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At least 847 records · Page 47

Information-entropy-driven generation of material-agnostic datasets for machine-learning interatomic potentials

In contrast to their empirical counterparts, machine-learning interatomic potentials (MLIAPs) promise to deliver near-quantum accuracy over broad regions of configuration space. However, due to their generic functional forms and extreme flexibility, they can catastrophically fail to capture the properties of novel, out-of-sample configurations, making the quality of the training set a determining factor, especially when investigating materials under extreme conditions. We propose a novel automated dataset generation method based on the maximization of the information entropy of the feature distribution, aiming at an extremely broad coverage of the configuration space in a way that is agnostic to the properties of specific target materials. The ability of the dataset to capture unique material properties is demonstrated on a range of unary materials, including elements with the FCC (Al), BCC (W), HCP (Be, Re and Os), graphite (C), and trigonal (Sb, Te) ground states. MLIAPs trained to this dataset are shown to be accurate over a range of application-relevant metrics, as well as extremely robust over very broad swaths of configurations space, even without dataset fine-tuning or hyper-parameter optimization, making the approach extremely attractive to rapidly and autonomously develop general-purpose MLIAPs suitable for simulations in extreme conditions.

36 MATERIALS SCIENCE↗

Refining Jets for CMS Run 3 using Fast Simulation

As the LHC moves into its high-luminosity phase, the CMS experiment must handle more complex data collected at much higher rates. While the Geant4-based simulation application (FullSim) provides highly accurate simulation to complement real data, FullSim’s intensive consumption of computing resources becomes an increasing liability as the rates increase, while faster tools offer an advantage. The fast MC production application (FastSim) delivers a complete simulation with a factor of 10 speedup over FullSim, but introduces inaccuracies in some observables. A specialized refinement method, Fast Perfekt, employs machine learning to improve the accuracy of FastSim. An initial report of this work focused on the refinement of jet flavor tagging observables. This article presents an update on the refinement, focusing on PUPPI jets with Run 3 data-taking conditions. Refinement is extended to include jet transverse momentum as well as its propagation to missing transverse momentum. A gridbased framework and real-time monitoring system have been developed to facilitate optimization and scaling of the refinement to a large number of target variables.

Güngördü, Açelya Deniz [Istanbul Tech. U.]↗

Modeling laser interactions with aluminum and tantalum targets using a hybrid atomistic-continuum model

A hybrid atomistic-continuum method can model the microstructure evolution of metals subjected to laser irradiation. This method combines classical molecular dynamics (MD) simulations with the two-temperature model (TTM) to account for the laser energy absorption and heat diffusion behavior. Accurate prediction of the temperature evolution in the combined MD-TTM method requires reliable accuracy in electron heat capacity, electron thermal conductivity, and electron–phonon coupling factor across the temperatures generated. This study uses the electronic density of states (DOS) obtained from first-principle calculations. The calculated electron temperature-dependent parameters are used in MD-TTM simulations to study the laser metal interactions in FCC and BCC metals and the phenomenon of laser shock loading and melting. This study uses FCC Al and BCC Ta as model systems to demonstrate this capability. When subjected to short pulsed laser shocks, the dynamic failure behavior predicted using temperature-dependent parameters is compared with the experimentally reported single-crystal and nanocrystalline Al and Ta systems. The MD-TTM simulations also investigate laser ablation and melting behavior of Ta to compare with the ablation threshold reported experimentally. In conclusion, this manuscript demonstrates that integrating the temperature-dependent parameters into MD-TTM simulations leads to the accurate modeling of the laser–metal interaction and allows the prediction of the kinetics of the solid–liquid interface.

36 MATERIALS SCIENCE↗

Implementation of a laser–neutron pump–probe capability for inelastic neutron scattering

Knowledge about nonequilibrium dynamics in spin systems is of great importance to both fundamental science and technological applications. Inelastic neutron scattering (INS) is an indispensable tool to study spin excitations in complex magnetic materials. However, conventional INS spectrometers currently only perform steady-state measurements and probe averaged properties over many collision events between spin excitations in thermodynamic equilibrium, while the exact picture of re-equilibration of these excitations remains unknown. In this paper, we report on the design and implementation of a time-resolved laser–neutron pump–probe capability at hybrid spectrometer (beamline 14-B) at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory. This capability allows us to excite out-of-equilibrium magnons with a nanosecond pulsed laser source and probe the resulting dynamics using INS. Here, we discussed technical aspects to implement such a capability in a neutron beamline, including choices of suitable neutron instrumentation and material systems, laser excitation scheme, experimental configurations, and relevant firmware and software development to allow for time-synchronized pump–probe measurements. We demonstrated that the laser-induced nonequilibrium structure factor is able to be resolved by INS in a quantum magnet. In conclusion, the method developed in this work will provide SNS with advanced capabilities for performing out-of-equilibrium measurements, opening up an entirely new research direction to study out-of-equilibrium phenomena using neutrons.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Pre-screening to guide coronary artery calcium scoring for early identification of high-risk individuals in the general population

Abstract Aims To evaluate the ability of Systematic COronary Risk Estimation 2 (SCORE2) and other pre-screening methods to identify individuals with high coronary artery calcium score (CACS) in the general population. Methods and results Computed tomography-based CACS quantification was performed in 6530 individuals aged 45 years or older from the general population. Various pre-screening methods to guide referral for CACS were evaluated. Miss rates for high CACS (CACS ≥300 and ≥100) were evaluated for various pre-screening methods: moderate (≥5%) and high (≥10%) SCORE2 risk, any traditional coronary artery disease (CAD) risk factor, any Risk Or Benefit IN Screening for CArdiovascular Disease (ROBINSCA) risk factor, and moderately (>3 mg/24 h) increased urine albumin excretion (UAE). Out of 6530 participants, 643 (9.8%) had CACS ≥300 and 1236 (18.9%) had CACS ≥100. For CACS ≥300 and CACS ≥100, miss rate was 32 and 41% for pre-screening by moderate (≥5%) SCORE2 risk and 81 and 87% for high (≥10%) SCORE2 risk, respectively. For CACS ≥300 and CACS ≥100, miss rate was 8 and 11% for pre-screening by at least one CAD risk factor, 24 and 25% for at least one ROBINSCA risk factor, and 67 and 67% for moderately increased UAE, respectively. Conclusion Many individuals with high CACS in the general population are left unidentified when only performing CACS in case of at least moderate (≥5%) SCORE2, which closely resembles current clinical practice. Less stringent pre-screening by presence of at least one CAD risk factor to guide CACS identifies more individuals with high CACS and could improve CAD prevention.

Ties, Daan (ORCID:0000000164729886)↗

Spectroscopic signatures of next-nearest-neighbor hopping in the charge and spin dynamics of doped one-dimensional antiferromagnets

In this work, we study the impact of next-nearest-neighbor (nnn) hopping on the low-energy collective excitations of strongly correlated doped antiferromagnetic cuprate spin chains. Specifically, we use exact diagonalization and the density matrix renormalization group method to study the single-particle spectral function, the dynamical spin and charge structure factors, and the Cu L-edge resonant inelastic x-ray scattering (RIXS) intensity of the doped t-t'-J model for a set of t' values. We find evidence for the breakdown of spin-charge separation as |t'| increases and identify its fingerprints in the dynamical response functions. The inclusion of nnn hopping couples the spinon and holon excitations, resulting in the formation of a spin-polaron, where a ferromagnetic spin polarization cloud dresses the doped carrier. The spin-polaron manifests itself as additional spectral weight in the dynamical correlation functions, which appear simultaneously in the spin- and charge-sensitive channels. We also demonstrate that RIXS can provide a unique view of the spin-polaron, due to its sensitivity to both the spin and charge degrees of freedom.

1D spin chains↗

Explainable AI for a No-Teardown Vehicle Component Cost Estimation: A Top-Down Approach

The broader ambition of this article is to popularize an approach for the fair distribution of the quantity of a system's output to its subsystems while allowing for underlying complex subsystem level interactions. Particularly, we present the use of this framework on a very specific (but generalizable) application, interesting for a more general AI audience. Here, we detail a data-driven approach to vehicle price modeling and its component price estimation by leveraging a combination of concepts from machine learning and game theory. We show an alternative to common teardown methodologies and surveying approaches for component and vehicle price estimation at the manufacturer's suggested retail price (MSRP) level that has the advantage of bypassing uncertainties involved in gathering teardown data, the need to perform expensive and biased surveying, and the need to perform retail price equivalent or indirect cost multiplier adjustments to mark up direct manufacturing costs to MSRP. This novel exercise not only provides accurate pricing of the technologies at the customer level, but also shows the, a priori known, large gaps in pricing strategies between manufacturers, vehicle classes, market segments, etc. There is also clear interaction between the price of technologies and other specifications present in vehicles. Those results are indication that old methods of manufacturer-level component costing, aggregation, and application of flat and rigid adjustment factors should be carefully examined. The findings are based on a database developed by Argonne, which includes over 64,000 vehicles covering MY1990 to MY2020 with hundreds of vehicle specs.

97 MATHEMATICS AND COMPUTING↗

Lung cancer mortality among construction workers: implications for early detection

Objectives This study examined predictors of lung cancer mortality, beyond age and smoking, among construction workers employed at US Department of Energy (DOE) sites to better define eligibility for low-dose CT (LDCT) lung cancer screening. Methods Predictive models were based on 17 069 workers and 352 lung cancer deaths. Risk factors included age, gender, race/ethnicity, cigarette smoking, years of trade or DOE work, body mass index (BMI), chest X-ray results, spirometry results, respiratory symptoms, beryllium sensitisation and personal history of cancer. Competing risk Cox models were used to obtain HRs and to predict 5-year risks. Results Factors beyond age and smoking included in the final predictive model were chest X-ray changes, abnormal lung function, chronic obstructive pulmonary disease (COPD), respiratory symptoms, BMI, personal history of cancer and having worked 5 or more years at a DOE site or in construction. Risk-based LDCT eligibility demonstrated improved sensitivity, specificity and positive predictive value compared with current US Preventive Services Task Force guidelines. The risk of lung cancer death from 5 years of work in the construction industry or at a DOE site was comparable with the risk from a personal cancer history, a family history of cancer or a diagnosis of COPD. LDCT eligibility criteria used for DOE construction workers, which includes factors beyond age and smoking, identified 86% of participants who eventually would die from lung cancer compared with 51% based on age and smoking alone. Conclusions Results support inclusion of risk from occupational exposures and non-malignant respiratory clinical findings in LDCT clinical guidelines.

Public, Environmental & Occupational Health↗

Examining United States Nuclear Weapon Educational Initiatives_A Quantitative Research Study on the Satisfaction of Participants Within the Nuclear Weapons Community

This study focused on a few United States nuclear weapons educational initiatives exploring six classroom environment factors that may or may not influence Satisfaction in a virtual or live classroom environment within the nuclear weapons community. The research explored Personalization, Involvement, Student Cohesiveness, Task Orientation, Innovation, and Individualization. The United States nuclear weapons community needed to attract new and talented individuals to the nuclear weapons profession. This study added to the nuclear weapons community by researching factors that may aid academic instructors, and curriculum developers create new and inventive ways of incorporating these factors into existing or new nuclear weapons educational courses. Convenience sampling was the data collection method used to gather quantitative research data. One hundred and seven voluntary participants utilized the College and University Classroom Environment Inventory with the Los Alamos National Laboratory's consent. There is not much concurrent research on Satisfaction within the live and virtual classroom environment. This research was vital for future research into how to increase participant satisfaction. The study provided the nuclear weapons community with grounded analysis to help create and guide new classes and course creation, possibly increasing Satisfaction in a live and virtual classroom environment. According to binary logistic regression, there was a statistically significant relationship among the dependent variable, Satisfaction, and two independent variables, Involvement, and Task Orientation in the classroom environment within the nuclear weapons community. Future nuclear educational programs may increase Satisfaction in the classroom environment by increasing participant Involvement and Task Orientation within a class using the CUCEI as a reference.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

MalGen: Malware Generation with Specific Behaviors to Improve Machine Learning-based Detectors

In recent years, infections and damage caused by malware have increased at exponential rates. At the same time, machine learning (ML) techniques have shown tremendous promise in many domains, often out performing human efforts by learning from large amounts of data. Results in the open literature suggest that ML is able to provide similar results for malware detection, achieving greater than 99% classifcation accuracy [49]. However, the same detection rates when applied in deployed settings have not been achieved. Malware is distinct from many other domains in which ML has shown success in that (1) it purposefully tries to hide, leading to noisy labels and (2) often its behavior is similar to benign software only differing in intent, among other complicating factors. This report details the reasons for the diffcultly of detecting novel malware by ML methods and offers solutions to improve the detection of novel malware.

97 MATHEMATICS AND COMPUTING↗

MVP-CTL Fellowship for Suicide Intervention (CRADA Final Report)

Research conducted with Crisis Text Line (CTL) served as an important stepping stone in the group’s ongoing work of developing natural language processing (NLP) methodologies to discover indicators of suicide factors in the U.S. veteran population. With rising cases of suicide, detecting risk factors among veterans is of growing concern. Socio-economic factors are often under-reported along structured medical variables, and extracting information through NLP methods may improve the sensitivity of suicide prediction models. The research explored through the CTL collaboration provided insights on suicide crisis detection and de-escalation, experience in applying scalable data analysis on real world datasets, contributions to study designs for detecting rare-event and produced transferable methods applicable to the domain of veteran suicide mitigation. Tools developed during this research directly benefits ongoing work on the Million Veteran Project (MVP) collaboration with the Department of Veteran Affairs (VA).

99 GENERAL AND MISCELLANEOUS↗

Unsupervised Learning Based Interaction Force Model for Nonspherical Particles in Incompressible Flows

This project provides a neural network-based interaction force model for gas-solid flows from low to intermediate Reynolds numbers and concentration, which can be linked to MFiX-DEM. We have constructed a database of the interaction force between the irregular-shaped particles using a spherical harmonic method and the fluid phase based on the particle-resolved direct numerical simulation (PR-DNS) with immersed boundary-based gas kinetic scheme. Unsupervised learning method, i.e., variational auto-encoder (VAE) has been applied to extract the primitive shape factors determining the drag force, lifting forces, and torque. The interaction force model has been trained and validated with a simple but effective multi-layer feed-forward neural network: multi-layer perceptron (MLP), which will be concatenated after the encoder of the previously trained VAE for geometry feature extraction for single, irregular particles. We have trained transpose convolutional neural networks with the PR-DNS data to predict the velocity and pressure gradient of the single particle systems and utilized them to calculate drag force of multi-particle systems. This model can provide high computational efficiency because it does not require collecting multiparticle system data from PR-DNS.

99 GENERAL AND MISCELLANEOUS↗

Physical, Chemical, and Mineralogical Characterizations of MSWI Ash Product and Recommendations for Downstream Processing

The primary objectives of this project are to (1) systematically characterize MSWI ash, and (2) based on characterization findings, design preliminary flowsheets for downstream processing. To achieve these objectives, a total of ten tasks were completed, including sample collection, physical separation tests, liberation tests, synthetic MSWI ash preparation, elemental composition analysis, sequential chemical extraction, mineralogical characterization, pozzolanic activity characterization, thermal stability characterization, processing flowsheet design, TEA and T2M, and project performance reporting. Many useful findings and conclusions were obtained from the exhaustive efforts of this project from several different aspects, including: a) Valuable Metals in MSWI Ash: MSWI ash contains a diverse array of valuable metals. Based on potential recoverable values, the most valuable metals present in MSWI ash include Fe, Ti, Mn, Cu, Zn, V, Co, Ni, Sr, Sn, Ag, Mo, and Sc. Some of these metals have been identified as critical minerals by DOE and DOI, suggesting that MSWI is a promising feedstock for critical mineral recovery. Noticeable graphical and seasonable variations in the valuable metal content of MSWI ash were observed. Nevertheless, it was challenging to discern any clear, definitive patterns for conclusions from those observations. Compared with bottom ash, fly ash contains more volatile metals, such as Zn and Sn, but less nonvolatile metals, such as Fe, Mn, Cu, Zn, Co, and Ni. Mineralogical analyses showed that MSWI ash contains a substantial amount of calcium minerals, such as portlandite, lime, gypsum, and calcite. In addition, it was found that different types of valuable metals often exist in the same particles. b) Physical Separation of MSWI Ash: Both dry sieving and wet sieving were performed on MSWI ash. A notable disparity in the size distribution of the same material was observed when using the two different sieving methods. The disparity is due to the agglomeration of small particles. For the valuable metals investigated, no significant enrichment in a specific size fraction was observed, suggesting that it is challenging to preconcentrate the valuable metals through size fractionation. Due to the presence of ferromagnetic materials, such as Fe, most of the materials reported to the magnetic products obtained by dry magnetic separation. However, the enrichment effect is minimal due to the existence of particle agglomerates. Density separation at a cut-off density of 2.7 SG or higher led to noticeable enrichment of selected valuable metals, particularly Ti. The unburned carbon present in MSWI ash was effectively removed by flotation using diesel as the collector. A novel reagent scheme, Na2S plus cationic collectors, that can efficiently beneficiate nonferrous metals plus Co was developed. c) Liberation Tests: The particle size of MSWI ash was effectively reduced by grinding, and as a result, the encapsulated valuable metal particles (if any) were liberated to a certain degree. However, particle size reductions did not noticeably enhance the beneficiation performance using the physical separation methods, primarily due to the inefficiency of these methods in processing fine particles and/or a possibility that insufficient liberation is not a limiting factor for achieving satisfactory physical separation performance. Valuable metals were classified into water leachable, ion-exchangeable, acid soluble, reducible, oxidable, and insoluble forms. It was found that the distributions in the different categories, i.e., the occurrence modes of the valuable metals, were not affected by the particle size. d) Leaching Characteristics of Metals from MSWI Ash: Most of the valuable metals were extracted from the fly ash samples when using 1 M HCl or HNO3 as the lixiviant. The leaching reaction is a very fast process, which can reach equilibrium within the first 5 min. The releasing of Co, Ni and Ag are sensitive to leaching temperature, a higher recovery value could be obtained when using relatively higher leaching temperatures. The leachability of the valuable metals present in MSWI bottom ash is relatively lower than that of fly ash. Leaching recoveries increased with elevations in the acid concentration. Relatively high leaching recoveries were obtained for REEs, Mn, Co, Ni, Cu, and Zn using 1 M HCl or HNO3 as the lixiviant. Elevations in the reaction temperature noticeably increased the leachability of the valuable metals, whereas the leachability was barely influenced by oxidizing and reducing agents. Similar to fly ash, leaching valuable metals from bottom ash is a rapid process, with most of the leaching reaction completed within the first 5 minutes. e) Combusted iPhones: The original structure of iPhones was remained after treating at 400 ºC and 600 ºC, while after being treated at 800℃, the screen bent, and the back cover of iPhone melted. Increasing the combustion temperature to 1000℃, the screen scattered, and most of the components turned into ashes. Combustion enhanced the leachability of REEs, while the leachability of the other valuable metals, except for Zn, was barely affected. Most of the REEs present in the original iPhones occurred as oxidizable forms. With elevations in the combustion temperature up to 600 ºC, the oxidizable REEs were transformed to acid soluble forms. However, further elevations in temperature resulted in decreases in the acid soluble fraction and corresponding increases in the reducible and oxidizable forms. Additionally, combustion temperature also significantly altered the occurrence modes of other metals present in the iPhones. f) Synthetic MSWI Ash: It was found that in the absence of hydrogen peroxide, all the elements except for Si were leached to certain degrees. It is noteworthy that approximately 80% of Zn was leached with 1.2 M HCl. When hydrogen peroxide was added to the reaction system, noticeable increases in the leaching recovery of Fe, Mn, Co, Ni, and Cu were observed. The leaching recovery of Al and Si was barely affected by adding hydrogen peroxide. These results suggested that the majority of Zn in the synthetic MSWI ash existed as metal oxide, a portion of Fe, Mn, Co, Ni, and Cu existed as metal oxide, and Al and Si are associated with glasses which are difficult to leach. Additionally, the remaining Fe, Mn, Co, Ni, and Cu in the metallic form were efficiently oxidized in the presence of hydrogen peroxide. g) Pozzolanic Activity and Thermal Stability of MSWI Ash: MSWI fly ash has higher pozzolanic activity compared to the bottom ash sample, which indicates that the fly ash sample consumed more portlandite because of its smaller particle size as reactivity fundamentally relates to reaction surface area. However, after the recovery of valuable elements, the pozzolanic activity of both the valuable elements fraction and the less valuable elements-rich products decreased significantly, which means that the valuable elements recovery lowers the Ca(OH)2 consumption, thus leading to the low activity of SCM. h) Flowsheet Design for Metal Recovery from MSWI Ash: Based on the results of the comprehensive physical separation and acid leaching tests, circuits that enable the beneficiation of the valuable metals were developed. In these circuits, the valuable metals are recovered into nonferrous, ferrous, and other valuable metal concentrates, which are processed separately in the acid leaching step. The subsequent separation and purification steps are simplified due to the physical beneficiation step. In addition, the overall recovery cost is reduced since physical beneficiation is much cheaper compared with chemical processing. Using different technologies, such as selective precipitation and solvent extraction, a comprehensive hydrometallurgical circuit was designed, and compounds of Cu, Zn, Mn, Co, and Ni with a purity close to or even higher than 95% were successfully generated.

36 MATERIALS SCIENCE↗

Sensitivity of a Subject-specific Ankle Sprain Simulation to Extrinsic Versus Intrinsic Biomechanical Factors

Ankle sprains are the most common musculoskeletal injury in sport and military activity, despite existing prophylactic strategies. The purpose of this report was to develop a probabilistic simulation of lateral ankle sprains during single-limb drop landing, towards accelerating innovation in ankle sprain prevention. A deterministic, subject-specific musculoskeletal model was extended with automation and probabilistic distributions on sprain-related biomechanical factors. Probabilistic simulations were generated using traditional Monte Carlo techniques and the advanced mean value method, a more computationally-efficient approach. Predicted distributions of peak ankle joint rotations, velocities, and moments borne by supporting passive structures agreed favorably with the deterministic model and with reports of real sprain biomechanics. Parameter sensitivities identified that predictions were most strongly influenced by drop height, subtalar joint posture at contact, invertor/evertor co-activation, and passive ankle stiffness. The advanced mean value method predicted confidence bounds comparable to a 1000-trial Monte Carlo simulation, and required only 14 model evaluations and 4-min processing time. The extended probabilistic simulation may be useful to virtually test new prophylactic strategies for ankle sprains, and is made available for open-source use (https://simtk.org/projects/sprain-sim).

60 APPLIED LIFE SCIENCES↗

An evaluation of prognostic factors, oncologic outcomes, and management for primary and recurrent squamous cell carcinoma of the vulva

Objective: To evaluate prognostic factors, outcomes, and management patterns of patients treated for squamous cell carcinoma of the vulva. Methods: One hundred sixty-four women were retrospectively identified with primary squamous cell carcinoma of the vulva treated at our institution between 1/1996–12/2018. Descriptive statistics were performed on patient, tumor, and treatment characteristics. The χ 2 tests and t-tests were used to compare categorical variables and continuous variables, respectively. Recurrence free survival (RFS), overall survival (OS), and disease-specific survival (DSS) were analyzed with Kaplan-Meier estimates, the log-rank test, and Cox proportional hazards. Results: Median follow-up was 52.5 months. Five-year RFS was 67.9%, 60.0%, 42.1%, and 20.0% for stage I–IV, respectively. Five-year DSS was 86.2%, 81.6%, 65.0%, and 42.9% for stage I–IV, respectively. On multivariate analysis, positive margins predicted overall RFS (hazard ratio [HR]=3.55; 95% confidence interval [CI]=1.18–10.73; p=0.025), while presence of lichen sclerosus on pathology (HR=2.78; 95% CI=1.30–5.91; p=0.008) predicted local RFS. OS was predicted by nodal involvement (HR=2.51; 95% CI=1.02–6.13; p=0.043) and positive margins (HR=5.19; 95% CI=2.03–13.26; p=0.001). Adjuvant radiotherapy significantly improved RFS (p=0.016) and DSS (p=0.012) in node-positive patients. Median survival after treatment of local, groin, and pelvic/distant recurrence was 52, 8, and 5 months, respectively. Conclusion: For primary treatment, more conservative surgical approaches can be considered with escalation of treatment in patients with concurrent precursor lesions, positive margins, and/or nodal involvement. Further studies are warranted to improve risk stratification in order to optimize treatment paradigms for vulvar cancer patients.

60 APPLIED LIFE SCIENCES↗

MicroRNAs as diagnostic and prognostic biomarkers of age-related macular degeneration: advances and limitations

A main cause of vision loss in the elderly is age-related macular degeneration (AMD). Among the cellular, biochemical, and molecular changes linked to this disease, inflammation and angiogenesis appear as being crucial in AMD pathogenesis and progression. There are two forms of the disease: dry AMD, accounting for 80–90% of cases, and wet AMD. The disease usually begins as dry AMD associated with retinal pigment epithelium and photoreceptor degeneration, whereas wet AMD is associated with choroidal neovascularization resulting in severe vision impairment. The new vessels are largely malformed, leading to blood and fluid leakage within the disrupted tissue, which provokes inflammation and scar formation and results in retinal damage and detachment. MicroRNAs are dysregulated in AMD and may facilitate the early detection of the disease and monitoring disease progression. Two recent reviews of microRNAs in AMD had indicated weaknesses or limitations in four earlier investigations. Studies in the last three years have shown considerable progress in overcoming some of these concerns and identifying specific microRNAs as biomarkers for AMD. Further large-scale studies are warranted using appropriate statistical methods to take into account gender and age disparity in the study populations and confounding factors such as smoking status.

60 APPLIED LIFE SCIENCES↗

Minimum Detectable Quantity Calculation for Radiation Portal Monitors

The minimum detectable quantity of a radiation portal monitor is the smallest amount of radioactive material that can be detected passing through the monitor (with a specified detection probability). The minimum detectable quantity is a function of many factors, including isotope, velocity, distance between pillars, height of portal and vehicle, source distribution and position, background radiation, background suppression, detector volume and positions, detector efficiency, decision metrics and algorithms, the presence of NORM (naturally occurring radioactive material), and alarm thresholds. Experimentally testing a radiation portal monitor to failure for all combinations of these factors is extremely time-consuming and often cost prohibitive. This document outlines a straightforward method for quickly estimating the minimum detectable quantity for moving sources over a large variety of conditions with a minimal number of static measurements. The document also describes a proof of concept software application that the International Atomic Energy Agency has designed based on the described method that can be used by Member States to estimate a monitor’s minimum detectable quantity.

Blessinger, Christopher S.↗

Optical systems fabricated by printing-based assembly

Provided are optical devices and systems fabricated, at least in part, via printing-based assembly and integration of device components. In specific embodiments the present invention provides light emitting systems, light collecting systems, light sensing systems and photovoltaic systems comprising printable semiconductor elements, including large area, high performance macroelectronic devices. Optical systems of the present invention comprise semiconductor elements assembled, organized and/or integrated with other device components via printing techniques that exhibit performance characteristics and functionality comparable to single crystalline semiconductor based devices fabricated using conventional high temperature processing methods. Optical systems of the present invention have device geometries and configurations, such as form factors, component densities, and component positions, accessed by printing that provide a range of useful device functionalities. Optical systems of the present invention include devices and device arrays exhibiting a range of useful physical and mechanical properties including flexibility, shapeability, conformability and stretchablity.

Rogers, John↗