Discontinuous Regions Research Articles

Assessment of a hydrologic-land surface model to simulate thermo-hydrologic evolution of permafrost regions

Hydrologic-land surface models (H-LSMs) offer a physically-based framework for representing and predicting the present and future states of the extensive high-latitude permafrost areas worldwide. Their primary challenge, however, is that soil temperature data are severely limited, and traditional model validation, based only on streamflow, can show the right fit to these data for the wrong reasons. Here, we address this challenge by (1) collecting existing data in various forms including in-situ borehole data and different large-scale permafrost maps in addition to streamflow data, (2) comprehensively evaluating the performance of an H-LSM with a wide range of possible process parametrizations and initializations, and (3) assessing possible trade-offs in model performance in concurrently representing hydrologic and permafrost dynamics, thereby pointing to the possible model deficiencies that require improvement. As a case study, we focus on the sub-arctic Liard River Basin in Canada, which typifies vast northern sporadic and discontinuous permafrost regions. Our findings reveal that different process parameterizations tend to align with different data sources or variables, which largely exhibit inconsistencies among themselves. We further observe that a model may fail to represent permafrost occurrence yet seemingly fit streamflows adequately. Nonetheless, we demonstrate that accurately representing essential permafrost dynamics, including the active soil layer and insulation effects from snow cover and soil organic matter, is crucial for developing high-fidelity models in these regions. Given the complexity of processes and the incompatibility among different data sources/variables, we conclude that employing an ensemble of carefully designed model parameterizations is essential to provide a reliable picture of the current conditions and future spatio-temporal co-evolution of hydrology and permafrost.

Higher Stability of Soil Organic Matter near the Permafrost Table in a Peatland of Northeast China

Understanding the stability of soil organic matter (SOM) is essential for making accurate predictions regarding carbon release rates. However, there is limited information on the role of chemical composition of dissolved organic matter (DOM) in SOM stability. To address this gap, the peatland soil profile in the discontinuous frozen soil region of Northeast China was selected as the focus of this research, and a comprehensive analysis was conducted on the differences between the molecular composition of DOM and the stability of SOM. The results indicate a significant carbon accumulation phenomenon near the permafrost table. Through analyses using TG-50, δ13C, and δ15N, it was determined that SOM near the permafrost table exhibits high stability, whereas SOM within the permafrost layer demonstrates poor stability. Investigations utilizing UV-vis, 3D-EEM, FT-IR, and 1H-NMR technologies revealed that DOM near the permafrost table is of high quality and highly aromatic. Furthermore, compared to near the permafrost table, humic acid materials in the permafrost layer decreased by 17%, while protein materials increased by 17%. These findings offer a novel perspective on the understanding of SOM stability in peatland soil profiles within discontinuous permafrost regions.

One-shot structured light illumination based on shearlet transform.

Balancing speed and accuracy has always been a challenge in 3D reconstruction. One-shot structured light illuminations are of perfect performance on real-time scanning, while the related 3D point clouds are typically of relatively poor quality, especially in regions with rapid height changes. To solve this problem, we propose a one-shot reconstruction scheme based on shearlet transform, which combines spatial and frequency domain information to enhance reconstruction accuracy. First, we apply the shearlet transform to the deformed fringe pattern to obtain the transform coefficients. Second, pixel-wise select the indices associated with the N largest coefficients in magnitude to obtain a new filter. Finally, we refocus globally to extract phase using these filters and generate a reliable quality map based on coefficient magnitudes to guide phase unwrapping. Simultaneously, we utilize the maximum coefficient value to generate a quality map for guiding the phase unwrapping process. Experimental results show that the proposed method is robust in discontinuous regions, resulting in more accurate 3D point clouds.

A Dynamic Context Encoder Network for Liver Tumor Segmentation.

Accurate segmentation of liver tumor regions in medical images is of great significance for clinical diagnosis and the planning of surgical treatments. Recent advancements in machine learning have shown that convolutional neural networks are powerful in such image processing while largely reducing human labor. However, the variable shape, fuzzy boundary, and discontinuous tumor region of liver tumors in medical images bring great challenges to accurate segmentation. The feature extraction capability of a neural network can be improved by expanding its architecture, but it inevitably demands more computing resources in training and hyperparameter tuning. This study presents a Dynamic Context Encoder Network (DCE-Net), which incorporates multiple new modules, such as the Involution Layer, Dynamic Residual Module, Context Extraction Module, and Channel Attention Gates, for feature extraction and enhancement. In the experiment, we used a liver tumor CT dataset of LiTS2017 to train and test the DCE-Net for liver tumor segmentation. The experimental results showed that the four evaluation indexes of the method, precision, recall, dice, and AUC, were 0.8961, 0.9711, 0.9270, and 0.9875, respectively. Furthermore, our ablation study reported that the accuracy and training efficiency of our network were markedly superior to the networks without involution or dynamic residual modules. Therefore, the DCE-Net proposed in this study has great potential for automatic segmentation of liver lesion tumors in the clinical diagnostic environment.

Discontinuous permafrost detection from neural network-ensemble learning based electrical resistivity tomography

Electrical resistivity tomography (ERT) is an effective method for detecting the distribution of permafrost. However, the general inversion method of ERT cannot satisfy the engineering designation demand, resulting in the foundation of thaw settlement in discontinuous permafrost regions. In this study, we proposed a neural network-ensemble learning inversion method to improve the detection accuracy of discontinuous permafrost. First, a series of different resistivity distributions was evaluated to establish forward models for the training of a backpropagation neural network (BPNN). The resistivity distributions of the forward models varied with the temperature gradient, similar to the resistivity distribution of real discontinuous permafrost. The bagging algorithm of ensemble learning was then used to optimize the BPNN inversion models. Finally, three discontinuous permafrost resistivity models and two field data examples are considered to demonstrate the feasibility of the proposed inversion model. The inversion results of synthetic and field examples show that the neural network-ensemble learning model achieved a greater inversion effect with better accuracy and less noisy points than a single BPNN model or the Res2Dinv method. The trained ensemble learning inversion method has good application in field permafrost exploration.

A dual-population auxiliary multiobjective coevolutionary algorithm for constrained multiobjective optimization problems

The key to solving constrained multiobjective optimization problems (CMOPs) lies in maintaining the feasibility, convergence, and diversity of the population. In recent years, various constraint handling techniques (CHTs) and strategies have been proposed to enhance the performance of constrained multiobjective evolutionary algorithms (CMOEAs). However, most of these algorithms face difficulties in dealing with problems that have large infeasible regions and discontinuous small feasible regions, as they have trouble crossing large infeasible regions while simultaneously maintaining the convergence and diversity of the population. To tackle this issue, this paper proposes a dual-population auxiliary coevolutionary algorithm with an enhanced operator, denoted as DAEAEO. Auxiliary population 1 employs an improved ϵ-constraint handling technique to provide high-quality feasible solutions for the main population. Auxiliary population 2 adopts the non-dominated sorting method to provide favorable objective information for the main population to help it cross the infeasible region. In addition, to further improve diversity, each population adopts an enhanced operator and a genetic operator to generate offspring, respectively. Finally, knowledge transfer between offspring is realized. Compared to six state-of-the-art CMOEAs on DASCMOPs, LIR-CMOPs, DOC test suites, and two real-world problems, the proposed DAEAEO achieved superior performance, especially for CMOPs with large infeasible regions and discontinuous small feasible regions.

Weakening the mechanical property anisotropy of additively manufactured medium entropy alloy by controlling the cellular structure

Cellular structure is a unique microstructure characteristic of the additively manufactured face-centered cubic phase metallic materials. It typically grows preferentially along the temperature gradient, leading to anisotropy in mechanical properties and restricting the practical application. Herein, we adopted a discontinuous laser scanning strategy for fabricating the face-centered cubic FeCrNi alloy. The scanning layer is divided into nine discontinuous equal-width regions along which the laser beam prints discontinuously. This strategy can increase the temperature gradient in the melt pool by weakening the thermal influence between the adjacent scanning regions, which helps to suppress cellular structure growth along the temperature gradient. Compared with the sample prepared by the conventional continuous laser scanning strategy, the sample printed using the discontinuous laser scanning strategy exhibits finer cellular structures with a significantly shorter length along the growth direction, and the anisotropy of mechanical properties is weakened. The in-plane anisotropy of ultimate tensile strength decreases from 21.6 to 6.4. This study presents a novel approach to optimize the mechanical properties of additively manufactured face-centered cubic phase metallic materials.

Grey wolf optimization tuned drivetrain vibration controller with backlash compensation strategy using time-dependent-switched Kalman filter

To improve the performance and durability of vehicle components, efforts have been made to reduce driveline oscillations using advanced active control algorithms. However, existing methods often rely on subjective parameter adjustments, which can be burdensome for designers. This study introduces an effective tuning algorithm for a driveline vibration controller that accounts for nonlinear backlash effects. Initially, a driveline dynamics model is developed to focus on transient oscillations resulting from changes in driving force and the presence of nonlinear backlash. The backlash impact is incorporated into the model through a discontinuous dead-zone region. Two operational dynamics, which are the contact mode and the backlash mode, are considered. A dynamic output feedback [Formula: see text] controller is designed as a baseline controller to mitigate low-frequency resonance in the driveline. A solution for managing the nonlinear backlash challenges is introduced, involving the use of a simple control mode switching algorithm in conjunction with the controller. This algorithm relies on a time-dependent-switched Kalman filter. Additionally, the optimal settings for the parameters needed by the mode-switching algorithm are autonomously determined using the grey wolf optimizer (GWO). The proposed active controller can be implemented in real vehicles by using an on-vehicle acceleration sensor and electronic control unit (ECU). In a simulation environment, the vehicle body vibration is online fed back to the resultant controller, and an actuator is supposed to apply control commands to the driveline. The effectiveness of this newly proposed active controller is confirmed through comparative tests, revealing the superior vibration control.

Stress Evaluation Through the Layers of a Fibre-Metal Hybrid Composite by IHD: An Experimental Study

BackgroundIncremental hole-drilling (IHD) has shown its importance in the measurement of the residual stress distribution within the layers of composite laminates. However, validation of these results is still an open issue, especially near the interfaces between plies. ObjectivesIn this context, this study is focused on experimentally verifying its applicability to fibre metal laminates.MethodsTensile loads are applied to cross-ply GFRP-steel [0/90/steel]s samples. Due to the difference in the mechanical properties of each ply, Classical Lamination Theory (CLT) predicts a distribution of the uniform stress within each layer, with pulse gradients between them. The interfaces act as discontinuous regions between the plies. The experimental determination of such stress variation is challenging and is the focus of this research. A horizontal tensile test device was designed and built for this purpose. A differential method is used to eliminate the effect of the existing residual stresses in the samples, providing a procedure to evaluate the ability of the IHD technique to determine the distribution of stress due to the applied tensile loads only. The experimentally measured strain-depth relaxation curves are compared with those determined numerically using the finite element method (FEM) to simulate the hole-drilling. Both are used as input for the IHD stress calculation method (unit pulse integral method). The distribution of stress through the composite laminate, determined by classical lamination theory (CLT), is used as a reference.ResultsUnit pulse integral method results, using the experimental and numerical strain-depth relaxation curves, compare reasonably well with those predicted by CLT, provided that there is no material damage due to high applied loads.ConclusionsIHD seems to be an important measurement technique to determine the distribution of residual stresses in fibre metal laminates and should be further developed for a better assessment of the residual stresses at the interfaces between plies.

Local-scale heterogeneity of soil thermal dynamics and controlling factors in a discontinuous permafrost region

Abstract In permafrost regions, the strong spatial and temporal variability in soil temperature cannot be explained by the weather forcing only. Understanding the local heterogeneity of soil thermal dynamics and their controls is essential to understand how permafrost systems respond to climate change and to develop process-based models or remote sensing products for predicting soil temperature. In this study, we analyzed soil temperature dynamics and their controls in a discontinuous permafrost region on the Seward Peninsula, Alaska. We acquired one-year temperature time series at multiple depths (at 5 or 10 cm intervals up to 85 cm depth) at 45 discrete locations across a 2.3 km2 watershed. We observed a larger spatial variability in winter temperatures than that in summer temperatures at all depths, with the former controlling most of the spatial variability in mean annual temperatures. We also observed a strong correlation between mean annual ground temperature at a depth of 85 cm and mean annual or winter season ground surface temperature across the 45 locations. We demonstrate that soils classified as cold, intermediate, or warm using hierarchical clustering of full-year temperature data closely match their co-located vegetation (graminoid tundra, dwarf shrub tundra, and tall shrub tundra, respectively). We show that the spatial heterogeneity in soil temperature is primarily driven by spatial heterogeneity in snow cover, which induces variable winter insulation and soil thermal diffusivity. These effects further extend to the subsequent summer by causing variable latent heat exchanges. Finally, we discuss the challenges of predicting soil temperatures from snow depth and vegetation height alone by considering the complexity observed in the field data and reproduced in a model sensitivity analysis.

White spot syndrome virus endogenous viral elements (EVE) revealed by circular viral copy DNA (cvcDNA) in shrimp

Circular, viral copy DNA (cvcDNA) can reveal the existence of endogenous viral elements (EVE) in shrimp genomic DNA. Here we describe isolation and sequencing of cvcDNA from a breeding stock of the whiteleg shrimp Penaeus vannamei. The stock was developed by onward breeding and selection for white spot syndrome virus (WSSV)-free individual survivors of white spot disease outbreaks. The stock exhibits high tolerance to WSSV. A pool of DNA extracted from 10 shrimp from this stock was subjected to cvcDNA isolation and amplification followed by high throughput sequencing. This revealed DNA fragments corresponding to locations covering much of the 300,000 bp WSSV genome. However, high frequency-read-fragments (HFRF) mapped to a surprisingly small region of approximately 1400 bp. We hypothesized that the HFRF reflected their selection due to provision of tolerance to WSSV. Four PCR primer sets were designed to cover the 1365 bp mapped region. One pair (Set 1) targeted the whole 1365 bp mapped region, while another 3 primer sets (Set 2–4), targeted regions within the 1365 bp target. All 4 primer sets were used with DNA samples from each of 36 shrimp from the same breeding stock (including the 10 used for cvcDNA preparation). Individual positive PCR results varied from shrimp to shrimp, ranging from only 1 primer set up to 4 primer sets. Only 1 specimen gave an amplicon of 1365 bp, while others gave single to multiple positive amplicons in both continuous and discontinuous regions. This indicated that the amplicons did not arise from contiguous targets and might vary in insertion length. The results also confirmed that none of the shrimp were infected with WSSV. Sequencing of the PCR amplicons of expected sizes revealed sequence identity to extant WSSV genomes. This data will be used to screen the breeding stock for EVE that provide WSSV tolerance.

Expression of Nephronectin in the Descemet's membrane of mouse corneas during development and adult homeostasis

Nephronectin (Npnt) is an extracellular matrix (ECM) protein with pleiotropic functions during organogenesis, disease, and homeostasis. Although the ECM plays a crucial role during development and homeostasis of the adult cornea, little is known about the expression of Npnt in the mammalian cornea. Here, we investigated the expression of Npnt during early embryonic and postnatal development, and in adult mouse corneas. We combined ultrastructural and immunohistochemical analyses to study the early formation of the Descemet's membrane and how the expression of Npnt relates to key basement membrane proteins. Our section in situ hybridization and immunohistochemical analyses revealed that Npnt mRNA is expressed by the nascent corneal endothelial cells at embryonic day (E) 14.5, whereas the protein is localized in the adjacent extracellular matrix. These expression patterns were maintained in the corneal endothelium and Descemet's membrane throughout development and in adult corneas. Ultrastructural analysis revealed discontinuous electron dense regions of protein aggregates at E18.5 that was separated from the endothelial layer by an electron lucent space. At birth (postnatal day, P0), the Descemet's membrane was a single layer, which continuously thickened throughout P4, P8, P10, and P14. Npnt was localized to the Descemet's membrane by E18.5 and overlapped with Collagens IV and VIII, Laminin, and Perlecan. However, the proteins subsequently shifted and formed distinct layers in the adult cornea, whereby Npnt localized between two Collagen VIII bands and anterior to Collagen IV but overlapped with Laminin and Perlecan. Combined, our results reveal the expression of Npnt in the mouse cornea and define its spatiotemporal localization relative to key basement membrane proteins during the formation of the Descemet's membrane and in the adult cornea. Understanding the spatiotemporal expression of Npnt is important for future studies to elucidate its function in the mammalian cornea.

Dual-power nonlinear energy sink for targeted energy transfer in ultra-wide range of impulsive energy

Recently, the NES with one third power (OTP) nonlinearity was proposed to attenuate micro-vibrations under low-level initial impulsive energy. However, the targeted energy transfer (TET) region for effective vibration mitigation is narrow. This paper develops a new type of NES with dual-power (DP) nonlinearity by combining the third power (TP) nonlinearity and the OTP one in parallel. Firstly, the dynamic behaviors of the DP NES are investigated, and significant vibration mitigation is observed in two discontinuous TET regions that are separately induced by the OTP and TP nonlinearities. Furthermore, the parameter analysis is conducted to find out a feasible avenue to merge such two discontinuous TET regions. It demonstrates that there exist optimal parameters to achieve a wide and continuous TET region. Finally, the design optimization of the DP NES is carried out with the aid of the genetic algorithm, and the optimal parameters enable the DP NES to trigger TET in an ultra-wide and continuous range of initial impulsive energy. Consequently, the proposed DP NES should be an effective solution to substantially broaden the TET region and attenuate vibration in an ultra-wide range of initial impulsive energy.

High‐Resolution Maps of Near‐Surface Permafrost for Three Watersheds on the Seward Peninsula, Alaska Derived From Machine Learning

AbstractPermafrost soils are a critical component of the global carbon cycle and are locally important because they regulate the hydrologic flux from uplands to rivers. Furthermore, degradation of permafrost soils causes land surface subsidence, damaging infrastructure that is crucial for local communities. Regional and hemispherical maps of permafrost are too coarse to resolve distributions at a scale relevant to assessments of infrastructure stability or to illuminate geomorphic impacts of permafrost thaw. Here we train machine learning models to generate meter‐scale maps of near‐surface permafrost for three watersheds in the discontinuous permafrost region. The models were trained using ground truth determinations of near‐surface permafrost presence from measurements of soil temperature and electrical resistivity. We trained three classifiers: extremely randomized trees (ERTr), support vector machines (SVM), and an artificial neural network (ANN). Model uncertainty was determined using k‐fold cross validation, and the modeled extents of near‐surface permafrost were compared to the observed extents at each site. At‐a‐site near‐surface permafrost distributions predicted by the ERTr produced the highest accuracy (70%–90%). However, the transferability of the ERTr to the sites outside of the training data set was poor, with accuracies ranging from 50% to 77%. The SVM and ANN models had lower accuracies for at‐a‐site prediction (70%–83%), yet they had greater accuracy when transferred to the non‐training site (62%–78%). These models demonstrate the potential for integrating high‐resolution spatial data and machine learning models to develop maps of near‐surface permafrost extent at resolutions fine enough to assess infrastructure vulnerability and landscape morphology influenced by permafrost thaw.

Development of safe operation technology of crude oil pipeline in permafrost regions

China Mohe‒Daqing Pipeline is the world first large diameter and positive temperature buried pipeline that crosses the unstable and discontinuous permafrost regions. The permafrost along the pipeline is characterized by its high temperature, large ice content, high sensitivity to external disturbance and extremely poor thermal stability. Thus, it is a great global engineering challenge to lay and operate a stable positive temperature pipeline under the harsh conditions of “permafrost land, frigid environment and fragile ecology” while, at the same time, protecting its fragile ecological environment. Herein, the characteristics of permafrost along the pipeline were systematically analyzed, and the current scientific and technical problems in the phases of pipeline designing, constructing and operating were put forward. This thesis made significant innovative breakthroughs in the coupling mechanism of permafrost and pipelines, the design and control of hydro-thermal stable environment for permafrost and pipeline, and the monitoring, prevention and control of permafrost and pipeline disasters, thus creating a complete set of key technical systems for pipeline construction and operation in frozen soil regions. Through analyzing the performance of this system in recent ten years, it is verified that the technical achievements served to the high-quality construction and stable operation of the pipeline.

Numerical studies on heat and mass transport during large-sized fused silica glass synthesis by multi-burner chemical vapor deposition

With the development of modern optical systems towards large scale, the fused silica glass with a large size is receiving increasing attention. In this paper, multi-burner chemical vapor deposition technique was proposed to synthesize the large-sized fused silica glass, and an integrated computational model was used to describe the fluid flow, combustion and heat transfer in the furnace. The effects of various process parameters on the distributions of temperature and species were investigated. Based on the evaluation of temperature and key species concentrations on deposition surface, the size and quality of the synthesized fused silica glass were indirectly estimated. Results showed that reducing the deposition surface height and increasing the number of burners could improve the temperature and species concentrations on the deposition surface, while an increase in the number of furnace outlets led to their decreases. The use of two burners would lead to the formation of discontinuous glass regions at the current conditions and a circular glass structure was generated when employing three burners and deposition surface height of 0.5 m, based on the proposed temperature criterion. The combined process parameters of four burners, deposition surface height of 0.5 m, H2/O2 equivalence ratio of 1.00 and two furnace outlets are be of advantage to synthesize the large-sized and high-quality fused silica glass at current sizes and structures of the furnace and burner.

Arctic-boreal lakes of interior Alaska dominated by contemporary carbon

Northern high-latitude lakes are critical sites for carbon processing and serve as potential conduits for the emission of permafrost-derived carbon and greenhouse gases. However, the fate and emission pathways of permafrost carbon in these systems remain uncertain. Here, we used the natural abundance of radiocarbon to identify and trace the predominant sources of methane, carbon dioxide, dissolved inorganic and organic carbon in nine lakes within the Yukon Flats National Wildlife Refuge in interior Alaska, a discontinuous permafrost region with high landscape heterogeneity and susceptibility to climate, permafrost, and hydrological changes. We find that although Yukon Flats lakes primarily process young carbon (modern to 1290 ± 60 years before present), permafrost-derived carbon is present in some of the sampled lakes and contributes, at most, 30 ± 10% of the dissolved carbon in lake surface waters. Apportionment of young carbon and legacy carbon (carbon with radiocarbon age ⩾5000 years before present) is decoupled among the dissolved inorganic and organic carbon species, with methane showing a stronger legacy signature. Our observations suggest that permafrost-thaw-related transport of carbon through Yukon Flats lacustrine ecosystems and into the atmosphere is small, and likely regulated by surficial sediments, permafrost distribution, wildfire occurrence, or masked by contemporary carbon processes. The heterogeneity of lakes across our study area and northern landscapes more broadly cautions against using any one region (e.g. Yedoma permafrost lakes) to upscale their contribution across the pan-Arctic.

Stereo matching method based on high-precision occlusion-recovering and discontinuity-preserving

Stereo matching is the core of machine vision, such as 3D reconstruction, posture perception and driverless technology in the future etc. Currently, there are still great difficulties in improving the matching accuracy of disparity discontinuity and occlusion regions. In this paper, we propose a new high-precision occlusion-recovering and discontinuity-preserving method for stereo matching. We focus on disparity refinement, and present an adaptability-based disparity reconstruction that achieves accurate occlusion-recovering by fusing color aberration, distance, and disparity value. For discontinuity-preserving, disparity-based secondary guided filtering is proposed, then introduce adaptive image enhancement and adaptive Canny edge detection to correct errors in discontinuous regions. The experiments on Middlebury standard dataset show that our algorithm has high overall accuracy, especially in the disparity discontinuity and occlusion regions. This novel method is more direct, efficient, and less sensitive to the accuracy of disparity estimation, and the live-action shooting shows the robustness of our algorithm. The method has the prospect of civil and engineering use, and presents scientific reference for high-precision target identification, target tracking, 3D measurement, etc.

Identification of a putative Gag binding site critical for feline immunodeficiency virus genomic RNA packaging.

The retroviral Gag precursor plays a central role in the selection and packaging of viral genomic RNA (gRNA) by binding to virus-specific packaging signal(s) (psi or ψ). Previously, we mapped the feline immunodeficiency virus (FIV) ψ to two discontinuous regions within the 5' end of the gRNA that assumes a higher order structure harboring several structural motifs. To better define the region and structural elements important for gRNA packaging, we methodically investigated these FIV ψ sequences using genetic, biochemical, and structure-function relationship approaches. Our mutational analysis revealed that the unpaired U85CUG88 stretch within FIV ψ is crucial for gRNA encapsidation into nascent virions. High-throughput selective 2' hydroxyl acylation analyzed by primer extension (hSHAPE) performed on wild type (WT) and mutant FIV ψ sequences, with substitutions in the U85CUG88 stretch, revealed that these mutations had limited structural impact and maintained nucleotides 80-92 unpaired, as in the WT structure. Since these mutations dramatically affected packaging, our data suggest that the single-stranded U85CUG88 sequence is important during FIV RNA packaging. Filter-binding assays performed using purified FIV Pr50Gag on WT and mutant U85CUG88 ψ RNAs led to reduced levels of Pr50Gag binding to mutant U85CUG88 ψ RNAs, indicating that the U85CUG88 stretch is crucial for ψ RNA-Pr50Gag interactions. Delineating sequences important for FIV gRNA encapsidation should enhance our understanding of both gRNA packaging and virion assembly, making them potential targets for novel retroviral therapeutic interventions, as well as the development of FIV-based vectors for human gene therapy.

Hybrid conservative central/WENO finite difference scheme for two-dimensional detonation problems

In the present work, a hybrid finite difference scheme is proposed and tested for the study of two-dimensional detonation problems. The hybrid scheme consists of a fifth-order weighted essentially nonoscillatory (WENO) method for discontinuous regions and a fourth or sixth-order robust conservative central finite difference scheme for the remaining domain. An arbitrary shock sensor is used to identify the discontinuities. The proposed shock sensor is based on the absolute value of the density gradient with an arbitrary threshold computed at each time step using a fast image segmentation technique. The sensor is complemented with a Ducros sensor to avoid the selection of vortices as discontinuities. The hybrid scheme is tested for several benchmark examples, including a two-dimensional transverse detonation wave, detonation wave diffraction, and a multiple obstacles test case. The obtained results show that the proposed sensor detects discontinuities adequately and the hybrid schemes give the same results as the fifth-order WENO in faster computational time.