Analytical Behavior Research Articles

Axially loaded square concrete-filled steel tubular long columns made of high-strength materials: Experimental investigation, analytical behavior and design

To explore the structural performance of axially loaded high-strength concrete-filled square steel tubular (HCFSST) long columns, a total of nine HCFSST specimens with various slenderness ratio (λ) values were experimentally tested and the working mechanism of the column was numerically revealed in this work. Parametric studies were also conducted to explore the column stability behavior, material strength matching relationship, and internal load distribution of each material. Combined with test results, various buckling curves (a0, a, b, c, and d) specified in code EC3 were reviewed to confirm an appropriate design curve for HCFSST columns. Furthermore, the predictions of the stability reduction factors and peak-loads of columns based on current design codes were compared and discussed. The results indicated that the failure modes of the columns were significantly affected by the λ values. To efficiently improve the load bearing performance of the column, the recommended value of fy/fcu ratio is within 6.57–7.00 as λ = 14–37 and is within 5.75–6.57 as λ > 37. The new design models of the axially loaded columns proposed in this work are applicable to the HCFSST columns and hence are recommended. This study will provide guidance for the engineering practice of HCFSST columns.

Analytical behavior of soliton solutions to the couple type fractional-order nonlinear evolution equations utilizing a novel technique

Shallow water waves are one of the most prominent and widely used waves in coastal areas. The anomalous bi-directional transmission of long waves over shallow water is described by the nonlinear fractional partial differential equations (NLFPDEs), namely space-time-fractional coupled Whitham-Broer-Kaup (WBK) and coupled approximate long water (ALW) wave equations. To achieve new analytical solutions, the enhanced extended tanh-function technique for the mentioned fractional equations in the sense of conformable derivative is used. Some well-known wave shapes of solitons, namely, kink, bell-shape, and other types, through the suggested technique are achieved, and the 3D, contour, list point plots, and vector plots of the solutions are sketched to further illustrate the wave profile. The results achieved in this study have been validated using the computational software Maple and found to be accurate. It is observed that the method is realistic, and dependable to investigate more generalized analytical wave solutions.

Twenty years of investigation with the case of prosopagnosia PS to understand human face identity recognition. Part I: Function

Following traumatic brain injury in adulthood, Pierrette Sapey (PS) became suddenly unable to recognize the identity of people from their faces. Thanks to her remarkable recovery of general brain function, liveliness, and willingness to be tested, PS's case of prosopagnosia has been extensively studied for more than 20 years. This investigation includes hundreds of hours of behavioral data collection that provide information about the nature of human face identity recognition (FIR). Here a theory-driven extensive review of behavioral and eye movement recording studies performed with PS is presented (part I). The specificity of PS's recognition disorder to the category of faces, i.e., with preserved visual object (identity) recognition, is emphasized, arguing that isolating this impairment is necessary to define prosopagnosia, offering a unique window to understand the nature of human FIR. Studies performed with both unfamiliar and experimentally or naturally familiar faces show that PS, while being able to perceive both detailed diagnostic facial parts and a coarse global facial shape, can no longer build a relatively fine-grained holistic visual representation of a face, preventing its efficient individuation. Her mandatory part-by-part analytic behavior during FIR causes increased difficulties at extracting diagnostic cues from the crowded eye region of the face, but also from relative distances between facial parts and from 3D shape more than from surface cues. PS's impairment is interpreted here for the first time in terms of defective (access to) cortical memories of faces following brain damage, causing her impaired holistic perception of face individuality. Implications for revising standard neurofunctional models of human face recognition and evaluation of this function in neurotypical individuals are derived.

Novel Analysis of Fuzzy Fractional Emden-Fowler Equations within New Iterative Transform Method

The analytical behavior of fractional differential equations is often puzzling and difficult to predict under uncertainty. It is crucial to develop a robust, extensive, and extremely successful theory to address these problems. An application of fuzzy fractional differential equations can be found in applied mathematics and engineering. Using the iterative transform technique, the study determines the analytic solution of fractional fuzzy Emden-Fowler equation in the sense of the Caputo operator, which is applied to evaluate the physical model range in several scientific and engineering disciplines. The derived solutions to the fractional fuzzy Emden-Fowler equations are more generic and applicable to a broader range of problems. Through the translation of fractional fuzzy differential equations into equivalent crisp systems of fractional differential equations, we obtain a parametric description of the solutions. The graphical and numerical representation demonstrates the symmetry among the upper and lower fuzzy solution representations in their simplest form, which may aid in the comprehension of artificial intelligence, control system models, computer science, image processing, quantum optics, medical science, physics, measure theory, stochastic optimization theory, biology, mathematical finance, and other domains, as well as nonfinancial evaluation.

Copper nanostructures anchored on renewable carbon as electrochemical platform for the detection of dopamine, fluoxetine and escitalopram

For the first time, renewable carbon (RC) from bamboo-biomass modified with copper nanoparticles (CuNPs) has been prepared via a chemical reduction step for the electroanalytical detection of dopamine (DOP), fluoxetine (FXT) and escitalopram (EST). The synthesized RCCuNPs nanocomposite morphology and structural composition were characterized by FEG-SEM along with EDS analysis. The electroanalytical behavior of the target analytes was investigated by cyclic voltammetry (CV) and differential pulse voltammetry (DPV). The analytical range of detection of DOP, FXT, and EST was 0.05–5.0, 0.1–10, and 0.02–5.0 µmol L−1, respectively. The limits of detection (LOD) were found to be 0.04, 0.05, and 0.25 µmol L−1, respectively. In addition, the standard addition method was used for the detection and recovery of DOP in synthetic human urine and EST in tap water samples. The synergistic effect of CuNPs coupled with the highly porous RC material provided a sensitive, low-cost, and easy to prepare sensing platform for detecting target analytes in clinical and environmental samples.

Pairing instabilities of the Yukawa-SYK models with controlled fermion incoherence

The interplay of non-Fermi liquid and superconductivity born out of strong dynamical interactions is at the heart of the physics of unconventional superconductivity. As a solvable platform of the strongly correlated superconductors, we study the pairing instabilities of the Yukawa-Sachdev-Ye-Kitaev (Yukawa-SYK) model, which describes spin-1/2 fermions coupled to bosons by the random, all-to-all, spin-independent and dependent Yukawa interactions. In contrast to the previously studied models, the random Yukawa couplings are sampled from a collection of Gaussian ensembles whose variances follow a continuous distribution rather than being fixed to a constant. By tuning the analytic behaviour of the distribution, we could control the fermion incoherence to systematically examine various normal states ranging from the Fermi liquid to non-Fermi liquids that are different from the conformal solution of the SYK model with a constant variance. Using the linearised Eliashberg theory, we show that the onset of the unconventional spin-triplet pairing is preferred with the spin-dependent interactions while all pairing channels show instabilities with the spin-independent interactions. Although the interactions shorten the lifetime of the fermions in the non-Fermi liquid, the same interactions also dress the bosons to strengthen the tendency to pair the incoherent fermions. As a consequence, the onset temperature T_cTc of the pairing is enhanced in the non-Fermi liquid compared to the case of the Fermi liquid.

Recent Progress in Graphene Derivatives/Metal Oxides Binary Nanocomposites Based Chemi-resistive Sensors for Disease Diagnosis by Breath Analysis

Background: The scientific and clinical interest of breath analysis for non-invasive disease diagnosis has been focused by the scientific community over the past decade. This was due to the exhalation of prominent volatile organic compounds (VOCs) corresponding to the metabolic activities in the body and their concentration variation. To identify these biomarkers, various analytical techniques have been used in the past and the threshold concentration was established between a healthy and diseased state. Subsequently, various nanomaterials-based gas sensors were explored for their demand in quantifying these biomarkers for real-time, low cost and portable breathalyzers along with the essential sensor performances. Methods: We focus on the classification of graphene derivatives and their composites’ gas sensing efficiency for the application in the development of breathalyzers. The review begins with the feasibility of the application of nanomaterial gas sensors for healthcare applications. Then, we systematically report the gas sensing performance of various graphene derivatives/semiconductor metal oxides (SMO) binary nanocomposites and their optimizing strategies in selective detection of biomarkers specific to diseases. Finally, we provide insights on the challenges, opportunity and future research directions for the development of breathalyzers using other graphene derivatives/SMO binary nanocomposites. Results: On the basis of these analyses, graphene and its derivatives/metal oxides based binary nanocomposites have been a choice for gas sensing material owing to their high electrical conductivity and extraordinary thickness-dependent physicochemical properties. Moreover, the presence of oxygen vacancies in SMO does not only alter the conductivity but also accelerates the carrier transport rate and influence the adsorption behavior of target analyte on the sensing materials. Hence researchers are exploring the search of ultrathin graphene and metal oxide counterpart for high sensing performances. Conclusion: Their impressive properties compared to their bulk counterpart have been uncovered towards sensitive and selective detection of biomarkers for its use in portable breathalyzers.

Analytical Hysteretic Behavior of Square Concrete-Filled Steel Tube Pier Columns under Alternate Sulfate Corrosion and Freeze-Thaw Cycles.

The hysteretic behavior of square concrete-filled steel tube (CFST) stub columns subjected to sulfate corrosion and freeze-thaw cycle is examined by numerical investigation. The constitutive model of steel considered the Bauschinger effect, and compression (tension) damage coefficient was also adopted for the constitutive model of core concrete. The experimental results are used to verify the finite element (FE) model, which could accurately predict the hysteretic behaviors of the CFST piers. Then, the effects of the yield strength of steel, compressive strength of concrete, steel ratio, axial compression ratio, and alternation time on ultimate horizontal load are evaluated by a parametric study. The results showed that the yield strength of steel and the steel ratio have a positive effect of hysteretic behavior. The compressive strength of concrete and alternation time significantly decreased the unloading stiffness which causes the pinching phenomenon. The yield strength of steel, compressive strength of concrete, and alternation time of environmental factors (corrosion-freeze-thaw cycles) has no obvious effect on the initial stiffness, while the steel ratio has a remarkable effect. The ultimate horizontal load increases with the increasing steel ratio, yield strength of steel and compressive strength of concrete. Meanwhile, the decrement of alternation time led to the increase of ultimate horizontal load. This suggests that the confinement coefficient and alternation time are the two main factors that impact the ultimate horizontal load. A formula which considers the reduction coefficient for the ultimate horizontal load of the CFST columns subjected to sulfate corrosion and freeze-thaw cycles is proposed. The formulae can accurately predict the ultimate horizontal load with mean value of 1.022 and standard deviation of 0.003.

Efficiency Analytical Characterization for Brushless Electric Drives

The paper is focused on the formalization of an experimental procedure aimed to characterize the efficiency behaviour of a Permanent Magnet Synchronous Motor-based drive. The characterization is intended to expose the analytical behaviour of the system efficiency by the actual operating condition assigned through torque/speed value. The availability of such a relation in a simple analytical form would allow for real-time adjustment by advanced power management strategies to maximize the whole system efficiency. The proposed method is based on a defined set of measures corresponding to several drive operating conditions. A straightforward elaboration procedure is then formulated with the aim to quantify the different parameters, which intervene in the efficiency characterization. The method has been applied on a 155 kW drive. The results show that good accuracy is achieved while keeping the analytical approach relatively simple.

Application of MnO2 Nanorod–Ionic Liquid Modified Carbon Paste Electrode for the Voltammetric Determination of Sulfanilamide

The current work introduced a convenient single-phase hydrothermal protocol to fabricate MnO2 nanorods (MnO2 NRs). Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), Energy-dispersive X-ray spectroscopy (EDX) and field-emission scanning electron microscopy (FE-SEM) were used to determine the characteristics of MnO2 NR. Then, ionic liquid (IL) and MnO2 NRs were utilized to modify a carbon paste electrode (CPE) surface (MnO2NR-IL/CPE) to voltammetrically sense the sulfanilamide (SAA). An enhanced voltammetric sensitivity was found for the as-developed modified electrode toward SAA when compared with a bare electrode. The optimization experiments were designed to achieve the best analytical behavior of the SAA sensor. Differential pulse voltammetry (DPV) in the optimized circumstances portrayed a linear dependence on various SAA levels (between 0.07 and 100.0 μM), possessing a narrow detection limit (0.01 μM). The ability of the modified electrode to be used in sensor applications was verified in the determination of SAA present in the actual urine and water specimens, with impressive recovery outcomes.

Non-perturbative thermal QCD at all temperatures: the case of mesonic screening masses

We present a strategy based on the step-scaling technique to study non-perturbatively thermal QCD up to very high temperatures. As a first concrete application, we compute the flavour non-singlet meson screening masses at 12 temperatures covering the range from T ∼ 1 GeV up to ∼ 160 GeV in the theory with three massless quarks. The calculation is carried out by Monte Carlo simulations on the lattice by considering large spatial extensions in order to have negligible finite volume effects. For each temperature we have simulated 3 or 4 values of the lattice spacing, so as to perform the continuum limit extrapolation with confidence at a few permille accuracy. Chiral symmetry restoration manifests itself in our results through the degeneracy of the vector and the axial vector channels and of the scalar and the pseudoscalar ones. In the entire range of temperatures explored, the meson screening masses deviate from the free theory result, 2πT, by at most a few percent. These deviations, however, cannot be explained by the known leading term in the QCD coupling constant g up to the highest temperature, where other contributions are still very relevant. In particular the vector-pseudoscalar mass splitting turns out to be of O(g4) in the entire range explored, and it remains clearly visible up to the highest temperature, where the two screening masses are still significantly different within our numerical precision. The pattern of different contributions that we have found explains why it has been difficult in the past to match non-perturbative lattice results at T ∼ 1 GeV with the analytic behaviour at asymptotically high temperatures.

Statistical analysis of isocratic chromatographic data using Bayesian modeling.

Chromatographic retention times are usually modeled considering only one analyte at a time. However, it has certain limitations as no information is shared between the analytes, and consequently the model predictions poorly generalize to out-of-sample analytes. In this work, a publicly available dataset was used to illustrate the benefits of pooling the individual data and analyzing them simultaneously utilizing Bayesian hierarchical approach. Statistical analysis was carried out using the Stan program coupled with R, which enables full Bayesian inference with Markov chain Monte Carlo sampling. This methodology allows (i) incorporating prior knowledge about the likely values of model parameters, (ii) considering the between-analyte variability and the correlation between the model parameters, (iii) explaining the between-analyte variability by available predictors, and (iv) sharing information across the analytes. The latter is especially valuable when only limited information is available in the data about certain model parameters. The results are obtained in the form of posterior probability distribution, which quantifies uncertainty about the model parameters and predictions. Posterior probability is also directly relevant for decision-making. In this work, we used the Neue model to describe the relationship between retention factor and acetonitrile content in the mobile phase for 1026 analytes. The model was parametrized in terms of retention factor in 100% water, retention factor in 100% acetonitrile, and curvature coefficient, and considered log P and pKa as predictors. From this analysis, we discovered that the analytes formed two clusters with different retention depending on the degree of analyte dissociation. The final model turned out to be well calibrated with the data. It gives insight into the behavior of analytes in the chromatographic column and can be used to make predictions for a structurally diverse set of analytes if their log P and pKa values are known.

Quadratic Twists of Central Values For GL(3)

Abstract We prove that a cuspidal automorphic representation of $\mathrm{GL}(3)$ over any number field is determined by the quadratic twists of its central value. In the case π is not a Gelbart–Jacquet lift, the result is conditional on the analytic behavior of a certain Euler product. We deduce the nonvanishing of infinitely many quadratic twists of central values. This generalizes a result of Chinta and Diaconu that was valid only over Q and explored only for Gelbart–Jacquet lifts.

Pólya–Carlson dichotomy for coincidence Reidemeister zeta functions via profinite completions

We consider coincidence Reidemeister zeta functions for tame endomorphism pairs of nilpotent groups of finite rank, shedding new light on the subject by means of profinite completion techniques.In particular, we provide a closed formula for coincidence Reidemeister numbers for iterations of endomorphism pairs of torsion-free nilpotent groups of finite rank, based on a weak commutativity condition, which derives from simultaneous triangularisability on abelian sections. Furthermore, we present results in support of a Pólya–Carlson dichotomy between rationality and a natural boundary for the analytic behaviour of the zeta functions in question.

Ratiometric immunosensor with DNA tetrahedron nanostructure as high-performance carrier of reference signal and its applications in selective phoxim determination for vegetables

A ratiometric electrochemical immunosensor, based on DNA tetrahedron nanostructure (DTNS), is introduced for vegetable phoxim determination. DTNS spontaneously adheres onto gold-nanoparticle-modified electrode and forms stable three-dimensional structure, providing plenty of binding sites to the built-in reference, methylene blue (MB). Monoclonal antibody (m-Ab) is vertically linked onto DTNS vertex, selectively responses antigenic phoxim, and promotes the target signal of IPHO. Thus, a ratiometric indicator, IPHO/IMB, is sensibly established with the target signal (IPHO) and the reference signal (IMB). Modifications, mechanisms and advances of the proposed method are subsequently examined with morphological methods and electrochemical experiments. This method brings considerable advances in analytical behaviors. The ratiometric signal presents better performance than solo system in repeatability and long-time stability. As-fabricated sensor presents wide dynamic range as 0.1∼30 μg/L, and limit of detection is well defined as 0.003 μg/L (S/N = 3). Finally, this method is verified with real-vegetable-sample analysis, certified HPLC and recovery test.

Coupling of chiral and achiral stationary phases in supercritical fluid chromatography: Evaluating and improving retention prediction

Isomers and stereoisomers are always challenging to separate. Column coupling may provide improved chromatographic selectivity, necessary for the separation of the compounds with similar chemical and structural properties. The relatively low viscosity of supercritical fluids, used as mobile phases allows for the coupling of several columns in series in supercritical fluid chromatography (SFC), without exceeding the pressure limits of the system. The aim of this study is to propose reliable prediction of the retention behaviour of analytes on a coupled column system, based on a limited number of initial analyses. The chiral compounds atenolol, ephedrine, propranolol, mianserin, labetalol and nadolol, besides the diastereomers quinine and quinidine, and the structural isomers of aminophenol and aminocresol were used as model analytes. The retention behaviour of the analytes was determined on the individual chiral columns Lux Cellulose-1, Lux Cellulose-2, Lux Cellulose-3, Lux Cellulose-4, Lux Amylose-2 and the achiral columns Luna NH2, Luna Silica, Synergi RP and FluoroSep RP. The mobile phase was composed of CO2 mixed with 20% (v/v) MeOH, which contained 0.1% (v/v) trifluoroacetic acid and 0.1% (v/v) isopropylamine. The retention factors of the analytes on coupled stationary phases were predicted, and subsequently compared to the experimentally obtained ones. Relative deviations of predicted and experimental retention factors were in range from 0.00% to 51.91%. Flow rate and back pressure of the screening conditions were adjusted to improve prediction precision on four column combinations, with varying success rates. The average relative deviations of retention factors were reduced to 2.84% - 6.59% by adjusting flow rate, and to 2.30% - 8.57% by adjusting back pressure. The most successful approach, flow rate adjustment, was then applied to select a column combination providing improved resolution of the structurally similar components of silymarin extract.

An innovative electrically conductive biopolymer based on poly(β‐cyclodextrin) towards recognition of ascorbic acid in real sample: Utilization of biocompatible advanced materials in biomedical analysis

In this study, a sensitive platform was designed for the electrocatalytical oxidation and recognition of ascorbic acid (AA) based on poly(β-cyclodextrin) modified glassy carbon electrode (p(β-CD-GCE). Electropolymerization of β-CD on the surface of GCE was performed on the potential range of -1 to 1.5V. So, a novel biopolymer was prepared on the surface of GCE towards sensitive recognition of AA in human plasma samples. The developed platform has good sensitivity and accuracy for electrooxidation and detection of AA with lower limit of quantification (LLOQ) of 1nM and linear range of 1nM to 100 mM. Moreover, the designed electrochemical sensor was employed for the analysis of AA on human plasma samples with high sensitivity. Based on advantages of p(β-CD) prepared by electropolymerization procedure (green, fast, homogeny, and efficient eletrocatalytical behaviour), this conductive biopolymer showed excellent analytical behaviour towards electrooxidation of AA. It is expected that the prepared polymeric interface is able to use in the analysis of biological species in clinical samples.

Forecasting extreme events in collective dynamics: An analytic signal approach to detecting discrete scale invariance

A challenging problem in physics concerns the possibility of forecasting rare but extreme phenomena such as large earthquakes, financial market crashes and material rupture. A promising line of research involves the early detection of precursory log-periodic oscillations to help forecast extreme events in collective phenomena where discrete scale invariance plays an important role. Here we investigate two distinct approaches towards the general problem of how to detect log-periodic oscillations in arbitrary time series without prior knowledge of the location of the moveable singularity. We first show that the problem has a definite solution in Fourier space; however, the technique involved requires an unrealistically large signal-to-noise ratio. Then we show that the quadrature signal obtained via analytic continuation onto the imaginary axis, using the Hilbert transform, necessarily retains the log-periodicities found in the original signal. This finding allows the development of a new method of detecting log-periodic oscillations that relies on calculation of the instantaneous phase of the analytic signal. We then illustrate the method by applying it to the stock market crash of 1987 and explore the important role played by positive feedback mechanisms in relation to economic bubble formation, financial crashes, log-periodic dynamics and analytic behavior. Finally, we discuss the relevance of these findings for parametric rather than nonparametric estimation of critical times.

Lumos: Increasing Awareness of Analytic Behavior during Visual Data Analysis.

Visual data analysis tools provide people with the agency and flexibility to explore data using a variety of interactive functionalities. However, this flexibility may introduce potential consequences in situations where users unknowingly overemphasize or underemphasize specific subsets of the data or attribute space they are analyzing. For example, users may overemphasize specific attributes and/or their values (e.g., Gender is always encoded on the X axis), underemphasize others (e.g., Religion is never encoded), ignore a subset of the data (e.g., older people are filtered out), etc. In response, we present Lumos, a visual data analysis tool that captures and shows the interaction history with data to increase awareness of such analytic behaviors. Using in-situ (at the place of interaction) and ex-situ (in an external view) visualization techniques, Lumos provides real-time feedback to users for them to reflect on their activities. For example, Lumos highlights datapoints that have been previously examined in the same visualization (in-situ) and also overlays them on the underlying data distribution (i.e., baseline distribution) in a separate visualization (ex-situ). Through a user study with 24 participants, we investigate how Lumos helps users' data exploration and decision-making processes. We found that Lumos increases users' awareness of visual data analysis practices in real-time, promoting reflection upon and acknowledgement of their intentions and potentially influencing subsequent interactions.

Retracted] The Mathematical Analysis of the New Fractional Order Ebola Model

This research study focuses on the analytical behavior and numerical computation of the fractional order Ebola model. In this study we have calculated the conditions for the existence, uniqueness, and stability of the solution with the help of the fixed point results. In addition to this, we calculated the numerical solution of the fractional order smoke model with the help two‐step fractional Adam’s Bashforth method using the Caputo’s fractional derivative of order μ. Furthermore, the results obtained for different orders of the fractional derivative μ have been shown graphically with the help of Matlab.