Aurorasaurus:a citizen science platform for viewing and reporting the aurora

A new, citizen science based, aurora observing and reporting platform has been developed with the primary aim of collecting auroral observations made by the general public to further improve the modeling of the aurora. In addition, the real-time ability of this platform facilitates the combination of citizen science observations with auroral oval models to improve auroral visibility nowcasting. Aurorasaurus provides easily understandable aurora information, basic gamification, and real-time location-based notification of verified aurora activity to engage citizen scientists. The Aurorasaurus project is one of only a handful of space weather citizen science projects and can provide useful results for the space weather and citizen science communities. Early results are promising with over 2,000 registered users submitting over 1,000 aurora observations and verifying over 1,700 aurora sightings posted on Twitter

Small strain stiffness within logarithmic contractancy model for structured anisotropic clay.

ABSTRACT: Stiffness of soils in the small strain region is high and it decays nonlinearly with increasing shear strains or with mobilization of shear stresses. However, the commonly used critical state based constitutive models use a simple elastic formulation at small strains that falls short in the prediction of the small strain nonlinearity and anisotropy. This paper proposes a simple way for rendering the existing constitutive models with the capability to capture the small strain behaviour of soils. This is illustrated by proposing a new model for structured anisotropic clay extending an existing model that uses the framework of logarithmic contractancy called ESCLAY1S. The proposed model is implemented into a Finite Element program as a user-defined soil model. The model predictions are compared with experimental data for various clays. Furthermore, the effect of nonlinearity is investigated for an excavation in soft clay

Feminicide and counterdata production: Activist efforts to monitor and challenge gender-related violence

Gender-related violence against women and its lethal outcome, feminicide, are a serious problem throughout the world. Official government data on gender violence and feminicide are often absent, incomplete, infrequently updated, and contested. We draw on data feminism to situate feminicide data as missing data. Building on qualitative interviews, this study discusses the informatic work of ten activist and civil society organizations across six countries who combat missing data by producing counterdata. Activists enact alternative epistemological approaches to data science that center care, memory, and justice. Activists also face significant information challenges that increase monitoring labor and add emotional burden to reading about violent deaths. This work contributes to literature on data activism and critical data studies, proposing feminicide data practices as an important research subject. The empirical insights contribute to human-computer interaction (HCI) research, suggesting ways that the field may support and sustain the counterdata production practices of activists

The Fitness Cost of Antibiotic Resistance in Streptococcus pneumoniae: Insight from the Field

Laboratory studies have suggested that antibiotic resistance may result in decreased fitness in the bacteria that harbor it. Observational studies have supported this, but due to ethical and practical considerations, it is rare to have experimental control over antibiotic prescription rates.We analyze data from a 54-month longitudinal trial that monitored pneumococcal drug resistance during and after biannual mass distribution of azithromycin for the elimination of the blinding eye disease, trachoma. Prescription of azithromycin and antibiotics that can create cross-resistance to it is rare in this part of the world. As a result, we were able to follow trends in resistance with minimal influence from unmeasured antibiotic use. Using these data, we fit a probabilistic disease transmission model that included two resistant strains, corresponding to the two dominant modes of resistance to macrolide antibiotics. We estimated the relative fitness of these two strains to be 0.86 (95% CI 0.80 to 0.90), and 0.88 (95% CI 0.82 to 0.93), relative to antibiotic-sensitive strains. We then used these estimates to predict that, within 5 years of the last antibiotic treatment, there would be a 95% chance of elimination of macrolide resistance by intra-species competition alone.Although it is quite possible that the fitness cost of macrolide resistance is sufficient to ensure its eventual elimination in the absence of antibiotic selection, this process takes time, and prevention is likely the best policy in the fight against resistance

Development and validation of deep learning classifiers to detect Epstein-Barr virus and microsatellite instability status in gastric cancer: a retrospective multicentre cohort study

Background: Response to immunotherapy in gastric cancer is associated with microsatellite instability (or mismatch repair deficiency) and Epstein-Barr virus (EBV) positivity. We therefore aimed to develop and validate deep learning-based classifiers to detect microsatellite instability and EBV status from routine histology slides. Methods: In this retrospective, multicentre study, we collected tissue samples from ten cohorts of patients with gastric cancer from seven countries (South Korea, Switzerland, Japan, Italy, Germany, the UK and the USA). We trained a deep learning-based classifier to detect microsatellite instability and EBV positivity from digitised, haematoxylin and eosin stained resection slides without annotating tumour containing regions. The performance of the classifier was assessed by within-cohort cross-validation in all ten cohorts and by external validation, for which we split the cohorts into a five-cohort training dataset and a five-cohort test dataset. We measured the area under the receiver operating curve (AUROC) for detection of microsatellite instability and EBV status. Microsatellite instability and EBV status were determined to be detectable if the lower bound of the 95% CI for the AUROC was above 0·5. Findings: Across the ten cohorts, our analysis included 2823 patients with known microsatellite instability status and 2685 patients with known EBV status. In the within-cohort cross-validation, the deep learning-based classifier could detect microsatellite instability status in nine of ten cohorts, with AUROCs ranging from 0·597 (95% CI 0·522–0·737) to 0·836 (0·795–0·880) and EBV status in five of eight cohorts, with AUROCs ranging from 0·819 (0·752–0·841) to 0·897 (0·513–0·966). Training a classifier on the pooled training dataset and testing it on the five remaining cohorts resulted in high classification performance with AUROCs ranging from 0·723 (95% CI 0·676–0·794) to 0·863 (0·747–0·969) for detection of microsatellite instability and from 0·672 (0·403–0·989) to 0·859 (0·823–0·919) for detection of EBV status. Interpretation: Classifiers became increasingly robust when trained on pooled cohorts. After prospective validation, this deep learning-based tissue classification system could be used as an inexpensive predictive biomarker for immunotherapy in gastric cancer. Funding: German Cancer Aid and German Federal Ministry of Health

Association between multimorbidity and postoperative mortality in patients undergoing major surgery: a prospective study in 29 countries across Europe

BackgroundMultimorbidity poses a global challenge to healthcare delivery. This study aimed to describe the prevalence of multimorbidity, common disease combinations and outcomes in a contemporary cohort of patients undergoing major abdominal surgery.MethodsThis was a pre-planned analysis of a prospective, multicentre, international study investigating cardiovascular complications after major abdominal surgery conducted in 446 hospitals in 29 countries across Europe. The primary outcome was 30-day postoperative mortality. The secondary outcome measure was the incidence of complications within 30 days of surgery.ResultsOf 24,227 patients, 7006 (28.9%) had one long-term condition and 10,486 (43.9%) had multimorbidity (two or more long-term health conditions). The most common conditions were primary cancer (39.6%); hypertension (37.9%); chronic kidney disease (17.4%); and diabetes (15.4%). Patients with multimorbidity had a higher incidence of frailty compared with patients <= 1 long-term health condition. Mortality was higher in patients with one long-term health condition (adjusted odds ratio 1.93 (95%CI 1.16-3.23)) and multimorbidity (adjusted odds ratio 2.22 (95%CI 1.35-3.64)). Frailty and ASA physical status 3-5 mediated an estimated 31.7% of the 30-day mortality in patients with one long-term health condition (adjusted odds ratio 1.30 (95%CI 1.12-1.51)) and an estimated 36.9% of the 30-day mortality in patients with multimorbidity (adjusted odds ratio 1.61 (95%CI 1.36-1.91)). There was no improvement in 30-day mortality in patients with multimorbidity who received pre-operative medical assessment.ConclusionsMultimorbidity is common and outcomes are poor among surgical patients across Europe. Addressing multimorbidity in elective and emergency patients requires innovative strategies to account for frailty and disease control. The development of such strategies, that integrate care targeting whole surgical pathways to strengthen current systems, is urgently needed for multimorbid patients. Interventional trials are warranted to determine the effectiveness of targeted management for surgical patients with multimorbidity

First-time landslides in Vashon advance glaciolacustrine deposits, Puget Lowland, U.S.A.

Advance glaciolacustrine (Qglv) deposits from the last continental glaciation are widespread in the densely populated Puget Lowland and are prone to shallow landsliding. Much less frequently in historic time, new landslides propagate deeply within intact Qglv deposits. The exceptional volume and highly mobile nature of the 22 March 2014, State Route 530 (Oso) landslide generated considerable uncertainty and public concern about the likelihood for similar deep-seated failures initiating from most any slope where these deposits crop out. The primary study objectives are to utilize geotechnical data from the small data set of available published and public-domain investigations to characterize, in general terms, hydrogeologic, geotechnical and geomorphic factors and their relative contribution to initiating deep-seated landslides within intact Qglv deposits; and to inform future hazard and risk assessments for first-time landslides within these deposits. Qglv deposits are overconsolidated, very stiff to hard, laminated to massive, silt and clay. Shear strength is anisotropic, with cohesion being a significant component of bedding-parallel strength and friction dominating strength perpendicular to bedding. Hydraulic conductivity is likely also anisotropic. Multi-year records of pore pressures within Qglv deposits show no to minor seasonal flux; only minor pore pressure responses to multi-day to multi-week episodes of heavy precipitation have been detected. Back analyses using limit-equilibrium methods and peak anisotropic strength under drained conditions demonstrate initial stability of the slopes. Instability occurs near the fully softened strength. We conclude that, over the long term, loss of cohesive strength, rather than hydroclimatic pore pressure response, is the more important contributor to diminishing stability and, in some cases, initiation of first-time landslides in Qglv deposits. The shape and location of the slide surface is strongly influenced by strength anisotropy and stress state. Sliding surfaces developed near the basal contact of the Qglv deposits in all of the five studied landslides. Higher stress states associated with increasing sequence thickness of the landslide masses decrease stability. The length of the basal slide surface, and thus the aspect ratio of the landslide mass, appears to increase proportionally with sequence thickness of the landslide mass.acceptedVersio