Advancements in Nanomedicine for Allergic Diseases: Diagnosis, Toxicity, and Therapeutic Strategies.

BackgroundTo describe quantitative data quality monitoring and performance metrics adopted by the Global Network’s (GN) Maternal Newborn Health Registry (MNHR), a maternal and perinatal population-based registry (MPPBR) based in low and middle income countries (LMICs).MethodsOngoing prospective, population-based data on all pregnancy outcomes within defined geographical locations participating in the GN have been collected since 2008. Data quality metrics were defined and are implemented at the cluster, site and the central level to ensure data quality. Quantitative performance metrics are described for data collected between 2010 and 2013.ResultsDelivery outcome rates over 95% illustrate that all sites are successful in following patients from pregnancy through delivery. Examples of specific performance metric reports illustrate how both the metrics and reporting process are used to identify cluster-level and site-level quality issues and illustrate how those metrics track over time. Other summary reports (e.g. the increasing proportion of measured birth weight compared to estimated and missing birth weight) illustrate how a site has improved quality over time.ConclusionHigh quality MPPBRs such as the MNHR provide key information on pregnancy outcomes to local and international health officials where civil registration systems are lacking. The MNHR has measures in place to monitor data collection procedures and improve the quality of data collected. Sites have increasingly achieved acceptable values of performance metrics over time, indicating improvements in data quality, but the quality control program must continue to evolve to optimize the use of the MNHR to assess the impact of community interventions in research protocols in pregnancy and perinatal health.Trial registration numberNCT01073475

Quantitative team performance metrics for dismounted infantry battle drill analysis.

ESD is an endoscopic technique for en bloc resection of gastrointestinal lesions. ESD is a widely-used in Japan and throughout Asia, but not as prevalent in Europe or the US. The procedure is technically challenging and has higher adverse events (bleeding, perforation) compared to endoscopic mucosal resection. Inadequate training platforms and lack of established training curricula have restricted its wide acceptance in the US. Thus, we aim to develop a Virtual Endoluminal Surgery Simulator (VESS) for objective ESD training and assessment. In this work, we performed task and performance analysis of ESD surgeries. We performed a detailed colorectal ESD task analysis and identified the critical ESD steps for lesion identification, marking, injection, circumferential cutting, dissection, intraprocedural complication management, and post-procedure examination. We constructed a hierarchical task tree that elaborates the order of tasks in these steps. Furthermore, we developed quantitative ESD performance metrics. We measured task times and scores of 16 ESD surgeries performed by four different endoscopic surgeons. The average time of the marking, injection, and circumferential cutting phases are 203.4 (σ: 205.46), 83.5 (σ: 49.92), 908.4s. (σ: 584.53), respectively. Cutting the submucosal layer takes most of the time of overall ESD procedure time with an average of 1394.7s (σ: 908.43). We also performed correlation analysis (Pearson's test) among the performance scores of the tasks. There is a moderate positive correlation (R = 0.528, p = 0.0355) between marking scores and total scores, a strong positive correlation (R = 0.7879, p = 0.0003) between circumferential cutting and submucosal dissection and total scores. Similarly, we noted a strong positive correlation (R = 0.7095, p = 0.0021) between circumferential cutting and submucosal dissection and marking scores. We elaborated ESD tasks and developed quantitative performance metrics used in analysis of actual surgery performance. These ESD metrics will be used in future validation studies of our VESS simulator.

Security Operation Center represents nowadays an indispensable component of the socio-technical system by supporting businesses to protect their security and ensure the confidentiality, integrity, and availability against cyberthreats and security attacks.The Security Operation Center provides various service levels and capabilities that need to be continuously assessed and tracked to ensure improvement of the main success factor of the SOC, which include technologies, processes, and SOC analysts. SOC analysts’ performance evaluation remains problematic due to the choice of the performance metrics and their inadequacy with the SOC socio-technical system. While we have some quantitative and qualitative measures to assess the performance of a SOC analyst, SOC capabilities, and SOC maturity levels, this evaluation is based on root cause analysis and independent evaluation of SOC elements, which is unrealistic, given the complex and evolving nature of SOC systems. However, the baselines of the performance metrics are the SOC challenges announced by the SOC analysts and their ability to face, reduce, and overcome them to provide and maintain a high detection rate of malicious and abnormal behaviors. We provide a comprehensive overview of the challenges faced by SOC analysts based on our previous study, and we provide a deep analysis of the challenges and the interconnexion of those challenges. Furthermore, we present the quantitative performance metrics and their weaknesses to assess the performance of the SOC analysts due to the SOC socio-technical system nature. Our study will enable SOC managers, analysts, and decision-makers to have clear visibility and details on the quantitative performance metrics and will provide a baseline for a new performance metrics model.

A novel white balancing algorithm is proposed in this paper to automatically enhance the global contrast degraded imperceptible images. The technique is applied on four publicly available image dataset, CSIQ, KADID, TID and SIPI. Colour images consist of three channels viz. Red, Blue and Green. A contrast degraded colour image visually appears similar to an image with one or more distorted channel. 12 images are obtained by enhancing one channel of the contrast degraded image at the cost of other channel using White Balancing algorithm. Four images with best quantitative performance metrics, visual similarity index (VSI), gradient magnitude similarity index (GMSD), patch-based contrast quality index (PCQI) and peak signal-to-noise ratio (PSNR) determines the pair of weak and prominent channels. An optimization algorithm then enhances these channels and the image with the best quantitative performance metrics is chosen as the enhanced image. Quantitative and qualitative results demonstrate that the proposed method produces an enhanced image with superior perceptual quality, and gives the best average results for all the parameters across every dataset as compared to the state-of-the-art methods.

A long-term gridded historical data at 3 km spatial resolution has been generated for practical regional applications such as hydrologic modelling. However, overly high or low values have been found at some grid points where complex topography or sparse observational network exist. In this study, the Inverse Distance Weighting (IDW) method was applied to properly smooth the overly predicted values of Improved GIS-based Regression Model (IGISRM), called the IDW-IGISRM grid data, at the same resolution for daily precipitation, maximum temperature and minimum temperature from 2001 to 2010 over South Korea. We tested various effective distances in the IDW method to detect an optimal distance that provides the highest performance. IDW-IGISRM was compared with IGISRM to evaluate the effectiveness of IDW-IGISRM with regard to spatial patterns, and quantitative performance metrics over 243 AWS observational points and four selected stations showing the largest biases. Regarding the spatial pattern, IDW-IGISRM reduced irrational overly predicted values, i. e. producing smoother spatial maps that IGISRM for all variables. In addition, all quantitative performance metrics were improved by IDW-IGISRM; correlation coefficient (CC), Index Of Agreement (IOA) increase up to 11.2% and 2.0%, respectively. Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were also reduced up to 5.4% and 15.2% respectively. At the selected four stations, this study demonstrated that the improvement was more considerable. These results indicate that IDW-IGISRM can improve the predictive performance of IGISRM, consequently providing more reliable high-resolution gridded data for assessment, adaptation, and vulnerability studies of climate change impacts.

Eosinophilic organ infiltration without eosinophilia or direct parasite infection

Advanced statistical machine learning (ML) algorithms are being developed, trained, tuned, optimized, and validated for real-time prognostics for internet-of-things (IoT) applications in the fields of manufacturing, transportation, and utilities. For such applications, we have achieved greatest prognostic success with ML algorithms from a class of pattern recognition known as nonlinear, nonparametric regression. To intercompare candidate ML algorithmics to identify the best algorithms for IoT prognostic applications, we use three quantitative performance metrics: false alarm probability (FAP), missed alarm probability (MAP), and overhead compute cost (CC) for real-time surveillance. This paper presents a comprehensive framework, SimML, for systematic parametric evaluation of statistical ML algorithmics for IoT prognostic applications. SimML evaluates quantitative FAP, MAP, and CC performance as a parametric function of input signals' degree of cross-correlation, signal-to-noise ratio, number of input signals, sampling rates for the input signals, and number of training vectors selected for training. Output from SimML is provided in the form of 3D response surfaces for the performance metrics that are essential for comparing candidate ML algorithms in precise, quantitative terms.

Interoperability in modeling and simulation is understood as the ability of simulations to exchange information and use the information exchanged. Several alternative models have been applied to support interoperability. The traditional approach has been to apply standards, such as the High-level Architecture, to create a federation and use a runtime infrastructure to physically connect simulations. Recently, there has been a move towards web-based standards to loosely couple simulations, and the future points to cloud-enabled interoperability services. Despite the existence of implementations of these models from industry, academia and government, very few performance metrics have been formulated to evaluate them. In this paper, we propose quantitative performance metrics that includes a set of dependent and independent variables for implementations of interoperability models. We apply the metrics to a web-based infrastructure that uses web standards and a traditional runtime infrastructure. We analyze the results and discuss the tradeoffs that federation developers have to consider when selecting an implementation of an interoperability model.

This research examines the relationship between prerequisite algebra knowledge and graduate corporate finance course performance. Standardized math questions designed for an undergraduate introductory finance course also predict quantitative performance metrics among 128 business graduate students. Results demonstrate that prerequisite math skills, while to a lesser extent than with undergraduate finance courses, do remain an obstacle for the quantitative performance metrics of a graduate corporate finance course. However, math skills demonstrate an inverse relationship with team-based case study performance, thereby obscuring the overall impact of any math skills deficiencies. This research presents a three-question course-embedded assessment tool to support finance course assurance of learning in an AACSB context.

BackgroundParkinson’s Disease (PD) is a highly prevalent neurodegenerative disease whose incidence is increasing with an aging population. One of the most serious manifestations of PD is gait instability, leading to falls and subsequent complications that can be debilitating, even fatal. Boxing therapy (BT) uses gait and balance exercises to improve ambulation in people with PD, though its efficacy has not yet been fully proven.MethodsIn the current longitudinal observational study, 98 participants with idiopathic PD underwent twice-weekly BT sessions. Primary outcome was self-reported falls per month; secondary outcomes were quantitative and semi-quantitative gait and balance performance evaluations. Statistical methods included segmented generalized estimating equation with an independent correlation structure, binomial distribution, and log link.ResultsThe average number of self-reported falls per month per participant decreased by 87%, from 0.86 ± 3.58 prior to BT, to 0.11 ± 0.26 during BT. During the lockdown imposed by COVID-19, this increased to 0.26 ± 0.48 falls per month. Females and those > 65 years old reported the greatest increase in falls during the lockdown period. Post-lockdown resumption of BT resulted in another decline in falls, to 0.14 ± 0.33. Quantitative performance metrics, including standing from a seated position and standing on one leg, largely mirrored the pattern of falls pre-and post-lockdown.ConclusionsBT may be an effective option for many PD patients.

Background:Parkinson’s Disease (PD) is a highly prevalent neurodegenerative disease whose incidence is increasing with an aging population. One of the most serious manifestations of PD is gait instability, leading to falls and subsequent complications that can be debilitating, even fatal. Boxing therapy (BT) uses gait and balance exercises to improve ambulation in people with PD, though its efficacy has not yet been fully proven.Methods:In the current longitudinal observational study, 98 participants with idiopathic PD underwent twice-weekly BT sessions. Primary outcome was self-reported falls per month; secondary outcomes were quantitative and semi-quantitative gait and balance performance evaluations. Statistical methods included segmented generalized estimating equation with an independent correlation structure, binomial distribution, and log link.Results:The average number of self-reported falls per month per participant decreased by 87%, from 0.86 ± 3.58 prior to BT, to 0.11 ± 0.26 during BT. During the lockdown imposed by COVID-19, this increased to 0.26 ± 0.48 falls per month. Females and those > 65 years old reported the greatest increase in falls during the lockdown period. Post-lockdown resumption of BT resulted in another decline in falls, to 0.14 ± 0.33. Quantitative performance metrics, including standing from a seated position and standing on one leg, largely mirrored the pattern of falls pre- and post-lockdown.Conclusions:BT may be an effective option for many PD patients.

First posted January 7, 2016 For additional information, contact: Director, Patuxent Wildlife Research Center12100 Beech Forest Rd., Ste 4039Laurel, MD 20708-4039http://www.pwrc.usgs.gov/ The U.S. Geological Survey, in cooperation with the Bureau of Reclamation, National Park Service, and Argonne National Laboratory, completed a decision analysis to use in the evaluation of alternatives in the Environmental Impact Statement concerning the long-term management of water releases from Glen Canyon Dam and associated management activities. Two primary decision analysis methods, multicriteria decision analysis and the expected value of information, were used to evaluate the alternative strategies against the resource goals and to evaluate the influence of uncertainty. A total of 18 performance metrics associated with 8 out of 12 resource goals (fundamental objectives) were developed by the Bureau of Reclamation and National Park Service in partnership with subject-matter teams composed of Federal, State, tribal, and private experts. A total of 19 long-term strategies associated with 7 alternatives were developed by the Bureau of Reclamation, National Park Service, Argonne National Laboratory, U.S. Geological Survey, and Cooperating Agencies. The 19 long-term strategies were evaluated against the 18 performance metrics using a series of coupled simulation models, taking into account the effects of several important sources of uncertainty. A total of 27 Federal, State, tribal, and nongovernmental agencies were invited by the Assistant Secretary of Interior to participate in a swing-weighting exercise to understand the range of perspectives about how to place relative value on the resource goals and performance metrics; 14 of the 27 chose to participate. The results of the swing-weighting exercise were combined with the evaluation of the alternatives to complete a multicriteria decision analysis. The effects of uncertainty on the ranking of long-term strategies were evaluated through calculation of the value of information. The alternatives and their long-term strategies differed across performance metrics, producing unavoidable tradeoffs; thus, there was no long-term strategy that was dominated by another across all performance metrics. When the performance of each alternative was weighted across performance metrics, three alternatives (B, D, and G) were top-ranked depending on the set of weights proposed: Alternative B was favored by those stakeholders that placed a high value on hydropower; Alternative G was favored by those stakeholders that placed a high value on the restoration of natural processes, like beachbuilding and natural vegetation; and Alternative D was favored by the remaining stakeholders. Surprisingly, these rankings were not sensitive to the critical uncertainties that were evaluated; that is, the choice of a preferred long-term strategy was sensitive to the value-based judgment about how to place relative weight on the resource goals but was not sensitive to the uncertainties in the system dynamics that were evaluated in this analysis. The one area of uncertainty that did slightly affect the ranking of alternatives was the long-term pattern of hydrological input; because of this sensitivity, some attention to the possible effects of climate change is warranted. The results of the decision analysis are meant to serve as only one of many sources of information that can be used to evaluate the alternatives proposed in the Environmental Impact Statement. These results only focus on those resource goals for which quantitative performance metrics could be formulated and evaluated; there are other important aspects of the resource goals that also need to be considered. Not all the stakeholders who were invited to participate in the decision analysis chose to do so; thus, the Bureau of Reclamation, National Park Service, and U.S. Department of Interior may want to consider other input.

Stroke, affecting approximately 15 million people worldwide, has long been a global cause of death and disability. Virtual Reality (VR) has shown its potential as an assistive tool for post-stroke rehabilitation. The objective of this pilot study was to define the task-specific performance metrics of VR tasks to assess the performance level of healthy subjects and patients quantitatively and to obtain their feedback for improving the developed framework. A pilot prospective study was designed. We tested the designed VR tasks on forty healthy right-handed subjects to evaluate its potential. Qualitative trajectory plots and three quantitative performance metrics—time taken to complete the task, percentage relative error, and trajectory smoothness—were computed from the recorded data of forty healthy subjects. Two patients with stroke were also enrolled to compare their performance with healthy subjects. Each participant received one VR session of 90 min. No adverse effects were noticed throughout the study. Performance metrics obtained from healthy subjects were used as a reference for patients. Relatively higher values of task completion time and trajectory smoothness and lower values of relative % error was observed for the affected hands w.r.t the unaffected hands of both the patients. For the unaffected hands of both the patients, the performance levels were found objectively closer to that of healthy subjects. A library of VR tasks for wrist and fingers were designed, and task-specific performance metrics were defined in this study. The evaluation of the VR exercises using these performance metrics will help the clinicians to assess the patient’s progress quantitatively and to design the rehabilitation framework for a future clinical study.

The objectives of this study were: 1) to develop and implement a set of automated performance metrics into the Western myringotomy simulator, and 2) to establish construct validity. Prospective simulator-based assessment study. The Auditory Biophysics Laboratory at Western University, London, Ontario, Canada. Eleven participants were recruited from the Department of Otolaryngology-Head & Neck Surgery at Western University: four senior otolaryngology consultants and seven junior otolaryngology residents. Educational simulation. Discrimination between expert and novice participants on five primary automated performance metrics: 1) time to completion, 2) surgical errors, 3) incision angle, 4) incision length, and 5) the magnification of the microscope. Automated performance metrics were developed, programmed, and implemented into the simulator. Participants were given a standardized simulator orientation and instructions on myringotomy and tube placement. Each participant then performed 10 procedures and automated metrics were collected. The metrics were analyzed using the Mann-Whitney U test with Bonferroni correction. All metrics discriminated senior otolaryngologists from junior residents with a significance of p < 0.002. Junior residents had 2.8 times more errors compared with the senior otolaryngologists. Senior otolaryngologists took significantly less time to completion compared with junior residents. The senior group also had significantly longer incision lengths, more accurate incision angles, and lower magnification keeping both the umbo and annulus in view. Automated quantitative performance metrics were successfully developed and implemented, and construct validity was established by discriminating between expert and novice participants.