Data-driven modeling on anisotropic mechanical behavior of brain tissue with internal pressure

Brain tissue is one of the softest parts of the human body,composed of white matter and grey matter.The mechanical behavior of the brain tissue plays an essential role in regulating brain morphology and brain function.Besides,traumatic brain injury(TBI)and various brain diseases are also greatly influenced by the brain's mechanical properties.Whether white matter or grey matter,brain tissue contains multiscale structures composed of neurons,glial cells,fibers,blood vessels,etc.,each with different mechanical properties.As such,brain tissue exhibits complex mechanical behavior,usually with strong nonlinearity,heterogeneity,and directional dependence.Building a constitutive law for multiscale brain tissue using traditional function-based approaches can be very challenging.Instead,this paper proposes a data-driven approach to establish the desired mechanical model of brain tissue.We focus on blood vessels with internal pressure embedded in a white or grey matter matrix material to demonstrate our approach.The matrix is described by an isotropic or anisotropic nonlinear elastic model.A representative unit cell(RUC)with blood vessels is built,which is used to generate the stress-strain data under different internal blood pressure and various proportional displacement loading paths.The generated stress-strain data is then used to train a mechanical law using artificial neural networks to predict the macroscopic mechanical response of brain tissue under different internal pressures.Finally,the trained material model is implemented into finite element software to predict the mechanical behavior of a whole brain under intracranial pressure and distributed body forces.Compared with a direct numerical simulation that employs a reference material model,our proposed approach greatly reduces the computational cost and improves modeling efficiency.The predictions made by our trained model demonstrate sufficient accuracy.Specifically,we find that the level of internal blood pressure can greatly influence stress distribution and determine the possible related damage behaviors.

Effects of counter-current driven by electron cyclotron waves on neoclassical tearing mode suppression

Through theoretical analysis,we construct a physical model that includes the influence of counter-external driven current opposite to the plasma current direction in the neoclassical tearing mode(NTM).The equation is used with this model to obtain the modified Rutherford equation with co-current and counter-current contributions.Consistent with the reported experimental results,numerical simulations have shown that the localized counter external current can only partially suppress NTM when it is far from the resonant magnetic surface.Under some circumstances,the Ohkawa mechanism dominated current drive(OKCD)by electron cyclotron waves can concurrently create both co-current and counter-current.In this instance,the minimal electron cyclotron wave power that suppresses a particular NTM was calculated by the Rutherford equation.The result is marginally less than when taking co-current alone into consideration.As a result,to suppress NTM using OKCD,one only needs to align the co-current with a greater OKCD peak well with the resonant magnetic surface.The effect of its lower counter-current does not need to be considered because the location of the counter-current deviates greatly from the resonant magnetic surface.

Investigation of system parameters towards safer impact based shock-to-detonation transition in a novel laser driven flyer plate prototype

Laser driven flyer plate technology offers improved safety and reliability for detonation of explosives in industrial applications ranging from mining and stone quarrying to the aerospace and defense industries.This study is based on developing a safer laser driven flyer plate prototype comprised of a laser initiator and a flyer plate subsystem that can be used with secondary explosives.System parameters were optimized to initiate the shock-to-detonation transition(SDT)of a secondary explosive based on the impact created by the flyer plate on the explosive surface.Rupture of the flyer was investigated at the mechanically weakened region located on the interface of these subsystems,where the product gases from the deflagration of the explosive provide the required energy.A bilayer energetic material was used,where the first layer consisted of a pyrotechnic component,zirconium potassium perchlorate(ZPP),for sustaining the ignition by the laser beam and the second layer consisted of an insensitive explosive,cyclotetramethylene-tetranitramine(HMX),for deflagration.A plexiglass interface was used to enfold the energetic material.The focal length of the laser beam from the diode was optimized to provide a homogeneous beam profile with maximum power at the surface of the ZPP.Closed bomb experiments were conducted in an internal volume of 10 cm^(3) for evaluation of performance.Dependency of the laser driven flyer plate system output on confinement,explosive density,and laser beam power were analyzed.Measurements using a high-speed camera resulted in a flyer velocity of 670±20 m/s that renders the prototype suitable as a laser detonator in applications,where controlled employment of explosives is critical.

Effect of power supply parameters on discharge characteristics and sterilization efficiency of magnetically driven rotating gliding arc

Plasma sterilization is a new generation of high-tech sterilization method that is fast,safe,and pollution free.It is widely used in medical,food,and environmental protection fields.Home air sterilization is an emerging field of plasma application,which puts higher requirements on the miniaturization,operational stability,and operating cost of plasma device.In this study,a novel magnetically driven rotating gliding arc(MDRGA)discharge device was used to sterilize Lactobacillus fermentation.Compared with the traditional gas-driven gliding arc,this device has a simple structure and a more stable gliding arc.Simulation using COMSOL Multiphysics showed that adding permanent magnets can form a stable magnetic field,which is conducive to the formation of gliding arcs.Experiments on the discharge performance,ozone concentration,and sterilization effect were conducted using different power supply parameters.The results revealed that the MDRGA process can be divided into three stages:starting,gliding,and extinguishing.Appropriate voltage was the key factor for stable arc gliding,and both high and low voltages were not conducive to stable arc gliding and ozone production.In this experimental setup,the sterilization effect was the best at 6.6 kV.A high modulation duty ratio was beneficial for achieving stable arc gliding.However,when the duty ratio exceeded a certain value,the improvement in the sterilization effect was slow.Therefore,considering the sterilization effect and energy factors comprehensively,we chose 80%as the optimal modulation duty ratio for this experimental device.

Research on the Microstructure Construction Technology of Fully Degraded Polymer Vascular Stent Based on Electric Field Driven 3D Printing

The so-called fourth-generation biodegradable vascular stent has become a research hotspot in thefield of bioengineering because of its good degradation ability and drug-loading characteristics.However,the preparationof polymer-degraded vascular stents is affected by known problem such as poor processflexibility,low formingaccuracy,large diameter wall thickness,limited complex pore structure,weak mechanical properties of radial support and high process cost.In this study,a deposition technique based on a high-voltage electric-field-driven continuous rotating jet is proposed to fabricate fully degraded polymer vascular stents.The experimental results showthat,due to the rotation of the deposition axis,the deposition direction of PCL(polycaprolactone)micro-jet isalways tangent to the surface of the deposition axis.The direction of the viscous drag force is also consistent withthe deposition direction of the jet.It is shown that by setting different rotation speeds of deposition axisωandlinear motion speeds of the nozzle V,the direction of rotation,pitch and angle of the individual printed spiralcurve can be precisely tuned.In the process of multiple spiral curves matching the deposition forming thin walltube mesh,the mesh shape and size of the thin wall tube can be accurately controlled by changing the number ofmatching spiral curves and the size of the matching position bias distance.Finally,the characteristics of a PCLtubular stent sample(with uniform-size microfibers and mesh shape),fabricated under the appropriate processparameters are described in detail.

Data Driven Vibration Control:A Review

With the ongoing advancements in sensor networks and data acquisition technologies across various systems like manufacturing,aviation,and healthcare,the data driven vibration control(DDVC)has attracted broad interests from both the industrial and academic communities.Input shaping(IS),as a simple and effective feedforward method,is greatly demanded in DDVC methods.It convolves the desired input command with impulse sequence without requiring parametric dynamics and the closed-loop system structure,thereby suppressing the residual vibration separately.Based on a thorough investigation into the state-of-the-art DDVC methods,this survey has made the following efforts:1)Introducing the IS theory and typical input shapers;2)Categorizing recent progress of DDVC methods;3)Summarizing commonly adopted metrics for DDVC;and 4)Discussing the engineering applications and future trends of DDVC.By doing so,this study provides a systematic and comprehensive overview of existing DDVC methods from designing to optimizing perspectives,aiming at promoting future research regarding this emerging and vital issue.

MPC-based Torque Distribution for Planar Motion of Four-wheel Independently Driven Electric Vehicles:Considering Motor Models and Iron Losses

The most critical obstacle for four-wheel independently driven electric vehicles(4WID-EVs)is the driving range.Being the actuators of 4WID-EVs,motors account for its major power consumption.In this sense,by properly distributing torques to minimize the power consumption,the driving range of 4WID-EV can be effectively improved.This paper proposes a model predictive control(MPC)-based torque distribution scheme,which minimizes the power consumption of 4WID-EVs while guaranteeing its tracking performance of planar motions.By incorporating the motor model considering iron losses,the optimal torque distribution can be achieved without an additional torque controller.Also,for this reason,the proposed control scheme is computationally efficient,since the power consumption term to be optimized,which is expressed as the product of the motor voltages and currents,is much simpler than that derived from the efficiency map.With reasonable simplification and linearization,the MPC problem is converted to a quadratic programming problem,which can be solved efficiently.The simulation results in MATLAB and CarSim co-simulation environments demonstrate that the proposed scheme effectively reduces power consumption with guaranteed tracking performance.

Power Consumption Characteristics Research on Mobile System of Electrically Driven Large-Load-Ratio Six-Legged Robot

The electrically driven large-load-ratio six-legged robot with engineering capability can be widely used in outdoor and planetary exploration.However,due to the particularity of its parallel structure,the effective utilization rate of energy is not high,which has become an important obstacle to its practical application.To research the power consumption characteristics of robot mobile system is beneficial to speed up it toward practicability.Based on the configuration and walking modes of robot,the mathematical model of the power consumption of mobile system is set up.In view of the tripod gait is often selected for the six-legged robots,the simplified power consumption model of mobile system under the tripod gait is established by means of reducing the dimension of the robot’s statically indeterminate problem and constructing the equal force distribution.Then,the power consumption of robot mobile system is solved under different working conditions.The variable tendencies of the power consumption of robot mobile system are respectively obtained with changes in the rotational angles of hip joint and knee joint,body height,and span.The articulated rotational zones and the ranges of body height and span are determined under the lowest power consumption.According to the walking experiments of prototype,the variable tendencies of the average power consumption of robot mobile system are respectively acquired with changes in duty ratio,body height,and span.Then,the feasibility and correctness of theory analysis are verified in the power consumption of robot mobile system.The proposed analysis method in this paper can provide a reference on the lower power research of the large-load-ratio multi-legged robots.

A deep learning driven hybrid beamforming method for millimeter wave MIMO system

The hybrid beamforming is a promising technology for the millimeter wave MIMO system,which provides high spectrum efficiency,high data rate transmission,and a good balance between transmission performance and hardware complexity.The most existing beamforming systems transmit multiple streams by formulating multiple orthogonal beams.However,the Neural network Hybrid Beamforming(NHB)adopts a totally different strategy,which combines multiple streams into one and transmits by employing a high-order non-orthogonal modulation strategy.Driven by the Deep Learning(DL)hybrid beamforming,in this work,we propose a DL-driven nonorthogonal hybrid beamforming for the single-user multiple streams scenario.We first analyze the beamforming strategy of NHB and prove it with better Bit Error Rate(BER)performance than the orthogonal hybrid beamforming even with the optimal power allocation.Inspired by the NHB,we propose a new DL-driven beamforming scheme to simulate the NHB behavior,which avoids time-consuming neural network training and achieves better BERs than traditional hybrid beamforming.Moreover,our simulation results demonstrate that the DL-driven nonorthogonal beamforming outperforms its traditional orthogonal beamforming counterpart in the presence of subconnected schemes and imperfect Channel State Information(CSI).

Deoxyribonucleic acid methylation driven aberrations in pancreatic cancer-related pathways

Pancreatic cancer(PanCa)presents a catastrophic disease with poor overall survival at advanced stages,with immediate requirement of new and effective treatment options.Besides genetic mutations,epigenetic dysregulation of signaling pathway-associated enriched genes are considered as novel therapeutic target.Mechanisms beneath the deoxyribonucleic acid methylation and its utility in developing of epi-drugs in PanCa are under trails.Combinations of epigenetic medicines with conventional cytotoxic treatments or targeted therapy are promising options to improving the dismal response and survival rate of PanCa patients.Recent studies have identified potentially valid pathways that support the prediction that future PanCa clinical trials will include vigorous testing of epigenomic therapies.Epigenetics thus promises to generate a significant amount of new knowledge of biological and medical importance.Our review could identify various components of epigenetic mechanisms known to be involved in the initiation and development of pancreatic ductal adenocarcinoma and related precancerous lesions,and novel pharmacological strategies that target these components could potentially lead to breakthroughs.We aim to highlight the possibilities that exist and the potential therapeutic interventions.

Implosion Plasma Driven Fusion Pellet of Inertial Confinement(A Short Memorandum)

The implosion plasma drive fusion pellet of inertial confinement is a concept related to nuclear fusion,a process in which atomic nuclei combine to form heavier nuclei,releasing a large amount of energy in the process.The implosion plasma drive fusion pellet is a potential fuel source for achieving controlled nuclear fusion.ICF(inertial confinement fusion)is a technique used to achieve fusion by compressing a small target containing fusion fuel to extremely high densities and temperatures using lasers or other methods.The implosion plasma drive fusion pellet concept involves using a small pellet of deuterium and tritium(two isotopes of hydrogen)as fusion fuel,and then rapidly heating and compressing it using a pulsed power system.The implosion process creates a high-pressure plasma that ignites the fusion reactions,releasing energy in the form of neutrons and charged particles.The resulting energy can be captured and used for power generation.This technology is still in the experimental stage,and significant research and development is required to make it commercially viable.However,it has the potential to provide a virtually limitless source of clean energy with no greenhouse gas emissions or long-term radioactive waste.Be that as it may,ICF has to get exact control of the implosion process,mitigate insecurities,and create modern materials and advances to resist the extraordinary conditions of the combined response.

On the Effects of Driven Element L/D Ratio and Length in VHF-SHF Yagi-Uda Arrays

While the Yagi-Uda array has been studied for decades, one issue appears to have received less attention than perhaps it should, namely, the effects on performance of the array’s driven element length and its length-to-diameter ratio. This paper looks at that question. It shows that decreasing the L/D ratio increases impedance bandwidth, but it may shift the IBW band sufficiently far from the design frequency that other parameters such as gain and front-to-back ratio probably are adversely affected. It also shows that array performance is not relatively independent of element diameters. This paper also investigates the effect of lengthening the driven element, which can substantially improve IBW. Several iterations of a 3-element prototype and improved arrays are modeled with the Method of Moments and discussed in detail. A five step design procedure is recommended and applied to a Genetic Algorithm-optimized 3-element Yagi at 146 MHz. This array exhibits excellent performance in terms of gain, front-to-back ratio, and especially impedance bandwidth (nearly 14% for voltage standing wave ratio ≤ 2:1 with two frequencies at which 50 ? is almost perfectly matched). While the analysis and recommended design steps are applied to cylindrical array elements, which commonly are aluminum tubing for stand-alone VHF-SHF Yagis, they can be applied to other element geometries as well using equivalent cylindrical radii, for example, Printed Circuit Board traces for planar arrays. One consequence of lengthening the driven element while reducing its L/D ratio is that some reactance is introduced at the array feedpoint which must be tuned out, and two approaches for doing so are suggested.

Solar-Driven Water Treatment: New Technologies, Challenges, and Futures

In this review, the new solar water treatment technologies, including solar water desalination in two direct and indirect methods, are comprehensively presented. Recent advances and applications of five major solar desalination technologies include solar-powered humidification–dehumidification, multi-stage flash desalination, multi-effect desalination, RO, and solar stills. Each technology’s productivity, energy consumption, and water production costs are presented. Also, common methods of solar water disinfection have been reviewed as one of the common and low-cost methods of water treatment, especially in areas with no access to drinking water. However, although desalination technologies have many social, economic, and public health benefits, they are energy-intensive and negatively affect the environment. In addition, the disposal of brine from the desalination processes is one of the most challenging and costly issues. In this regard, the environmental effects of desalination technologies are presented and discussed. Among direct solar water desalination technologies, solar still technology is a low-cost, low-tech, and low-investment method suitable for remote areas, especially in developing countries with low financial support and access to skilled workers. Indirect solar-driven water desalination technologies, including thermal and membrane technologies, are more reliable and technically more mature. Recently, RO technology has received particular attention thanks to its lower energy demand, lower cost, and available solutions to increase membrane durability. Disposal of brines can account for much of the water cost and potentially negatively affect the environment. Therefore, in addition to efforts to improve the efficiency and reduce the cost of solar technologies and water treatment processes, future research studies should consider developing new solutions to this issue.

Modeling of Mixed Convection in a Lid Driven Wavy Enclosure with Two Square Blocks Placed at Different Positions

The purpose of this paper is to investigate the simulation of mixed convection in a lid-driven wavy enclosure with blocks positioned at various positions. This study also examined the impact of the longitudinal position of the heated block on heat transfer enhancement. The Galerkin weighted residual finite element method is employed to computationally solve the governing equations of Navier-Stokes, thermal energy, and mass conservation. The enclosure consists of two square heated blocks strategically placed at different heights—firstly, one set is closer to the bottom surface;secondly, one set is nearer to the middle area and finally, one set is closer to the upper undulating surface of the enclosure. The wavy top wall’s thermal insulation, along with active heating of the bottom wall and blocks, generates a dynamic convective atmosphere. In addition, the left wall ascends as the right wall falls, causing the flow formed by the lid. The study investigates the impact of the Richardson number on many factors, such as streamlines, isotherms, dimensionless temperature, velocity profiles, and average Nusselt numbers. These impacts are depicted through graphical illustrations. In all instances, two counter-rotating eddies were generated within the cage. Higher rotating speed consistently leads to improved performance, irrespective of other characteristics. Furthermore, an ideal amalgamation of the regulating factors would lead to increased heat transmission.

Making Data-Driven Transportation Decisions for Freight Operations

Using Louisiana’s Interstate system, this paper aims to demonstrate how data can be used to evaluate freight movement reliability, economy, and safety of truck freight operations to improve decision-making. Data mainly from the National Performance Management Research Data Set (NPMRDS) and the Louisiana Crash Database were used to analyze Truck Travel Time Reliability Index, commercial vehicle User Delay Costs, and commercial vehicle safety. The results indicate that while Louisiana’s Interstate system remained reliable over the years, some segments were found to be unreliable, which were annually less than 12% of the state’s Interstate system mileage. The User Delay Costs by commercial vehicles on these unreliable segments were, on average, 65.45% of the User Delay Cost by all vehicles on the Interstate highway system between 2016 and 2019, 53.10% between 2020 and 2021, and 70.36% in 2022, which are considerably high. These disproportionate ratios indicate the economic impact of the unreliability of the Interstate system on commercial vehicle operations. Additionally, though the annual crash frequencies remained relatively constant, an increasing proportion of commercial vehicles are involved in crashes, with segments (mileposts) that have high crash frequencies seeming to correspond with locations with recurring congestion on the Interstate highway system. The study highlights the potential of using data to identify areas that need improvement in transportation systems to support better decision-making.

Data-Driven Model Identification and Control of the Inertial Systems

In the synthesis of the control algorithm for complex systems, we are often faced with imprecise or unknown mathematical models of the dynamical systems, or even with problems in finding a mathematical model of the system in the open loop. To tackle these difficulties, an approach of data-driven model identification and control algorithm design based on the maximum stability degree criterion is proposed in this paper. The data-driven model identification procedure supposes the finding of the mathematical model of the system based on the undamped transient response of the closed-loop system. The system is approximated with the inertial model, where the coefficients are calculated based on the values of the critical transfer coefficient, oscillation amplitude and period of the underdamped response of the closed-loop system. The data driven control design supposes that the tuning parameters of the controller are calculated based on the parameters obtained from the previous step of system identification and there are presented the expressions for the calculation of the tuning parameters. The obtained results of data-driven model identification and algorithm for synthesis the controller were verified by computer simulation.

Domain-Oriented Data-Driven Data Mining Based on Rough Sets

Data mining (also known as Knowledge Discovery in Databases - KDD) is defined as the nontrivial extraction of implicit, previously unknown, and potentially useful information from data. The aims and objectives of data mining are to discover knowledge of interest to user needs.Data mining is really a useful tool in many domains such as marketing, decision making, etc. However, some basic issues of data mining are ignored. What is data mining? What is the product of a data mining process? What are we doing in a data mining process? Is there any rule we should obey in a data mining process? In order to discover patterns and knowledge really interesting and actionable to the real world Zhang et al proposed a domain-driven human-machine-cooperated data mining process.Zhao and Yao proposed an interactive user-driven classification method using the granule network. In our work, we find that data mining is a kind of knowledge transforming process to transform knowledge from data format into symbol format. Thus, no new knowledge could be generated (born) in a data mining process. In a data mining process, knowledge is just transformed from data format, which is not understandable for human, into symbol format,which is understandable for human and easy to be used.It is similar to the process of translating a book from Chinese into English.In this translating process,the knowledge itself in the book should remain unchanged. What will be changed is the format of the knowledge only. That is, the knowledge in the English book should be kept the same as the knowledge in the Chinese one.Otherwise, there must be some mistakes in the translating proces, that is, we are transforming knowledge from one format into another format while not producing new knowledge in a data mining process. The knowledge is originally stored in data (data is a representation format of knowledge). Unfortunately, we can not read, understand, or use it, since we can not understand data. With this understanding of data mining, we proposed a data-driven knowledge acquisition method based on rough sets. It also improved the performance of classical knowledge acquisition methods. In fact, we also find that the domain-driven data mining and user-driven data mining do not conflict with our data-driven data mining. They could be integrated into domain-oriented data-driven data mining. It is just like the views of data base. Users with different views could look at different partial data of a data base. Thus, users with different tasks or objectives wish, or could discover different knowledge (partial knowledge) from the same data base. However, all these partial knowledge should be originally existed in the data base. So, a domain-oriented data-driven data mining method would help us to extract the knowledge which is really existed in a data base, and really interesting and actionable to the real world.

Material driven workability simulation by FEM including 3D processing maps for magnesium alloy

The three-dimensional （3D） processing maps considering strain based on the two-dimensional （2D） processing maps proposed by PRASAD can describe the distribution of the efficiency of power dissipation and flow instability regions at various temperatures, strain rates and strains, which exhibit intrinsic workability related to material itself. Finite element （FE） simulation can obtain the distribution of strain, strain rate, temperature and die filling status, which indicates state-of-stress （SOS） workability decided by die shape and different processing conditions. On the basis of this, a new material driven analysis method for hot deformation was put forward by the combination of FE simulation with 3D processing maps, which can demonstrate material workability of the entire hot deformation process including SOS workability and intrinsic workability. The hot forging process for hard-to-work metal magnesium alloy was studied, and the 3D thermomechanical FE simulation including 3D processing maps of complex hot forging spur bevel gear was first conducted. The hot forging experiments were carried out. The results show that the new method is reasonable and suitable to determine the aoorooriate nrocess narameters.

ARCHITECTURE OF DYNAMIC DATA DRIVEN SIMULATION FOR WILDFIRE AND ITS REALIZATION

Dynamic data driven simulation （DDDS） is proposed to improve the model by incorporaing real data from the practical systems into the model. Instead of giving a static input, multiple possible sets of inputs are fed into the model. And the computational errors are corrected using statistical approaches. It involves a variety of aspects, including the uncertainty modeling, the measurement evaluation, the system model and the measurement model coupling ,the computation complexity, and the performance issue. Authors intend to set up the architecture of DDDS for wildfire spread model, DEVS-FIRE, based on the discrete event speeification （DEVS） formalism. The experimental results show that the framework can track the dynamically changing fire front based on fire sen- sor data, thus, it provides more aecurate predictions.

Winds and buoyancy-driven circulation in the Tampa Bay

The present study is concentrated on the empirical studies on the circulation in the Tampa Bay by analyzing velocity data at the Skyway Bridge Station in the Tampa Bay. Analyses focus on three factors responsible for the circulation: tides, winds and buoyancy gradients. The analysis of the current data obtained at the Skyway Bridge Station shows these three components of the circulation: the tidal currents are nearly uniform with depth; a vigorous and persistent buoyancy-driven mean now is directed into the bay at this location with speed of about 6 -- 8 cm/s; and synoptic scale wind fluctuations result in similarly large current fluctuations with winds blowing into the bay causing currents to flow out of the bay, and the versa.