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As one of the knee preservation surgical approaches, good clinical outcomes of high tibial osteotomy were reported. Aims of this study were to analyze the clinical outcome and pre- and postoperative radiographical parameter and knee functional score between distal tibial tubercle high tibial osteotomy (DTTHTO) and open wedge- high tibial osteotomy (OWHTO) in patients with varus knee osteoarthritis after more than 1 year following-up. A total of 194 consecutive patients in our joint center from March 2016 to October 2021 were enrolled, according to the surgical method, patients were divided into DDTHTO and OWHTO groups. Radiographic parameters of Kellgren-Lawrence grading, hip-knee-ankle angle, weight bearing line ratio and medial tibial plateau angle, knee functional score of American knee society (AKS) score, western Ontario and McMaster universities arthritis index (WOMAC) score, visual analogue score (VAS) were introduced to evaluate clinical outcome for patients who received DDTHTO and OWHTO. There were 103 knees and 89 knees in the OWHTO and DTTHTO group, respectively. Mean weight bearing line ratio for OWHTO and DTTHTO were 25.1 ± 11.7 and 25.2 ± 12.0% respectively, medial tibial plateau angle and hip-knee-ankle angle angle demonstrated that all patients in the present study inherited a varus angle ranges from 3.4° to 9.5°. Preoperative AKS, WOMAC and VAS were 68.4 ± 5.7 versus 69.0 ± 5.9, 109.3 ± 15.0 versus 107.7 ± 14.0 and 6.8 ± 1.0 versus 6.9 ± 0.8, and there was no significant difference between 2 groups (P .05). Mean postoperative AKS and WOMAC score for patients in both OWHTO and DTTHTO group were significantly improved, moreover, postoperative VAS of DTTHTO patients was lower than that in OWHTO group (P .05). When comparing the operation time, intraoperative blood loss and bone union time, DHHTO group shows a superiority in these variables over patients in OWHTO (121 ± 29.6 vs 145.7 ± 35.2 minutes, 115.0 ± 20.8 vs 103.3 ± 17.3 mL, 13.7 ± 4.1 vs 12.0 ± 2.8 weeks; P .005) and incidence of complication was lower for DTTHTO group. DTTHTO in patients with varus knee osteoarthritis has good clinical outcomes, and it can achieve a better postoperative alignment. Operation time and surgical trauma were also less in patients who underwent DTTHTO.

SignificanceDespite the ample progress made towards faster and more accurate Monte Carlo (MC) simulation tools over the past decade, the limited usability and accessibility of these advanced modeling tools remain key barriers towards widespread use among the broad user community.AimAn open-source, high-performance, web-based MC simulator that builds upon modern cloud computing architectures is highly desirable to deliver state-of-the-art MC simulations and hardware acceleration to general users without the need for special hardware installation and optimization.ApproachWe have developed a configuration-free, in-browser 3-D MC simulation platform – MCX Cloud – built upon an array of robust and modern technologies, including a Docker Swarm-based cloud-computing backend and a web-based graphical user interface (GUI) that supports in-browser 3-D visualization, asynchronous data communication, and automatic data validation via JavaScript Object Notation (JSON) schemas.ResultsThe front-end of the MCX Cloud platform offers an intuitive simulation design, fast 3-D data rendering, and convenient simulation sharing. The Docker Swarm container orchestration backend is highly scalable and can support high-demand GPU MC simulations using Monte Carlo eXtreme (MCX) over a dynamically expandable virtual cluster.ConclusionMCX Cloud makes fast, scalable, and feature-rich MC simulations readily available to all biophotonics researchers without overhead. It is fully open-source and can be freely accessed at http://mcx.space/cloud.

H9N2 avian influenza virus (AIV) is regarded as a principal donor of viral genes through reassortment to cocirculating influenza viruses that can result in zoonotic reassortants. Whether H9N2 virus can maintain a sustained evolutionary impact on such reassortants is unclear. Since 2013, avian H7N9 virus had caused five sequential human epidemics in China; the fifth wave in 2016 to 2017 was by far the largest, but the mechanistic explanation behind the scale of infection is not clear. Here, we found that just prior to the fifth H7N9 virus epidemic, H9N2 viruses had phylogenetically mutated into new subclades, changed antigenicity, and increased their prevalence in chickens vaccinated with existing H9N2 vaccines. In turn, the new H9N2 virus subclades of PB2 and PA genes, housing mammalian adaptive mutations, were reassorted into cocirculating H7N9 virus to create a novel dominant H7N9 virus genotype that was responsible for the fifth H7N9 virus epidemic. H9N2-derived PB2 and PA genes in H7N9 virus conferred enhanced polymerase activity in human cells at 33°C and 37°C and increased viral replication in the upper and lower respiratory tracts of infected mice, which could account for the sharp increase in human cases of H7N9 virus infection in the 2016–2017 epidemic. The role of H9N2 virus in the continual mutation of H7N9 virus highlights the public health significance of H9N2 virus in the generation of variant reassortants of increasing zoonotic potential. IMPORTANCE Avian H9N2 influenza virus, although primarily restricted to chicken populations, is a major threat to human public health by acting as a donor of variant viral genes through reassortment to cocirculating influenza viruses. We established that the high prevalence of evolving H9N2 virus in vaccinated flocks played a key role as a donor of new subclade PB2 and PA genes in the generation of a dominant H7N9 virus genotype (genotype 72 [G72]) with enhanced infectivity in humans during the 2016–2017 H7N9 virus epidemic. Our findings emphasize that the ongoing evolution of prevalent H9N2 virus in chickens is an important source, via reassortment, of mammalian adaptive genes for other influenza virus subtypes. Thus, close monitoring of the prevalence and variants of H9N2 virus in chicken flocks is necessary for the detection of zoonotic mutations.

The voxel-based Monte Carlo method (VMC) offers efficiency in modeling light transport in complex bio-tissues, but is known to produce erroneous results due to its terraced boundaries. We present a significantly improved VMC by incorporating mesh-based boundary information in a hybrid modeling approach. A fast preprocessing step first extracts surface meshes from an arbitrary voxelated domain using the marching-cubes algorithm. An extended voxel format is developed to encode oblique surface information while keeping the data structure efficient for parallel processing. This enables modeling of subvoxel boundaries, resulting in significantly improved accuracy in benchmarks, including an MRI human brain atlas.

Tree species surveys are crucial to forest resource management and can provide references for forest protection policy making. The traditional tree species survey in the field is labor-intensive and time-consuming, supporting the practical significance of remote sensing. The availability of high-resolution satellite remote sensing data enable individual tree species (ITS) recognition at low cost. In this study, the potential of the combination of such images and a convolutional neural network (CNN) to recognize ITS was explored. Firstly, individual tree crowns were delineated from a high-spatial resolution WorldView-3 (WV3) image and manually labeled as different tree species. Next, a dataset of the image subsets of the labeled individual tree crowns was built, and several CNN models were trained based on the dataset for ITS recognition. The models were then applied to the WV3 image. The results show that the distribution maps of six ITS offered an overall accuracy of 82.7% and a kappa coefficient of 0.79 based on the modified GoogLeNet, which used the multi-scale convolution kernel to extract features of the tree crown samples and was modified for small-scale samples. The ITS recognition method proposed in this study, with multi-scale individual tree crown delineation, avoids artificial tree crown delineation. Compared with the random forest (RF) and support vector machine (SVM) approaches, this method can automatically extract features and outperform RF and SVM in the classification of six tree species.

In the current research, a new Mn(II)-based coordination polymer, {(NH2Me)2[Mn4(Hntb)4(4,4′-bpy)(OH)2] DMF} (1) have been formed by mixing the ligands of H3ntb (4,4′,4′′-nitrilotris-benzoic) and 4,4′-bpy (4,4′-bipyridine). According to the results of UV detection, complex 1 has strong blue luminescence, which means that it can be used as a fluorescent probe for specific detection of Fe3+ ion in water with a Ksv value of 3.2 × 104 M−1. Furthermore, the treatment activity of the compound on sepsis treatment was assessed and the protentional mechanism was revealed. Firstly, the inflammatory cytokines released into the plasma was measured with ELISA detection kit. Then, the survival rate of the infected animals was recorded after compound treatment.

The purpose of image colorization is to map reasonable colors for grayscale images. Although more and more deep neural networks have been proposed and shown good performance, the color images generated usually have the phenomenon of color crossing. In this paper, we propose DDGAN, a Generative Adversarial Networks (GANs) with double auto-encoding discriminators to solve this problem. The purpose of adding a discriminator is to use the complementary statistical properties of KL divergence and reverse KL divergence to avoid mode collapse and improve training stability. The auto-encoding structure is used for pixel level adversarial training to obtain color images with accurate edges. Experiments show that DDGAN has a better performance in the correctness of color migration and the suppression of excessive smoothing of color at the boundary.

Objective: To develop a risk prediction model to identify the high-risk individuals of large niche formation after cesarean section (CS). Design A retrospective study. Setting Women’s health research in Anhui, China. Population: Women received CS between Jan 2012 to Jun 2017. Methods: Women were arranged to receive uterine scar examination by transvaginal ultrasonography, and those diagnosed with niche were divided into two groups according to whether they suffer from postmenstrual spotting. The cut-off values of depth, RMT (residual myometrium thickness), and depth/AMT (adjacent myometrium thickness) were chosen to define a large niche. Then, all participants were classified into three groups, including a control, a small niche, and a large niche group. The scores of each variable in the prediction model were calculated by dividing the minimum β-coefficient from the multivariate logistic analysis. Main outcome: Primary outcome was a prediction scoring model for large niche formation. Results: In total, 727 women were recruited in this study, and the large niche was defined as more than 0.50 cm in depth, less than 0.21 cm in RMT, more than 0.56 in depth/AMT. The large niche prediction model included eight variables of age at delivery, retroflexed uterine, meconium-stained amniotic fluid, history of CS, B-Lynch suture, operation duration, premature rupture of membranes and cervical dilatation more than 4 cm. The cut-off value of 5 in this score-based model presented sensitivity and specificity as 67.48% and 90.07% respectively. Conclusions: This score-based risk prediction model could present the risk of large niche formation of individuals after CS.

The mesh-based Monte Carlo (MMC) technique has grown tremendously since its initial publication nearly a decade ago. It is now recognized as one of the most accurate Monte Carlo (MC) methods, providing accurate reference solutions for the development of novel biophotonics techniques. In this work, we aim to further advance MMC to address a major challenge in biophotonics modeling, i.e. light transport within highly complex tissues, such as dense microvascular networks, porous media and multi-scale tissue structures. Although the current MMC framework is capable of simulating light propagation in such media given its generality, the run-time and memory usage grow rapidly with increasing media complexity and size. This greatly limits our capability to explore complex and multi-scale tissue structures. Here, we propose a highly efficient implicit mesh-based Monte Carlo (iMMC) method that incorporates both mesh- and shape-based tissue representations to create highly complex yet memory efficient light transport simulations. We demonstrate that iMMC is capable of providing accurate solutions for dense vessel networks and porous tissues while reducing memory usage by greater than a hundred- or even thousand-fold. In a sample network of microvasculature, the reduced shape complexity results in nearly 3x speed acceleration. The proposed algorithm is now available in our open-source MMC software at http://mcx.space/#mmc.

The mesh-based Monte Carlo (MMC) technique has grown tremendously since its initial publication nearly a decade ago. It is now recognized as one of the most accurate Monte Carlo (MC) methods, providing accurate reference solutions for the development of novel biophotonics techniques. In this work, we aim to further advance MMC to address a major challenge in biophotonics modeling, i.e. light transport within highly complex tissues, such as dense microvascular networks, porous media and multi-scale tissue structures. Although the current MMC framework is capable of simulating light propagation in such media given its generality, the run-time and memory usage grow rapidly with increasing media complexity and size. This greatly limits our capability to explore complex and multi-scale tissue structures. Here, we propose a highly efficient implicit mesh-based Monte Carlo (iMMC) method that incorporates both mesh- and shape-based tissue representations to create highly complex yet memory-efficient light transport simulations. We demonstrate that iMMC is capable of providing accurate solutions for dense vessel networks and porous tissues while reducing memory usage by greater than a hundred- or even thousand-fold. In a sample network of microvasculature, the reduced shape complexity results in nearly 3x speed acceleration. The proposed algorithm is now available in our open-source MMC software at http://mcx.space/#mmc.

Over the past decade, an increasing body of evidence has suggested that threedimensional (3-D) Monte Carlo (MC) light transport simulations are affected by the inherent limitations and errors of voxel-based domain boundaries. In this work, we specifically address this challenge using a hybrid MC algorithm, namely split-voxel MC or SVMC, that combines both mesh and voxel domain information to greatly improve MC simulation accuracy while remaining highly flexible and efficient in parallel hardware, such as graphics processing units (GPU). We achieve this by applying a marching-cubes algorithm to a pre-segmented domain to extract and encode sub-voxel information of curved surfaces, which is then used to inform ray-tracing computation within boundary voxels. This preservation of curved boundaries in a voxel data structure demonstrates significantly improved accuracy in several benchmarks, including a human brain atlas. The accuracy of the SVMC algorithm is comparable to that of mesh-based MC (MMC), but runs 2x-6x faster and requires only a lightweight preprocessing step. The proposed algorithm has been implemented in our open-source software and is freely available at http://mcx.space.

This study investigated how metabolism of active oxygen is involved in core browning of “Yali” pears during storage. “Yali” pears from early, middle, and late harvests were stored under rapid or slow cooling regimes. It was shown that the delayed core browning under slow cooling regime was associated with high activities of superoxide dismutase (SOD), catalase (CAT), peroxidase (POD), glutathione reductase (GR), low activity of lipoxygenase (LOX), delayed membrane lipid peroxidation, suppressed accumulation of malondialdehyde (MDA), O2-· and H₂O₂, and reduced cell membrane damage. In contrast, rapid cooling enhanced the process of core browning. Fruit from the late harvest developed severe core browning associated with membrane lipid peroxidation and lower activities of SOD, CAT, POD, and GR. Fruit from the middle harvest maintained high SOD, CAT, POD, and GR activities and low level of active oxygen, correlative to lowest core browning. PRACTICAL APPLICATIONS: Moderate maturity at harvest and slow cooling storage are the best combination to inhibit core browning of “Yali” pears through suppressing the accumulation of activated oxygen. The results can help guide farmers in production and aid in producing higher quality produce.

SignificanceFunctional near-infrared spectroscopy (fNIRS) has become an important research tool in studying human brains. Accurate quantification of brain activities via fNIRS relies upon solving computational models that simulate the transport of photons through complex anatomy.AimWe aim to highlight the importance of accurate anatomical modeling in the context of fNIRS, and propose a robust method for creating high-quality brain/full-head tetrahedral mesh models for neuroimaging analysis.ApproachWe have developed a surface-based brain meshing pipeline that can produce significantly better brain mesh models compared to conventional meshing techniques. It can convert segmented volumetric brain scans into multi-layered surfaces and tetrahedral mesh models, with typical processing times of only a few minutes and broad utilities, such as in Monte Carlo or finite-element based photon simulations for fNIRS studies.ResultsA variety of high quality brain mesh models have been successfully generated by processing publicly available brain atlases. In addition, we compare 3 brain anatomical models - the voxel-based brain segmentation, tetrahedral brain mesh and layered-slab brain model, and demonstrate noticeable discrepancies in brain partial-pathlengths when using approximated brain anatomies, ranging between −1.5-23% with the voxelated brain and 36-166% with the layered-slab brain.ConclusionThe generation and utility of high-quality brain meshes can lead to more accurate brain quantification in fNIRS studies. Our open-source meshing toolboxes “Brain2Mesh” and “Iso2Mesh” are freely available at http://mcx.space/brain2mesh.

We propose an implicit mesh-based Monte Carlo algorithm utilizing the edges, nodes and faces in a tetrahedral mesh to facilitate light-simulations in highly-sophisticated tissues, showing hundreds-fold reduction in memory usage.

Due to a growing penetration of permanent magnet synchronous generator-based wind turbine generation (PMSG-WTG) systems into the modern power grid, there is a strong interest in leveraging the potential capabilities of PMSG-WTG system to participate in the system frequency regulation during the grid event. In this work, a novel comprehensive frequency regulation (CFR) scheme is proposed specifically for rotor-speed-control-oriented PMSG-WTG systems. The step-wise inertial power response enables PMSG to perform the temporary frequency support. The rotor speed and pitch angle controllers are coordinated to curtail the wind power output for the persistent de-loaded operation, which can facilitate the primary frequency regulation through the variable-slope droop control. Furthermore, this CFR control scheme is implemented into the controls advanced research turbine 2 (CART2)-PMSG model, so as to investigate its potential impact on the structural loads of wind turbine. Simulation results show CFR can dramatically enhance overall frequency regulation capability of the PMSG-WTG's system and mitigate the frequency oscillations over a full range of wind speeds without causing large mechanical damages to the wind turbine.

With an increasing penetration of wind power in the modern electrical grid, the increasing replacement of large conventional synchronous generators by wind power plants will potentially result in deteriorated frequency regulation performance due to the reduced system inertia and primary frequency response. A series of challenging issues arise from the aspects of power system planning, operation, control and protection. Therefore, it is valuable to develop variable speed wind turbines (VSWTs) equipped with frequency regulation capabilities that allow them to effectively participate in addressing severe frequency contingencies. This paper provides a comprehensive survey on frequency regulation methods for VSWTs. It fully describes the concepts, principles and control strategies of prevailing frequency controls of VSWTs, including future development trends. It concludes with a performance comparison of frequency regulation by the four main types of wind power plants.

A novel inertial control method based on the torque limit control (TLC) is proposed in this study for the purpose of maximizing the temporary inertial response of permanent magnet synchronous generator-wind turbine generator (PMSG-WTG) over a wide range of variable wind speed conditions. To eliminate the secondary frequency drop issue during the rotor speed restoration, a small-scale battery energy storage system (BESS) is utilized by adopting the coordinated control strategy between BESS and PMSG-WTG. For the sake of minimizing the excessive use of BESS energy, this control strategy can smoothly discontinue the participation of BESS once the system frequency restores to the specified value. The simulation results conclude that the overall system frequency regulation performance can be significantly improved through such coordination control of BESS, PMSG-WTG, and conventional generators for the enhanced inertial response under different wind power penetration levels as well as variable wind speed conditions. Furthermore, the potential impact of TLC on the mechanical structures of wind turbine throughout the inertial response is investigated by using the CART2-PMSG integrated model.

Background The aim of this study is to determine pathological factors that increase the risk of LNM and indicate poor survival of patients diagnosed with endometrial cancer and treated with surgical staging. Method Between January 2010 and November 2018, we enrolled 874 eligible patients who received staging surgery in the First Affiliated Hospital of Anhui Medical University. The roles of prognostic risk factors, such as age, histological subtype, tumor grade, myometrial infiltration, tumor diameter, cervical infiltration, lymphopoiesis space invasion (LVSI), CA125, and ascites, were evaluated. Multivariable logistic regression models were used to identify the predictors of LNM. Kaplan–Meier and COX regression models were utilized to study the overall survival. Results Multivariable regression analysis confirmed cervical stromal invasion (OR 3.412, 95% CI 1.631–7.141; P P = 0.04) and ovarian metastasis (OR 6.236, 95% CI 1.561–24.904; P = 0.01) as significant predictors of nodal dissemination. Furthermore, pathological pattern (P = 0.03), myometrial invasion (OR 2.70, 95% CI 1.139–6.40; P = 0.01), and lymph node metastasis (OR 9.675, 95% CI 3.708–25.245; P Conclusions Cervical invasion, lymphopoiesis space invasion, and ovarian metastasis significantly convey the risk of LNM. Pathological type, myometrial invasion, and lymph node metastasis are all important predictors of survival and should be scheduled for completion when possible in the surgical staging procedure.

The mesh-based Monte Carlo (MMC) algorithm is increasingly used as the gold-standard for developing new biophotonics modeling techniques in 3-D complex tissues, including both diffusion-based and various Monte Carlo (MC)-based methods. Compared to multilayered and voxel-based MCs, MMC can utilize tetrahedral meshes to gain improved anatomical accuracy but also results in higher computational and memory demands. Previous attempts of accelerating MMC using graphics processing units (GPUs) have yielded limited performance improvement and are not publicly available. We report a highly efficient MMC—MMCL—using the OpenCL heterogeneous computing framework and demonstrate a speedup ratio up to 420× compared to state-of-the-art single-threaded CPU simulations. The MMCL simulator supports almost all advanced features found in our widely disseminated MMC software, such as support for a dozen of complex source forms, wide-field detectors, boundary reflection, photon replay, and storing a rich set of detected photon information. Furthermore, this tool supports a wide range of GPUs/CPUs across vendors and is freely available with full source codes and benchmark suites at http://mcx.space/#mmc.

A data-driven control method is proposed in super-large-scale energy storage station. This control strategy is embedded in power converter and can solve the serious parallel control problems, that is, the output voltage amplitude, phase angle and frequency may be different due to their model mismatch and unknown dynamics, when high power converters are connected in parallel. Based on the model free adaptive control algorithm, the data-driven controller is designed in high power converter system. The parallel power converter system is dynamically linearized by introducing the pseudo partial derivative. In order to keep that output voltage amplitude, frequency and phase of each power converters are equal at the point of common connection in super-large-scale energy storage station, the control parameters of power converter are updated through the input and output data acquired in real time, when the parallel power converters is running. The simulation results show that the model free adaptive algorithm of power converter is effective in super-large-scale energy storage station.

With the rapid development of spatial light modulators, structured light strategies have been readily implemented for efficient diffuse optical tomography (DOT) and fluorescent molecular tomography (FMT) applications. Compared to traditional pencil-beam sources, wide-field illumination enables larger imaging field-of-view (FOV), higher signal-to-noise ratios (SNR), and faster data acquisition speed, making it attractive for small-animal whole-body imaging. As the gold-standard for simulating photon propagations inside complex biological tissues, the Monte Carlo (MC) method is one of the most accurate approaches for imaging general media. Recently, thanks to parallel hardware such as graphics processing units (GPUs), MC simulations can be computed with high efficiency even with personal computers. While we have added support for wide-field illumination patterns in our widely distributed MC platform (http://mcx.space), the computation for multiple patterns is currently performed sequentially. To further accelerate forward modeling of large number of wide-field patterns, we propose a new method, referred to as “photon sharing”, to simultaneously simulate multiple structure-light sources. We demonstrate a 5- to 10-fold reduction of the MC simulation time. This technique is particularly valuable in DOT or FMT applications using structured light illumination and/or single-pixel-camera based systems. The proposed algorithm has been implemented in our open-source MC simulation platforms, supporting both CPUs and GPUs.

Over the past decade, an increasing body of evidence has suggested that three-dimensional (3-D) Monte Carlo (MC) light transport simulations are affected by the inherent limitations and errors of voxel-based domain boundaries. In this work, we specifically address this challenge using a hybrid MC algorithm, namely split-voxel MC or SVMC, that combines both mesh and voxel domain information to greatly improve MC simulation accuracy while remaining highly flexible and efficient in parallel hardware, such as graphics processing units (GPU). We achieve this by applying a marching-cubes algorithm to a pre-segmented domain to extract and encode sub-voxel information of curved surfaces, which is then used to inform ray-tracing computation within boundary voxels. This preservation of curved boundaries in a voxel data structure demonstrates significantly improved accuracy in several benchmarks, including a human brain atlas. The accuracy of the SVMC algorithm is comparable to that of mesh-based MC (MMC), but runs 2x-6x faster and requires only a lightweight preprocessing step. The proposed algorithm has been implemented in our open-source software and is freely available at http://mcx.space.

The increasing use of spatially modulated imaging and single-pixel detection techniques demands computationally efficient methods for light transport modeling. Herein, we report an easy-to-implement yet significantly more efficient Monte Carlo (MC) method for simultaneously simulating spatially modulated illumination and detection patterns accurately in 3D complex domains. We have implemented this accelerated algorithm, named “photon sharing,” in our open-source MC simulators, reporting 13.6 × and 5.5 × speedups in mesh- and voxel-based MC benchmarks, respectively. In addition, the proposed algorithm is readily used to accelerate the solving of inverse problems in spatially modulated imaging systems by building Jacobians of all illumination-detection pattern pairs concurrently, resulting in a 12.4-fold speed improvement.

Significance: Functional near-infrared spectroscopy (fNIRS) has become an important research tool in studying human brains. Accurate quantification of brain activities via fNIRS relies upon solving computational models that simulate the transport of photons through complex anatomy. Aim: We aim to highlight the importance of accurate anatomical modeling in the context of fNIRS and propose a robust method for creating high-quality brain/full-head tetrahedral mesh models for neuroimaging analysis. Approach: We have developed a surface-based brain meshing pipeline that can produce significantly better brain mesh models, compared to conventional meshing techniques. It can convert segmented volumetric brain scans into multilayered surfaces and tetrahedral mesh models, with typical processing times of only a few minutes and broad utilities, such as in Monte Carlo or finite-element-based photon simulations for fNIRS studies. Results: A variety of high-quality brain mesh models have been successfully generated by processing publicly available brain atlases. In addition, we compare three brain anatomical models—the voxel-based brain segmentation, tetrahedral brain mesh, and layered-slab brain model—and demonstrate noticeable discrepancies in brain partial pathlengths when using approximated brain anatomies, ranging between −1.5% to 23% with the voxelated brain and 36% to 166% with the layered-slab brain. Conclusion: The generation and utility of high-quality brain meshes can lead to more accurate brain quantification in fNIRS studies. Our open-source meshing toolboxes “Brain2Mesh” and “Iso2Mesh” are freely available at http://mcx.space/brain2mesh.

A simplified method for evaluating a pile-supported embankment reinforced with geosynthetic (PGRS embankment) is proposed in this paper. The method takes into account not only the arching effect, the membrane effect of the deflected geosynthetic, and the subsoil reaction, but also the pile head settlement, which makes the method applicable for floating piles, as well as piles seated on a firm soil layer. The settlement of the subsoil surface is considered to consist of two parts: (a) the settlement of the subsoil surface equals that of the pile cap with no deformation in geosynthetic yet (b) the subsoil surface subsides along with the geosynthetic deforming, and the deflected geosynthetic being considered as catenary shaped. The formula for the maximum differential settlement between the subsoil surface and the piles is worked out by analyzing the force equilibrium of the geosynthetic and the stress-strain relationship of the geosynthetic at the edge of the pile cap. The comparison of the calculated results with the observed data and the six current analytical methods has been implemented to verify the proposed method. The influence of the tensile stiffness of the geosynthetic, compression modulus of soft soil, soft soil thickness, embankment height, internal friction angle of the embankment fill and the pile spacing on the subsoil reaction, the stress concentration ratio (SCR) and the tension of the geosynthetic are investigated using the proposed method. The influence significance of these factors has been investigated using the evaluation theory of binary variance analysis for the non-repeatability tests, which helps optimize the design of the PGRS embankment. V tem članku je predlagana poenostavljena metoda za ovrednotenje nasipa, podprtega s piloti in ojačenim z geosintetikom (PGRS nasip). Metoda upošteva poleg ločnega učinka, membranskega učinka odklonjenega geosintetika in reakcije tal, tudi posedek glave pilota. Zaradi slednjega se metoda lahko uporablja tako za viseče pilote kot tudi za pilote, ki stojijo na trdnem zemljinskem sloju. Posedek sloja zemljine pod površjem je sestavljen iz dveh delov: (a) posedka sloja zemljine pod površjem, ki je enak posedku glave pilota brez deformacij v geosintetiku (b) ugrezka sloja zemljine pod površjem zaradi deformiranja geosintetika, pri čemer je upoštevana deformirana oblika za geosintetik enaka obliki deformacije vrvi. Enačba za največji diferencialni posedek med površino podlage in piloti je dobljena s pomočjo analize ravnotežja sil geosintetika in razmerja napetost-specifična deformacija geosintetika na robu glave pilota. Za preveritev predlagane metode je bila izvedena primerjava izračunanih rezultatov z opazovanimi podatki in šestimi trenutnimi analitskimi metodami. Z uporabo predlagane metode je bil preučevan vpliv natezne togosti geosintetika, kompresijskega modula mehke zemljine, debeline mehke zemljine, višine nasipa, notranjega kota trenja nasipnega materiala in razmika pilotov na reakcijo zemljine, razmerja koncentracije napetosti (SCR) in napetosti geosintetika. Učinek teh faktorjev je bil raziskan z uporabo teorije vrednotenja binarne analize variance za neponovljive preizkuse, kar pomaga optimirati načrtovanje PGRS nasipa.

Microgrid is a kind of weak small power network. Because there are a large number of distributed generators in microgrid, it is easy to cause the unstable operation of system. Aiming at the stability issue caused by the change of parameters of many distributed generators in microgrid, a multi-parameter rapid optimization method using matrix perturbation theory is proposed so that the optimization time can be shortened. Firstly, the small signal model of two distributed generators connected in parallel is established. Through the stability analysis, the stability boundaries of the dominant control parameters of distributed generator are obtained. Then the optimization model of microgrid considering the small signal stability, damping ratio and stability margin is established. In order to accelerate the optimization speed and reduce the computational burden caused by the repeated calculation of eigenvalue, a unified equation for the calculation of eigenvalue of proposed system is derived using matrix perturbation theory when the parameters of the power controller, current controller and voltage controller in distributed generator are perturbed. Thus, the small signal stability of microgrid can be improved and the fluctuation of voltage and frequency of microgrid can be reduced. The simulation results show that the fast optimization method based on matrix perturbation theory is feasible.

A simple and rapid capillary electrophoresis (CE) method was developed for the determination of trace thiophanate-methyl, carbendazim and benomyl in fruits and vegetables. Herein, bacterial cellulose (BC) was used as additive in running buffer to improve the separation efficiency. CE experimental parameters such as detection wavelength, concentration and pH of the running buffer, separation voltage as well as the contents of BC in running buffer were systematically investigated. Under the optimized conditions, three benzimidazole fungicides could be accurate quantified in 8 min using H3BO3/Na2B4O7 (4 mmol/L, pH 9.0) containing 0.3% (mass fraction) BC for background electrolyte, 15 kV for the separation voltage, 25℃ for the column temperature and 275 nm for detection wavelength. Good linearities for the three benzimidazole fungicides were obtained with correlation coefficients (r2) ≥ 0.997. The limits of detection (LODs) of the three benzimidazole fungicides were between 5.0 and 10.0 μg/L. The relative standard deviations (RSDs, n=5) of inter-day were 0.82%-1.0% for retention times and 2.4%-2.9% for peak areas. The proposed method was further applied to determine the residues of the three benzimidazole fungicides in fruits and vegetables. The recoveries were in the range of 93.5%-103.0% with RSDs no more than 8.0%. These results indicated that the proposed method can serve as an efficient tool for the simultaneous determination of the three benzimidazole fungicides in fruits and vegetables.

We report a new technique to accelerate mesh-based Monte Carlo (MMC) photon transport simulations by using a coarsely tessellated tetrahedral mesh to represent tissue boundaries and a voxelated space to store output fluence.