An evaluation of resolution, accuracy, and precision in FT-IR spectroscopy

Infrared spectroscopy is a foundational technique for the elucidation of chemical structures. The advancements in interferometric spectroscopy, and specifically the development of Fourier transform infrared (FT-IR) spectroscopy, are responsible for the widespread usage of IR spectrometers ranging from teaching labs to pharmaceutical quality control. FT-IR affords an excellent signal-to-noise ratio that permits sensitive sampling with quantitative accuracy and high wavenumber precision based on well documented advantages (Jacquinot, Fellgett, Connes). However, the effect of resolution and instrument-to-instrument variation on wavenumber accuracy is not well understood, with previous work grossly overestimating error. Here, a recommendation of wavenumber accuracy as a function of spectral resolution, accounting for instrument variation among leading manufacturers, is given based on an experimental study of polystyrene and acetaminophen. For peaks that are well resolved and not saturated, the position can be known within 1.1 cm-1 at a spectral resolution of 4 cm-1 or higher, and within 2.2 cm-1 at 8 cm-1 resolution. Other sources of variation are also discussed (e.g., poorly resolved peaks, peak saturation, water interference, spectral noise) to give general recommendations on when IR peak positions can be considered significantly different. Such guidelines are critical for interpreting subtle positional variations, as are often present in different crystal forms of pharmaceuticals.

A mathematical fractal-fractional model to control tuberculosis prevalence with sensitivity, stability, and simulation under feasible circumstances

BACKGROUND

Tuberculosis, a global health concern, was anticipated to grow to 10.6 million new cases by 2021, with an increase in multidrug-resistant tuberculosis. Despite 1.6 million deaths in 2021, present treatments save millions of lives, and tuberculosis may overtake COVID-19 as the greatest cause of mortality. This study provides a six-compartmental deterministic model that employs a fractal-fractional operator with a power law kernel to investigate the impact of vaccination on tuberculosis dynamics in a population.

METHODS

Some important characteristics, such as vaccination and infection rate, are considered. We first show that the suggested model has positive bounded solutions and a positive invariant area. We evaluate the equation for the most important threshold parameter, the basic reproduction number, and investigate the model's equilibria. We perform sensitivity analysis to determine the elements that influence tuberculosis dynamics. Fixed-point concepts show the presence and uniqueness of a solution to the suggested model. We use the two-step Newton polynomial technique to investigate the effect of the fractional operator on the generalized form of the power law kernel.

RESULTS

The stability analysis of the fractal-fractional model has been confirmed for both Ulam-Hyers and generalized Ulam-Hyers types. Numerical simulations show the effects of different fractional order values on tuberculosis infection dynamics in society. According to numerical simulations, limiting contact with infected patients and enhancing vaccine efficacy can help reduce the tuberculosis burden. The fractal-fractional operator produces better results than the ordinary integer order in the sense of memory effect at diffract fractal and fractional order values.

CONCLUSION

According to our findings, fractional modeling offers important insights into the dynamic behavior of tuberculosis disease, facilitating a more thorough comprehension of their epidemiology and possible means of control.

Sixth order compact multi-phase block-AGE iteration methods for computing 2D Helmholtz equation

We discuss sixth order accurate 9-point compact 2- and 3-phase block alternating group explicit (block-AGE) iteration methods for computing 2D Helmholtz equation. We use Dirichlet boundary conditions and no fictitious points are involved outside the solution region for computation. The proposed 2- and 3-phase block-AGE methods require only two and three sweeps for computation and the error analysis of the suggested approximation is analyzed. We have compared the 2- and 3-phase block-AGE iteration methods with the corresponding block successive over relaxation (block-SOR) method in three experiments, in regard to number of iterations required for convergence and cpu time, where the importance of the role performed by optimal relaxation parameters of the proposed block-AGE iteration methods become evident in stipulating the convergence and precision of the calculated results. In all cases we use the tridiagonal solver and obtain the optimal relaxation parameters through computation.

Noise-dependent bias in quantitative STEM-EMCD experiments revealed by bootstrapping

Electron magnetic circular dichroism (EMCD) is a powerful technique for estimating element-specific magnetic moments of materials on nanoscale with the potential to reach atomic resolution in transmission electron microscopes. However, the fundamentally weak EMCD signal strength complicates quantification of magnetic moments, as this requires very high precision, especially in the denominator of the sum rules. Here, we employ a statistical resampling technique known as bootstrapping to an experimental EMCD dataset to produce an empirical estimate of the noise-dependent error distribution resulting from application of EMCD sum rules to bcc iron in a 3-beam orientation. We observe clear experimental evidence that noisy EMCD signals preferentially bias the estimation of magnetic moments, further supporting this with error distributions produced by Monte-Carlo simulations. Finally, we propose guidelines for the recognition and minimization of this bias in the estimation of magnetic moments.

Rethinking the applicability domain analysis in QSAR models

Notwithstanding the wide adoption of the OECD principles (or best practices) for QSAR modeling, disparities between in silico predictions and experimental results are frequent, suggesting that model predictions are often too optimistic. Of these OECD principles, the applicability domain (AD) estimation has been recognized in several reports in the literature to be one of the most challenging, implying that the actual reliability measures of model predictions are often unreliable. Applying tree-based error analysis workflows on 5 QSAR models reported in the literature and available in the QsarDB repository, i.e., androgen receptor bioactivity (agonists, antagonists, and binders, respectively) and membrane permeability (highest membrane permeability and the intrinsic permeability), we demonstrate that predictions erroneously tagged as reliable (AD prediction errors) overwhelmingly correspond to instances in subspaces (cohorts) with the highest prediction error rates, highlighting the inhomogeneity of the AD space. In this sense, we call for more stringent AD analysis guidelines which require the incorporation of model error analysis schemes, to provide critical insight on the reliability of underlying AD algorithms. Additionally, any selected AD method should be rigorously validated to demonstrate its suitability for the model space over which it is applied. These steps will ultimately contribute to more accurate estimations of the reliability of model predictions. Finally, error analysis may also be useful in "rational" model refinement in that data expansion efforts and model retraining are focused on cohorts with the highest error rates.

Deep analysis of adsorption isotherm for rapid sorption of Acid Blue 93 and Reactive Red 195 on reactive graphene

Graphene-based adsorbent was prepared by adopting a green synthetic route via the chemical exfoliation of graphite and low-temperature thermal activation. Prepared reactive graphene (RG) was characterized through various techniques, and its adsorption capabilities for textile dye removal were investigated for Acid Blue-93 (AB) and Reactive Red-195 (RR) under different operational conditions. The dye sorption equilibrium and mechanism were comprehensively studied using isotherm and kinetic models and compared statistically to explain the sorption behavior. Results show AB and RR adsorption by RG attains equilibrium in 60 min and 70 min, with a high sorption quantity of 397 mg g-1 and 262 mg g-1 (initial dye concentration of 100 mg L-1), respectively. The dye sorption anticipates that the high surface area (104.52 m2 gm-1) and constructed meso-macroporous features of RG facilitated the interaction between the dye molecules and graphitic skeleton. The R-P isotherm fitted the best of equilibrium data, having the least variance in residuals for both dyes (AB = 0.00031 and RR = 0.00047). The pseudo-second order model best fitted the kinetics of sorption on RG, with chemisorption being the predominant process delimiting step. The overall results promise the dye removal capability of RG to be an efficient adsorbent for azo-based dyes from textile effluents.

The application of objective clinical human reliability analysis (OCHRA) in the assessment of basic robotic surgical skills

BACKGROUND

Using a validated, objective, and standardised assessment tool to assess progression and competency is essential for basic robotic surgical training programmes. Objective clinical human reliability analysis (OCHRA) is an error-based assessment tool that provides in-depth analysis of individual technical errors. We conducted a feasibility study to assess the concurrent validity and reliability of OCHRA when applied to basic, generic robotic technical skills assessment.

METHODS

Selected basic robotic surgical skill tasks, in virtual reality (VR) and dry lab equivalent, were performed by novice robotic surgeons during an intensive 5-day robotic surgical skills course on da Vinci® X and Xi surgical systems. For each task, we described a hierarchical task analysis. Our developed robotic surgical-specific OCHRA methodology was applied to error events in recorded videos with a standardised definition. Statistical analysis to assess concurrent validity with existing tools and inter-rater reliability were performed.

RESULTS

OCHRA methodology was applied to 272 basic robotic surgical skills tasks performed by 20 novice robotic surgeons. Performance scores improved from the start of the course to the end using all three assessment tools; Global Evaluative Assessment of Robotic Skills (GEARS) [VR: t(19) = - 9.33, p < 0.001] [dry lab: t(19) = - 10.17, p < 0.001], OCHRA [VR: t(19) = 6.33, p < 0.001] [dry lab: t(19) = 10.69, p < 0.001] and automated VR [VR: t(19) = - 8.26, p < 0.001]. Correlation analysis, for OCHRA compared to GEARS and automated VR scores, shows a significant and strong inverse correlation in every VR and dry lab task; OCHRA vs GEARS [VR: mean r = - 0.78, p < 0.001] [dry lab: mean r = - 0.82, p < 0.001] and OCHRA vs automated VR [VR: mean r = - 0.77, p < 0.001]. There is very strong and significant inter-rater reliability between two independent reviewers (r = 0.926, p < 0.001).

CONCLUSION

OCHRA methodology provides a detailed error analysis tool in basic robotic surgical skills with high reliability and concurrent validity with existing tools. OCHRA requires further evaluation in more advanced robotic surgical procedures.

Open-source navigation system for tracking dissociated parts with multi-registration

PURPOSE

During reconstructive surgery, knee and hip replacements, and orthognathic surgery, small misalignments in the pose of prosthesis and bones can lead to severe complications. Hence, the translational and angular accuracies are critical. However, traditional image-based surgical navigation lacks orientation data between structures, and imageless systems are unsuitable for cases of deformed anatomy. We introduce an open-source navigation system using a multiple registration approach that can track instruments, implants, and bones to precisely guide the surgeon in emulating a preoperative plan.

METHODS

We derived the analytical error of our method and designed a set of phantom experiments to measure its precision and accuracy. Additionally, we trained two classification models to predict the system reliability from fiducial points and surface matching registration data. Finally, to demonstrate the procedure feasibility, we conducted a complete workflow for a real clinical case of a patient with fibrous dysplasia and anatomical misalignment of the right femur using plastic bones.

RESULTS

The system is able to track the dissociated fragments of the clinical case and average alignment errors in the anatomical phantoms of [Formula: see text]  mm and [Formula: see text]. While the fiducial-points registration showed satisfactory results given enough points and covered volume, we acknowledge that the surface refinement step is mandatory when attempting surface matching registrations.

CONCLUSION

We believe that our device could bring significant advantages for the personalized treatment of complex surgical cases and that its multi-registration attribute is convenient for intraoperative registration loosening cases.

Written Language Characteristics of Deaf and Hard of Hearing Students in Terms of the Components of the Language

Hearing has vital importance for language development. Deaf and hard of hearing children have problems in spoken and written language due to hearing loss. The development of written language is directly related to language skills such as listening, speaking, and reading skills. This study aims to evaluate the use of language components in written language in deaf and hard of hearing students. In the study, writing samples of eight deaf and hard of hearing students who continue 4th grade in the school for the deaf were taken and error analysis was conducted. Besides, interviews were made with their classroom teacher about their language development, and in-class observations were conducted. It was seen as a result of the study that deaf and hard of hearing students have significant difficulties in all components of language in written language.

What do children's errors tell us about the strategies used during a word inferencing task?

A vital and often overlooked aspect of word learning is the ability to establish deep semantic knowledge by adjusting and fine-tuning new word meanings as information becomes available. Here we studied differences in children's ability to update incorrect or incomplete word meanings by studying error types in a word inferencing task. The participants, 45 8- and 9-year-olds, read three sentences that all ended with the same nonsense word and were asked to identify the meaning of the last word. Importantly, the third sentence always provided the most useful information about the word's meaning. When children made errors, two types of responses were of interest. The first was when children gave a response that ignored the third sentence but fit one or two of the earlier ones. This suggests that the children had failed to update the meaning accurately. The second was when children were given enough information in the three sentences yet said that they were still unable to identify a word meaning. This suggests that the children would not attempt to infer a word when they were unsure of the answer. When controlling for number of correct responses, we found that children with smaller vocabularies were significantly more likely to fail to incorporate the third sentence, whereas children with large vocabularies were more likely to say that they were still unable to identify a meaning. These findings indicate that children with smaller vocabularies may be at risk of incorrectly inferring a new word's meaning rather than seeking further information to ensure accuracy.

An innovative modulating functions method for pseudo-state estimation of fractional order systems

In this paper, the objective is to estimate the pseudo-state of fractional order systems defined by the Caputo fractional derivative from discrete noisy output measurement. For this purpose, an innovative modulating functions method is proposed, which can provide non-asymptotic estimation within finite-time and is robust against corrupting noises. First, the proposed method is directly applied to the Brunovsky's observable canonical form of the considered system. Then, the initial value of the pseudo-state is exactly expressed by an algebraic integral formula, based on which the pseudo-state is estimated. Second, the properties and construction of the required modulating functions are studied. Furthermore, error analysis is provided in discrete noise cases, which is useful for improving the estimation accuracy. In order to show the advantages of the proposed method, two numerical examples are given, where both rational order and irrational order dynamical systems are considered. After selecting the design parameters using the provided noise error bound, the pseudo-states of considered systems are estimated. The fractional order Luenberger-like observer and the fractional order H_∞-like observer are also applied. Better than the applied fractional order observers, the proposed method can guarantee the convergence speed and robustness at the same time.

A comparative study of Sumudu HPM and Elzaki HPM for coupled Burgers' equation

The two hybrid algorithms Sumudu HPM and Elzaki HPM are used in the current study to tackle coupled Burgers' equations and produce accurate results. To demonstrate the validity of the given approaches, three instances are used. Applying Sumudu HPM and Elzaki HPM yields the same approximate and exact answers in all of the examples taken into consideration, which is proved with the help of the accompanying figures. It attests to the entire acceptance and accuracy of the solutions produced by these methods. The proposed regimes also have error and convergence analyses available. The current analytical regimes offer a more effective method of handling partial differential equations than the intricate numerical systems. It is also asserted that exact and approximation solutions are compatible. Also announced is the planned regime's numerical convergence.

Energy forecasting of the building-integrated photovoltaic façade using hybrid LSTM

Effective building energy management systems need a reliable approach to estimating future energy needs using renewable energy sources. However, nonlinear and nonstationary trends in building energy use data make prediction more challenging for integrating the photovoltaic system. To estimate future energy forecast, this work presents a hybrid approach based on random forest (RF) and long short-term memory (LSTM) using complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). Initial steps in our suggested procedure include utilizing CEEMDAN to translate the raw energy usage data into multiple components. Then, the component with the most significant frequency is predicted using RF, and the other components are forecasted using hybrid LSTM. Finally, all of the individual parts' predictions are combined to form a whole. Real-world output energy usage data has been predicted to test the suggested strategy. Results from the experiments show that the suggested strategy outperforms the reference methods.

Enhance Safety in Aneurysm Surgery: Strategies for Prevention of Intraoperative Vascular Complications

Complications during surgery for intracranial aneurysms can be devastating. Notorious pitfalls include premature rupture, parent vessel occlusion, local cerebral injury and brain contusion, and incomplete neck obliteration. These unfavorable intraoperative events can result in major neurological deficits with permanent morbidity and even mortality. Herein, the author highlights the relevant surgical strategies used in his daily practice of aneurysm surgery (e.g., aneurysm clipping with adenosine-induced temporary cardiac arrest), application of which may help prevent vascular complications and enhance surgical safety through reduction of the associated risks, thus allowing improvement of postoperative outcomes. Overall, all described methods and techniques should be considered as small pieces in the complex puzzle of prevention of vascular complications during aneurysm surgery.

A New Numerical Approach for the Analysis of Variable Fractal and Fractional Order Differential Equations

The variable fractional dimensions differential and integral operator overrides the phenomenon of the constant fractional order. This leads to exploring some new ideas in the proposed direction due to its varied applications in the recent era of science and engineering. The present papers deal with the replacement of the constant fractional order by variable fractional order in various fractal-fractional differential equations. An advanced numerical scheme is developed with the help of Lagrange three-point interpolation and further, it is employed for the solution of the proposed differential equations. However, the properties of these new operators are presented in detail. Finally, the error analysis is also conducted for the numerical scheme deployed. The results are validated by the suitable choice of applications to real-life problems. The well- known multi-step-Adams-Bashforth numerical scheme for classical differential equations is recovered when the non-integer order is one.

What children's number naming errors tell us about early understanding of multidigit numbers

This investigation examined the nature and development of a foundational symbolic numeric skill-number identification-focusing on children's emerging knowledge of multidigit numbers. Two studies were conducted with Russian preschoolers. Study 1 (N = 350; 51-77 months of age) investigated age-related changes in the accuracy of number naming and in the types of errors children produced. The errors fell into distinct categories: syntactic (structural errors such as naming each digit separately without using place-value markers) and lexical (nonstructural errors such as replacing the name of a digit with the name of another digit). Number reading accuracy improved with age, primarily due to a decreased frequency of syntactic errors. Boys made fewer syntactic errors than girls. Study 2 (N = 110; 61-74 months of age) showed that accuracy of naming double-digit numbers was related to conceptual understanding of the base-10 numeric structure. The frequency of syntactic errors in number naming was negatively associated with the use of base-10 representations, whereas lexical errors were not related to children's ability to represent base-10 number structure. Implications for understanding children's mathematics trajectories are discussed.

Performance of air temperature from ERA5-Land reanalysis in coastal urban agglomeration of Southeast China

Near-surface air temperature is an important indicator of climate change and extreme events. ERA5-Land reanalysis products feature finer spatial and temporal resolutions, and have been widely adopted in global climate-related research. However, the performance of ERA5-Land air temperature data in coastal urban agglomerations has received little attention. In this study, a comprehensive evaluation is conducted in the Guangdong-Hong Kong-Macau Greater Bay Area (GBA) using the observations of 1080 automatic weather stations in 2018 as reference. Generally, ERA5-Land underestimates temperature (an average bias of 0.90 °C), and performs better at low temperatures than at high temperatures. At the station level, it is observed that the correlation shows a strong positive linear relationship with the distance to the coastline in summer, and that the bias increases with increasing altitude throughout the year. With respect to different land cover types, data accuracy over urban and built-up lands is the lowest. The spatial pattern of ERA5-Land is generally consistent with that of stations but relatively poor in urban areas. In addition, ERA5-Land properly captures daily and monthly variations, as well as intraday temperature fluctuations. These conclusions provide a reference for the implementation of ERA5-Land in coastal urban agglomerations.

A new fractional orthogonal basis and its application in nonlinear delay fractional optimal control problems

This paper aims to devise a novel fractional orthogonal basis to solve a certain class of nonlinear fractional optimal control problems with delay whose system dynamics is governed by a nonlinear fractional differential equation of the Caputo type. The foundation of the new framework is based on a hybrid of block-pulse and fractional-order Legendre functions. A new integral operator associated with the proposed orthogonal basis is constructed by using the Riemann-Liouville integral operator. This operator enables one to immensely reduce the complexity of computations related to the Riemann-Liouville integral operator. Some significant theoretical results concerning the new fractional basis are provided. Several problems are tested for the validation and verification of our numerical findings. It is demonstrated that the new fractional basis produces an exact solution for a specific class of nonlinear delay fractional optimal control problems. Generally, the developed fractional basis is a promising mathematical tool for investigating fractional-order systems.

Classifying the causes of morbidity and error following treatment of facial fractures

Analysing morbidity and using this to improve the quality of patient care is an important component of clinical governance. Several methods of data collection and clinical analysis have been suggested, but to date none have been widely adopted. All adult patients sustaining facial fractures were prospectively identified between 01 March 2019 and 28 February 2020, and matched to those who required a return to theatre for surgical complications. Morbidity resulting in a return to theatre was determined using the Clavien-Dindo classification and the Northwestern University error ascribing method. During this period, return to theatre occurred for 33/285 (11.6%) procedures and 23/173 (13.3%) of patients being treated for facial fractures. According to the 27 procedures discussed, Clavien-Dindo Grade IIIb was most commonly found (20/27). Error in judgement (13/35) and nature of disease (12/35) were ascribed as the most common causes of error. Presence of a consultant was associated with increased odds of a return to theatre (p = 0.014). Standardised national data collection of morbidity and error is required for comparisons of outcomes within a single institution or between institutions. To the best of our knowledge, this is the first paper to utilise these widely used methods of morbidity analysis for facial fracture surgery. We would recommend further development of an error analysis method that is more specific to complications from facial fracture surgery.

The Space-Time Coupled Fractional Cattaneo-Friedrich Maxwell Model with Caputo Derivatives

In the current article, we have thoroughly investigated the collective impact of mixed convection with thermal radiation and chemical reaction on MHD flow of viscous and electrically conducting fluid (Cattaneo–Friedrich Maxwell-CFM model) over a permeable surface embedded in a porous medium. Here we have utilized the Caputo time-fractional derivatives and mechanical laws (generalized shear stress constitutive equation and generalized Fourier’s and Fick’s laws) are being used to fractionalize the presented model. The effects of radiative heat flux, Ohmic dissipation, and internal absorption are presented through generalized Fourier’s law while Fick’s law or mass transfer equation offers the effects of first order chemically reactive species. The finite element method and finite difference method are being utilized to numerically solve the nonlinear coupled differential equations. It is established, through compression of numerical and analytical solutions, that the presented model is convergent. Further, error analysis of the subject model is also carried out. Moreover, for better illustration of results, we have also offered a graphical and tabular presentation of impacts of the parameters of interest on velocity, temperature, concentration profile, local skin friction coefficient, and heat and mass transfer. It is evident from the obtained results that velocity near and away from the surface increases with the enhancement of fractional derivative parameter whereas an opposite trend is observed in the case of temperature. Furthermore, it is noticed that temperature shows a decreasing behavior for the value \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\Lambda }_{\theta }<2$$\end{document}Λθ<2 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\Lambda }_{\phi }<2$$\end{document}Λϕ<2, on the other hand entirely opposite trend is witnessed for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\Lambda }_{\theta }\ge 3$$\end{document}Λθ≥3 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\Lambda }_{\phi }\ge 3$$\end{document}Λϕ≥3. From an engineering perspective, we have acquired comprehensive outcomes such that the heat transfer offers an increasing trend in the case of T_R and thermal fractional parameter \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\beta_{1}$$\end{document}β1 . Additionally, the chemical reaction parameter and Sc significantly contribute towards the mass transfer rate. Since, in literature, one cannot refer to such results with non-integer Caputo fractional derivatives thus the results obtained through the current assessment hold significance for future research avenues. Moreover, the numerical inferences of the subject study may contribute to an advanced thermal processing method in the food industry to swiftly increase the temperature for cooking or sterilization drives.

Quantifying uncertainty cascading from climate, watershed, and lake models in harmful algal bloom predictions

In response to increased harmful algal blooms (HABs), hypoxia, and nearshore algae growth in Lake Erie, the United States and Canada agreed to phosphorus load reduction targets. While the load targets were guided by an ensemble of models, none of them considered the effects of climate change. Some watershed models developed to guide load reduction strategies have simulated climate effects, but without extending the resulting loads or their uncertainties to HAB projections. In this study, we integrated an ensemble of four climate models, three watershed models, and four HAB models. Nutrient loads and HAB predictions were generated for historical (1985-1999), current (2002-2017), and mid-21st-century (2051-2065) periods. For the current and historical periods, modeled loads and HABs are comparable to observations but exhibit less interannual variability. Our results show that climate impacts on watershed processes are likely to lead to reductions in future loading, assuming land use and watershed management practices are unchanged. This reduction in load should help reduce the magnitude of future HABs, although increases in lake temperature could mitigate that decrease. Using Monte-Carlo analysis to attribute sources of uncertainty from this cascade of models, we show that the uncertainty associated with each model is significant, and that improvements in all three are needed to build confidence in future projections.

Parametric study on interply tracking in multilayer composites by analytic-signal technology

Recently, researchers proposed the use of ultrasound combined with analytic-signal concepts for the reconstruction of the internal ply structure of composites. Optimal parameters for the pulse-echo mode ultrasonic testing are determined by modeling the analytic-signal response. The internal structure can be reconstructed by instantaneous metrics based on the interaction of the multilayer structure and the ultrasonic wave. However, there are certain drawbacks associated with the use of instantaneous metrics. The phase-derived interply track tends to be sensitive to the inspection conditions. This paper analytically studies the errors of the interply tracking for a wide range of parameters, including (i) signal-to-noise ratio, (ii) bandwidth, (iii) interply thickness, and (iv) attenuation, amongst others. It provides a guideline on how to improve the performance of the interply tracking procedure in real measurements. An experimental study combining the analytic-signal procedure with a standard log-Gabor filter in the frequency domain is performed to derive the interply tracks of a 24-layer composite laminate in a robust way. The bandpass filter selects the appropriate frequency band of the analytic-signal response from the composite. It shows a good ability for frequency and bandwidth selection, and can efficiently cope with noise features. The reconstructed ply tracks in A-scan, B-scan, and C-scan modes are analyzed to verify the performance of this procedure.

Error evaluation of Judd-Ofelt spectroscopic analysis

Judd-Ofelt (J-O) spectroscopic knowledge of a rare-earth-doped luminescent material is crucial to its application. Although a large number of papers with regard to the J-O study of various rare-earth-doped luminescent materials have been reported each year, few papers presented the errors of the J-O intensity parameters Ω_i (i = 2, 4, 6) and radiative probabilities evaluated from them. Present study focuses on the error evaluation of the J-O parameters and radiative probabilities. An error theory is established for the J-O analysis and radiative probability. Two error analysis methods based on root mean square of the difference either between measured and calculated oscillator strengths (δf_rms) or between measured and calculated line strengths (δS_rms) are studied. Explicit error expressions are presented for the J-O parameters and radiative probability. The validity of the theory is verified by applying it to widely studied Er³⁺, Tm³⁺, Ho³⁺ and Nd³⁺ ions that are doped into four single-crystals (LiNbO₃, SrGdGa₃O₇, LiYF₄ and YVO₄) and a glass. The two methods are identical in nature and give similar results of errors of Ω_i.

Decision tree-based diagnosis of coronary artery disease: CART model

BACKGROUND AND OBJECTIVE

As the most common cardiovascular defect, coronary artery disease (CAD), also called ischemic heart disease, is one of the substantial causes of death globally. Several diagnosis approaches such as baseline electrocardiography, echocardiography, magnetic resonance imaging, and coronary angiography are suggested for screening the suspected patients that may suffer from CAD. However, applying such methods may have health side effects and/or expensive costs.

METHODS

As an alternative to the available diagnosis tools/methods, this research involves a decision tree learning algorithm called classification and regression tree (CART) for a simple and reliable diagnosis of CAD. Several CART models are developed based on the recently CAD dataset published in the literature.

RESULTS

Utilizing all the features of the dataset (55 independent parameters), it was found that only 40 independent parameters influence the CAD diagnosis and consequently development of the predictive model. Based on the feature importance obtained from the first CART model, three new CART models are then developed using 18, 10, and 5 selected features. Except for the five-feature CART model, the outcomes of developed CART models demonstrate the maximum achievable accuracy, sensitivity, and specificity for CAD diagnosis (100%), while comparing the predictions with the reported targets. The error analysis reveals that the literature models including sequential minimal optimization (SMO), bagging SMO, Naïve Bayes (NB), artificial neural network (ANN), C4.5, J48, Bagging, and ANN in conjunction with the genetic algorithm (GA) do not outperform the CART methodology in classifying patients as normal or CAD.

CONCLUSIONS

Hence, the robustness of the tree-based algorithm in accurate and fast predictions is confirmed, implying the proposed classification technique can be successfully utilized to develop a coherent decision-making system for the CAD diagnosis.

Linear and Nonlinear Isotherm Models and Error Analysis for the Sorption of Kresoxim-Methyl in Agricultural Soils of India

Kresoxim methyl sorption in soils of five agro-climatic zones of India varied from 41.6% to 84.7%. Highest sorption was recorded in organic carbon rich Almora soil. Isotherm parameters for linear and non-linear Freundlich and Temkin models were almost same, whereas Langmuir parameter Q₀, for linear (1.60 to 9.434 μg g^-1) and non-linear (8.48 to 17.129 μg g^-1) models were quite different. For isotherms optimization different error functions such as sum of squares error (SSE), root mean square error (RMSE), Chi square error, hybrid fractional error (HYBRID) and average relative error (ARE) were calculated. Lowest error function values were obtained for Freundlich isotherm in all the soils except inceptisol (Kolkata) for which Langmuir isotherm gave the best fit. Statistical analysis using SAS 9.3 software and Tukey's HSD test revealed the significant effect (p < 0.001) of soil type on sorption. Sorption correlated positively with the organic carbon and clay contents of the soil.