A review on the multi-scaled structures and mechanical/thermal properties of tool steels fabricated by laser powder bed fusion additive manufacturing

The laser powder bed fusion(LPBF) process can integrally form geometrically complex and high-performance metallic parts that have attracted much interest,especially in the molds industry.The appearance of the LPBF makes it possible to design and produce complex conformal cooling channel systems in molds.Thus,LPBF-processed tool steels have attracted more and more attention.The complex thermal history in the LPBF process makes the microstructural characteristics and properties different from those of conventional manufactured tool steels.This paper provides an overview of LPBF-processed tool steels by describing the physical phenomena,the microstructural characteristics,and the mechanical/thermal properties,including tensile properties,wear resistance,and thermal properties.The microstructural characteristics are presented through a multiscale perspective,ranging from densification,meso-structure,microstructure,substructure in grains,to nanoprecipitates.Finally,a summary of tool steels and their challenges and outlooks are introduced.

基于Ladybug Tools对日光温室的方位角与光照模拟

日光温室是重要的农业基础设施,温室的方位角是评判温室结构设计是否合理的基础之一。选择较好的温室方位角拥有更优的采光性能是本文研究的意义。为此,选择三维可视化技术模拟分析日光温室的光照值,为更好地研究分析日光温室采光性能及光照变化提供较为直观的途径和方法,为优化设计高产、高效、节能的日光温室提供一定的辅助作用。通过实测数据和模拟数据的对比,说明Ladybug Tools软件模拟不同方位角的变化及和田日光温室的光照的对比准确度较高,误差不超过5%,为研究日光温室在光照方面的设计提供了一定的理论依据和参考。

Nutritional Assessment Tools for Patients with Cancer:A Narrative Review

Cancer patients are at high risk of malnutrition,which can lead to adverse health outcomes such as prolonged hospitalization,increased complications,and increased mortality.Accurate and timely nutritional assessment plays a critical role in effectively managing malnutrition in these patients.However,while many tools exist to assess malnutrition,there is no universally accepted standard.Although different tools have their own strengths and limitations,there is a lack of narrative reviews on nutritional assessment tools for cancer patients.To address this knowledge gap,we conducted a non-systematic literature search using PubMed,Embase,Web of Science,and the Cochrane Library from their inception until May 2023.A total of 90 studies met our selection criteria and were included in our narrative review.We evaluated the applications,strengths,and limitations of 4 commonly used nutritional assessment tools for cancer patients:the Subjective Global Assessment(SGA),Patient-Generated Subjective Global Assessment(PG-SGA),Mini Nutritional Assessment(MNA),and Global Leadership Initiative on Malnutrition(GLIM).Our findings revealed that malnutrition was associated with adverse health outcomes.Each of these 4 tools has its applications,strengths,and limitations.Our findings provide medical staff with a foundation for choosing the optimal tool to rapidly and accurately assess malnutrition in cancer patients.It is essential for medical staff to be familiar with these common tools to ensure effective nutritional management of cancer patients.

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.

Research Progress of Measuring Tools for Patient Medication Compliance

This paper introduced the content, compilation process, reliability and validity, scoring method of the evaluation tool for patients’ medication compliance at home and abroad, and reviewed the research progress of the tool. The evaluation method, dimension, scoring method, evaluation content and application scope of the tool were compared, so as to provide reference for nurses to comprehensively and accurately evaluate patients’ medication status.

Phosphorylated protein chip combined with artificial intelligence tools for precise drug screening

We have developed a protein array system,named"Phospho-Totum",which reproduces the phosphorylation state of a sample on the array.The protein array contains 1471 proteins from 273 known signaling pathways.According to the activation degrees of tyrosine kinases in the sample,the corresponding groups of substrate proteins on the array are phosphorylated under the same conditions.In addition to measuring the phosphorylation levels of the 1471 substrates,we have developed and performed the artificial intelligence-assisted tools to further characterize the phosphorylation state and estimate pathway activation,tyrosine kinase activation,and a list of kinase inhibitors that produce phosphorylation states similar to that of the sample.The Phospho-Totum system,which seamlessly links and interrogates the measurements and analyses,has the potential to not only elucidate pathophysiological mechanisms in diseases by reproducing the phosphorylation state of samples,but also be useful for drug discovery,particularly for screening targeted kinases for potential drug kinase inhibitors.

Emerging molecules,tools,technology,and future of surgical knife in gastroenterology

The 21^(st) century has started with several innovations in the medical sciences,with wide applications in health care management.This development has taken in the field of medicines(newer drugs/molecules),various tools and technology which has completely changed the patient management including abdominal surgery.Surgery for abdominal diseases has moved from maximally invasive to minimally invasive(laparoscopic and robotic)surgery.Some of the newer medicines have its impact on need for surgical intervention.This article focuses on the development of these emerging molecules,tools,and technology and their impact on present surgical form and its future effects on the surgical intervention in gastroenterological diseases.

Tool Wear State Recognition with Deep Transfer Learning Based on Spindle Vibration for Milling Process

The wear of metal cutting tools will progressively rise as the cutting time goes on. Wearing heavily on the toolwill generate significant noise and vibration, negatively impacting the accuracy of the forming and the surfaceintegrity of the workpiece. Hence, during the cutting process, it is imperative to continually monitor the tool wearstate andpromptly replace anyheavilyworn tools toguarantee thequality of the cutting.The conventional tool wearmonitoring models, which are based on machine learning, are specifically built for the intended cutting conditions.However, these models require retraining when the cutting conditions undergo any changes. This method has noapplication value if the cutting conditions frequently change. This manuscript proposes a method for monitoringtool wear basedonunsuperviseddeep transfer learning. Due to the similarity of the tool wear process under varyingworking conditions, a tool wear recognitionmodel that can adapt to both current and previous working conditionshas been developed by utilizing cutting monitoring data from history. To extract and classify cutting vibrationsignals, the unsupervised deep transfer learning network comprises a one-dimensional (1D) convolutional neuralnetwork (CNN) with a multi-layer perceptron (MLP). To achieve distribution alignment of deep features throughthe maximum mean discrepancy algorithm, a domain adaptive layer is embedded in the penultimate layer of thenetwork. A platformformonitoring tool wear during endmilling has been constructed. The proposedmethod wasverified through the execution of a full life test of end milling under multiple working conditions with a Cr12MoVsteel workpiece. Our experiments demonstrate that the transfer learning model maintains a classification accuracyof over 80%. In comparisonwith the most advanced tool wearmonitoring methods, the presentedmodel guaranteessuperior performance in the target domains.

Further Analysis of Machine Tool Dimensional Accuracy and Thermal Stability under Varying Floor Temperature

Machining is as old as humanity, and changes in temperature in both the machine’s internal and external environments can be of great concern as they affect the machine’s thermal stability and, thus, the machine’s dimensional accuracy. This paper is a continuation of our earlier work, which aimed to analyze the effect of the internal temperature of a machine tool as the machine is put into operation and vary the external temperature, the machine floor temperature. Some experiments are carried out under controlled conditions to study how machine tool components get heated up and how this heating up affects the machine’s accuracy due to thermally induced deviations. Additionally, another angle is added by varying the machine floor temperature. The parameters mentioned above are explored in line with the overall thermal stability of the machine tool and its dimensional accuracy. A Robodrill CNC machine tool is used. The CNC was first soaked with thermal energy by gradually raising the machine floor temperature to a certain level before putting the machine in operation. The machine was monitored, and analytical methods were deplored to evaluate thermal stability. Secondly, the machine was run idle for some time under raised floor temperature before it was put into operation. Data was also collected and analyzed. It is observed that machine thermal stability can be achieved in several ways depending on how the above parameters are joggled. This paper, in conclusion, reinforces the idea of machine tool warm-up process in conjunction with a carefully analyzed and established machine floor temperature variation for the approximation of the machine tool’s thermally stability to map the long-time behavior of the machine tool.

Evidence for the Reliability and Validity of the Arabic Version of the Student Risk Screening Scale for Internalizing and Externalizing Behaviors (SRSS-IE)

School-based universal screening for behavioral/emotional risk is a necessary first step to providing services in an educational setting for students with emotional and behavioral disorders (EBDs). Psychometric properties are critical to making decisions about choosing a screening instrument. The purpose of the present study was to examine the psychometric properties of the student risk screening scale for internalizing and externalizing behaviors (SRSS-IE). Participants included 3145 students and their teachers. Item-level analyses of the current sample supported the retention of all items. The internal consistency of the SRSS items ranged from 0.83 to 0.85. Convergent validity between the SRSS-IE and a well-established screening tool, the strength and difficulties questionnaire (SDQ), was found for the total score (r = 0.70). Additionally, the results of this study demonstrate strong social validity, suggesting the SRSS-IE to be a useful and functional screening tool. We conclude that the SRSS-IE is a valid and reliable instrument for assessing the level of emotional and behavioral difficulties among elementary students.

Research Progress of Assessment Tools for Peripheral Venous Access Difficulties in Children

Objective:To review the research progress of peripheral venous access difficulty assessment tools in children and to provide a reference for clinical nurses to select and develop appropriate assessment tools.Methods:Search the literature at home and abroad and summarize and analyze the existing evaluation tools.Results:There is no unified assessment tool about difficult venous access in children at home and abroad.The existing tools include the difficult venous access assessment scale and peripheral venous grading assessment tool.Conclusion:The current assessment tools for venous access difficulties in children have their own limitations,and it is necessary to develop further the assessment tools suitable for the cultural background of children's venous access difficulties.This paper summarized the current progress of research on peripheral venous access difficulty assessment tools.It also analyzed and summarized the shortcomings of existing tools to provide a reference for clinical staff to choose appropriate assessment tools.

Digital Generative Multimedia Tool Theory (DGMTT): A Theoretical Postulation

The development of digital technology has brought about a substantial evolution in the multimedia field.The use of generative technologies to produce digital multimedia material is one of the newer developments in this field.The“Digital Generative Multimedia Tool Theory”(DGMTT)is therefore presented in this theoretical postulation by Timothy Ekeledirichukwu Onyejelem and Eric Msughter Aondover.It discusses and describes the principles behind the development and deployment of generative tools in multimedia creation.The DGMTT offers an all-encompassing structure for comprehending and evaluating the fundamentals and consequences of generative tools in the production of multimedia content.It provides information about the creation and use of these instruments,thereby promoting developments in the digital media industry.These tools create dynamic and interactive multimedia content by utilizing machine learning,artificial intelligence,and algorithms.This theory emphasizes how crucial it is to comprehend the fundamental ideas and principles of generative tools in order to use them efficiently when creating digital media content.A wide range of industries,including journalism,advertising,entertainment,education,and the arts,can benefit from the practical use of DGMTT.It gives artists the ability to use generative technologies to create unique and customized multimedia content for its viewers.

Research on Machine Tool Fault Diagnosis and Maintenance Optimization in Intelligent Manufacturing Environments

In the context of intelligent manufacturing,machine tools,as core equipment,directly influence production efficiency and product quality through their operational reliability.Traditional maintenance methods for machine tools,often characterized by low efficiency and high costs,fail to meet the demands of modern manufacturing industries.Therefore,leveraging intelligent manufacturing technologies,this paper proposes a solution optimized for the diagnosis and maintenance of machine tool faults.Initially,the paper introduces sensor-based data acquisition technologies combined with big data analytics and machine learning algorithms to achieve intelligent fault diagnosis of machine tools.Subsequently,it discusses predictive maintenance strategies by establishing an optimized model for maintenance strategy and resource allocation,thereby enhancing maintenance efficiency and reducing costs.Lastly,the paper explores the architectural design,integration,and testing evaluation methods of intelligent manufacturing systems.The study indicates that optimization of machine tool fault diagnosis and maintenance in an intelligent manufacturing environment not only enhances equipment reliability but also significantly reduces maintenance costs,offering broad application prospects.

Scale and Associated Factors of Using Pyrethroid-Impregnated Mosquito Nets as Fishing Tools on Nokoué Lake within Sô-Ava Municipality in Benin, 2020

Background: In lacustrine communities, whether in Benin or elsewhere, populations use impregnated mosquito nets (IMNs) as fishing nets. This depletes the lake of its fishery resources, which in turn are contaminated by the pyrethroids impregnated in the nets. This study aims to determine the scale and factors associated with the use of pyrethroid-impregnated mosquito nets as fishing tools in the municipality of Sô-Ava in Benin. Methods: This is a cross-sectional and analytical study with two components. First, a quantitative component was made up of 280 volunteers who were interviewed in the seven districts of the city. Data collection was done in two phases: the first from September to October 2020, and the second in August 2022. Data were analyzed with Stata and logistic regression was used. Another qualitative component was made up of forty participants chosen by reasoned choice, of which 32 were split into four focus groups of eight members each, and the rest participated in semi-structured interviews. Triangulation of the different sources was used to analyze the data. Results: Around 67% of the population reported using impregnated mosquito nets as fishing tools and 33% exclusively for malaria. Seasonal fishermen (ORa = 2.03, CI = 1.35 - 4.97, P = 0.004) and years of professional experience (ORa = 1.53, CI = 1.00 - 2.05, P = 0.021) increase the risk of using these nets as fishing tools. The use of insecticide-treated mosquito nets against mosquitoes causes skin scratching and impairs breathing because of the impregnation products, as reported by respondents. Conclusion: A high prevalence of inappropriate use of impregnated mosquito nets in fishing practices is highlighted in this study. Interviews in the field revealed that nets are diverted for fishing purposes to increase the volume of catches. Consequently, it will be appropriate to assess the pyrethroid content in water and fishery products.

Effect of Tool Shoulder and Pin Probe Profiles on Friction Stirred Aluminum Welds-a Comparative Study

在海洋的申请，海洋的等级钢通常被使用为拖并且上层建筑。然而，铝也由于它的小质量成为了一种好选择，当铝生锈与钢相比是最小的时。在磨擦上在这糊研究促使铝合金焊接被介绍。现在的调查处理不同磨擦的效果促使在机械强度和铝合金焊接的微观结构性质上焊接工具几何学。有肩膀和工具探查侧面的不同类型的三不同工具几何学根据设计矩阵在调查被使用。焊接上的每个工具肩膀和探查几何学的效果被评估。磨擦搅动焊接工具几何学，这也被观察在焊接加强， microhardness，和焊接强度上有重要效果。

Modeling the Effects of Tool Shoulder and Probe Profile Geometries on Friction Stirred Aluminum Welds Using Response Surface Methodology

现在的论文讨论当模特儿磨擦上的效果搅动铝焊接使用的工具几何学反应表面方法论。磨擦促使焊接工具基于一个设计矩阵与不同肩膀和工具探查几何学被设计。为设计的工具的矩阵为定义肩膀表面类型和探查侧面几何学各为工具的三种类型被做，基于探针的三种类型，与三个层次。然后，工具肩膀的效果和磨擦上的探查几何学搅动了铝焊接试验性地关于焊接强度，焊接十字节区域，焊接的谷物尺寸和 thermo 机械地影响的地区的谷物尺寸被调查。这些效果被建模用多重并且反应表面回归分析。当模特儿的反应表面回归被发现为定义磨擦适当搅动焊接特征。

基于Arc Hydro Tools的祁连山国家公园小流域划分

以祁连山国家公园为研究区,基于30 m分辨率数字高程模型数据,利用Arc Hydro Tools水文数据模型与河网密度法,在确定最佳集水面积阈值的基础上提取河网并划分小流域,统计小流域的部分特征参数.结果表明,集水面积阈值与河网密度呈幂函数关系,祁连山国家公园最佳集水面积阈值为6000栅格数;河网提取结果与全国1∶250000三级水系流域数据集的河网套合差为2.62%,叠加至遥感图像对比,发现提取结果相较于全国1∶250000三级水系流域数据集更接近真实水系;共划分祁连山国家公园小流域5717个,约80%的小流域面积在3~50 km2.从提取效率和结果精度来看,Arc Hydro Tools模型与河网密度法相结合可较准确提取山地区域河网及小流域.

改良Aldrete量表和DPART在全身麻醉术后复苏病人中的应用效果比较

目的:探讨中文版DPART量表与改良Aldrete量表对全身麻醉病人术后复苏效果的评估效果。方法:以全身麻醉术后入麻醉复苏室(PACU)接受治疗的病人为研究对象,按手术日期先后顺序分为改良Aldrete组和DPART组。改良Aldrete组105例病人采用改良Aldrete作为出室评估工具,DPART组109例病人采用DPART作为出室评估工具,比较两组病人PACU停留时间、出室时疼痛评分、镇静躁动得分、苏醒期躁动发生率、恶心呕吐评分和护士对于两种量表的可行性、实用性评价。结果:DPART组PACU停留时间长于改良Aldrete组(P<0.05),但出室时疼痛评分、恶心呕吐评分低于改良Aldrete组(P<0.05);两组出室时镇静躁动得分及苏醒期躁动发生率比较差异无统计学意义(P>0.05);DPART组量表的可行性评分低于改良Aldrete组(P<0.05),实用性评分高于改良Aldrete组(P<0.05)。结论:应用中文版DPART量表评估PACU病人,病人PACU停留时间较使用改良Aldrete量表评估延长,但病人出室时各项体征表现较好,更有利于保障全身麻醉术后病人安全转出PACU。

卒中后认知障碍评估工具筛查准确性的Meta分析

背景卒中后认知障碍(PSCI)给患者及其家庭带来沉重的负担,早期识别及干预有助于延缓PSCI的发生及进展,因此,使用准确的神经心理评估工具对PSCI进行筛查,对于患者的管理和治疗至关重要。目的采用Meta分析的方法评价PSCI筛查工具的筛查准确性,为准确筛查PSCI提供依据。方法检索数据库中国知网、维普网、万方数据知识服务平台、中国生物医学文献服务系统、PubMed、Embase、Web of Science、Cochrane Library中有关PSCI筛查工具的诊断性试验研究,检索日期为建库至2022年12月。2位研究者各自筛选文献、提取数据、评估偏倚风险。采用Stata 17.0软件分析数据。结果共纳入57篇文献,包含12113例患者,报告了7种PSCI筛查工具:美国国立神经疾病和卒中研究院-加拿大卒中网5-min测验(NINDS-CSN 5-min测验)、蒙特利尔认知评估量表(MoCA)、简易精神状况检查量表(MMSE)、老年认知功能减退知情者问卷(IQCODE)、阿登布鲁克认知能力检查-修订版(ACE-R)、认知功能电话问卷修订版(TICS-m)、5分钟蒙特利尔评估(MoCA-5 min)。Meta分析结果显示:MoCA筛查PSCI的合并灵敏度及特异度分别为0.84(95%CI=0.80~0.87)和0.74(95%CI=0.67~0.80),合并AUC为0.87(95%CI=0.84~0.90);MMSE筛查PSCI的合并灵敏度及特异度为0.73(95%CI=0.67~0.79)和0.76(95%CI=0.69~0.82),合并AUC为0.81(95%CI=0.77~0.84);IQCODE筛查PSCI的合并灵敏度及特异度为0.73(95%CI=0.48~0.89)和0.95(95%CI=0.75~0.99),合并AUC为0.91(95%CI=0.88~0.93);NINDS-CSN 5-min测验筛查PSCI的合并灵敏度及特异度为0.83(95%CI=0.78~0.87)、0.69(95%CI=0.60~0.76),合并AUC为0.85(95%CI=0.81~0.88);ACE-R筛查PSCI的合并灵敏度及特异度为0.90(95%CI=0.80~0.95)、0.61(95%CI=0.19~0.91),合并AUC为0.90(95%CI=0.87~0.92);TICS-m筛查PSCI的合并灵敏度及特异度为0.84(95%CI=0.75~0.91)、0.67(95%CI=0.61~0.74),合并AUC为0.66(95%CI=0.60~0.71)。结论IQCODE和ACE-R的合并AUC较高,且IQCODE具有较高的合并特异度,ACE-R具有较高的合并灵敏度,故IQCODE和ACE-R是较为准确的PSCI筛查工具。因IQCODE和ACE-R纳入文献数量有限,以上结论仍需多中心、大样本研究予以验证。

基于FIR-Stacking的刀具磨损预测

针对铣刀加工工件时传感器信号存在噪声、单一传统机器学习模型预测效果不理想的问题,提出一种基于自适应FIR滤波器和Stacking集成模型的刀具磨损预测方法。首先,采用自适应FIR滤波器去噪,计算时域、频域和时频域常用统计量作为信号特征,并对同一信号的多源信号特征进行拼接,经Pearson相关系数筛选保留相关系数大于0.2的特征;最后,以LightGBM、支持向量回归(support vector regression,SVR)、多层感知机(multilayer perceptron,MLP)作为基模型,Lasso作为元模型,构建Stacking集成模型进行刀具磨损预测。使用铣削加工数据集进行验证,结果表明该方法可有效提高预测准确性。