Number Research Articles

Cut-off points to classify numeric values of quality of life into normal, mild, moderate, and severe categories: an update for EORTC-QLQ-H&N35

BackgroundQuality of life (QoL) is an important determinant of physical and mental health. QoL in head and neck cancer tends to deteriorate due to changes in the physical, functional, psychological aspects. EORTC-QLQ-H&N35 is an instrument that measure the QoL specifically in head and neck cancer patients. EORTC-QLQ-H&N35 give a numeric value to QoL of patients with high value correspond to better QoL.ObjectiveThe aim of present study was to find out the cut-off points of numeric values of EORTC-QLQ-H&N35 to categorize QoL impairment into different categories (normal, mild, moderate, and severe). Present study also aims analyze the QoL among head and neck cancer patients under these new categories.MethodologyTotal 205 patients of head and neck cancer visiting to the outpatient unit were enrolled in this study. Hindi version of EORTC-QLQ-H&N35 was used to evaluate the QoL. Total 9 classification schemes were created with different cut-off points to classify the global QoL score into normal, mild, moderate and severe categories. QoL data was then analyze using the scheme having highest F value in ANOVA test.ResultsClassification scheme having cut-off values 76–100 for normal QoL, 51–75 for mild QoL impairment, 26–50 for moderate and 0–25 for severe QoL impairment found to have highest F value (729.915) in ANOVA test. The mean QoL score among total 205 patients were 60.08 ± 19.06. Based on the new classification scheme, QoL was normal in 46 (22.4%) patients whereas QoL was impaired to mild level in 76 (37.1%) patients, to moderate level in 76 (37.1%) and to severe level in 7 (3.4%) patients. Role functioning, emotional functioning and social functioning was impaired to severe level in 4 (2.0%), 13 (6.3%) and 3 (1.5%) patients respectively.ConclusionEORTC-QLQ-H&N35 offer a comprehensive review of QoL in head and neck cancer patients. By designating the QoL score into different categories, it will become easier for clinician to have a better idea of QoL of head and neck cancer patients.

Cation exchange capacity- An alternative method to investigate the geological barrier for landfills?

Clays and clay minerals are ideal raw materials for geological barriers and landfill liners because of their low-hydraulic permeabilities, their swelling properties and adsorption capacities. The geological barrier is a supplementary barrier beneath the body of the landfill, intended to protect the environment from uncontrolled leachate from the waste material. An Austrian standard defines the process for site exploration and the required laboratory tests and parameters for the analysis of the geological barrier. The most important laboratory tests besides grain size analysis are the Atterberg limits and the determination of the clay mineralogy using X-ray diffraction. However, the analysis of the cation exchange capacity (CEC) is not included in the list of laboratory tests. CEC is a numerical value that describes the physical properties of clays, such as the diffusion of charged and uncharged molecules and the cation retention. Hence, the objective of this study is to clarify whether the determination of the CEC using the Cu-trien method represents a possible alternative to currently used laboratory tests.For this purpose, three samples (loess, sand and clay) from two landfill sites owned and operated by Zöchling GmbH as well as six mixtures of these samples with varying compositions were examined for their mineralogical, chemical and geotechnical properties. The samples consisted of varying amounts of quartz, feldspar, calcite, dolomite and the clay minerals smectite, illite, kaolinite, vermiculite and chlorite. The results showed that the bulk clay mineralogy correlates well with the Atterberg liquid limit (R2 = 0.73) and the CEC (R2 = 0.88) and furthermore, the results of the two methods – Atterberg liquid limit and CEC- even correlated better (R2 = 0.95).This demonstrates that the CEC can be an alternative to the Atterberg liquid limit and/or the analysis of the mineralogical composition of the material. Advantages of the CEC are rapidness, its good reproducibility and cost-efficiency of the analyses compared to the other two methods. Based on the results of this study, a partial substitution of the currently used laboratory tests is considered feasible and CEC could at least be used for fast and efficient screening.

Real Gas Effect on Motion of Self-gravitating Cylindrical Detonation Waves

Abstract: The effect of real gas on the adiabatic propagation of strong cylindrical imploding detonation waves in the nonhomogeneous medium having power varying density distribution. Ignoring the effect of overtaking disturbances the CCW solution has been obtained for the problem at the detonation waves are initially in Chapman-Jouguet state. The analytical expressions for the detonation velocity just behind the front along with other flow variables are derived. The expressions for the freely propagating velocity of detonation front are derived. Using the jump condition across the strong detonation front, the numerical values of the pressure and density across the front have been computed with the help of the software MATLAB. It is observed that the variation of flow parameters with convergence of detonation front is depend upon the change in Alfven Mach number, the parameters of realness of the gas and initial density distribution. Finally, it is found that change in parameter of realness of the medium plays an important role on the post flow variables. The effect of change in Alfven Mach number and density parameter is also discussed through graphs. The outcome of the present study is compared with the results for the case of ideal reacting gas.

Developing Safety Performance Functions for Severe Distraction-Related Crashes along Kentucky’s Rural and Urban Two-Lane Roadways

This study develops safety performance functions (SPFs) for severe (“KA” or “fatal and suspected serious injury”) distraction-related crashes along Kentucky’s rural and urban two-lane undivided roadway segments using recent four-year (2018–2021) crash records. Additional efforts were made to meticulously scrutinize crash narratives categorized as non-distracted and correct those cases. To account for crash under-dispersion, the Conway–Maxwell–Poisson, heterogeneous Conway–Maxwell–Poisson, zero-inflated Conway–Maxwell–Poisson, and zero-inflated heterogeneous Conway–Maxwell–Poisson (ZI-HTCMP) models were fitted and compared. The ZI-HTCMP model outperformed the other models with respect to several goodness-of-fit measures (e.g., mean absolute deviance and mean square prediction error). From the developed SPFs for rural and urban two-lane roads, wider lanes and higher speed limits (55 mph) were associated with increased severe distraction-related crash frequencies. Furthermore, some variables were found to be significant in rural areas, but insignificant in urban areas, and vice versa. For example, major collector roads, minor collector/local roads, the presence of roadside guardrails, wider right-hand shoulders, the presence of horizontal curves, and the presence of vertical grades were associated with increased crash frequencies along rural two-lane roads. In addition, the proportion of heavy vehicles (>5%) and the existence of paved shoulders were associated with increased crashes along urban two-lane roads. The empirical Bayes method was then used to rank the top 10 distraction-related high crash locations (HCLs) for both rural and urban two-lane segments. In-depth investigation of HCLs highlighted single-vehicle distraction-related crashes as the most common collision type. Countermeasures were proposed to help reduce severe distraction-related crashes, for example, installing chevron signs along rural two-lane roads.

Method for determining the Lyapunov exponent of a continuous model using the monodrome matrix

The Lyapunov exponent is a measure of the sensitivity of a dynamic system to any changes and disturbances. It is therefore applicable in many fields of science, including physics, chemistry, economics, psychology, biology, medicine, and technology. Therefore, there is a need to have effective methods for determining the value of this exponent. In particular, it concerns the definition of its sign. The positive value of the Lyapunov exponent confirms the sensitivity of the system, especially when the system is chaotic. A negative value indicates the stability of the dynamic system being tested. The numerical value of the Lyapunov exponent indicates the degree of sensitivity of the dynamic system under study. Although the mathematical definition of the Lyapunov exponent is clear and simple, in practice determining its value is not a trivial matter, especially for continuous models. This paper presents a method for determining the Lyapunov exponent for continuous models. This method is based on the monodromy matrix. The work, for example, presents research on the following models of physical systems: the Van der Pol model with external forcing, the nonlinear mathematical pendulum model with external forcing and the Lorenz weather model.

Interface stabilization and propagation in phase field models of solidification: resolving the issue of large driving forces

Abstract One of the long-standing problems in the phase field, namely, combining the principles of thermodynamics and capillarity with the numerical aspects of interface propagation in simulations, is re-investigated. Numerical schemes are discussed which allow for stable simulations with arbitrary driving forces, considering or excluding capillarity. We re-investigate a classical stabilization scheme that decouples interface stabilization from curvature evaluation, ensuring stable simulations even under large driving forces. A novel mathematical analysis gives a rigorous estimate for the time stepping and a numerical value of the required stabilization strength. The proposed stabilization scheme is benchmarked for 3-dimensional dendritic growth under directional solidification conditions for different solidification speeds.

Nonlinear behavior of existing pre-tensioned concrete beams: Experimental study and finite element modeling with the constitutive Serial-Parallel rule of mixtures

The performance of existing prestressed concrete (PC) beams and their time-dependent behavior have been concerns for bridge maintenance services. In this paper, laboratory tests of three PC void slab beams taken away from an obsolete bridge were conducted and an alternative more efficient finite element (FE) method was developed. In preparing the three beam specimens, two retained their original reinforced concrete (RC) overlay and one chiseled off its RC overlay. Through the four-point loading tests, the load response plots of the beams from elastic to plastic failure were carefully documented, including the strains along the mid-span section, the strains of longitudinal rebars and strands, and the mid-span deflection. The test results showed that no interface slip was observed between the RC overlay and the top of void slab during the whole loading process, and the yield load of the test beams with the overlay was approximately 45 % higher than that without the overlay. Regarding the proposed nonlinear numerical formulation, the modelling process avoided the treatment of complex reinforcement and prestressing tendon layouts. The prestressed concrete was simulated as a composite material whose behavior is depicted by a constitutive serial-parallel rule of mixtures (SP-RoM). The generalized Maxwell model and generalized Kelvin model were applied to calculate the time-dependent losses of prestress. All the developments have been implemented within the open-source FE code Kratos-Multiphysics environment and are fully available. Compared with the test outcomes, it shows that the numerical results are in good agreement with the solutions in terms of stiffness, load-deflection curves, and damage evolution. The differences between the experimental and numerical values of ultimate load for the specimens with and without RC overlay were all within 10 %. Furthermore, the proposed nonlinear models can also predict the time-dependent prestress losses of existing PC beams.

Study on interior beam–column joint sub-assemblage under bi-directional loading using finite element analysis

Purpose The purpose of this paper is to study the shearing performance under bi-directional loading of an interior beam–column joint (BCJ) sub-assemblage using the finite element analysis (FEA) tool (midas fea), validated in this research. Design/methodology/approach The BCJ can be defined as an essential part of the column that transfers the forces at the ends of the members connected to it. The members of the rigid jointed plane frame resist external forces by developing twisting moment, bending moment, axial force and shear force in the frame members. On the type of joints, the response to the action of lateral loads depends on reinforced concrete (RC) framed structures. The joint is considered rigid if the angle between the members remains unchanged during the structural deformation. This work examined the shear deformation, load displacement and strength of a non-seismically detailed internal concentric RC joint using non-linear FEA. The bi-directional loading imposes the oblique compression zone on one joint corner. This joint core’s oblique compression strut mechanism differs significantly from that under unidirectional loading. The numerical results are compared with experimental results in this study, with the data published in the literature. Findings Numerical analysis results show that, in the comparative study of numerical and experimental values, the FEA tool predicts the behaviour of the RC BCJ well. The discrepancy between the experimental and numerical results amounts to 6 to 12% end displacement of the beam, 7% resultant joint shear force, 4.23% column bar strain and 0.70% hoop strain. Originality/value The current code of practice describes the joint sub-assemblage behaviour along the single axis individually. In the non-orthogonal system, the superposition of the two axes for joint space results in overlapping the stresses and, hence, the formation of the oblique strut. This may result in a reduction in the joint capacity under bi-directional loading. The behaviour must be explored in depth, and an attempt is made for further exploration.

Label-free surface-enhanced Raman spectroscopy analysis method for liquid biopsy and its application in serum-based lung cancer diagnosis and classification

Liquid biopsy offers promise for the diagnosis of malignant tumors or their precancerous lesions at the subclinical stage, which is crucial for improving the survival rate of cancer. Label-free surface-enhanced Raman spectroscopy (SERS) has become an emerging detection method in liquid biopsy. The accuracy of SERS-based diagnosis relies on both precise measurement and effective data analysis. In our previous study, a large laser spot SERS method was proposed for the precise detection of complex liquids. In this work, a logical Raman data analysis method was developed, to address the lack of Raman characteristics and biological significance in current SERS-based diagnosis data analysis. The measured Raman data is classified to obtain a weighting matrix of classification criteria, and this matrix is used to establish a material correspondence with the Raman spectra, extract key Raman peaks, determine corresponding biomolecules and biological processes, thus enabling a logical analysis of the data. This method has been used to analyze the SERS data of lung cancer, it can not only show exceptional performance in diagnosing lung cancer and differentiating small cell lung cancer, but also obtain the Raman diagnostic and classification criteria with clear numerical values and reasonable biological significance, demonstrating its great potential value in precise biosensing.

Visualizing numbers: Investigating the effect of presentation format on emotional responses and performance in lottery tasks.

Numeracy is the ability to understand, manipulate, and make sense of numerical information. It is crucial for everyday decision making that involves dealing with numbers. In this study, we tested whether we can help people make better choices in monetary lotteries by communicating numerical values (i.e., payoffs and probabilities) using visual aids. We also checked whether presenting this information in a visual form reduces affect negativity. Participants (N = 210) made choices in 10 monetary lotteries accompanied with visual aids (experimental condition) or without visual aids (control condition). After the lottery task, participants completed questionnaires measuring experienced emotions and numerical skills. Despite finding no hypothesized effect of visual aids on performance in a lottery task, the exploratory analysis revealed the interaction effect. In a visual aid condition, participants who were relatively less educated scored significantly higher in a lottery task in comparison to those in the control condition. Additionally, participants in the visual aid condition reported significantly lower intensity of negative emotions after the lottery task than those in the control condition. We discuss possible causes and mechanisms that can explain the results we obtained. We argue that visual aids are a promising tool for future learning, and their friendly format can positively influence people's reactions to decisions involving numerical information. However, we also point out the necessity for further research and exploration of the role of different designs of visual aids and individual differences. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Numerical and Theoretical Analyses of Laminated Veneer Lumber Beams Strengthened with Fiber-Reinforced Polymer Sheets

This study outlines a method of utilizing the finite element method and a simple mathematical model to predict the behavior of laminated veneer lumber (LVL) beams strengthened with composite sheets. The numerical models were created using the Abaqus 2017 software. The LVL was considered as a linearly elastic or elastic–plastic material, factoring in Hill’s yield criterion. The composites were simulated as linearly elastic–ideally plastic materials. The mathematical models were predicated on the methodology of transformed cross-section. The theoretical and numerical outcomes were juxtaposed with previous empirical investigations. The comparison encompassed load-bearing capacity, stiffness, and deformation under peak force. Furthermore, presentations of normal stress maps in the LVL and composite have been illustrated. The derived maps were juxtaposed with the delineations of failure modes. An adequate correlation was identified between the theoretical, numerical, and empirical values in the case of beams reinforced with aramid, glass, and carbon sheets. The relative deviation varied from several to multiple percentages. This technique is not applicable for evaluating load-bearing capacity and deformation when only dealing with sheets with low elongation of rupture. This is a consequence of their premature failure. The proposed models may be utilized by researchers and engineers in the design of reinforcements for timber structures.

Caution Regarding ChatGPT's Appropriateness and Reliability Regarding Surgery for Wrist Arthritis.

Chat Generative Pre-Trained Transformer (ChatGPT), an artificial intelligence (AI) program, is widely used for information compilation. This study sought to analyze the quality and consistency of the information generated by ChatGPT regarding common procedures for wrist arthritis. 32 standardized questions regarding wrist osteoarthritis and related procedures (4-corner-fusion [4CF], proximal row carpectomy [PRC], resurfacing capitate pyrocarbon implant, wrist denervation, and total wrist arthrodesis and arthroplasty) were presented to the ChatGPT-3.5 interface 3 separate times, without feedback. ChatGPT's answers were evaluated for medical accuracy by 3 reviewers and rated as "appropriate," "appropriate but incomplete," or "inappropriate." Ratings were then converted to numerical values to calculate an intraclass correlation coefficient (ICC). A DISCERN score was used to assess quality, and Flesch-Kincade Grade Level and Flesch Reading Ease Score for readability. 75% of the responses were deemed "appropriate," with 23 questions receiving unanimous appropriate ratings across all responses. The ICC was 0.97 (95% CI [0.46, 0.98]), indicating excellent reliability. DISCERN score was 60 (good). The Flesch-Kincaid Grade Level was 14.6 ± 1.9, and the Flesch Reading Ease Score was 25.3 ± 6.7, implying a college reading level. The information that ChatGPT provided for PRC and total wrist arthrodesis and arthroplasty, appeared to be more reliable than for 4CF and denervation. ChatGPT's reliability and accuracy of information varied across procedures, possibly due to unknown and diverse sources. Furthermore, while some answers were factually correct, many provided generic information across differing questions, limiting usefulness. ChatGPT must be used cautiously and the limitations understood.

Stochastic neuro-swarming intelligence paradigm for the analysis of magneto-hydrodynamic Prandtl–Eyring fluid flow with diffusive magnetic layers effect over an elongated surface

In recent years, the integration of stochastic techniques, especially those based on artificial neural networks, has emerged as a pivotal advancement in the field of computational fluid dynamics. These techniques offer a powerful framework for the analysis of complex fluid flow phenomena and address the uncertainties inherent in fluid dynamics systems. Following this trend, the current investigation portrays the design and construction of an important technique named swarming optimized neuro-heuristic intelligence with the competency of artificial neural networks to analyze nonlinear viscoelastic magneto-hydrodynamic Prandtl–Eyring fluid flow model, with diffusive magnetic layers effect along an extended sheet. The currently designed computational technique is established using inverse multiquadric radial basis activation function through the hybridization of a well-known global searching technique of particle swarm optimization and sequential quadratic programming, a technique capable of rapid convergence locally. The most appropriate scaling group involved transformations that are implemented on governing equations of the suggested fluidic model to convert it from a system of nonlinear partial differential equations into a dimensionless form of a third-order nonlinear ordinary differential equation. The transformed/reduced fluid flow model is solved for sundry variations of physical quantities using the designed scheme and outcomes are matched consistently with Adam's numerical technique with negligible magnitude of absolute errors and mean square errors. Moreover, it is revealed that the velocity of the fluid depreciates in the presence of a strong magnetic field effect. The efficacy of the designed solver is depicted evidently through rigorous statistical observations via exhaustive numerical experimentation of the fluidic problem.

Mathematical modeling and machine learning-based optimization for enhancing biofiltration efficiency of volatile organic compounds

Biofiltration is a method of pollution management that utilizes a bioreactor containing live material to absorb and destroy pollutants biologically. In this paper, we investigate mathematical models of biofiltration for mixing volatile organic compounds (VOCs) for instance hydrophilic (methanol) and hydrophobic (α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document}-pinene). The system of nonlinear diffusion equations describes the Michaelis-Menten kinetics of the enzymic chemical reaction. These models represent the chemical oxidation in the gas phase and mass transmission within the air-biofilm junction. Furthermore, for the numerical study of the saturation of α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document}-pinene and methanol in the biofilm and gas state, we have developed an efficient supervised machine learning algorithm based on the architecture of Elman neural networks (ENN). Moreover, the Levenberg-Marquardt (LM) optimization paradigm is used to find the parameters/ neurons involved in the ENN architecture. The approximation to a solutions found by the ENN-LM technique for methanol saturation and α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document}-pinene under variations in different physical parameters are allegorized with the numerical results computed by state-of-the-art techniques. The graphical and statistical illustration of indications of performance relative to the terms of absolute errors, mean absolute deviations, computational complexity, and mean square error validates that our results perfectly describe the real-life situation and can further be used for problems arising in chemical engineering.

Mechanical Properties of Rock Salt from the Kłodawa Salt Dome-A Statistical Analysis of Geomechanical Data.

Rock salt is a potential medium for underground storage of energy resources and radioactive substances due to its physical and mechanical properties, distinguishing it from other rock media. Designing storage facilities that ensure stability, tightness, and safety requires understanding the geomechanical properties of rock salt. Despite numerous research efforts on the behaviour of rock salt mass, many cases still show unfavourable phenomena occurring within it. Therefore, the formulation of strength criteria in a three-dimensional stress state and the prediction of deformation processes significantly impact the functionality of storage in salt caverns. This article presents rock salt's mechanical properties from the Kłodawa salt dome and a statistical analysis of the determined geomechanical data. The analysis is divided into individual mining fields (Fields 1-6). The analysis of numerical parameter values obtained in uniaxial compression tests for rock salt from mining Fields 1-6 indicates an average variation in their strength and deformation properties. Upon comparing the results of Young's modulus (E) with uniaxial compressive strength (UCS), its value was observed with a decrease in uniaxial compressive strength (E = 4.19968·UCS2, R-square = -0.61). The tensile strength of rock salt from mining Fields 1-6 also exhibits moderate variability. An increasing trend in tensile strength was observed with increased bulk density (σt = 0.0027697·ρ - 4.5892, r = 0.60). However, the results of triaxial tests indicated that within the entire range of normal stresses, the process of increasing maximum shear stresses occurs linearly ((σ1 - σ3)/2 = ((σ1 + σ3)/2)·0.610676 + 2.28335, r = 0.92). A linear relationship was also obtained for failure stresses as a function of radial stresses (σ1 = σ3·2.51861 + 32.9488, r = 0.73). Based on the results, the most homogeneous rock salt was from Field 2 and Field 6, while the most variable rock salt was from Field 3.

Theory of consumption value: A lens to examine the use and continual use intention of online game subscription services

Using the theory of consumption value as the theoretical framework and online game subscription as the subject, this study considered the antecedents (game motivations, fear of missing out [FoMO], and variety preference) and consequences (use and continual use intention) of the values (playing games, social, enjoyment, price, and quality) offered by subscription services. Using the partial least squares method, an empirical analysis of 412 subscribers' and 265 non-subscribers’ views at the online game subscription service level revealed the limited consequences of game motivations for the use (continual use) of online game subscription services. Perceiving FoMO as a bidimensional construct (losing-out and interactive aspects) could provide more insights into how online game players perceive subscription services. FoMO's (interactive aspect) contribution to value is more evident among non-subscribers than subscribers. For both subscribers and non-subscribers, variety preference positively contributes to numerous value types. Three value types (playing games, enjoyment, and price) contribute to the use (continual use) intention. This study augments the rather limited subscription retail literature by focusing on online game subscription services. By viewing FoMO as bidimensional instead of the usual unidimensional construct, this study found that these two FoMO types behaved differently. Moreover, this study showed that studies at the game level cannot be applied to the subscription level in a lock, stock, and barrel manner.

A quantitative image analysis platform for assessing trophoblast differentiation

Immunofluorescence microscopy is extensively used in characterization of trophoblast differentiation in vitro. However, such data is primarily used to confirm the presence of protein markers or qualitatively compare levels of protein markers across experimental conditions. Imaging data, when processed and analyzed appropriately can provide quantitative and spatial information, and provide biological insight. Towards this end, here we present MATroph, an open-source MATLAB-based computational tool to process images generated by immunofluorescent microscopy. MATroph automatically executes a series of image processing operations, including the classification of red, blue, and green channels from images, background extraction, morphological operations, and image filtering. From the isolated blue channels corresponding to nuclear staining, this tool generates numerical values for cell number. Additionally, relative levels and spatial location of proteins are obtained by mapping red and green channel pixels to blue pixels by assigning minimum pixel distance between the blue and other color objects. Thus, this tool provides information about intracellular protein accumulation areas. Additionally, this tool can also classify cells as single cells or part of colonies, and extract information on protein levels for each; this is particularly useful for quantitative studies on extravillous trophoblast maturation. We provide a user-guide to analyze the relative levels of markers relevant to human trophoblast stem cell self-renewal and differentiation. Importantly, MATroph is composed of a simple MATLAB algorithm, and its implementation requires minimal expertise in programming.

Analysis of an initially stressed functionally graded thermoelastic medium (type III) without energy dissipation

AbstractThe current investigation deals with the deformation of a non-homogeneous thermoelastic half space under hydrostatic initial stress for the Green–Naghdi model III. The medium is supposed to be rotating with a constant angular velocity. The non-homogeneous properties of the material are along the x-direction. At the first instance, the problem has been solved analytically to obtain stress and displacement components. Further, the numerical values of these expressions are evaluated using a computer program for a particular medium. The numerical values obtained are then presented graphically to show the effect of initial stress parameter and non-homogeneity parameter on the quantities.

Technological aspects and requirements to raw materials for increasing the nutritional value of glaze

Glaze, giving confectionery products an aesthetically attractive appearance, provides the possibility of prolonging their shelf life. The main raw components of the glaze are sugar and fat, which determines its high caloric content. Modern trends dictate the need to create confectionery products enriched with essential nutrients found in vegetables, berries and fruits. The introduction of finely ground additives in the form of fruit and vegetable powder into the glaze formulation may entail changes in the rheological and crystallization properties of the glaze. The aim of the research is to develop technological methods of fruit and vegetable confectionery glaze production with increased content of dietary fibers and reduced amount of added sugar, as well as to establish requirements for fruit and vegetable powders as raw materials used in the production of confectionery glaze. The objects of the research were industrial samples of fruit and vegetable powders from raspberry, apple, carrot and beet, as well as samples of confectionery glaze produced in laboratory conditions. Common and special research methods were used in the work. The technological acceptability of using fruit and vegetable powders in the production of confectionery glaze according to their physical and chemical parameters has been determined. The yield stress of the glaze increased as the content of fruit and vegetable powder increased from 3 to 15% to varying degrees depending on its fat-absorbing capacity. The crystallization characteristic of the glaze changed: the solidification temperature decreased by 1-2 °C, the crystallization duration increased by 27-40% compared to the control sample. The nomenclature is substantiated and numerical values of quality criteria of fruit and vegetable powders to ensure technological properties of glaze are given. The influence of step-by-step introduction of surfactants on the value of yield stress of confectionery glazes with fruit and vegetable powders is shown. The technology of fruit and vegetable confectionery glaze with a high content of dietary fiber (9 g/100 g) and with a reduced amount of added sugar has been developed.

An efficient learning based approach for automatic record deduplication with benchmark datasets

With technological innovations, enterprises in the real world are managing every iota of data as it can be mined to derive business intelligence (BI). However, when data comes from multiple sources, it may result in duplicate records. As data is given paramount importance, it is also significant to eliminate duplicate entities towards data integration, performance and resource optimization. To realize reliable systems for record deduplication, late, deep learning could offer exciting provisions with a learning-based approach. Deep ER is one of the deep learning-based methods used recently for dealing with the elimination of duplicates in structured data. Using it as a reference model, in this paper, we propose a framework known as Enhanced Deep Learning-based Record Deduplication (EDL-RD) for improving performance further. Towards this end, we exploited a variant of Long Short Term Memory (LSTM) along with various attribute compositions, similarity metrics, and numerical and null value resolution. We proposed an algorithm known as Efficient Learning based Record Deduplication (ELbRD). The algorithm extends the reference model with the aforementioned enhancements. An empirical study has revealed that the proposed framework with extensions outperforms existing methods.