Estimation of Absolute States of Human Skeletal Muscle via Standard B-Mode Ultrasound Imaging and Deep Convolutional Neural Networks

Objective: To test automated in vivo estimation of active and passive skeletal muscle states using ultrasonic imaging. Background: Current technology (electromyography, dynamometry, shear wave imaging) provides no general, non-invasive method for online estimation of skeletal muscle states. Ultrasound (US) allows non-invasive imaging of muscle, yet current computational approaches have never achieved simultaneous extraction nor generalisation of independently varying, active and passive states. We use deep learning to investigate the generalizable content of 2D US muscle images. Method: US data synchronized with electromyography of the calf muscles, with measures of joint moment/angle were recorded from 32 healthy participants (7 female, ages: 27.5, 19-65). We extracted a region of interest of medial gastrocnemius and soleus using our prior developed accurate segmentation algorithm. From the segmented images, a deep convolutional neural network was trained to predict three absolute, driftfree, components of the neurobiomechanical state (activity, joint angle, joint moment) during experimentally designed, simultaneous, independent variation of passive (joint angle) and active (electromyography) inputs. Results: For all 32 held-out participants (16-fold cross-validation) the ankle joint angle, electromyography, and joint moment were estimated to accuracy 55±8%, 57±11%, and 46±9% respectively. Significance: With 2D US imaging, deep neural networks can encode in generalizable form, the activitylength-tension state relationship of these muscles. Observation only, low power, 2D US imaging can provide a new category of technology for non-invasive estimation of neural output, length and tension in skeletal muscle. This proof of principle has value for personalised muscle assessment in pain, injury, neurological conditions, neuropathies, myopathies and ageing

Mesozoic–Tertiary exhumation history of the Altai Mountains, northern Xinjiang, China: New constraints from apatite fission track data

This study uses apatite fission track (FT) analysis to constrain the exhumation history of bedrock samples collected from the Altai Mountains in northern Xinjiang, China. Samples were collected as transects across the main structures related to Palaeozoic crustal accretion events. FT results and modeling identify three stages in sample cooling history spanning the Mesozoic and Tertiary. Stage one records rapid cooling to the low temperature part of the fission track partial annealing zone circa 70 ± 10 °C. Stage two, records a period of relative stability with little if any cooling taking place between 75 and 25–20 Ma suggesting the Altai region had been reduced to an area of low relief. Support for this can be found in the adjacent Junngar Basin that received little if any sediment during this interval. Final stage cooling took place in the Miocene at an accelerated rate bringing the sampled rocks to the Earth's surface. This last stage, linked to the far field effects of the Himalayan collision, most likely generated the surface uplift and relief that define the present-day Altai Mountains

Automated Generation of Data Quality Checks by Identifying Key Dimensions and Values

Monitoring the quality and integrity of the data stored in a data warehouse is necessary to ensure correct and reliable operation. Such checks can include detecting anomalous and/or impermissible values for the metrics and dimensions present in the database tables. Determining useful and effective checks and bounds is difficult and tedious, and requires high levels of expertise and familiarity with the data. This disclosure describes techniques for automating the creation of data quality checks based on examining database schema and contents to identify important dimensions and values for data quality checks. The techniques utilize the observation that, in practice, a subset of the values of a database field are likely of operational importance. These are automatically identified based on calculating importance-adjusted data quality coverage by assigning importance to metrics, dimensions, and dimension values. Data quality checks are automatically generated for effective coverage of the key dimensions and values. The generation of checks can involve selecting from a repository of historically effective checks generated by experts and/or applying time series anomaly detection to metrics in entirety or sliced by key dimension values

Data Quality Coverage

The quality of data is typically measured on a subset of all available data. It is of interest to know if such a measurement, performed on a subset of data, is representative of the entire corpus of data. This disclosure describes techniques that use historical data and metadata of a given time series to determine the set of useful data quality checks that can exist. The set of useful data quality checks is compared to the actual set of data quality checks to provide a percentage of data quality coverage that a given data set has

Characterizing temporary hydrological regimes at a European scale

Monthly duration curves have been constructed from climate data across Europe to help address the relative frequency of ecologically critical low flow stages in temporary rivers, when flow persists only in disconnected pools in the river bed. The hydrological model is 5 based on a partitioning of precipitation to estimate water available for evapotranspiration and plant growth and for residual runoff. The duration curve for monthly flows has then been analysed to give an estimate of bankfull flow based on recurrence interval. The corresponding frequency for pools is then based on the ratio of bank full discharge to pool flow, arguing from observed ratios of cross-sectional areas at flood 10 and low flows to estimate pool flow as 0.1% of bankfull flow, and so estimate the frequency of the pool conditions that constrain survival of river-dwelling arthropods and fish. The methodology has been applied across Europe at 15 km resolution, and can equally be applied under future climatic scenarios

SPARTAN: a global network to evaluate and enhance satellite-based estimates of ground-level particulate matter for global health applications

Ground-based observations have insufficient spatial coverage to assess long-term human exposure to fine particulate matter (PM2.5) at the global scale. Satellite remote sensing offers a promising approach to provide information on both short-and long-term exposure to PM2.5 at local-to-global scales, but there are limitations and outstanding questions about the accuracy and precision with which ground-level aerosol mass concentrations can be inferred from satellite remote sensing alone. A key source of uncertainty is the global distribution of the relationship between annual average PM2.5 and discontinuous satellite observations of columnar aerosol optical depth (AOD). We have initiated a global network of ground-level monitoring stations designed to evaluate and enhance satellite remote sensing estimates for application in health-effects research and risk assessment. This Surface PARTiculate mAtter Network (SPARTAN) includes a global federation of ground-level monitors of hourly PM2.5 situated primarily in highly populated regions and collocated with existing ground-based sun photometers that measure AOD. The instruments, a three-wavelength nephelometer and impaction filter sampler for both PM2.5 and PM10, are highly autonomous. Hourly PM2.5 concentrations are inferred from the combination of weighed filters and nephelometer data. Data from existing networks were used to develop and evaluate network sampling characteristics. SPARTAN filters are analyzed for mass, black carbon, water-soluble ions, and metals. These measurements provide, in a variety of regions around the world, the key data required to evaluate and enhance satellite-based PM2.5 estimates used for assessing the health effects of aerosols. Mean PM2.5 concentrations across sites vary by more than 1 order of magnitude. Our initial measurements indicate that the ratio of AOD to ground-level PM2.5 is driven temporally and spatially by the vertical profile in aerosol scattering. Spatially this ratio is also strongly influenced by the mass scattering efficiency.Fil: Snider, G.. Dalhousie University Halifax; CanadáFil: Weagle, C. L.. Dalhousie University Halifax; CanadáFil: Martin, R. V.. Dalhousie University Halifax; Canadá. University of Cambridge; Reino UnidoFil: van Donkelaar, A.. Dalhousie University Halifax; CanadáFil: Conrad, K.. Dalhousie University Halifax; CanadáFil: Cunningham, D.. Dalhousie University Halifax; CanadáFil: Gordon, C.. Dalhousie University Halifax; CanadáFil: Zwicker, M.. Dalhousie University Halifax; CanadáFil: Akoshile, C.. University of Ilorin; NigeriaFil: Artaxo, P.. Governo Do Estado de Sao Paulo; BrasilFil: Anh, N. X.. Vietnam Academy of Science and Technology. Institute of Geophysics; VietnamFil: Brook, J.. University of Toronto; CanadáFil: Dong, J.. Tsinghua University; ChinaFil: Garland, R. M.. North-West University; SudáfricaFil: Greenwald, R.. Rollins School of Public Health; Estados UnidosFil: Griffith, D.. Council for Scientific and Industrial Research; SudáfricaFil: He, K.. Tsinghua University; ChinaFil: Holben, B. N.. NASA Goddard Space Flight Center; Estados UnidosFil: Kahn, R.. NASA Goddard Space Flight Center; Estados UnidosFil: Koren, I.. Weizmann Institute Of Science Israel; IsraelFil: Lagrosas, N.. Manila Observatory, Ateneo de Manila University campus; FilipinasFil: Lestari, P.. Institut Teknologi Bandung; IndonesiaFil: Ma, Z.. Rollins School of Public Health; Estados UnidosFil: Vanderlei Martins, J.. University of Maryland; Estados UnidosFil: Quel, Eduardo Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Rudich, Y.. Weizmann Institute Of Science Israel; IsraelFil: Salam, A.. University Of Dhaka; BangladeshFil: Tripathi, S. N.. Indian Institute Of Technology, Kanpur; IndiaFil: Yu, C.. Rollins School of Public Health; Estados UnidosFil: Zhang, Q.. Tsinghua University; ChinaFil: Zhang, Y.. Tsinghua University; ChinaFil: Brauer, M.. University of British Columbia; CanadáFil: Cohen, A.. Health Effects Institute; Estados UnidosFil: Gibson, M. D.. Dalhousie University Halifax; CanadáFil: Liu, Y.. Rollins School of Public Health; Estados Unido

Bacillus anthracis edema factor substrate specificity: evidence for new modes of action

Since the isolation of Bacillus anthracis exotoxins in the 1960s, the detrimental activity of edema factor (EF) was considered as adenylyl cyclase activity only. Yet the catalytic site of EF was recently shown to accomplish cyclization of cytidine 5'-triphosphate, uridine 5'-triphosphate and inosine 5'-triphosphate, in addition to adenosine 5'-triphosphate. This review discusses the broad EF substrate specificity and possible implications of intracellular accumulation of cyclic cytidine 3':5'-monophosphate, cyclic uridine 3':5'-monophosphate and cyclic inosine 3':5'-monophosphate on cellular functions vital for host defense. In particular, cAMP-independent mechanisms of action of EF on host cell signaling via protein kinase A, protein kinase G, phosphodiesterases and CNG channels are discussed

Do female association preferences predict the likelihood of reproduction?

Sexual selection acting on male traits through female mate choice is commonly inferred from female association preferences in dichotomous mate choice experiments. However, there are surprisingly few empirical demonstrations that such association preferences predict the likelihood of females reproducing with a particular male. This information is essential to confirm association preferences as good predictors of mate choice. We used green swordtails (<i>Xiphophorus helleri</i>) to test whether association preferences predict the likelihood of a female reproducing with a male. Females were tested for a preference for long- or short-sworded males in a standard dichotomous choice experiment and then allowed free access to either their preferred or non-preferred male. If females subsequently failed to produce fry, they were provided a second unfamiliar male with similar sword length to the first male. Females were more likely to reproduce with preferred than non-preferred males, but for those that reproduced, neither the status (preferred/non-preferred) nor the sword length (long/short) of the male had an effect on brood size or relative investment in growth by the female. There was no overall preference based on sword length in this study, but male sword length did affect likelihood of reproduction, with females more likely to reproduce with long- than short-sworded males (independent of preference for such males in earlier choice tests). These results suggest that female association preferences are good indicators of female mate choice but that ornament characteristics of the male are also important

Distinguishing elliptic fibrations with AI

We use the latest techniques in machine-learning to study whether from the landscape of Calabi-Yau manifolds one can distinguish elliptically fibred ones. Using the dataset of complete intersections in products of projective spaces (CICY3 and CICY4, totalling about a million manifolds) as a concrete playground, we find that a relatively simple neural network with forward-feeding multi-layers can very efficiently distinguish the elliptic fibrations, much more so than using the traditional methods of manipulating the defining equations. We cross-check with control cases to ensure that the AI is not randomly guessing and is indeed identifying an inherent structure. Our result should prove useful in F-theory and string model building as well as in pure algebraic geometry