A comparative study on characteristics of retracted publications across different open access levels

Purpose:Recently,global science has shown an increasing open trend,however,the characteristics of research integrity of open access(OA)publications have rarely been studied.The aim of this study is to compare the characteristics of retracted articles across different OA levels and discover whether OA level influences the characteristics of retracted articles.Design/methodology/approach:The research conducted an analysis of 6,005 retracted publications between 2001 and 2020 from the Web of Science and Retraction Watch databases.These publications were categorized based on their OA levels,including Gold OA,Green OA,and non-OA.The study explored retraction rates,time lags and reasons within these categories.Findings:The findings of this research revealed distinct patterns in retraction rates among different OA levels.Publications with Gold OA demonstrated the highest retraction rate,followed by Green OA and non-OA.A comparison of retraction reasons between Gold OA and non-OA categories indicated similar proportions,while Green OA exhibited a higher proportion due to falsification and manipulation issues,along with a lower occurrence of plagiarism and authorship issues.The retraction time lag was shortest for Gold OA,followed by non-OA,and longest for Green OA.The prolonged retraction time for Green OA could be attributed to an atypical distribution of retraction reasons.A comparative study on characteristics of retracted publications across different open access levels Research limitations:There is no exploration of a wider range of OA levels,such as Hybrid OA and Bronze OA.Practical implications:The outcomes of this study suggest the need for increased attention to research integrity within the OA publications.The occurrences offalsification,manipulation,and ethical concerns within Green OA publications warrant attention from the scientific community.Originality/value:This study contributes to the understanding of research integrity in the realm of OA publications,shedding light on retraction patterns and reasons across different OA levels.

Chip Surface Character Recognition Based on OpenCV

Chip surface character recognition is an important part of quality inspection in the field of microelectronics manufacturing.By recognizing the character information on the chip,automated production,quality control,and data collection and analysis can be achieved.This article studies a chip surface character recognition method based on the OpenCV vision library.Firstly,the obtained chip images are preprocessed.Secondly,the template matching method is used to locate the chip position.In addition,the surface characters on the chip are individually segmented,and each character image is extracted separately.Finally,a Support Vector Machine(SVM)is used to classify and recognize characters.The results show that this method can accurately recognize the surface characters of chips and meet the requirements of chip quality inspection.

基于CAPE-OPEN标准的简捷炼油过程建模及常减压蒸馏流程在线模拟

简捷炼油过程模型广泛应用于运行监测、在线计算、实时优化等领域,但大多数模型只是将输入、输出变量进行关联,无法计算出各组分流量组成,难以集成在模拟软件中进行全流程模拟。本研究简化了炼油分离过程,开发了基于CAPE-OPEN标准的简捷炼油塔模型。首先,将炼油过程简化为连续的分离单元,根据实际产品数据校正模型参数,实现某一实际工况流程模拟;其次,将模型参数与实际工况操作变量数据相结合,采用径向基函数插值确定操作变量对模型参数的影响关系,实现多种工况流程模拟;最后,通过常减压蒸馏工业装置实例的3种工况进行验证。结果表明:各工况模拟结果与Aspen计算结果相比,初馏塔塔顶油馏出温度点偏差大多在2%以内,常减压蒸馏塔各侧线油的馏出温度点平均偏差在3%以内;与实际结果相比,平均误差都在5%以内,符合工程允许误差范围要求。所建模型的计算速度快,各塔均在0.2 s左右完成计算,适用于在线生产、调度等。

我国高质量教育资源供给机制创新与路径研究——来自美国“#GoOpen”计划的启示

数字化是当下教育改革的重点,也是未来教育发展的趋势。无论是作为“十四五”规划中的战略举措,还是党的二十大中提出的必然要求,构建数字化教育资源为主体的高质量教育资源体系在当下具有必要性与迫切性。美国#GoOpen计划自实施以来,在教育资源数字化、个性化、均等化三个方面均取得了一定成果。通过对该计划官方文件与政策进行解读,对其内涵与特点进行分析,我国在进行高质量教育资源建设及其供给路径探究过程中应当重视统筹规划,循序渐进,同时完善多重考核与评估机制,结合社会多方力量,保证每个学习者的享有权利,最终走向教育公平,共同发展。

基于YOLO-OpenMax的水声通信信号开集识别方法

水声通信信号调制方式随着技术进步从典型的传统调制方式发展为水声通信机厂商私有开发的新型调制方式,这使得现有的水声通信信号闭集调制识别技术实用性受到制约,但现阶段鲜有研究基于深度学习的水声通信信号调制方式的开集识别方法。针对此现状,提出一种基于YOLO图像检测识别网络和OpenMax模型的开集识别方法。利用YOLOv5网络的输出特点,将传统OpenMax模型的处理方法进行改进,提出一种两步测试方法,实现了在多径信道下的水声通信信号的开集识别。仿真实验表明:在归一化系数为0.5,信噪比等于10 dB条件下的归一化开集识别准确率达到90%以上,实测数据同样验证了本文方法的有效性。

Optimised CNN Architectures for Handwritten Arabic Character Recognition

Handwritten character recognition is considered challenging compared with machine-printed characters due to the different human writing styles.Arabic is morphologically rich,and its characters have a high similarity.The Arabic language includes 28 characters.Each character has up to four shapes according to its location in the word(at the beginning,middle,end,and isolated).This paper proposed 12 CNN architectures for recognizing handwritten Arabic characters.The proposed architectures were derived from the popular CNN architectures,such as VGG,ResNet,and Inception,to make them applicable to recognizing character-size images.The experimental results on three well-known datasets showed that the proposed architectures significantly enhanced the recognition rate compared to the baseline models.The experiments showed that data augmentation improved the models’accuracies on all tested datasets.The proposed model outperformed most of the existing approaches.The best achieved results were 93.05%,98.30%,and 96.88%on the HIJJA,AHCD,and AIA9K datasets.

Effect of Co on Solidification Characteristics and Microstructural Transformation of Non-equilibrium Solidified Cu-Ni Alloys

Non-equilibrium solidification structures of Cu55Ni45 and Cu55Ni43Co2 alloys were prepared by the molten glass purification cycle superheating method.The variation of the recalescence phenomenon with the degree of undercooling in the rapid solidification process was investigated using an infrared thermometer.The addition of the Co element affected the evolution of the recalescence phenomenon in Cu-Ni alloys.The images of the solid-liquid interface migration during the rapid solidification of supercooled melts were captured by using a high-speed camera.The solidification rate of Cu-Ni alloys,with the addition of Co elements,was explored.Finally,the grain refinement structure with low supercooling was characterised using electron backscatter diffraction(EBSD).The effect of Co on the microstructural evolution during nonequilibrium solidification of Cu-Ni alloys under conditions of small supercooling is investigated by comparing the microstructures of Cu55Ni45 and Cu55Ni43Co2 alloys.The experimental results show that the addition of a small amount of Co weakens the recalescence behaviour of the Cu55Ni45 alloy and significantly reduces the thermal strain in the rapid solidification phase.In the rapid solidification phase,the thermal strain is greatly reduced,and there is a significant increase in the characteristic undercooling degree.Furthermore,the addition of Co and the reduction of Cu not only result in a lower solidification rate of the alloy,but also contribute to the homogenisation of the grain size.

Artificial Self-Recovery Opens up a New Journey of Autonomous Health of Mechanical Equipments

1.Introduction With the implementation of modern production strategies,such as“Industry 4.0”and“Made in China 2025,”the development of high-end mechanical equipment is gradually reaching a high degree of parameterization,digitalization,networking,and intelligence[1].High-end mechanical equipment no longer consists of traditional single devices,but is closely linked to the overall production process;that is,a variety of devices interact with each other and collectively form a complex system.However,faults can lead to production delays throughout the system and even seriously threaten the safety of workers[2].In addition,equipment operating in unmanned air or space vehicles(including space robots)cannot be repaired by humans if they break down[3].Until recently,the typical method of addressing machine faults was primarily the“fault cure”method,which involves manually shutting down,inspecting,and repairing the equipment to restore normal operation.Accordingly,the maintenance cycle of the traditional“fault cure”method is time-consuming,and the quality of the maintenance depends on the skills of the technician[4].

Dust-Holding Capacity and Bio-Chemical Changes of Plant Species Growing in an Around Opencast Mining Area of Bundelkhand Region of Uttar Pradesh, India

The present study has been carried out on a total of 50 available plant species to assess their dust-capturing capacity and biochemical performances in and around open cast granite mine areas of Jhansi district and Bundelkhand University campus treated as control site. Plant species existing under a polluted environment for a long time may be considered as potentially resistant species and recommended for green belt design in mining areas, especially to cope with dust pollution. Results showed the pollution level, especially of mining-originated dust particles holding capacity of leaves and effects of different biochemical parameters (Total Chlorophyll, Protein and Carotenoid) of existing plant species both from mining areas as well as from Bundelkhand University campus. Based on their performances, Tectona grandis L., Ficus hispida L., Calotropis procera Aiton., Butea monosperma Lam. and Ficus benghalensis L., etc. are highly tolerant species while Ficus infectoria L., Artocarpus heterophyllus Lam., Ipomoea purpurea L., Allianthus excelsa Roxb. and Bauhinia variegata L. are intermediate tolerant species. T. grandis had shown the highest dust-holding capacity (2.566 ± 0.0004 mg/cm2) whereas Albizia procera (0.018 ± 0.0002 mg/cm2) was found to be the lowest dust-holding capacity. Our findings also showed that the T. grandis and F. hispida have significant dust deposition with minimal effect of dust on their leaf chlorophyll (17.447 ± 0.019 mg/g and 14.703 ± 0.201 mg/g), protein (0.699 ± 0.001 mg/g and 0.604 ± 0.002 mg/g) and carotenoid (0.372 ± 0.003 mg/g and 0.354 ± 0.003 mg/g) content respectively among all selected plant species. Therefore, in the present investigation, plant species with high tolerance to high dust-holding capacity on their leaf surfaces are preferable for green corridors as open cast granite mines and their adjacent areas.

Instance Segmentation of Characters Recognized in Palmyrene Aramaic Inscriptions

This study presents a single-class and multi-class instance segmentation approach applied to ancient Palmyrene inscriptions,employing two state-of-the-art deep learning algorithms,namely YOLOv8 and Roboflow 3.0.The goal is to contribute to the preservation and understanding of historical texts,showcasing the potential of modern deep learning methods in archaeological research.Our research culminates in several key findings and scientific contributions.We comprehensively compare the performance of YOLOv8 and Roboflow 3.0 in the context of Palmyrene character segmentation—this comparative analysis mainly focuses on the strengths and weaknesses of each algorithm in this context.We also created and annotated an extensive dataset of Palmyrene inscriptions,a crucial resource for further research in the field.The dataset serves for training and evaluating the segmentation models.We employ comparative evaluation metrics to quantitatively assess the segmentation results,ensuring the reliability and reproducibility of our findings and we present custom visualization tools for predicted segmentation masks.Our study advances the state of the art in semi-automatic reading of Palmyrene inscriptions and establishes a benchmark for future research.The availability of the Palmyrene dataset and the insights into algorithm performance contribute to the broader understanding of historical text analysis.

基于CAPE-OPEN标准的乙苯脱氢反应器模块开发与全流程模拟

基于某乙苯负压绝热脱氢制苯乙烯装置转化率低于设计值的现状,建立了包括小分子水蒸气转化反应在内的乙苯绝热脱氢制苯乙烯反应动力学模型和反应器模型,基于工业数据,估计了模型动力学参数,模型具有较高的精度;采用C++语言和COM技术开发了符合CAPE-OPEN标准的乙苯脱氢制苯乙烯反应器单元模块;在Aspen Plus平台构建了内嵌反应器模块的乙苯脱氢制苯乙烯全流程模型,反应器与精馏塔的模拟结果与实际相吻合;进一步考察了工艺参数对装置运行中期反应的影响,提出了适宜的工艺参数,为乙苯脱氢制苯乙烯的工艺设计、生产优化提供有益的支持。

Effect of Mouth Opening Training Stick Combined with Oral Massage on Mouth Opening Difficulty in Head and Neck Cancer Patients after Treatment

Objective: To study the application effect of mouth-opening training sticks combined with oral massage on patients with mouth-opening difficulty after treatment for head and neck cancer. Methods: Using convenient sampling, 60 patients with mouth-opening difficulty after treatment for head and neck cancer admitted to the Oncology Department from February 2022 to October 2023 were selected for a 2-week exercise and nursing program. The patients were divided into a control group (February 1, 2022 to November 30, 2022) and an observation group (December 1, 2022 to October 31, 2023), with 30 patients in each group. The control group underwent routine mouth-opening functional exercises combined with cork for oral support training, while the observation group underwent routine mouth-opening functional exercises combined with oral massage and mouth-opening training sticks for oral support training. The mouth-opening degree, mouth-opening difficulty level, comfort level, compliance, and quality of life were observed in both groups. Results: Before the intervention, there were no statistically significant differences in mouth-opening degree and mouth-opening difficulty level between the two groups (P > 0.05). After the intervention, the mouth-opening degree, mouth-opening difficulty level, oral comfort level, compliance, and QLICP-HN scores in the observation group were all better than those in the control group, with statistically significant differences (P < 0.05). Conclusion: The combination of mouth-opening training sticks and oral massage with mouth-opening functional exercises can effectively improve the degree of mouth-opening difficulty, enhance oral comfort, increase compliance with mouth-opening exercises, and improve quality of life.

Establishment and evaluation of an improved rat model of open abdomen

Introduction:This study aimed to establish an animal model of open abdomen(OA)through temporary abdominal closure via different techniques.Methods:Adult male Sprague-Dawley rats were randomly divided into three groups:group A(OA with polypropylene mesh alone);group B(OA with polypro-pylene mesh combined with a patch);and group C(OA with polypropylene mesh and a sutured patch).Vital signs,pathophysiological changes,and survival rates were closely monitored in the rats for 7 days after surgery.Abdominal X-rays and histopathological examinations were performed to assess abdominal organ changes and wound healing.Results:The results showed no significant difference in mortality rates among the three groups(p>0.05).However,rats in group B exhibited superior overall condi-tion,cleaner wounds,and a higher rate of wound healing compared to the other groups(p<0.05).Abdominal X-rays indicated that varying degrees of distal intestinal obstruction in all groups.Histopathological examinations revealed fibrous hyperpla-sia,inflammatory cell infiltration,neovascularization,and collagen deposition in all groups.Group B demonstrated enhanced granulation tissue generation,neovasculari-zation,and collagen deposition compared to the other groups(p<0.05).Conclusions:Polypropylene mesh combined with patches is the most suitable method for establishing an animal model of OA.This model successfully replicated the patho-logical and physiological changes in postoperative patients with OA,specifically the progress of abdominal skin wound healing.It provides a practical and reliable animal model for OA research.

A Method for Detecting and Recognizing Yi Character Based on Deep Learning

Aiming at the challenges associated with the absence of a labeled dataset for Yi characters and the complexity of Yi character detection and recognition,we present a deep learning-based approach for Yi character detection and recognition.In the detection stage,an improved Differentiable Binarization Network(DBNet)framework is introduced to detect Yi characters,in which the Omni-dimensional Dynamic Convolution(ODConv)is combined with the ResNet-18 feature extraction module to obtain multi-dimensional complementary features,thereby improving the accuracy of Yi character detection.Then,the feature pyramid network fusion module is used to further extract Yi character image features,improving target recognition at different scales.Further,the previously generated feature map is passed through a head network to produce two maps:a probability map and an adaptive threshold map of the same size as the original map.These maps are then subjected to a differentiable binarization process,resulting in an approximate binarization map.This map helps to identify the boundaries of the text boxes.Finally,the text detection box is generated after the post-processing stage.In the recognition stage,an improved lightweight MobileNetV3 framework is used to recognize the detect character regions,where the original Squeeze-and-Excitation(SE)block is replaced by the efficient Shuffle Attention(SA)that integrates spatial and channel attention,improving the accuracy of Yi characters recognition.Meanwhile,the use of depth separable convolution and reversible residual structure can reduce the number of parameters and computation of the model,so that the model can better understand the contextual information and improve the accuracy of text recognition.The experimental results illustrate that the proposed method achieves good results in detecting and recognizing Yi characters,with detection and recognition accuracy rates of 97.5%and 96.8%,respectively.And also,we have compared the detection and recognition algorithms proposed in this paper with other typical algorithms.In these comparisons,the proposed model achieves better detection and recognition results with a certain reliability.

OpenAI发布首个文生视频模型Sora

2024年2月16日,OpenAI发布首个文生视频模型Sora。Sora模型可以通过文本描述生成60秒长视频,还可以对视频色彩风格等要素精确理解,创造出人物表情丰富、情感生动的视频内容。据介绍,Sora模型有三大突出亮点,实现了AIGC领域的里程碑式进展。

Open-Source Software Defined Networking Controllers:State-of-the-Art,Challenges and Solutions for Future Network Providers

Software Defined Networking(SDN)is programmable by separation of forwarding control through the centralization of the controller.The controller plays the role of the‘brain’that dictates the intelligent part of SDN technology.Various versions of SDN controllers exist as a response to the diverse demands and functions expected of them.There are several SDN controllers available in the open market besides a large number of commercial controllers;some are developed tomeet carrier-grade service levels and one of the recent trends in open-source SDN controllers is the Open Network Operating System(ONOS).This paper presents a comparative study between open source SDN controllers,which are known as Network Controller Platform(NOX),Python-based Network Controller(POX),component-based SDN framework(Ryu),Java-based OpenFlow controller(Floodlight),OpenDayLight(ODL)and ONOS.The discussion is further extended into ONOS architecture,as well as,the evolution of ONOS controllers.This article will review use cases based on ONOS controllers in several application deployments.Moreover,the opportunities and challenges of open source SDN controllers will be discussed,exploring carriergrade ONOS for future real-world deployments,ONOS unique features and identifying the suitable choice of SDN controller for service providers.In addition,we attempt to provide answers to several critical questions relating to the implications of the open-source nature of SDN controllers regarding vendor lock-in,interoperability,and standards compliance,Similarly,real-world use cases of organizations using open-source SDN are highlighted and how the open-source community contributes to the development of SDN controllers.Furthermore,challenges faced by open-source projects,and considerations when choosing an open-source SDN controller are underscored.Then the role of Artificial Intelligence(AI)and Machine Learning(ML)in the evolution of open-source SDN controllers in light of recent research is indicated.In addition,the challenges and limitations associated with deploying open-source SDN controllers in production networks,how can they be mitigated,and finally how opensource SDN controllers handle network security and ensure that network configurations and policies are robust and resilient are presented.Potential opportunities and challenges for future Open SDN deployment are outlined to conclude the article.

Fireworks Optimization with Deep Learning-Based Arabic Handwritten Characters Recognition Model

Handwritten character recognition becomes one of the challenging research matters.More studies were presented for recognizing letters of various languages.The availability of Arabic handwritten characters databases was confined.Almost a quarter of a billion people worldwide write and speak Arabic.More historical books and files indicate a vital data set for many Arab nationswritten in Arabic.Recently,Arabic handwritten character recognition(AHCR)has grabbed the attention and has become a difficult topic for pattern recognition and computer vision(CV).Therefore,this study develops fireworks optimizationwith the deep learning-based AHCR(FWODL-AHCR)technique.Themajor intention of the FWODL-AHCR technique is to recognize the distinct handwritten characters in the Arabic language.It initially pre-processes the handwritten images to improve their quality of them.Then,the RetinaNet-based deep convolutional neural network is applied as a feature extractor to produce feature vectors.Next,the deep echo state network(DESN)model is utilized to classify handwritten characters.Finally,the FWO algorithm is exploited as a hyperparameter tuning strategy to boost recognition performance.Various simulations in series were performed to exhibit the enhanced performance of the FWODL-AHCR technique.The comparison study portrayed the supremacy of the FWODL-AHCR technique over other approaches,with 99.91%and 98.94%on Hijja and AHCD datasets,respectively.

Suicide risk in juvenile open angle glaucoma patients

AIM:To investigate the association between juvenile open angle glaucoma(JOAG)and mental health among Koreans.METHODS:This study used nationally representative data from the 8th Korea National Health and Nutrition Examination Survey(KNHANES)2021.Glaucoma diagnosis followed the International Society of Geographical and Epidemiological Ophthalmology criteria based on glaucomatous structural defects,visual field defects,corrected vision,and intraocular pressure.As outcomes,suicidal behaviors,psychiatric counseling,and depression were evaluated through mental health questionnaires.Odds ratios(ORs)with 95%confidence intervals(CIs)were estimated using logistic regression models,adjusting for covariates.RESULTS:Among 7090 participants,3446 met the inclusion criteria for analysis,and 88(2.6%)were diagnosed with open angle glaucoma(OAG).After adjusting for age,sex,and best-corrected visual acuity(VA),participants with OAG were revealed to have significantly higher odds of suicidal behaviors(i.e.,ideation,planning,or attempts)compared with those without OAG(OR:2.70;95%CI:1.12-6.54;P=0.028).This association remained significant after further adjustments for socioeconomic status,lifestyle factors,and presence of chronic conditions(P=0.031 and 0.035,respectively).However,there was no significant difference for the other two outcomes,psychiatric counseling and depression.An age-stratified analysis revealed a stronger association between OAG and suicidal behaviors in younger JOAG participants(<40y)than in older OAG participants(≥40y;OR:3.80 vs 2.22;95%CI:0.79-18.22 vs 0.56-8.80,respectively).CONCLUSION:OAG patients show a higher risk of suicidal behaviors than those without glaucoma particularly in JOAG patients.

Atomically Dispersed Ruthenium Catalysts with Open Hollow Structure for Lithium-Oxygen Batteries

Lithium–oxygen battery with ultrahigh theoretical energy density is considered a highly competitive next-generation energy storage device,but its practical application is severely hindered by issues such as difficult decomposition of discharge products at present.Here,we have developed N-doped carbon anchored atomically dispersed Ru sites cathode catalyst with open hollow structure(h-RuNC)for Lithium–oxygen battery.On one hand,the abundance of atomically dispersed Ru sites can effectively catalyze the formation and decomposition of discharge products,thereby greatly enhancing the redox kinetics.On the other hand,the open hollow structure not only enhances the mass activity of atomically dispersed Ru sites but also improves the diffusion efficiency of catalytic molecules.Therefore,the excellent activity from atomically dispersed Ru sites and the enhanced diffusion from open hollow structure respectively improve the redox kinetics and cycling stability,ultimately achieving a high-performance lithium–oxygen battery.

The Importance of Stakeholder Engagement in Progressive Rehabilitation of Large-Scale Open Pit Mines—A Case Study of Lumwana Mine

Mining globally contributes to the growth of many economies of the world. Since its inception, the Zambian mining industry has contributed largely to the country’s economy. The various developments both in technology and knowledge have contributed to the scale at which mining is being done. Challenges in such a setting arise due to the socio-economic and environmental impacts of mining, which create multidimensional problems. The study investigated the importance of engaging stakeholders in progressive rehabilitation programs for large-scale open pit mines, using a case study of the Lumwana Mine and its host community, Manyama. A qualitative approach was used, and data was collected through one-on-one interviews. A combination of convenient and quota sampling was used to engage with host community leaders, professionals and academicians from various fields and institutions. Results showed that most participants had agreed that stakeholder engagement is important for progressive rehabilitation, but the challenge was that the host community and municipal council representatives were not aware of any progressive rehabilitation efforts at Lumwana Mine. This was attributed to a lack of stakeholder engagement and communication of mitigation progress activities by the Lumwana Mine. Results also revealed that the lack of environmental impact assessment regulations to compel companies to involve stakeholders throughout the entire life of the mine other than just at the pre-mining stage led to a lack of compliance and accountability in rehabilitation.