traditional regularization methods add a unique penalty to all the frequency bands of the solution, which may cause the reconstructed result to be too smooth to retain certain features of the original brightness temperature map such as the edge information. In this paper, a multi-parameter regularization method is proposed to reconstruct SAIR brightness temperature distribution. Different from classical single-parameter regularization, the multi-parameter regularization adds multiple different penalties which can exhibit multi-scale characteristics of the original distribution. Multiple regularization parameters are selected by use of the simplified multi-dimensional generalized cross-validation method. The experimental results show that, compared with the conventional total variation, Tikhonov, and band-limited regularization methods, the multi-parameter regularization method can retain more detailed information and better improve the accuracy of the reconstructed brightness temperature distribution, and exhibit superior noise suppression, demonstrating the effectiveness and the robustness of the proposed method.

Among many parameters characterizing atmospheric aerosols, aerosol mass extinction efficiency (MEE) is important for understanding the optical properties of aerosols. MEE is expressed as a function of the refractive indices (i.e., composition) and size distributions of aerosol particles. Aerosol MEE is often considered as a size-independent constant that depends only on the chemical composition of aerosol particles. The famous Malm’s reconstruction equation and subsequent revised methods express the extinction coefficient as a function of aerosol mass concentration and MEE. However, the used constant MEE does not take into account the effect of the size distribution of polydispersed chemical composition. Thus, a simplified expression of size-dependent MEE is required for accurate and conventional calculations of the aerosol extinction coefficient and also other optical properties. In this study, a simple parameterization of MEE of polydispersed aerosol particles was developed. The geometric volume–mean diameters of up to 10 µm with lognormal size distributions and varying geometric standard deviations were used to represent the sizes of various aerosol particles (i.e., ammonium sulfate and nitrate, elemental carbon, and sea salt). Integrating representations of separate small mode and large mode particles using a harmonic mean-type approximation generated the flexible and convenient parameterizations of MEE that can be readily used to process in situ observations and adopted in large-scale numerical models. The calculated MEE and the simple forcing efficiency using the method developed in this study showed high correlations with those calculated using the Mie theory without losing accuracy.

Reconstruction methods for discrete data, such as the Moving Least Squares (MLS) and Moving Total Least Squares (MTLS), have made a great many achievements with the progress of modern industrial technology. Although the MLS and MTLS have good approximation accuracy, neither of these two approaches are robust model reconstruction methods and the outliers in the data cannot be processed effectively as the construction principle results in distorted local approximation. This paper proposes an improved method that is called the Moving Total Least Trimmed Squares (MTLTS) to achieve more accurate and robust estimations. By applying the Total Least Trimmed Squares (TLTS) method to the orthogonal construction way in the proposed MTLTS, the outliers as well as the random errors of all variables that exist in the measurement data can be effectively suppressed. The results of the numerical simulation and measurement experiment show that the proposed algorithm is superior to the MTLS and MLS method from the perspective of robustness and accuracy.

As an extension of the immersed boundary method with unified interpolation stencil (Kor, Badri Ghomizad, and Fukagata, J. Fluid Sci. Technol., Vol. 12, 2017, JFST0011), we propose an immersed boundary method that can handle moving boundary problems with a lower level of spurious force oscillation. The key modification to the previously proposed method, which was validated for fixed boundary problems, is to adopt the reconstruction method, in which the velocities outside the body are reconstructed, instead of the ghost-cell method, in which the velocities inside the body are set to satisfy the boundary conditions. From the comparison between the ghost-cell and reconstruction methods, both methods work equally well for a fixed boundary problem, but the reconstruction method is found to be effective in suppressing the spurious force oscillations that appear in moving boundary problems. The capability of the proposed method is demonstrated by numerical investigations of some typical problems. Both predefined motions, such an oscillating cylinder and a hovering flat plate, and interacting motions of rigid bodies are simulated to validate the method. For the latter, sedimentation of a single cylinder as well as a group of interacting cylinders under the gravitational force is examined to demonstrate the capability of the present method for fluid-structure interaction problems. The results show that the proposed method can properly handle the moving boundary problems, while preserving the simplicity of the unified interpolation stencil.

Electrical capacitance tomography exhibits great potentials in the visualization measurement of industrial processes, and high-precision images are of great significance for the reliability and usefulness of measurement results. In this paper, we propose a deep learning-based inversion method to ameliorate the reconstruction accuracy. With the aid of the deep learning methodology, the prior from the images reconstructed by a certain imaging technique to the true images is abstracted and stored in the deep extreme learning machine. A new cost function is constructed to encapsulate the prior from the proposed deep learning model and the domain expertise about imaging targets, and the split Bregman algorithm and the fast iterative shrinkage thresholding technique are combined into a new numerical method to effectively solve it to get the final reconstruction. The numerical and experimental results validate that the inversion method proposed in this paper reduces the reconstruction artifacts and deformations and leads to the much improvement in the imaging quality. [ABSTRACT FROM AUTHOR]

The gas temperature field measurement is crucial for the monitoring of the objects of interest. Owing to the distinct advantages, including non-invasive sensing, high safety, etc., the ultrasonic tomography (UT) method is considered to be a promising visualization measurement method, in which acquiring high-quality images is vital for real-world applications. In this paper, a new UT measurement system that integrates the Data Acquisition Card and a Single Chip Microcomputer is proposed for the temperature distribution measurement. A hardware system is designed to alleviate the inertia delay phenomenon. A reconstruction model that simultaneously emphasizes the inaccurate properties on the reconstruction model and the measurement data is proposed. By means of introducing the radial basis function method and the framework of the Tikhonov regularization technique, a two-stage reconstruction method is proposed to alleviate the ill-posed nature in the UT inverse problem. A new objective functional is proposed to convert the original reconstruction task into an optimization problem, and the simulated annealing algorithm is deployed to effectively solve the proposed objective functional. Experimental results validate the feasibility and effectiveness of the proposed reconstruction method. [ABSTRACT FROM AUTHOR]

Tailoring thermal expansion of structures is in urgent need in engineering applications where the structures are susceptible to suffer large temperature fluctuation. Here, a method to reconstruct 3D truss structures is developed to obtain large positive, zero and even negative coefficient of thermal expansion (CTE). As the basis, theoretical analysis and numerical verification of the bi-material pyramid and tetrahedron lattice cells explicitly reveal that with thick members, the influence of the cross section on the CTEs should be well considered, and the CTEs should be accurately calculated by the solid model. Furthermore, two kinds of 3D lattice structures with isotropic tailorable CTEs are originally devised. Moreover, bi-pyramid and bi-tetrahedron units are devised, and a reconstruction method, which can reconstruct an arbitrary 3D truss structures to obtain specific target CTE, is originally developed. Typical supporting structure and platform used in satellites are reconstructed by the proposed method, and near zero thermal expansion, which is urgent needed in satellite, can be flexibly obtained. The analysis and proposal of three dimensional lattice structures and reconstruction method provide a new approach to develop structures with light weight and tailorable CTEs. [ABSTRACT FROM AUTHOR]

Purpose: This study primarily aimed to investigate the short- and long-term remission rates of type 2 diabetes (T2D) in patients who underwent surgical treatment for gastric cancer, especially patients who were non-obese, and secondarily to determine the potential factors associated with remission. Materials and Methods: We retrospectively reviewed the clinical records of patients with T2D who underwent radical gastrectomy for gastric cancer, from January 2008 to December 2012. Results: T2D improved in 39 out of 70 (55.7%) patients at the postoperative 2-year follow-up and 21 of 42 (50.0%) at the 5-year follow-up. In the 2-year data analysis, preoperative body mass index (BMI) (P=0.043), glycated hemoglobin (A1C) level (P=0.039), number of anti-diabetic medications at baseline (P=0.040), reconstruction method (statistical difference was noted between Roux-en-Y reconstruction and Billroth I; P=0.035) were significantly related to the improvement in glycemic control. Unlike the results at 2 years, the 5-year data analysis revealed that only preoperative BMI (P=0.043) and A1C level (P=0.039) were statistically significant for the improvement in glycemic control; however, the reconstruction method was not. Conclusions: All types of gastric cancer surgery can be effective in short- and long-term T2D control in non-obese patients. In addition, unless long-limb bypass is considered in gastric cancer surgery, the long-term glycemic control is not expected to be different between the reconstruction methods. [ABSTRACT FROM AUTHOR]

In this paper, a reconstruction-based method is proposed to monitor nonlinear processes and isolate their fault types. The fault direction and enhanced statistics are introduced to improve the monitoring results and effectiveness of fault isolation. The main contributions are given as follows: 1) For fault detection, two statistics, which are decomposed according to the load directions, are defined in the complementary subspaces. 2) The fault direction is used to obtain the reconstruction model. 3) Based on the reconstruction model, the fault type can be isolated. An electro-fused magnesia furnace is introduced to test the proposed method, and the results of this test validate its effectiveness. [ABSTRACT FROM AUTHOR]