Local Method Research Articles

Vibration analysis and experimental study of three-dimensional orthogonally coupled plates with through edge cracks

A modeling method for transverse vibration of three-dimensional (3D) orthogonally coupled plates is proposed and the through cracks located at coupling edges are considered. Corresponding experimental tests are performed to validate the effectiveness of this method. The main conflict for modelling 3D orthogonally coupled plates lies in the conflict of local coordinates of neighboring plates at the orthogonally coupled edge. The resolution of this conflict is effectively achieved by employing local collocation points method, this method is used to derive a universal expression for the coupling of plates under any coordinate system. Several cases were analyzed to compare natural frequencies, modal shapes, and dynamic responses against reference and experimental findings. Consequently, the present results are found to closely align with the measured outcomes, confirming the convergence and correctness of the proposed model and its solutions. The effects of crack parameters, such as length and number, on the vibration characteristics of orthogonally coupled plate structures are investigated. It is found that the vibrational characteristics of the coupled plates are more sensitive to the presence and variation of cracks at high frequencies. In the case of this study, as the number of cracks increases, response peaks appear at lower frequencies, with the maximum peak differing by up to twice. These findings are shown to have significant practical implications for understanding and predicting the effects of cracks in real orthogonally coupled plate structures. The effectiveness and convenience of the modeling approach for three-dimensional orthogonally coupled plates with through cracks are demonstrated in this study.

Local Discontinuous Galerkin Methods with Decoupled Implicit-Explicit Time Marching for the Growth-Mediated Autochemotactic Pattern Formation Model

Local Discontinuous Galerkin Methods with Decoupled Implicit-Explicit Time Marching for the Growth-Mediated Autochemotactic Pattern Formation Model

Do FDI inflows bring both capital and CO2 emissions? Evidence from non-parametric modelling for the G7 countries

Foreign direct investment profoundly influences environmental conditions while promoting economic growth. This study examines the effects of FDI on CO2 emissions across the G7 countries from 1971 to 2020. Utilizing panel data, we employ a local linear dummy variable estimation method to analyze the non-linear and time-varying relationships between FDI and CO2 emissions. Our findings reveal a negative correlation between FDI and CO2 emissions during the period 1971–1995. In contrast, from 2000 to 2015, a significant positive correlation is observed. After 2015, no significant relationship is detected. Furthermore, we investigate the moderating effect of trade openness, urbanization level, and energy consumption to gain a deeper understanding of how the relationship between FDI and CO2 emissions is influenced under different national contexts. These findings underscore the dynamic nature of the relationship between FDI and CO2 emissions, offering significant implications for the advancement of a low-carbon economy.

Nonexcavation Localization Method for Buried PE Pipes Based on Elastic Wave Reflection Imaging and the BPA Method

Nonexcavation Localization Method for Buried PE Pipes Based on Elastic Wave Reflection Imaging and the BPA Method

Pilot study to evaluate automated laboratory data transfer into Medidata Rave for NCI-supported pediatric cooperative group trials in the Pediatric Early Phase Clinical Trials Network (PEP-CTN) and Pediatric Brain Tumor Consortium (PBTC).

e23017 Background: Electronic data capture (EDC) has the potential to improve data accuracy and efficiency. As an initial step toward improvement in the accuracy and completeness of data acquisition for clinical trials, PEP-CTN and PBTC conducted a pilot project to assess the feasibility of automated transfer of laboratory data from participating institutions’ electronic health records to the NCI Medidata Rave EDC that is housed within each consortium’s Uniform Resource Locator (URL). The pilot aimed to assess feasibility of automated laboratory data extraction and transfer and to evaluate discrepancies between laboratory data obtained retrospectively through automated extraction and data manually ascertained during the original conduct of the study. Methods: Data from patients treated on 7 completed PEP-CTN or PBTC trials at 7 sites were included. Each consortium created a Rave EDC study to receive data. Sites used the ExtractEHR R package or local methods to map and extract laboratory data for designated patients. Post-extraction data were uploaded via a file transfer protocol (FTP) periodically polled by the Rave Batch Uploader (BU) that uploaded data into Rave EDC. After successful upload, extracted data (EHR) were compared to laboratory data that had been manually reported when patients were enrolled on the trials (MANUAL) and discrepancies were identified. Discrepancy types were categorized and 2 sites reviewed discrepancies at their sites to identify reasons. Results: Preparation and support for automated extraction and upload required significant central operations and local site effort. All sites successfully extracted specified laboratory data and had at least one complete upload via BU to Rave EDC. There were more laboratory data in the EHR datasets than MANUAL datasets across most sites. These results were due to multiple EHR results on a given day or from additional days in the study window than specified in MANUAL. Sites verified that laboratory data in MANUAL and not EHR were stored in un-extractable formats (e.g. PDFs) or outside laboratories. Most discrepant results in both EHR and MANUAL were mismatched values or units. Conclusions: This pilot demonstrated the feasibility of implementing automated laboratory data extraction and transfer in the cooperative group setting. Automated data transfer requires significant central operational support as well as detailed protocols, data specifications, and case report forms and engagement of site technical teams to be successful, but also permits collection of more comprehensive data with reduced manual data entry. Clinical trial information: NCT05020951 .

Research on New Energy Transmission Line Fault Localization Method Based on APSVMD-NTEO

Abstract Given the new energy transmission line fault, traveling wave head detection difficulties, wave speed uncertainty, positioning errors, and other problems, this paper proposes a new Teager energy operator based on adaptive parameter selection variational mode decomposition (APSVMD) and new energy transmission line fault location method (NTEO). The envelope fuzzy entropy is introduced to select the key parameters of SVM, and the sampling range of the Teager energy operator (TEO) is improved to effectively improve the capture accuracy of the wave head. In terms of fault location, by improving the double-ended traveling wave method, the uncertainty of wave speed and the effect of actual line length error is eliminated, and the ranging error is reduced.

Neural representations of statistical and rule-based predictions in Gilles de la Tourette syndrome.

Gilles de la Tourette syndrome (GTS) is a disorder characterised by motor and vocal tics, which may represent habitual actions as a result of enhanced learning of associations between stimuli and responses (S-R). In this study, we investigated how adults with GTS and healthy controls (HC) learn two types of regularities in a sequence: statistics (non-adjacent probabilities) and rules (predefined order). Participants completed a visuomotor sequence learning task while EEG was recorded. To understand the neurophysiological underpinnings of these regularities in GTS, multivariate pattern analyses on the temporally decomposed EEG signal as well as sLORETA source localisation method were conducted. We found that people with GTS showed superior statistical learning but comparable rule-based learning compared to HC participants. Adults with GTS had different neural representations for both statistics and rules than HC adults; specifically, adults with GTS maintained the regularity representations longer and had more overlap between them than HCs. Moreover, over different time scales, distinct fronto-parietal structures contribute to statistical learning in the GTS and HC groups. We propose that hyper-learning in GTS is a consequence of the altered sensitivity to encode complex statistics, which might lead to habitual actions.

A damage localization technique using wave front shapes in composite laminates without knowing the velocity profile

Composite laminates are widely used in various fields, but their structures are prone to cracks and damage. Due to the difference in angles of the instantaneous direction of the wave front propagation and the direction of the energy flow in an anisotropic material, the use of Lamb waves for damage localization in composite laminates is a challenging task. Establishing the wave front shape equation can overcome the difficulty of damage localization caused by anisotropy, but this usually requires a priori knowledge of the acoustic velocity distribution of the laminates, which is not convenient for efficient damage localization. In this paper, a damage localization method based on wave front shapes for composite laminates without any knowledge of the velocity profile is presented. Numerical simulation and experimental results show that the proposed method works. This method shows good damage localization accuracy and has broad application prospects in non-destructive testing for plate structures with strong anisotropy.

Accurate Fault Location Method for Multiple Faults in Transmission Networks Using Travelling Waves

Accurate Fault Location Method for Multiple Faults in Transmission Networks Using Travelling Waves

Chemical reaction inspired approach for routing problems with hard time constraints

ABSTRACT One of the most common issues in logistics and transportation planning is the vehicle routing problem. The objective is to find minimum cost-vehicle routes for serving a set of dispersed customers with deterministic demands while satisfying some constraints. In this paper, we focus on two main constraints, which are vehicle capacity and time windows for customers. We propose to tackle this NP-hard problem with a bio-inspired approach based on a hybridization of Chemical Reaction Optimization and local search method. The solving process of our approach mimics the chemical reactions between molecules to attain their stability with lowest energy. For more diversification of the search space, we involved in the initialization stage a local search method based on greedy adaptive procedure. The performances of our hybrid approach are assessed on the base of various benchmark instances. Simulation results show the good performances and the efficiency of the proposed approach.

A Real Time Facial Recognition and Tracking System for Personnel Presence

Abstract: Our project aims to revolutionize the conventional attendance system by implementing a facial recognition-based solution. The existing manual methods are prone to human error and require significant maintenance. By leveraging facial recognition technology, our system will offer improved precision and efficiency, reducing the need for manual work. The system will maintain a database of students' images, matching them during class to mark attendance accurately. Utilizing machine learning techniques, specially the Haar-Cascade classifier and local binary pattern histogram method for face detection and recognition, respectively, our system will ensure reliable attendance tracking. The attendance data will be stored in a MySQL database and Microsoft Excel file, providing a streamlined and secure alternative to the traditional attendance process.

Religious Chanting and Self-Related Brain Regions: A Multi-Modal Neuroimaging Study.

This protocol presents a multi-modal neuroimaging approach to explore the potential brain activity associated with repetitive religious chanting, a widespread form of mind training in both Eastern and Western cultures. High-density electroencephalogram (EEG), with its superior temporal resolution, allows for capturing the dynamic changes in brain activity during religious chanting. Through source localization methods, these can be attributed to various alternative potential brain region sources. Twenty practitioners of religious chanting were measured with EEG. However, the spatial resolution of EEG is less precise, in comparison to functional magnetic resonance imaging (fMRI). Thus, one highly experienced practitioner underwent an fMRI scanning session to guide the source localization more precisely. The fMRI data helped guide the selection of EEG source localization, making the calculation of K-means of the EEG source localization in the group of 20 intermediate practitioners more precise and reliable. This method enhanced EEG's ability to identify the brain regions specifically engaged during religious chanting, particularly the cardinal role of the posterior cingulate cortex (PCC). The PCC is a brain area related to focus and self-referential processing. These multimodal neuroimaging and neurophysiological results reveal that repetitive religious chanting can induce lower centrality and higher delta-wave power compared to non-religious chanting and resting state conditions. The combination of fMRI and EEG source analysis provides a more detailed understanding of the brain's response to repetitive religious chanting. The protocol contributes significantly to the research on the neural mechanisms involved in religious and meditative practices, which is becoming more prominent nowadays. The results of this study could have significant implications for developing future neurofeedback techniques and psychological interventions.

Knowledge and practices related to plague persistence in plague-endemic foci, Mbulu District, Tanzania.

Plague continues to be a major public health concern in African countries. Several social practices and environmental conditions have been associated with the reoccurrence of bubonic plague, especially in places where the disease is prevalent. Therefore, it remains important to understand people knowledge, behavior and practices related to disease risks in order to identify factors that may hinder prevention and control strategies in the foci. A study survey of 100 households was conducted in Mbulu district to assess plague knowledge, factors that influence flea bite and measures used for rodent and flea control. Majority of participants (86%) were familiar with the plague disease and about (50%) mentioned swelling lymph nodes as a common symptom. Most of the participants (62%) claimed to observe human plague cases during the long rain season. The majority of participants (97%) reported to experience flea bite in their domestic settings, with most stating that they experienced more flea bites during the dry season. Houses with livestock had a greater likelihood of flea bite (OR = 2.7; 95% CI: 0.36-18.80, p = 0.267) compared to houses with no livestock. Furthermore, residents reported using both local and chemical methods to control rodents and flea inside houses. Most respondents preferred using local methods in flea control. Respondents stated that the efficacy of flea control methods being applied ranged from few days to several months. There was limited knowledge of the residual effects of the agricultural chemicals being used to control fleas among the surveyed community. Our study highlights the importance of raising awareness and adopting effective control methods for controlling fleas and lower the risk of plague transmission and other flea borne diseases in the local communities. Sensitization of the local community on the use of appropriate chemicals for flea control is urgent to avoid any potential long-term impacts of the residual effects on the health of the local communities.

Insider Research in Migration and Music Sociology: Contextualizing Indigenous and (G)local Method(ologie)s in Studying Migrant Musicians

Insider Research in Migration and Music Sociology: Contextualizing Indigenous and (G)local Method(ologie)s in Studying Migrant Musicians

Site Suitability Evaluation of a Large Commercial Complex Using an Improved Projection Pursuit Model

In developing countries, especially China, large-scale commercial complexes are the current trend in commercial real estate. Compared with other similar buildings, scientific site selection is very important for the smooth construction and efficient operation of these complexes. However, there is still a lack of a targeted evaluation index system and quantitative evaluation methods. Therefore, this paper put forward the evaluation index system and method of large-scale commercial-complex location based on a projection pursuit model. First, this paper comprehensively considered the environmental, social, and economic factors, and used secondary and tertiary indicators to systematically establish an evaluation index system. This index system effectively dealt with the complex problem of its site selection. Compared with the traditional multi-attribute evaluation method based on expert advice, the evaluation method of the improved projection pursuit model based on a sparrow search algorithm constructed in this paper was to mine key information from the evaluation data, which could evaluate the site suitability of large commercial complexes more scientifically and objectively. In addition, this paper made a detailed empirical study of the Joy City project in Nanchang, China. The research results found the key factors affecting the site selection of the project and determined that the site-selection evaluation result of the project was medium. The research results of this paper provide the scientific and objective decision-making basis for the development enterprises of large commercial complexes to reduce site-selection risk and improve investment efficiency.

Formulation and evaluation of transdermal patch of carbamazepine

Transdermal drug delivery system (TDDS) is a widely accepted mode of drug delivery method due to various advantages and one of the novel routes for systemic delivery of drugs through intact skin. Topical drug administration is a systemic and localized method of delivering drugs through skin and is considered an attractive alternative to oral and parenteral routes. The aim of present study was to formulate and evaluate Matrix type transdermal drug delivery system (TDDS) of Carbamazepine was prepared by the solvent evaporation technique. Several batches were prepared by using combination of HPMC E-15, Eudragit RL-100, and Ethyl Cellulose different ratios. Propylene glycol was used as plasticizer and DMSO was incorporated as a permeation enhancer. These Formulated transdermal patches were characterized for their physicochemical parameters like thickness, weight variation, folding endurance, percentage moisture uptake, Percentage moisture uptake and In vitro drug release studies were examined. Among the above all formulation F6 was chosen as a best Formulation, because this optimised formulation showed satisfactory drug content, physical characteristic for its thickness, weight uniformity, percentage moisture content, percentage moisture uptake, and maximum % of drug release i.e., 93.95 % in 12 hours. The optimized formulation (F6) showed maximum highest percentage of drug release.

Exploring the Substructure of the Near-surface Shear Layer of the Sun

The gradient of rotation in the near-surface shear layer (NSSL) of the Sun provides valuable insights into the dynamics associated with the solar activity cycle and the dynamo. Results obtained with global oscillation mode splittings lack resolution near the surface, prompting the use of the local helioseismic ring-diagram method. While the Helioseismic and Magnetic Imager ring-analysis pipeline has been used previously for analyzing this layer, default pipeline parameters limit the accuracy of the near-surface gradients. To address these challenges, we fitted the flow parameters to power spectra averaged over one-year periods at each location, followed by additional averaging over 12 yr. We find that the NSSL can be divided into three fairly distinct regions: a deeper, larger region with a small shear, steepening toward the surface; a narrow middle layer with a strong shear, with a gradient approximately 3 times larger; and a layer very close to the surface, where the logarithmic gradient is close to zero but becomes steeper again toward the surface. The middle layer appears to be centered at 3 Mm, but the poor resolution in these layers implies that it is potentially located closer to the surface, around 1.5 Mm deep. While our analysis primarily focused on regions along the central meridian, we also investigated systematic errors at longitudes off the center. The east–west antisymmetric component of the gradient reveals a layer of substantial differences between the east and west longitude of around 1.7 Mm, and the amplitude of the differences increases with the longitude.

Improvement of assessment system of investment attractiveness of regions

The article studies some foreign and local methods of assessing the investment attractiveness of regions, and based on these, the author proposed a system for assessing the investment attractiveness in regions. Formulas for calculating investment potential and investment risk indicators have been displayed in this assessment system and the region can be assessed based on the results.

Map-based localization for intelligent vehicles based on fusion of multiple visual features in underground parking

The ‘last mile’ problem in intelligent car localization within underground parking lots presents challenges such as localization blind spots and feature extraction difficulties. To tackle these issues, this paper proposes a mapping and multiscale matching localization method based on the fusion of multiple feature sources using a ‘binocular mapping, monocular localization’ approach. By combining traditional features with deep learning features, the proposed method enhances feature matching accuracy and addresses feature extraction challenges. A sparse three-dimensional reconstruction method based on local feature-optical flow is also proposed to mitigate localization blind spots. During the mapping process, the underground parking lot scene is segmented into several nodes to store map information, each consisting of a feature layer, scene structure layer, and trajectory layer. In the multiscale matching localization process, ORB, LoFTR, and BoW multisource features are fused to achieve feature matching, determine the nearest node, and estimate vehicle pose using the PnP model through optical flow. Finally, a localization optimization algorithm outputs the localization result. Experiments were conducted across multiple underground parking lots encompassing a total area of over 100,000 square meters. The results demonstrated that the average error of map construction using the proposed algorithm is approximately 15 mm, and the average error rate of localization is 4.45%.

Spatial acoustic emission localization method for damage to prestressed steel strands of girders using special-shaped waveguide rods

As an essential load-bearing member of post-tensioned prestressed girders, prestressed steel strands will inevitably reduce the safety and durability of the bridge if damaged. However, traditional damage localization methods for the steel strand require numerous acoustic emission (AE) sensors with a complex arrangement in the prestressed girder. This study proposes a spatial AE localization method using a dual-sensor array with the assistance of special-shaped waveguide rods. The spatial damage localization is achieved by combining the time difference of arrival (TDOA) of the AE wave with the propagation attenuation law. Transverse and longitudinal damage localization for prestressed steel strands are verified on a simplified platform containing different special-shaped waveguide rods. For transverse damage localization, the TDOA of the maximum AE amplitudes is superior to that of the first waves. For longitudinal damage localization, the relative localization accuracy reaches 94%. With this method, only two AE sensors are required to localize the three-dimensional damage to the prestressed steel strands in a girder.