3D induction log modelling with integral equation method and domain decomposition preconditioning

The deployment of electromagnetic (EM) induction tools while drilling is one of the standard routines for assisting the geosteering decision-making process. The conductivity distribution obtained through the inversion of the EM induction log can provide important information about the geological structure around the borehole. To image the 3D geological structure in the subsurface, 3D inversion of the EM induction log is required. Because the inversion process is mainly dependent on forward modelling, the use of fast and accurate forward modelling is essential. In this paper, we present an improved version of the integral equation (IE) based modelling technique for general anisotropic media with domain decomposition preconditioning. The discretised IE after domain decomposition equals a fixed-point equation that is solved iteratively with either the block Gauss-Seidel or Jacobi preconditioning. Within each iteration, the inverse of the block matrix is computed using a Krylov subspace method instead of a direct solver. An additional reduction in computational time is obtained by using an adaptive relative residual stopping criterion in the iterative solver. Numerical experiments show a maximum reduction in computational time of 35 per cent compared to solving the full-domain IE with a conventional GMRES solver. Additionally, the reduction of memory requirement for covering a large area of the induction tool sensitivity enables acceleration with limited GPU memory. Hence, we conclude that the domain decomposition method is improving the efficiency of the IE method by reducing the computation time and memory requirement.Comment: This article is a manuscript submitted to Geophysical Journal Internationa

Distributed versus massed training: efficiency of training psychomotor skills

Virtual reality simulators have shown to be valid and useful tools for training psychomotor skills for endoscopic surgery. Discussion arises how to integrate these simulators into the surgical training curriculum. Distributed training is referred to as short training periods, with rest periods in between. Massed training is training in continuous and longer training blocks. This study investigates the difference between distributed and massed training on the initial development and retention of psychomotor skills on a virtual reality simulator. Four groups of eight medical students lacking any experience in endoscopic training were created. Two groups trained in a distributed fashion, one group trained in a massed fashion and the last group not at all (control group). All performed a post-test immediately after finishing their training schedule. Two months after this test a second post- test was performed. The one-way analysis of variance (ANOVA) with Post-Hoc test Tukey-Bonferoni was used to determine differences in mean scores between the four groups, whereas a pvalue ≤0.05 was considered to be statistically significant. Distributed training resulted in higher scores and a better retention of relevant psychomotor skills. Distributed as well as massed training resulted in better scores and retention of skills than no training at all. Our study clearly shows that distributed training yields better results in psychomotor endoscopic skills. Therefore, in order to train as efficient as possible, training programs should be (re)-programmed accordingly

Will the Playstation generation become better endoscopic surgeons?

A frequently heard comment is that the current "Playstation generation" will have superior baseline psychomotor skills. However, research has provided inconsistent results on this matter. The purpose of this study was to investigate whether the "Playstation generation" shows superior baseline psychomotor skills for endoscopic surgery on a virtual reality simulator. The 46 study participants were interns (mean age 24 years) of the department of surgery and schoolchildren (mean age 12.5 years) of the first year of a secondary school. Participants were divided into four groups: 10 interns with videogame experience and 10 without, 13 schoolchildren with videogame experience and 13 without. They performed four tasks twice on a virtual reality simulator for basic endoscopic skills. The one-way analysis of variance (ANOVA) with post hoc test Tukey-Bonferroni and the independent Student's t test were used to determine differences in mean scores. Interns with videogame experience scored significantly higher on total score (93 vs. 74.5; p=0.014) compared with interns without this experience. There was a nonsignificant difference in mean total scores between the group of schoolchildren with and those without videogame experience (61.69 vs. 55.46; p=0.411). The same accounts for interns with regard to mean scores on efficiency (50.7 vs. 38.9; p=0.011) and speed (18.8 vs. 14.3; p=0.023). In the group of schoolchildren, there was no statistical difference for efficiency (32.69 vs. 27.31; p=0.218) or speed (13.92 vs. 13.15; p=0.54). The scores concerning precision parameters did not differ for interns (23.5 vs. 21.3; p=0.79) or for schoolchildren (mean 15.08 vs. 15; p=0.979). Our study results did not predict an advantage of videogame experience in children with regard to superior psychomotor skills for endoscopic surgery. However, at adult age, a difference in favor of gaming is present. The next generation of surgeons might benefit from videogame experience during their childhoo

Genome-wide identification of directed gene networks using large-scale population genomics data

Identification of causal drivers behind regulatory gene networks is crucial in understanding gene function. Here, we develop a method for the large-scale inference of gene–gene interactions in observational population genomics data that are both directed (using local genetic instruments as causal anchors, akin to Mendelian Randomization) and specific (by controlling for linkage disequilibrium and pleiotropy). Analysis of genotype and whole-blood RNA-sequencing data from 3072 individuals identified 49 genes as drivers of downstream transcriptional changes (Wald P < 7 × 10−10), among which transcription factors were overrepresented (Fisher’s P = 3.3 × 10−7). Our analysis suggests new gene functions and targets, including for SENP7 (zinc-finger genes involved in retroviral repression) and BCL2A1 (target genes possibly involved in auditory dysfunction). Our work highlights the utility of population genomics data in deriving directed gene expression networks. A resource of trans-effects for all 6600 genes with a genetic instrument can be explored individually using a web-based browser

On-chip silicon Mach-Zehnder interferometer sensor for ultrasound detection

A highly sensitive ultrasound sensor based on an integrated photonics Mach-Zehnder interferometer (MZI) fabricated in silicon-on-insulator technology is reported. The sensing spiral is located on a membrane of size 121 mu m x 121 mu m. Ultrasound waves excite the membrane's vibrational mode, which translates to modulation of the MZI transmission. The measured sensor transfer function is centered at 0.47 MHz and has a -6 dBbandwidth of 21.2%. The sensor sensitivity is linear in the optical input power and reaches a maximum 0.62 mV/Pa, which is limited by the interrogation method. At 0.47 MHz and for an optical power of 1.0 mW the detection limit is 0.38 mPa/Hz(1/2) and the dynamic range is 59 dB. The MZI's gradual transmission function allows a wide range of wavelength operation points. This strongly facilitates sensor use and is promising for applications. (C) 2019 Optical Society of Americ

Highly sensitive silicon Mach-Zehnder interferometer based ultrasound sensor

We report a highly sensitive ultrasound sensor based on an integrated photonics silicon Mach-Zehnder interferometer (MZI). One arm of the MZI is located on a thin membrane, acting as the sensing part of the device. Ultrasound waves excite the membrane's vibrational mode, thus inducing modulation of the MZI transmission. The measured sensor transfer function is centered at 0.47 MHz and has a -6 dB bandwidth of 21.2%. For 1.0 mW optical input power, we obtain a high sensitivity of 0.62 mV/Pa, a low detection limit of 0.38 mPa/Hz(1/2) at the resonance frequency and a large dynamic range of 59 dB. In preliminary ultrasound imaging experiments using this sensor, an image of a wire phantom is obtained. The properties of this sensor and the generated image show that this sensor is very promising for ultrasound imaging applications