Consistent Structure Research Articles

EXPRESS: Unpacking the Role of Ethical Leadership in the Era of Sustainable Development Goals and Values-based Marketing

Tackling sustainable development goals (SDGs) has become a key strategic marketing activity for multinational enterprises (MNEs) to build their reputation and ensure their brand value. However, SDGs can cause goal conflicts for MNEs, resulting in firms not being equally responsive to all stakeholders. Therefore, this study aimed to explore how ethical leadership, underpinned by a corporate purpose, enables MNEs to pursue SDGs in foreign markets. The researchers argued that ethical leadership based on a corporate purpose can provide strategic direction for MNEs, thus enabling them to focus on selected SDGs that can be integrated into their values-based marketing agendas. Further, the findings revealed that a corporate purpose can offer consistency and perseverance in the exertion of ethical leadership at the local market level; however, ethical leadership may require organizational members to disassociate from structural inconsistencies and goal conflicts in pursuit of aspired SDGs. Thus, the study makes a significant contribution to the literature on international marketing by adopting an ethical perspective to explain how MNEs can strategically position themselves in relation to SDGs in international markets. The findings suggest that ethical leadership can build a foundation for credible marketing communication while serving as a driver of values-based marketing programs.

Enhancing the Precision of the Self-Compassion Scale Short Form (SCS-SF) with Rasch Methodology

Abstract Objectives Precise measurement of self-compassion is essential for informing well-being–related policies. Traditional assessment methods have led to inconsistencies in the factor structure of self-compassion scales. We used Rasch methodology to enhance measurement precision and assess the psychometric properties of the Self-Compassion Scale Short Form (SCS-SF), including its invariance across Ghana, Germany, India, and New Zealand. Method We employed the Partial Credit Rasch model to analyse responses obtained from 1000 individuals randomly selected (i.e. 250 from each country) from a total convenience sample of 1822 recruited from the general populations of Germany, Ghana, India, and New Zealand. Results The initial identification of local dependency among certain items led to a significant misfitting of the SCS-SF to the Rasch model (χ2 (108) = 260.26, p < 0.001). We addressed this issue by merging locally dependent items, using testlets. The solution with three testlets resulted in optimal fit of the SCS-SF to the Rasch model (χ2 (27) = 23.84, p = 0.64), showing evidence of unidimensionality, strong sample targeting (M = 0.20; SD = 0.72), and good reliability (Person Separation Index = 0.71), including invariance across sociodemographic factors. We then developed ordinal-to-interval conversion tables based on the Rasch model’s person estimates. The SCS-SF showed positive correlations with measures of compassion towards others, optimism, and positive affect, alongside negative associations with psychological distress and negative affect. Conclusions The current study supports the reliability, as well as the structural, convergent, and external validity of the SCS-SF. By employing the ordinal-to-interval conversion tables published here, the precision of the measure is significantly enhanced, offering a robust tool for investigating self-compassion across different cultures.

Joint Inversion of DC Resistivity and Gravity Data with Undulating Terrain Based on Deformed Hexahedral Mesh

In the field of mineral resource exploration, accurate imaging of subsurface structures is key to discovering and assessing potential mineral deposits. Traditional single geophysical methods, limited by terrain variations and their own constraints, can lead to divergent solutions and structural inconsistencies, affecting the reliability of exploration outcomes. To address these challenges, this paper presents a joint inversion method for three-dimensional direct current (DC) resistivity and gravity data based on a deformed hexahedral mesh. The article begins by outlining the current state of development of the method under study and proposes a research plan, followed by a detailed explanation of the theoretical basis and algorithmic implementation of the proposed method. Model tests confirm the advantages of the deformed hexahedral mesh in reducing terrain impacts and enhancing model resolution, demonstrating the optimization and complementarity of the resolution between the two methods after joint inversion. Finally, applying this method to actual data from the Huaniu Mountain area shows that joint inversion not only improves the consistency of the ore belt structure but also provides a more precise analysis for the quantitative interpretation of the distribution of underground mineral resources. This confirms the method’s effectiveness and potential in practical geological exploration.

Relationship between asymmetry of transverse sinus and difference in intraocular pressure Based on MRV imaging examination

Transverse sinus asymmetry refers to the inconsistencies in the shape structure, size or blood flow of the intracranial transverse sinus. Intraocular pressure difference refers to the obvious difference in intraocular pressure between the two eyes. Transversal sinus asymmetry may be correlated with intraocular pressure difference, but the mechanism of correlation is still unclear. To investigate the relationship between transverse sinus asymmetry and IOP differences based on MRV examination, and to explore the possible mechanism. Patients with transverse sinus asymmetry were selected and examined using the MRV technique. At the same time, the patients' IOP was measured using standard methods of IOP measurement. Correlation analysis and statistical methods were used to evaluate the association between transverse sinus asymmetry and IOP differences. There was a statistically significant distinction observed between groups I and V (Z=6.78, P<0.01). Significant variations were also noted in the intraocular pressures across all groups, encompassing the average measurements of the right eye and left eye, along with the variance between the two (right eye: F=15.43, P<0.01; left eye: F=4.62, P=0.002; variance between eyes: F=41.79, P<0.01). The asymmetry of the transverse sinus exhibited a negative relationship with the intraocular pressure of the right eye (r=0.51, P<0.01) and the difference between the pressures of the two eyes (r=0.79, P<0.01); no significant association was found between the asymmetry and the left eye's intraocular pressure. In conclusion, a certain correlation exists between the intraocular pressures of the left and right eyes and the morphology of the transverse sinus. When the transverse sinus is thicker on one side, the corresponding drainage veins are thicker, resulting in lower intraocular pressure on that same side.

GNN-based structural information to improve DNN-based basal ganglia segmentation in children following early brain lesion

Analyzing the basal ganglia following an early brain lesion is crucial due to their noteworthy role in sensory–motor functions. However, the segmentation of these subcortical structures on MRI is challenging in children and is further complicated by the presence of a lesion. Although current deep neural networks (DNN) perform well in segmenting subcortical brain structures in healthy brains, they lack robustness when faced with lesion variability, leading to structural inconsistencies. Given the established spatial organization of the basal ganglia, we propose enhancing the DNN-based segmentation through post-processing with a graph neural network (GNN). The GNN conducts node classification on graphs encoding both class probabilities and spatial information regarding the regions segmented by the DNN. In this study, we focus on neonatal arterial ischemic stroke (NAIS) in children. The approach is evaluated on both healthy children and children after NAIS using three DNN backbones: U-Net, UNETr, and MSGSE-Net. The results show an improvement in segmentation performance, with an increase in the median Dice score by up to 4% and a reduction in the median Hausdorff distance (HD) by up to 93% for healthy children (from 36.45 to 2.57) and up to 91% for children suffering from NAIS (from 40.64 to 3.50). The performance of the method is compared with atlas-based methods. Severe cases of neonatal stroke result in a decline in performance in the injured hemisphere, without negatively affecting the segmentation of the contra-injured hemisphere. Furthermore, the approach demonstrates resilience to small training datasets, a widespread challenge in the medical field, particularly in pediatrics and for rare pathologies.

Operative time and relative value units for total shoulder arthroplasty based on pathology in the United States

BackgroundDespite total shoulder arthroplasty (TSA) and reverse TSA (rTSA) being fundamentally different procedures, and indicated in different pathologies (rTSA for rotator cuff deficiency [RCD] and proximal humeral fractures [PHFx] and anatomic TSA [aTSA] for glenohumeral osteoarthritis [GHOA]), they have the same Current Procedural Terminology (CPT) code (23472). This paper’s aim is to investigate differences in operative time and work-related value units (wRVUs) per hour among these pathologies, and ultimately determine if there is a need to assign separate CPTs for aTSA and rTSA. MethodsA retrospective cohort of data from the American College of Surgeons–National Surgical Quality Improvement Program was collected, all patients who underwent aTSA or rTSA (CPT: 23472) between the years of 2006 and 2019 for diagnoses of GHOA, RCD, and PHFx were included. Data collected included patient age, body mass index, operative time, and wRVUs per hour. ResultsCompared to GHOA (reference group), the average operative time for the RCD cohort was 12.242 minutes shorter (P < .001), while the wRVUs were higher by 1.627 (P < .001). The average operative time for rTSAs in the PHFx cohort were 17.615 minutes longer (P < .001), while the wRVUs were lower by 2.205 (P < .001). ConclusionThe average operative time for rTSAs for both RCDs and PHFx were longer than that for aTSAs for GHOA. Additionally, wRVUs were lower for rTSAs for RCD and PHFx compared to aTSAs for GHOA. This elucidates inconsistency in reimbursement structure for the procedures, which should be revisited.

On the use of GNN-based structural information to improve CNN-based semantic image segmentation

Convolutional neural networks (CNNs) are widely used for semantic image segmentation across various fields (medicine, robotics), capturing local pixel dependencies for good results. Nevertheless, CNNs struggle to grasp global contextual representations, sometimes leading to structural inconsistencies. Recent approaches aim to broaden their scope using attention mechanisms or deep models, resulting in heavy-weight architectures. To boost CNN performance in semantic segmentation, we propose using a graph neural network (GNN) as a post-processing step. The GNN conducts node classification on appropriately coarsened graphs encoding class probabilities and structural information related to regions segmented by the CNN. The proposal, applicable to any CNN producing a segmentation map, is evaluated on several CNN architectures, using two public datasets (FASSEG and IBSR), with four graph convolution operators. Results reveal performance improvements, enhancing on average the Hausdorff distance by 24.3% on FASSEG and by 74.0% on IBSR. Furthermore, our approach demonstrates resilience to small training datasets.

DiG-In-GNN: Discriminative Feature Guided GNN-Based Fraud Detector against Inconsistencies in Multi-Relation Fraud Graph

Fraud detection on multi-relation graphs aims to identify fraudsters in graphs. Graph Neural Network (GNN) models leverage graph structures to pass messages from neighbors to the target nodes, thereby enriching the representations of those target nodes. However, feature and structural inconsistency in the graph, owing to fraudsters' camouflage behaviors, diminish the suspiciousness of fraud nodes which hinders the effectiveness of GNN-based models. In this work, we propose DiG-In-GNN, Discriminative Feature Guided GNN against Inconsistency, to dig into graphs for fraudsters. Specifically, we use multi-scale contrastive learning from the perspective of the neighborhood subgraph where the target node is located to generate guidance nodes to cope with the feature inconsistency. Then, guided by the guidance nodes, we conduct fine-grained neighbor selection through reinforcement learning for each neighbor node to precisely filter nodes that can enhance the message passing and therefore alleviate structural inconsistency. Finally, the two modules are integrated together to obtain discriminable representations of the nodes. Experiments on three fraud detection datasets demonstrate the superiority of the proposed method DiG-In-GNN, which obtains up to 20.73% improvement over previous state-of-the-art methods. Our code can be found at https://github.com/GraphBerry/DiG-In-GNN.

O121: Advancing Surgical Innovations: A Novel Approach to Engineering an Off-The-Shelf Bone-Tendon Junction Scaffold Suitable for Transplantation

Abstract Background Musculoskeletal injuries occurring at a staggering rate of 1.7 billion annually, frequently involve the complex bone-tendon junction (BTJ) often due to tear from tendon end due to cyclical strain. Current treatment options, varying from repair to reconstruction usually result in suboptimal outcomes due to structural inconsistencies. Methods In this novel study, we developed comprehensive approach to tackle this clinical challenge. We subjected BTJ tissue harvested from rabbit lower limbs (N=22) to decellularisation process. This involved 5-day demineralisation with 5% formic acid, followed by 8-day proprietary decellularisation method. Further, decellularised bone segments were immersed in Ca-P simulated body fluid for 24 hours to achieve mineral phase and enhance cell attachment. To facilitate recellularisation, adipose-derived stem cells were cultured in differentiating media for 14 days, differentiating into osteoblasts and fibroblasts for bone and tendon segments respectively. Cell phenotype was characterised using cell identification assays. Precise injection of differentiated cells into respective segments was conducted under cyclical mechanical loading with innovative stepper motor device, simulating native tissue physiology. Results Confirmation of effective decellularisation was established through histological characterisation and DNA quantification, with DNA content reduced to &amp;lt;50ng/mg (p&amp;lt;0.05) in bone segment. Successful recellularisation of decellularised scaffold and cell alignment in direction of mechanical load was confirmed through histological analysis on day 5. Comparative analysis revealed similarities in properties between control, remineralised, and recellularised bone, presenting this approach as a promising regenerative technique. Conclusion Our approach offers hope to potentially revolutionise clinical outcomes in this challenging domain by effectively replicating native tissue properties.

An MRI Study of Morphology, Asymmetry, and Sex Differences of Inferior Precentral Sulcus

Numerous studies utilizing magnetic resonance imaging (MRI) have observed sex and interhemispheric disparities in sulcal morphology, which could potentially underpin certain functional disparities in the human brain. Most of the existing research examines the precentral sulcus comprehensively, with a rare focus on its subsections. To explore the morphology, asymmetry, and sex disparities within the inferior precentral sulcus (IPCS), we acquired 3.0T magnetic resonance images from 92 right-handed Chinese adolescents. Brainvisa was used to reconstruct the IPCS structure and calculate its mean depth (MD). Based on the morphological patterns of IPCS, it was categorized into five distinct types. Additionally, we analyzed four different types of spatial relationships between IPCS and inferior frontal sulcus (IFS). There was a statistically significant sex disparity in the MD of IPCS, primarily observed in the right hemisphere. Females exhibited significantly greater asymmetry in the MD of IPCS compared to males. No statistically significant sex or hemispheric variations were identified in sulcal patterns. Our findings expand the comprehension of inconsistencies in sulcal structure, while also delivering an anatomical foundation for the study of related regions’ function.

Real‐time generation of spherical panoramic video using an omnidirectional multi‐camera system

AbstractThis paper presents a novel method for real‐time generation of seamless spherical panoramic videos from an omnidirectional multi‐camera system (OMS). Firstly, a multi‐view video alignment model called spherical projection constrained thin‐plate spline (SP‐TPS) was established and estimated using an approximately symmetrical seam‐line, maintaining the structure inconsistency around the seam‐line. Then, a look‐up table was designed to support real‐time processing of video re‐projection, video dodging and seam‐line updates. In the table, the overlapping areas in OMS multi‐view videos, the seam‐lines between spherical panoramas and OMS multi‐view videos and the pixel coordinate mapping relationship between spherical panoramas and OMS multi‐view videos were pre‐stored as a whole. Finally, a spherical panoramic video was outputted in real‐time through look‐up table computation under an ordinary GPU processor. The experiments were conducted on multi‐view video taken by “1 + 4” and “1 + 7” OMS, respectively. Experimental results demonstrate that compared with four state‐of‐the‐art methods reported in the literature and two bits of commercial software for video stitching, the proposed method excels in eliminating visual artefacts and demonstrates superior adaptability to scenes with varying depths of field. Assuming that OMS is not movable in the scene, this method can generate seamless spherical panoramic videos with a resolution of 8 K in real time, which is of great value to the surveillance field.

Влияние экзогенных факторов макросреды на воспроизводство кадров аграрного сектора экономики: теория и методология

Annually the number of rural settlements in Russia is decreasing, at the same time the number of rural areas without inhabitants is increasing. There are a sufficient number of factors influencing the reduction of rural set-tlements. But in our opinion, the most significant negative impact is exerted by the low level of remuneration of workers in the agricultural sector of the economy, as well as the very specifics of agricultural labor. The prob-lem of youth outflow, which is directly related to the lack of attractive social infrastructure in rural areas, has not been solved yet. To ensure staffing needs, a mechanism of sustainable reproduction of agricultural personnel is a necessary condition. Macro-environment factors have a significant impact on the nature of personnel re-production processes, since they largely determine the conditions for decision-making by participants in the reproduction process. The labor resources of the agricultural sector are characterized primarily by lower quality relative to other sectors of the economy. The reduction in the number of agrarian personnel, inconsistency in the qualitative structure of personnel cannot fully ensure the competitiveness of the industry, as well as fully realize the tasks facing the multi-structure agriculture-based economy. The article highlights the features of the process of reproduction of personnel in rural areas, which will allow structuring analytical data in the analysis of the system of reproduction of agricultural personnel. The aim of the present article is to develop a methodology for analyzing and systematizing the factors of the macro-environment of personnel reproduction. The study applies the methods of STEP-analysis and STEEPLE-analysis. The scientific novelty of this study lies in the systematization of macro-environment factors that affect the reproduction of rural personnel, based on which the methodology of three-level analysis is substantiated. The practical significance of the results obtained lies in the systematization of the factors of personnel reproduction in rural areas, based on Russian studies and taking into account, in particular, the size and socio-economic heterogeneity of territories. The result of the study is the identification, justification and systematization of macro-environment factors that influence the re-production of personnel in rural areas.

Stability of intermetallic compounds: Geometrical and topological aspects

We have applied a universal geometrical-topological approach to analyze 23507 robust crystal structures of intermetallic compounds, which are deposited in the Inorganic Crystal Structure Database. All the structures were represented as three-periodic nets and arranged into 2551 topological types each of which possesses a unique system of interatomic bonds. For all 104309 topologically different atoms in these structures their environments (local atomic configurations, LACs) were explored within the first and second coordination shells. In total, 5251 topologically distinct types of coordination polyhedra and 21450 types of two-shell LACs were distinguished and deposited into our interactive database system TopCryst. We have found that the local density of the nearest environment of an atom naturally depends on its coordination number (CN) with a maximum at CN = 9. It was shown that LACs at CN ≥ 9 follow the close packing model of hard balls with Slater's atomic radii. At lower CNs, covalent interactions make a significant contribution that results in a decrease of the local density. Resting upon the dependence between the local density and CN we have proposed criteria for the estimation of the geometric instability (disbalance) of both a separate LAC and the whole intermetallic structure. We have revealed that strong geometric disbalance can be caused by errors in the structural data, incorrect description of the crystal structure, non-metallic nature of the chemical bonding or metastability of the crystalline phase. Thus the instability criteria can serve as important indicators of the structure inconsistency that is especially useful for checking crystallographic information on intermetallics or validating the structural models predicted by theoretical methods.

Converting Concurrent Range Index Structure to Range Index Structure for Disaggregated Memory

In this work, we propose the Spread approach, which tailors a concurrent range index structure to a range index structure for disaggregated memory connected via RDMA (Remote Direct Memory Access). The Spread approach leverages the concept of tolerating transient inconsistencies in a concurrent range index structure to reduce the amount of expensive RDMA operations. Based on the Spread approach, we converted Blink-tree, a concurrent range index structure, to a range index structure for disaggregated memory called RF-tree. In our experimental study, RF-tree shows comparable performance to Sherman, a state-of-the-art and carefully crafted range index structure for disaggregated memory.

Research on seamless image stitching based on fast marching method

AbstractImage stitching is an important way to achieve large‐field high‐resolution imaging. The inconsistencies in brightness and structure and defects in ghosting, blurring and misalignment between images, which are inevitable and difficult to eliminate, make a challenge to image stitching, due to the external lighting environment and changes in camera pose and parameters. Here, a novel method is proposed to search for the optimal seamline based on the fast marching method, which can stitch large parallax images with high quality. A feature weight map is first formed based on the similarity in colour, edge, texture and saliency of the images. Then it is used as the cost value of the seamline to search for the optimal seamline by fast marching method. The results show that this new method is more efficient to reduce defects, such as ghosting, misalignment and chromatic aberration, and realize high quality image stitching compared with traditional stitching tools and methods, which provides a new perspective for image stitching technology.

Corey Wakeling. Beckett’s Laboratory: Experiments in the Theatre Enclosure

Beckett’s Laboratory argues that Beckett’s dramaturgy, rehearsal practices, collaborators, and legacy constitute a laboratory for experiments in human behaviour as well as developing new forms and uses for the theatre itself. Despite inconsistencies in structure and some rhetorical excesses, the book advances the cause of a more “open” Beckettian futurity.

Identifying climate model structural inconsistencies allows for tight constraint of aerosol radiative forcing

Abstract. Aerosol radiative forcing uncertainty affects estimates of climate sensitivity and limits model skill in terms of making climate projections. Efforts to improve the representations of physical processes in climate models, including extensive comparisons with observations, have not significantly constrained the range of possible aerosol forcing values. A far stronger constraint, in particular for the lower (most-negative) bound, can be achieved using global mean energy balance arguments based on observed changes in historical temperature. Here, we show that structural deficiencies in a climate model, revealed as inconsistencies among observationally constrained cloud properties in the model, limit the effectiveness of observational constraint of the uncertain physical processes. We sample the uncertainty in 37 model parameters related to aerosols, clouds, and radiation in a perturbed parameter ensemble of the UK Earth System Model and evaluate 1 million model variants (different parameter settings from Gaussian process emulators) against satellite-derived observations over several cloudy regions. Our analysis of a very large set of model variants exposes model internal inconsistencies that would not be apparent in a small set of model simulations, of an order that may be evaluated during model-tuning efforts. Incorporating observations associated with these inconsistencies weakens any forcing constraint because they require a wider range of parameter values to accommodate conflicting information. We show that, by neglecting variables associated with these inconsistencies, it is possible to reduce the parametric uncertainty in global mean aerosol forcing by more than 50 %, constraining it to a range (around −1.3 to −0.1 W m−2) in close agreement with energy balance constraints. Our estimated aerosol forcing range is the maximum feasible constraint using our structurally imperfect model and the chosen observations. Structural model developments targeted at the identified inconsistencies would enable a larger set of observations to be used for constraint, which would then very likely narrow the uncertainty further and possibly alter the central estimate. Such an approach provides a rigorous pathway to improved model realism and reduced uncertainty that has so far not been achieved through the normal model development approach.

Effects of Structural Inequalities and Misleading Discourse of Social Policymakers on African American families in God Help the Child

In sociological and anthropological studies of African American family formation and development, racial hierarchies, criminal violence, social policies, and systemic disparities are often ignored. This study emphasizes the gradual development of consequences of xenophobic attitude of the society that stigmatizes African American family culture in the United States. The prevalent approach in social sciences was to blame the victim on certain group membership or racial specification such as color, background, and physical traits. These structural inconsistencies have been undervalued or studied only occasionally and irregularly. This is qualitative study that analysis Toni Morrison’s Gold Help the Child in the light of a rethinking history, a postmodern notion. The textual analysis of the selected text reveals that that formative policy makers focused on Black people’s violence and individual level incongruities but ignored their fundamental problems and latent potentialities. The finding further shows that the lack of structural and systematic analysis misled the discourse of policy makers and more precisely often justified black violence that reflects cultural inferiority and unique experiences of legitimatizing all kinds of violence and negativity propogated against them.

Ambiguous Trends in the Regional Labor Market During the Ongoing Sanctions Policy

As a follow up study, the authors present the results of an assessment of very ambiguous trends in the regional labor market that have developed as a result of the extension of the sanctions policy. Along with the achievement of a record low level of unemployment, the formation of additional demand in the labor market, there are obvious disproportions in the dynamics of the socio-economic development of enterprises and organizations in the region. Meanwhile, an assessment of the emerging socio-economic situation showed the presence of a whole range of negative risks of destabilization, which may have adverse consequences for the functioning of the labor market in the medium term. The article highlights the structural imbalances that create unsatisfied demand, identifies conditions that can reduce the demand for labor due to structural inconsistencies, and analyzes the potential scale of the emerging excess labor supply. The study revealed that the starting points of bifurcation in the labor market will be associated with unfavorable trends in the demographics of organizations in the region. Disproportions in the dynamics of industrial production indices in the most important sectors of the economy are identified. We established that over the past year since the introduction of sanctions, there has been an increase in the share of unprofitable enterprises and organizations. The presented trends made it possible to identify the trajectories of the possible development of the labor market in the near future.

Structure Flow-Guided Network for Real Depth Super-resolution

Real depth super-resolution (DSR), unlike synthetic settings, is a challenging task due to the structural distortion and the edge noise caused by the natural degradation in real-world low-resolution (LR) depth maps. These defeats result in significant structure inconsistency between the depth map and the RGB guidance, which potentially confuses the RGB-structure guidance and thereby degrades the DSR quality. In this paper, we propose a novel structure flow-guided DSR framework, where a cross-modality flow map is learned to guide the RGB-structure information transferring for precise depth upsampling. Specifically, our framework consists of a cross-modality flow-guided upsampling network (CFUNet) and a flow-enhanced pyramid edge attention network (PEANet). CFUNet contains a trilateral self-attention module combining both the geometric and semantic correlations for reliable cross-modality flow learning. Then, the learned flow maps are combined with the grid-sampling mechanism for coarse high-resolution (HR) depth prediction. PEANet targets at integrating the learned flow map as the edge attention into a pyramid network to hierarchically learn the edge-focused guidance feature for depth edge refinement. Extensive experiments on real and synthetic DSR datasets verify that our approach achieves excellent performance compared to state-of-the-art methods. Our code is available at: https://github.com/Yuanjiayii/DSR-SFG.