A combined estimator using TEC and b-value for large earthquake prediction

[EN] Ionospheric anomalies have been shown to occur a few days before several large earthquakes. The published works normally address examples limited in time (a single event or few of them) or space (a particular geographic area), so that a clear method based on these anomalies which consistently yields the place and magnitude of the forthcoming earthquake, anytime and anywhere on earth, has not been presented so far. The current research is aimed at prediction of large earthquakes, that is with magnitude M-w 7 or higher. It uses as data bank all significant earthquakes occurred worldwide in the period from January 1, 2011 to December 31, 2018. The first purpose of the research is to improve the use of ionospheric anomalies in the form of TEC grids for earthquake prediction. A space-time TEC variation estimator especially designed for earthquake prediction will show the advantages with respect to the use of simple TEC values. Further, taking advantage of the well-known predictive abilities of the Gutenberg-Richter law's b-value, a combined estimator based on both TEC anomalies and b-values will be designed and shown to improve prediction performance even more.Baselga Moreno, S. (2020). A combined estimator using TEC and b-value for large earthquake prediction. Acta Geodaetica et Geophysica Hungarica. 55(1):63-82. https://doi.org/10.1007/s40328-019-00281-5S6382551Abordán A, Szabó NP (2018) Metropolis algorithm driven factor analysis for lithological characterization of shallow marine sediments. Acta Geod Geophys 53:189–199. https://doi.org/10.1007/s40328-017-0210-zAkhoondzadeh M, Saradjian MR (2011) TEC variations analysis concerning Haiti (January 12, 2010) and Samoa (September 29, 2009) earthquakes. Adv Space Res 47(1):94–104. https://doi.org/10.1016/j.asr.2010.07.024Asencio-Cortés G, Morales-Esteban A, Shang X, Martínez-Álvarez F (2018) Earthquake prediction in California using regression algorithms and cloud-based big data infrastructure. Comput Geosci 115:198–210. https://doi.org/10.1016/j.cageo.2017.10.011Baselga S (2018) Fibonacci lattices for the evaluation and optimization of map projections. Comput Geosci 117:1–8. https://doi.org/10.1016/j.cageo.2018.04.012Baselga S (2019) TestGrids: evaluating and optimizing map projections. J Surv Eng 144(3):04019004Berényi KA, Barta V, Kis Á (2018) Midlatitude ionospheric F2-layer response to eruptive solar events-caused geomagnetic disturbances over Hungary during the maximum of the solar cycle 24: a case study. Adv Space Res 61(5):1230–1243. https://doi.org/10.1016/j.asr.2017.12.021Biswas A, Sharma SP (2017) Interpretation of self-potential anomaly over 2-D inclined thick sheet structures and analysis of uncertainty using very fast simulated annealing global optimization. Acta Geod Geophys 52:439–455. https://doi.org/10.1007/s40328-016-0176-2Borgohain JM, Borah K, Biswas R, Bora DK (2018) Seismic b-value anomalies prior to the 3rd January 2016, Mw = 6.7 Manipur earthquake of northeast India. J Asian Earth Sci 154:42–48. https://doi.org/10.1016/j.jseaes.2017.12.013Buonsanto M (1999) Ionospheric storms—a review. Space Sci Rev 88:563–601. https://doi.org/10.1023/A:1005107532631Buskirk RE, Frohlich CL, Latham GV (1981) Unusual animal behavior before earthquakes: a review of possible sensory mechanisms. Rev Geophys 19:247–270. https://doi.org/10.1029/RG019i002p00247Dobrovolsky IR, Zubkov SI, Myachkin VI (1979) Estimation of the size of earthquake preparation zones. Pure appl Geophys 117:1025–1044. https://doi.org/10.1007/BF00876083Dogan U, Ergintav S, Skone S, Arslan N, Oz D (2011) Monitoring of the ionosphere TEC variations during the 17th August 1999 Izmit earthquake using GPS data. Earth Planets Space 63(12):1183–1192. https://doi.org/10.5047/eps.2011.07.020Florido E, Martínez-Álvarez F, Morales-Esteban A, Reyes J, Aznarte-Mellado JL (2015) Detecting precursory patterns to enhance earthquake prediction in Chile. Comput Geosci 76:112–120. https://doi.org/10.1016/j.cageo.2014.12.002Florido E, Asencio-Cortés G, Aznarte JL, Rubio-Escudero C, Martínez-Álvarez F (2018) A novel tree-based algorithm to discover seismic patterns in earthquake catalogs. Comput Geosci 115:96–104. https://doi.org/10.1016/j.cageo.2018.03.005Freund FT, Kulahci IG, Cyr G, Ling J, Winnick M, Tregloan-Reed J, Freund MM (2009) Air ionization at rock surfaces and pre-earthquake signals. J Atmos Sol Terr Phys 71(17–18):1824–1834. https://doi.org/10.1016/j.jastp.2009.07.013Gopinath S, Prince PR (2018) Nonextensive and distance-based entropy analysis on the influence of sunspot variability in magnetospheric dynamics. Acta Geod Geophys 53:639–659. https://doi.org/10.1007/s40328-018-0235-yGrant RA, Halliday T (2010) Predicting the unpredictable; evidence of pre-seismic anticipatory behaviour in the common toad. J Zool 281:263–271. https://doi.org/10.1111/j.1469-7998.2010.00700.xGrant RA, Halliday T, Balderer WP, Leuenberger F, Newcomer M, Cyr G, Freund FT (2011) Ground water chemistry changes before major earthquakes and possible effects on animals. Int J Environ Res Public Health 8:1936–1956. https://doi.org/10.3390/ijerph8061936Guo J, Yu H, Li W, Liu X, Kong Q, Zhao C (2017) Total electron content anomalies before Mw 6.0 + earthquakes in the seismic zone of southwest China between 2001 and 2013. J Test Eval 45(1):131–139. https://doi.org/10.1520/JTE20160032International GNSS Service (2019) IGS products. https://www.igs.org/products. Accessed 5 May 2019Kane RP (2005) Ionospheric foF2 anomalies during some intense geomagnetic storms. Ann Geophys 23:2487–2499. https://doi.org/10.5194/angeo-23-2487-2005Kulhanek O, Persson L, Nuannin P (2018) Variations of b-values preceding large earthquakes in the shallow subduction zones of Cocos and Nazca plates. J South Am Earth Sci 82:207–214. https://doi.org/10.1016/j.jsames.2018.01.005Lin JW (2010) Ionospheric total electron content (TEC) anomalies associated with earthquakes through Karhunen–Loéve Transform (KLT). Terr Atmos Ocean Sci 21(2):253–265. https://doi.org/10.3319/TAO.2009.06.11.01(T)Lin JW (2011) Latitude-time total electron content anomalies as precursors to Japan’s large earthquakes associated with principal component analysis. Int J Geophys. https://doi.org/10.1155/2011/763527Liu JY, Chen YI, Chuo YJ, Chen CS (2006) A statistical investigation of preearthquake ionospheric anomaly. J Geophys Res 111:A05304. https://doi.org/10.1029/2005JA011333Liu JY, Chen YI, Chen CH, Liu CY, Chen CY, Nishihashi M, Li JZ, Xia YQ, Oyama KI, Hattori K, Lin CH (2009) Seismoionospheric GPS total electron content anomalies observed before the 12 May 2008 Mw7.9 Wenchuan earthquake. J Geophys Res 114:A04320. https://doi.org/10.1029/2008JA013698Nuannin P, Kulhanek O, Persson L (2005) Spatial and temporal b value anomalies preceding the devastating off coast of NW Sumatra earthquake of December 26, 2004. Geophys Res Lett 32:L11307. https://doi.org/10.1029/2005GL022679Pardalos PM, Romeijn HE (eds) (2002) Handbook of global optimization, vols. 1 & 2. Kluwer, DordretchPaul B, De BK, Guha A (2018) Latitudinal variation of F-region ionospheric response during three strongest geomagnetic storms of 2015. Acta Geod Geophys 53:579–606. https://doi.org/10.1007/s40328-018-0221-4Pulinets S, Boyarchuk K (2004) Ionospheric precursors of earthquakes. Springer, BerlinPulinets SA, Legen’ka AD, Gaivoronskaya TV, Depuev VKh (2003) Main phenomenological features of ionospheric precursors of strong earthquakes. J Atmos Sol Terr Phys 65:1337–1347. https://doi.org/10.1016/j.jastp.2003.07.011Reyes J, Morales-Esteban A, Martínez-Álvarez F (2013) Neural networks to predict earthquakes in Chile. Appl Soft Comput 13:1314–1328. https://doi.org/10.1016/j.asoc.2012.10.014Şentürk E, Çepni MS (2018a) A statistical analysis of seismo ionospheric TEC anomalies before 63 Mw ≥ 5.0 earthquakes in Turkey during 2003–2016. Acta Geophys 66:1495–1507. https://doi.org/10.1007/s11600-018-0214-2Şentürk E, Çepni MS (2018b) Ionospheric temporal variations over the region of Turkey: a study based on long-time TEC observations. Acta Geod Geophys 53:623–637. https://doi.org/10.1007/s40328-018-0233-0Şentürk E, Çepni MS (2019) Performance of different weighting and surface fitting techniques on station-wise TEC calculation and modified sine weighting supported by the sun effect. J Spat Sci 64(2):209–220. https://doi.org/10.1080/14498596.2017.1417169Şentürk E, Livaoğlu H, Çepni MS (2019) A comprehensive analysis of ionospheric anomalies before the mw 7.1 Van earthquake on 23 October 2011. J Navig 72(3):702–720. https://doi.org/10.1017/S0373463318000826Shiuly A, Roy N (2018) A generalized VS–N correlation using various regression analysis and genetic algorithm. Acta Geod Geophys 53:479–502. https://doi.org/10.1007/s40328-018-0220-5U.S. Geological Survey (2019) Earthquake catalog. https://earthquake.usgs.gov/earthquakes/search/. Accessed 5 May 2019Warwick JW, Stoker C, Meyer TR (1982) Radio emission associated with rock fracture: possible application to the Great Chilean Earthquake of May 22, 1960. J Geophys Res Solid Earth 87:2851–2859. https://doi.org/10.1029/JB087iB04p02851Yao Y, Chen P, Wu H, Zhang S, Peng W (2012) Analysis of ionospheric anomalies before the 2011 M w 9.0 Japan earthquake. Chin Sci Bull 57(5):500–510. https://doi.org/10.1007/s11434-011-4851-yZakharenkova IE, Shagimuratov II, Krankowski A (2007a) Features of the ionosphere behavior before the Kythira 2006 earthquake. Acta Geophys 55(4):524–534. https://doi.org/10.2478/s11600-007-0031-5Zakharenkova IE, Shagimuratov II, Krankowski A, Lagovsky AF (2007b) Precursory phenomena observed in the total electron content measurements before great Hokkaido earthquake of September 25, 2003 (M = 8.3). Stud Geophys Geod 51(2):267–278. https://doi.org/10.1007/s11200-007-0014-

Predictive value of atrial electromechanical delay for atrial fibrillation recurrence

Background: We investigated the predictive value of atrial electromechanical delay (AEMD) for recurrence of atrial fibrillation (AF) at 1-month after cardioversion.Methods: Seventy-seven patients with persistent AF were evaluated and finally 50 patients (12 men, 38 women) were included. All patients underwent transthoracic electrical DC cardioversion under amiodarone treatment. AEMD was measured as the time interval from the onset of the P wave on electrogram (ECG) to the beginning of late diastolic wave (Am) from the ventricular annulus and atrial walls on tissue Doppler imaging, in the apical 4-chamber view 24 h after cardiversion. P wave maximum-duration (Pmax), P wave minimum-duration (Pmin) and P wave dispersion-duration (Pdis) were calculated on the 12-lead ECG at 24-h postcardioversion. We followed the heart rate and rhythm by 12-lead ECG at 24-h, 1-week and 1-month.Results: At 1-month follow-up after cardioversion, 28 (56%) patients were in sinus rhythm (SR), whereas 22 (44%) patients reverted to AF. The AEMD durations were longer in AF group than SR group (p < 0.001) and were signifi cantly correlated with Pmax and Pdis (p < 0.001 for both). For AF recurrence; duration of AF, left atrial (LA) diameter, maximum LA volume index, mitral A velocity and LA lateral AEMD were significant parameters in univariate-analysis, however LA lateral AEMD was the only significant parameter in multivariate-analysis (OR: 1.46; 95% CI 1.02–2.11; p = 0.03).Conclusions: Our results suggest that AEMD is associated with an increased risk of recurrence of AF within 1-month. These data may have implications for the identification of patients who are most likely to experience substantial benefit from cardiversion therapy for AF

Postresectional lung injury in thoracic surgery pre and intraoperative risk factors: a retrospective clinical study of a hundred forty-three cases

<p>Abstract</p> <p>Introduction</p> <p>Acute respiratory dysfunction syndrome (ARDS), defined as acute hypoxemia accompanied by radiographic pulmonary infiltrates without a clearly identifiable cause, is a major cause of morbidity and mortality after pulmonary resection. The aim of the study was to determine the pre and intraoperative factors associated with ARDS after pulmonary resection retrospectively.</p> <p>Methods</p> <p>Patients undergoing elective pulmonary resection at Adnan Menderes University Medical Faculty Thoracic Surgery Department from January 2005 to February 2010 were included in this retrospective study. The authors collected data on demographics, relevant co-morbidities, the American Society of Anesthesiologists (ASA) Physical Status classification score, pulmonary function tests, type of operation, duration of surgery and intraoperative fluid administration (fluid therapy and blood products). The primary outcome measure was postoperative ARDS, defined as the need for continuation of mechanical ventilation for greater than 48-hours postoperatively or the need for reinstitution of mechanical ventilation after extubation. Statistical analysis was performed with Fisher exact test for categorical variables and logistic regression analysis for continuous variables.</p> <p>Results</p> <p>Of one hundred forty-three pulmonary resection patients, 11 (7.5%) developed postoperative ARDS. Alcohol abuse (p = 0.01, OR = 39.6), ASA score (p = 0.001, OR: 1257.3), resection type (p = 0.032, OR = 28.6) and fresh frozen plasma (FFP)(p = 0.027, OR = 1.4) were the factors found to be statistically significant.</p> <p>Conclusion</p> <p>In the light of the current study, lung injury after lung resection has a high mortality. Preoperative and postoperative risk factor were significant predictors of postoperative lung injury.</p

The 2010 very high energy gamma-ray flare & 10 years of multi-wavelength observations of M 87

Abridged: The giant radio galaxy M 87 with its proximity, famous jet, and very massive black hole provides a unique opportunity to investigate the origin of very high energy (VHE; E>100 GeV) gamma-ray emission generated in relativistic outflows and the surroundings of super-massive black holes. M 87 has been established as a VHE gamma-ray emitter since 2006. The VHE gamma-ray emission displays strong variability on timescales as short as a day. In this paper, results from a joint VHE monitoring campaign on M 87 by the MAGIC and VERITAS instruments in 2010 are reported. During the campaign, a flare at VHE was detected triggering further observations at VHE (H.E.S.S.), X-rays (Chandra), and radio (43 GHz VLBA). The excellent sampling of the VHE gamma-ray light curve enables one to derive a precise temporal characterization of the flare: the single, isolated flare is well described by a two-sided exponential function with significantly different flux rise and decay times. While the overall variability pattern of the 2010 flare appears somewhat different from that of previous VHE flares in 2005 and 2008, they share very similar timescales (~day), peak fluxes (Phi(>0.35 TeV) ~= (1-3) x 10^-11 ph cm^-2 s^-1), and VHE spectra. 43 GHz VLBA radio observations of the inner jet regions indicate no enhanced flux in 2010 in contrast to observations in 2008, where an increase of the radio flux of the innermost core regions coincided with a VHE flare. On the other hand, Chandra X-ray observations taken ~3 days after the peak of the VHE gamma-ray emission reveal an enhanced flux from the core. The long-term (2001-2010) multi-wavelength light curve of M 87, spanning from radio to VHE and including data from HST, LT, VLA and EVN, is used to further investigate the origin of the VHE gamma-ray emission. No unique, common MWL signature of the three VHE flares has been identified.Comment: 19 pages, 5 figures; Corresponding authors: M. Raue, L. Stawarz, D. Mazin, P. Colin, C. M. Hui, M. Beilicke; Fig. 1 lightcurve data available online: http://www.desy.de/~mraue/m87

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Correction to: Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

The original version of this article unfortunately contained a mistake

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat