Individual Array Research Articles

Evaluating factors influencing infrasonic signal detection and automatic processing performance utilizing a regional network.

Physical and deployment factors that influence infrasound signal detection and assess automatic detection performance for a regional infrasound network of arrays in the Western U.S. are explored using signatures of ground truth (GT) explosions (yields). Despite these repeated known sources, published infrasound event bulletins contain few GT events. Arrays are primarily distributed toward the south-southeast and south-southwest at distances between 84 and 458 km of the source with one array offering azimuthal resolution toward the northeast. Events occurred throughout the spring, summer, and fall of 2012 with the majority occurring during the summer months. Depending upon the array, automatic detection, which utilizes the adaptive F-detector successfully, identifies between 14% and 80% of the GT events, whereas a subsequent analyst review increases successful detection to 24%-90%. Combined background noise quantification, atmospheric propagation analyses, and comparison of spectral amplitudes determine the mechanisms that contribute to missed detections across the network. This analysis provides an estimate of detector performance across the network, as well as a qualitative assessment of conditions that impact infrasound monitoring capabilities. The mechanisms that lead to missed detections at individual arrays contribute to network-level estimates of detection capabilities and provide a basis for deployment decisions for regional infrasound arrays in areas of interest.

Predicting User Performance in Augmented Reality User Interfaces with Image Analysis Algorithms

This study determines how to apply existing image analysis measures of visual clutter to augmented reality user interfaces, in conjunction with other factors that may affect performance such as the percentage of virtual objects compared to real objects in an interface, and the type of object a user is searching for (real or virtual). Image analysis measures of clutter were specifically chosen as they can be applied to complex and naturalistic images as is common to experience while using an AR UI. The end goal of this research is to develop an algorithm capable of predicting user performance for a given AR UI. In this experiment, twelve participants performed a visual search task of locating a target object in an array of objects where some objects were virtual, and some were real. Participants completed this task under three different clutter levels (low, medium, high) against five different levels of virtual object percentage (0%, 25%, 50%, 75%, 100%) and two types of targets (real, virtual) with repetition. Task performance was measured through response time. Results show significant differences in response time between clutter levels and between virtual object percentage, but not target type. Participants consistently had more difficulty finding objects in more cluttered scenes, where clutter was determined through image analysis methods, and had more difficulty in finding objects when the virtual of objects was at 50% as opposed to other scenarios. Response time positively correlated to measures of combined clutter (virtual and real) arrays but not for measures of clutter taken of the individual array components (virtual or real), and positively correlated with the clutter scores of the target objects themselves.

#NaturalDye

Natural dyes from plants, insects, and fungi can be used to color yarns and textiles by craftspeople. Craft communities interested in natural dyes are using social media platforms such as Instagram to connect and share knowledge and to generate commerce for their products. #Naturaldye is a documentary film that explores the use of Instagram as a pedagogical, social, commercial, and creative space where dyers foster community and support businesses. Participants in the film discuss what types of information they find essential to articulate while also describing themselves as part of a community of other makers and artists. Theoretically, #Naturaldye is situated at the intersection of the circuit of style-fashion-dress (Kaiser, 2012) and imagined communities (Anderson, 1983). Social media platforms like Instagram enable articulation between fashion, textiles, commerce, and craftspeople where knowledge of natural dyes, dyers, and their work is conveyed to a wider array of individuals that become part of an imagined community through craft.

Assessment of Red Blood Cell-Mediated Microvascular Occlusion in Sickle Cell Disease By a Novel Electrical Impedance-Based Microfluidic Device

Introduction: Sickle cell disease (SCD) is a recessive genetic disorder caused by the mutated sickle hemoglobin (HbS) in red blood cells (RBCs). HbS polymerizes in a hypoxic environment, which leads to increased adhesiveness and decreased deformability of RBCs, and ultimately contributes to microvascular occlusion in SCD. As RBC deformability and the associated microvascular occlusion are predictors of individual microcirculatory health, previous studies have developed microfluidic devices for deformability-based RBC sorting in microscale flow, albeit with relatively low throughput. An easy-to-use, point-of-care assay to rapidly assess RBC-mediated microvascular occlusion can be clinically useful in examining the outcome of novel targeted and curative therapies, such as anti-sickling drugs and gene therapies, for patients with SCD. Here, we present an electrical impedance-based microfluidic device and functional assessment of RBC-mediated microvascular occlusion in SCD. Methods: Venous blood samples were collected in EDTA from subjects with homozygous SCD (HbSS, N=12) and controls (HbAA, N=5) under consent in an IRB-approved protocol. Microfluidic devices were fabricated using standard photolithography and polydimethylsiloxane (PDMS) micro-molding protocols. The microchannel consisted of micropillar arrays forming microcapillaries from 3-12 μm, with each array coupled with a pair of gold electrodes on the channel bottom surface (Figure 1A). Two 40-μm-wide side passageways mimicking the anastomoses in the capillary bed were designed to prevent microchannel upstream clogging (Figure 1A inset). A macroscopic view of the device is shown in Figure 1B. The 12-μm array was designed to filter large-cell aggregates and was excluded from our analysis. An impedance analyzer coupled with a custom printed-circuit board was used to record the electrical impedance at a spot frequency of 10 kHz. Prior to the experiments, the microchannel was blocked and rinsed to prevent non-specific adhesion of blood cells. Thereafter, the initial electrical impedance reading of each array was obtained. RBCs suspended at 20% hematocrit in PBS were then perfused through the microchannel under the same inlet pressure for 20 min. Next, the microchannel was washed and a second electrical impedance reading was obtained. The microchannel was then imaged under an inverted microscope, and occlusions of each array were manually quantified. The electrical impedance and occlusion results are reported as percent changes. Data are reported as mean ± standard deviation (SD). Pearson's correlation coefficient (PCC) was used to derive correlation statistics. Results: We observed increased microcapillary occlusion caused by HbSS- vs. HbAA-containing RBCs (Figure 1C, mean microcapillary occlusion percentage ± SD (%) = 24.33 ± 16.88 vs. 5.01 ± 1.25 for 3-μm array, 6.05 ± 4.09 vs. 2.19 ± 0.59 for 4-μm array, 2.77 ± 2.59 vs. 0.82 ± 0.82 for 6-μm array, 1.08 ± 2.28 vs. 0 ± 0 for 8-μm array, and 0.42 ± 1.14 vs. 0 ± 0 for 10-μm array). Similarly, we observed elevated electrical impedance change induced by HbSS- vs. HbAA-containing RBCs (Figure 1D, mean electrical impedance change ± SD (%) = 12.03 ± 8.97 vs. 2.44 ± 0.84 for 3-μm array, 1.79 ± 1.65 vs. 0.91 ± 0.42 for 4-μm array, 0.88 ± 1.14 vs. 0.58 ± 0.67 for 6-μm array, 0.16 ± 0.31 vs. 0.32 ± 0.37 for 8-μm array, and 0.06 ± 0.16 vs. 0.05 ± 0.17 for 10-μm array). Moreover, we found that the electrical impedance changes of individual arrays exhibited a significant correlation to the occlusion percentage within the corresponding arrays (Figure 1E, PCC = 0.9817, N = 85, p < 0.001). Conclusions: Findings suggest that a novel microfluidic platform integrated with micropillar arrays and electrical impedance readout can be used for standardized in vitro functional assessment of RBC-mediated microvascular occlusion in SCD. Electrical impedance change due to RBC-mediated microcapillary occlusion may serve as a new parameter for monitoring RBC health and function without the need for high-resolution microscopic imaging. RBC mediated microcapillary occlusion may serve as a new parameter to assess the clinical efficacy of treatments that improve RBC deformability and rheology, such as hemoglobin modifying drugs, anti-sickling agents, and therapies with curative intent. Disclosures Maji: Xatek Inc.: Patents & Royalties. An:Hemex Health, Inc.: Patents & Royalties. Ahuja:Genentech: Consultancy, Honoraria; Sanofi Genzyme: Consultancy, Honoraria; XaTek, Inc.: Consultancy, Patents & Royalties, Research Funding. Little:BioChip Labs: Patents & Royalties: SCD Biochip (patent, no royalties); Hemex Health, Inc.: Patents & Royalties: Microfluidic electropheresis (patent, no royalties); Bluebird Bio: Research Funding; GBT: Research Funding; GBT: Membership on an entity's Board of Directors or advisory committees; NHLBI: Research Funding. Mohseni:Xatek Inc.: Consultancy, Patents & Royalties, Research Funding. Suster:Xatek Inc.: Consultancy, Patents & Royalties, Research Funding. Gurkan:BioChip Labs: Patents & Royalties; Xatek Inc.: Patents & Royalties; Dx Now Inc.: Patents & Royalties; Hemex Health, Inc.: Consultancy, Current Employment, Patents & Royalties, Research Funding.

Metformin decreases miR-122, miR-223 and miR-29a in women with polycystic ovary syndrome.

Metformin is associated with increased insulin sensitivity, whereas oral contraceptive pills (OCP) could increase the risk for type 2 diabetes (T2D) in women with polycystic ovary syndrome (PCOS). Certain miRNAs might serve as biomarkers for the risk of T2D. The aim of this study was to investigate changes in circulating miRNA levels during treatment with metformin and OCP in women with PCOS. Sixty-five women with PCOS according to Rotterdam criteria were randomized to metformin (2 g/day), metformin + OCP (150 mg desogestrel + 30 µg ethinylestradiol) or OCP alone for 12 months. Serum miRNA analysis was performed with individual RT-qPCR or Taqman low density array cards of 22 selected miRNAs previously related to PCOS, glucose and/or lipid metabolism. miR-122 and miR-29a levels were decreased after treatment with metformin compared with metformin + OCP and OCP group: miR-122: log2 difference −0.7 (P = 0.01) and −0.7 (P = 0.02), miR-29a: log2 difference −0.5 (P = 0.01) and −0.4 (P = 0.04), while miR-223 levels were decreased in the metformin + OCP group after treatment: log2 difference −0.5 (P = 0.02). During the treatment period, a significant weight loss was observed in the metformin group compared with the OCP group. In the OCP group, miRNA levels were unchanged during the treatment period. Levels of circulating miRNAs associated with lipid and glucose metabolism decreased during metformin treatment. Changes in miRNA levels in the metformin group could be explained by the simultaneous weight loss in the same group. These results support the notion that metformin treatment alone may be superior for metabolic health compared with OCP.

Assessing perceptions about medications for opioid use disorder and Naloxone on Twitter

Introduction: Qualitative analysis of Twitter posts reveals key insights about user norms, informedness, perceptions, and experiences related to opioid use disorder (OUD). This paper characterizes Twitter message content pertaining to medications for opioid use disorder (MOUD) and Naloxone.Methods: In-depth thematic analysis was conducted of 1,010 Twitter messages collected in June 2019. Our primary aim was to identify user perceptions and experiences related to harm reduction (e.g., Naloxone) and MOUD (e.g., sublingual and Extended-release buprenorphine, Extended-release naltrexone, Methadone).Results: Tweets relating to OUD were most commonly authored by general Twitter users (43.8%), private residential or detoxification programs (24.6%), healthcare providers (e.g., physicians, first responders; 4.3%), PWUOs (4.7%) and their caregivers (2.9%). Naloxone was mentioned in 23.8% of posts and authored most commonly by general users (52.9%), public health experts (7.4%), and nonprofit/advocacy organizations (6.6%). Sentiment was mostly positive about Naloxone (73.6%). Commonly mentioned MOUDs in our search consisted of Buprenorphine-naloxone (13.8%), Methadone (5.7%), Extended-release naltrexone (4.1%), and Extended-release buprenorphine (0.01%). Tweets authored by PWUOs (4.7%) most commonly related to factors influencing access to MOUD or adverse events related to MOUD (70.8%), negative or positive experiences with illicit substance use (25%), policies related to expanding access to treatments for OUD (8.3%), and stigma experienced by healthcare providers (8.3%).Conclusion: Twitter is utilized by a diverse array of individuals, including PWUOs, and offers an innovative approach to evaluate experiences and themes related to illicit opioid use, MOUD, and harm reduction.

A basal-bolus insulin regimen integrated microneedle patch for intraday postprandial glucose control.

Multiple daily insulin injections have been a common regimen worldwide for the management of diabetes mellitus but involved potential safety and compliance problems. In this context, a single integrated microneedle patch (IMP) with multiple release kinetics is demonstrated to provide better physiologic insulin coverage for postprandial glycemic excursion in a convenient and pain-free manner. The combination of rapid separating technique and multiple individual microneedle arrays provides the combined ability to efficiently deliver insulin into the skin within seconds and to independently control insulin release kinetics. In addition, the diabetic rats with a traditional breakfast-lunch-dinner lifestyle exhibit obvious intraday glucose fluctuations, while the hypoglycemic experiments indicate that the IMP is capable of simultaneous bolus and sustained insulin delivery to closely match the glucose rise that occurs in response to meals and efficiently minimize excessive fluctuations, suggesting the potential of this new transdermal insulin delivery system as substitutes for multiple daily injections.

Estimation and Testing of Self-Reporting Heterogeneity in Self-Assessed Health Questions

We propose a new methodology for statistically testing for reporting heterogeneity in self-assessed health (SAH) questions. We contribute to the literature by quantifying the effect of such heterogeneity in the probability distribution of SAH responses and providing a correction to that distribution that allows us to obtain an unbiased distribution of SAH responses as a function of true health. Our econometric approach extends typical ordered probit formulations for describing SAH responses by incorporating a consistent estimate of individuals' true health. True health is estimated as a latent variable obtained from information on an array of individuals' objective health binary indicators. This additional equation relating unobserved true health and observable health characteristics allows us to disentangle the effect of true health from self-reporting heterogeneity on SAH responses. We propose two different maximum likelihood procedures to estimate each effect consistently and show their performance in finite samples. The application of this methodology to the Understanding Society data set uncovers strong evidence of self-reporting heterogeneity across many individual characteristics. Failing to control for such heterogeneity masks the good health of individuals and exaggerates the occurrence of bad health states, while over(under)-states true health gradient of co-variates.

A Multi‐Array Back‐Projection Approach for Tsunami Warning

AbstractRecent development of dense strong‐motion networks and seismic array processing enables rapid tsunami predictions based on the back‐projection (BP) approach. We develop a multi‐array local BP method (MLBP) using seismic networks with epicentral distance from 0.7° to 3.5°. The local BPs using individual arrays are first calculated and are then merged into a single image of the rupture process. This multi‐array approach circumvents the issue of artifact in single‐array BP caused by the overlapping of multiple phases and coda waves. Based on the local BP approach, tsunami predictions are available 7 min after the origin time. Case studies of the 2003 Mw 8.1 Tokachi‐oki and the 2011 Mw 9.0 Tohoku earthquakes show that their rupture zones are well resolved and are comparable with principal slip areas inferred from tsunami observations. The amplitude and arrival time errors of the predicted tsunami waves are within −1.59 to 3.74 m and −10.0 to 10.0 min, which are sufficiently small for warning purposes.

Null Beamsteering Using Distributed Arrays and Shared Aperture Distributions

In this work, a novel technique using closed-form expressions is rigorously surveyed to collaboratively nullsteer uniformly distributed, planar ring, and volumetric shell distributions. To assess the radiation behavior of these geometries circular tapers is of interest for their attractiveness in derivation, design, application, and mathematical simplicity. A rigorous mathematical derivation is used for the generation of closed-form expressions of the mean-valued radiation characteristics. The numerical simulations are performed using both ANSYS HFSS and MATLAB using a finite-element distribution. To validate the analytical models, we include the measured results of a uniformly distributed ring array topology, constrained to a set of 18 elements and a uniformly distributed shell array topology constrained to 16 elements. The results of all methods are compared to demonstrate exceptional agreement in the recommended theoretical analysis. This process follows differently from traditional phased array nulling methods, which apply the unique amplitude tapers along individual phased array elements. Unlike typical adaptive beamforming algorithms, this process does not require the estimation of second-order statistical metrics and avoids expansions of large polynomial equations. It uses shared aperture characteristics in order to generate null beams simultaneously. This can also be extended to widen null widths from the compounding of these shared aperture distributions, which is shown in simulation.

Antenna performance enhancement using inter-coupling effect reducing mechanisms

Recently, thinning an antenna has resulted in attractive antenna radiation characteristics enhancement. This performance enhancement using a thin antenna array is achieved because the inter-coupling effects of the array elements are reduced. Though the thinning both reduces the weight of the antenna and enhances the radiation characteristics, iterative algorithms can further enhance the performance and hence, in this research, an optimizer algorithm and inter-coupling reducing mechanisms are applied. The excitation weights of the individual array elements are thinned by turning some of the elements off while some of the elements are turned on. The purpose of the thinning is to enhance the antenna performances like reduced SLL, high directivity, reduced power consumption and flexible radiation pattern. The SLL attenuation mechanism is applied to reduce the SLL in addition to the SLL reduction using the thinning and beamforming. Hence, in this paper, the three techniques (thinning, beamforming and SLL attenuation) are proposed to be integrated to enhance the antenna radiation characteristics. In general, the proposed combined method has resulted in much better SLL reduction, directivity improvement, and power wastage reduction.

T1. CLINICAL PROFILE AND PREVALENCE OF POSTTRAUMATIC STRESS SYMPTOMS AMONG SERVICE-USERS REFERRED FOR PSYCHOLOGICAL FOLLOW-UP: UTILITY OF ASSESSING SYMPTOMS SEVERITY RANGE

BackgroundIndividuals with psychosis and comorbid posttraumatic stress disorder (PTSD) typically present with more severe forms of illness. Subthreshold posttraumatic stress symptoms (PTSS) are also likely to cause significant distress. There is a need to enhance screening processes for distressing PTSS to encourage appropriate referral to specialized services. The PTSD checklist for DSM-5 (PCL-5) is a widely used self-report to assess PTSS, though there is concern regarding its validity for use in psychosis. If people scoring in the severe PTSS range on the PCL-5 also present with clinical profiles similar to those typically meeting diagnosis for PTSD, it will justify considering a broader range of PTSS and support the use of the PCL-5 as a brief screener. A severe range will arguably capture a wider array of individuals, including those with subthreshold PTSS who also likely require trauma-focused intervention.MethodsOne hundred and two individuals with psychosis completed the PCL-5 and a battery of clinical scales as part of an intake evaluation following referral for psychological follow-up at a clinic specializing in psychosocial interventions for psychosis. Prevalence and type of DSM-5 criterion A event were explored in conjunction with PTSS severity and referral-type. Pearson correlations identified clinical variables associated with PCL-5 total scores and were subsequently entered into a multivariate analysis of variance (MANOVA) with dichotomized PTSS severity categories (low, moderate, severe). Post hoc analyses explored significant interactions.ResultsOf the 102 participants, 21.6% reported no prior trauma and 14.7% reported non-valid events. Sixty-five participants were included in the analysis; 6.2% of which were referred for trauma. 81.5% reported criterion A events, 10.8% reported psychosis-related events, and 7.7% did not disclose an event. PCL-5 scores were dichotomized using the 33rd and 66th percentiles, translating into low (≤ 24), moderate (25–47), and severe (≥48) groups. Delusion severity and subjective stress, anxiety, depression, social anxiety, quality of life (QoL), and wellbeing were entered into a one-way MANOVA with PTSS severity groups. Significant main effects surviving Bonferroni correction emerged for all variables except delusion severity (F(2,40) = 3.06, p = .058) and wellbeing (F(2,56) = 1.50, p =.233). Stress (F(2,62) = 7.37, p = .001) was higher in the severe (M = 13.13, SD = 5.18) versus low group (M = 7.05, SD = 4.40, p = .001). Anxiety (F(2,62) = 8.02, p = .001) was also higher in the severe (M = 12.30, SD = 5.07) compared to low group (M = 5.85, SD = 5.06, p = .000), and depression (F(2,62) = 5.37, p = .007) was additionally higher in the severe (M = 12.61, SD = 5.73) compared to low group (M = 7.20, SD = 4.97, p = .005). Finally, social anxiety (F(2,58) = 4.25, p = .026.) was higher in the severe (M = 7.76, SD = 3.58) versus low group (M = 4.68, SD = 3.68, p = .029), while QoL (F(2,58) = 3.47, p = .038) was lower in the severe (M = 49.95, SD = 10.99) compared to low group (M = 58.95, SD = 13.76, p = .037).DiscussionDue to a relatively high number of invalid questionnaires (14.7%), service users should likely complete the PCL-5 in the presence of a health-care practitioner. Findings suggest inadequate referral rates for specialized services when they may indeed benefit the service-user. Severe PTSS was associated with increased symptoms of subjective anxiety, depression, stress, social anxiety, and decreased QoL, regardless of whether diagnostic criteria for PTSD was met. A severe PTSS category likely captures a broader range of individuals requiring specialized intervention and speaks to an important need to both facilitate and increase referral rate for trauma-focused therapy.

Integrated individually electrochemical array for simultaneously detecting multiple Alzheimer's biomarkers

Simultaneous detection of multiple biomarkers is benefit for reducing the detection cycles, avoiding the false-positive signals, and providing the cross validation, which provide the opportunity to understand the pathogenic mechanisms and achieve precise early diagnosis. Here, we demonstrate the mini-pillar-based individual electrochemical array for simultaneous detection of multiple biomarkers. On such platform, the mini-pillar could confine the microdroplet as individual and open-channel microreactor, which is extremely helpful for reducing reagent consumption and extracting internal information, and the electrodes array embedded in mini-pillar are integrated on one side to achieve multiple and simultaneous electrochemical sensing. The introduction of gold nanodendrites by electrodeposition has greatly enhanced sensitivity via improving probe-binding capacity and response signals. Sensitive and selective detection of multiple Alzheimer's biomarkers including Tau, ApoE4, Amyloid-β and miRNA-101 on such mini-pillar-based biosensor is also achieved. Such biosensor platform with the advantages of high-yield, high sensitivity, low-waste and multiple signals output shows great promise in sensing multiple biomolecules for disease diagnosis and health monitoring.

Trajectory-Aided Maximum-Likelihood Algorithm for Channel Parameter Estimation in Ultrawideband Large-Scale Arrays

Millimeter-wave with ultrawide bandwidth available and ability to pack massive number of antennas in a small area is considered the key enabler for future generation communication systems. Accurate understanding and modeling of the ultrawideband propagation channel with large-scale array configuration is essential. In this contribution, a realistic spherical-propagation signal model considering the spatial nonstationarity of path gain across the array elements is proposed. A novel trajectory-aided maximum-likelihood (TAMax) algorithm is proposed to extract propagation parameters from the measured data, since the existing high-resolution propagation parameter estimation algorithms are not applicable due to either prohibitively high computation loads or assumption violations. In the proposed TAMax algorithm, the high-dimensional maximum-likelihood estimation (MLE) problem is first decomposed into a subproblem where delays and amplitudes of multipath components (MPCs) are estimated at individual array elements. A novel transform is then proposed to identify multiple MPC trajectories in the delay-element domain. With interference cancellation and fast initialization obtained in the proposed transform, spherical propagation parameters are finally acquired via joint MLE with significantly decreased searching spaces. Moreover, a measurement campaign conducted at the frequency band of 27-29 GHz using a virtual uniform circular array is introduced, where the proposed TAMax algorithm is applied and validated.

(Invited) Nanoscale Llight Management Using Three-Dimensional Scanning Near-Field Optical Microscopy

In this talk, we will present an overview of aperture and apertureless type scanning near-field optical microscopy (SNOM) techniques that have been developed for the characterization of photonics-grade nanoscale materials, with a focus on three-dimensional (3D) SNOM methods. 3D SNOM has been undertaken to image the local distribution (within ~100 nm of the surface) of the electromagnetic radiation scattered by random and deterministic arrays ofmetal nanostructures or photonic crystal waveguides. Individual metal nanoparticles and metal nanoparticle arrays exhibit unique effects under light illumination, including plasmon resonance and waveguiding properties, which can be directly investigated using 3D-SNOM. In the second part of this article, we will review a few applications in which 3D-SNOM has proven to be useful for designing and understanding specific nano-optoelectronic structures and photonic materials. Examples will include the analysis of the nano-optical response phonetic crystal waveguides, aperture antennae and metal nanoparticle arrays, as well as the design of plasmonic solar cells incorporating random arrays of copper nanoparticles as an optical absorption enhancement layer, and the use of 3D-SNOM to probe multiple components of the electric and magnetic near-fields without requiring specially designed probe tips. A common denominator of these examples is the added value provided by 3D-SNOM in predicting the properties-performance relationship of nanostructured systems in photonics grade materials.

A method to estimate residential PV generation from net-metered load data and system install date

In the USA, residential photovoltaic (PV) systems are often configured for net metering “behind-the-meter”, where PV energy generation and building energy demand are reported as a combined net load to advanced metering infrastructure (AMI) meters, impeding estimates of PV generation. This work presents a methodology for modeling individual array and system-wide PV generation using only weather data, premise AMI data, and the approximate date of PV installation – information available to most distribution utilities. The study uses 36 months of data spanning nearly 850 homes with installed PV systems in Fort Collins, Colorado, USA. The algorithm estimates building energy consumption by comparing time periods before PV installation with similar periods after PV installation that have common weather and activity characteristics. Estimated building energy consumption is then compared with AMI meter data to estimate otherwise unobservable solar generation. To assess accuracy, modeled outputs are compared with directly metered PV generation and white-box physical models of PV production. Considering aggregate, utility-wide, generation estimates for the three year study period, the proposed method estimates over 75% of all days to within ±20% of established physical models. The method estimates more effectively in summer months when PV generation peaks and is of most interest to utilities. The model often outperforms physical models for days with snow cover and for arrays with shading or complex multi-roof implementations. The model also supports day-ahead PV prediction using forecasted weather data.

Electron microscopy dataset for the recognition of nanoscale ordering effects and location of nanoparticles

A unique ordering effect has been observed in functional catalytic nanoscale materials. Instead of randomly arranged binding to the catalyst surface, metal nanoparticles show spatially ordered behavior resulting in formation of geometrical patterns. Understanding of such nanoscale materials and analysis of corresponding microscopy images will never be comprehensive without appropriate reference datasets. Here we describe the first dataset of electron microscopy images comprising individual nanoparticles which undergo ordering on a surface towards the formation of geometrical patterns. The dataset developed in this study spans three levels of nanoscale organization: (i) individual nanoparticles (1–5 nm) and arrays of nanoparticles (5–20 nm), (ii) ordering effects (20–200 nm) and (iii) complex patterns (from nm to μm scales). The described dataset for the first time provides a possibility for the development of machine learning algorithms to study the unique phenomena of nanoparticles ordering and hierarchical organization.

A Weighting Function-Based Method for Resistivity Inversion in Subsurface Investigations

There is a high demand for high detection accuracy and resolution with respect to anomalous bodies due to the increased development of underground spaces. This study focused on the weighted inversion of observed data from individual array type electrical resistivity tomography (ERT), and developed an improved method of applying a data weighing function to the geoelectrical inversion procedure. In this method, the weighting factor as an observed data weighting term was introduced into the objective function. For individual arrays, the sensitivity decreases with increasing electrode interval. Therefore, the Jacobian matrices were computed for the observed data of individual arrays to determine the value of the weighting factor, and the weighting factor was calculated automatically during inversion. In this work, 2D combined inversion of ERT data from four-electrode Alfa-type arrays is examined. The effectiveness of the weighted inversion method was demonstrated using various synthetic and real data examples. The results indicated that the inversion method based on observed data weighted function could improve the contribution of observed data with depth information to the objective function. It has been proven that the combined weighted inversion method could be a feasible tool for improving the accuracies of positioning and resolution while imaging deep anomalous bodies in the subsurface.

Statistical Model for Quasicontinuum of Heavy Ions in Hot Plasma

A statistical description is proposed for the shape of heavy impurity spectra observed in tokamaks and stellarators, corresponding to the quasicontinuous radiation distribution, and called the quasicontinuum. For the tungsten ions, in particular, it is located in the spectral range of ∼2 to 7 nm. The method is based on the statistical plasma model of atom, which allows expressing the quasicontinuum structure through the electron density distribution of multielectron ions. The Slater distribution is used as a model density distribution. The quasicontinuum is formed by the great number of closely spaced lines of heavy ions with different degrees of ionization, and its calculation is very complicated. A comparison of the results obtained within the statistical approach with the results of the level-by-level quantum mechanical calculations shows that such a model plausibly describes the envelopes of the individual line arrays in the ion spectra. In contrast to the level-by-level calculation codes, the statistical atom model is rather simple and it can be used by a large number of users. The quasicontinuum was simulated for the tungsten, gold, lead, and gadolinium ions, which are observed in plasmas of fusion facilities. The simulation results are in fairly good agreement with the experimental data. The studies of the tungsten quasicontinuum are of interest from the point of view of plasma diagnostics, as well as determination of the tungsten impurity density and its transport in fusion facilities.

Inversion of multiple data sets acquired by different array configuration of geoelectrical resistivity method

The geoelectrical resistivity method is one of the most commonly used geophysical methods. This method uses different electrodes configuration, electrode array, depending on the purpose and conditions of the field, each type of array has its advantages and disadvantages. Due to the development of data acquisition technology, it is common for geoelectrical instruments enable to record data arising from different electrode arrays with negligible real-time construction. However, current software’s only allows to process for each individual electrode array. Inverted models of different electrode array can be integrated to build a common earth model. However, due to the nature of the geophysical inversion is non-unique solutions, it means that there will be an infinite of models that can be suitable for a measurement in a certain noise level. This leads to the same measurement data in an area with different electrode array may produce different geoelectrical models making the dificulty for integration process. To solve this problem, we utilise the simultaneous joint inversion algorithm of data sets arising from multiple electrode arrays. The test results on synthetic data show that this combination is better than the solution of each individual electrode array. The best result is a combination of pole - dipole (PD), dipole - pole (DP) and dipole - dipole (DD).