Research progress in friction stir processing of magnesium alloys and their metal matrix surface composites: Evolution in the 21^(st )century

Rising concerns about climate change drive the demand for lightweight components.Magnesium(Mg)alloys are highly valued for their low weight,making them increasingly important in various industries.Researchers focusing on enhancing the characteristics of Mg alloys and developing their Metal Matrix Composites(MMCs)have gained significant attention worldwide over the past decade,driven by the global shift towards lightweight materials.Friction Stir Processing(FSP)has emerged as a promising technique to enhance the properties of Mg alloys and produce Mg-MMCs.Initially,FSP adapted to refine grain size from the micro to the nano level and accelerated the development of MMCs due to its solid-state nature and the synergistic effects of microstructure refinement and reinforcement,improving strength,hardness,ductility,wear resistance,corrosion resistance,and fatigue strength.However,producing defect-free and sound FSPed Mg and Mg-MMCs requires addressing several variables and their interdependencies,which opens up a broad range of practical applications.Despite existing reviews on individual FSP of Mg,its alloys,and MMCs,an attempt has been made to analyze the latest research on these three aspects collectively to enhance the understanding,application,and effectiveness of FSP for Mg and its derivatives.This review article discusses the literature,classifies the importance of Mg alloys,provides a historical background,and explores developments and potential applications of FSPed Mg alloys.It focuses on novel fabrication methods,reinforcement strategies,machine and tool design parameters,material characterization,and integration with other methods for enhanced properties.The influence of process parameters and the emergence of defects are examined,along with specific applications in mono and hybrid composites and their microstructure evolution.The study identifies promising reinforcement materials and highlights research gaps in FSP for Mg alloys and MMCs production.It concludes with significant recommendations for further exploration,reflecting ongoing advancements in this field.

Mapping Climate Services for Disaster Risk Management: A Systematic Review and Research Gaps from a Policy Process Perspective

Climate services (CS) are crucial for mitigating and managing the impacts and risks associated with climate-induced disasters. While evidence over the past decade underscores their effectiveness across various domains, particularly agriculture, to maximize their potential, it is crucial to identify emerging priority areas and existing research gaps for future research agendas. As a contribution to this effort, this paper employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to review the state-of-the-art in the field of climate services for disaster risk management. A comprehensive search across five literature databases combined with a snowball search method using ResearchRabbit was conducted and yielded 242 peer-reviewed articles, book sections, and reports over 2013-2023 after the screening process. The analysis revealed flood, drought, and food insecurity as major climate-related disasters addressed in the reviewed literature. Major climate services addressed included early warning systems, (sub)seasonal forecasts and impact-based warnings. Grounded in the policy processes’ theoretical perspective, the main focus identified and discussed three prevailing policy-oriented priority areas: 1) development of climate services, 2) use-adoption-uptake, and 3) evaluation of climate services. In response to the limitations of the prevalent supply-driven and top-down approach to climate services promotion, co-production emerges as a cross-cutting critical aspect of the identified priority areas. Despite the extensive research in the field, more attention is needed, particularly pronounced in the science-policy interface perspective, which in practice bridges scientific knowledge and policy decisions for effective policy processes. This perspective offers a valuable analytical lens as an entry point for further investigation. Hence, future research agendas would generate insightful evidence by scrutinizing this critical aspect given its importance to institutions and climate services capacity, to better understand intricate facets of the development and the integration of climate services into disaster risk management.

Research Progress on Purification Process, Content Determination and Pharmacological Action of Atractylodin

Atractylodis Rhizoma comes from the dry rhizome of Atractylis lancea or Atractylodes chinensis in the Compositae family,and it is suitable for preventing and treating diseases such as cold,edema,night blindness and rheumatic arthralgia.Atractylodin is the main active component extracted and isolated from Atractylodis Rhizoma.A large number of studies have found that atractylodin has excellent drug activity in improving gastrointestinal emptying,anti-inflammation,inhibiting malignant tumor and reducing blood lipid.In this paper,the purification process and pharmacological activity of Atractylodin were summarized to provide a theoretical basis for basic research,clinical application and further development and utilization of atractylodin.

Research on Purification Process and Pharmacological Action of Andrographolide

This paper reviews the purification process,content determination methods and pharmacological action of Andrographolide,aiming to provide new ideas for the subsequent study of Andrographolide and its related drug development and application.

Research on Image Preprocessing Algorithm for Rail Surface Recognition

The rail surface status image is affected by the noise in the shooting environment and contains a large amount of interference information, which increases the difficulty of rail surface status identification. In order to solve this problem, a preprocessing method for the rail surface state image is proposed. The preprocessing process mainly includes image graying, image denoising, image geometric correction, image extraction, data amplification, and finally building the rail surface image database. The experimental results show that this method can efficiently complete image processing, facilitate feature extraction of rail surface status images, and improve rail surface status recognition accuracy.

Harnessing artificial intelligence for identifying conflicts of interest in research

This editorial explores the transformative potential of artificial intelligence(AI)in identifying conflicts of interest(COIs)within academic and scientific research.By harnessing advanced data analysis,pattern recognition,and natural language processing techniques,AI offers innovative solutions for enhancing transparency and integrity in research.This editorial discusses how AI can automatically detect COIs,integrate data from various sources,and streamline reporting processes,thereby maintaining the credibility of scientific findings.

Dendritic spine degeneration:a primary mechanism in the aging process

Recent reports suggest that aging is not solely a physiological process in living beings;instead, it should be considered a pathological process or disease(Amorim et al., 2022). Consequently, this process involves a wide range of factors, spanning from genetic to environmental factors, and even includes the gut microbiome(GM)(Mayer et al., 2022). All these processes coincide at some point in the inflammatory process, oxidative stress, and apoptosis, at different degrees in various organs and systems that constitute a living organism(Mayer et al., 2022;AguilarHernández et al., 2023).

Research on Detection of Food additives Based on Terahertz Spectroscopy and Analytic Hierarchy Process

Terahertz time-domain spectroscopy is a kind of far-infrared spectroscopy technology,and its spectrum reflects the internal properties of substances with rich physical and chemical information,so the use of terahertz waves can be used to qualitatively identify food additives containing nitrogen elements.Analytic hierarchy process(AHP)was originally used to solve evaluation-type problems,and this paper introduces it into the field of terahertz spectral qualitative analysis,proposes a terahertz time-domain spectral qualitative identification method combined with analytic hierarchy process,and verifies the feasibility of the method by taking four common food additives(xylitol,L-alanine,sorbic acid,and benzoic acid)and two illegal additives(melamine,and Sudan Red No.I)as the objects of study.Firstly,the collected terahertz time-domain spectral data were pre-processed and transformed into a data set consisting of peaks,peak positions,peak numbers and overall trends;then,the data were divided into comparison and test sets,and a qualitative additive identification model incorporating analytic hierarchy process was constructed and parameter optimisation was performed.The results showed that the qualitative identification accuracies of additives based on single factors,i.e.,overall trend,peak value,peak position,and peak number,were 80.23%,70.93%,67.44%,and 40.70%,respectively,whereas the identification accuracy of the analytic hierarchy process qualitative identification method based on multi-factors could be improved to 92.44%.In addition,the fuzzy characterisation of the absorption spectrum data was binarised in the data pre-processing stage and used as the base data for the overall trend,and the recognition accuracy was improved to 94.19%by combining the fuzzy characterisation method of such data with the hierarchical analysis qualitative recognition model.The results show that it is feasible to use terahertz technology to identify different varieties of additives,and this paper constructs a hierarchical analytical qualitative model with better effect,which provides a new means for food additives detection,and the method is simple in steps,with a small demand for samples,which is suitable for the rapid detection of small samples.

Machine learning applications in healthcare clinical practice and research

Machine learning(ML)is a type of artificial intelligence that assists computers in the acquisition of knowledge through data analysis,thus creating machines that can complete tasks otherwise requiring human intelligence.Among its various applications,it has proven groundbreaking in healthcare as well,both in clinical practice and research.In this editorial,we succinctly introduce ML applications and present a study,featured in the latest issue of the World Journal of Clinical Cases.The authors of this study conducted an analysis using both multiple linear regression(MLR)and ML methods to investigate the significant factors that may impact the estimated glomerular filtration rate in healthy women with and without non-alcoholic fatty liver disease(NAFLD).Their results implicated age as the most important determining factor in both groups,followed by lactic dehydrogenase,uric acid,forced expiratory volume in one second,and albumin.In addition,for the NAFLD-group,the 5th and 6th most important impact factors were thyroid-stimulating hormone and systolic blood pressure,as compared to plasma calcium and body fat for the NAFLD+group.However,the study's distinctive contribution lies in its adoption of ML methodologies,showcasing their superiority over traditional statistical approaches(herein MLR),thereby highlighting the potential of ML to represent an invaluable advanced adjunct tool in clinical practice and research.

An Unprecedented Efficiency with Approaching 21%Enabled by Additive‑Assisted Layer‑by‑Layer Processing in Organic Solar Cells

Recently published in Joule,Feng Liu and colleagues from Shanghai Jiaotong University reported a record-breaking 20.8%power conversion efficiency in organic solar cells(OSCs)with an interpenetrating fibril network active layer morphology,featuring a bulk p-in structure and proper vertical segregation achieved through additive-assisted layer-by-layer deposition.This optimized hierarchical gradient fibrillar morphology and optical management synergistically facilitates exciton diffusion,reduces recombination losses,and enhances light capture capability.This approach not only offers a solution to achieving high-efficiency devices but also demonstrates the potential for commercial applications of OSCs.

Synthetic data as an investigative tool in hypertension and renal diseases research

There is a growing body of clinical research on the utility of synthetic data derivatives,an emerging research tool in medicine.In nephrology,clinicians can use machine learning and artificial intelligence as powerful aids in their clinical decision-making while also preserving patient privacy.This is especially important given the epidemiology of chronic kidney disease,renal oncology,and hypertension worldwide.However,there remains a need to create a framework for guidance regarding how to better utilize synthetic data as a practical application in this research.

Research on Petri Net Based Modeling and Analyzing Methods for Workflow Process

Workflow management is an important aspect in CSCW at present. The elementary knowledge of workflow process is introduced, the Petri nets based process modeling methodology and basic definitions are provided, and the analysis and verification of structural and behavioral correctness of workflow process are discussed. Finally, the algorithm of verification of process definitions is proposed.

RESEARCH OF VOXELIZATION PROCESS IN SWEPT-VOLUME TECHNIQUE

Now the image display techniques have made great progress. The planar display and a fully new true 3-D volumetric display technique are rapidly researched and come into the application. A method based on the voxel makes the observer able to get a true 3-D effect freely without any additional facilities. This paper introduces the basic form of the swept-volume display technique and discusses its voxelization process. By the translational motion prototype, this paper emphasizes how to get the voxel mapping matrix. The translated image data are the data of the beam source deflections. Finally the voxel ordering and the optimizing are also discussed.

RESEARCH ON SATELLITE IMAGE PROCESSING AND RECOGNITION WITH PARALLEL ALGORITHM

Using the method of mathematical morphology,this paper fulfills filtration,segmentation and extraction of morphological features of the satellite cloud image.It also gives out the relative algorithms,which is realized by parallel C programming based on Transputer networks.It has been successfully used to process the typhoon and the low tornado cloud image.And it will be used in weather forecast.

Design and Research of Information Processing System Based on Mix Platform

Aim To develop an information processing system with real time processing capability and artistic user interface for the optoelectronic antagonism general measuring system. Methods The A/D board and the multifunctional board communicating with every instruments were designed, data collecting and processing were realized by selecting appropriate software platform. Results Simulating results show the information processing system can operate correctly and dependably, the measuring rules, interactive interface and data handling method were all accepted by the user. Conclusion The designing approach based on the mix platform takes advantages of the two operating systems, the desired performances are acquired both in the real time processing and with the friendly artistic user interface.

Quality Management Research on the Purchasing of Food Processing Enterprises

In order to improve the purchased goods quality management level of food processing enterprises, the causes of quality management problems were ana- lyzed, which were classified into four categories, namely, natural toxins in raw ma- terials, quality problems in planting and breeding, quality problems in transportation, quality problems in delivery acceptance. Then, based on the causes, eight measures to improve goods purchasing management were put forward, and graphs were used to illustrate the corresponding countermeasure to each cause. This study is of theo- retical significance for the food processing enterprises to improve the quality man- agement of purchased goods through formulating improvement measures based on their operating states.

The Empirical Research of Native Thinking in the Process of English Composition

The method of questionnaire is employed to investigate the impact of Chinese thinking in the writing processes of 80 college English majors.It reveals that the English writing process is a bilingual event(namely,English writers have both Chinese and English at their disposal when they are composing in English).And no matter whether the English proficiency of the learners is high or low,the learners have a great dependence on Chinese thinking in the process of English writing.In the categories of task reacting and content organizing,there is no great difference between the high and low English proficiency students.But in the category of linguistic form,the influence of Chinese thinking on the low level students is far greater than the high level students.

基于Arduino与Processing的心率检测计设计研究

随着社会经济的高速发展,人们的物质生活也有了极大的提高,但同时也伴随着各种疾病的到来,身体健康已经成为人们普遍关注的焦点,因此,心率检测仪、血压计、血糖仪等各种家用医疗监测仪器已经逐渐融入日常生活。心脏病是人们难以预防的突发致命疾病之一,本文介绍的是一款基于Arduino【是基于易用硬件和软件的原型开源平台,包由可编程的电路板(简称微控制器),以及集成开发环境(称为Arduino IDE)的现成软件组成】Processing(开源编程语言,包括编辑器、编译器、展示器)的简易心率检测计系统,其功能实用、操作简单,可以测量心率,当超出正常心率范围时及时预警,是一款便携的实时心率测试仪。

An Example of Machine Vision Applied in Printing Quality Checking——Research on the Checking of Printing Quality by Image Processing

The traditional printing checking method always uses printing control strips,but the results are not very well in repeatability and stability. In this paper,the checking methods for printing quality basing on image are taken as research objects. On the base of the traditional checking methods of printing quality,combining the method and theory of digital image processing with printing theory in the new domain of image quality checking,it constitute the checking system of printing quality by image processing,and expound the theory design and the model of this system. This is an application of machine vision. It uses the high resolution industrial CCD(Charge Coupled Device) colorful camera. It can display the real-time photographs on the monitor,and input the video signal to the image gathering card,and then the image data transmits through the computer PCI bus to the memory. At the same time,the system carries on processing and data analysis. This method is proved by experiments. The experiments are mainly about the data conversion of image and ink limit show of printing.

Progress of Solidification Researches and the Applications in Materials Processing

The research achievements of solidification theories and technologies in the last decades are reviewed with the stresses on some new development in the recent years. Some new interesting areas emerged in the last years are also pointed out.