Optimization of the Use of Spherical Targets for Point Cloud Registration Using Monte Carlo Simulation

Registrations based on the manual placement of spherical targets are still being employed by many professionals in the industry.However,the placement of those targets usually relies solely on personal experience without scientific evidence supported by numerical analysis.This paper presents a comprehensive investigation,based on Monte Carlo simulation,into determining the optimal number and positions for efficient target placement in typical scenes consisting of a pair of facades.It demonstrates new check-up statistical rules and geometrical constraints that can effectively extract and analyze massive simulations of unregistered point clouds and their corresponding registrations.More than 6×10^(7) sets of the registrations were simulated,whereas more than IOO registrations with real data were used to verify the results of simulation.The results indicated that using five spherical targets is the best choice for the registration of a large typical registration site consisting of two vertical facades and a ground,when there is only a box set of spherical targets available.As a result,the users can avoid placing extra targets to achieve insignificant improvements in registration accuracy.The results also suggest that the higher registration accuracy can be obtained when the ratio between the facade-to-target distance and target-to-scanner distance is approximately 3:2.Therefore,the targets should be placed closer to the scanner rather than in the middle between the facades and the scanner,contradicting to the traditional thought. Besides,the results reveal that the accuracy can be increased by setting the largest projected triangular area of the targets to be large.

Potential of the Arkhangelsk seismic network for European Arctic monitoring

The Arkhangelsk Seismic Network(ASN)of the N.Laverov Federal Center for Integrated Arctic Research of the Ural Branch of the Russian Academy of Sciences,founded in 2003,includes 10 permanent seismic stations located on the coasts of the White,Barents,and Kara Seas and on the Arctic archipelagos of Novaya Zemlya,Franz Josef Land,and Severnaya Zemlya.The network is registered with the International Federation of Digital Seismograph Networks and the International Seismological Center.We used not only ASN data to process earthquakes but also the waveforms of various international seismic stations.The 13,000 seismic events were registered using ASN data for 2012-2022,and for 5,500 of them,we determined the parameters of the earthquake epicenters from the European Arctic.The spatial distribution of epicenters shows that the ASN monitors not only the main seismically active zones but also weak seismicity on the shelf of the Barents and Kara Seas.The representative magnitude of ASN was ML,rep=3.5.The level of microseismic noise has seasonal variations that affect the registration capabilities of each station included in the ASN and the overall sensitivity of the network as a whole.In summer,the sensitivity of the ASN decreased owing to the increasing microseismic and ambient noises,whereas in winter,the sensitivity of the ASN increased significantly because of the decrease.

The Impact of Simulation Education on Self-Efficacy in Pre-Registration Nursing Students

This literature review primarily aims to explore and synthesise the previous studies in simulation education research conducted over the past five years related to the effects of simulation training on the self-efficacy of undergraduate pre-registration nursing students. The second aim of this study is to explore additional outcome variables that were examined in the previous studies. Five electronic databases were searched systematically. These databases were MEDLINE, CINAHL Plus, Scopus, Embase and PsycINFO. The PICO model was employed to identify the search terms, with a thesaurus being used to provide synonyms. Reference lists of relevant articles were examined and hand searches of journals were also undertaken. The quality of each study was assessed using the Simulation Research Rubric (SRR). A total of 11 studies were included. All studies explored the impact of simulation education on undergraduate pre-registration nursing. Six studies explored nursing students’ competence and performance and two papers examined their critical thinking. Problem solving, learning motivation, communication skills and knowledge acquisition were examined once. The majority of studies indicated that simulation training has a positive impact on pre-registration nursing students’ self-efficacy and other outcome variables. Furthermore, the study results indicate that simulation training is more dependable than traditional training, and students were extremely satisfied with the simulation training. However, most of the studies included in this review had several gaps, including study design, sample size and dissimilarities between the scales used. Further research with large samples, reliable and valid instruments, and outcomes measures (such as critical thinking and transferability of skills) is required to provide better insight into the effectiveness of simulation in undergraduate nursing education. .

Automatic Extraction of the Sparse Prior Correspondences for Non-Rigid Point Cloud Registration

Non-rigid registration of point clouds is still far from stable,especially for the largely deformed one.Sparse initial correspondences are often adopted to facilitate the process.However,there are few studies on how to build them automatically.Therefore,in this paper,we propose a robust method to compute such priors automatically,where a global and local combined strategy is adopted.These priors in different degrees of deformation are obtained by the locally geometrical-consistent point matches from the globally structural-consistent region correspondences.To further utilize the matches,this paper also proposes a novel registration method based on the Coherent Point Drift framework.This method takes both the spatial proximity and local structural consistency of the priors as supervision of the registration process and thus obtains a robust alignment for clouds with significantly different deformations.Qualitative and quantitative experiments demonstrate the advantages of the proposed method.

New Path for Integrated Reform of Urban and Rural Household Registration System in the Context of Informationization

In China, household registration system has the problems of unreasonable standard setting and relevant supporting measures failure to keep pace with the development trend. From analysis of current problems and situations, it is believed that household registration system should undertake reform and take a new road by means of informationization. Strengthening informationization management in land, population, education and labor market can better perform urban and rural integration.

GAN-DIRNet:A Novel Deformable Image Registration Approach for Multimodal Histological Images

Multi-modal histological image registration tasks pose significant challenges due to tissue staining operations causing partial loss and folding of tissue.Convolutional neural network(CNN)and generative adversarial network(GAN)are pivotal inmedical image registration.However,existing methods often struggle with severe interference and deformation,as seen in histological images of conditions like Cushing’s disease.We argue that the failure of current approaches lies in underutilizing the feature extraction capability of the discriminator inGAN.In this study,we propose a novel multi-modal registration approach GAN-DIRNet based on GAN for deformable histological image registration.To begin with,the discriminators of two GANs are embedded as a new dual parallel feature extraction module into the unsupervised registration networks,characterized by implicitly extracting feature descriptors of specific modalities.Additionally,modal feature description layers and registration layers collaborate in unsupervised optimization,facilitating faster convergence and more precise results.Lastly,experiments and evaluations were conducted on the registration of the Mixed National Institute of Standards and Technology database(MNIST),eight publicly available datasets of histological sections and the Clustering-Registration-Classification-Segmentation(CRCS)dataset on the Cushing’s disease.Experimental results demonstrate that our proposed GAN-DIRNet method surpasses existing approaches like DIRNet in terms of both registration accuracy and time efficiency,while also exhibiting robustness across different image types.

Nonlinear Registration of Brain Magnetic Resonance Images with Cross Constraints of Intensity and Structure

Many deep learning-based registration methods rely on a single-stream encoder-decoder network for computing deformation fields between 3D volumes.However,these methods often lack constraint information and overlook semantic consistency,limiting their performance.To address these issues,we present a novel approach for medical image registration called theDual-VoxelMorph,featuring a dual-channel cross-constraint network.This innovative network utilizes both intensity and segmentation images,which share identical semantic information and feature representations.Two encoder-decoder structures calculate deformation fields for intensity and segmentation images,as generated by the dual-channel cross-constraint network.This design facilitates bidirectional communication between grayscale and segmentation information,enabling the model to better learn the corresponding grayscale and segmentation details of the same anatomical structures.To ensure semantic and directional consistency,we introduce constraints and apply the cosine similarity function to enhance semantic consistency.Evaluation on four public datasets demonstrates superior performance compared to the baselinemethod,achieving Dice scores of 79.9%,64.5%,69.9%,and 63.5%for OASIS-1,OASIS-3,LPBA40,and ADNI,respectively.

The Making of a Health Profession:How Chinese Medicine Became a Nationally Registered Allied Health Profession in Australia

In 2012, traditional Chinese medicine(TCM) practitioners in Australia became nationally-registered allied health professionals in three categories: acupuncturist, Chinese herbal medicine practitioner, and Chinese herbal medicine dispenser. Australia was the first Western country to introduce national registration for Chinese medicine, followed by Portugal and, recently, New Zealand. The practice of TCM in Australia can be traced back to the beginning of Chinese immigration to Australia during the Victorian Gold Rush which began in the 1850s. The process which led to national registration commenced in the early 1970s with the establishment of the first acupuncture courses. Decades of gradual development of courses from unaccredited part-time diplomas to accredited bachelor degrees, and the development, by the profession, of national consensus on educational standards were essential elements in the process which led to registration. Professional associations, such as the Australian Acupuncture and Chinese Medicine Association Ltd.(AACMA), also developed a framework of professional selfregulation, including Codes of Ethics, Codes of Conduct, ongoing professional development requirements and Infection Control Guidelines, and provided leadership in the development of the profession. After decades of tribalism and division within the TCM profession, the National Academic Standards Committee brought almost all stakeholders together to reach a consensus on the Australian Guidelines for Traditional Chinese Medicine Education which were published by AACMA in 2001. Professional associations also collaborated on joint submissions to the government in support of registration, which was introduced first in the state of Victoria in 2000, and subsequently became national in 2012. Despite national registration, some barriers still remain, and professional associations continue to lobby the federal government for inclusion in Medicare, chronic disease management scheme, and Veterans Affairs.

The Relationships between the Short Video Addiction,Self-Regulated Learning,and Learning Well-Being of Chinese Undergraduate Students

Background:With the global popularity of short videos,particularly among young people,short video addiction has become a worrying phenomenon that poses significant risks to individual health and adaptability.Self-regulated learning(SRL)strategies are key factors in predicting learning outcomes.This study,based on the SRL theory,uses short video addiction as the independent variable,SRL strategies as the mediating variable,and learning well-being as the outcome variable,aiming to reveal the relationships among short video addiction,self-regulated learning,and learning well-being among Chinese college students.Methods:Using a cross-sectional study design and applying the snowball sampling technique,an online survey was administered to Chinese undergraduate students.A total of 706 valid questionnaires were collected,with an effective response rate of 85.7%.The average age of the participants was 20.5 years.Results:The results of structural equation modeling indicate that 7 hypotheses were supported.Short video addiction was negatively correlated with self-regulated learning strategies(preparatory,performance,and appraisal strategy),while SRL strategies were positively correlated with learning well-being.Additionally,short video addiction had a mediating effect on learning well-being through the three types of SRL strategies.The three types of SRL strategies explained 39%of the variance in learning well-being.Conclusion:Previous research has typically focused on the impact of self-regulated learning strategies on media addiction or problematic media use.This study,based on the SRL model,highlights the negative issues caused by short video addiction and emphasizes the importance of cultivating self-regulation abilities and media literacy.Short video addiction stems from failures in trait self-regulation,which naturally impairs the ability to effectively engage in self-regulation during the learning process.This study confirms and underscores that the SRL model can serve as an effective theoretical framework for helping students prevent short video addiction,engage in high-quality learning,and consequently enhance their learning well-being.

Disordered Multi-view Registration Method Based on the Soft Trimmed Deep Network

Compared with the pair-wise registration of point clouds,multi-view point cloud registration is much less studied.In this dissertation,a disordered multi-view point cloud registration method based on the soft trimmed deep network is proposed.In this method,firstly,the expression ability of feature extraction module is improved and the registration accuracy is increased by enhancing feature extraction network with the point pair feature.Secondly,neighborhood and angle similarities are used to measure the consistency of candidate points to surrounding neighborhoods.By combining distance consistency and high dimensional feature consistency,our network introduces the confidence estimation module of registration,so the point cloud trimmed problem can be converted to candidate for the degree of confidence estimation problem,achieving the pair-wise registration of partially overlapping point clouds.Thirdly,the results from pair-wise registration are fed into the model fusion to achieve the rough registration of multi-view point clouds.Finally,the hierarchical clustering is used to iteratively optimize the clustering center model by gradually increasing the number of clustering categories and performing clustering and registration alternately.This method achieves rough point cloud registration quickly in the early stage,improves the accuracy of multi-view point cloud registration in the later stage,and makes full use of global information to achieve robust and accurate multi-view registration without initial value.

Improved Analytical Methods for Determination of Residues of Nitrapyrin and 6-Chloropicolinic Acid in Different Crop Matrices by Liquid Chromatography-Tandem Mass Spectrometry

Novel analytical methods were developed for the determination of nitrapyrin and 6-chloropicolinic acid (6-CPA) residues in agricultural products. Nitrapyrin was extracted with hexane: toluene (1:1, v/v) and 6-CPA with 0.1 N sodium hydroxide (NaOH). For nitrapyrin, samples were cleaned with silica solid phase extraction (SPE) and for 6-CPA with C18 or carbon SPE. Analysis was performed by liquid chromatography-tandem mass spectroscopy (LC-MS/MS) with external calibration (0.010 to 0.0010 µg∙mL−1 for nitrapyrin and 0.0050 to 0.00025 µg∙mL−1 for 6-CPA). Recoveries for nitrapyrin and 6-CPA were 68% - 102% and 66% - 90%, respectively. Nitrapyrin was detected in celery and onion (−1) and 6-CPA in onion, mustard greens and lettuce (−1). Lower level method validation (LLMV) for nitrapyrin and 6-CPA was 0.020 µg∙g−1 and 0.050 µg∙g−1, respectively. The methods presented in this study are robust and were utilized for the registration of nitrapyrin on agricultural commodities in the United States.

Performance Evaluation of Low-Carbon and Clean Transformation of China’s Coal Economy

In China,the oversupply of coal occurred in 2009,and from that year onwards,China’s coal economy began a low-carbon and clean transformation.Evaluating transformation performance is the research goal of this paper.The data collection for this paper includes data on deep processing of Chinese coal products from 2009 to 2020,as well as data on asset structure evolution and financial performance of 34 listed companies in the Chinese coal mining.Entropy value method is used to calculate the entropy value of low-carbon transformation,and the regression analysis is used to study the performance of cleaner transformation,the conclusion is as follows:(1)From 2009 to 2020,in China’s total energy consumption,coal consumption accounted for 71.6%in 2009 and 56.8%in 2020,the goals set by the state have been achieved.(2)The national goal of reducing the proportion of coal consumption and reducing carbon emissions has forced the transformation of deep processing of coal products.The transformation of coal enterprises towards low-carbon and clean production has achieved remarkable results.(3)From 2009 to 2020,the non coal industry income of 34 listed companies in China’s coal mining industry increased by 8.21%annually.At the same time,the asset structure was adjusted,and nearly 80%of the asset structure evolution showed an orderly development trend.(4)The regression analysis results show that the entropy value of coal deep processing products and the entropy value of asset structure adjustment are significantly related to transformation performance.The paper proposes to summarize the successful experience of China’s coal energy economic transformation,lay a foundation for achieving the carbon peak and carbon neutral goals in the future,further increase the intensity of coal deep processing,increase the proportion of clean energy in total energy consumption,and strive to control asset operation towards the goal of increasing the proportion of non coal industry income.

An Appraisal of the Major National Dialogue as a Panacea to the Anglophone Crisis in Cameroon

This paper explores the Major National Dialogue organised by Paul Biya from the 30th of September to the 4th of October,2019 as a panacea to the Anglophone.The paper also seeks to find out if this dialogue has been the panacea Cameroonians as a whole and the people of Southern Cameroons in particular have been waiting for to end this conflict.This research uses a qualitative research design.This is because the researcher culled information from Jeune Afrique Economie(2019a),Cameroon Tribune,and from Phoenix.Descriptive analysis was used to analyse the collected data.Descriptive analysis is used to get the views of the public whether the Major National Dialogue was really a panacea to the Anglophone crisis.The analysis revealed that there were two opposing opinions on the holding of this dialogue.The government thinks the dialogue was a panacea to put an end to this crisis because there is ongoing construction work in the war zones,and economic activities have witnessed an increase in the regions as the various production units of the Cameroon Development Corporation(CDC)and Pamol plantations have regained agricultural activities.The Ndawara tea estate now functions without problems.Trans-border trade is on the rise and transportation is fluid,except in the rural areas where the state of the road network is poor to name but these.On the other hand,politicians,political parties like the Social Democratic Front,activists,religious leaders,the affected populations,and Cameroonians at large think that the Major National Dialogue was a monologue and therefore was bound to fail because first,key actors arrested and detained in connection to this crisis were not part of this dialogue.For this reason,they are calling for a genuine and an inclusive dialogue.In addition,they argue that we cannot be talking of peace when fighting is still raging on and people are being killed,houses and schools are being burnt,and people are being kidnapped every day for ransom to mention but these.

Analysis of the Current Situation of Drug Clinical Trial Institutions in Shaanxi Province

To understand the current situation of institutional registration in Shaanxi Province after the implementation ofregistration system management in drug clinical trial institutions.Relevant information was collected on the“Announcement on the Accreditation of Drug Clinical Trial Institutions”issued by the National Medical Products Administration from 2005 to August 2022,the record management information system of drug and medical device clinical trial institutions,and the drug clinical trial registration and information publicity platform.A retrospective analysis was carried out in terms of institutional development,regional distribution,registered majors,principal investigators,and the number of drug clinical trials.After the implementation of institution registration,the number of drug clinical trial institutions in Shaanxi Province increased by 47.4%,884 principal investigators were registered,the number of registered majors expanded from 58 qualified to 117,and the professional scope increased by 50.4%.The policy of institution registration is conducive to promoting the rational use of medical resources and the development of drug clinical trial institutions and improving the healthy development of the pharmaceutical industry in Shaanxi Province.

Analysis of New Senior English for China Student’s Book 1

This article will firstly discuss the context overview of English teaching and learning in China. Under thiscircumstance, a problematic element will be examined of the New Senior English for China Student’s Book 1 and critical appraisal ofhow this element relates to other elements of curriculum development will be analyzed. The recommended changes and demonstrationmechanisms for evaluating the changes are put forward in the last two parts.

Using shape contexts method for registration of contra lateral breasts in thermal images

AIM: To achieve symmetric boundaries for left and right breasts boundaries in thermal images by registration. METHODS: The proposed method for registration consists of two steps. In the first step, shape context, an approach as presented by Belongie and Malik was applied for registration of two breast boundaries. The shape context is an approach to measure shape similarity. Two sets of finite sample points from shape contours of two breasts are then presented. Consequently, the correspondences between the two shapes are found. By finding correspondences, the sample point which has the most similar shape context is obtained. RESULTS: In this study, a line up transformation which maps one shape onto the other has been estimated in order to complete shape. The used of a thin plate spline permitted good estimation of a plane transformation which has capability to map unselective points from one shape onto the other. The obtained aligningtransformation of boundaries points has been applied successfully to map the two breasts interior points. Some of advantages for using shape context method in this work are as follows:(1) no special land marks or key points are needed;(2) it is tolerant to all common shape deformation; and(3) although it is uncomplicated and straightforward to use, it gives remarkably powerful descriptor for point sets significantly upgrading point set registration. Results are very promising. The proposed algorithm was implemented for 32 cases. Boundary registration is done perfectly for 28 cases.CONCLUSION: We used shape contexts method that is simple and easy to implement to achieve symmetric boundaries for left and right breasts boundaries in thermal images.

Evaluation of Deformable Image Registration and Dose Accumulation Using Histogram Matching Algorithm between kVCT and MVCT with Helical Tomotherapy

Purpose: To evaluate the accuracy of deformable image registration (DIR) between the planning kVCT (pCT) and the daily MVCT combined with the histogram matching (HM) algorithm, and evaluate the deformable dose accumulation using a suggested method for adaptive radiotherapy with Helical Tomotharapy (HT). Methods: For five prostate cancer patients (76 Gy/38 Fr) treated with HT in our institution, seven MVCT series (a total of 35 series) acquired weekly were investigated. First, to minimize the effect of different HU values between pCT and MVCT, this image-processing method adjusts HU values between pCT and MVCT images by using image cumulative histograms of HU values, generating an HM-MVCT. Then, the DIR of the pCT to the HM-MVCT was performed, generating a deformed pCT. Finally, deformable dose accumulation was performed toward the pCT image. Results: The accuracy of DIR was significantly improved by using the HM algorithm, compared with non-HM method for several structures (p ±0.05, 0.83 ±0.06, and 0.90 ± 0.04 for the CTV, rectum, and bladder, respectively, while that of the HM method was 0.81 ±0.06, 0.81 ±0.04, and 0.92 ±0.06, respectively. For the deformable dose accumulation, some difference was observed between the two methods, particularly for the small calculated regions, such as rectum V60 and V70. Conclusion: Adapting the HM method can improve the accuracy of DIR. Furthermore, dose calculation using the deformed pCT using HM methods can be an effective tool for adaptive radiotherapy.

Cone beam computed tomography-guided differences among registration methods for lung cancer and the effects of tumor position,treatment model,and tumor size on positioning errors

Objective To explore the differences in three different registration methods of cone beam computed tomography(CBCT)-guided down-regulated intense radiation therapy for lung cancer as well as the effects of tumor location,treatment mode,and tumor size on registration.Methods This retrospective analysis included 80 lung cancer patients undergoing radiotherapy in our hospital from November 2017 to October 2019 and compared automatic bone registration,automatic grayscale(t+r)registration,and automatic grayscale(t)positioning error on the X-,Y-,and Z-axes under three types of registration methods.The patients were also grouped according to tumor position,treatment mode,and tumor size to compare positioning errors.Results On the X-,Y-,and Z-axes,automatic grayscale(t+r)and automatic grayscale(t)registration showed a better trend.Analysis of the different treatment modes showed differences in the three registration methods;however,these were not statistically significant.Analysis according to tumor sizes showed significant differences between the three registration methods(P<0.05).Analysis according to tumor positions showed differences in the X-and Y-axes that were not significant(P>0.05),while the autopsy registration in the Z-axis showed the largest difference in the mediastinal and hilar lymph nodes(P<0.05).Conclusion The treatment mode was not the main factor affecting registration error in lung cancer.Three registration methods are available for tumors in the upper and lower lungs measuring<3 cm;among these,automatic gray registration is recommended,while any gray registration method is recommended for tumors located in the mediastinal hilar site measuring<3 cm and in the upper and lower lungs≥3 cm.

Design and Experiments of Ultrasound Image-Guided Multi-DOF Robot System for Brachytherapy

To implant radioactive seeds through a needle precisely and safely, a novel multi-DOF surgical robotic system is presented in this paper for percutaneous prostate intervention through the patient’s perineum under real-time ultrasound image guidance. The proposed robot, which is designed with 9-DOF, consists of a 3-DOF automatic location platform for position adjustment, 2-DOF for automatic ultrasonic probe adjustment mounted with electromagnetic trackers, and 4-DOF for manually adjusting the guided template. Meanwhile, a new registration method based on the quaternion algorithm and least square method is developed, and the needle insertion is performed under the real-time guidance of a navigation system. Furthermore, the robot system has undergone some preliminary experiments with a laser tracker to evaluate the repeatability and accuracy of the robot system. The location error of the puncture needle tip can be controlled under 0.7 mm in air for the whole robotic system. The acquired results endorse the precision of the robot system for prostate seed implantation brachytherapy. © 2017, Tianjin University and Springer-Verlag GmbH Germany.

A Study on Forecasting System of Patent Registration Based on Bayesian Network

Recently the importance of intellectual property has been increased. There has been various ways of research on analy- sis of companies, forecast of technology and so on through patents and many investments of money and time. Unlike traditional method of patent analysis such as company analysis, forecasting technologies, this research is to suggest the ways to forecast registration and rejection of patents which help minimize the efforts to register patents. To do so, in- formation such as inventors, applicants, application date, and IPC codes were extracted to be used as input variables for analyzing Bayesian network. Especially, among various forms of Bayesian network, we used Tree Augmented NBN (TAN) to forecast registration and rejection of patent. This is because, TAN was assumed to have dependence between variables. As a result of this Bayesian network, it was shown that there are nearly more than 80% of accuracy to fore- cast registration and rejection of patents. Therefore, we expect the minimization of time and cost of registration by forecasting registration and rejection of R&D patent through this research.