Real-time sparse-sampled Ptychographic imaging through deep neural networks

Ptychography has rapidly grown in the fields of X-ray and electron imaging for its unprecedented ability to achieve nano or atomic scale resolution while simultaneously retrieving chemical or magnetic information from a sample. A ptychographic reconstruction is achieved by means of solving a complex inverse problem that imposes constraints both on the acquisition and on the analysis of the data, which typically precludes real-time imaging due to computational cost involved in solving this inverse problem. In this work we propose PtychoNN, a novel approach to solve the ptychography reconstruction problem based on deep convolutional neural networks. We demonstrate how the proposed method can be used to predict real-space structure and phase at each scan point solely from the corresponding far-field diffraction data. The presented results demonstrate how PtychoNN can effectively be used on experimental data, being able to generate high quality reconstructions of a sample up to hundreds of times faster than state-of-the-art ptychography reconstruction solutions once trained. By surpassing the typical constraints of iterative model-based methods, we can significantly relax the data acquisition sampling conditions and produce equally satisfactory reconstructions. Besides drastically accelerating acquisition and analysis, this capability can enable new imaging scenarios that were not possible before, in cases of dose sensitive, dynamic and extremely voluminous samples

An Expert System-Driven Method for Parametric Trajectory Optimization During Conceptual Design

During the early phases of engineering design, the costs committed are high, costs incurred are low, and the design freedom is high. It is well documented that decisions made in these early design phases drive the entire design's life cycle cost. In a traditional paradigm, key design decisions are made when little is known about the design. As the design matures, design changes become more difficult in both cost and schedule to enact. The current capability-based paradigm, which has emerged because of the constrained economic environment, calls for the infusion of knowledge usually acquired during later design phases into earlier design phases, i.e. bringing knowledge acquired during preliminary and detailed design into pre-conceptual and conceptual design. An area of critical importance to launch vehicle design is the optimization of its ascent trajectory, as the optimal trajectory will be able to take full advantage of the launch vehicle's capability to deliver a maximum amount of payload into orbit. Hence, the optimal ascent trajectory plays an important role in the vehicle's affordability posture yet little of the information required to successfully optimize a trajectory is known early in the design phase. Thus, the current paradigm of optimizing ascent trajectories involves generating point solutions for every change in a vehicle's design parameters. This is often a very tedious, manual, and time-consuming task for the analysts. Moreover, the trajectory design space is highly non-linear and multi-modal due to the interaction of various constraints. When these obstacles are coupled with the Program to Optimize Simulated Trajectories (POST), an industry standard program to optimize ascent trajectories that is difficult to use, expert trajectory analysts are required to effectively optimize a vehicle's ascent trajectory. Over the course of this paper, the authors discuss a methodology developed at NASA Marshall's Advanced Concepts Office to address these issues. The methodology is two-fold: first, capture the heuristics developed by human analysts over their many years of experience; and secondly, leverage the power of modern computing to evaluate multiple trajectories simultaneously and therefore enable the exploration of the trajectory's design space early during the pre- conceptual and conceptual phases of design. This methodology is coupled with design of experiments in order to train surrogate models, which enables trajectory design space visualization and parametric optimal ascent trajectory information to be available when early design decisions are being made

Control of Vancomycin-Resistant Enterococcus in Health Care Facilities in a Region

Background In late 1996, vancomycin-resistant enterococci were first detected in the Siouxland region of Iowa, Nebraska, and South Dakota. A task force was created, and in 1997 the assistance of the Centers for Disease Control and Prevention was sought in assessing the prevalence of vancomycin-resistant enterococci in the region’s facilities and implementing recommendations for screening, infection control, and education at all 32 health care facilities in the region. Methods The infection-control intervention was evaluated in October 1998 and October 1999. We performed point-prevalence surveys, conducted a case– control study of gastrointestinal colonization with vancomycin-resistant enterococci, and compared infection-control practices and screening policies for vancomycin-resistant enterococci at the acute care and long-term care facilities in the Siouxland region. Results Perianal-swab samples were obtained from 1954 of 2196 eligible patients (89 percent) in 1998 and 1820 of 2049 eligible patients (89 percent) in 1999. The overall prevalence of vancomycin-resistant enterococci at 30 facilities that participated in all three years of the study decreased from 2.2 percent in 1997 to 1.4 percent in 1998 and to 0.5 percent in 1999 (P Conclusions An active infection-control intervention, which includes the obtaining of surveillance cultures and the isolation of infected patients, can reduce or eliminate the transmission of vancomycinresistant enterococci in the health care facilities of a region. (N Engl J Med 2001;344:1427-33.

Accurate Permittivity Measurements for Microwave Imaging via Ultra-Wideband Removal of Spurious Reflectors

The use of microwave imaging is becoming more prevalent for detection of interior hidden defects in manufactured and packaged materials. In applications for detection of hidden moisture, microwave tomography can be used to image the material and then perform an inverse calculation to derive an estimate of the variability of the hidden material, such internal moisture, thereby alerting personnel to damaging levels of the hidden moisture before material degradation occurs. One impediment to this type of imaging occurs with nearby objects create strong reflections that create destructive and constructive interference, at the receiver, as the material is conveyed past the imaging antenna array. In an effort to remove the influence of the reflectors, such as metal bale ties, research was conducted to develop an algorithm for removal of the influence of the local proximity reflectors from the microwave images. This research effort produced a technique, based upon the use of ultra-wideband signals, for the removal of spurious reflections created by local proximity reflectors. This improvement enables accurate microwave measurements of moisture in such products as cotton bales, as well as other physical properties such as density or material composition. The proposed algorithm was shown to reduce errors by a 4:1 ratio and is an enabling technology for imaging applications in the presence of metal bale ties

Soil Moisture Sensing via Swept Frequency Based Microwave Sensors

There is a need for low-cost, high-accuracy measurement of water content in various materials. This study assesses the performance of a new microwave swept frequency domain instrument (SFI) that has promise to provide a low-cost, high-accuracy alternative to the traditional and more expensive time domain reflectometry (TDR). The technique obtains permittivity measurements of soils in the frequency domain utilizing a through transmission configuration, transmissometry, which provides a frequency domain transmissometry measurement (FDT). The measurement is comparable to time domain transmissometry (TDT) with the added advantage of also being able to separately quantify the real and imaginary portions of the complex permittivity so that the measured bulk permittivity is more accurate that the measurement TDR provides where the apparent permittivity is impacted by the signal loss, which can be significant in heavier soils. The experimental SFI was compared with a high-end 12 GHz TDR/TDT system across a range of soils at varying soil water contents and densities. As propagation delay is the fundamental measurement of interest to the well-established TDR or TDT technique; the first set of tests utilized precision propagation delay lines to test the accuracy of the SFI instrument’s ability to resolve propagation delays across the expected range of delays that a soil probe would present when subjected to the expected range of soil types and soil moisture typical to an agronomic cropping system. The results of the precision-delay line testing suggests the instrument is capable of predicting propagation delays with a RMSE of +/−105 ps across the range of delays ranging from 0 to 12,000 ps with a coefficient of determination of r2 = 0.998. The second phase of tests noted the rich history of TDR for prediction of soil moisture and leveraged this history by utilizing TDT measured with a high-end Hewlett Packard TDR/TDT instrument to directly benchmark the SFI instrument over a range of soil types, at varying levels of moisture. This testing protocol was developed to provide the best possible comparison between SFI to TDT than would otherwise be possible by using soil moisture as the bench mark, due to variations in soil density between soil water content levels which are known to impact the calibration between TDR’s estimate of soil water content from the measured propagation delay which is converted to an apparent permittivity measurement. This experimental decision, to compare propagation delay of TDT to FDT, effectively removes the errors due to variations in packing density from the evaluation and provides a direct comparison between the SFI instrument and the time domain technique of TDT. The tests utilized three soils (a sand, an Acuff loam and an Olton clay-loam) that were packed to varying bulk densities and prepared to provide a range of water contents and electrical conductivities by which to compare the performance of the SFI technology to TDT measurements of propagation delay. For each sample tested, the SFI instrument and the TDT both performed the measurements on the exact same probe, thereby both instruments were measuring the exact same soil/soil-probe response to ensure the most accurate means to compare the SFI instrument to a high-end TDT instrument. Test results provided an estimated instrumental accuracy for the SFI of +/−0.98% of full scale, RMSE basis, for the precision delay lines and +/−1.32% when the SFI was evaluated on loam and clay loam soils, in comparison to TDT as the bench-mark. Results from both experiments provide evidence that the low-cost SFI approach is a viable alternative to conventional TDR/TDT for high accuracy applications

Implementing Evidence-Based Alcohol Interventions in a Resource-Limited Setting: Novel Delivery Strategies in Tomsk, Russia

Effective implementation of evidence-based interventions in “real-world” settings can be challenging. Interventions based on externally valid trial findings can be even more difficult to apply in resource-limited settings, given marked differences—in provider experience, patient population, and health systems—between those settings and the typical clinical trial environment. Under the auspices of the Integrated Management of Physician-Delivered Alcohol Care for Tuberculosis Patients (IMPACT) study, a randomized, controlled effectiveness trial, and as an integrated component of tuberculosis treatment in Tomsk, Russia, we adapted two proven alcohol interventions to the delivery of care to 200 patients with alcohol use disorders. Tuberculosis providers performed screening for alcohol use disorders and also delivered naltrexone (with medical management) or a brief counseling intervention either independently or in combination as a seamless part of routine care. We report the innovations and challenges to intervention design, training, and delivery of both pharmacologic and behavioral alcohol interventions within programmatic tuberculosis treatment services. We also discuss the implications of these lessons learned within the context of meeting the challenge of providing evidence-based care in resource-limited settings. (Harv Rev Psychiatry 2012;20:58–67.

Deep learning at the edge enables real-time streaming ptychographic imaging

Coherent microscopy techniques provide an unparalleled multi-scale view of materials across scientific and technological fields, from structural materials to quantum devices, from integrated circuits to biological cells. Driven by the construction of brighter sources and high-rate detectors, coherent X-ray microscopy methods like ptychography are poised to revolutionize nanoscale materials characterization. However, associated significant increases in data and compute needs mean that conventional approaches no longer suffice for recovering sample images in real-time from high-speed coherent imaging experiments. Here, we demonstrate a workflow that leverages artificial intelligence at the edge and high-performance computing to enable real-time inversion on X-ray ptychography data streamed directly from a detector at up to 2 kHz. The proposed AI-enabled workflow eliminates the sampling constraints imposed by traditional ptychography, allowing low dose imaging using orders of magnitude less data than required by traditional methods

Is an ecosystem services-based approach developed for setting specific protection goals for plant protection products applicable to other chemicals?

Clearly defined protection goals specifying what to protect, where and when, are required for designing scientifically sound risk assessments and effective risk management of chemicals. Environmental protection goals specified in EU legislation are defined in general terms, resulting in uncertainty in how to achieve them. In 2010, the European Food Safety Authority (EFSA) published a framework to identify more specific protection goals based on ecosystem services potentially affected by plant protection products. But how applicable is this framework to chemicals with different emission scenarios and receptor ecosystems? Four case studies used to address this question were: (i) oil refinery waste water exposure in estuarine environments; (ii) oil dispersant exposure in aquatic environments; (iii) down the drain chemicals exposure in a wide range of ecosystems (terrestrial and aquatic); (iv) persistent organic pollutant exposure in remote (pristine) Arctic environments. A four-step process was followed to identify ecosystems and services potentially impacted by chemical emissions and to define specific protection goals. Case studies demonstrated that, in principle, the ecosystem services concept and the EFSA framework can be applied to derive specific protection goals for a broad range of chemical exposure scenarios. By identifying key habitats and ecosystem services of concern, the approach offers the potential for greater spatial and temporal resolution, together with increased environmental relevance, in chemical risk assessments. With modifications including improved clarity on terminology/definitions and further development/refinement of the key concepts, we believe the principles of the EFSA framework could provide a methodical approach to the identification and prioritization of ecosystems, ecosystem services and the service providing units that are most at risk from chemical exposure