Stress-assisted corrosion mechanism of 3Ni steel by using gradient boosting decision tree machining learning method

Traditional 3Ni weathering steel cannot completely meet the requirements for offshore engineering development,resulting in the design of novel 3Ni steel with the addition of microalloy elements such as Mn or Nb for strength enhancement becoming a trend.The stress-assisted corrosion behavior of a novel designed high-strength 3Ni steel was investigated in the current study using the corrosion big data method.The information on the corrosion process was recorded using the galvanic corrosion current monitoring method.The gradi-ent boosting decision tree(GBDT)machine learning method was used to mine the corrosion mechanism,and the importance of the struc-ture factor was investigated.Field exposure tests were conducted to verify the calculated results using the GBDT method.Results indic-ated that the GBDT method can be effectively used to study the influence of structural factors on the corrosion process of 3Ni steel.Dif-ferent mechanisms for the addition of Mn and Cu to the stress-assisted corrosion of 3Ni steel suggested that Mn and Cu have no obvious effect on the corrosion rate of non-stressed 3Ni steel during the early stage of corrosion.When the corrosion reached a stable state,the in-crease in Mn element content increased the corrosion rate of 3Ni steel,while Cu reduced this rate.In the presence of stress,the increase in Mn element content and Cu addition can inhibit the corrosion process.The corrosion law of outdoor-exposed 3Ni steel is consistent with the law based on corrosion big data technology,verifying the reliability of the big data evaluation method and data prediction model selection.

Nontraditional energy-assisted mechanical machining of difficult-to-cut materials and components in aerospace community:a comparative analysis

The aerospace community widely uses difficult-to-cut materials,such as titanium alloys,high-temperature alloys,metal/ceramic/polymer matrix composites,hard and brittle materials,and geometrically complex components,such as thin-walled structures,microchannels,and complex surfaces.Mechanical machining is the main material removal process for the vast majority of aerospace components.However,many problems exist,including severe and rapid tool wear,low machining efficiency,and poor surface integrity.Nontraditional energy-assisted mechanical machining is a hybrid process that uses nontraditional energies(vibration,laser,electricity,etc)to improve the machinability of local materials and decrease the burden of mechanical machining.This provides a feasible and promising method to improve the material removal rate and surface quality,reduce process forces,and prolong tool life.However,systematic reviews of this technology are lacking with respect to the current research status and development direction.This paper reviews the recent progress in the nontraditional energy-assisted mechanical machining of difficult-to-cut materials and components in the aerospace community.In addition,this paper focuses on the processing principles,material responses under nontraditional energy,resultant forces and temperatures,material removal mechanisms,and applications of these processes,including vibration-,laser-,electric-,magnetic-,chemical-,advanced coolant-,and hybrid nontraditional energy-assisted mechanical machining.Finally,a comprehensive summary of the principles,advantages,and limitations of each hybrid process is provided,and future perspectives on forward design,device development,and sustainability of nontraditional energy-assisted mechanical machining processes are discussed.

Assessment of Wet Season Precipitation in the Central United States by the Regional Climate Simulation of the WRFG Member in NARCCAP and Its Relationship with Large-Scale Circulation Biases

Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.

On dry machining of AZ31B magnesium alloy using textured cutting tool inserts

Magnesium alloys have many advantages as lightweight materials for engineering applications,especially in the fields of automotive and aerospace.They undergo extensive cutting or machining while making products out of them.Dry cutting,a sustainable machining method,causes more friction and adhesion at the tool-chip interface.One of the promising solutions to this problem is cutting tool surface texturing,which can reduce tool wear and friction in dry cutting and improve machining performance.This paper aims to investigate the impact of dimple textures(made on the flank face of cutting inserts)on tool wear and chip morphology in the dry machining of AZ31B magnesium alloy.The results show that the cutting speed was the most significant factor affecting tool flank wear,followed by feed rate and cutting depth.The tool wear mechanism was examined using scanning electron microscope(SEM)images and energy dispersive X-ray spectroscopy(EDS)analysis reports,which showed that at low cutting speed,the main wear mechanism was abrasion,while at high speed,it was adhesion.The chips are discontinuous at low cutting speeds,while continuous at high cutting speeds.The dimple textured flank face cutting tools facilitate the dry machining of AZ31B magnesium alloy and contribute to ecological benefits.

Enhancing Cybersecurity through Cloud Computing Solutions in the United States

This study investigates how cybersecurity can be enhanced through cloud computing solutions in the United States. The motive for this study is due to the rampant loss of data, breaches, and unauthorized access of internet criminals in the United States. The study adopted a survey research design, collecting data from 890 cloud professionals with relevant knowledge of cybersecurity and cloud computing. A machine learning approach was adopted, specifically a random forest classifier, an ensemble, and a decision tree model. Out of the features in the data, ten important features were selected using random forest feature importance, which helps to achieve the objective of the study. The study’s purpose is to enable organizations to develop suitable techniques to prevent cybercrime using random forest predictions as they relate to cloud services in the United States. The effectiveness of the models used is evaluated by utilizing validation matrices that include recall values, accuracy, and precision, in addition to F1 scores and confusion matrices. Based on evaluation scores (accuracy, precision, recall, and F1 scores) of 81.9%, 82.6%, and 82.1%, the results demonstrated the effectiveness of the random forest model. It showed the importance of machine learning algorithms in preventing cybercrime and boosting security in the cloud environment. It recommends that other machine learning models be adopted to see how to improve cybersecurity through cloud computing.

Field-assisted machining of difficult-to-machine materials

Difficult-to-machine materials (DMMs) are extensively applied in critical fields such as aviation,semiconductor,biomedicine,and other key fields due to their excellent material properties.However,traditional machining technologies often struggle to achieve ultra-precision with DMMs resulting from poor surface quality and low processing efficiency.In recent years,field-assisted machining (FAM) technology has emerged as a new generation of machining technology based on innovative principles such as laser heating,tool vibration,magnetic magnetization,and plasma modification,providing a new solution for improving the machinability of DMMs.This technology not only addresses these limitations of traditional machining methods,but also has become a hot topic of research in the domain of ultra-precision machining of DMMs.Many new methods and principles have been introduced and investigated one after another,yet few studies have presented a comprehensive analysis and summarization.To fill this gap and understand the development trend of FAM,this study provides an important overview of FAM,covering different assisted machining methods,application effects,mechanism analysis,and equipment design.The current deficiencies and future challenges of FAM are summarized to lay the foundation for the further development of multi-field hybrid assisted and intelligent FAM technologies.

Maternal Mortality Rates among Im/Migrant Populations in the United States

Introduction: Maternal mortality rates have more than doubled in the U.S over the last two decades, making it one of the few places in the world where maternal mortality is increasing. Differences in maternal mortality among certain races and ethnicities are known but few studies examine maternal mortality among immigrants. Since immigrants represent 13.7% of the U.S. population, it is essential to examine immigrant subsets to understand maternal mortality among this vulnerable population. Methods: A literature search identified 318 articles on maternal mortality and immigrants, with 12 articles from the U.S. The keywords included maternal mortality, United States, migrants, asylum seekers, immigrants, and disparities. Maternal mortality statistics were obtained from the World Health Organization and Center for Disease Control. Results: Studies analyzed in this review found an overall lower maternal mortality rate among immigrant women compared to U.S.-born women, except for Hispanic immigrant women. Black women had the highest maternal mortality rate, regardless of immigration status. Conclusion: Although the literature points to lower maternal mortality among immigrants, the data is still somewhat mixed, making it challenging to draw comprehensive conclusions. Additional research examining maternal mortality among Im/migrants in the U.S. is needed to guide future training among healthcare professionals and policymakers.

The Enforcement of Occupational Safety and Health Requirements in Public and Private Sectors in the Emirate of Abu Dhabi, the United Arab Emirates

Research Problem: In Abu Dhabi, limited implementation of OSH Regulations contributes to the general unawareness among employees and workers about occupational hazards and safety measures, resulting in slow responsiveness toward enforcement measures and a lack of self-regulatory approaches within companies. Purpose: The purpose of this study is to examine the implementation methods practised in Abu Dhabi with those in developed countries with established OSH regulatory bodies. Methodology: Qualitative and quantitative research methods were employed to gather primary research data. Workers from various industries in Abu Dhabi were sampled on purpose and asked to respond to questionnaires and interviews on OSH protocol awareness and implementation, and circumstances of workplace incidence. Results: The findings of this study showed that the enforcement of OSH requirements in UAE positively correlated to a reduction in the rate of work-related injury and improved business performance. The quantitative research data showed that the energy sector had the highest score (15) while the tourism sector had the lowest score (5.3) in occupational health systems and improvements in business efficiency and productivity. Implications: The outcomes of this study shed light on the importance of implementing OSH Guidelines for companies to empower their safety managers to fully enforce OSH requirements in their organisations. In conclusion, effective OSH enforcement requires cooperation between general workers and OSH managers and facilitation from business owners.

Travel-Limiting Disabilities in the United States: Why Accessibility Matters?

This study evaluates the distribution of travel-limiting disabilities across genders and geographic locations in the United States. This study aims to describe and compare the socioeconomic and demographic variables of the people with and without travel-limiting disabilities across geographic locations and gender. The study further evaluates the trip purpose and impact of Covid-19 fourth wave pandemic on the use of public transit and travel to physical workplace for the people with and without travel-limiting disabilities across gender and geographic locations. The study uses the 2022 weighted National Household Travel Survey dataset and employs descriptive statistics. Results reaffirm the findings from previous literature that there are more people with travel-limiting disabilities in urban areas and among women. Over 50 percent of people aged 65 and above have a form of travel-limiting disabilities. The most trip for people with travel-limiting disabilities is made for shopping and medical purposes. Across all categories, rural areas, urban areas, male and female for the people without travel-limiting disabilities, COVID-19 fourth wave did not change the pattern of trips made to physical workplace as pre-COVID-19 era. This pattern is also observable for the people with travel-limiting disabilities in rural and urban areas. Females with travel-limiting disabilities reported making less trips to physical workplaces while male reported doing the same as before COVID-19 era. The study concludes that the quantification of travel-limiting disabilities across geographic location and gender is vital in disability study and could drive policy implementation for improved accessibility for the vulnerable population.

Characteristics of patients with Wilson disease in the United States: An insurance claims database study

BACKGROUND Wilson disease(WD)is a progressive,potentially fatal degenerative disease affecting the liver and central nervous system.Given its low prevalence,collecting data on large cohorts of patients with WD is challenging.Comprehensive insur-ance claims databases provide powerful tools to collect retrospective data on large numbers of patients with rare diseases.AIM To describe patients with WD in the United States,their treatment and clinical outcome,using a large insurance claims database.METHODS This retrospective,longitudinal study was performed in the Clarivate Real-World Data Product database.All patients with≥2 claims associated with an Interna-tional Classification of Diseases 10(ICD-10)diagnostic code for WD(E83.01)between 2016 and 2021 were included and followed until death or study end.Patients were divided into two groups by whether or not they were documented to have received a specific treatment for WD.Clinical manifestations,hospital-isations,liver transplantation and death were documented.RESULTS Overall,5376 patients with an ICD-10 diagnostic code for WD were identified.The mean age at inclusion was 41.2 years and 52.0%were men.A specific WD treatment was documented for 885 patients(15.1%),although the number of patients taking zinc salts may be underestimated due to over the counter purchase.At inclusion,the mean age of patients with a documented treatment was 36.6±17.8 years vs 42.2±19.6 years in those without a documented treatment.During follow-up,273 patients(5.1%)died.Compared with the American general population,the standardised mortality ratio was 2.19.The proportion of patients with a documented WD-specific treatment who died during follow-up was 4.0%and the mean age at death 52.7 years.CONCLUSION Patients treated for WD in the United States had an excess early mortality compared with the American population.These findings indicate that there is a significant unmet need for effective treatment for WD in the United States.

Geologic characteristics,exploration and production progress of shale oil and gas in the United States:An overview

We present a systematic summary of the geological characteristics,exploration and development history and current state of shale oil and gas in the United States.The hydrocarbon-rich shales in the major shale basins of the United States are mainly developed in six geological periods:Middle Ordovician,Middle-Late Devonian,Early Carboniferous(Middle-Late Mississippi),Early Permian,Late Jurassic,and Late Cretaceous(Cenomanian-Turonian).Depositional environments for these shales include intra-cratonic basins,foreland basins,and passive continental margins.Paleozoic hydrocarbon-rich shales are mainly developed in six basins,including the Appalachian Basin(Utica and Marcellus shales),Anadarko Basin(Woodford Shale),Williston Basin(Bakken Shale),Arkoma Basin(Fayetteville Shale),Fort Worth Basin(Barnett Shale),and the Wolfcamp and Leonardian Spraberry/Bone Springs shale plays of the Permian Basin.The Mesozoic hydrocarbon-rich shales are mainly developed on the margins of the Gulf of Mexico Basin(Haynesville and Eagle Ford)or in various Rocky Mountain basins(Niobrara Formation,mainly in the Denver and Powder River basins).The detailed analysis of shale plays reveals that the shales are different in facies and mineral components,and"shale reservoirs"are often not shale at all.The United States is abundant in shale oil and gas,with the in-place resources exceeding 0.246×10^(12)t and 290×10^(12)m^(3),respectively.Before the emergence of horizontal well hydraulic fracturing technology to kick off the"shale revolution",the United States had experienced two decades of exploration and production practices,as well as theory and technology development.In 2007-2023,shale oil and gas production in the United States increased from approximately 11.2×10^(4)tons of oil equivalent per day(toe/d)to over 300.0×10^(4)toe/d.In 2017,the shale oil and gas production exceeded the conventional oil and gas production in the country.In 2023,the contribution from shale plays to the total U.S.oil and gas production remained above 60%.The development of shale oil and gas has largely been driven by improvements in drilling and completion technologies,with much of the recent effort focused on“cube development”or“co-development”.Other efforts to improve productivity and efficiency include refracturing,enhanced oil recovery,and drilling of“U-shaped”wells.Given the significant resources base and continued technological improvements,shale oil and gas production will continue to contribute significant volumes to total U.S.hydrocarbon production.

Temporal Variability of Tropospheric NO_(2) over Cities in the United States,Western Europe and China from 2005 to 2022

Anthropogenic Nitrogen oxides(NO_(x)=NO_(2)+NO)emissions are highly concentrated in urban area,and the weekly cycles,seasonal patterns and long-term trends of tropospheric NO_(2) columns over cities differ from region to region due to different emission sectoral compositions and human activities.In this study,we used satellite observed tropospheric NO_(2) column data to compare the longand short-term NO_(2) column density time series over cities in the United Sates(the U.S.),western Europe and China.The results showed that in all the targeted cities,the outbreak of the Corona Virus Disease in 2019(COVID-19)moved the December peak of the city-level NO_(2)columns forward to November and October or even earlier in 2020 and 2021.On weekly level,cities in the U.S.show the lowest NO_(2) columns ratio on weekend/work day,then come the western European cities,and a weak weekly pattern is seen in Chinese cities.For all the cites,we find a higher weekend/work day NO_(2) ratio in cold seasons than in warm seasons,indicating a higher contribution from NOx emission sectors of residential,industry and power plants in the warm seasons.In the long-term,NO_(2) columns over the U.S.and western European cities declined by a fraction twice that of the regional mean level from 2004 to 2021.In China,NO_(2) columns started to decrease since 2012,at a similar rate between the city and regional level.This work confirms the importance to quantify and control NOx emissions from cities.

Coping with the Impact of Climate Change: A Dive into Precision Agriculture in the United States

With the continued increase in the number of people that are food insecure globally, which could be increasing because of the ongoing Ukraine-Russia war, leading to reduction in international agribusinesses, coupled with drastic climate change exacerbating the problem of food insecurity, there is a constant need to come up with innovative approaches to solve this global issue. In this article, we articulated how precision agriculture can be a tool for ensuring food security in the United States. This study aims to reiterate the significance of precision agriculture in solving global food insecurity.

Designing a Protection Scheme in Micro-Grid Systems with DG Using Central Protection Unite and Multiple Setting Group Protection Relays

Distributed generators now is widely used in electrical power networks, in some cases it works seasonally, and some types works at special weather conditions like photo voltaic systems and wind energy, and due to this continuous changes in generation condition, the fault current level in network will be affected, this changes in fault current level will affect in the coordination between protection relays and to keep the coordination at right way, an adaptive protection system is required that can adaptive its setting according to generation changes, the fault current level in each case is evaluated using ETAP software, and the required relay setting in each case is also evaluated using Grey Wolf Optimizer (GWO) algorithm, and to select suitable setting which required in each condition, to select the active setting group of protection relay according to generation capacity, central protection unite can be used, and to improve protection stability and minimizing relays tripping time, a proposed method for selecting suitable backup relay is used, which leads to decrease relays tripping time and increase system stability, output settings for relays in all cases achieved our constrains.

Perspectives on non-emergent neonatal intensive care unit to pediatric intensive care unit care transfers in the United States

BACKGROUND There is a substantial population of long-stay patients who non-emergently transfer directly from the neonatal intensive care unit(NICU)to the pediatric intensive care unit(PICU)without an interim discharge home.These infants are often medically complex and have higher mortality relative to NICU or PICUonly admissions.Given an absence of data surrounding practice patterns for nonemergent NICU to PICU transfers,we hypothesized that we would encounter a broad spectrum of current practices and a high proportion of dissatisfaction with current processes.AIM To characterize non-emergent NICU to PICU transfer practices across the United States and query PICU providers’evaluations of their effectiveness.METHODS A cross-sectional survey was drafted,piloted,and sent to one physician representative from each of 115 PICUs across the United States based on membership in the PARK-PICU research consortium and membership in the Children’s Hospital Association.The survey was administered via internet(REDCap).Analysis was performed using STATA,primarily consisting of descriptive statistics,though logistic regressions were run examining the relationship between specific transfer steps,hospital characteristics,and effectiveness of transfer.RESULTS One PICU attending from each of 81 institutions in the United States completed the survey(overall 70%response rate).Over half(52%)indicated their hospital transfers patients without using set clinical criteria,and only 33%indicated that their hospital has a standardized protocol to facilitate non-emergent transfer.Fewer than half of respondents reported that their institution’s nonemergent NICU to PICU transfer practices were effective for clinicians(47%)or patient families(38%).Respondents evaluated their centers’transfers as less effective when they lacked any transfer criteria(P=0.027)or set transfer protocols(P=0.007).Respondents overwhelmingly agreed that having set clinical criteria and standardized protocols for non-emergent transfer were important to the patient-family experience and patient safety.CONCLUSION Most hospitals lacked any clinical criteria or protocols for non-emergent NICU to PICU transfers.More positive perceptions of transfer effectiveness were found among those with set criteria and/or transfer protocols.

自然语言处理研究综述

近年来,自然语言处理因在分析与建模人类语言任务领域取得诸多成果而备受关注。当前,大规模预训练语言模型展现出强大的对话问答和文本生成能力,带来自然语言处理研究的新一轮热潮。自然语言处理在机器翻译、文本摘要、信息抽取等领域应用广泛。文本首先讨论自然语言处理针对语言学四个不同层次文本信息的分析手段,对自然语言处理的基本任务组成进行概述;其次,讨论自然语言处理在具体下游任务中的应用现状,包括自然语言处理在具体任务中的应用历史、当前的研究趋势以及面临的挑战;最后,在大规模预训练语言模型研究对数据集提出更高要求的背景下,对自然语言处理领域已有的数据集及评测基准集等进行讨论。

基于电子商务环境的农机管理系统设计

介绍了电子商务环境的背景和现状,详细描述了农机管理系统的实际需求和业务流程,并根据系统设计原则设计了系统总体架构,最后从人机管理、作业管理及综合信息等3个方面实现了农机管理系统。系统在测试过程中取得了较好的应用效果,是一种具有广泛应用前景的高效农机管理系统。

光伏发电机组异动信息主动增量式更新算法

针对进行光伏发电机组密集型异动信息更新操作时,出现更新时延长、更新结果不完整的问题,提出了光伏发电机组异动信息主动增量式更新算法。通过特征提取、小波变换和模极大值计算来获取有效的增量式特征;构建增量特征成词袋模型并进行标注;结合蚁群算法搜索异动信息,计算最小平均带宽和最佳更新路径,通过动态更新相容类和决策类异动信息完善数据;采用2阶段集合式更新方案进行信息增量收集和校验增量分发,以获取主动增量式更新异动信息。由实验结果可知,该算法更新时延在全部校验节点下未超过40 s,且能够保证更新结果具有完整性。

纤维肌痛综合征生物标记物的筛选及免疫细胞浸润分析

背景:纤维肌痛综合征作为常见风湿病,其发病与中枢敏化及免疫异常有关,但具体过程尚未阐明,缺乏特异性诊断标志物,不断探索该病的发病机制具有重要的临床意义。目的:基于加权基因共表达网络分析(WGCNA)等生物信息学方法和机器学习算法筛选纤维肌痛综合征潜在的诊断相关标志基因,并分析其免疫细胞浸润特征。方法:对来自基因表达综合数据库(GEO)的纤维肌痛综合征数据集转录谱进行差异分析和WGCNA分析,整合筛选出差异共表达基因,进一步采用机器学习套索回归(LASSO)算法、支持向量机递归特征消除(SVM-RFE)机器学习算法来识别核心生物标志物,并绘制受试者工作特征(ROC)曲线以评估诊断价值。最后,采用单样本基因集富集分析(ssGSEA)和基因集富集分析(GSEA)评估纤维肌痛综合征的免疫细胞浸润情况及通路富集。结果与结论:①对GSE67311数据集按照log2|(FC)|>0,P<0.05的条件进行差异分析后获得8个下调的差异表达基因;进行WGCNA分析后获得正相关性最高(r=0.22,P=0.04)的模块(MEdarkviolet)内含基因497个,负相关性最高(r=-0.41,P=6×10-5)的模块(MEsalmon2)内含基因19个;将差异表达基因与WGCNA的2个高相关性模块基因取交集,获得7个基因。②对上述7个基因进行LASSO回归算法筛选出4个基因,进行SVM-RFE机器学习算法筛选出5个基因,两者取交集后确定了3个核心基因,分别为重组1号染色体开放阅读框150蛋白(germinal center associated signaling and motility like,GCSAML)、整合素β8(Integrin beta-8,ITGB8)和羧肽酶A3(carboxypeptidase A3,CPA3);绘制3个核心基因的ROC曲线下面积分别为0.744,0.739,0.734,提示均具有很好的诊断价值,可作为纤维肌痛综合征的生物标志物。③免疫浸润分析结果显示,与对照组相比纤维肌痛综合征患者记忆B细胞、CD56 bright NK细胞和肥大细胞显著下调(P<0.05),且与上述3个生物标志物显著正相关(P<0.05)。④富集分析结果提示,纤维肌痛综合征的富集途径包括9条,主要与嗅觉传导、神经活性配体-受体相互作用及感染等通路密切相关。⑤上述结果显示,纤维肌痛综合征的发生发展与多基因参与、免疫调节异常及多个通路失调有关,但这些基因与免疫细胞之间的相互作用,以及它们与各通路之间的关系尚需进一步研究。

Non-traditional Machining Techniques for Fabricating Metal Aerospace Filters

Thanks to recent advances in manufacturing technology, aerospace system designers have many more options to fabricate high-quality, low-weight, high-capacity, cost-effective filters. Aside from traditional methods such as stamping, drilling and milling, many new approaches have been widely used in filter-manufacturing practices on account of their increased processing abilities. How- ever, the restrictions on costs, the need for studying under stricter conditions such as in aggressive fluids, the complicity in design, the workability of materials, and others have made it difficult to choose a satisfactory method from the newly developed processes, such as, photochemical machining （PCM）, photo electroforming （PEF） and laser beam machining （LBM） to produce small, inexpensive, lightweight aerospace filters. This article appraises the technical and economical viability of PCM, PEF, and LBM to help engineers choose the fittest approach to turn out aerospace filters.