Equivalent Maps Research Articles

Molecular Characterization of Aged Bitumen with Selective and Nonselective Ionization Methods by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry. 2. Statistical Approach on Multiple-Origin Samples

Bitumen is a very viscous and complex mixture primarily used as a binder for asphalt construction. During its service life, this binder is subjected to oxidative aging, which leads to asphalt stiffness and thermal cracking of the pavement structure. The behavior of bitumen toward oxidative aging is greatly dependent on its intrinsic properties and particularly on its content of nitrogen, oxygen, and sulfur functional groups. This is of fundamental importance as the origin of the crude will influence its resistance to oxidation after several years of use in a road. It is then essential to correlate the native composition of bitumen and their corresponding oxidized products to explain changes in the physicochemical behavior of asphalt binders. Pressure aging vessel is probably the most widely used technique to simulate long-time aging of bitumen. This artificial aging technique leads to accelerated aging under high-pressure and -temperature conditions. To understand such mechanisms, characterization at the molecular level is required. Nowadays, Fourier transform ion cyclotron resonance (FTICR) is the most-used technique for the analysis of petroleum products. Bitumen samples from three different origins were subjected to PAV aging and analyzed by FTICR-MS. Coupling of electrospray ionization (ESI) and atmospheric pressure photo ionization (APPI) sources were used to provide an exhaustive characterization of the samples. Principal component analysis (PCA), which is a multivariate statistical approach, was used to separate samples according to aging and origin. Indeed, ESI coupled to PCA allowed a significant separation of samples according to their PAV-aging on the PC1 axis. PC1 scores were then used as an intensity scale to carry out a modified double bond equivalent versus carbon number (DBE vs C#) mapping. This technique allowed the characterization of specific aging markers in Oz and OzSy families for each bitumen sample. In addition, PC1 coordinates were used to develop a predictive model by principal component regression (PCR). Significant differences in sensitivity to oxidation were obtained for the three bitumen samples. Concerning APPI results, less significant differences were obtained for aging compared to those obtained by ESI. PCA coupled to APPI was also used for modified DBE vs C# maps, separating samples according to their origin. Significant differences were obtained in each bitumen sample in the different compound classes (HC, S1, N1, O1, etc.). Overall, this study demonstrates the great interest of coupling FTICR MS data to a PCA statistical approach to characterize oxidative aging of bitumen samples according to their origin.

Imaging effective oxygen diffusivity in the human brain with multiparametric magnetic resonance imaging

Cerebrovascular diseases can impair blood circulation and oxygen extraction from the blood. The effective oxygen diffusivity (EOD) of the capillary bed is a potential biomarker of microvascular function that has gained increasing interest, both for clinical diagnosis and for elucidating oxygen transport mechanisms. Models of capillary oxygen transport link EOD to measurable oxygen extraction fraction (OEF) and cerebral blood flow (CBF). In this work, we confirm that two well established mathematical models of oxygen transport yield nearly equivalent EOD maps. Furthermore, we propose an easy-to-implement and clinically applicable multiparametric magnetic resonance imaging (MRI) protocol for quantitative EOD mapping. Our approach is based on imaging OEF and CBF with multiparametric quantitative blood oxygenation level dependent (mq-BOLD) MRI and pseudo-continuous arterial spin labeling (pCASL), respectively. We evaluated the imaging protocol by comparing MRI-EOD maps of 12 young healthy volunteers to PET data from a published study in different individuals. Our results show comparably good correlation between MRI- and PET-derived cortical EOD, OEF and CBF. Importantly, absolute values of MRI and PET showed high accordance for all three parameters. In conclusion, our data indicates feasibility of the proposed MRI protocol for EOD mapping, rendering the method promising for future clinical evaluation of patients with cerebrovascular diseases.

Characteristics of Jupiter's X‐Ray Auroral Hot Spot Emissions Using Chandra

AbstractTo help understand and determine the driver of jovian auroral X‐rays, we present the first statistical study to focus on the morphology and dynamics of the jovian northern hot spot (NHS) using Chandra data. The catalog we explore dates from December 18, 2000 up to and including September 8, 2019. Using a numerical criterion, we characterize the typical and extreme behavior of the concentrated NHS emissions across the catalog. The mean power of the NHS is found to be 1.91 GW with a maximum brightness of 2.02 Rayleighs (R), representing by far the brightest parts of the jovian X‐ray spectrum. We report a statistically significant region of emissions at the NHS center which is always present, the averaged hot spot nucleus (AHSNuc), with mean power of 0.57 GW and inferred average brightness of 1.2 R. We use a flux equivalence mapping model to link this distinct region of X‐ray output to a likely source location and find that the majority of mappable NHS photons emanate from the pre‐dusk to pre‐midnight sector, coincident with the dusk flank boundary. A smaller cluster maps to the noon magnetopause boundary, dominated by the AHSNuc, suggesting that there may be multiple drivers of X‐ray emissions. On application of timing analysis techniques (Rayleigh, Monte Carlo, Jackknife), we identify several instances of statistically significant quasi‐periodic oscillations (QPOs) in the NHS photons ranging from 2.3 to 36.4 min, suggesting possible links with ultra‐low frequency activity on the magnetopause boundary (e.g., dayside reconnection, Kelvin‐Helmholtz instabilities).

An adaptive equivalent consumption minimization strategy considering catalyst temperature for plug-in hybrid electric vehicle

In the process of sufficiently considering fuel economy of plug-in hybrid electric vehicle (PHEV), the working time of engine will be reduced accordingly. The increased frequency that the three-way catalytic converter (TWCC) works in abnormal operating temperature will lead to the increasing of emissions. This paper proposes the equivalent consumption minimization strategy (ECMS) to ensure the catalyst temperature of PHEV can work in highly efficient areas, and the influence of catalyst temperature on fuel economy and emissions is considered. The simulation results show that the fixed equivalent factor of ECMS has great limitations for the underutilized battery power and the poor fuel economy. In order to further reduce fuel consumption and keep the emission unchanged, an equivalent factor map based on initial state of charge (SOC) and vehicle mileage is established by the genetic algorithm. Furthermore, an Adaptive changing equivalent factor is achieved by using the following strategy of SOC trajectory. Ultimately, adaptive equivalent consumption minimization strategy (A-ECMS) considering catalyst temperature is proposed. The simulation results show that compared with ordinary ECMS, HC, CO, and NOX are reduced by 14.6%, 20.3%, and 25.8%, respectively, which effectively reduces emissions. But the fuel consumption is increased by only 2.3%. To show that the proposed method can be used in actual driving conditions, it is tested on the World Light Vehicle Test Procedure (WLTC).

General surgeon involvement in the care of patients designated with an American Association for the Surgery of Trauma-endorsed ICD-10-CM emergency general surgery diagnosis code in Wisconsin.

The current national burden of emergency general surgery (EGS) illnesses and the extent of surgeon involvement in the care of these patients remain largely unknown. To inform needs assessments, research, and education, we sought to: (1) translate previously developed International Classification of Diseases (ICD), 9th Revision, Clinical Modification (ICD-9-CM) diagnosis codes representing EGS conditions to ICD 10th Revision, CM (ICD-10-CM) codes and (2) determine the national burden of and assess surgeon involvement across EGS conditions. We converted ICD-9-CM codes to candidate ICD-10-CM codes using General Equivalence Mappings then iteratively refined the code list. We used National Inpatient Sample 2016 to 2017 data to develop a national estimate of the burden of EGS disease. To evaluate surgeon involvement, using Wisconsin Hospital Association discharge data (January 1, 2016 to June 30, 2018), we selected adult urgent/emergent encounters with an EGS condition as the principal diagnosis. Surgeon involvement was defined as a surgeon being either the attending provider or procedural physician. Four hundred and eighty-five ICD-9-CM codes mapped to 1,696 ICD-10-CM codes. The final list contained 985 ICD-10-CM codes. Nationally, there were 2,977,843 adult patient encounters with an ICD-10-CM EGS diagnosis. Of 94,903 EGS patients in the Wisconsin Hospital Association data set, most encounters were inpatient as compared with observation (75,878 [80.0%] vs. 19,025 [20.0%]). There were 57,780 patients (60.9%) that underwent any procedure. Among all Wisconsin EGS patients, most had no surgeon involvement (64.9% [n = 61,616]). Of the seven most common EGS diagnoses, surgeon involvement was highest for appendicitis (96.0%) and biliary tract disease (77.1%). For the other five most common conditions (skin/soft tissue infections, gastrointestinal hemorrhage, intestinal obstruction/ileus, pancreatitis, diverticular disease), surgeons were involved in roughly 20% of patient care episodes. Surgeon involvement for EGS conditions ranges from highly likely (appendicitis) to relatively unlikely (skin/soft tissue infections). The wide range in surgeon involvement underscores the importance of multidisciplinary collaboration in the care of EGS patients. Prognostic/epidemiological, Level III.

Acute myocardial infarction: Development and application of an ICD-10-CM-based algorithm to a large U.S. healthcare claims-based database.

BackgroundHealthcare administrative claims data hold value for monitoring drug safety and assessing drug effectiveness. The U.S. Food and Drug Administration Biologics Effectiveness and Safety Initiative (BEST) is expanding its analytical capacity by developing claims-based definitions—referred to as algorithms—for populations and outcomes of interest. Acute myocardial infarction (AMI) was of interest due to its potential association with select biologics and the lack of an externally validated International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) algorithm.ObjectiveDevelop and apply an ICD-10-CM-based algorithm in a U.S. administrative claims database to identify and characterize AMI populations.MethodsA comprehensive literature review was conducted to identify validated AMI algorithms. Building on prior published methodology and consistent application of ICD-9-CM codes, an ICD-10-CM algorithm was developed via forward-backward mapping using General Equivalence Mappings and refined with clinical input. An AMI population was then identified in the IBM® MarketScan® Research Databases and characterized using descriptive statistics.Results and discussionBetween 2014–2017, 2.83–3.16 individuals/1,000 enrollees/year received ≥1 AMI diagnosis in any healthcare setting. The 2015 transition to ICD-10-CM did not result in a substantial change in the proportion of patients identified. Average patient age at first AMI diagnosis was 64.9 years, and 61.4% of individuals were male. Unspecified chest pain, hypertension, and coronary atherosclerosis of native coronary vessel/artery were most commonly reported within one day of AMI diagnosis. Electrocardiograms were the most common medical procedure and beta-blockers were the most commonly ordered cardiac medication in the one day before to 14 days following AMI diagnosis. The mean length of inpatient stay was 5.6 days (median 3 days; standard deviation 7.9 days). Findings from this ICD-10-CM-based AMI study were internally consistent with ICD-9-CM-based findings and externally consistent with ICD-9-CM-based studies, suggesting that this algorithm is ready for validation in future studies.

Manifold-Inspired Search-Based Algorithm for Automated Test Case Generation

Automated test case generation based on path coverage (ATCG-PC) is a black-box optimization problem whose difficulty is attributed to the one-to-many relationship between path and test cases. It results in a large number of redundant function evaluations in the search process of algorithms for ATCG-PC. To minimize the redundant function evaluations for solving ATCG-PC, the equivalent mapping subspaces are defined to decompose the search space according to the paths. Inspired by the data distribution hypothesis, we assume that the target path can be covered by searching in one neighborhood of a test case (equivalent mapping subspace) instead of the whole search space. This paper presents a manifold-inspired search-based algorithm that finds the equivalent mapping subspaces with the test-case-path relationship matrix. Furthermore, the algorithm generates test cases covering all possible paths by searching in the found subspaces. The experimental results show the proposed algorithm has significantly lower function evaluation consumption than the state-of-the-art algorithms with the highest path coverage rate in two open-source toolkits and 16 open-source real-world programs. Several orders of magnitude of function evaluations can be saved by searching in the found equivalent mapping subspaces instead of exploring the whole search space.

Towards a Non-Destructive Method of Mapping the E-J Relation Using Force Decay Measurements on Superconducting Bulks

In many applications of high-temperature superconductivity, such as superconducting magnetic bearings, precise knowledge of the non-linear voltage-current (E-J) relation is necessary for making accurate quantitative predictions of performance. Magnetic microscopy allows the spatial mapping of coated conductor superconducting properties. There is no equivalent spatial mapping technique for bulk superconductors. A convenient method of mapping the E-J relation for superconductor bulks to be used in superconducting magnetic bearings is desired. The maglev force in a superconducting bearing decays logarithmically over time due to flux creep. The non-linear E-J behaviour describes this flux-creep behaviour and maximum force. It should, therefore, be possible to map the E-J power law of a bulk superconductor using levitation force decay characteristics. Using the H-formulation finite-element method we have simulated the levitation force decay under zero field cooled conditions and identified a relation between the logarithmic force decay parameters and the n-index of the E-J power law. This potentially offers a non-destructive method of determining the E-J relation in large superconducting bulks.

The equivalent method of double V-wing honeycombs on the in-plane dynamic impact

The double V-wing honeycomb can be applied in many fields because of its lower mass and higher performance. In this study, the volume, in-plane elastic modulus and unit cell area of the double V-wing honeycomb were analytically derived, which became parts of the theoretical basis of the novel equivalent method. Based on mass, plateau load, in-plane elastic modulus, compression strain and energy absorption of the double V-wing honeycomb, a novel equivalent method mapping relationship between the thickness–width ratio and the basic parameters was established. The various size factor of the equivalent honeycomb model was denoted as n and constructed by the explicit finite element analysis method. The mechanical properties and energy absorption performance for equivalent honeycombs were investigated and compared with hexagonal honeycombs under dynamic impact. Numerical results showed a well coincidence for each honeycomb under dynamic impact before 0.009 s. Honeycombs with the same thickness–width ratio had similar mechanical properties and energy absorption characteristics. The equivalent method was verified by theoretical analysis, finite element analysis and experimental testing. Equivalent honeycombs exceeded the initial honeycomb in performance efficiency. Improvement of performance and weight loss reached 173.9% and 13.3% to the initial honeycomb. The double V-wing honeycomb possessed stronger impact resistance and better load-bearing capacity than the hexagonal honeycomb under impact in this study. The equivalent method could be applied to select the optimum honeycomb based on requirements and improve the efficiency of the double V-wing honeycomb.

Updating and Validating the U.S. Veterans Affairs Frailty Index: Transitioning From ICD-9 to ICD-10.

The Veterans Affairs Frailty Index (VA-FI) is an electronic frailty index developed to measure frailty using administrative claims and electronic health records data in Veterans. An update to ICD-10 coding is needed to enable contemporary measurement of frailty. International Classification of Diseases, ninth revision (ICD-9) codes from the original VA-FI were mapped to ICD-10 first using the Centers for Medicaid and Medicare Services (CMS) General Equivalence Mappings. The resulting ICD-10 codes were reviewed by 2 geriatricians. Using a national cohort of Veterans aged 65 years and older, the prevalence of deficits contributing to the VA-FI and associations between the VA-FI and mortality over years 2012-2018 were examined. The updated VA-FI-10 includes 6422 codes representing 31 health deficits. Annual cohorts defined on October 1 of each year included 2 266 191 to 2 428 115 Veterans, for which the mean age was 76 years, 97%-98% were male, 78%-79% were White, and the mean VA-FI was 0.20-0.22. The VA-FI-10 deficits showed stability before and after the transition to ICD-10 in 2015, and maintained strong associations with mortality. Patients classified as frail (VA-FI > 0.2) consistently had a hazard of death more than 2 times higher than nonfrail patients (VA-FI ≤ 0.1). Distributions of frailty and associations with mortality varied with and without linkage to CMS data and with different assessment periods for capturing deficits. The updated VA-FI-10 maintains content validity, stability, and predictive validity for mortality in a contemporary cohort of Veterans aged 65 years and older, and may be applied to ICD-9 and ICD-10 claims data to measure frailty.

Quantized Convolutional Neural Network Implementation on a Parallel-Connected Memristor Crossbar Array for Edge AI Platforms.

There are many challenges in the hardware implementation of a neural network using nanoscale memristor crossbar arrays where the use of analog cells is concerned. Multi-state or analog cells introduce more stringent noise margins, which are difficult to adhere to in light of variability. We propose a potential solution using a 1-bit memristor that stores binary values "0" or "1" with their memristive states, denoted as a high-resistance state (HRS) and a low-resistance state (LRS). In addition, we propose a new architecture consisting of 4-parallel 1-bit memristors at each crosspoint on the array. The four 1-bit memristors connected in parallel represent 5 decimal values according to the number of activated memristors. This is then mapped to a synaptic weight, which corresponds to the state of an artificial neuron in a neural network. We implement a convolutional neural network (CNN) model on a framework (tensorflow) using an equivalent quantized weight mapping model that demonstrates learning results almost identical to a high-precision CNN model. This radix-5 CNN is mapped to hardware on the proposed parallel-connected memristor crossbar array. Also, we propose a method for negative weight representation on a memristor crossbar array. Then, we verify the CNN hardware on an edge-AI (e-AI) platform, developed on a field-programmable gate array (FPGA). In this e-AI platform, we represent five weights per crosspoint using CLB logics. We test the learning results of the CNN hardware using an e-AI platform with a dataset consisting of 4×4 images in three classes. We verify the functionality of our radix-5 CNN implementation showing comparable classification accuracy to high-precision use cases, with reduction of the area of the memristor crossbar array by half, all verified on a FPGA. Implementing the CNN model on the FPGA board can contribute to the practical use of edge-AI.

Objective Analysis of SMOS and SMAP Sea Surface Salinity to Reduce Large-Scale and Time-Dependent Biases from Low to High Latitudes

AbstractTen years of L-band radiometric measurements have proven the capability of satellite sea surface salinity (SSS) to resolve large-scale-to-mesoscale SSS features in tropical to subtropical ocean. In mid-to-high latitudes, L-band measurements still suffer from large-scale and time-varying errors. Here, a simple method is proposed to mitigate the large-scale and time-varying errors. First, an optimal interpolation using a large correlation scale (~500 km) is used to map independently Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) level-3 (L3) data. The mapping is compared with the equivalent mapping of in situ observations to estimate the large-scale and seasonal biases. A second mapping is performed on adjusted SSS at the scale of SMOS/SMAP spatial resolution (~45 km). This procedure merges both products and increases the signal-to-noise ratio of the absolute SSS estimates, reducing the root-mean-square difference of in situ satellite products by about 26%–32% from mid- to high latitudes, respectively, in comparison with the existing SMOS and SMAP L3 products. However, in the Arctic Ocean, some issues on satellite retrieved SSS related to, for example, radio frequency interferences, land–sea contamination, and ice–sea contamination remain challenging to reduce given the low sensitivity of L-band radiometric measurements to SSS in cold water. Using the International Thermodynamic Equation Of Seawater—2010 (TEOS-10), the resulting level-4 SSS satellite product is combined with satellite-microwave SST products to estimate sea surface density, spiciness, and haline contraction and thermal expansion coefficients. For the first time, we illustrate how useful these satellite-derived parameters are to fully characterize the surface ocean water masses at large mesoscale.

Design and optimization of a CMOS IC novel RF tracking sensor

SummaryThis research reports the development of an RF sensor integrated circuit (IC) chip capable of tracking the directionality of RF remote emissions. The IC design uses an angle‐of‐arrival algorithm, and it is designed for the 180 nm CMOS technology and applicable to other technologies, also. The sensor chip requires two pairs of antennas aligned and placed at distance s for detection of azimuthal and polar angles of the RF incident wave. The circuit consists of custom designed low‐noise amplifiers (LNAs) at the front end, with a novel design of double‐balanced Gilbert cell mixers (GCMs). This amplifies and mixes the signals from the antennas and converts the phase difference Δφ into an equivalent output voltage map suitable for an 18‐bit analog to digital converter. Systematic optimization techniques were developed to maximize the third‐order intercept point and suppress flicker noise for the LNAs and GCMs, resulting in improved sensing accuracy. The overall system‐level evaluation results showed state‐of‐art angle‐of‐arrival sensing capability with an upper limit error of 3.447°.

Impact of ICD-9-CM to ICD-10-CM coding transition on trauma hospitalization trends among young adults in 12 states

BackgroundWe aimed to estimate the impact of the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) coding transition on traumatic injury-related hospitalization trends among young adults across a geographically and demographically diverse group of U.S. states.MethodsInterrupted time series analyses were conducted using statewide inpatient databases from 12 states and including traumatic injury-related hospitalizations in adults aged 19–44 years in 2011–2017. Segmented regression models were used to estimate the impact of the October 2015 coding transition on external cause of injury (ECOI) completeness (percentage of hospitalizations with a documented ECOI code) and on population-level rates of injury-related hospitalizations by nature, intent, mechanism, and severity of injury.ResultsThe transition to ICD-10-CM was associated with a drop in ECOI completion in the transition month (− 3.7%; P < .0001), but there was no significant change in the positive trend in ECOI completion from the pre- to post-transition periods. There were significant increases post-transition in the measured rates of hospitalization for traumatic brain injury (TBI), unintentional injury, mild injury (injury severity score (ISS) < 9), and injuries caused by drowning, firearms, machinery, other pedestrian, suffocation, and unspecified mechanism. Conversely, there were significant decreases in October 2015 in the rates of hospitalization for assault, injuries of undetermined intent, injuries of moderate severity (ISS 9–15), and injuries caused by fire/burn, other pedal cyclist, other transportation, natural/environmental, and other specified mechanism. A significant increase in the percentage of hospitalizations classified as resulting from severe injury (ISS > 15) was observed when the general equivalence mapping maximum severity method for converting ICD-10-CM codes to ICD-9-CM codes was used. State-specific results for the outcomes of ECOI completion and TBI-related hospitalization rates are provided in an online supplement.ConclusionsThe U.S. transition from ICD-9-CM to ICD-10-CM coding led to a significant decrease in ECOI completion and several significant changes in measured rates of injury-related hospitalizations by injury intent, mechanism, nature, and severity. The results of this study can inform the design and analysis of future traumatic injury-related health services research studies that use both ICD-9-CM and ICD-10-CM coded data.Level of evidenceII (Interrupted Time Series)

Analytical Modeling of Variable-Reluctance Tubular Resolver Based on Magnetic Equivalent Circuit and Conformal Mapping

Compared with flat linear structures, tubular linear machines do not face edge effects, making their performance better than their flat counterparts. In this article, a novel linear variable-reluctance resolver with tubular configuration is proposed. To optimize the design of an electromagnetic structure, modeling methods are used. Thus, in this article, an analytical model for the proposed resolver is presented. This model is based on the magnetic equivalent circuit (MEC) method and is considerably less time-consuming than finite element analysis (FEA), yet provides accurate results. A conformal mapping is employed to compute the permeance of the air-gap. The proposed model is then utilized to compensate the resolver’s performance for the longitudinal end-effects. The results of the MEC model are compared with those of FEA, and good agreement is seen. Finally, the compensated sensor is experimentally built and tested, and the simulation results are verified.

Research on Vibration Reduction Characteristics of Continuum and Noncontinuum System on Coupling for High‐Power Gear Transmission Based on Particle Damping Materials

High‐power gears are widely used in various engineering fields. The gear transmission system is an extremely complex elastic system, which produces complex vibration under internal and external excitation. For the vibration and noise problems caused by transmission error, a discrete element and finite coupling method based on the particle filling rate is proposed. Firstly, the gear dynamic model was established, and the particle damper was installed in the gear to reduce the vibration of the gear. Secondly, through the coupling process, the contact force and contact position between the noncontinuous medium and the continuous medium were correctly transferred to the corresponding nodes of the finite element analysis model. Then, the equivalent displacement mapping of the contact loads’ node of the gear was realized, and the transformation of the local coordinate to the global coordinate was carried out. Finally, by combining theoretical analysis with experimental verification, the influence of the filling rate of damping particles on the vibration reduction effect of the gearbox under different working conditions was studied. The 2 mm tungsten particles were selected, and the particle damper had the best damping effect when the filling rate was 88%.

MIMO Modeling by Learning Explicitly the Projection Space: The Maximum Correlation Ratio Cost Function

Maximal correlation measures the statistical dependence between two random variables and has been broadly used by statisticians. In this paper, we present a novel regression framework based on a special case of the maximal correlation using the correlation ratio to train a Multiple-input Multiple-output (MIMO) model called the Bank of Wiener Models (BWM). Nonlinear time series modeling under maximal correlation unifies the cost and the mapping function under the same mathematical optimization framework. This provides direct optimality (maximal statistical dependence) between BWM model outputs and the desired response, without the restriction of constructing an error signal as conventionally done in regression. Based on the idea of correlation ratio, we propose the Maximal Correlation Algorithm (MCA), which approximates directly the correlation ratio between BWM outputs and the desired response. As an important consequence, MCA modularizes the training of models with hidden layers and avoids the end-to-end training of backpropagation (BP), while improving the equivalent mapping capability. We further propose several possible multi layer arrangements to create deep networks trained with MCA. We demonstrate experimentally that MCA performs at the same level of output error or better when compared to a single and multiple-hidden-layer MLP trained with BP and the Mean Squared Error (MSE). We also show that the system identification capabilities of MCA are superior to MLPs trained with BP. Hence, MCA has great promise in both nonlinear system identification and machine learning.

Measuring complications of serious pediatric emergencies using ICD-10.

To create definitions for complications for 16 serious pediatric conditions using the International Classification of Diseases, 10th Revision, Clinical Modification or Procedure Coding System (ICD-10-CM/PCS), and to assess whether complication rates are similar to those measured with ICD-9-CM/PCS. The Healthcare Cost and Utilization Project State Emergency Department and Inpatient Databases from five states between 2014 and 2017 were used to identify cases and assess complication rates. Incidences were calculated using population counts from the 5-year American Community Survey. Patients were identified by the presence of a diagnosis code for one of the 16 serious conditions. Only the first encounter for a given condition by a patient was included. Encounters resulting in transfer were excluded as the presence of complications was unknown. We defined complications using data elements routinely available in administrative databases including ICD-10-CM/PCS codes. The definitions were adapted from ICD-9-CM/PCS using general equivalence mappings and refined using consensus opinion. We included 16 serious conditions: appendicitis, bacterial meningitis, compartment syndrome, new-onset diabetic ketoacidosis (DKA), ectopic pregnancy, empyema, encephalitis, intussusception, mastoiditis, myocarditis, orbital cellulitis, ovarian torsion, sepsis, septic arthritis, stroke, and testicular torsion. Using data from children under 18years, we compared incidences and complication rates across the ICD-10-CM/PCS transition for each condition using interrupted time series. There were 61314 ED visits for a serious condition; the most common was appendicitis (n=37493). Incidence rates for each condition were not significantly different across the ICD-10-CM/PCS transition for 13/16 conditions. Three differed: empyema (increased 42%), orbital cellulitis (increased 60%), and sepsis (increased 26%). Complication rates were not significantly different for each condition across the ICD-10-CM/PCS transition, except appendicitis (odds ratio 0.62, 95% CI 0.57-0.68), DKA (OR 3.79, 95% CI 1.92-7.50), and orbital cellulitis (OR 0.53, 95% CI 0.30-0.95). For most conditions, incidences and complication rates were similar before and after the transition to ICD-10-CM/PCS codes, suggesting our system identifies complications of conditions in administrative data similarly using ICD-9-CM/PCS and ICD-10-CM/PCS codes. This system may be applied to screen for cases with complications and in health services research.

Noise prediction based on acoustic maps and vehicle fleet composition

Developing countries are experiencing rapid urbanization that directly and negatively affects their acoustic environments due, in large part, to increased road traffic. Several studies have shown that noise is a public health problem that should be mitigated, given that the tardy implementation of control measures may render them ineffective. Noise mitigation projects often overlook long-term aspects, which reflects the transient morphology of urban centers, although this point is addressed in Directive 2002/49/EC. A methodology is proposed here to assess noise pollution in a subregion of Brazil, the city of Goiânia, which has a population of approximately 1.3 million, based on in situ measurements of equivalent sound pressure levels (Leq) and noise mapping. In addition, we sought to determine at what future time the Leq would be above 60 dB(A) at all the evaluated points. The aim is to evaluate the effect of increasing noise levels and their impact on the population as a function of road traffic growth rates. In 2016, the Leq was measured at 67 points distributed throughout the metropolis, and a count was made of the flow rate of light vehicles, heavy vehicles and motorcycles, and their stratified percentage. Spatiotemporal modeling was performed using Predictor® software to forecast the Leq in the years 2021, 2026 and 2036. The results indicated that the Leq in more than 90% of the region under study was higher than that specified by the Brazilian noise assessment standard NBR 10151:2019 and by the World Health Organization. Noise maps for the years 2021, 2026 and 2036 showed an average increase in noise levels of 0.28 dB(A)/year between 2016 and 2036. Moreover, after 2036, the Leq at 100% of the points assessed is expected to exceed 60 dB(A), which is the maximum allowed by current noise regulations.

Infodemic amid the COVID-19 pandemic

The unfortunate arrival of the COVID-19 pandemic has also brought along with it a tsunami of information that can be both authentic and important as well as non-reliable and misguiding. The World Health Organization (WHO) coins this outburst of information in this era of pandemic as an infodemic. It becomes essential for societies to consume and act on trusted information in these times of uncertainty and grief. In this article, we describe and assess the role of blockchain technology and its features to establish an environment of a trusted information ecosystem. We present an equivalence mapping of these important parameters to curb an infodemic with blockchain technology features and applications. This equivalence mapping provides a directional sense to stakeholders, decision-makers, policy-makers and investors to gauge and synthesize the potential of blockchain technology for tackling an infodemic.