Numerical prediction of the printable density range of lattice structures for additive manufacturing

Structured cellular structures are nowadays printed using additive manufacturing methods like powder bed fusion. The relative density of the cellular structures has a big role in the suitability of a lattice for printing due to the minimum printable radius constraint and powder being trapped inside an inclusion. In this work, the theoretical limits of the printable range of relative density of different lattice types are found based on the cell size using computer methods by leaving other process parameters for further research as the current parameters are the most basic ones. The results are approximated using simple polynomials to enable practical usage. (C) 2017 Elsevier Ltd. All rights reserved

Accountability and Risk Governance: A Scenario-informed Reflection on European Regulation of GMOs

Scientific and technological progress in an ever more globalized economy has resulted innew innovations, which have often contributed to improved living conditions (Archibugiand Iammarino 1999; Archibugi and Pietrobelli 2003; Castells 1999; International MonetaryFund 2000). Yet, the very same progress has produced unprecedented risks, which are oftenuncertain and incalculable in nature (Giddens 1991; Beck 1986, 1999). Such ‘uncertain risks’are usually associated with large-scale, long-term and transboundary hazards with whichsociety has no or only limited experience (van Asselt and Vos 2008; van Asselt et al. 2009).As a result, their risk potential is highly contested. An exemplary uncertain risk is posedby genetically modified organisms (GMOs).1 As it is contested whether GMOs constitutea risk to the environment and/or human health, scholars have pointed out that GMOsshould be conceived of in terms of uncertainty (ibid.; Lang and Hallmann 2005; Levidow etal. 2005). Indeed, even though scientific or historical proofs of harmful consequences withregard to GMOs are lacking, “suspicions cannot be fully refuted either” (van Asselt andVos 2008, 281). A decisive question is thus how to take decisions in the face of uncertainty(Beck 1999; Löfstedt, 2009)

Systematic Changes of Earthquake Rupture with Depth: A Case Study from the 2010Mw 8.8 Maule, Chile, Earthquake Aftershock Sequence

The very shallow part of subduction megathrusts occasionally hosts tsunami earthquakes, with unusually slow rupture propagation. The aftershock sequence of the 2010 Mw 8.8 Maule earthquake, offshore Chile, provides us with the opportunity to study systematic changes in source properties for smaller earthquakes within a single segment of a subduction zone. We invert amplitude spectra for double-couple moment tensors and centroid depths of 71 aftershocks of the Maule earthquake down to magnitudes Mw 4.0. In addition, we also derive average source durations.We find that shallower earthquakes tend to have longer normalized source durations on average, similar to the pattern observed previously for larger magnitude events. This depth dependence is observable for thrust and normal earthquakes. The normalized source durations of normal- faulting earthquakes are at the lower end of those for thrust earthquakes, probably because of the higher stress drops of intraplate earthquakes compared to interplate earthquakes. We suggest from the similarity of the depth dependence of normal and thrust events and between smaller and larger magnitude earthquakes that the depth-dependent variation of rigidity, rather than frictional conditional stability at the plate interface, is primarily responsible for the observed pattern. Tsunami earthquakes probably require both low rigidity and conditionally stable frictional conditions; the presence of longduration moderate-magnitude events is therefore a helpful but not sufficient indicator for areas at risk of tsunami earthquakes

Fascial closure in giant ventral hernias after preoperative botulinum toxin a and progressive pneumoperitoneum : a systematic review and meta-analysis

Background: The primary objective was to assess the perioperative efficacy of the preoperative use of progressive pneumoperitoneum or Botulinum Toxin A injections in ventral hernia repair. Methods: Embase, Medline Ovid, Web of Science, Cochrane Central, and Google Scholar were systematically searched. Studies in English reporting on fascial closure, indications, complications or postoperative outcomes in adult patients that had undergone progressive pneumoperitoneum, Botulinum Toxin A injections, or both before ventral hernia repair were included. Study quality was assessed with the Oxford Levels of Evidence guidelines and the Methodological Index for Non-Randomized Studies criteria. A pooled fascial closure rate and recurrence rate were calculated with random effects models. Results: Twenty studies were included from the 905 identified, comprising the use progressive pneumoperitoneum (n = 11), Botulinum Toxin A (n = 6), and both techniques (n = 3). The overall fascial closure rate was 0.94 (95% confidence interval 0.89-0.98). Indications for the use of progressive pneumoperitoneum or Botulinum Toxin A were based on objective (eg, computed tomography measurements) or subjective measures (eg, foreseen surgical problems). In contrast to the use of Botulinum Toxin A, reported complications with the use of progressive pneumoperitoneum were ample and sometimes severe. The cumulative reported recurrence rate was 0.03 (95% confidence interval 0.01-0.06). Conclusion: Preoperative progressive pneumoperitoneum and Botulinum Toxin A can facilitate fascial closure without causing significant numbers of adverse events. Botulinum Toxin A qualifies for low threshold use, yet progressive pneumoperitoneum should be used cautiously owing to a larger number of complications. Definitive recommendations cannot be made as the quality of included studies is low, bias is present, and comparative information is scarce. Registration number Information about the design and conduct of this systematic review has been registered on PROSPERO, registration number CRD42020181679

PickBlue: Seismic phase picking for ocean bottom seismometers with deep learning

Detecting phase arrivals and pinpointing the arrival times of seismic phases in seismograms is crucial for many seismological analysis workflows. For land station data machine learning methods have already found widespread adoption. However, deep learning approaches are not yet commonly applied to ocean bottom data due to a lack of appropriate training data and models. Here, we compiled an extensive and labeled ocean bottom seismometer dataset from 15 deployments in different tectonic settings, comprising ~90,000 P and ~63,000 S manual picks from 13,190 events and 355 stations. We propose PickBlue, an adaptation ot the two popular deep learning networks EQTransformer and PhaseNet. PickBlue joint processes three seismometer recordings in conjunction with a hydrophone component and is trained with the waveforms in the new database. The performance is enhanced by employing transfer learning, where initial weights are derived from models trained with land earthquake data. PickBlue significantly outperforms neural networks trained with land stations and models trained without hydrophone data. The model achieves a mean absolute deviation (MAD) of 0.05 s for P waves and 0.12 s for S waves. We integrate our dataset and trained models into SeisBench to enable an easy and direct application in future deployments

PickBlue: Seismic Phase Picking for Ocean Bottom Seismometers With Deep Learning

Detecting phase arrivals and pinpointing the arrival times of seismic phases in seismograms is crucial for many seismological analysis workflows. For land station data, machine learning methods have already found widespread adoption. However, deep learning approaches are not yet commonly applied to ocean bottom data due to a lack of appropriate training data and models. Here, we compiled an extensive and labeled ocean bottom seismometer (OBS) data set from 15 deployments in different tectonic settings, comprising ∼90,000 P and ∼63,000 S manual picks from 13,190 events and 355 stations. We propose PickBlue, an adaptation of the two popular deep learning networks EQTransformer and PhaseNet. PickBlue joint processes three seismometer recordings in conjunction with a hydrophone component and is trained with the waveforms in the new database. The performance is enhanced by employing transfer learning, where initial weights are derived from models trained with land earthquake data. PickBlue significantly outperforms neural networks trained with land stations and models trained without hydrophone data. The model achieves a mean absolute deviation of 0.05 s for P-waves and 0.12 s for S-waves, and we apply the picker on the Hikurangi Ocean Bottom Tremor and Slow Slip OBS deployment offshore New Zealand. We integrate our data set and trained models into SeisBench to enable an easy and direct application in future deployments

MMORF—FSL’s MultiMOdal Registration Framework

We present MMORF—FSL’s MultiMOdal Registration Framework—a newly released nonlinear image registration tool designed primarily for application to magnetic resonance imaging (MRI) images of the brain. MMORF is capable of simultaneously optimising both displacement and rotational transformations within a single registration framework by leveraging rich information from multiple scalar and tensor modalities. The regularisation employed in MMORF promotes local rigidity in the deformation, and we have previously demonstrated how this effectively controls both shape and size distortion, leading to more biologically plausible warps. The performance of MMORF is benchmarked against three established nonlinear registration methods—FNIRT, ANTs, and DR-TAMAS—across four domains: FreeSurfer label overlap, diffusion tensor imaging (DTI) similarity, task-fMRI cluster mass, and distortion. The evaluation is based on 100 unrelated subjects from the Human Connectome Project (HCP) dataset registered to the Oxford-MultiModal-1 (OMM-1) multimodal template via either the T1w contrast alone or in combination with a DTI/DTI-derived contrast. Results show that MMORF is the most consistently high-performing method across all domains—both in terms of accuracy and levels of distortion. MMORF is available as part of FSL, and its inputs and outputs are fully compatible with existing workflows. We believe that MMORF will be a valuable tool for the neuroimaging community, regardless of the domain of any downstream analysis, providing state-of-the-art registration performance that integrates into the rich and widely adopted suite of analysis tools in FSL

Implementing preoperative Botulinum toxin A and progressive pneumoperitoneum through the use of an algorithm in giant ventral hernia repair

Background Repair of large ventral hernias with loss of domain can be facilitated by preoperative Botulinum toxin A (BTA) injections and preoperative progressive pneumoperitoneum (PPP). The aim of this study is to evaluate the outcomes of ventral hernioplasty using a standardized algorithm, including component separation techniques, preoperative BTA and PPP. Methods All patients between June 2014 and August 2018 with giant hernias (either primary or incisional) of more than 12 cm width were treated according to a previously developed standardized algorithm. Retrospective data analysis from a prospectively collected dataset was performed. The primary outcome was closure of the anterior fascia. Secondary outcomes included complications related to the preoperative treatment, postoperative complications, and recurrences. Results Twenty-three patients were included. Median age was 65 years (range 28-77) and median BMI was 31.4 (range 22.7-38.0 kg/m(2)). The median loss of domain was 29% (range 12-226%). For the primary and secondary endpoints, 22 patients were analyzed. Primary closure of the anterior fascia was possible in 82% of all patients. After a median follow-up of 19.5 months (range 10-60 months), 3 patients (14%) developed a hernia recurrence and 16 patients (73%) developed 23 surgical site occurrences, most of which were surgical site infections (54.5%). Conclusion Our algorithm using both anterior or posterior component separation, together with preoperative BTA injections and PPP, achieved an acceptable fascial closure rate. Further studies are needed to explore the individual potential of BTA injections and PPP, and to research whether these methods can prevent the need for component separation, as postoperative wound morbidity remains high in our study

Relation Between Oceanic Plate Structure, Patterns of Interplate Locking and Microseismicity in the 1922 Atacama Seismic Gap

We deployed a dense geodetic and seismological network in the Atacama seismic gap in Chile. We derive a microseismicity catalog of >30,000 events, time series from 70 GNSS stations, and utilize a transdimensional Bayesian inversion to estimate interplate locking. We identify two highly locked regions of different sizes whose geometries appear to control seismicity patterns. Interface seismicity concentrates beneath the coastline, just downdip of the highest locking. A region with lower locking (27.5°S–27.7°S) coincides with higher seismicity levels, a high number of repeating earthquakes and events extending toward the trench. This area is situated where the Copiapó Ridge is subducted and has shown previous indications of both seismic and aseismic slip, including an earthquake sequence in 2020. While these findings suggest that the structure of the downgoing oceanic plate prescribes patterns of interplate locking and seismicity, we note that the Taltal Ridge further north lacks a similar signature

Structure of the central Sumatran subduction zone revealed by local earthquake travel-time tomography using an amphibious network

The Sumatran subduction zone exhibits strong seismic and tsunamogenic potential with the prominent examples of the 2004, 2005 and 2007 earthquakes. Here, we invert travel time data of local earthquakes for vp and vp/vs velocity models of the central Sumatran forearc. Data were acquired by an amphibious seismometer network consisting of 52 land stations and 10 ocean bottom seismometers located on a segment of the Sumatran subduction zone that had not ruptured in a great earthquake since 1797 but witnessed recent ruptures to the north in 2005 (Nias earthquake, Mw = 8.7) and to the south in 2007 (Bengkulu earthquake, Mw = 8.5). 2D and 3D vp velocity anomalies reveal the downgoing slab and the sedimentary basins. Although the seismicity pattern in the study area appears to be strongly influenced by the obliquely subducting Investigator Fracture Zone to at least 200 km depth, the 3D velocity model shows prevailing trench parallel structures at depths of the plate interface. The tomographic model suggests a thinned crust below the basin east of the forearc islands (Nias, Pulau Batu, Siberut) at ~ 180 km distance to the trench. Vp velocities beneath the magmatic arc and the Sumatran fault zone SFZ are around 5 km/s at 10 km depth and the vp/vs ratios in the uppermost 10 km are low, indicating the presence of felsic lithologies typical for continental crust. We find moderately elevated vp/vs values of 1.85 at ~ 150 km distance to the trench in the region of the Mentawai fault. Vp/vs ratios suggest absence of large scale alteration of the mantle wedge and might explain why the seismogenic plate interface (observed as a locked zone from geodetic data) extends below the continental forearc Moho in Sumatra. Reduced vp velocities beneath the forearc basin covering the region between Mentawai Islands and the Sumatra mainland possibly reflect a reduced thickness of the overriding crust