Ratio Of Deviation Research Articles

A Digital Approach to via Edge Roughness Characterization and Quantification

This paper introduces a new digital integration that combines edge diffractometry with convolutional neural networks (CNN) for via metrology and inspection. The beam propagation method (BMP) was used to simulate the interferogram generated by edge diffractometry to characterize via edge roughness (VER). A comprehensive database was established to link different fringe patterns to VER for CNN training. The well-trained CNN-based methodology provided a fast and accurate assessment of VER, with a root mean squared error (RMSE) of 0.073 and an average mean absolute deviation ratio (MADR) of 2.274%. In addition, the proposed digital approach was compared to the multilayer perceptron machine (MLP) in terms of computational efficiency and predictive accuracy. The proposed digital integration greatly improved the accuracy and speed of VER measurement, characterization, and quantification, potentially enhancing device yield and reliability. The successful application of this digital approach could open up possibilities for various types of via or pattern metrology.

Simultaneous Determination of Pyridoxine HCl, Isoniazid, Trimethoprim and Sulfamethoxazole by Double Divisor Ratio Spectra Derivative Spectroscopic Method

Tuberculosis could be regarded as a serious and enduring menace to global health. A significant hurdle in tuberculosis treatment lies in drug resistance, including the emergence of multiple drug resistance. A regulatory agency has recently endorsed the fixed-dose combination of pyridoxine HCl, isoniazid, trimethoprim, and sulfamethoxazole as a robust therapy for cases of tuberculosis resistant to multiple drugs. Therefore, a successful attempt was made to develop and validate a novel spectroscopic method, i.e., double deviation ratio spectra derivative spectroscopic method, for the simultaneous determination of pyridoxine HCl, Isoniazid, trimethoprim, and sulfamethoxazole in their pure form. The optimized divisor concentration in the developed method was found to be a mixture of 6 μg/mL of sulfamethoxazole and 16 μg/mL of pyridoxine HCl for the determination of isoniazid and trimethoprim in the same quaternary mixture. Similarly, the optimized divisor concentration for the determination of sulfamethoxazole and pyridoxine HCl was found to be a mixture of isoniazid and trimethoprim with concentrations of 10 and 12 μg/mL, respectively. With the developed method, the linearity for pyridoxine HCl, isoniazid, trimethoprim, and sulfamethoxazole was found to be in the range of 8 to 40 μg/mL, 10 to 30 μg/mL, 12 to 36 μg/mL, and 4 to 12 μg/mL, respectively. The results of the accuracy study, in terms of percentage recovery, were found to be 99.92 ± 0.978, 100.04 ± 1.731, 99.87 ± 1.811, and 98.83 ± 0.922 for the simultaneous determination of pyridoxine HCl, isoniazid, trimethoprim, and sulfamethoxazole, respectively, using the developed method. The developed method has been successfully validated as per the ICH guidelines.

A Comparison Study of the Solid Phantom and Water Phantom Using 6 MV and 15 MV Photon Energies, Depending on the Depth

Water is such an environmental element that is considered the best human body tissue equivalent. In the field of dosimetry studies, water is frequently used. This comparison study is conducted by a solid phantom and a water phantom with 6 MV and 15 MV photon energies, respectively. A cylindrical-type ionization chamber is used to collect charge when beams are on. The distance between the ray source and the surface of the phantom was fixed at 100 cm i.e. to SSD (Source to Surface Distance) of during the experiment. Chamber travels 1 cm to 20 cm in both phantoms and an electrometer is attached in the experimental set-up to measure the charge. The field size was 10x10 cm2. The relative deviation ratio of the solid phantom to the water phantom was calculated. In the result, the maximum deviation was 0.64%, while the minimum deviation was 0%, corresponding to the depths of 1 cm and 2.5 cm, respectively, for 6 MV and at 15 MV, maximum deviation and minimum deviation were 1.90% and 0.167% respectively, corresponding to the depths of 1.5 cm and 13 cm. Therefore, it can be said that the solid phantom can overcome the disadvantages of installation time required for the water phantom and problems while water level changing for depth measurement, simultaneously can used to measure the radiological dose precisely. Bangladesh J. Nuclear Med. 27(1): 34-38, 2024

Solar activity dependence for the relationship between nighttime medium-scale traveling ionospheric disturbance and sporadic E (Es) layer activities in summer during 1998–2019 over Japan

To investigate solar activity dependence of the coupling between medium-scale traveling ionosphere disturbance (MSTID) and sporadic E (Es) layer, we analyzed the total electron content (TEC) obtained from a Japanese global positioning system (GPS) receivers and ionosonde at Kokubunji (35.7° N, 139.5° E) in Japan during the summer period of May–August from 1998 to 2019. To obtain perturbation TEC caused by MSTIDs, the detrended TEC is calculated by subtracting 1-h moving averages from the measured TEC for each pair of GPS satellite and receiver. The detrended TEC data are mapped on to the geographical coordinates to make detrended 2-D maps with spatial resolution of 0.15° × 0.15° in longitude and latitude. The MSTID activity is defined as a ratio of the standard deviation to the background TEC over Kokubunji in Japan. Day-to-day variations of the MSTID activity during summer nights was compared to Es layer parameters [critical frequency (foEs\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${f}_{o}Es$$\\end{document}) and Δfo-b≡foEs-fbE\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\Delta f}_{o-b}\\equiv {f}_{o}Es-{f}_{b}E$$\\end{document}, where fbEs\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${f}_{{\ ext{b}}}Es$$\\end{document} is blanketing frequency] derived from ionosonde station at Kokubunji. We have found that the correlation coefficient between the MSTID activity and foEs\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${f}_{o}Es$$\\end{document}(Δfo-b\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\Delta f}_{o-b}$$\\end{document}) between 1998 and 2019 is 0.5 3 (0.46) on average, suggesting that there is an electrodynamical coupling between the Es layer and F region could generate nighttime MSTIDs. We also have found that the correlation coefficient positively correlates with solar activity. This finding indicates that in the high solar activity conditions, when the growth rate of Perkins instability is relatively low, generation of the polarization electric fields in the Es\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$Es$$\\end{document} layer could play a more important role to grow MSTIDs than in the low solar activity conditions.Graphical

Creating a Lactation Model for 305-Day Milk Yield with Different Resampling Techniques (Bagging Mars) in Mars Modeling

The main purpose of this research is to obtain a prediction model for milk yield by using Multivariate Adaptive Regression Splines (MARS) and Bagging MARS algorithms as a non-parametric regression technique. For this purpose, the effects on milk yield of 305 days were investigated by using lactation parameters in dairy cattle. In the study, 9337 lactation milk yield records belonging to 37 animals belonging to the 2022-2023 period were used and the data set was created by randomly ordering the animals. Data on milk yield results were analyzed with MARS and Bagging MARS algorithms. For dairy cattle; it was modeled with explanatory variables such as lactation month (month), service period (SP), last 7 days average milk yield (L7DMMY), animal's first birth age (FP), animal's age (Age), number of lactations (LN).Correlation coefficient (r), coefficient of determination (R2), Adjusted R2, Root of Square Mean Error (RMSE), standard deviation ratio (SD ratio), mean absolute percent error (MAPE), mean absolute for MARS algorithm estimating total average milk yield deviation (MAD) and Akaike Information Criteria (AIC) values are 0.9986, 0.997, 0.977, 0.142, 0.052, 0.2389, 0.086 and -88, respectively. Similar statistics for the Bagging MARS algorithm are 0.754, 0.556, 0.453, 1.8, 0.666, 3.96, 1.47, and 115, respectively. It has been observed that MARS and Bagging MARS algorithms provide correct results according to the goodness of fit statistics. In this study, it was revealed that MARS algorithm gave better results in milk yield modeling of 305-day lactation.

Investigation on particle slug flow using large eddy simulation combined a particle kinetic energy model

In this study, an investigation on particle hydrodynamic behaviors of gas-particle slug flow is modeled and numerically simulated. A novelty particle kinetic energy model at subgrid-scale level is developed to consider the effect of gas turbulence on particle movement and a four-way coupling approach is combined. Anisotropic particle dispersions and the multiphase interactions is revealed by using a second-order moment turbulence model and large eddy simulation is performed to solve the Euler-Euler two-fluid transport equations, Predictions are well agreed with the experimental data and reported results by discrete particle model built-in the multiphase flow model with interphase exchanges code. Bubble motions have great effects on the particle dynamics due to bubble entrainment. Flow patterns of particle circulation are generated between higher and lower concentrations. The largest frequency of power spectrum density at center of top surface is approximately 4.5 times larger than that of wall region. Bubblelike granular temperatures are much larger than smaller-scale particle granular temperature. At the top surface, maximum value of vertical bubblelike Reynolds stress is found at x/W = 0.28, it is 4.0 times larger than that of the lateral x-direction. In addition, the mean values, and the standard deviation of SGS particle kinetic energy at center are both approximately 3.5 times larger than those of z = 10.0 cm. For particle shear stress at middle section, maximum ratios of mean value and standard deviation at central regions to those of walls reach up to 8.0 and 11.0.

A hybrid CNN–RNN model for rainfall–runoff modeling in the Potteruvagu watershed of India

AbstractAccurate rainfall‐runoff analysis is essential for water resource management, with artificial intelligence (AI) increasingly used in this and other hydrological areas. The need for precise modelling has driven substantial advancements in recent decades. This study employed six AI models. These were the support vector regression model (SVR), the multilinear regression model (MLR), the extreme gradient boosting model (XGBoost), the long‐short‐term memory (LSTM) model, the convolutional neural network (CNN) model, and the convolutional recurrent neural network (CNN‐RNN) hybrid model. It covered 1998–2006, with 1998–2004 for calibration/training and 2005–2006 for validation/testing. Five metrics were used to measure model performance: coefficient of determination (R2), Nash‐Sutcliffe efficiency (NSE), mean absolute error (MAE), root‐mean square error (RMSE), and RMSE‐observations standard deviation ratio (RSR). The hybrid CNN‐RNN model performed best in both training and testing periods (training: R2 is 0.92, NSE is 0.91, MAE is 10.37 m3s−1, RMSE is 13.13 m3s−1, and RSR is 0.30; testing: R2 is 0.95, NSE is 0.94, MAE is 12.18 m3s−1, RMSE is 15.86 m3s−1, and RSR is 0.25). These results suggest the hybrid CNN‐RNN model is highly effective for rainfall‐runoff analysis in the Potteruvagu watershed.

Improved heat transfer mathematical model forpyramid shaped seasonal heat storage water pit and the influence of boundary conditions

Seasonal heat storage can make use of urban waste heat for low-carbon heating throughout the year. Previous models for pyramid shaped water pit have limited adaptability and ignore the impact of soil temperature in the early stages of operation on the performance of water pits. This article combines two classic mathematical models to establish a mathematical model that can adapt to various sizes of inverted pyramid shaped water pits. The validation of this model was conducted using experimental data from 60000 m3 water pit of Dronninglund, and the influence of boundary conditions for this module were calculated and discussed. The results showed that the root mean square errors of the simulated top, bottom, and average temperature of the water pit were 3.07 °C, 2.39 °C, and 1.37 °C, with relative deviation ratios of 4.25 %, 2.27 %, and 6.62 %, respectively. Furthermore, it was found that for every 5 °C increase in the set average soil temperature, the storage efficiency of the water pits increases by 0.4 %∼0.5 %. In the case of common top insulation of the water pit, the total heat loss at the top, side walls, and bottom are 66.83 %, 31.8 %, 1.37 %. While considering comprehensive insulation in all directions, the heat loss rate for the top, side walls, and bottom are similar with the former, being 67.84 %, 30.79 %, and 1.37 %, respectively. The proposal and findings of this article provide a basis for simplified optimization planning and design of large-scale seasonal heat storage systems.

Generalized Confidence Intervals for Ratios of Standard Deviations Based on Log-Normal Distribution when Times Follow Weibull Distributions.

Modern anesthetic drugs ensure the efficacy of general anesthesia. Goals include reducing variability in surgical, tracheal extubation, post-anesthesia care unit, or intraoperative response recovery times. Generalized confidence intervals based on the log-normal distribution compare variability between groups, specifically ratios of standard deviations. The alternative statistical approaches, performing robust variance comparison tests, give P-values, not point estimates nor confidence intervals for the ratios of the standard deviations. We performed Monte-Carlo simulations to learn what happens to confidence intervals for ratios of standard deviations of anesthesia-associated times when analyses are based on the log-normal, but the true distributions are Weibull. We used simulation conditions comparable to meta-analyses of most randomized trials in anesthesia, and coefficients ofvariation . The estimates of the ratios of standard deviations were positively biased, but slightly, the ratios being 0.11% to0.33% greater than nominal. In contrast, the 95% confidence intervals were very wide (i.e., > 95% of P ≥ 0.05). Although substantive inferentially, the differences inthe confidence limits were small from a clinical or managerial perspective, with amaximum absolute difference inratios of 0.016. Thus, P < 0.05 isreliable, but investigators should plan for TypeII errors atgreater than nominal rates.

Statistical Performance of Gridded Rainfall Datasets Over Ungauged Jalaur River Basin, Philippines

The study presented aims to find the most appropriate climate dataset for the data-scarce Jalaur River Basin (JRB), Iloilo, Philippines, by evaluating the statistical performance of five rainfall datasets (APHRODITE, CPC NOAA, ERA5, SA-OBS, and PGF-V3) with resolutions of 0.25° and 0.5° having a time domain of 1981 to 2005. Bilinear interpolation implemented through Climate Data Operator (CDO) was used to extract and process grid climate datasets with Linear scaling as bias correction to minimize product simulation uncertainties. The datasets were compared to the lone meteorological station nearest to JRB investigated at monthly and annual timescales using six statistical metrics, namely, Pearson’s correlation coefficient (r), coefficient of determination (R2), modified index of agreement (d1), Kling-Gupta efficiency, Nash-Sutcliffe efficiency (NSE), and RMSE-observations standard deviation ratio (RSR). The results indicate a strong positive correlation with the observed data for both rainfall and temperature (r &gt; 0.8; R2, d1 &gt; 0.80). Although graphical observation shows an underestimation of rainfall, goodness-of-fit values indicate very good model performance (NSE, KGE &gt; 0.75; RSR &lt; 0.50). In terms of temperature, variable responses are observed with significant overestimation for maximum temperature and underestimation for minimum temperature. SA-OBS proved to be the best-performing dataset, followed by ERA5 and PGF-V3. These key findings supply useful information in deciding the most appropriate gridded climate dataset for hydrometeorological investigation in the JRB and could enhance the regional representation of global datasets.

Comparative analysis of HEC-HMS and SWAT hydrological models for simulating the streamflow in sub-humid tropical region in India.

Assessment of water availability in sub-humid regions is important due to distinct climatic and environmental conditions. In this study, Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) models have been assessed in simulating streamflows in the sub-humid tropical Kabini basin in Kerala, India, spanning 1260 km2. Calibration and validation utilized daily weather data from 1997 to 2015 from the Muthankera gauging station. The study investigated the impact of routing methods on runoff simulation in the ArcSWAT, exploring Muskingum and Variable Storage methods. Evaluation metrics encompassed Nash-Sutcliffe Efïciency (NSE), Coefficient of Determination (R2), Percent bias (PBIAS), RMSE-observations standard deviation ratio (RSR), and Peak Percent Threshold Statistics (PPTS) approach for high-flow values. The result indicates that HEC-HMS outperforms SWAT concerning R2 and NSE values during daily calibration and validation. Monthly simulations showed HEC-HMS closely aligning with SWAT (Variable storage), outperforming SWAT (Muskingum). The PPTS approach proved effective in simulating high-flow values. Both models exhibited proficiency in streamflow analysis within the study area, promising predictive potential for future hydrological studies in sub-humid regions.

Identifying Heterogeneity in SAR Data with New Test Statistics

This paper presents a statistical approach to identify the underlying roughness characteristics in synthetic aperture radar (SAR) intensity data. The physical modeling of this kind of data allows the use of the Gamma distribution in the presence of fully developed speckle, i.e., when there are infinitely many independent backscatterers per resolution cell, and none dominates the return. Such areas are often called “homogeneous” or “textureless” regions. The GI0 distribution is also a widely accepted law for heterogeneous and extremely heterogeneous regions, i.e., areas where the fully developed speckle hypotheses do not hold. We propose three test statistics to distinguish between homogeneous and inhomogeneous regions, i.e., between gamma and GI0 distributed data, both with a known number of looks. The first test statistic uses a bootstrapped non-parametric estimator of Shannon entropy, providing a robust assessment in uncertain distributional assumptions. The second test uses the classical coefficient of variation (CV). The third test uses an alternative form of estimating the CV based on the ratio of the mean absolute deviation from the median to the median. We apply our test statistic to create maps of p-values for the homogeneity hypothesis. Finally, we show that our proposal, the entropy-based test, outperforms existing methods, such as the classical CV and its alternative variant, in identifying heterogeneity when applied to both simulated and actual data.

Improved Land Use Efficiency Through Spectral Beam Splitting in Agrivoltaic Farms

Installing photovoltaic (PV) collectors above arable land (Agrivoltaics) can aid with the shortage of available land area for solar power generation and food production. Most open field agrivoltaics are based on opaque PV devices which absorb photosynthetically active radiation (PAR, 400-700 nm), reducing crop yield and increasing variability in light distribution across the field. This research evaluates the performance of spectral beam splitter integrated photovoltaic (BSIPV) modules using a PV performance model. A high percentage (66 %) of PAR incident on the spectral beam splitter is transmitted effectively to the plants, while the near infrared radiation (NIR, &gt; 700 nm) is reflected to the adjacent bifacial opaque photovoltaic module to generate power. In the model, seven rows of modules were placed uniformly across the field at a height of four meters from the ground. Considering a cool season (November – March) in Yuma, Arizona, in a conventional opaque PV agrivoltaic farm received 43 % lower total daylight integral (TDLI) across the season in comparison to open field with a coefficient of variation (ratio of standard deviation to mean expressed in percentage) of 56 % in TDLI across the field. On the other hand, the BSIPV agrivoltaic farm limited the drop in TDLI to 7 % in comparison to open field and the coefficient of variation to 14 % across the field. Thus, BSIPV showed a 36 % improvement in TDLI relative to the conventional opaque PV agrivoltaic farm. The results of the current study justify further research on the proposed collector concept.

Design and optimization of heat pump with infrared drying for Glycyrrhiza uralensis (Licorice) processing.

A new dryer, integrating infrared and heat pump drying technologies, was designed to enhance licorice processing standardization, aiming at improved drying efficiency and product quality. Numerical simulation using COMSOL software validated the air distribution model through prototype data comparison. To address uneven air distribution, a spoiler was strategically placed based on CFD simulation to optimize its size and position using the velocity deviation ratio and non-uniformity coefficient as indices. Post-optimization, the average velocity deviation ratio decreased from 0.5124 to 0.2565%, and the non-uniformity coefficient dropped from 0.5913 to 0.3152, achieving a more uniform flow field in the drying chamber. Testing the optimized dryer on licorice demonstrated significant improvements in flow field uniformity, reducing licorice drying time by 23.8%. Additionally, optimized drying enhanced licorice color (higher L* value) and increased retention rates of total phenol, total flavone, and vitamin C. This research holds substantial importance for advancing licorice primary processing, fostering efficiency, and improving product quality.

Reference intervals for knee functions specific to outpatients with knee osteoarthritis: a cross-sectional study

BackgroundReference values (RVs) for knee function tests have been reported in perioperative patients with knee osteoarthritis (KOA); however, such values for practical use in outpatient setting has yet to be determined. Therefore, we aimed to establish the reference intervals (RIs) for outpatients with mild to moderate KOA.MethodsThis cross-sectional study enrolled 202 outpatients with KOA from 8 Japanese orthopedic clinics and measured knee extensor/flexor muscle strength (MS) and knee extension/flexion range of motion (ROM). We used multiple regression analysis to evaluate the sources of variation, including sex, age, body mass index, Kellgren–Lawrence (K-L) classification, bilateral KOA, and exercise habits. Magnitude of between-subgroup differences is expressed as standard deviation ratio (SDR) based on a three-level nested analysis of variance, with SDR ≥ 0.4 as the threshold for requiring RIs specific for subgroups. RIs were calculated parametrically using two-parameter Box-Cox formula if Gaussian transformation of RVs was successful, otherwise calculated nonparametrically.ResultsPartitioning was required by sex for extensor and flexor MS (SDR = 0.65, 0.57, respectively) and by K-L classification for flexion ROM (SDR = 0.54). RIs were determined parametrically for extensor MS as 0.27–2.09 (male) and 0.27–1.54 (female) Nm/kg and for flexor MS 0.18–1.20 (male) and 0.13–0.79 (female) Nm/kg. On the other hand, RIs for extension and flexion ROM were determined nonparametrically due to discrete nature of their RVs. The RIs determined for extension ROM were -15°–0° and for flexion ROM were 105°–150° (for K-L grade I/II) and 95°–140° (for K-L grade III/IV).ConclusionsThe ranges of RIs determined specifically for patients with mild to moderate KOA were in-between those of age-matched healthy controls and pre-surgical KOA patients, both of which we had reported for use in physiotherapeutic management of KOA patients undergone total knee arthroplasty. The newly derived RIs will provide an objective benchmark for physiotherapy targeting outpatients with mild to moderate KOA.

Feasibility of using in situ UV/Vis spectrometer probe for measuring COD in WWTP based on UASB reactor

The aim of this work is to report the use of a UV/Vis spectrometer for real time, in situ monitoring of the chemical oxygen demand (COD) in a municipal wastewater treatment plant (WWTP) operating with upflow anaerobic sludge blanket (UASB) reactor, installed in south of Brazil. The spectrometer was used according to the factory calibration procedures: global, local offset and local linear. COD probe measurements were compared to laboratory analyses for the calibration procedures. Continuous operation led to increasing errors, which was related to grime deposition on the probe window and avoided with periodic cleaning. Performance of the probe measurements versus laboratory analyses was evaluated with coefficient of determination, root mean squared error (RMSE), relative RMSE, RMSE to standard deviation ratio (RSR) and Student’s t-test. It is concluded that the best calibration procedures is the local linear, for the influent and the effluent of UASB reactor. The probe consists of an improvement to real time and in situ monitoring of South America WWTPs.

Mixing properties of coronary infusion catheters assessed by in vitro experiments and computational fluid dynamics.

Continuous infusion thermodilution is an established technique for the assessment of absolute coronary blood flow and microvascular resistance due to its proven accuracy and reproducibility. However, for this technique to yield reliable measurements, direct and homogenous mixing of injected saline and blood is mandatory. This study aimed to assess and compare the mixing properties of two different microcatheters, namely the Rayflow® (with sideholes for infusion) and the Finecross® catheter (single end-hole for infusion), which are commonly used in the catheterization laboratory. The study employed three different methods to evaluate the mixing properties of the catheters. Firstly, a qualitative assessment of mixing was performed using ink injections in an in vitro bench model of a coronary artery. Secondly, in analogy to the human catheterization laboratory, mixing properties over the length of the coronary artery were assessed semi-quantitatively by temperature measurements in the bench model. Lastly, a quantitative assessment was performed by 3D computational fluid dynamics, where the standard deviation and entropy ratio of the temperature over the cross-section in the coronary artery model were calculated for both catheters. All three evaluation methods demonstrated that the Rayflow catheter's specific design leads to a more optimal, homogeneous mixture of blood and saline over both the cross-section and length of a coronary vessel, as compared with the standard end-hole catheter.

Analysis Of The Attitude Of Secondary School Teachers Towards The Use Of Bichronous Online Learning

Bichronous online learning is a recently coined terminology that refers to a blended form of synchronous (real-time online meeting) and asynchronous (anywhere, anytime learning) online learning. The present study aims to analyse the attitude of secondary school teachers towards bichronous online learning based on gender, locality, age, and type of institution. The sample consists of 100 secondary school teachers from 20 schools (10 each from government and private) in the Samba district. The investigator adopted the descriptive survey method and used a self-developed attitude scale for collecting data. The reliability and validity of the scale were also established by the investigator. For the analysis of data, Mean (M), Standard Deviation (SD), and Critical Ratio (CR) were used. The findings of the study reveal that there is a significant difference between the attitude of secondary school teachers based on gender (male and female), locality (urban and rural), age (below 40 and above 40), and type of institution (government and private). The results of the present investigation will help the stakeholders to take necessary steps to develop willingness among the teachers to use bichronous online learning in the teaching-learning process and make it more interesting and innovative.

Hyperspectral and Fluorescence Imaging Approaches for Nondestructive Detection of Rice Chlorophyll.

Estimating and monitoring chlorophyll content is a critical step in crop spectral image analysis. The quick, non-destructive assessment of chlorophyll content in rice leaves can optimize nitrogen fertilization, benefit the environment and economy, and improve rice production management and quality. In this research, spectral analysis of rice leaves is performed using hyperspectral and fluorescence spectroscopy for the detection of chlorophyll content in rice leaves. This study generated ninety experimental spectral datasets by collecting rice leaf samples from a farm in Sichuan Province, China. By implementing a feature extraction algorithm, this study compresses redundant spectral bands and subsequently constructs machine learning models to reveal latent correlations among the extracted features. The prediction capabilities of six feature extraction methods and four machine learning algorithms in two types of spectral data are examined, and an accurate method of predicting chlorophyll concentration in rice leaves was devised. The IVSO-IVISSA (Iteratively Variable Subset Optimization-Interval Variable Iterative Space Shrinkage Approach) quadratic feature combination approach, based on fluorescence spectrum data, has the best prediction performance among the CNN+LSTM (Convolutional Neural Network Long Short-Term Memory) algorithms, with corresponding RMSE-Train (Root Mean Squared Error), RMSE-Test, and RPD (Ratio of standard deviation of the validation set to standard error of prediction) indexes of 0.26, 0.29, and 2.64, respectively. We demonstrated in this study that hyperspectral and fluorescence spectroscopy, when analyzed with feature extraction and machine learning methods, provide a new avenue for rapid and non-destructive crop health monitoring, which is critical to the advancement of smart and precision agriculture.

Regularities of subsidence progress in terms of the repeated earth’s surface undermining in the context of Lviv-Volyn coal basin

Study of deformation manifestation within the undermined rock formation and at the earth’s surface is among the key problems during underground mineral mining. The paper has analyzed the available methods identifying the earth’s surface subsidence in the process of its undermining through underground excavation. The analysis has shown branching as well as different approaches and numerous factors. The researchers believe they influence the results. Hence, the purpose is to substantiate regularities of the earth’s surface subsidence while its undermining by means of longwalls varying in their length. The study was carried out using materials of the actual observations on the subsidence in 31 profile lines under the conditions of SE Lvivvuhillia mines. To identify the functional regularities, the factors were assumed which researchers consider as the most influential ones. The performed correlation and regression analysis demonstrated clear relation only for longwall length and moderate relation between subsidence deviation and longwall length-mining depth ratio. A graphical-analytical technique was applied to define distribution of subsidence deviation points depending upon a longwall length-mining depth ratio; moreover, a coefficient was determined to be used while calculating design subsidence values if the longwall length-mining depth ratio is 0.1-0.7.