Scale Selection Research Articles

THE USE OF PATIENT REPORTED OUTCOME MEASURES BY PRIMARY MEDICAL PROVIDERS IN THE PEDIATRIC SPORTS POPULATION

Background: Patient reported outcome measures (PROs) allow medical providers to assess functional limitations, track progress, and evaluate outcomes. Although progress has been made developing and validating PROs, much of this work has been done within the adult population, and only a limited number of pediatric specific PROs exist. The use of PROs within pediatric orthopedics remains unstudied. The purposes of this study are to evaluate the current use of PROs within pediatric sports medicine and determine how the information from PROs is used for treatment decisions. Methods: An online email survey was sent to members of the Pediatric Research in Sports Medicine Society (PRiSM) using REDCap™. The survey was developed and pilot tested by 4 physical therapists and 3 orthopedic surgeons. The final survey consisted of 24 multiple choice questions, designed to garner information relative to provider use of PROs. Some questions allowed free text for answers not previously-defined. The survey took 3-5 minutes to complete and was open for an 8 week period. Although PRiSM is a multi-disciplinary society, only data from primary medical providers (PMPs -orthopedic surgeons, sports medicine primary care physicians, nurse practitioners, physician assistants) was utilized. Descriptive statistics and frequency tallies were used to analyze the data. Results: Seventy-two surveys were used for analysis; a response rate of 45% given total membership. The sample distribution can be seen in Table 1. The use of PROs was reported by 57% (n=41) of PMPs. PROs administration occurred at post-operative encounters (83%, n=34), new patient visits (73%, n=30), pre-op visits 44% (n=18), when there is a change in status/new injury 27% (n=11), and every visit 12% (n=5). The majority of information from PROs was used for research (85%, n=35), assess response to treatment (51%), inform clinical prognosis (37%) and guide clinical decisions (32%). There were no PMPs that reported distributing PROs to satisfy insurance requirements. PRO use was reported at the highest frequency for knee (98%, n=40) and shoulder (68%, n=28) injuries. There was variability in specific PRO selection with 80%, 56% and 34% using the Pedi-IKDC, IKDC, and KOOS, respectively. For the shoulder, the DASH and QuickDASH garnered the highest use (32% each) however variability in scale selection persisted with 24% using “other” scales, including activity and fear avoidance scales. PRO use for the hip (41%), ankle (39%), back (20%) and neck (17%) were reported less frequently. (Figure 3 details scale specifics). Nearly half the sample (46%) reported using affective domain or quality of life scales like the Pedi-Fabs (24%) and ACL-RSI (17%) and PROMIS (12%). Interestingly, 43% (n=31/41) of the sample indicated they do not use PROs, with 39% of these respondents citing inadequate time as the primary barrier to use, 23% were unsure of which measure to use and 16% did not find them useful or relevant. Additional barriers are presented in Figure 4. Conclusions: Only 57% of PMPs are using PROs within their practice. The information from PROs is largely used to perform research and demonstrate the effectiveness of treatment. Interestingly, no one used PROs to satisfy insurance requirements. Within all body regions, there is little consistency in scale selection. A large number of respondents indicated that PROs for hip, ankle and spine were “not applicable” to their practice, making generalization of this data difficult. Although it cannot be determined why there was such a low percentage of PRO use for these body regions, the authors feel this may be related to a small volume of patients seen with diagnoses of these regions among our sample or perceptions that no existing scale is useful for this population. It was surprising that over 40% of the sample did not use PROs in their practice. Among those respondents, inadequate time for administration and indecision regarding which measure to use, were indicated as the greatest barriers to use. Clinical Relevance: Healthcare policy within the United States is undergoing a transformation towards a value-based system, under which PROs will be heavily relied upon to demonstrate effectiveness of treatment and help determine reimbursement; this transition has already occurred in adults/the Medicare system. Our results show that although 85% of PMPs use PROs for research purposes, the use of PROs in the clinical setting is low. Given the changing payment model and increased emphasis on patient-centered care, our results highlight the importance of integrating PROs into clinical practice and support the need for ongoing research related to the validation research and scale development as many of the scales have not been evaluated in pediatrics. Tables and Figures: [Table: see text][Figure: see text][Figure: see text][Figure: see text]

THE USE OF PATIENT REPORTED OUTCOME MEASURES BY PHYSICAL THERAPISTS IN THE PEDIATRIC SPORTS POPULATION

Purpose: Patient reported outcome measures (PROs) allow physical therapists (PTs) the ability to objectively understand a patients’ perception of their symptoms, functional status, and health related quality of life. Although professional organizations have issued recommendations for PRO use, many of these measures were developed and validated within the adult population which may limit their application to pediatric orthopedics. It is currently unknown which measures are being used within this population, and thus the purpose of this study is to evaluate the current use of PROs among pediatric sports PT and determine how PRO information is used in clinical care. Methods: An online survey, developed in REDCap™, was administered via email to members of the Sports Section Youth Athlete Special Interest Group (YASIG) and the Pediatric Research in Sports Medicine Society (PRiSM), over the course of 8 weeks. The survey was developed and pilot tested by 4 physical therapists and 3 orthopedic surgeons and consisted of 24 possible questions, taking 3-5 minutes to complete. Descriptive statistics and frequency tallies were utilized to analyze the data. Results: There was a total of 70 respondents (response rate YASIG 17%; response rate PRiSM 90%) who completed the questionnaire in its entirety. There was a wide range of clinical experience with 31% reporting 0-5 years, 23%, 6-10 years, 16%, 11-15 years, and 30% >16 years. The majority (54%) reported working in a hospital based outpatient setting or private practice (24%). Ninety four percent (n=66) of respondents reported using PROs, with 100% (n=66) of these subjects issuing them at the initial visit, 94% (n=62) at discharge, and 91% (n=60) monthly. The Neck Disability Index (76%, n=50), Oswestry (76%, n=50), and QuickDASH (68%, n=45) were most frequently used for neck, back and shoulder disorders, respectively. The Lower Extremity Functional Scale (LEFS) was the most widely utilized measure for multiple body regions including 74% (n=49) for either hip or knee dysfunction, and 26% (n=16) for ankle. In general, knee disorders demonstrated the highest degree of variability in scale selection with 52% (n=34) using the IKDC, 35% (n=23) using the Pedi-IKDC and 20% (n=13) (using the KOOS). The information obtained from PROs was used to demonstrate effectiveness of treatment (80%, n=53), inform clinical decisions (77%, n=51), satisfy insurance requirements (59%, n=39), used for goal writing (60%, n=40), and research (36%, n=24). Only 6% (n=4) of PTs indicated that PROs did not impact clinical reasoning within their plan of care. When asked how the information from PROs is used within clinical practice, it was noted that 71% (n=47) of PTs would ‘revise physical therapy goals’ if scores were either higher or lower than expected and 38% (n=25) would ‘refer patient back to the physician’ if PRO results showed lack of progress or regression. In addition, 20% (n=13) of PTs noted they utilize the results from PROs to help inform discharge decision making. When asked regarding barriers to using PROs, PTs reported inadequate time (42%, n=28), difficultly remembering to administer (38%, n=25) and uncertainty regarding which PRO to use (21%, n=14) as the main impediments in using PROs. Conclusions: Our results indicate that the majority of pediatric sports PTs are using PROs to establish efficacy of treatment, inform clinical decision making and set goals. Inadequate time and indecision with regards to which scale to use, were identified as barriers to use. Knee disorders demonstrated the largest variability in scale use. Interestingly, the LEFS was reported at high frequencies for the hip, knee and ankle joints despite the availability of other joint specific measures available. The Oswestry and NDI are also used by 76% of respondents despite neither tool being validated in pediatrics. This finding may be due to the absence of any pediatric specific alternative measures. Clinical Relevance: The Center for Medicare and Medicaid implemented value based purchasing program per the mandate of the Affordable Care Act. The Act established a performance based approach to payment with a goal of ensuring better clinical outcomes and improved patient experience. As a result, there is an increased emphasis on using PROs to demonstrate efficacy and functional improvement. It is reassuring that many PTs are using PROs and using the obtained data to drive clinical care. However, the high variability in scale choice makes comparative outcomes research difficult. In addition, the majority of the PROs used are not validated within the pediatric population and thus may not be appropriate tools for assessing these patients perception of care delivered or even represent their functional/athletic limitations. Given the high prevalence of use and importance to clinical practice, the need for psychometric testing and/or scale development specifically for pediatric sports population is imperative.

Wavelet-based optical velocimetry for oil spill flow rate estimation

Flow rate estimation of an underwater oil spill is challenging due to the complex flow dynamics of an oil spill. Existing techniques such as particle image velocimetry (PIV) and feature tracking velocimetry (FTV) were unable to accurately estimate the flow rate of the oil spill in the Macondo well incident, with the most accurate technique being optical plume velocimetry (OPV). OPV estimates the velocity field based on temporal averaging algorithm, which has a better temporal resolution compared to PIV and FTV. This is useful for flow estimation where the temporal evolution of turbulent flow is significant. However, the classical temporal cross correlation algorithm used in OPV is not appropriate to deal with multi-scale flow behaviour associated with a turbulent flow such as that of oil spills. Several methods were previously used to multi-scale representation, such as Short-Time Fourier Transform, Wavelet Transform (WT) and Empirical Mode Decomposition. Among all of these methods, wavelet transform (WT) is more appropriate for turbulent flow applications, since the interesting point is the presentation of flow spectral changes over time. This is because the wavelet convolution has the ability to balance between temporal and frequency information. This paper proposed an alternative technique called wavelet-based optical velocimetry (WOV). WOV estimates the velocity field based on cross correlation of wavelet coefficients. Continuous wavelet transform was first utilized to transform two intensity signals into the wavelet domain. The Fast Fourier Transform (FFT) algorithm was then used for wavelet coefficient correlation, from which the velocity was estimated. To validate the accuracy of the WOV technique, a turbulent jet flow was experimentally simulated at Reynold's number ranging from 1847 to 11,656 at the nozzle. In our experimental work, WOV estimated the nozzle flow rate with an error of 8.3%, while the OPV estimated the nozzle flow rate with an error of 19.7%. The better estimation of WOV technique is due to its advantage to deal with the multi-scale behaviour of turbulent flow, since the WT has a multi-resolution scheme. The accuracy of WOV algorithm, however is sensitive to the selection of wavelet scaling, as well as the wavelet function. A significant influence was observed for the wavelet scaling, due to the difference of the frequency bandwidth width of WT, while the influence of wavelet function is less significant.

Selection and evaluation of optimal segmentation scale for high-resolution remote sensing images based on prior thematic maps and image features

Multiscale segmentation is the premise and key step of geographic object-based image analysis (GEOBIA), but scale selection remains a challenge in multiscale segmentation. Over the years, scale selection and evaluation in image segmentation has been extensively explored and many methods have been developed. In these methods, when a scale is chosen or evaluated, all the features are generally extracted from images. In addition, an optimal scale is generally selected based on the pre-estimation of the statistical variance in remote sensing images or determined based on the postsegmentation evaluation of segmented results. In this study, a method was proposed to identify the optimal scale of each segmented object during the segmentation through combining the a priori thematic map knowledge with image features. First, 25 image segmentations were obtained using multiresolution segmentation algorithm of Definiens Professional 9.0 with different scales. A global score (GS) value was assigned to each segmentation based on the calculation results of the weighted variance and global Moran’s I and the single-scale optimal segmentation result was determined according to each GS of 25 segmentation scales. Second, the image feature complexity information and the a priori thematic map complexity information of each segmentation object were extracted to calculate complexity values for each object. Third, the optimal scale of each segmentation object was determined through the iterative calculation with the multithreshold method. Finally, the segmentation results of the proposed method were evaluated. The proposed method was applied to process Gaofen-2 (GF-2), GF-1, Korea Multipurpose Satellite (KOMPSAT-2), IKONOS, QuickBird and WorldView-2 high resolution satellite images to obtain the segmentation results and classification results, compared with results obtained of the optimal single-scale segmentation and the unsupervised evaluation method. The experimental results of GEOBIA showed that the method was helpful for generating the segmentation object with the optimal scale.

Impacts of changing spatial scales on CPUE–factor relationships of Ommastrephes bartramii in the northwest Pacific

AbstractThe selection of spatial scales is of particular importance in modeling relationships between fishery abundance and its influencing factors, because these relationships are significantly affected by spatial scale. Here, we explore the spatial scale effects of catch per unit effort (CPUE)–factor relationships for Ommastrephes bartramii in the northwest Pacific. The original commercial fishery data and oceanographic factors were tessellated to 12 spatial scales from 5′ to 60′ with an interval of 5′. Under the original scale and 12 tessellated scales, we constructed the generalized additive models (GAMs) to model the relationships between the O. bartramii CPUE and the influencing factors, including Year, Month, Latitude (Lat), Longitude (Lon), sea surface salinity (SSS), sea surface temperature (SST), sea surface chlorophyll‐a (Chl‐a) concentration, and sea surface height (SSH). Our multi‐scale analysis showed that the relationships are sensitive to spatial scales. Among the factors, Year, Month, and SSS share quadratic polynomial scaling relations; Lat, SST, and Chl‐a illustrate power law scaling relations; Lon has a linear scaling relation; and SSH presents an exponential scaling relation. Considering the scale sensitivity of the factor sort‐order and the accumulation of explained residual deviance in GAM, we suggest 30′–45′ as the optimal range of spatial scales for analyzing the CPUE–factor relationships for O. bartramii. Our research improves understanding of the impacts of changing scales in fisheries and provides a potential method for the selection of a suitable spatial scale for fisheries analysis and resource surveying.

Selection of appropriate time scale with Boruta algorithm for regional drought monitoring using multi-scaler drought index

Spatial distribution of drought plays key role specifically in hydrological research. Drought is a complex stochastic natural hazard caused by prolonging shortage of rainfall and available water resources. The multi-scalar drought indices (based on probability distribution) are commonly used for making effective drought mitigation policies. In addition, the multi-scalar drought indices have great extent of the inaccurate determination of drought classes due to its probabilistic nature. However, the interpretation and applicability of various time scales are cumbersome for multi-scalar drought in various meteorological stations at a particular region. In this regards, accurate estimation and continuous monitoring of future drought at regional level requires a more appropriate and important time scale with respect to regions under study. In this study, we aimed to investigate the appropriate time scale for multi-scalar drought indices by using geo-reference points of meteorological stations. We used Boruta algorithm with two random forest adapters of machine learning algorithms for regionalized optimization of drought monitoring time scale. We explored the appropriate time scale for the Standardized Precipitation Temperature Index (SPTI) of 52 meteorological stations that are located across Pakistan. Results show that the significant importance of SPTI-1 (1-month time scale) for further spatial and temporal studies. That is, being high ranked and prominence, SPTI-1 has the ability to capture the characteristics of all other time scales that are in some circumstances applicable for drought characterization and classification.

Development of the Shaking Table and Array System Technology in China

Shaking table is important experimental equipment to carry out antiseismic research. Research, conclusion, comparison, and analysis concerning the developmental history, constructional situation, performance index, control algorithm, and experimental technique of the internal shaking table were reviewed and compared. Such functional parameters as internal shaking table’s table‐board size, bearing capacity, working frequency, and maximum acceleration were given. Shaking table’s constructional status quo and developmental trend were concluded. The advantages and disadvantages of different control algorithms were contrastively analyzed. Typical shaking table test, array system tests, and experimental simulation materials were induced and contrasted. Internal existing shaking table and array system test’s structural type, reduced scale, and model‐material selection were provided. Analysis and exposition about the developmental tendency of shaking table’s enlargement, multiple shaking tables array, full digitalization, and network control were made. The developmental direction, comparison of technical features, and relevant research status quo of shaking table with high‐performance were offered. The result can be reference for domestic or overseas shaking table’s design and type selection, control technique, and research on experimental technique.

Dominance-based rough sets in multi-scale intuitionistic fuzzy decision tables

To represent the structure of data measured at different granularity levels hierarchically, the concept of multi-scale information table or decision table has been presented from the perspective of granular computing. In this study, we mainly address the issue of optimal scale selection and rule acquisition in dominance-based multi-scale intuitionistic fuzzy (IF) decision tables. By considering a type of decision systems where condition attributes are taken as dominant IF values and those of decision attributes are symbolic dominance ones, we propose two dominance-based rough sets in multi-scale IF decision tables and discuss their optimal scale selection and rule acquisition algorithms, which are used to acquire decision rules for information system security auditing risk judgment for certified information systems auditors, candidate global supplier selection, and car classification. Unlike in the existing literature, the selection of the optimal scales and reduction are simultaneously performed in the viewpoint of local and global approximations in dominance-based multi-scale IF decision tables.

Root-Knot Nematodes (Meloidogyne spp.) Prevention on Tomato Plants by Utilizing Rhizosphere Bacteria for Sustainable Agriculture

Root-Knot Nematodes are one of roots damaging nematodes. Their existence leads to decrease in tomatoes productivity in Indonesia as much as 46.2%. Currently, the pest and damage prevention is focused on biological control to attain the sustainability in agriculture. Utilizing of rhizosphere bacteria is an alternative for this purpose by both direct mechanism and indirect mechanism through induced resistance. This researchis proposed to obtain the effective rhizosphere bacteria as an agent of tomato plants resistance induction on nematodes and observe its influence on the growth and productivity of the tomato plants. The methods conducted are exploration, isolation, selection, and laboratory scale experiments. Exploration in five tomato planting regions provided 189 isolates. The further laboratory scale selection resulted in 18 candidates of bacteria having the potency in growth and superiority in antagonist, and nine appropriate consortium isolates was obtained in the next compatibility test. On the final test in the field, it was concluded that P7 consortium isolate consisting of (LM24 and CK212), P52 (LM38+CN26+CK27+CK212) simply suppressed the presence of nematodes more over P40 (LM24 + CN26) solely provided the proper growth, whereas P31 (LM24+CN26+CK27) was not only able to inhibit nematodes but also provide the satisfying growth and productivity.

Microlens-Enhanced Substrate Patterning and MBE Growth of GaP Nanowires

In this paper we demonstrate the results on selective area growth of GaP nanowires via self-catalyzed growth method using molecular beam epitaxy (MBE) technique on patterned Si(111) substrates. The pattern fabrication method on a base of the photolithography process over an array of microspherical lenses has been studied theoretically and then optimized in order to obtain the nanostructures with controlled morphology. It was found that the positive resist thickness corresponding to the best achievable resolution in the subwavelength region is 250 nm in case of 1.5 μm silica spheres and excitation with 365 nm LED. The silica growth mask for selective epitaxy was fabricated. The ordered array of GaP nanowires was synthesized with MBE. Large scale ordering and selectivity of the growth technique is demonstrated.

Selection of scale can reverse the importance of stochastic controls on community assembly

ABSTRACTReconciling the long-standing debate on the importance of niche-related and neutral factors on community assembly, recent research suggests that both deterministic and stochastic processes operate simultaneously along a continuum in many biogeographical systems. In particular, stochastic processes seem to lose importance under stressful conditions, which results in the increasing influence of deterministic counterparts. In this paper, I show that, at local scales, this stochasticity–stress relationship can be reversed along the environmental stress gradients within a salt marsh: stochasticity manifested under harshness. Here, low-lying, more stressful sites contained all of the plant species of the local pool (i.e. a greater chance of ecological drift), whereas high-elevation, less stressful sites exhibited reduced species richness due to competitive exclusion (i.e. a lower chance of ecological drift). I conclude that determining whether the importance of stochasticity in shaping community structure is greater under benign or harsh conditions depends on the scale of interest.

Selection of the Optimal Segmentation Scale in High-resolution Remote Sensing Image

The selection of the optimal segmentation scale is of great significance in high-resolution remote sensing image multiple scale segmentation, which directly influences the information extraction precision from image. In order to find the optimal segmentation scale, a calculation model of the optimal segmentation scale in terms of several factors have been suggested. This method firstly calculates the best segmentation scale on the consideration of multi-band information, therefore, avoiding the potential subjectivity of human visual. Secondly, the quality evaluation function is put forward using the method of samples controlling which considering area and perimeter as factor s to evaluate consistency between segmented objects and samples. This method of the optimal segmentation scale based on multiple scale and the evaluation of the consistency between the sample and the segmented object in terms of the spectral band is proposed and verified. Results show that the method can obtain the optimal segmentation scale of remote sensing image quickly and efficiently. The algorithm of the model is simple, and is easy to realize, and it is a practical algorithm model.

Pedestrian Detection via Body Part Semantic and Contextual Information With DNN

Pedestrian detection has achieved great improve-ments in recent years, while complex occlusion handling and high-accurate localization are still the most important problems. To take advantage of the body part semantic information and the contextual information for pedestrian detection, we propose the part and context network (PCN) in this paper. A PCN is composed of three branches: the basic branch; the part branch; and the context branch. It specially utilizes two branches to detect the pedestrians through the body part semantic information and the contextual information, respectively. In the part branch, the semantic information of body parts can communicate with each other via long short-term memory (LSTM). In the context branch, we adopt a local competition mechanism (maxout) for adaptive context scale selection. By combining the outputs of all branches, we develop a strong complementary pedestrian detector with a lower miss rate and higher localization accuracy, especially for the occlusion pedestrian. The combination of the body part semantic information and the contextual information in pedestrian detection is fully explored in this paper. Comprehensive evaluations on three challenging pedestrian detection datasets (i.e., Caltech, INRIA and KITTI) well demonstrate the effectiveness of our proposed PCN. Code for PCN is publicly available on GitHub https://github.com/sunnyxiaohu/pcn_pedestrian .

Optimal Investment Timing and Scale Choice of Overseas Oil Projects: A Real Option Approach

This article presents a real option model for helping investors to determine the optimal investment timing and scale of overseas oil projects. The model is suitable for the highly uncertain environments in which many oil companies operate, where they have to suspend upstream investment, stop new oilfield construction, and wait for proper oil prices in order to avoid losses. Considering the uncertainty of oil prices and exchange rates, the results of analytical solutions presented in this paper show the critical oil price that can be seen as the investment threshold for triggering oilfield development as well as the optimal recoverable factor for every oil price level to indicate the optimal investment scale. Results of the case project show the critical oil price, which is 82.32 US dollar per barrel, and the selection of optimal investment scale. The article also demonstrates the impact of investment scale on investment timing in overseas oil projects. The policy implication from the case project is that investment decisions are finitely impacted by geological conditions. Besides, the existence of tax holiday directly contributes to a lower investment threshold. In addition, reducing unit operation cost can obviously enlarge optimal investment scale and initiate oil projects in a relatively low level of investment threshold.

A scheduling selection process for energy‐efficient task execution on DVFS processors

SummaryThe efficient execution of parallel programs with respect to execution time and energy consumption is a major concern, and often, scheduling methods are used to achieve a good performance. In this article, we consider the problem of scheduling a set of independent tasks on a parallel system with homogeneous execution units providing frequency scaling. The set of tasks has the property that the tasks exhibit a task‐specific inhomogeneous and non‐linear behavior of their specific time‐energy relation. In addition, it is assumed that execution time and energy consumption behave in a non‐linear manner with respect to frequency scaling. For the assignment of these tasks to execution units, we propose a scheduling selection process combining scheduling algorithms, which determine a task assignment, with a subsequent selection of frequency scaling, which we call schedule execution modes. This process builds a rich set of alternative schedule execution modes from which efficient (or Pareto‐optimal) schedule execution modes can be selected. Experiments are done for the SPEC CPU benchmarks. Experimental results illustrate that the enriched scheduling process leads to task assignments resulting in an efficient execution on DVFS processors.

Strategy for the selection of the minimum processing scale for the economic feasibility of biorefineries

AbstractMoving from fossil‐based economies to bio‐based economies is one of humanity's most important necessities. Bio‐based economies are sustainable alternative ways to obtain chemicals, materials, and energy, and biorefineries have been proposed as promising technological schemes for this purpose. However, the economic performance of biorefineries is strongly related to the scale of the process, as different elements (energy consumption, equipment cost, etc.) vary to different degrees when the scale varies. This situation shows the importance of evaluating the performance of the biorefinery at different scales (analysis of scale) from the design stages. The problem with the analysis of these scales is that there is no unanimous definition of ‘scale’ and the term is used imprecisely to refer to the raw material or product. Taking this into consideration, this work proposed a strategy for determining the Minimum Processing Scale for Economic Feasibility (MPSEF) and identifying the minimum scale at which a given biorefinery can operate. As study cases, three different biorefineries, based on different raw materials (cocoyam, Andes berry, and coffee cut stems) were used to exemplify the applicability of the design strategy. The MPSEF calculated for Andes berry, coffee cut stems, and cocoyam‐based biorefineries were 9.27, 35.6 and 683 ton day−1, respectively. These results showed the application of the design strategy and how it allows the determination of the minimum amount of feedstock to be processed to achieve a positive economic performance, and from this point, to calculate the rate of return that an investor would require and the appropriate scale to achieve it. © 2018 Society of Chemical Industry and John Wiley & Sons, Ltd

Dynamic moisture mode versus moisture mode in MJO dynamics: importance of the wave feedback and boundary layer convergence feedback

The Madden–Julian oscillation (MJO) is an equatorial eastward moving system with a planetary-scale coupled Kelvin–Rossby wave structure. The equatorial waves and their interaction with convection are expected to play an important role in MJO dynamics. Using the trio-interaction model for essential MJO dynamics, this study investigates the importance of dynamic feedback that includes wave feedback (WF) and boundary layer convergence feedback (BLCF), by comparing the moisture mode (MM) that contains only moisture feedback (MF) and cloud-radiative feedback (CRF), with the dynamic moisture mode (DMM) that includes additional WF and BLCF. It is shown that the dynamic feedbacks fundamentally change the properties of the MJO mode. For the MM, the MF alone yields a damping and quasi-stationary mode on wavenumber 2–4. The CRF can destabilize the MM, but it cannot produce planetary wave selection. By including the dynamic feedbacks (WF and BLCF), the resultant DMM is an unstable mode with a preferred planetary scale, which moves eastward slowly, yielding a 30–90-day period. The dynamic feedbacks produce the planetary scale selection of the DMM through generating more eddy available moist static energy on the longer wavelengths. The WF can significantly change the structure of the MM and links the propagation of the DMM to the Kelvin and Rossby wave components, with stronger Kelvin (Rossby) wave favoring faster (slower) propagation. The BLCF enhances the Kelvin wave component on the longer wavelengths, changing the horizontal structures and accelerating the eastward propagation. The WF relates the dispersion feature of the DMM to the properties of the Kelvin and Rossby waves. Since the Kelvin-wave (Rossby-wave) frequency increases (decreases) with increasing wavenumber, their coupling in the DMM yields a quasi-constant frequency at the planetary scales (wavenumber 1–3).

Statistical state dynamics of vertically sheared horizontal flows in two-dimensional stratified turbulence

Simulations of strongly stratified turbulence often exhibit coherent large-scale structures called vertically sheared horizontal flows (VSHFs). VSHFs emerge in both two-dimensional (2D) and three-dimensional (3D) stratified turbulence with similar vertical structure. The mechanism responsible for VSHF formation is not fully understood. In this work, the formation and equilibration of VSHFs in a 2D Boussinesq model of stratified turbulence is studied using statistical state dynamics (SSD). In SSD, equations of motion are expressed directly in the statistical variables of the turbulent state. Restriction to 2D turbulence facilitates application of an analytically and computationally attractive implementation of SSD referred to as S3T, in which the SSD is expressed by coupling the equation for the horizontal mean structure with the equation for the ensemble mean perturbation covariance. This second-order SSD produces accurate statistics, through second order, when compared with fully nonlinear simulations. In particular, S3T captures the spontaneous emergence of the VSHF and associated density layers seen in simulations of turbulence maintained by homogeneous large-scale stochastic excitation. An advantage of the S3T system is that the VSHF formation mechanism, which is wave–mean flow interaction between the emergent VSHF and the stochastically excited large-scale gravity waves, is analytically understood in the S3T system. Comparison with fully nonlinear simulations verifies that S3T solutions accurately predict the scale selection, dependence on stochastic excitation strength, and nonlinear equilibrium structure of the VSHF. These results constitute a theory for VSHF formation applicable to interpreting simulations and observations of geophysical examples of turbulent jets such as the ocean’s equatorial deep jets.

Literature review to characterize the empirical basis for response scale selection in pediatric populations

BackgroundDespite the importance of response option selection for patient-reported outcome measures, there seems to be little empirical evidence for the selected scale type. This article provides an overview of the published research on response scale types and empirical support within pediatric populations.MethodsA comprehensive review of the scientific literature was conducted to identify response scale option types appropriate for use in pediatric populations and to review and summarize the available empirical evidence for each scale type.ResultsEleven review/consensus guideline/expert opinion articles and 20 empirical articles that provided guidance or evidence regarding pediatric response scale selection were identified. There was general consensus that 5-point verbal rating scales, including Likert scales, were appropriate for children aged 7 or 8 and older, while graphical or faces scales are often used in pediatric studies with children of younger ages.ConclusionIn general, the verbal rating scale, numeric rating scale, visual analogue scale, and graphical scales have each demonstrated to be reliable and valid response option formats in specific contexts among pediatric populations; however, their appropriateness is dependent upon sample age. When selecting response scales, it is important to consider target population and context of use during the development of patient-reported outcome measures, especially with respect to tense, recall period, attribution, number of options, etc. In addition to age, cognitive development is an important aspect to consider for optimizing pediatric self-reported measures. More research is needed to determine clinically relevant changes and differences within pediatric research, which includes different response scale options.

Inclusion measure-based multi-granulation decision-theoretic rough sets in multi-scale intuitionistic fuzzy information tables

Multi-granulation rough sets (MGRSs) and decision-theoretic rough sets (DTRSs) are important and popular extended types of Pawlak’s classical rough set model. Multi-granulation DTRSs (MG-DTRSs), which combine these two generalized rough set models, have been investigated in depth in recent years to handle noisy distributed data. However, this combination cannot be used to acquire knowledge from multi-scale information systems, in which an object may take on different values under the same attribute depending on the scale used to measure it. Two novel types of MG-DTRSs in multi-scale intuitionistic fuzzy (IF) information tables have been developed on the basis of IF inclusion measures in this study to solve this problem. First, we introduce a type of inclusion measure between two IF sets and present the concept of inclusion measure-based DTRSs in multi-scale IF information tables. Second, we present the inclusion measure-based optimistic and pessimistic MG-DTRSs in multi-scale IF information tables, examine their properties, and analyze the three-way decision method based on the presented models. Third, we define the optimal scale selection and present the two optimal scale selection algorithms based on MG-DTRSs in multi-scale IF information tables. Fourth, we provide the reducts of the optimal scales based on MG-DTRSs in multi-scale IF information tables, examine the discernibility function reduction method, and devise two algorithms for computing an optimal approximation scale reduct. Finally, we discuss several possible generalizations related to MG-DTRSs in multi-scale IF information tables. This study provides an MG-DTRS method for acquiring knowledge from multi-scale IF information tables.