Influence Matrix Research Articles

Dynamically variable intensity patterns projected using an optofluidic phase-shifter array

We present a concept for the dynamically variable definition of arbitrary intensity distributions using an array of optofluidic phase-shifters. These components consist of cylindrical fluidic surfaces whose interface may be controllably shaped using electrowetting-on-dielectrics actuation. Key to the generation of defined intensity distributions is the ability to calculate the required shape for this phase-shifting interface and to this end we present a novel procedure, to our knowledge, that combines a real-time optimization algorithm with an influence matrix approach to generate the required surface. We illustrate the effectiveness of this approach by reconstructing arbitrary surface profiles with one optofluidic phase-shifting component that is then used to project a desired two-dimensional intensity distribution. Using this approach, we further demonstrate the capability of a two-dimensional phase-shifter array to generate larger dynamically programmable intensity patterns by combining individual intensity distributions.

Exact Hidden Markovian Dynamics in Quantum Circuits.

Characterizing nonequilibrium dynamics in quantum many-body systems is a challenging frontier of physics. In this Letter, we systematically construct solvable nonintegrable quantum circuits that exhibit exact hidden Markovian subsystem dynamics. This feature thus enables accurately calculating local observables for arbitrary evolution time. Utilizing the influence matrix method, we show that the influence of the time-evolved global system on a finite subsystem can be analytically described by sequential, time-local quantum channels acting on the subsystem with an ancilla of finite Hilbert space dimension. The realization of exact hidden Markovian property is facilitated by a solvable condition on the underlying two-site gates in the quantum circuit. We further present several concrete examples with varying local Hilbert space dimensions to demonstrate our approach.

The Analysis of Trigger Factors of the Environmental Entrepreneurship Process in Saudi Arabia: An Innovative Approach

Environmental entrepreneurship is considered a critical avenue for sustainable development. Despite increasing studies on its benefits and impacts, we lack insights about its corresponding process. There is an increasing need for policymakers to know how to develop this process and what is required for its definition. This research aims to build an innovative theoretical model to explore the trigger factors for the environmental entrepreneurship process in Saudi Arabia, which is the ultimate focus point of this research. To achieve this objective, a deep literature review and a survey of expert entrepreneurs’ opinions were performed. Experts and professionals in entrepreneurship validated the opportunity of readiness factors identified. Data were gathered using a combined approach based on closed-ended questionnaires and arranged interviews according to a schedule. Employing the mixed influence matrix of cross-impact multiplications applied to classification (MICMAC) and the Interpretive Structural Modeling (ISM) approach, the research identifies a hierarchical model of these factors, addressing why and how they interact according to a specific order and priorities. The investigation reveals 15 factors that are structured into three main levels of influence: (1) factors driving the adoption of environmental entrepreneurship orientation, (2) factors related to environmental entrepreneurship intention, and (3) factors for materializing environmental entrepreneurship behavior. The findings emphasize the complementarity between environmental entrepreneurship intention and orientation as a key factor in generating entrepreneurial behavior. This research pioneers the empirical exploration of environmental entrepreneurship as a process. It contributes significantly to theoretical and practical domains by offering a pragmatic framework and better understanding for policymakers and stakeholders to focus on key factors that facilitate this process. This paper is innovative because it uses the integrative ISM–MICMAC approach, supported by a primary and brief bibliometric analysis of entrepreneurship.

Calculation method of temporary cable force in incremental launching construction of large span steel box girder without auxiliary pier

The Fenshui River Bridge is a steel–concrete composite girder bridge with a main span of 90 m. Due to the topographical constraints, the steel box girder was constructed without the use of auxiliary piers, employing incremental launching techniques. This article focuses on the construction technology used for the steel box girder of the Fenshui River Bridge. Firstly, using the influence matrix method, the cable force is determined based on the maximum cantilever state of the structure, with the vertical deformation of the front end of the guide beam and the horizontal deformation of the top of the tower as the control objectives. The unstressed cable length is then calculated based on the mechanical relationship between cable deformation and cable force. A calculation method for adaptive cable force is proposed, which is based on the variation of the stress-free cable length within the adaptive structural system. Next, the finite element analysis method was employed to determine the optimal layout position for the tower. The results indicate that during the incremental launching construction of the steel box girder, the calculated cable forces using the method proposed in this paper are in close agreement with the measured cable forces. At the maximum cantilever state of the structure, the calculated and measured values of the cable force resulted in a percentage difference of 3.96%. The calculated values of deformation and stress in key sections showed a percentage difference of 6.4% for deformation and 6.6% for stress. To maximize the effectiveness of the tower and cable, the tower should be positioned above the bridge pier when the guide beam crosses the maximum span. The findings of this paper can serve as a reference for the construction of similar types of bridges.

Cracking the Pericellular Matrix Code: Exploring how MMP-2, -3, and -7 influence matrix breakdown and biomechanical properties

IntroductionThe intricate process of articular cartilage remodeling, pivotal for both physiological functions and osteoarthritis (OA) progression, is orchestrated through a balance of matrix synthesis and breakdown, which is mediated by matrix metalloproteinase enzymes (MMPs). At the heart of this remodeling lies the pericellular matrix (PCM), a specialized microenvironment encapsulating each chondrocyte and composed mainly of collagen type VI and perlecan. The aim of this study was to assess the impact of MMP-2, -3, and -7 on the structural integrity and biomechanical attributes of the PCM. MethodsHuman articular cartilage explants (N=10 patients) were incubated with activated MMP-2, -3, or -7, individually or in combination. Structural alterations in the PCM were evaluated by immunolabeling. The biomechanical properties of the PCM were measured using atomic force microscopy (AFM). ResultsCollagen type VI structural integrity and fluorescence intensity uniformly decreased across all enzyme groups, while perlecan was selectively affected by MMP-3 and -7. AFM measurements demonstrated decreased PCM stiffness after incubation with individual MMPs, leading to an overall ~31 % reduction in elastic modulus for each enzyme. Combinations of enzymes induced comparable significant biomechanical alterations (~35 %), except for MMP-2+MMP-7. DiscussionThis study highlights the significant influence of MMP-induced alterations in PCM composition on biomechanical properties, mirroring characteristics observed in early OA. Each MMP showed specificity in breaking down PCM, and an intriguing interplay, especially between MMP-2 and -7, indicated reduced efficacy in lowering PCM stiffness. Overall, MMP-2, -3, and -7 directly induce functional and structural PCM modifications.

Identification of hanger damage based on deflection influence matrix

Tied-arch bridges, a vital component of modern infrastructure, are susceptible to various forms of damage, particularly hangers. The detection and identification of such damages are crucial for maintaining structural integrity and safety. However, traditional methods face challenges in terms of accuracy and efficiency. This study aims to develop a refined method for hanger damage identification in tied-arch bridges, to address the limitations of existing techniques. By focusing on deflection changes at the anchoring points between the hangers and tie beams, we sought to enhance the precision of damage detection. We propose an innovative approach based on the concept of influence lines, introducing the ‘generalized deflection difference influence line'and the ‘deflection difference influence matrix’. Then proposed a new identification index for identifying the damaged hanger after matrix. An actual tied-arch bridge was used to validate the proposed approach. A detailed three-dimensional finite element model of the bridge was developed and calibrated using dynamic and static response data. Thirty different hanger-damage conditions were simulated to evaluate the effectiveness of the proposed method. Our findings reveal that the deflection difference influence matrix offers more detailed and comprehensive information on bridge distribution points than traditional methods. Our method proved effective in identifying hanger damage, irrespective of its location on the bridge. In additionally, the identification efficiency of the method can be improved by adjusting the magnitude of the applied load, with larger loads amplifying the detectability of damage. This study highlights the potential of the deflection difference influence matrix to revolutionize hanger damage identification for tied-arch bridges. Its adaptability, accuracy, and efficiency are significant advancements over existing methods. This study successfully demonstrates an innovative and reliable method for hanger damage identification.

An automated optimized design of practical post-tensioned slabs

In this paper, an efficient methodology that could be implemented within any analysis software is developed to automate the design process of post-tensioned slabs. Optimization techniques are used to compute the necessary number of strands. The present methodology is based on computing an innovative influence matrix that contains the effect of each strand on stresses at a set of control points (points of peak stresses). This matrix will be used in the optimization avoiding reanalysis in each optimization iteration. The sum of the squares of the difference between the allowable stress and the computed stresses at all control points is considered an objective function. The optimization is then carried out under the constraints that the stresses at each control point should not exceed the allowable limit and to ensure that the number of strands is an integer value. Alternatively, the proposed methodology could be used as a value-engineering tool. Practical examples are presented to demonstrate the efficiency of the developed methodology.

The Active Compensation Technique for Large Reflector Antennas Based on Quadratic Curve Fitting

Active reflectors are often used to compensate the surface distortion caused by environmental factors that degrade the electromagnetic performance of large high-frequency reflector antennas. This is crucial for maintaining high gain operation in antennas. A distortion compensation method for the active reflector of a large dual-reflector antenna is proposed. A relationship is established between the surface deformation and the optical path difference for the primary reflector by geometric optics. Subsequently, employing finite element analysis, a polynomial fitting approach is used to describe the impact of adjusting points on the reflector surface based on the coordinates of each node. By standardizing the positions of various panels on the reflector, the fitting ns can be applied to the reflector panels of similar shapes. Then, based on the distribution characteristics of the primary reflector panels, the adjustment equation for the actuators is derived by the influence matrix method. It can be used to determine the adjustment amount of actuators to reduce the rms of the optical path difference. And, the least squares method is employed to resolve the matrix equation. The example of a 110 m aperture dual-reflector antenna is carried out by finite element analysis and the proposed method. The results show that the optical path difference is reduced significantly at various elevation cases, which indicates that the proposed method is effective.

A Practical Approach to Alignment and Error Feedback Control for Long-Span Arch Bridges

The accurate installation of long-span arch bridges’ arch ribs remains a challenge due to the complex calculations required for cable forces and arch rib displacements, as well as the significant influence of environmental and construction loads. In this study, we propose a practical approach to alignment and error feedback control for long-span arch bridges. Cable forces were optimized using multiple control objectives based on influence matrix principles. The impact of temperature on the next segment to be installed was analyzed using the metastatic GM(1, 1) model and fitting results. Several tunable parameters were employed to account for parameter errors and environmental interference. These parameters were adjusted based on the deviations between practical and theoretical alignments for different arch rib segments, achieving a model output of an offset-free-tracking arch rib structure. This technology was applied to monitor the construction of the Tian’e Longtan Grand Bridge. Compared to conventional alignment control approaches, the proposed method achieved excellent arch ring alignment after the closure of the high-accuracy arch rib and cable release, as well as effective control of cable force uniformity and tower deviation. Field measurement data indicate that the closing deviation of the arch ring is only 3 mm. This study provides a valuable reference for the construction control of long-span arch bridges.

Optimal influence design in networks

We examine an influence designer's optimal intervention in the presence of social learning in a network. Before learning begins, the designer alters initial opinions of agents within the network to shift their ultimate opinions to be as close as possible to the target opinions. By decomposing the influence matrix, which summarizes the learning structure, we transform the designer's problem into one with an orthogonal basis. This transformation allows us to characterize optimal interventions under complete information. We also demonstrate that even in cases where the designer has incomplete information about the network structure, the designer can still design an asymptotically optimal intervention in a large network. Finally, we provide examples and extensions, including repeated social learning and competition.

Evaluation of Air Pollution Control Management In Jakarta by Crossed-Impact Matrix Multiplications Applied to Classification (MICMAC)

Abstract The rapid activity in Jakarta due to high economic growth increases air pollution, which impacts health problems and environmental, social, and ecological disturbances. The research objectives are to determine factors for controlling air pollution, score and evaluate the matrix of direct influence (MDI), draw a direct and indirect influence graph, and make rating and classification comparisons. The information collection was carried out by applying the Center Gather Dialog strategy to decide the factors that impact contamination control. Information evaluation was carried out utilizing the interpretive structural modelling (ISM) with matrice d’ impacts cruises multiplication appliqué a classement (cross-impact matrix multiplication applied to classification, abbreviated as MICMAC). The results show that the factor that influences air pollution control is high concentrations resulting from activities in the transportation sector and industrial sector. Economic growth has an indirect effect because economic growth is correlated in the same direction as air pollution. The transportation sector consists of motorized vehicle activities such as cars, two-wheeled motorbikes, aeroplanes, trains, and ships that use oil fuel, which contributes to the high concentration of air pollution in Jakarta. Controlling air pollution must involve all parties, including government responsibility, public awareness, transportation, and industrial actors. All parties should implement and comply with regulations effectively and efficiently. Air pollution monitoring activities must be carried out appropriately and regularly.

Hydraulic Connectiveness Metric for the Analysis of Criticality in Water Distribution Networks

Capturing the criticality of a water distribution network (WDN) is difficult because of its many constituent factors. In terms of operation, the arrangement of demand nodes and how they connect have a significant influence. This study aims to integrate hydraulic and topologic aspects into a single criticality measure by adapting the structural hole influence matrix concept. This method applies the nodal demand to the corresponding pipes to construct a weighted network. The matrix stores each node’s local and global connection information, and the criticality value is then assigned based on the adjacency information. The criticality value can reveal the locations in terms of nodes or pipes that are vital for maintaining a network’s level of service. By analyzing pipe-failure scenarios, the criticality value can be related to the loss of performance. Assessing the nodal criticality change behavior under an increased stress scenario can help uncover the impacted areas. The metric for district metered area (DMA) creation demonstrates its potential as a weighting to be considered. This unified criticality metric enables the evaluation of nodes and pipes in a WDN, thereby enabling resilient and sustainable development planning.

Exploring energy selection methods for robust biologically optimized carbon ion arc for head&neck cancer patients

BackgroundDue to the advantageous depth dose profile of carbon ion beams, carbon ion therapy is commonly applied in the form of intensity modulated particle therapy (IMPT) with few treatment fields. Carbon ion arc therapy (C-Arc) has recently been proposed to improve dose conformity and increase the dose-averaged linear energy transfer (LETd) inside the target to levels relevant for overcoming tumor radioresistance. In this work, we investigate different energy selection approaches for C-Arc, including a novel greedy energy layer refinement strategy.MethodsRobust biologically optimized C-Arc plans were generated for six head &neck cancer patient previously treated at the Shanghai Proton and Heavy Ion Center (SPHIC). Different heuristic approaches for mono- and dual-energy C-Arc were implemented, and compared to carbon IMPT pans. A novel greedy energy layer refinement was developed, acting directly on the dose influence matrix, rather than on an iterative plan optimization. A key challenge in C-Arc with few energy layers per angle is the sharpness of the carbon ion Bragg peak, which is challenging for plan robustness. To improve robustness and plan quality, we propose the use of a 6 mm ripple filter instead of the typical 3 mm ripple filter used for carbon IMPT.ResultsMost mono-energetic C-Arc plans were able to meet the established clinical goals, but some of the heuristic energy selection schemes were not universally applicable with low plan quality in some patients. The developed energy layer refinement strategy delivered high quality plans even for complex cases. Mono-energetic C-Arc plans presented an average increase between 10% and 33% in the maximum LETd in the target, with similar or up to 19% improved average target LETd50%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{50\\%}$$\\end{document} compared to the IMPT carbon ion plans. C-Arc plans with 2 energies per treatment angle, for the employed energy selection heuristic, improved dosimetric quality compared to mono-energetic C-Arc plans, but did not provide the same natural improvement in LETd compared to IMPT.ConclusionsFor small, centrally located targets C-Arc demonstrates the greatest potential, but feasible plans could also be achieved for more complex cases in this work. Further development is necessary for improving C-Arc delivery efficiency and plan quality toward possible clinical application.

Balancing homophily and prejudices in opinion dynamics: An extended Friedkin–Johnsen model

In this paper we propose an extended version of the Friedkin–Johnsen (FJ) model where we analyze the effects that a homophily-based influence matrix has on the opinion formation process. In particular, we assume that the influence matrix varies over time, and its entries (that represent the appraisals that individuals have of the other individuals) update based on the comparison between their opinions and can take both positive and negative values. This leads to a system of two difference equations, where the first one corresponds to the standard FJ model, except that the influence matrix is no longer constant, and the second one models the dynamics of this matrix. We show that a necessary and sufficient condition for the convergence of this modified version of the classical FJ model is that the influence matrix becomes constant in a finite number of steps. Moreover, we provide the explicit expression for the agents’ asymptotic opinions in some special cases: the purely cooperative setting, the case of a structurally balanced network and the case of a single discussion topic. Finally, the case when the topics are correlated and the influence matrix depends on the average opinion vectors is investigated.

Determination of Replacement Cable Force of in-Service Suspension Bridge Based on Refined Modelling Approach

In this paper, the replacement cable force of suspension bridge slings in service is systematically analyzed by adopting the coupling analysis model of internal force influence matrix and displacement influence matrix. The sling replacement project of an existing bridge serves as the basis for considering the technical condition and stress state of slings and other components comprehensively. Key control indexes, such as internal force, offset, linear or adjacent cable force change, are defined according to vehicle traffic requirements and structural safety considerations. Refined finite element numerical calculation is employed to determine the target cable force applied to the replacement sling, while analyzing changes in key control indexes of relevant components and structures during adjustment. The target cable force of the replacement sling is adjusted and determined based on a comparison with the target demand index. Compared with the traditional influence matrix method, the double matrix method also has the advantage that it does not need to select the initial adjustment cable force, which avoids the problem that the convergence result may not be obtained, and aims to provide a basis for the subsequent calculation of cable force replacement when the suspension bridge is in service.

Product Influence Matrix on Purchase Intentions: Unravelling the Dynamics of Consumer Perception Towards Smartphone

This research study aims to examine consumer perceptions regarding the product influence matrix and its impact on purchase intentions among smartphone users in the Kathmandu Valley of Nepal. A descriptive and exploratory research design was employed, and data was collected through questionnaires distributed both in-person and online. The sample size of 412 respondents was determined using non-probability convenience sampling. The results showed that compatibility, brand, product features, and social influence were positively perceived by consumers, with compatibility and brand being the most influential factors. However, purchase intention received a slightly lower mean score, suggesting that there might be other factors influencing consumers' purchase decisions. The correlation analysis revealed significant correlations between all the product influence factors and purchase intention. The multiple regression analysis demonstrated that the combination of compatibility, brand, product features, and social influence significantly predicted purchase intention, explaining approximately 65.4% of its variance. The findings suggest that building strong brands, emphasizing attractive product features, and leveraging social influence can positively impact consumers' purchase intentions. The study provides valuable insights for smartphone marketers in understanding and influencing consumer behaviour in the Kathmandu Valley market. However, further research is recommended to explore specific aspects of compatibility and identify additional factors that may influence consumer purchasing decisions in this context.

Design and Simulation of a 19-Electrode MEMS Piezoelectric Thin-Film Micro-Deformable Mirror for Ophthalmology.

This study presents a numerical simulation-based investigation of a MEMS (micro-electromechanical systems)technology-based deformable mirror employing a piezoelectric film for fundus examination in adaptive optics. Compared to the classical equal-area electrode arrangement model, we optimize the electrode array for higher-order aberrations. The optimized model centralizes electrodes around the mirror center, which realizes low-voltage driving with high-accuracy correction. The optimized models exhibited commendable correction abilities, achieving a unidirectional displacement of 5.74 μm with a driven voltage of 15 V. The voltage-displacement relationship demonstrated high linearity at 0.99. Furthermore, the deformable mirror's influence matrix was computed, aligning with the Zernike standard surface shape of the order 1-3. To quantify aberration correction capabilities, fitting residuals for both models were calculated. The results indicate an average removal of 96.8% of aberrations to the human eye. This underscores that the optimized model outperforms the classical model in correcting high-order aberrations.

Research on Optimization of Quantitative Evaluation Model of Value for Money for PPP Projects

With the continuous development of China construction industry, in recent years, government departments are actively cooperating with social capital in the PPP model to solve public infrastructure construction problems. This study explores the interaction between the driving factors that affect value for money in the PPP model and their respective importance proportions. It combines the literature analysis method and the Delphi method to construct an index system, uses the analytic hierarchy process to calculate the weight of the driving factors, and adopts decision-making The laboratory method was used to construct a comprehensive influence matrix and calculate centrality. The results show that the comprehensive impact of reasonable risk sharing, recognition of stakeholders, organizational and operational capabilities, long-term contract, full life cycle costs, and government control of prices is relatively high. Government factors are easily affected by other types of factors, while society and the environment have a higher degree of impact on other factors.

A Novel Influence Analysis-Based University Major Similarity Study

In the field of education, investigating the relationships between different majors in universities is an important topic in current educational research. The application of social networks from informatics provides new opportunities and potentials for the field of education. Due to the complexity of social interactions, the social network connections surrounding individuals exert a significant influence on their daily decision-making processes. This paper aims to introduce the social network and influence analysis theories from informatics into the field of education, regarding major as a variable, and comparing and analyzing the influence relationships between majors. An empirical study was conducted, involving the collection of questionnaire data on graduates’ evaluations of various aspects of their university experiences across different majors. The evolution of this model follows the DeGroot opinion dynamics with the inclusion of stubborn nodes. By defining leader majors and general majors based on the data and modeling the questionnaire data as the outcome of a discrete random process, an influence matrix is ultimately generated through the opinion dynamic model. Through this modeling approach, we revealed the underlying influence relationships between different disciplines (majors). These findings provide schools with insights to adjust the directions of discipline cultivation, and offer new perspectives and methods for the study of majors in higher education.

РАСПАРАЛЛЕЛИВАНИЕ ВЫЧИСЛЕНИЙ НА ГРАФИЧЕСКОМ ПРОЦЕССОРЕ ДЛЯ УСКОРЕНИЯ ГРАНИЧНО-ЭЛЕМЕНТНЫХ РАСЧЕТОВ В МЕХАНИКЕ

In solving problems of computer modeling using various methods, accuracy and computational efficiency questions always arise. This study explores the application of two modifications of the boundary element method to solve the problem of potential distribution within a closed two-dimensional domain with a uniform potential distribution on its boundary. The first modification involves using three nonlinear shape functions instead of one. The second modification applies the Galerkin method to the boundary element approach with three nonlinear shape functions. The essence of this modification lies in the fact that the system of equations is formulated in integral form over the entire boundary element, rather than at collocation points. In addition to this, the paper describes and investigates the advantages and disadvantages of the smoothing modification applied to these approaches. Since the influence matrix consists of independently computable elements, parallelization of calculations using NVIDIA CUDA technology has been proposed to enhance computational efficiency, significantly accelerating the calculation of interaction matrix. The choice of this technology is advantageous due to the prevalence of NVIDIA graphics accelerators in almost every personal computer or laptop, as well as it is easy to use. The study presents an approach to the application of this technology and demonstrates the results, showing the acceleration of parallelized calculations which show the dependence on the number of boundary elements. A comparison of the efficiency of the selected technology when applied to two methods, collocation and Galerkin, is also presented, indicating a significant speedup of up to 22 times by computing the influence matrix of the boundary elements.