Dynamic Interaction Analysis of Coupled Axial-Torsional-Lateral Mechanical Vibrations in Rotary Drilling Systems

Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and petroleum.To achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emphasis on structural durability and monitoring is required.This study focuses on the mechanical vibrations that occur in rotary drilling systems,which have a substantial impact on the structural integrity of drilling equipment.The study specifically investigates axial,torsional,and lateral vibrations,which might lead to negative consequences such as bit-bounce,chaotic whirling,and high-frequency stick-slip.These events not only hinder the efficiency of drilling but also lead to exhaustion and harm to the system’s components since they are difficult to be detected and controlled in real time.The study investigates the dynamic interactions of these vibrations,specifically in their high-frequency modes,usingfield data obtained from measurement while drilling.Thefindings have demonstrated the effect of strong coupling between the high-frequency modes of these vibrations on drilling sys-tem performance.The obtained results highlight the importance of considering the interconnected impacts of these vibrations when designing and implementing robust control systems.Therefore,integrating these compo-nents can increase the durability of drill bits and drill strings,as well as improve the ability to monitor and detect damage.Moreover,by exploiting thesefindings,the assessment of structural resilience in rotary drilling systems can be enhanced.Furthermore,the study demonstrates the capacity of structural health monitoring to improve the quality,dependability,and efficiency of rotary drilling systems in the petroleum industry.

ST-Map:an Interactive Map for Discovering Spatial and Temporal Patterns in Bibliographic Data

Getting insight into the spatiotemporal distribution patterns of knowledge innovation is receiving increasing attention from policymakers and economic research organizations.Many studies use bibliometric data to analyze the popularity of certain research topics,well-adopted methodologies,influential authors,and the interrelationships among research disciplines.However,the visual exploration of the patterns of research topics with an emphasis on their spatial and temporal distribution remains challenging.This study combined a Space-Time Cube(STC)and a 3D glyph to represent the complex multivariate bibliographic data.We further implemented a visual design by developing an interactive interface.The effectiveness,understandability,and engagement of ST-Map are evaluated by seven experts in geovisualization.The results suggest that it is promising to use three-dimensional visualization to show the overview and on-demand details on a single screen.

Advances in applying somatosensory interaction technology in geriatric care:A bibliometric analysis

Objectives:Somatosensory Interaction Technology(SIT)is used in various aspects of geriatric care.We aimed to conduct a bibliometric analysis to summarize relevant publications and visualize publication characteristics,current hotspots,and development trends,thereby inspiring subsequent researches.Methods:We searched theWeb of Science Core Collection database for publications on the application of SIT in geriatric care.Bibliometric visualization and clustering analysis were performed using VOSviewer V1.6.18 Software,while keywords burst detection analysis was conducted with CiteSpace 6.1.R6 Software.Results:After screening,a total of 1,019 publications were included.The number of publications on SIT in geriatric care is gradually increasing,exhibiting a rapid growth rate.The United States,Canada,and Australia led in terms of publication volume.Keyword clustering analysis identified major research hotspots:crisis warning,somatic abilities,rehabilitation training and psychosocial support.Initial studies primarily explored themes such as recovery,movement,systems,and later shifted towards gait analysis,muscle strength,parameters,and home-based care.More recently,research themes have evolved to dementia,machine learning,and gamification.Conclusions:SIT is innovative for promoting active aging,advancing intelligent healthcare,and elevating the daily quality of life for older adults in clinical and domestic settings.Applications of SIT can be categorized into early warning systems for crises,detailed analyses of physical conditions,rehabilitation enhancement,and support for psychosocial health.Research trends have transitioned from whole-body recognition to precise feedback,from a focus on physical health to mental health,and from technical feasibility to user-friendliness.Future research should focus on developing accessible and user-friendly devices,fostering interdisciplinary collaborations for innovation,expanding research to address both the physical and mental health needs of diverse older adults,and integrating emerging technologies to enhance data precision and accelerate the development of intelligent platforms.

Transition Logic Regression Method to Identify Interactions in Binary Longitudinal Data

Logic regression is an adaptive regression method which searches for Boolean (logic) combinations of binary variables that best explain the variability in the outcome, and thus, it reveals interaction effects which are associated with the response. In this study, we extended logic regression to longitudinal data with binary response and proposed “Transition Logic Regression Method” to find interactions related to response. In this method, interaction effects over time were found by Annealing Algorithm with AIC (Akaike Information Criterion) as the score function of the model. Also, first and second orders Markov dependence were allowed to capture the correlation among successive observations of the same individual in longitudinal binary response. Performance of the method was evaluated with simulation study in various conditions. Proposed method was used to find interactions of SNPs and other risk factors related to low HDL over time in data of 329 participants of longitudinal TLGS study.

Context-Aware Animation Data Description and Interaction Method Based on Sketch

In this paper,an interactive method is proposed to describe computer animation data and accelerate the process of animation generation.First,a semantic model and a resource description framework(RDF)are utilized to analyze and describe the relationships between animation data.Second,a novel context model which is able to keep the context-awareness was proposed to facilitate data organization and storage.In our context model,all the main animation elements in a scene are operated as a whole.Then sketch is utilized as the main interactive method to describe the relationships between animation data,edit the context model and make some other user operations.Finally,a context-aware computer animation data description system based on sketch is generated and it also works well in animation generation process.

Spatial Interactions of China's Steel Output: An Empirical Analysis Based on Chinese Inter-provincial Panel Data

In view of the extensive growth of China's steel production in recent years, this paper analyzed the industrial development background and economic geography theory, and discussed the possible spatial interaction mechanism. Based on panel data of China's inter-provincial steel output from 2001 to 2015, using spatial econometric model, this paper also explored whether China's provincial steel production shows material orientation, market orientation and traffic orientation, and isolated spatial interactions of interprovincial steel output. The results showed that the inter-provincial steel production in China did show both material orientation, market orientation and traffic orientation and that there was a significant negative spatial interaction, indicating that there might be strong competition and a crowing-out effect between neighboring provinces, and that the smaller the spatial scope, the more significant the spatial interactions of steel production.

Revealing GE Interactions from Trial Data without Replications

Detecting genotype-by-environment (GE) interaction effects or yield stability is one of the most important components for crop trial data analysis, especially in historical crop trial data. However, it is statistically challenging to discover the GE interaction effects because many published data were just entry means under each environment rather than repeated field plot data. In this study, we propose a new methodology, which can be used to impute replicated trial data sets to reveal GE interactions from the original data. As a demonstration, we used a data set, which includes 28 potato genotypes and six environments with three replications to numerically evaluate the properties of this new imputation method. We compared the phenotypic means and predicted random effects from the imputed data with the results from the original data. The results from the imputed data were highly consistent with those from the original data set, indicating that imputed data from the method we proposed in this study can be used to reveal information including GE interaction effects harbored in the original data. Therefore, this study could pave a way to detect the GE interactions and other related information from historical crop trial reports when replications were not available.

Spatio-temporal Analysis of Urban Spatial Interaction in Globalizing China—A Case Study of Beijing-Shanghai Corridor

This paper aims to explore urban geography with a new perspective. Endowed with the urban geography connotations, an improved data field model is employed to integrate temporal dimension into spatial process of cities in a typical region in this article. Taking the Beijing-Shanghai Corridor including 18 cities as an example, the authors chose the city centricity index (CCI) and the spatial data field model to analyze the evolution process and features of sub-region and urban spatial interaction in this corridor based on the data of 1991, 1996 and 2002. Through the analy- sis, we found that: 1) with the improvement of the urbanization level and the development of urban economy, the cit- ies’ CCI grew, the urban spatial radiative potential enhanced and the radiative range expanded gradually, which reflects the urban spatial interaction’s intensity has been increasing greatly; 2) although the spatial interaction intensity among the cities and sub-regions in the Beijing-Shanghai Corridor was growing constantly, the gap of the spatial interaction strength among different cities and sub-regions was widening, and the spatial division between the developed areas and the less developed areas was obvious; and 3) the intensity of the spatial interaction of Beijing, Shanghai and their urban agglomerations was far greater than that in small cities of other parts of the corridor, and it may have a strong drive force on the choice of spatial location of the economic activities.

The Nonlinear Interaction Process in the Wave Assimilation Model and Its Experiments

This paper presents a composite interaction formula based on the discrete-interaction operator of wave-wave nonlinear interaction for deriving its adjoint source function in the wave assimilation model. Assimilation experiments were performed using the significant wave heights observed by the TOPES/POSEIDON satellite, and the gradient distribution in the physical space was also analyzed preliminarily.

Integration of Soil Information System and Interactive Self-Organizing Data for Agricultural Developing Zones in Red Soil Region

Integration of soil information system (SIS) and interactive self-organizing data (ISODATA) was studied to establish proper agricultural developing zones in red soil region of southern China which are of crucial importance to farmers, researchers, and decision makers while utilizing and managing red soil resources. SIS created by using ARC/INPO was used to provide data acquisition, systematic model parameter assignment, and visual display of analytic results. Topography, temperature, soil component (e.g., organic matter and pH) and condition of agricultural production were selected as parameters of ISODATA model. Taking Longyou County, Zhejiang Province as the case study area, the effect of the integration and recommendations are discussed for future research.

Advanced User-Based Interaction Model in Cloud

With the increasing popularity of cloud computing, there is an increased de mand for cloud resources in cloud. It has be come even more urgent to find solutions to improve resource utilization. From the per spective of a cloud consumer, a cloud applica tion processes a large information flow in volving user actions that access resources, but little work has so far been devoted to research from the perspective of the interaction be tween the user and the cloud application. In this paper, we analyze the interaction in detail, and propose a general mathematical interac tion model to formulate the challenge pertain ing to storage resource allocation as an opti mization problem, focusing on minimizing both the user＇s cost and server＇s consumption. A potential response mechanism is then de signed based on the interaction model. Fur thermore, the proposed model is used to ex plore strategies when multiple users access the same file simultaneously. Additionally, an improved queuing system, namely M/ G~ oo queue with standby, is introduced. Finally, an evaluation is presented to verify the interac- tion model.

Mixed Model, AMMI and Eberhart-Russel Comparison via Simulation on Genotype ×Environment Interaction Study in Sugarcane

Brazil is the world leader in sugarcane production and the largest sugar exporter. Developing new varieties is one of the main factors that contribute to yield increase. In order to select the best genotypes, during the final selection stage, varieties are tested in different environments (locations and years), and breeders need to estimate the phenotypic performance for main traits such as tons of cane yield per hectare (TCH) considering the genotype × environment interaction (GEI) effect. Geneticists and biometricians have used different methods and there is no clear consensus of the best method. In this study, we present a comparison of three methods, viz. Eberhart-Russel (ER), additive main effects and multiplicative interaction (AMMI) and mixed model (REML/BLUP), in a simulation study performed in the R computing environment to verify the effectiveness of each method in detecting GEI, and assess the particularities of each method from a statistical standpoint. In total, 63 cases representing different conditions were simulated, generating more than 34 million data points for analysis by each of the three methods. The results show that each method detects GEI differently in a different way, and each has some limitations. All three methods detected GEI effectively, but the mixed model showed higher sensitivity. When applying the GEI analysis, firstly it is important to verify the assumptions inherent in each method and these limitations should be taken into account when choosing the method to be used.

Online Data Processing Methods in Xlet Applications for Seismic Early Warning and Emergency Services on Interactive Digital Television

In this paper, I described the methods that I used for the creation of Xlets, which are Java applets that are developed for the IDTV environment;and the methods for online data retrieval and processing that I utilized in these Xlets. The themes that I chose for the Xlets of the IDTV applications are Earthquake and Tsunami Early Warning;Recent Seismic Activity Report;and Emergency Services. The online data regarding the Recent Seismic Activity Report application are provided by the Kandilli Observatory and Earthquake Research Institute (KOERI) of Bogazici University in Istanbul;while the online data for the Earthquake and Tsunami Early Warning and the Emergency Services applications are provided by the Godoro website which I used for storing (and retrieving by the Xlets) the earthquake and tsunami early warning simulation data, and the DVB network subscriber data (such as name and address information) for utilizing in the Emergency Services (Police, Ambulance and Fire Department) application. I have focused on the methodologies to use digital television as an efficient medium to convey timely and useful information regarding seismic warning data to the public, which forms the main research topic of this paper.

A novel computational method for protein-protein interaction networks prediction of alpha-synuclein

Alpha-synuclein plays an important role in Parkinson's disease(PD).The current study of alpha-synuclein mainly concentrates at the gene level.However, it is found that the study at the protein level has special significance.Meanwhile, there is free information on the Internet, such as databases and algorithms of protein-protein interactions(PPIs).In this paper, a novel method which integrates distributed heterogeneous data sources and algorithms to predict PPIs for alpha-synuclein in silico is proposed.The PPIs generated by the method take advantage of various experimental data, and indicate new information about PPIs for alpha-synuclein.In the end of this paper, the result illustrates that the method is practical.It is hoped that the prediction result obtained by this method can provide guidance for biological experiments of PPIs for alpha-synuclein to reveal possible mechanisms of PD.

Interactive Generalization on Large-Scale Topographical Map Supported by a Database Platform

This paper makes astudy on the interactive digital gener-alization, where map generalizationcan be divided into intellective reason-ing procedure and operational proce-dure, which are done by human andcomputer, respectively. And an inter-active map generalization environmentfor large scale topographic map is thendesigned and realized. This researchfocuses on: ① the significance of re-searching an interactive map generali-zation environment, ② the features oflarge scale topographic map and inter-active map generalization, ③ the con-struction of map generalization-orien-ted database platform.

MINE:A Method of Multi-Interaction Heterogeneous Information Network Embedding

Interactivity is the most significant feature of network data,especially in social networks.Existing network embedding methods have achieved remarkable results in learning network structure and node attributes,but do not pay attention to the multi-interaction between nodes,which limits the extraction and mining of potential deep interactions between nodes.To tackle the problem,we propose a method called Multi-Interaction heterogeneous information Network Embedding(MINE).Firstly,we introduced the multi-interactions heterogeneous information network and extracted complex heterogeneous relation sequences by the multi-interaction extraction algorithm.Secondly,we use a well-designed multi-relationship network fusion model based on the attention mechanism to fuse multiple interactional relationships.Finally,applying a multitasking model makes the learned vector contain richer semantic relationships.A large number of practical experiments prove that our proposed method outperforms existing methods on multiple data sets.

Galaxy Interactions in Filaments and Sheets:Insights from EAGLE Simulations

We study the color and star formation rates of paired galaxies in filaments and sheets using the EAGLE simulations.We find that the major pairs with pair separation<50 kpc are bluer and more star-forming in filamentary environments compared to those hosted in sheet-like environments.This trend reverses beyond a pair separation of~50 kpc.The interacting pairs with larger separations(>50 kpc)in filaments are on average redder and low-star-forming compared to those embedded in sheets.The galaxies in filaments and sheets may have different stellar mass and cold gas mass distributions.Using a KS test,we find that for paired galaxies with pair separation<50 kpc,there are no significant differences in these properties in sheets and filaments.The filaments transport gas toward the cluster of galaxies.Some earlier studies find preferential alignment of galaxy pairs with the filament axis.Such alignment of galaxy pairs may lead to different gas accretion efficiency in galaxies residing in filaments and sheets.We propose that the enhancement of star formation rate at smaller pair separation in filaments is caused by the alignment of galaxy pairs.A recent study with SDSS data reports the same findings.The confirmation of these results by the EAGLE simulations suggests that the hydrodynamical simulations are powerful theoretical tools for studying galaxy formation and evolution in the cosmic web.

Specificities of the Local Data and Interactive Visualization

The objective is to know and to exploit specificities of the local data because Madagascar needs to the media economic surveys deepened on its cultural and social diversities. The problems remain on the facts that the journalists are exceeded by the events and are often constrained to be unaware of the environment of proximity--policies, societies, and economics which could become inexhaustible sources. In this case, how and up to what point will they manage to collect all the data related there, to exploit them and to place them at the disposal of the public？ We chose a methodology of investigation according to the research methods developed for the study of the industrial and agricultural systems （Bear, Gibbon, Haggblade, ＆ Ritchie, 1993; Boomgard, Davies, Haggblade, ＆ Mead, 1992; Laurent, 1993; Montigaud, 1992） in order to establish the cartography of the media, the actors, the sets of themes to the menu. This enabled us to raise a whole proliferation of the media. The lnternet has also been diffused since 1997.

Uncertainties of ENSO-related Regional Hadley Circulation Anomalies within Eight Reanalysis Datasets

El Nino-Southern Oscillation(ENSO),the leading mode of global interannual variability,usually intensifies the Hadley Circulation(HC),and meanwhile constrains its meridional extension,leading to an equatorward movement of the jet system.Previous studies have investigated the response of HC to ENSO events using different reanalysis datasets and evaluated their capability in capturing the main features of ENSO-associated HC anomalies.However,these studies mainly focused on the global HC,represented by a zonal-mean mass stream function(MSF).Comparatively fewer studies have evaluated HC responses from a regional perspective,partly due to the prerequisite of the Stokes MSF,which prevents us from integrating a regional HC.In this study,we adopt a recently developed technique to construct the three-dimensional structure of HC and evaluate the capability of eight state-of-the-art reanalyses in reproducing the regional HC response to ENSO events.Results show that all eight reanalyses reproduce the spatial structure of HC responses well,with an intensified HC around the central-eastern Pacific but weakened circulations around the Indo-Pacific warm pool and tropical Atlantic.The spatial correlation coefficient of the three-dimensional HC anomalies among the different datasets is always larger than 0.93.However,these datasets may not capture the amplitudes of the HC responses well.This uncertainty is especially large for ENSO-associated equatorially asymmetric HC anomalies,with the maximum amplitude in Climate Forecast System Reanalysis(CFSR)being about 2.7 times the minimum value in the Twentieth Century Reanalysis(20CR).One should be careful when using reanalysis data to evaluate the intensity of ENSO-associated HC anomalies.

Data Visualization in Big Data Analysis: Applications and Future Trends

The advent of the big data era has made data visualization a crucial tool for enhancing the efficiency and insights of data analysis. This theoretical research delves into the current applications and potential future trends of data visualization in big data analysis. The article first systematically reviews the theoretical foundations and technological evolution of data visualization, and thoroughly analyzes the challenges faced by visualization in the big data environment, such as massive data processing, real-time visualization requirements, and multi-dimensional data display. Through extensive literature research, it explores innovative application cases and theoretical models of data visualization in multiple fields including business intelligence, scientific research, and public decision-making. The study reveals that interactive visualization, real-time visualization, and immersive visualization technologies may become the main directions for future development and analyzes the potential of these technologies in enhancing user experience and data comprehension. The paper also delves into the theoretical potential of artificial intelligence technology in enhancing data visualization capabilities, such as automated chart generation, intelligent recommendation of visualization schemes, and adaptive visualization interfaces. The research also focuses on the role of data visualization in promoting interdisciplinary collaboration and data democratization. Finally, the paper proposes theoretical suggestions for promoting data visualization technology innovation and application popularization, including strengthening visualization literacy education, developing standardized visualization frameworks, and promoting open-source sharing of visualization tools. This study provides a comprehensive theoretical perspective for understanding the importance of data visualization in the big data era and its future development directions.