Model Of Mechanism Research Articles

Attention mechanism models for precision medicine.

The development of deep learning models plays a crucial role in advancing precision medicine. These models enable personalized medical treatments and interventions based on the unique genetic, environmental and lifestyle factors of individual patients, and the promotion of precision medicine is achieved mainly through genomic data analysis, variant annotation and interpretation, pharmacogenomics research, biomarker discovery, disease typing, clinical decision support and disease mechanism interpretation. Extensive research has been conducted to address precision medicine challenges using attention mechanism models such as SAN, GAT and transformers. Especially, the recent popularity of ChatGPT has significantly propelled the application of this model type to a new height. Therefore, I propose a Special Issue for Briefings in Bioinformatics about the topic 'Attention Mechanism Models for Precision Medicine'. This Special Issue aims to provide a comprehensive overview and presentation of innovative researches on the application of graph attention mechanism models in precision medicine.

Microscopic Chemical Reaction Mechanism and Kinetic Model of Al/PTFE.

In order to study the microscopic reaction mechanism and kinetic model of Al/PTFE, a reactive force field (ReaxFF) was used to simulate the interface model of the Al/PTFE system with different oxide layer thicknesses (0 Å, 5 Å, 10 Å), and the thermochemical behavior of Al/PTFE at different heating rates was analyzed by simultaneous thermal analysis (TG-DSC). The results show that the thickness of the oxide layer has a significant effect on the reaction process of Al/PTFE. In the system with an oxide layer thickness of 5 Å, the compactness of the oxide layer changes due to thermal rearrangement, resulting in the diffusion of reactants (fluorine-containing substances) through the oxide layer into the Al core. The reaction mainly occurs between the oxide layer and the Al core. For the 10 Å oxide layer, the reaction only exists outside the interface of the oxide layer. With the movement of the oxygen ions in the oxide layer and the Al atoms in the Al core, the oxide layer moves to the Al core, which makes the reaction continue. By analyzing the reaction process of Al/PTFE, the mechanism function of Al/PTFE was obtained by combining the shrinkage volume model (R3 model) and the three-dimensional diffusion (D3 model). In addition, the activation energy of Al/PTFE was 258.8 kJ/mol and the pre-exponential factor was 2.495 × 1015 min-1. The research results have important theoretical significance and reference value for the in-depth understanding of the microscopic chemical reaction mechanism and the quantitative study of macroscopic energy release of Al/PTFE reactive materials.

Prediction of liquid holdup and pressure drop in gas-liquid two-phase flow based on integrating mechanism analysis and data mining

Gas-liquid two-phase flow widely exists in gas transportation pipelines, and the prediction of liquid holdup and pressure drop is crucial for the safety and efficiency of pipelines. Due to the complexity of multiphase flow, the mechanism model is difficult to accurately and quickly predict the liquid holdup and pressure drop. Machine learning (ML) models have high accuracy, but the lack of physical meaning limits their application. In order to fully leverage the advantages of mechanism models and machine learning models, a new method using physically guided neural networks (PGNN) to predict pressure drop and liquid holdup is proposed. Based on the flow mechanism analysis of different flow patterns, the structure of PGNN is designed according to the calculation process of the mechanism model. Key physical intermediate variables such as shear stress and friction coefficient are added to the model as neurons. Physical constraints in gas-liquid two-phase flow are added to the loss function to give physical significance to neurons. 1390 publicly available experimental data are collected for model training and testing. Due to the uneven distribution of experimental data, the local outlier factor (LOF) algorithm is used to screen outlier of data. By comparing PGNN with other ML models, empirical models, and semi empirical models, it is proved that integrating mechanism into the ML model improves the accuracy and physical consistency. This research presents a fresh outlook on the investigation of the flow dynamics in gas-liquid two-phase systems.

Strategies for optimizing interfacial thermal resistance of thermally conductive hexagonal boron nitride/polymer composites: A review

AbstractWith the continuous development of high‐end electronic information technologies such as 5G communications, thermal management is an urgent issue in the electronic and circuit industries due to the miniaturization, functionalization and integration. Recently, polymer‐based composites with the fillers of hexagonal boron nitride (h‐BN) have been regarded as promising candidates resulting from their excellent thermal conductivity (TC), good insulation and remarkable comprehensive properties. However, the high surface inertness of h‐BN itself, incompatibility with matrix and other fillers and mismatch of phonon‐spectrum will bring about the matrix/filler and filler/filler interfacial thermal resistance (ITR), which will greatly decline the TC of the composites, and limit their thermal management ability. Therefore, how to design, regulate and improve the interfacial states in composites and eventually enhance the TC is a current challenge. Researchers have made great effort to reduce the ITR of the composites to improve their TC. However, a comprehensive summary and analysis of researches on the improvement methods of the interface states in composites in the past 3 years is still lacking. In this work, the commonly used mechanism models, and simulation methods for calculating and predicting TC was summarized. From perspectives of Synthesis of h‐BNNs, modification, orientation, bridging and three‐dimensional structures construction, we reviewed strategies for improving the interface states in composites, and focused on the ITR regulation and TC improvement. The improvement effects of various methods on TC were compared. The development trend of high TC composite materials was prospected.Highlights Crystallinity, defect, size, flatness, thickness of hexagonal boron nitride nanosheets (BNNSs) affect interfacial thermal resistance (ITR). Nature of interaction between adjacent layers of BNNS need exploited. Interface and defect are root cause of extra phonon scattering. Shape, density, surface area, distribution and compatibility reduce ITR. Theory, model, simulation methods need developed on different levels.

A theoretical exploration of polyvagal theory in creative arts and psychomotor therapies for emotion regulation in stress and trauma.

Polyvagal theory advocates for working with the body, becoming aware of the body and connecting with the senses. Similarly, paying attention to and influencing one's physical and sensory experience is a core aspect of the creative arts and psychomotor therapies. Polyvagal theory offers opportunities for strengthening resilience by treating emotion-regulation problems, stress, and trauma, as well as restoring regulation of the autonomic nervous system. Paying attention to and influencing physical and sensory experiences are core aspects of creative arts and psychomotor therapies. This theoretical paper explores how polyvagal theory can serve as a foundational theory and support the creative arts and psychomotor therapies for emotion regulation in stress and trauma. A number of pillars in polyvagal theory have links with arts therapies, such as an emphasis on physical and sensory experience in situations of safety or threat. This theory may offer insight into the role of the body in stressful situations, the role of co-and self-regulation, and thus the functioning of and the rationale for use of creative arts and psychomotor therapies. Through interventions focused on promoting healthy autonomic responses and regulating physiological responses, clients can learn to better regulate and process their emotional experiences. Although this could be broadly useful, it would seem particularly promising in therapies focused on stress and trauma. This article provides an introduction to polyvagal theory and outlines how it can serve as an explanatory, hypothetical model for the working mechanisms that underlie creative arts and psychomotor therapies. The application of PVT in creative arts and psychomotor therapies will be explored by describing techniques for "noticing and naming" and "learning to change," as well as by highlighting the role of PVT in the therapeutic relationship. It provides case examples and discusses the role of creative arts and psychomotor therapies for stress regulation and resilience conceptualized in line with the polyvagal theory.

High‐Dissolution Mechanism of Ti–48Al–2Cr–2Nb Alloy in Electrochemical Machining from a Nonlinear Dynamic Perspective

High‐rate dissolution process of Ti–48Al–2Cr–2Nb alloy in electrochemical machining exhibits strong nonlinear dynamic characteristics, but the quantitative relationship between these nonlinear characteristics and surface topography, as well as the electro‐dissolution mechanism, is unknown. Therefore, the fractal and recursive features of dissolution behavior and quantitative characterization of the dissolved surface topography were investigated. Additionally, an electro‐dissolution mechanism model in electrochemical machining process was presented. Applying a higher potential of 11 V can enhance the stability of the electrochemical system, resulting in a smoother and uniform surface. The saturation correlation dimension, surface roughness, and integral area of lacunarity initially decrease before increasing with higher electrolytic pressure, while laminarity and determinism show an initial increase followed by a decrease. These five characteristic parameters reach their optimal values at an electrolyte pressure of 0.4 MPa, indicating that achieving a stable and deterministic electrochemical system is crucial for obtaining a uniform smooth surface. These nonlinear dynamic characteristic parameters can be considered as in‐situ monitoring parameters for surface quality in ECM. The anodic dissolution process comprises three stages: initial passive film dissolution and breakdown, rapid dissolving with surface coarsening, and stable dissolving with polishing.

Capture dynamics and driving method of origami capture mechanism in orbit

This article focuses on the dynamic problem of origami capture mechanism capturing space debris in orbit. It delves into the envelope characteristics of the origami capture mechanism, analyzing the motion laws of its axisymmetric folding state. Furthermore, it establishes a kinematic model for the axisymmetric envelope of the origami capture mechanism. A rigid body dynamic model of the origami capture mechanism and a generalized torque equation for the hinge at the crease were established based on the D–H parameter method and the Lagrange method. The enveloping process of the origami capture mechanism in the microgravity environment was simulated using ADAMS software, and the accuracy of the rigid body dynamics model of the origami capture mechanism and the generalized moment equation of the hinge at the crease was verified. Using Ls-Dyna software to simulate the capture process of space debris by force-driven and displacement-driven flexible origami capture mechanisms in microgravity environments, the results show that displacement-driven origami capture mechanisms can quickly capture space debris and are suitable for capturing large-sized space debris; The force-driven origami capture mechanism can quickly complete envelope capture of space debris, suitable for capturing small-sized space debris.

A comprehensive setting method for the optimal setpoint of controlled variables in the zinc smelting solution purification process under multi-variation inlet status

The zinc smelting solution purification process regulates the oxidation-reduction reactions (characterized by the oxidation-reduction potential (ORP)) by controlling the amount of zinc powder added to remove the impurity ions. In order to ensure the optimal operation of the process, the target key technical indicators should be converted into the optimal setpoint of controlled variables (that is, ORP). Based on the mechanism knowledge, fuzzy rules, and preference-guided predictive optimization, a comprehensive setting method for the optimal setpoint of controlled variables under multi-variation inlet status is proposed. It includes a hybrid trend detection method for inlet status, a mechanism model under multiple operating modes, and a fuzzy correction method and a preference-guided predictive optimization method to deal with slight and violent fluctuations in the inlet status, respectively. The experimental results show that the proposed method can obtain the optimal setpoint of controlled variables and reduce zinc powder consumption by approximately 3.6%.

Mathematical modelling for compliance-assisted artificial muscle based ornithopter

PurposeThis study aims to discuss the mathematical modelling of a compliance-assisted flapping mechanism and morphable structures for an UAV.Design/methodology/approachA compliance-assisted flapping wing was designed and modelled mathematically, and signals for the corresponding curves were calculated. The actual wing tip trace of a hummingbird was taken, and variables a, b, h and k were calculated from the image. This data was given to the mathematical model for plotting the graph, and the curve was compared with the input curve. The wing frame and mechanism for control surfaces using morphing is modelled along with single pivoted spine for centre of gravity augmentation and flight orientation control.FindingsThe model efficiently approximates the 2D path of the wing using line segments using the muscle and compliance mechanism.Practical implicationsUsing a compliance-assisted flapping mechanism offers practical advantages. It allows us to synchronize the flapping frequency with the input signal frequency, ensuring efficient operation. Additionally, the authors can enhance the torque output by using multiple muscle strands, resulting in a substantial increase in the system’s torque-to-weight ratio. This approach proves to be more favourable when compared to conventional methods involving motors or servos, ultimately offering a more efficient and robust solution for practical application.Social implicationsThis model focuses on creating a flexible and tunable mechanism that can at least trace four types of wing traces from the same design, for shifting from one mode of flight to another.Originality/valueConventional ornithopter flapping mechanisms are gear or servo driven and cannot trace a wing tip, but some can trace complicated curves, but only one at a time. This model can trace multiple curves using the same hardware, allowing the user to program the curve based on their needs or bird. The authors may vary the shape of the wing tip trace to switch between forward flight, hovering, backward flying, etc., which is not conceivable with any traditional flapping mechanism.

Research on Displacement Sensorless Control for Bearingless Synchronous Reluctance Motor Based on the Whale Optimization Algorithm–Elman Neural Network

The unique structure of bearingless motors requires extra displacement sensors to monitor rotor movement, unlike conventional synchronous motors. However, this requirement inevitably escalates the cost and size of the motor. To address these issues, this paper proposes a novel approach: a bearingless synchronous reluctance motor (BSRM) without displacement sensors, utilizing the whale optimization algorithm–Elman neural network (WOA-ENN). The paper firstly introduces the suspension mechanism and mathematical model of the BSRM, upon which a function containing rotor position information is constructed. Subsequently, a sensorless method based on Elman neural network (ENN) is proposed, optimized using the whale optimization algorithm (WOA). Finally, the feasibility and reliability of the proposed approach are validated through simulations and experiments.

Design of Digital Twin Cutting Experiment System for Shearer.

This study presents an advanced simulated shearer machine cutting experiment system enhanced with digital twin technology. Central to this system is a simulated shearer drum, designed based on similarity theory to accurately mirror the operational dynamics of actual mining cutters. The setup incorporates a modified machining center equipped with sophisticated sensors that monitor various parameters such as cutting states, forces, torque, vibration, temperature, and sound. These sensors are crucial for precisely simulating the shearer cutting actions. The integration of digital twin technology is pivotal, featuring a real-time data management layer, a dynamic simulation mechanism model layer, and an application service layer that facilitates virtual experiments and algorithm refinement. This multifaceted approach allows for in-depth analysis of simulated coal cutting, utilizing sensor data to comprehensively evaluate the shearer's performance. The study also includes tests on simulated coal samples. The system effectively conducts experiments and captures cutting condition signals via the sensors. Through time domain analysis of these signals, gathered while cutting materials of varying strengths, it is determined that the cutting force signal characteristics are particularly distinct. By isolating the cutting force signal as a key feature, the system can effectively distinguish between different cutting modes. This capability provides a robust experimental basis for coal rock identification research, offering significant insights into the nuances of shearer operation.

Economic mechanism as a tool for sustainable economic development: Challenges and solutions

Subject. This article discusses the theoretical basics and practice of the creation and application of economic mechanisms of various types. Objectives. The article aims to identify the reasons for the low efficiency of the use of economic mechanisms in practice. Methods. For the study, we used comparison, observation, deduction, and the dialectical method. Results. The article proposes a developed schematic model of the economic mechanism for ensuring sustainable development, based on the process of generating benefits, and a procedure for implementing the economic mechanism parameters for ensuring sustainable development in reality. Conclusions. The technological process is the main factor that determines the composition of the economic mechanism and the algorithm of interaction of its elements.

Analysis and Modeling of Intermittent Fluctuation Mechanisms of Piezoelectric Impact-Induced Vibration Cantilever Energy Harvester

Analysis and Modeling of Intermittent Fluctuation Mechanisms of Piezoelectric Impact-Induced Vibration Cantilever Energy Harvester

Review on critical liquid loading models and their application in deep unconventional gas reservoirs

The exploitation of deep unconventional gas resources has gradually become more significant attributing to their huge reserves and the severe depletion of convention gas resources in the world. The proportion of deep unconventional gas reservoirs in the total gas resources cannot be underestimated, including shale gas, tight gas, and gas of coal seam. Due to the low permeability and porosity, hydraulic fracturing technology is still an important means to develop deep unconventional gas resources. However, the presence of fracturing fluids and water accumulation at the bottom of the wellbore significantly reduce gas production. The liquid loading model can be used to determine when the gas well begins to load the liquid. In this work, different types of liquid loading models are classified, and the applicability of different models is analyzed. At present, the existing critical liquid carrying models can be divided into mechanism models and semi-empirical models. The model established by Turner is a typical mechanism model. There are great differences in the application of a critical liquid loading model between vertical and horizontal wells. The field cases of a liquid loading model in different gas fields are provided and discussed. The mechanism of liquid loading models in recent years is introduced and analyzed. The physical simulations and experimental work therein are described and discussed to clarify the feasibility of the modeling mechanism. This article also presents the limitation and future work for improving the liquid loading models.

The role of administrative discretion in the coping behaviour of street-level bureaucrats in higher education institutions of Pakistan

Policies are created at the highest level, and street-level bureaucrats (SLBs) implement them at lower levels. SLBs work directly with citizens and exercise significant discretion in their service. According to Lipsky's theory, SLBs face various problems and use multiple coping techniques to deal with them. This study focused on the discretionary powers of the heads of departments (HODs) and the use of coping mechanisms when faced with challenges in enacting the semester system policy. The existing study used the theoretical model of coping mechanisms using a single-case research methodology to investigate the HODs of a prestigious public university's coping behaviour in implementing the semester system. Semi-structured interviews were employed to get the perspectives of HODs in this qualitative research. This study used the classification model of coping families developed by Tummers, Bekkers, Vink, and Michael (2015) and concludes that management has given HODs some task-discretionary authority for carrying out the semester system policy based on thematic analysis. The findings reveal that HODs move against the students rather than towards or away from them in coping behaviour. HODs strictly follow the semester system's policy by adhering to rigid rule-following.

Fast robust optimization of ORC based on an artificial neural network for waste heat recovery

Uncertainty in the organic Rankine cycle (ORC) system and the highly complex ORC models pose challenges to optimal operation. A data-driven robust parametric optimization for the ORC system is proposed to ensure high and stable performance under uncertainty. The uncertainty of the cyclic variables is estimated by their distribution parameters, and the average (expected) thermodynamic performance (the net output power of the ORC) is maximized as the optimization objective while minimizing its variance. An artificial neural network with the rectified linear unit is used as a surrogate model for optimization. Then the robust parametric optimization problem can be transformed into a mixed-integer linear optimization problem with a chance-constrained form, and the robust optimal solution can be solved quickly. Case studies show that the solution time of the robust optimization problem using the proposed method is about 1.4 s, which is much less than obtaining the optimal solution based on ORC mechanism models. Meanwhile, the optimal operating condition derived by the proposed robust optimization approach outperforms that obtained by the traditional deterministic strategy. The proposed approach not only improves the robustness of the system but also demonstrates the importance of considering uncertainty in parametric optimization.

Optimizing the surface quality of heat-treated 2Cr13 stainless steel via electrochemical machining

The improvement of mechanical properties and surface quality was of great significance for materials. In this study, 2Cr13 stainless steel was subjected to the quenching and tempering treatment. The electrochemical machining approach was adopted for surface treatment. The results showed that the quenching and tempering treatment improved the Vickers microhardness of 2Cr13 stainless steel. The enhancement of microhardness was facilitated by the formation of tempered sorbite and grain refinement. Electrochemical machining provided high quality surfaces. The heat-treated workpice had more advantages in electrochemical machining efficiency. The polarization curves proved a downward shift of the self-corrosion potential for the heat-treated 2Cr13 stainless steel, which was strongly related to the electrochemical behavior. A mechanism model for promoting anode electrochemical dissolution was proposed.

Multiphase photoclinometry as applied to the lunar photometry with LROC NAC data

An original method for photometric and geometric correction of LROC NAC data with high resolution (up to 0.5 m/pix) has been developed. The technique is based on photogrammetry and multiphase photoclinometry and allows us to obtain a longitudinal slope map and digital elevation model (DEM) with the resolution of LROC NAC CDR input images as well as to map parameters of model phase function. Obtained DEMs, requiring only LROC NAC images and LRO SPICE-kernels, exhibit significantly fewer defects and artifacts compared to existing DEMs, because they are derived from the same images they correct (self-orthorectification).This method was used to study the area of the photometric anomaly, the Irregular Mare Patch (IMP) formation Ina. A zoning map of the correlation diagram of phase ratio vs. equigonal albedo shows significant differences in the optical (photometric) properties of the regolith for hummocky and blocky formations of the IMP Ina, compared to the surrounding areas, which indicates the different nature of their formation, age, and surface roughness, contradicting some models of the IMP formation. The analysis reveals the incompleteness or inconsistencies of previously proposed models of the IMP's formation mechanisms. The high-quality DEM of the Ina formation and surrounding area with a resolution of 0.5 m/pixel was constructed.

A maturity-driven selection model for effective digital transformation governance mechanisms in large organizations

PurposeThis research paper aims to conceptualize digital transformation governance and its conventional mechanisms and to present governance solutions tailored to an organization’s level of digital maturity. The objective is to provide a framework for large organizations to select appropriate governance mechanisms based on their digital maturity level, enabling them to effectively manage and govern their digital transformation journey.Design/methodology/approachThe study employs a meta-synthesis methodology, systematically reviewing and synthesizing findings from 175 academic papers and 31 reports/white papers. The research involves a rigorous qualitative approach, including literature search, selection of relevant texts, information extraction, analysis of qualitative findings, quality control and presentation of findings.FindingsThe proposed model suggests a three-tiered approach to digital transformation governance based on the organization’s digital maturity: “beginner,” “intermediate” and “advanced” stages. The findings indicate that as an organization advances in its digital maturity, its governance mechanism tends to be less centralized and involves multiple relevant units. Conversely, organizations with lower digital maturity require a more concentrated approach to digital governance.Research limitations/implicationsThe study is based on a systematic review and synthesis of existing literature. Further empirical research could validate and refine the proposed model.Practical implicationsBy using the proposed maturity-driven model, organizations can choose a more suitable and effective governance mechanism for the realization of their digital transformation roadmap based on their digital maturity level. The model offers a comprehensive framework for selecting and combining appropriate governance mechanisms at each maturity stage.Originality/valueThe proposed framework offers a strategic and novel yet practical tool, enabling organizations to advance their digital governance capabilities in sync with their transformation roadmap. The study consolidates dispersed findings and expands the range of viable governance mechanisms contingent on digital progression.

Electronic mechanical braking system executive mechanism design, calculation, and modeling based on dynamic control

Introduction: As science and technology develop, automobiles are moving toward intelligence and electrification and need better braking systems.Methods: To improve the braking system’s response speed and braking effect, a longitudinal dynamics control system for automobiles based on the electronic mechanical braking system was proposed, and the electronic mechanical braking system was improved through automatic disturbance rejection control.Results: The experimental results show that the time required for achieving the target clamping force in the electronic mechanical braking system using self-disturbance rejection control and proportional integral differential control is only 0.01 s, but there is an issue of excessive control in the proportional integral differential system between 0.12 s and 0.2 s, while the self-disturbance rejection controller does not have this problem. Meanwhile, regardless of the interference applied, the electronic mechanical braking system with automatic disturbance rejection control can ensure that the clamping force does not fluctuate. In the joint simulation experiment, the expected acceleration and actual acceleration can remain consistent, and if the expected braking force is 9000 N, then the actual braking force of the electronic mechanical brake (EMB) is also 9000 N.Discussion: The above results indicate that the vehicle longitudinal dynamics control system using the electronic mechanical braking system not only responds fast but also has a good braking effect, avoiding the problem of excessive control and improving the driving experience.