Pro/ ENGINEER软件二次开发技术(英文)

Pro/ENGINEER软件的二次开发接口 Pro/TOOLKIT是一个用户化的工具箱 ,文章论述了 Pro/TOOLKIT的工作方式及应用程序的编译和注册步骤 ,以方便 Pro/ENGINEER软件的二次开发的应用 .

Constructing a biofunctionalized 3D-printed gelatin/sodium alginate/chitosan tri-polymer complex scaffold with improvised biological andmechanical properties for bone-tissue engineering

Sodium alginate(SA)/chitosan(CH)polyelectrolyte scaffold is a suitable substrate for tissue-engineering application.The present study deals with further improvement in the tensile strength and biological properties of this type of scaffold to make it a potential template for bone-tissue regeneration.We experimented with adding 0%–15%(volume fraction)gelatin(GE),a protein-based biopolymer known to promote cell adhesion,proliferation,and differentiation.The resulting tri-polymer complex was used as bioink to fabricate SA/CH/GEmatrices by three-dimensional(3D)printing.Morphological studies using scanning electron microscopy revealed the microfibrous porous architecture of all the structures,which had a pore size range of 383–419μm.X-ray diffraction and Fourier-transform infrared spectroscopy analyses revealed the amorphous nature of the scaffold and the strong electrostatic interactions among the functional groups of the polymers,thereby forming polyelectrolyte complexes which were found to improve mechanical properties and structural stability.The scaffolds exhibited a desirable degradation rate,controlled swelling,and hydrophilic characteristics which are favorable for bone-tissue engineering.The tensile strength improved from(386±15)to(693±15)kPa due to the increased stiffness of SA/CH scaffolds upon addition of gelatin.The enhanced protein adsorption and in vitro bioactivity(forming an apatite layer)confirmed the ability of the SA/CH/GE scaffold to offer higher cellular adhesion and a bone-like environment to cells during the process of tissue regeneration.In vitro biological evaluation including the MTT assay,confocal microscopy analysis,and alizarin red S assay showed a significant increase in cell attachment,cell viability,and cell proliferation,which further improved biomineralization over the scaffold surface.In addition,SA/CH containing 15%gelatin designated as SA/CH/GE15 showed superior performance to the other fabricated 3D structures,demonstrating its potential for use in bone-tissue engineering.

Precursor engineering enables high-performance all-inorganic CsPbIBr_(2) perovskite solar cells with a record efficiency approaching 13%

All-inorganic CsPbIBr_(2) perovskite has attracted widespread attention in photovoltaic and other optoelectronic devices because of its superior thermal stability.However,the deposition of high-quality solutionprocessed CsPbIBr_(2) perovskite films with large thicknesses remains challenging.Here,we develop a triple-component precursor(TCP) by employing lead bromide,lead iodide,and cesium bromide,to replace the most commonly used double-component precursor(DCP) consisting of lead bromide and cesium iodide.Remarkably,the TCP system significantly increases the solution concentration to 1.3 M,leading to a larger film thickness(~390 nm) and enhanced light absorption.The resultant CsPbIBr_(2) films were evaluated in planar n-i-p structured solar cells,which exhibit a considerably higher optimal photocurrent density of 11.50 mA cm^(-2) in comparison to that of DCP-based devices(10.69 mA cm^(-2)).By adopting an organic surface passivator,the maximum device efficiency using TCP is further boosted to a record efficiency of 12.8% for CsPbIBr_(2) perovskite solar cells.

A Comparative Study of Metaheuristic Optimization Algorithms for Solving Real-World Engineering Design Problems

Real-world engineering design problems with complex objective functions under some constraints are relatively difficult problems to solve.Such design problems are widely experienced in many engineering fields,such as industry,automotive,construction,machinery,and interdisciplinary research.However,there are established optimization techniques that have shown effectiveness in addressing these types of issues.This research paper gives a comparative study of the implementation of seventeen new metaheuristic methods in order to optimize twelve distinct engineering design issues.The algorithms used in the study are listed as:transient search optimization(TSO),equilibrium optimizer(EO),grey wolf optimizer(GWO),moth-flame optimization(MFO),whale optimization algorithm(WOA),slimemould algorithm(SMA),harris hawks optimization(HHO),chimp optimization algorithm(COA),coot optimization algorithm(COOT),multi-verse optimization(MVO),arithmetic optimization algorithm(AOA),aquila optimizer(AO),sine cosine algorithm(SCA),smell agent optimization(SAO),and seagull optimization algorithm(SOA),pelican optimization algorithm(POA),and coati optimization algorithm(CA).As far as we know,there is no comparative analysis of recent and popular methods against the concrete conditions of real-world engineering problems.Hence,a remarkable research guideline is presented in the study for researchersworking in the fields of engineering and artificial intelligence,especiallywhen applying the optimization methods that have emerged recently.Future research can rely on this work for a literature search on comparisons of metaheuristic optimization methods in real-world problems under similar conditions.

Evaluations of Chris-Jerry Data Using Generalized Progressive Hybrid Strategy and Its Engineering Applications

A new one-parameter Chris-Jerry distribution,created by mixing exponential and gamma distributions,is discussed in this article in the presence of incomplete lifetime data.We examine a novel generalized progressively hybrid censoring technique that ensures the experiment ends at a predefined period when the model of the test participants has a Chris-Jerry(CJ)distribution.When the indicated censored data is present,Bayes and likelihood estimations are used to explore the CJ parameter and reliability indices,including the hazard rate and reliability functions.We acquire the estimated asymptotic and credible confidence intervals of each unknown quantity.Additionally,via the squared-error loss,the Bayes’estimators are obtained using gamma prior.The Bayes estimators cannot be expressed theoretically since the likelihood density is created in a complex manner;nonetheless,Markov-chain Monte Carlo techniques can be used to evaluate them.The effectiveness of the investigated estimations is assessed,and some recommendations are given using Monte Carlo results.Ultimately,an analysis of two engineering applications,such as mechanical equipment and ball bearing data sets,shows the applicability of the proposed approaches that may be used in real-world settings.

Biomaterials and tissue engineering in traumatic brain injury:novel perspectives on promoting neural regeneration

Traumatic brain injury is a serious medical condition that can be attributed to falls, motor vehicle accidents, sports injuries and acts of violence, causing a series of neural injuries and neuropsychiatric symptoms. However, limited accessibility to the injury sites, complicated histological and anatomical structure, intricate cellular and extracellular milieu, lack of regenerative capacity in the native cells, vast variety of damage routes, and the insufficient time available for treatment have restricted the widespread application of several therapeutic methods in cases of central nervous system injury. Tissue engineering and regenerative medicine have emerged as innovative approaches in the field of nerve regeneration. By combining biomaterials, stem cells, and growth factors, these approaches have provided a platform for developing effective treatments for neural injuries, which can offer the potential to restore neural function, improve patient outcomes, and reduce the need for drugs and invasive surgical procedures. Biomaterials have shown advantages in promoting neural development, inhibiting glial scar formation, and providing a suitable biomimetic neural microenvironment, which makes their application promising in the field of neural regeneration. For instance, bioactive scaffolds loaded with stem cells can provide a biocompatible and biodegradable milieu. Furthermore, stem cells-derived exosomes combine the advantages of stem cells, avoid the risk of immune rejection, cooperate with biomaterials to enhance their biological functions, and exert stable functions, thereby inducing angiogenesis and neural regeneration in patients with traumatic brain injury and promoting the recovery of brain function. Unfortunately, biomaterials have shown positive effects in the laboratory, but when similar materials are used in clinical studies of human central nervous system regeneration, their efficacy is unsatisfactory. Here, we review the characteristics and properties of various bioactive materials, followed by the introduction of applications based on biochemistry and cell molecules, and discuss the emerging role of biomaterials in promoting neural regeneration. Further, we summarize the adaptive biomaterials infused with exosomes produced from stem cells and stem cells themselves for the treatment of traumatic brain injury. Finally, we present the main limitations of biomaterials for the treatment of traumatic brain injury and offer insights into their future potential.

Developing Lexicons for Enhanced Sentiment Analysis in Software Engineering:An Innovative Multilingual Approach for Social Media Reviews

Sentiment analysis is becoming increasingly important in today’s digital age, with social media being a significantsource of user-generated content. The development of sentiment lexicons that can support languages other thanEnglish is a challenging task, especially for analyzing sentiment analysis in social media reviews. Most existingsentiment analysis systems focus on English, leaving a significant research gap in other languages due to limitedresources and tools. This research aims to address this gap by building a sentiment lexicon for local languages,which is then used with a machine learning algorithm for efficient sentiment analysis. In the first step, a lexiconis developed that includes five languages: Urdu, Roman Urdu, Pashto, Roman Pashto, and English. The sentimentscores from SentiWordNet are associated with each word in the lexicon to produce an effective sentiment score. Inthe second step, a naive Bayesian algorithm is applied to the developed lexicon for efficient sentiment analysis ofRoman Pashto. Both the sentiment lexicon and sentiment analysis steps were evaluated using information retrievalmetrics, with an accuracy score of 0.89 for the sentiment lexicon and 0.83 for the sentiment analysis. The resultsshowcase the potential for improving software engineering tasks related to user feedback analysis and productdevelopment.

Building Custom Spreadsheet Functions with Python: End-User Software Engineering Approach

End-user computing empowers non-developers to manage data and applications, enhancing collaboration and efficiency. Spreadsheets, a prime example of end-user programming environments widely used in business for data analysis. However, Excel functionalities have limits compared to dedicated programming languages. This paper addresses this gap by proposing a prototype for integrating Python’s capabilities into Excel through on-premises desktop to build custom spreadsheet functions with Python. This approach overcomes potential latency issues associated with cloud-based solutions. This prototype utilizes Excel-DNA and IronPython. Excel-DNA allows creating custom Python functions that seamlessly integrate with Excel’s calculation engine. IronPython enables the execution of these Python (CSFs) directly within Excel. C# and VSTO add-ins form the core components, facilitating communication between Python and Excel. This approach empowers users with a potentially open-ended set of Python (CSFs) for tasks like mathematical calculations, statistical analysis, and even predictive modeling, all within the familiar Excel interface. This prototype demonstrates smooth integration, allowing users to call Python (CSFs) just like standard Excel functions. This research contributes to enhancing spreadsheet capabilities for end-user programmers by leveraging Python’s power within Excel. Future research could explore expanding data analysis capabilities by expanding the (CSFs) functions for complex calculations, statistical analysis, data manipulation, and even external library integration. The possibility of integrating machine learning models through the (CSFs) functions within the familiar Excel environment.

Analysis on the development of chemically-improved soil in railway engineering

Purpose-Explore the development trend of chemically-improved soil in railway engineering.Design/methodology/approach–In this paper,the technical standards home and abroad were analyzed.Laboratory test,field test and monitoring were carried out.Findings–The performance design system of the chemically-improved soil should be established.Originality/value–On the basis of the performance design,the test methods and standards for various properties of chemically-improved soil should be established to evaluate the improvement effect and control the engineering quality.

Accuracy comparison and improvement for state of health estimation of lithium-ion battery based on random partial recharges and feature engineering

State of health(SOH)estimation of e-mobilities operated in real and dynamic conditions is essential and challenging.Most of existing estimations are based on a fixed constant current charging and discharging aging profiles,which overlooked the fact that the charging and discharging profiles are random and not complete in real application.This work investigates the influence of feature engineering on the accuracy of different machine learning(ML)-based SOH estimations acting on different recharging sub-profiles where a realistic battery mission profile is considered.Fifteen features were extracted from the battery partial recharging profiles,considering different factors such as starting voltage values,charge amount,and charging sliding windows.Then,features were selected based on a feature selection pipeline consisting of filtering and supervised ML-based subset selection.Multiple linear regression(MLR),Gaussian process regression(GPR),and support vector regression(SVR)were applied to estimate SOH,and root mean square error(RMSE)was used to evaluate and compare the estimation performance.The results showed that the feature selection pipeline can improve SOH estimation accuracy by 55.05%,2.57%,and 2.82%for MLR,GPR and SVR respectively.It was demonstrated that the estimation based on partial charging profiles with lower starting voltage,large charge,and large sliding window size is more likely to achieve higher accuracy.This work hopes to give some insights into the supervised ML-based feature engineering acting on random partial recharges on SOH estimation performance and tries to fill the gap of effective SOH estimation between theoretical study and real dynamic application.

Model-Based Systems Engineering Approach to Design a Human Settlement to Better Serve Displaced People

The challenge of transitioning from temporary humanitarian settlements to more sustainable human settlements is due to a significant increase in the number of forcibly displaced people over recent decades, difficulties in providing social services that meet the required standards, and the prolongation of emergencies. Despite this challenging context, short-term considerations continue to guide their planning and management rather than more integrated, longer-term perspectives, thus preventing viable, sustainable development. Over the years, the design of humanitarian settlements has not been adapted to local contexts and perspectives, nor to the dynamics of urbanization and population growth and data. In addition, the current approach to temporary settlement harms the environment and can strain limited resources. Inefficient land use and ad hoc development models have compounded difficulties and generated new challenges. As a result, living conditions in settlements have deteriorated over the last few decades and continue to pose new challenges. The stakes are such that major shortcomings have emerged along the way, leading to disruption, budget overruns in a context marked by a steady decline in funding. However, some attempts have been made to shift towards more sustainable approaches, but these have mainly focused on vague, sector-oriented themes, failing to consider systematic and integration views. This study is a contribution in addressing these shortcomings by designing a model-driving solution, emphasizing an integrated system conceptualized as a system of systems. This paper proposes a new methodology for designing an integrated and sustainable human settlement model, based on Model-Based Systems Engineering and a Systems Modeling Language to provide valuable insights toward sustainable solutions for displaced populations aligning with the United Nations 2030 agenda for sustainable development.

Construction Technology of Lightning Protection Devices in Building Electrical Installation Engineering

To better improve the electrical safety of buildings and fulfill the role of lightning protection and grounding,this article combines cases and discusses seven aspects of lightning protection devices’construction technology.These aspects include the lightning protection classification of buildings,air terminals,down conductors,grounding devices,division of lightning protection zones,and lightning electromagnetic pulse shielding.Through the introduction of this article,readers can gain a comprehensive understanding of the application and value of lightning protection grounding construction technology in building electrical installation projects.

Financial Calculation Problems and Countermeasure Analysis of Large-Scale Engineering Construction Projects

The financial aspects of large-scale engineering construction projects profoundly influence their success.Strengthening cost control and establishing a scientific financial evaluation system can enhance the project’s economic benefits,minimize unnecessary costs,and provide decision-makers with a robust financial foundation.Additionally,implementing an effective cash flow control mechanism and conducting a comprehensive assessment of potential project risks can ensure financial stability and mitigate the risk of fund shortages.Developing a practical and feasible fundraising plan,along with stringent fund management practices,can prevent fund wastage and optimize fund utilization efficiency.These measures not only facilitate smooth project progression and improve project management efficiency but also enhance the project’s economic and social outcomes.

The Determination Method of Product Engineering Features Based on Linguistic Variables

To overcome the problem of imprecise and unclear information in the development of quality functions,a method for determining the priority of engineering features based on mixed linguistic variables is proposed.First,the evaluation member uses the determined linguistic variable to give the correlation strength evaluation matrix of customer requirements and engineering features.Secondly,the relative importance of the evaluation member and customer requirements are aggregated.Finally,the priority of engineering features is obtained by calculating the deviation.The feasibility and practicability of this method are proven by taking the design of a new product of a long bag low-pressure pulse dust collector as an example.

Biomimetic natural biomaterials for tissue engineering and regenerative medicine:new biosynthesis methods,recent advances,and emerging applications

Biomimetic materials have emerged as attractive and competitive alternatives for tissue engineering(TE)and regenerative medicine.In contrast to conventional biomaterials or synthetic materials,biomimetic scaffolds based on natural biomaterial can offer cells a broad spectrum of biochemical and biophysical cues that mimic the in vivo extracellular matrix(ECM).Additionally,such materials have mechanical adaptability,micro-structure interconnectivity,and inherent bioactivity,making them ideal for the design of living implants for specific applications in TE and regenerative medicine.This paper provides an overview for recent progress of biomimetic natural biomaterials(BNBMs),including advances in their preparation,functionality,potential applications and future challenges.We highlight recent advances in the fabrication of BNBMs and outline general strategies for functionalizing and tailoring the BNBMs with various biological and physicochemical characteristics of native ECM.Moreover,we offer an overview of recent key advances in the functionalization and applications of versatile BNBMs for TE applications.Finally,we conclude by offering our perspective on open challenges and future developments in this rapidly-evolving field.

Phase-engineering modulation of Mn-based oxide cathode for constructing super-stable sodium storage

The Mn-based oxide cathode with enriched crystal phase structure and component diversity can provide the excellent chemistry structure for Na-ion batteries.Nevertheless,the broad application prospect is obstructed by the sluggish Na^(+)kinetics and the phase transitions upon cycling.Herein,we establish the thermodynamically stable phase diagram of various Mn-based oxide composites precisely controlled by sodium content tailoring strategy coupling with co-doping and solid-state reaction.The chemical environment of the P2/P'3 and P2/P3 biphasic composites indicate that the charge compensation mechanism stems from the cooperative contribution of anions and cations.Benefiting from the no phase transition to scavenge the structure strain,P2/P'3 electrode can deliver long cycling stability(capacity retention of 73.8%after 1000 cycles at 10 C)and outstanding rate properties(the discharge capacity of 84.08 mA h g^(-1)at 20 C)than P2/P3 electrode.Furthermore,the DFT calculation demonstrates that the introducing novel P'3 phase can significantly regulate the Na^(+)reaction dynamics and modify the local electron configuration of Mn.The effective phase engineering can provide a reference for designing other high-performance electrode materials for Na-ion batteries.

Decade Milestone Advancement of Defect-Engineered g-C_(3)N_(4) for Solar Catalytic Applications

Over the past decade, graphitic carbon nitride(g-C_(3)N_(4)) has emerged as a universal photocatalyst toward various sustainable carbo-neutral technologies. Despite solar applications discrepancy, g-C_(3)N_(4) is still confronted with a general fatal issue of insufficient supply of thermodynamically active photocarriers due to its inferior solar harvesting ability and sluggish charge transfer dynamics. Fortunately, this could be significantly alleviated by the “all-in-one” defect engineering strategy, which enables a simultaneous amelioration of both textural uniqueness and intrinsic electronic band structures. To this end, we have summarized an unprecedently comprehensive discussion on defect controls including the vacancy/non-metallic dopant creation with optimized electronic band structure and electronic density, metallic doping with ultraactive coordinated environment(M–N_(x), M–C_(2)N_(2), M–O bonding), functional group grafting with optimized band structure, and promoted crystallinity with extended conjugation π system with weakened interlayered van der Waals interaction. Among them, the defect states induced by various defect types such as N vacancy, P/S/halogen dopants, and cyano group in boosting solar harvesting and accelerating photocarrier transfer have also been emphasized. More importantly, the shallow defect traps identified by femtosecond transient absorption spectra(fs-TAS) have also been highlighted. It is believed that this review would pave the way for future readers with a unique insight into a more precise defective g-C_(3)N_(4) “customization”, motivating more profound thinking and flourishing research outputs on g-C_(3)N_(4)-based photocatalysis.

Defect engineering in transition-metal(Fe,Co,andNi)-based electrocatalysts for water splitting

Electrocatalytic water splitting seems to be an efficient strategy to deal with increasingly serious environmental problems and energy crises but still suffers from the lack of stable and efficient electrocatalysts.Designing practical electrocatalysts by introducing defect engineering,such as hybrid structure,surface vacancies,functional modification,and structural distortions,is proven to be a dependable solution for fabricating electrocatalysts with high catalytic activities,robust stability,and good practicability.This review is an overview of some relevant reports about the effects of defect engineering on the electrocatalytic water splitting performance of electrocatalysts.In detail,the types of defects,the preparation and characterization methods,and catalytic performances of electrocatalysts are presented,emphasizing the effects of the introduced defects on the electronic structures of electrocatalysts and the optimization of the intermediates'adsorption energy throughout the review.Finally,the existing challenges and personal perspectives of possible strategies for enhancing the catalytic performances of electrocatalysts are proposed.An in-depth understanding of the effects of defect engineering on the catalytic performance of electrocatalysts will light the way to design high-efficiency electrocatalysts for water splitting and other possible applications.

Compositional and Hollow Engineering of Silicon Carbide/Carbon Microspheres as High-Performance Microwave Absorbing Materials with Good Environmental Tolerance

Microwave absorbing materials(MAMs)characterized by high absorption efficiency and good environmental tolerance are highly desirable in practical applications.Both silicon carbide and carbon are considered as stable MAMs under some rigorous conditions,while their composites still fail to produce satisfactory microwave absorption performance regardless of the improvements as compared with the individuals.Herein,we have successfully implemented compositional and structural engineering to fabricate hollow Si C/C microspheres with controllable composition.The simultaneous modulation on dielectric properties and impedance matching can be easily achieved as the change in the composition of these composites.The formation of hollow structure not only favors lightweight feature,but also generates considerable contribution to microwave attenuation capacity.With the synergistic effect of composition and structure,the optimized SiC/C composite exhibits excellent performance,whose the strongest reflection loss intensity and broadest effective absorption reach-60.8 dB and 5.1 GHz,respectively,and its microwave absorption properties are actually superior to those of most SiC/C composites in previous studies.In addition,the stability tests of microwave absorption capacity after exposure to harsh conditions and Radar Cross Section simulation data demonstrate that hollow SiC/C microspheres from compositional and structural optimization have a bright prospect in practical applications.

Biomaterials and emerging technologies for tissue engineering and in vitro models

The latest advances in the field of biomaterials have opened new avenues for scientific breakthroughs in tissue engineer-ing which greatly contributed for the successful translation of tissue engineering products into the market/clinics.Bio-materials are easily processed to become similar to natural extracellular matrix,making them ideal temporary supports for mimicking the three-dimensional(3D)microenvironment required for maintaining the adequate cell/tissue functions both in vitro and in vivo^([1]).