Analytical Results Research Articles

Ultrahigh-contrast plasmonic mode conversion in coupled graphene waveguides by manipulating the graphene chemical potential and the gyration

We investigate ultrahigh-contrast plasmonic mode conversion in a coupled graphene waveguide structure with manipulated gyration and graphene chemical potential by using both analytic theory and numeric simulations. The ultrahigh contrast is supported by a magnetic resonance at the expense of high sensitivity on the design and material parameters and the operation frequency. The analytical study reveals that the ultrahigh contrast mode conversion can be preserved by adjusting the gyration and the chemical potential in the deviation of structural and material parameter values due to imperfect fabrication and harsh environment and for tuning its operation frequency over a broadband frequency range. We derive explicit analytical results for the resonance gyration and chemical potential that answer to those questions how to manipulate the gyration and the chemical potential according to the design and material parameters and the operation frequency. Numerical simulations demonstrate the robust and broadband tunable plasmonic mode conversion preserves the contrast higher than 103 (99.9%) for different design and material parameter values over a one-octave-spanning broadband frequency range. In practice, the chemical potential and the gyration can be manipulated by controlling the gate voltage of the graphene and the external magnetic field, respectively. Our findings can be of great importance in the design of high-integration nanophotonic circuits and for probing of ultrafast magnetization dynamics. Published by the American Physical Society 2024

Analysis of Fracturing Above Block Caving Back: A Spherical Shell Theory Approach and BEM Numerical Simulation

ABSTRACTExperiments and field monitoring have revealed that in block caving, fractures over the cave crown tend to form in narrow curved bands that are parallel or subparallel to the cave back surface. These fractures delineate curved shells of orebody between the bands and the cave back. The effectiveness of block caving hinges on the subsequent fracturing and fragmentation of these orebody shells. This study adopts a dual approach, combining thin spherical shell theory and full 3D numerical simulations along with principles of linear elastic fracture mechanics, to investigate the fracturing behaviour of these shells. Analytical analysis indicates that under axisymmetric loading, latitudinal tensile fractures predominantly initiate across the most part of the shell, occurring on both the upper and lower surfaces, except at a localised area. Additionally, longitudinal tensile fractures may initiate at the central area of the upper surface, while shear fractures tend to occur around the edge of the shell. Consequently, the shells become susceptible to fracturing, leading to the collapse or cave‐in of the orebody. Numerical simulations agree with these findings, illustrating that fracturing points within the shell region are longitudinally dispersed throughout the entire shell. Most of these fracturing points satisfy the criteria for tensile fracturing, particularly within the middle portion of the shell, aligning with the analytical results. Furthermore, simulations considering nonaxisymmetric loading patterns demonstrate that regions surrounding the caving cavity, aligned with the minimum principal in situ stress, exhibit heightened susceptibility to fracture initiation. This insight holds potential significance for optimising the design of the caving process.

On buckling of compact I-section beams subjected to biaxial bending

This paper aims at providing a new insight into the lateral-torsional buckling behavior of compact I-section steel beams subjected to biaxial bending, without axial force, a subject seldom treated in the literature. This investigation is based on both analytical and numerical results, the latter obtained using a two-node geometrically exact beam finite element developed by one of the authors (Gonçalves, 2019), which has all the required features. Several geometrically non-linear analysis (GNA) types are used to characterize the buckling behavior, namely with geometric imperfections (GNIA), with material non-linearity (GMNA) and combining material non-linearity and imperfections (GMNIA). Different boundary conditions along the two principal planes are allowed and particular attention is paid to cases which involve the same first-order bending moment diagrams but different support schemes. As a consequence, it is shown that the buckling behavior depends not only on the slenderness and the first-order moment diagrams, but also on the supports. On the basis of results obtained concerning the application of the Eurocode 3 provisions for different support conditions, it is shown that unsafe results can be obtained but may be resolved using the recommendations presented in the paper.

Comprehensive evaluation of cocaine and its hydroxy metabolites in seized cocaine and a large cohort of hair samples.

As cocaine (COC) is not only incorporated into hair via blood following ingestion but also by external contamination, hair samples are commonly tested for COC metabolites to prove ingestion. However, COC metabolites can also be present as degradation products in typical street COC samples. The present study investigates minor hydroxycocaine (OH-COC) metabolites p- and m-OH-COC together with p- and m-hydroxybenzoylecgonine (OH-BE) in seized COC (n = 200) and hair samples from routine case work (n = 2389). Analytical results of hair samples were interpreted using an established decision model for the differentiation between actual use and external contamination using metabolic ratios (metabolite to COC). They were further examined concerning background of request, hair color, body site of sample collection, sex, and metabolic ratios of the main metabolites [benzoylecgonine (BE), norcocaine (NC), and cocaethylene (CE)]. All seized COC samples were positive for p- and m-OH-COC with a maximum percentage of 0.025% and 0.052%, respectively; p- and m-OH-BE were detected in 55% and 56% of samples with a maximum percentage of 0.044% and 0.024%, respectively. Analytical results of 424 hair samples (17.7%) were interpreted as being predominantly from contamination; the majority of these samples were from traffic medicine cases (83.7%). Metabolic ratios of minor OH-COC metabolites were significantly higher in hair samples interpreted as originating from use than in samples interpreted as caused by contamination. Metabolic ratios for OH-COCs were significantly higher in forensic cases compared to abstinence controls and also in black hair compared to blond/gray hair. However, this was not the case for OH-BE metabolic ratios. No statistical difference was observed with regard to the donor's sex. OH-COC metabolic ratios increased significantly with increasing ratios of NC and CE to COC, respectively. The study demonstrates that OH-COC metabolites (including thresholds for their metabolic ratios) must be used for a reliable interpretation of positive COC results in hair samples.

Pathways into Computing Fields by Florida’s Community College Students: An Intersectional Descriptive Analysis

ABSTRACT While it is well understood that gender and racial stratification in computing fields continues to exist, we too often approach this workforce problem from a deficit perspective and look to typical sites (where status quo norms are reproduced) to investigate potential solutions. Using an intersectional descriptive analysis on state administrative data on Florida state colleges, we prioritize centering the academic journeys of Asian, Black, Indigenous, Latina/e/o/x, and Multiracial community college women and men, addressing the often-overlooked effects of holding multiple marginalized identities in quantitative research. Analytic results from this study suggest that women of color completed high school computing courses significantly less often than men. Further, our findings reveal that these disparities in high school computing coursetaking were even greater among those who enrolled in Advanced Placement Computer Science. Employing an intersectional approach enabled this study to dive into these and other nuanced effects. Implications offer directions for future research, practice, and policy that may enhance efforts to broaden participation in computing in high school and among community college students.

On the Quasi-diagonalization and Uncoupling of Gyroscopic Circulatory Multi-degree-of-freedom Systems

Abstract A new central result that gives the necessary and sufficient conditions for two n by n skew-symmetric matrices and one symmetric matrix to be simultaneously quasi-diagonalized by a real orthogonal congruence is proved. Based on this result, the decomposition of linear multi-degree-of-freedom dynamical systems with gyroscopic, circulatory, and potential forces is investigated through a real linear coordinate transformation generated by an orthogonal matrix. Several sets of conditions, applicable to real-life structural and mechanical systems arising in aerospace, civil, and mechanical engineering, under which such a coordinate transformation exists are found, thereby allowing these systems to be decomposed into independent, uncoupled subsystems, each with a maximum of two degrees of freedom. The conditions are expressed in terms of the coefficient matrices of the system. A specific form for the circulatory (gyroscopic) matrix is posited, and when the gyroscopic (circulatory) matrix is simple—a situation that commonly appears in real-life applications—it is shown that just a single necessary and sufficient condition is required for the decomposition of the multi-degree-of-freedom system. Numerical examples are provided throughout to demonstrate the analytical results.

A composite film of oxidized levan crosslinked with gelatin: strong hydrophobic and mechanical properties and effective preservation of fresh Mozzarella cheese.

The fructosan levan was synthesized in vitro using a recombinant levansucrase. The levan was oxidized with sodium periodate to prepare oxidized levan (OLevan) with three oxidation degrees. OLevan, gelatin (Gel), and gallic acid (GA) were used to prepare the composite films by the method of plate pouring. The analytical results of FT-IR and XPS indicated that OLevan and gelatin were covalently crosslinked through a Schiff base reaction. The crosslinked films had better properties compared to the non-crosslinked films, especially the Gel/GA/50%OLevan film. The film had the lowest swelling degree (44.4 %), while that of Gel/GA/Levan film was 352.6 %. Gel/GA/50%OLevan film also had the highest tensile strength (25.48 MPa), while that of Gel/GA film was 9.48 MPa. Also, Gel/GA/50%OLevan film was used as a packaging material of Mozzarella cheese. The film effectively slowed down changes in the texture and color of the cheese. On the first day, the coliform in the control and PE groups had already exceeded the maximum acceptable limit of cheese (2.0 Log CFU/g). However, that of Gel/GA/50%OLevan group reached the limit on the fifth day. The results show that the new film prepared by crosslinking and composite of natural edible materials has good potential as a safe food packaging material.

Tacit Knowledge Mapping for Business Intelligence Analysis

The tacit knowledge in a higher institution, especially in university libraries, contains a series of intuition and inspiration that a librarian arises in exploring solutions to the various problems. Thus, limited sources of knowledge or information is a critical factor in the failure to provide accurate information. The main problem of the BI system is to capture tacit knowledge and use tacit knowledge as one of the data sources for data analysis to enhance the analytic results. The unstructured data can define as tacit knowledge in the form of data and information presented in the Knowledge Management System (KMS), and the cognitive business use both structured and unstructured data with highly sophisticated analytical techniques to identify, evaluate, and recommend a business plan of actions. The idea of being able to capture knowledge from different sources can be very beneficial to the BI system. This paper explored the solution to extracting tacit knowledge from librarians in order to enhance the data sources to be used in the BI by exploring the library's academic services, which use much tacit knowledge for answering questions with the requirement of data analysis as online or offline queries.

Exact Time-Dependent Thermodynamic Relationships for a Brownian Particle Navigating Complex Networks

The thermodynamic characteristics of systems driven out of equilibrium are examined for M Brownian ratchets organized in a complex network. The precise time-dependent solution reveals that the entropy S, entropy production ep(t), and entropy extraction hd(t) of the system in complex networks increase with system size, which is plausible as these thermodynamic quantities display extensive properties. In other words, as the number of lattice sites increases, the entropy S, entropy production ep(t), and entropy extraction hd(t) increase, demonstrating that these complex networks cannot be reduced to the corresponding one-dimensional lattice. Conversely, the rates for thermodynamic quantities such as velocity V, entropy production rate e˙p(t), and entropy extraction rate h˙ d(t) become independent of the network size in the long-term limit. The exact analytic results also indicate that the free energy decreases with system size. The model system is further analyzed by incorporating heat transfer via kinetic energy. Since heat exchange via kinetic energy does affect the energy extraction rate, the heat dumped to the cold reservoirs also contributes to internal entropy production. Consequently, such systems exhibit a higher degree of irreversibility. The thermodynamic features of a system operating between hot and cold baths are also compared and contrasted with a system functioning in a heat bath where temperature varies linearly along the reaction coordinate. Regardless of the network arrangements, the entropy, entropy production, and extraction rates are significantly larger for the linearly varying temperature case than for a system operating between hot and cold baths.

Studying a cylindrical moving boundary problem in ductal carcinoma in situ

In this paper, a mathematical model of ductal carcinoma in situ (DCIS) is considered as a moving boundary problem in cylindrical coordinates. Using the front-fixing technique, first, we transform the problem into a nonlinear parabolic problem on a fixed domain, and then some essential properties of the solution, such as the uniqueness of the solution, are shown. A numerical approach based on the finite difference method is established for solving the fixed domain problem. The solvability of the proposed finite difference method is proved, and the stability and convergence of the numerical solution are shown. For a test case problem, analytical and numerical results are compared to demonstrate the ability and effectiveness of the numerical method.

Analysis of the Vibration Effect on the Trailing Edge Noise for Wind Turbine Applications

The noise emitted is a factor in determining the location for installing wind turbines. It can be a concern for people living near wind farms due to the nuisance and health problems caused by noise emissions. Therefore, noise estimation is one of the most relevant aspects of wind turbine design. Aerodynamic noise can be caused by air motion around the turbine blades. This can create a swooshing or whooshing sound as the blades pass through the air. Aerodynamic noise tends to be more prominent at higher wind speeds when the turbine is operating at full capacity. The trailing edge noise is the main source of wind turbine aerodynamic noise. In this work, semi-analytical solutions for modeling this effect are used. The Ffowcs Williams and Hawkings (FW-H) acoustic analogy is used to predict far-field noise generated by wind turbine blades moving in the air. The equations of the rotor–tower–nacelle structure are obtained by the classical finite element method for a typical onshore wind turbine to predict the blade vibration signal. This new formulation is applied to rotating sources and statistical analysis of broadband trailing edge noise. The novelty of this work is to model the acoustic–structure interaction between the wind flow and the blade structure vibration. In this context, the acoustic far-field pressure emissions are modified by source vibration. In this point, this work compares the acoustic pressure values from rigid and flexible sources. Once the relationship between acoustic emission and wind turbine structural vibration is determined, the potential application of this research is, for example, to provide valuable information about the health and integrity of the blades. Thus, the goal of this work is to predict the aerodynamic noise of a typical large wind turbine taking into account its structural behavior. Therefore, Formulation 1A is used to calculate the far-field noise radiated from the trailing edge of wind turbine blades in a low Mach number flow. The vibration effects are input variables to evaluate the intensity and acoustic pressure values. Some computational aspects are discussed and the numerical model is clarified. The acoustic predictions are validated with analytical results and experimental measurements that are available in the scientific literature. The numerical results of the FW-H acoustic analogy demonstrate that the aerodynamic noise value is predominantly low frequency in the sections closest to the source.

Implementation and Application of Cell-Based S-FEM Based on the Object-Oriented Programming Framework

The object-oriented programming is widely used in different fields of finite element analysis (FEA). The commonly used object-oriented codes were almost written by C++. Due to the inability to automatically manage memory and the lack of gigantic standard library and a third-party library for C++, building matrix classes are needed and a strong programming ability for program developers is also necessary. The conventional FEM method still has many disadvantages such as poor accuracy, hard stiffness matrix, mesh dependence and lack of upper bound solution. The smoothed FEM (S-FEM) method proposed by Liu et al. can efficiently overcome these disadvantages and is therefore widely used in FEA. In this work, the elastic-plastic CS-FEM method is extended and implemented using Python programming based on the framework proposed [H. Li and Y. Xiao, Implementation and numerical simulation on object-oriented elastic-plastic finite element method based on Python, J. Syst. Simul. 36(5) (2024) 1107–1117] The resulting object-oriented elastic-plastic CS-FEM framework is then applied to FEA of elastic-plastic mechanics problems. The correctness of the resulting framework and the high computational accuracy and good mesh adaptability of CS-FEM models have been verified by comparing the corresponding results with an analytical solution or ABAQUS results. The object-oriented elastic-plastic CS-FEM framework provides a more efficient and adaptable approach to FEA, and can also overcome many limitations of the conventional FEM method and C++ programming. The use of Python and the CS-FEM method offers improved computational accuracy, mesh adaptability and development efficiency, and this will make it a valuable tool for solving practical problems in mechanics and engineering.

The role of hydroponic solution of Ulva fasciata in modulating the antibiotic resistance of Vibrio alginolyticus.

This study aimed to ascertain the active substances in the hydroponic solution of Ulva (U.) fasciata (HSUF) and their effects on antibiotics resistance of pathogenic bacteria Vibrio alginolyticus (Va.) at environmental levels. Analytical results of HSUF by solid-phase extraction and gas chromatography-mass spectrometry showed that HSUF contained rich active substances and dominated by 2,4,6-tribromophenol, acetal, mono (2-ethylhexyl) phthalate and 2- (4-hydroxybenzene) ethanol, etc. Thereinto, 2,4,6-tribromophenol had the lowest minimal inhibitory concentrations (MICs) of 64-128μg mL-1 for Va. strains. The rich antibacterial substances of HSUF inhibited 47%-63% of isolated Va. strains. After 20 generations of subculture for Va. strains in three dilutes (1/2 (HT), 1/20 (MT) and 1/50 (LT)) of HSUF (20g L-1), the resistance to streptomycin of Va. S1 and Va. M3 changed from intermediate resistance ability to susceptible level. The large promotion of reactive oxygen species was observed in different HSUF levels, but the biofilm formation of Va. S1 did not changed significantly. Transcriptome sequencing of Va. S1 demonstrated that antibiotic resistance gene lpxA was down-regulated at different HSUF levels. Live U. fasciata excreted a variety of active secondary metabolites (SMs) in HSUF, which exhibited strong inhibitory effects on three isolated Va. strains. HSUF changed the antibiotic resistance of Va. Strain, especially at a higher HSUF concentrations.

Experimental and analytical assessment of the bending behaviour of floating inflated membrane beams

The study aims to study the bending and failure behaviour of the inflated membrane beams under floating conditions to support their application in floating platforms. Bending tests are conducted to assess the structural stiffness and ultimate bearing capacity of the beam with various diameters and inflated pressures. With the elastic modulus determined through four-point bending tests, a new analytical formula based on Winkler elastic foundation theory is then developed to predict the deflection of the beams. The results revealed that the beams initially undergo total submersion, followed by end turn-up and anti-arching deformation in the loaded section. The bearing capacity of the beams increases with the increase in internal pressure and diameter. Localised wrinkling is a typical failure mode at low internal pressures, while at high pressures, the failure mode shifts to boundary failure, characterised by submerging in water. The experimental and analytical results show quite good agreement, confirming the accuracy of the current analysis. Overall, this paper contributes to understanding the bending and failure behaviour of inflated membrane beams under floating conditions and supports the offshore structure safety design.

Unveiling the Composition of La Pajarita PVAc-Based Paints in Joan Miró’s Studio and in Three Artworks from the 1970s

In this study, we present the first characterisation of the polyvinyl acetate (PVAc) paints of commercial Spanish brand La Pajarita preserved in the studios of Joan Miró (1893–1983) in Mallorca, Spain. Investigation of several black and white paint samples using complementary analytical techniques (XRD, SEM–EDX, FTIR, and Py–GC–MS) allowed for the identification of pigments and binding media in studio materials, as well as in three artworks dating from the 1970s. Through comparative analysis, it was possible to find significant similarities between the composition of La Pajarita paints conserved in cans in the artist’s studio with black and white painted layers from three artworks by Miró. Miró’s use of La Pajarita paints is extensively documented in studio notes, photographs, and videos, and these paints are known to have been used by other significant Spanish artists. However, their composition has remained largely undiscovered until now. This research contributes to the knowledge of PVAc paints, providing evidence of their use by Joan Miró. The analytical results serve as a valuable reference for comparing and identifying these synthetic paints in other artworks, as well as aiding in attribution or dating studies. Furthermore, the study demonstrates the significance of materials found in artists’ studios as a fundamental resource for identifying the materials present in artworks.

End-To-End Latency of Cause-Effect Chains: A Tutorial

In many applications of cyber-physical systems, a sequence of tasks is necessary to perform a certain functionality. For example, from a sensor to an actuator, the first task reads the sensor value (cause), the second task processes the data, and the third task produces an output for the actuator (an effect is triggered). For such scenarios, the end-to-end timing properties (the so-called end-to-end latency) of the sequence of tasks (the so-called cause-effect chain) are of importance. This tutorial recaps different metrics for the end-to-end latency of cause-effect chains, and summarizes fundamental properties and existing analytical results in a systematic manner. To that end, this tutorial has a special focus on the reaction time (how fast can a reaction be in the worst case) and the data age (how old is the data source of an actuation in the worst case). The goal of this tutorial is to provide a systematic view of the fundamental end-to-end timing properties of cause-effect chains and offer an outlook of possible research directions in the near future. Furthermore, we extend the proof of one fundamental property in the literature to comply with the current state-of-the-art definition of end-to-end latencies.

Transition Path Dynamics of Non-Markovian Systems across a Rough Potential Barrier.

Transition paths refer to rare events in physics, chemistry, and biology where the molecules cross barriers separating stable molecular conformations. The conventional analysis of the transition path times employs a diffusive and memoryless transition over a smooth potential barrier. However, it is widely acknowledged that the free energy profile between two minima in biomolecular processes is inherently not smooth. In this article, we discuss a theoretical model with a parabolic rough potential barrier and obtain analytical results of the transition path distribution and mean transition path times by incorporating absorbing boundary conditions across the boundaries under the driving of Gaussian white noise. Further, the influence of anomalous dynamics in rough potential driven by a power-law memory kernel is analyzed by deriving a time-dependent scaled diffusion coefficient that coarse-grains the effects of roughness, and the system's dynamics is reduced to a scaled diffusion on a smooth potential. Our theoretical results are tested and validated against numerical simulations. The findings of our study show the influence of the boundary conditions, barrier height, barrier roughness, and memory effect on the transition path time distributions in a rough potential, and the validity of the scaling diffusion coefficient has been discussed.

Analytical solution of time-fractional Emden-Fowler equations arising in astronomy and mathematical physics

The time-fractional Emden-Fowler model is an interesting mathematical model because it is widely used and important in mathematics and applied sciences. The current investigation compiles the Elzaki transform homotopy perturbation method (ET-HPM) and the Laplace transform homotopy perturbation method (LT-HPM) for the analytical solution of the considered model. In their developments, we show that fractional orders are simple to compute, and the resulting series lead to accurate results after a few iterations. We consider the fractional orders in the context of the Caputo form. The primary aim of these approaches is to compare the analytical results of the models under consideration. These schemes do not impose any constraints on the parameters or make any assumptions that could complicate the process of obtaining the analytical results. We show that the derived outcomes are in convergent sequence with a rapid iterative formula. The iterative series and the graphical illustrations in various fractional orders confirm the efficiency of the proposed approaches. The derived results are also compared to the precise solutions, which show that our suggested approaches are simple, effective, and accurate.

Impact of the Prey Refuge Parameter in the Presence of Fear Effect on the Fuzzy Two-Prey–One Predator Model with Switching Effect

It has been thought of as a class of models where a generalist predator feeds on two distinct prey species. We wish to examine how prey refuge factors affect prey–predator models when fear effects are present. In order to achieve this, a two-prey–one predator model with prey refuge has been taken into consideration in the presence of the predator’s fear effect on two prey species. Both prey species engage in intra-specific competition. We enhance our model by including a switching mechanism in predation. In order to account for the inherent imperfection of environmental conditions, some parameters have been taken as fuzzy numbers. Analytical and numerical results on the system have been examined in fuzzy sense. The system’s positivity, boundedness, and permanence are examined. The system’s local and global stability analyses have been investigated. Hopf bifurcation analysis around the positive interior equilibrium point has been explored. The stability of the limit cycle of our suggested fuzzy system has been discussed. The system’s numerical simulations have been investigated with pertinent tables and graphical illustrations. When the prey refuge parameter and fear parameter exceed the critical value, the system experiences Hopf bifurcation at the positive interior equilibrium point.

Enhancing Predictive Analytics in Business Intelligence through Explainable AI: A Case Study in Financial Products

Today, when the importance of data-based decision-making is impossible to question, the use of Explainable Artificial Intelligence (XAI) in business intelligence (BI) has inestimable benefits for the financial industry. This paper discusses how XAI influences predictive analytics in BI systems and how it may improve interpretability, and useful suggestions for financial product companies. Thus, within the context of this study, an XAI framework helps the financial institutions to employ higher-performing and more accurate models, like gradient boosting and neural networks, while sustaining interpretability required in tendentious planning and satisfying governance and supervision necessities. These studies reveal that, as applied to the credit scoring dilemma, XAI techniques such as SHAP and LIME do not only enhance prediction consistency and performance, but also offer a detailed understanding of customer behaviours, risk profiles and product performance. They help in interacting and acting within fields that involve decision making on aspects like customer loyalty, probable risks and audit. Furthermore, the study establishes that by incorporating XAI into BI improves model interpretability, which helps financial experts provide tangible rationale for analytical results and conform to regulatory directives. This framework and findings also support the importance of introducing XAI for financial BI applications to improve analytics practice within the sector. , enabling the generation of higher confidence, reliable decisions, which place the subject of XAI as a profound evolution of business intelligence in finance.