Fault interpretation in seismic reflection data: an experiment analyzing the impact of conceptual model anchoring and vertical exaggeration

[EN]This paper presents an analysis on the limitations and advantages that some types of seismic data display present on the interpretation of the dataset

Fault interpretation in seismic reflection data: an experiment analysing the impact of conceptual model anchoring and vertical exaggeration

The use of conceptual models is essential in the in- terpretation of reflection seismic data. It allows interpreters to make geological sense of seismic data, which carries inherent uncertainty. However, conceptual models can create powerful anchors that prevent interpreters from reassessing and adapting their interpretations as part of the interpretation process, which can subsequently lead to flawed or erroneous outcomes. It is therefore critical to understand how conceptual models are generated and applied to reduce unwanted effects in interpretation results. Here we have tested how interpretation of vertically exaggerated seismic data influenced the creation and adoption of the conceptual models of 161 participants in a paper-based interpretation experiment. Participants were asked to interpret a series of faults and a horizon, offset by those faults, in a seismic section. The seismic section was randomly presented to the participants with different horizontal-vertical exaggeration (1 : 4 or 1 : 2). Statistical analysis of the results indicates that early anchoring to specific conceptual models had the most impact on interpretation outcome, with the degree of vertical exaggeration having a subdued influence. Three different conceptual models were adopted by participants, constrained by initial observations of the seismic data. Interpreted fault dip angles show no evidence of other constraints (e.g. from the application of accepted fault dip models). Our results provide evidence of biases in interpretation of uncertain geological and geophysical data, including the use of heuristics to form initial conceptual models and anchoring to these models, confirming the need for increased understanding and mitigation of these biases to improve interpretation outcomes

Association between Several Clinical and Radiological Determinants with Long-Term Clinical Progression and Good Prognosis of Lower Limb Osteoarthritis

OBJECTIVE: To investigate the factors associated with clinical progression and good prognosis in patients with lower limb osteoarthritis (OA). METHODS: Cohort study of 145 patients with OA in either knee, hip or both. Progression was defined as 1) new joint prosthesis or 2) increase in WOMAC pain or function score during 6-years follow-up above pre-defined thresholds. Patients without progression with decrease in WOMAC pain or function score lower than pre-defined thresholds were categorized as good prognosis. Relative risks (RRs) for progression and good prognosis with 95% confidence interval (95% CI) were calculated by comparing the highest tertile or category to the lowest tertile, for baseline determinants (age, sex, BMI, WOMAC pain and function scores, pain on physical examination, total range of motion (tROM), osteophytes and joint space narrowing (JSN) scores), and for worsening in WOMAC pain and function score in 1-year. Adjustments were performed for age, sex, and BMI. RESULTS: Follow-up was completed by 117 patients (81%, median age 60 years, 84% female); 62 (53%) and 31 patients (26%) showed progression and good prognosis, respectively. These following determinants were associated with progression: pain on physical examination (RR 1.2 (1.0 to 1.5)); tROM (1.4 (1.1 to 1.6); worsening in WOMAC pain (1.9 (1.2 to 2.3)); worsening in WOMAC function (2.4 (1.7 to 2.6)); osteophytes 1.5 (1.0 to 1.8); and JSN scores (2.3 (1.5 to 2.7)). Worsening in WOMAC pain (0.1 (0.1 to 0.8)) and function score (0.1 (0.1 to 0.7)), were negatively associated with good prognosis. CONCLUSION: Worsening of self-reported pain and function in one year, limited tROM and higher osteophytes and JSN scores were associated with clinical progression. Worsening in WOMAC pain and function score in 1- year were associated with lower risk to have good prognosis. These findings help to inform patients with regard to their OA prognosis

Clusters of biochemical markers are associated with radiographic subtypes of osteoarthritis (OA) in subject with familial OA at multiple sites. The GARP study

SummaryObjectiveTo assess the relationship of biochemical markers and radiographic signs of osteoarthritis (ROA) in the subjects with symptomatic osteoarthritis (OA) at multiple sites of the Genetics osteoARthritis and Progression (GARP) study.MethodsWe have measured eight biochemical markers, representing tissue turnover of cartilage, bone, synovium, and inflammation. ROA was assessed in the knees, hips, hands, vertebral facet joints and spinal disc degeneration (DD) by using the Kellgren score. A proportionate score was subsequently made for each joint location based on the number of joints with ROA. Principal component and linear mixed model analyses were applied to analyze the data.ResultsThree different clusters of markers were identified that may reflect different pathophysiological processes of OA. The first component appeared to be reflected by structural markers of cartilage and bone turnover and associated especially in subjects with hip ROA. The second component was reflected by a marker of inflammation and was associated with knee ROA, high Western Ontario and McMaster Universities (WOMAC) scores and body mass index (BMI). The third component included markers of cartilage turnover and was associated with ROA at hands, spine as well as age. High familial aggregation was observed for serum cartilage oligomeric matrix protein (S-COMP) (70%) and serum N-propeptide of collagen type IIA (S-PIIANP) (62%).ConclusionUsing a large well-characterized study and eight biochemical markers, we were able to observe three components that may reflect different molecular mechanisms (bone, cartilage, synovium turnover and inflammation). Our data suggested that these components contribute differently to ROA at different joint sites

The (3×3)-SiC-(¯1¯1¯1) Reconstruction: Atomic Structure of the Graphene Precursor Surface from a Large-Scale First-Principles Structure Search

Silicon carbide (SiC) is an excellent substrate for growth and manipulation of large scale, high quality epitaxial graphene. On the carbon face (the ($\bar{1}\bar{1}\bar{1}$) or $(000\bar{1}$) face, depending on the polytype), the onset of graphene growth is intertwined with the formation of several competing surface phases, among them a (3$\times$3) precursor phase suspected to hinder the onset of controlled, near-equilibrium growth of graphene. Despite more than two decades of research, the precise atomic structure of this phase is still unclear. We present a new model of the (3$\times$3)-SiC-($\bar{1}\bar{1}\bar{1}$) reconstruction, derived from an {\it ab initio} random structure search based on density functional theory including van der Waals effects. The structure consists of a simple pattern of five Si adatoms in bridging and on-top positions on an underlying, C-terminated substrate layer, leaving one C atom per (3$\times$3) unit cell formally unsaturated. Simulated scanning tunneling microscopy (STM) images are in excellent agreement with previously reported experimental STM images

Bone marrow edema-like lesions change in volume in the majority of patients with osteoarthritis; associations with clinical features

It has been suggested that bone marrow edema-like (BME) lesions in the knee are associated with progression of osteoarthritis (OA). The purpose of our study in patients with OA was to evaluate prospectively changes of BME lesions over 2 years and their relationship with clinical features. Magnetic resonance (MR) images of the knee were obtained from 182 patients (20% male; aged 43–76 years; mean age 59 years) who had been diagnosed with familial symptomatic OA at multiple joint sites. MR images were made at baseline and at 2 years follow-up. BME lesions in 2 years were associated with clinical features assessed by Western Ontario and McMaster Universities Osteoarthritis (WOMAC) scores. A total of 327 BME lesions were recorded. Total size of BME lesions changed in 90 patients (66%). Size of individual lesions changed in 147 foci (45%): new lesions appeared in 69 (21%), existing lesions disappeared in 32 (10%), increased in size in 26 (8%) and decreased in size in 20 (6%) lesions. Increase or decrease of BME lesions, over a 2-year time period, was not associated with severity of WOMAC scores. BME lesions fluctuated in the majority of patients with OA over a 2-year time period. These changes were not associated with severity of WOMAC scores at the study end point

GaitSmart motion analysis compared to commonly used function outcome measures in the IMI-APPROACH knee osteoarthritis cohort

[Abstract] Background: There are multiple measures for assessment of physical function in knee osteoarthritis (OA), but each has its strengths and limitations. The GaitSmart® system, which uses inertial measurement units (IMUs), might be a user-friendly and objective method to assess function. This study evaluates the validity and responsiveness of GaitSmart® motion analysis as a function measurement in knee OA and compares this to Knee Injury and Osteoarthritis Outcome Score (KOOS), Short Form 36 Health Survey (SF-36), 30s chair stand test, and 40m self-paced walk test. Methods: The 2-year Innovative Medicines Initiative-Applied Public-Private Research enabling OsteoArthritis Clinical Headway (IMI-APPROACH) knee OA cohort was conducted between January 2018 and April 2021. For this study, available baseline and 6 months follow-up data (n = 262) was used. Principal component analysis was used to investigate whether above mentioned function instruments could represent one or more function domains. Subsequently, linear regression was used to explore the association between GaitSmart® parameters and those function domains. In addition, standardized response means, effect sizes and t-tests were calculated to evaluate the ability of GaitSmart® to differentiate between good and poor general health (based on SF-36). Lastly, the responsiveness of GaitSmart® to detect changes in function was determined. Results: KOOS, SF-36, 30s chair test and 40m self-paced walk test were first combined into one function domain (total function). Thereafter, two function domains were substracted related to either performance based (objective function) or self-reported (subjective function) function. Linear regression resulted in the highest R2 for the total function domain: 0.314 (R2 for objective and subjective function were 0.252 and 0.142, respectively.). Furthermore, GaitSmart® was able to distinguish a difference in general health status, and is responsive to changes in the different aspects of objective function (Standardized response mean (SRMs) up to 0.74). Conclusion: GaitSmart® analysis can reflect performance based and self-reported function and may be of value in the evaluation of function in knee OA. Future studies are warranted to validate whether GaitSmart® can be used as clinical outcome measure in OA research and clinical practice

Farmer seed networks make a limited contribution to agriculture? Four common misconceptions

The importance of seed provisioning in food security and nutrition, agricultural development and rural livelihoods, and agrobiodiversity and germplasm conservation is well accepted by policy makers, practitioners and researchers. The role of farmer seed networks is less well understood and yet is central to debates on current issues ranging from seed sovereignty and rights for farmers to GMOs and the conservation of crop germplasm. In this paper we identify four common misconceptions regarding the nature and importance of farmer seed networks today. (1) Farmer seed networks are inefficient for seed dissemination. (2) Farmer seed networks are closed, conservative systems. (3) Farmer seed networks provide ready, egalitarian access to seed. (4) Farmer seed networks are destined to weaken and disappear. We challenge these misconceptions by drawing upon recent research findings and the authors’ collective field experience in studying farmer seed systems in Africa, Europe, Latin America and Oceania. Priorities for future research are suggested that would advance our understanding of seed networks and better inform agricultural and food policy