Abstract: The current pedagogical culture recognizes an educational scope within the sports practices. It is widely accepted, in the pedagogical culture, that thanks to the acquisition and development of motor skills, it is also possible to exercise abilities that concern the way of facing and managing the difficulties of everyday life. Sport is a peculiar educational environment: the children have the opportunity to discover the possibilities of their body, to correlate with their peers, and to learn how to manage the rules and the relationship with authorities, such as coaches. Educational aspects of the sport concern both non-formal and formal educational environments. Coaches play a critical role in an agonistic sphere: exactly like the competencies developed by the children, coaches have to work on their skills to properly set up the educational scene. Facing these new educational tasks - which are not new per se, but new because they are brought back to awareness - a few questions arise: does the coach have adequate preparation? Is the training of the coach in this specific area appropriate? This contribution aims to explore the issue in depth by focusing on the reality of the Football School. Starting from a possible sense of pedagogical inadequacy detected during a series of meetings with several football clubs in Piedmont (Italy), there have been highlighted some important educational needs within the professional training of sports coaches. It is indeed necessary for the coach to know the processes underlying the educational relationship in order to better understand the centrality of the assessment during the educational intervention and to be able to manage the asymmetry in the coach-athlete relationship. In order to provide a response to these pedagogical needs, a formative plan has been designed to allow both an in-depth study of educational issues and a correct self-evaluation of certain pedagogical skills’ control levels, led by the coach. This plan has been based on particular practices, the Educational Practices of Pre-test (EPP), a specific version of community practices designed for the extracurricular activities. The above-mentioned practices realized through the use of texts meant as pre-tests, promoted a reflection within the group of coaches: they set up real and plausible sports experiences - in particular football, triggering a reflection about the relationship’s object, spaces, and methods. The characteristic aspect of pre-tests is that it is impossible to anticipate the reflection as it is necessarily connected to the personal experience and sensitivity, requiring a strong interest and involvement by participants: situations must be considered by the coaches as possible settings in which they could be found on the field.
Abstract: A reliable, real-time, and non-invasive system that can identify patients at risk for hemodynamic instability is needed to aid clinicians in their efforts to anticipate patient deterioration and initiate early interventions. The purpose of this pilot study was to explore the clinical capabilities of a real-time analytic from a single lead of an electrocardiograph to correctly distinguish between rapid response team (RRT) activations due to hemodynamic (H-RRT) and non-hemodynamic (NH-RRT) causes, as well as predict H-RRT cases with actionable lead times. The study consisted of a single center, retrospective cohort of 21 patients with RRT activations from step-down and telemetry units. Through electronic health record review and blinded to the analytic’s output, each patient was categorized by clinicians into H-RRT and NH-RRT cases. The analytic output and the categorization were compared. The prediction lead time prior to the RRT call was calculated. The analytic correctly distinguished between H-RRT and NH-RRT cases with 100% accuracy, demonstrating 100% positive and negative predictive values, and 100% sensitivity and specificity. In H-RRT cases, the analytic detected hemodynamic deterioration with a median lead time of 9.5 hours prior to the RRT call (range 14 minutes to 52 hours). The study demonstrates that an electrocardiogram (ECG) based analytic has the potential for providing clinical decision and monitoring support for caregivers to identify at risk patients within a clinically relevant timeframe allowing for increased vigilance and early interventional support to reduce the chances of continued patient deterioration.
Abstract: Here a methodology is considered aiming at evaluating the economic benefit of the provision of a primary frequency control unit using a Battery Energy Storage System (BESS). In this methodology, two control types (basic and hysteresis) are implemented and the corresponding minimum energy storage system power allowing to maintain the frequency drop inside a given threshold under a given contingency is identified and compared using DigSilent’s PowerFactory software. Following this step, the corresponding energy storage capacity (in MWh) is calculated. As PowerFactory is dedicated to dynamic simulation for transient analysis, a first order model related to the IEEE 9 bus grid used for the analysis under PowerFactory is characterized and implemented on MATLAB-Simulink. Primary frequency control is simulated using the two control types over one-month grid's frequency deviation data on this Simulink model. This simulation results in the energy throughput both basic and hysteresis BESSs. It emerges that the 15 minutes operation band of the battery capacity allocated to frequency control is sufficient under the considered disturbances. A sensitivity analysis on the width of the control deadband is then performed for the two control types. The deadband width variation leads to an identical sizing with the hysteresis control showing a better frequency control at the cost of a higher delivered throughput compared to the basic control. An economic analysis comparing the cost of the sized BESS to the potential revenues is then performed.
Abstract: The management of COVID-19 patients based on chest imaging is emerging as an essential tool for evaluating the spread of the pandemic which has gripped the global community. It has already been used to monitor the situation of COVID-19 patients who have issues in respiratory status. There has been increase to use chest imaging for medical triage of patients who are showing moderate-severe clinical COVID-19 features, this is due to the fast dispersal of the pandemic to all continents and communities. This article demonstrates the development of machine learning techniques for the test of COVID-19 patients using Chest X-Ray (CXR) images in nearly real-time, to distinguish the COVID-19 infection with a significantly high level of accuracy. The testing performance has covered a combination of different datasets of CXR images of positive COVID-19 patients, patients with viral and bacterial infections, also, people with a clear chest. The proposed AI scheme successfully distinguishes CXR scans of COVID-19 infected patients from CXR scans of viral and bacterial based pneumonia as well as normal cases with an average accuracy of 94.43%, sensitivity 95%, and specificity 93.86%. Predicted decisions would be supported by visual evidence to help clinicians speed up the initial assessment process of new suspected cases, especially in a resource-constrained environment.
Abstract: The deformation behaviour of additively manufactured AlSi10Mg alloy under low strains, high strain rates and elevated temperature conditions is essential to analyse and predict its response against dynamic loading such as impact and thermomechanical fatigue. The constitutive relation of Johnson-Cook is used to capture the strain rate sensitivity and thermal softening effect in AlSi10Mg alloy. Johnson-Cook failure model is widely used for exploring damage mechanics and predicting the fracture in many materials. In this present work, Johnson-Cook material and damage model parameters for additively manufactured AlSi10Mg alloy have been determined numerically from four types of uniaxial tensile test. Three different uniaxial tensile tests with dynamic strain rates (0.1, 1, 10, 50, and 100 s-1) and elevated temperature tensile test with three different temperature conditions (450 K, 500 K and 550 K) were performed on 3D printed AlSi10Mg alloy in ABAQUS/Explicit. Hexahedral elements are used to discretize tensile specimens and fracture energy value of 43.6 kN/m was used for damage initiation. Levenberg Marquardt optimization method was used for the evaluation of Johnson-Cook model parameters. It was observed that additively manufactured AlSi10Mg alloy has shown relatively higher strain rate sensitivity and lower thermal stability as compared to the other Al alloys.
Abstract: Introduction: Marginal gingivitis is a disease with considerable frequency among patients who present routinely for periodontal control and treatment. In fact, this disease may not have alarming symptoms in patients and may go unnoticed by themselves when personal hygiene conditions are optimal. The aim of this study was to collect retrograde data on the prevalence of marginal gingiva in the respective group of patients, evaluated according to specific periodontal diagnostic tools. Materials and methods: The study was conducted in two patient groups. The first group was with 34 patients, during December 2019-January 2020, and the second group was with 64 patients during 2010-2018 (each year in the mentioned monthly period). Bacterial plaque index, hemorrhage index, amount of gingival fluid, presence of xerostomia and candidiasis were recorded in patients. Results: Analysis of the collected data showed that susceptibility to marginal gingivitis shows higher values according to retrograde data, compared to cross-sectional ones. Susceptibility to candidiasis and the occurrence of xerostomia, even in the combination of both pathologies, as risk factors for the occurrence of marginal gingivitis, show higher values according to retrograde data. The female are presented with a reduced bacterial plaque index than the males, but more importantly, this index in the females is also associated with a reduced index of gingival hemorrhage, in contrast to the males. Conclusions: Cross-sectional data show that the prevalence of marginal gingivitis is more reduced, compared to retrograde data, based on the hemorrhage index and the bacterial plaque index together. Changes in production in the amount of gingival fluid show a higher prevalence of marginal gingivitis in cross-sectional data than in retrograde data; this is based on the sophistication of the way data are recorded, which evolves over time and also based on professional sensitivity to this phenomenon.
Abstract: The purpose of this paper is to develop a multi-product economic production quantity model under vendor management inventory policy and restrictions including limited warehouse space, budget, and number of orders, average shortage time and maximum permissible shortage. Since the “costs” cannot be predicted with certainty, it is assumed that data behave under uncertain environment. The problem is first formulated into the framework of a bi-objective of multi-product economic production quantity model. Then, the problem is solved with three multi-objective decision-making (MODM) methods. Then following this, three methods had been compared on information on the optimal value of the two objective functions and the central processing unit (CPU) time with the statistical analysis method and the multi-attribute decision-making (MADM). The results are compared with statistical analysis method and the MADM. The results of the study demonstrate that augmented-constraint in terms of optimal value of the two objective functions and the CPU time perform better than global criteria, and goal programming. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The contribution of this research is the use of random costs data in developing a multi-product economic production quantity model under vendor management inventory policy with several constraints.
Abstract: In this paper, we report the development of a portable and inexpensive infrared lightbox for improving the detection limits of paper-based phosphate devices. Commercial paper-based devices utilize the molybdenum blue protocol to detect phosphate in the environment. Although these devices are easy to use and have a long shelf life, their main deficiency is their low sensitivity based on the qualitative results obtained via a color chart. To improve the results, we constructed a compact infrared lightbox that communicates wirelessly with a smartphone. The system measures the absorbance of radiation for the molybdenum blue reaction in the infrared region of the spectrum. It consists of a lightbox illuminated by four infrared light-emitting diodes, an infrared digital camera, a Raspberry Pi microcontroller, a mini-router, and an iPhone to control the microcontroller. An iPhone application was also developed to analyze images captured by the infrared camera in order to quantify phosphate concentrations. Additionally, the app connects to an online data center to present a highly scalable worldwide system for tracking and analyzing field measurements. In this study, the detection limits for two popular commercial devices were improved by a factor of 4 for the Quantofix devices (from 1.3 ppm using visible light to 300 ppb using infrared illumination) and a factor of 6 for the Indigo units (from 9.2 ppm to 1.4 ppm) with repeatability of less than or equal to 1.2% relative standard deviation (RSD). The system also provides more granular concentration information compared to the discrete color chart used by commercial devices and it can be easily adapted for use in other applications.
Abstract: Modeling dam-break flows over non-flat beds requires
an accurate representation of the topography which is the main
source of uncertainty in the model. Therefore, developing robust
and accurate techniques for reconstructing topography in this class
of problems would reduce the uncertainty in the flow system. In
many hydraulic applications, experimental techniques have been
widely used to measure the bed topography. In practice, experimental
work in hydraulics may be very demanding in both time and cost.
Meanwhile, computational hydraulics have served as an alternative
for laboratory and field experiments. Unlike the forward problem,
the inverse problem is used to identify the bed parameters from the
given experimental data. In this case, the shallow water equations
used for modeling the hydraulics need to be rearranged in a way
that the model parameters can be evaluated from measured data.
However, this approach is not always possible and it suffers from
stability restrictions. In the present work, we propose an adaptive
optimal control technique to numerically identify the underlying bed
topography from a given set of free-surface observation data. In this
approach, a minimization function is defined to iteratively determine
the model parameters. The proposed technique can be interpreted
as a fractional-stage scheme. In the first stage, the forward problem
is solved to determine the measurable parameters from known data.
In the second stage, the adaptive control Ensemble Kalman Filter is
implemented to combine the optimality of observation data in order to
obtain the accurate estimation of the topography. The main features
of this method are on one hand, the ability to solve for different
complex geometries with no need for any rearrangements in the
original model to rewrite it in an explicit form. On the other hand, its
achievement of strong stability for simulations of flows in different
regimes containing shocks or discontinuities over any geometry.
Numerical results are presented for a dam-break flow problem over
non-flat bed using different solvers for the shallow water equations.
The robustness of the proposed method is investigated using different
numbers of loops, sensitivity parameters, initial samples and location
of observations. The obtained results demonstrate high reliability and
accuracy of the proposed techniques.
Abstract: We have designed a Holter that measures the heart´s activity for over 24 hours, implemented a prediction methodology, and generate alarms as well as indicators to patients and treating physicians. Various diagnostic advances have been developed in clinical cardiology thanks to Holter implementation; however, their interpretation has largely been conditioned to clinical analysis and measurements adjusted to diverse population characteristics, thus turning it into a subjective examination. This, however, requires vast population studies to be validated that, in turn, have not achieved the ultimate goal: mortality prediction. Given this context, our Insight Research Group developed a mathematical methodology that assesses cardiac dynamics through entropy and probability, creating a numerical and geometrical attractor which allows quantifying the normalcy of chronic and acute disease as well as the evolution between such states, and our Tigum Research Group developed a holter device with 12 channels and advanced computer software. This has been shown in different contexts with 100% sensitivity and specificity results.
Abstract: In this paper, the performance of a medium power (25 kW/25 kHz) hybrid inverter with a reactive transformer is investigated. To analyze the sensitivity of the inverster, the RSM technique is employed to manifest the effective factors in the inverter to minimize current passing through the Insulated Bipolar Gate Transistors (IGBTs) (current stress). It is revealed that the ratio of the axillary inductor to the effective inductance of resonant inverter (N), is the most effective parameter to minimize the current stress in this type of inverter. In practice, proper selection of N mitigates the current stress over IGBTs by five times. This reduction is very helpful to keep the IGBTs at normal temperatures.
Abstract: This article presents an analytical model to estimate the harvested power from a Magnetostrictive cantilevered beam with tip excitation. Furthermore, the effects of internal and external damping on harvested power are investigated. The magnetostrictive material in this harvester is Galfenol. In comparison to other popular smart materials like Terfenol-D, Galfenol has higher strength and machinability. In this article, first, a mechanical model of the Euler-Bernoulli beam is employed to calculate the deflection of the harvester. Then, the magneto-mechanical equation of Galfenol is combined with Faraday's law to calculate the generated voltage of the Magnetostrictive cantilevered beam harvester. Finally, the beam model is incorporated in the aforementioned combination. The results show that a 30×8.5×1 mm Galfenol cantilever beam harvester with 80 turn pickup coil can generate up to 3.7 mV and 9 mW. Furthermore, sensitivity analysis made by Response Surface Method (RSM) shows that the harvested power is only sensitive to the internal damping coefficient.
Abstract: Fourier Transform Infrared (FT-IR) spectroscopy coupled with chemometrics was used to distinguish between butter samples and non-butter samples. Further, quantification of the content of margarine in adulterated butter samples was investigated. Fingerprinting region (1400-800 cm–1) was used to develop unsupervised pattern recognition (Principal Component Analysis, PCA), supervised modeling (Soft Independent Modelling by Class Analogy, SIMCA), classification (Partial Least Squares Discriminant Analysis, PLS-DA) and regression (Partial Least Squares Regression, PLS-R) models. PCA of the fingerprinting region shows a clustering of the two sample types. All samples were classified in their rightful class by SIMCA approach; however, nine adulterated samples (between 1% and 30% w/w of margarine) were classified as belonging both at the butter class and at the non-butter one. In the two-class PLS-DA model’s (R2 = 0.73, RMSEP, Root Mean Square Error of Prediction = 0.26% w/w) sensitivity was 71.4% and Positive Predictive Value (PPV) 100%. Its threshold was calculated at 7% w/w of margarine in adulterated butter samples. Finally, PLS-R model (R2 = 0.84, RMSEP = 16.54%) was developed. PLS-DA was a suitable classification tool and PLS-R a proper quantification approach. Results demonstrate that FT-IR spectroscopy combined with PLS-R can be used as a rapid, simple and safe method to identify pure butter samples from adulterated ones and to determine the grade of adulteration of margarine in butter samples.
Abstract: In the tropics, indoor thermal environment is usually provided by a cooling mode to maintain comfort all year. Indoor thermal environment performance is sometimes different from the standard or from the first design process because of operation, maintenance, and utilization. The field study of thermal environment in the green building is still limited in this region, while the green building continues to increase. This study aims to clarify thermal performance and subjective perception in the green building by testing the temperature set-points. A Thai green office was investigated twice in October 2018 and in May 2019. Indoor environment variables (temperature, relative humidity, and wind velocity) were collected continuously. The temperature set-point was normally set as 23 °C, and it was changed into 24 °C and 25 °C. The study found that this gap of temperature set-point produced average room temperature from 22.7 to 24.6 °C and average relative humidity from 55% to 62%. Thermal environments slight shifted out of the ASHRAE comfort zone when the set-point was increased. Based on the thermal sensation vote, the feeling-colder vote decreased by 30% and 18% when changing +1 °C and +2 °C, respectively. Predicted mean vote (PMV) shows that most of the calculated median values were negative. The values went close to the optimal neutral value (0) when the set-point was set at 25 °C. The neutral temperature was slightly decreased when changing warmer temperature set-points. Building-related symptom reports were found in this study that the number of votes reduced continuously when the temperature was warmer. The symptoms that occurred by a cooler condition had the number of votes more than ones that occurred by a warmer condition. In sum, for this green office, there is a possibility to adjust a higher temperature set-point to +1 °C (24 °C) in terms of reducing cold sensitivity, discomfort, and symptoms. All results could support the policy of changing a warmer temperature of this office to become “a better green building”.
Abstract: Background: Breast cancer is the leading cause of death for women around the world. Screening mammography is the reference examination, due to its sensitivity for detecting small lesions and micro-calcifications. Therefore, it is essential to ensure quality mammographic examinations with the most optimal dose. These conditions depend on the choice of exposure parameters. Clinically, practices must be evaluated in order to determine the most appropriate exposure parameters. Material and Methods: We performed our measurements on a mobile mammography unit (PLANMED Sofie-classic.) in Morocco. A solid dosimeter (AGMS Radcal) and a MTM 100 phantom allow to quantify the delivered dose and the image quality. For image quality assessment, scores are defined by the rate of visible inserts (MTM 100 phantom), obtained and compared for each acquisition. Results: The results show that the parameters of the mammography unit on which we have made our measurements can be improved in order to offer a better compromise between image quality and breast dose. The last one can be reduced up from 13.27% to 22.16%, while preserving comparable image quality.
Abstract: One of the main practical difficulties attended with tunnel construction is related to underground water. Uncontrolled water behavior may cause extra loads on the lining, mechanical instability, and unfavorable environmental problems. Estimating underground water inflow rate to the tunnels is a complex skill. The common calculation methods are: empirical methods, analytical solutions, numerical solutions based on the equivalent continuous porous media. In this research the rate of underground water inflow to the Tabriz metro first line tunnel has been investigated by numerical finite difference method using FLAC2D software. Comparing results of Heuer analytical method and numerical simulation showed good agreement with each other. Fully coupled and one-way coupled hydro mechanical states as well as water-free conditions in the soil around the tunnel are used in numerical models and these models have been applied to evaluate the loading value on the tunnel support system. Results showed that the fully coupled hydro mechanical analysis estimated more axial forces, moments and shear forces in linings, so this type of analysis is more conservative and reliable method for design of tunnel lining system. As sensitivity analysis, inflow water rates into the tunnel were evaluated in different soil permeability, underground water levels and depths of the tunnel. Result demonstrated that water level in constant depth of the tunnel is more sensitive factor for water inflow rate to the tunnel in comparison of other parameters investigated in the sensitivity analysis.
Abstract: A decline in visual sensitivity at arbitrary points on the retina can be measured using a precise perimetry apparatus along with a fundus camera. However, the retinal layer associated with this decline cannot be identified accurately with current medical technology. To investigate cryptogenic diseases, such as macular dystrophy, acute zonal occult outer retinopathy (AZOOR), and multiple evanescent white dot syndrome (MEWDS), we evaluated an electroretinogram (ERG) function that allows moving the center of the multifocal hexagonal stimulus array to a chosen position. Macular dystrophy is a generalized term used for a variety of functional disorders of the macula lutea, and the ERG shows a diminution of the b-wave in these disorders. AZOOR causes an acute functional disorder to an outer layer of the retina, and the ERG shows a-wave and b-wave amplitude reduction as well as delayed 30 Hz flicker responses. MEWDS causes acute visual loss and the ERG shows a decrease in a-wave amplitude. We combined an electroretinographic optical system and a perimetric optical system into an experimental apparatus that has the same optical system as that of a fundus camera. We also deployed an EO-50231 Edmund infrared camera, a 45-degree cold mirror, a lens with a 25-mm focal length, a halogen lamp, and an 8-inch monitor. Then, we also employed a differential amplifier with gain 10, a 50 Hz notch filter, a high-pass filter with a 21.2 Hz cut-off frequency, and two non-inverting amplifiers with gains 1001 and 11. In addition, we used a USB-6216 National Instruments I/O device, a NE-113A Nihon Kohden plate electrode, a SCB-68A shielded connector block, and LabVIEW 2017 software for data retrieval. The software was used to generate the multifocal hexagonal stimulus array on the computer monitor with C++Builder 10.2 and to move the center of the array toward the left and right and up and down. Cone and bright flash ERG results were observed using the moving ERG function. The a-wave, b-wave, c-wave, and the photopic negative response were identified with cone ERG. The moving ERG function allowed the identification of the retinal layer causing visual alterations.
Abstract: A precise, sensitive, rapid and selective method for the solvent extraction, spectrophotometric determination of palladium(II) using para-methylphenyl thiourea (PMPT) as an extractant is developed. Palladium(II) forms yellow colored complex with PMPT which shows an absorption maximum at 300 nm. The colored complex obeys Beer’s law up to 7.0 µg ml-1 of palladium. The molar absorptivity and Sandell’s sensitivity were found to be 8.486 x 103 l mol-1cm-1 and 0.0125 μg cm-2 respectively. The optimum conditions for the extraction and determination of palladium have been established by monitoring the various experimental parameters. The precision of the method has been evaluated and the relative standard deviation has been found to be less than 0.53%. The proposed method is free from interference from large number of foreign ions. The method has been successfully applied for the determination of palladium from alloy, synthetic mixtures corresponding to alloy samples.
Abstract: A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market.
Abstract: In this paper, a method is provided for content-based image retrieval. Content-based image retrieval system searches query an image based on its visual content in an image database to retrieve similar images. In this paper, with the aim of simulating the human visual system sensitivity to image's edges and color features, the concept of color difference histogram (CDH) is used. CDH includes the perceptually color difference between two neighboring pixels with regard to colors and edge orientations. Since the HSV color space is close to the human visual system, the CDH is calculated in this color space. In addition, to improve the color features, the color histogram in HSV color space is also used as a feature. Among the extracted features, efficient features are selected using entropy and correlation criteria. The final features extract the content of images most efficiently. The proposed method has been evaluated on three standard databases Corel 5k, Corel 10k and UKBench. Experimental results show that the accuracy of the proposed image retrieval method is significantly improved compared to the recently developed methods.