Boundary Of Body Research Articles

Stress Analysis of Radial Compression Disk Based on MATLAB

Elastic mechanics is an important branch of solid mechanics, mainly studies the deformation and internal force of elastic objects under the action of external forces and other external factors, also known as elastic theory. The study object of elasticity is elastomer. The detailed theoretical structure helps us solve more practical engineering problems. We used Matlab software in the data simulation for visualization processing. On the basis of the study of elasticity, this paper explores the stress distribution of the uniform ideal elastic body to the radial compression disk model, and observes the change of the stress of the radial compression disk when the external pressure changes gradually. The expressions of the corresponding stress components , and are obtained by using the theory of normal concentrated force on the boundary of a half plane body. The stress solutions considering the thickness t of the disk are derived. Finally, the drawing software in Matlab software is used to visualize the theoretical derivation results in order to intuitively feel the change of stress. After the data simulation, the data simulation results are compared with the stress analysis results derived from the theoretical deduction, and the conclusion is drawn.

Women Academics Forgo Childbirth for Career Progression? Performances of Their Body Boundaries

ABSTRACTIn recent decades, research has explored tension between women academics' motherhood and institutional discourse. This study, however, delves into the performances of nine Chinese women academics who are mothers and their body boundaries between motherhood and career progression based on semistructured interview data, using thematic analysis driven by the Butlerian theoretical concept of bodies. This approach contributes to a more nuanced understanding of academic mothers in the Chinese higher education context. The findings show that academic mothers strategically perform their bodies by maintaining, crossing and disciplining their body boundaries to satisfy social and institutional discourses. The findings reveal that academic mothers constantly face the tension between career expectations and motherhood. This study has implications for policy makers in academia, higher education institutions and women academics.

Analyzing the Terminologies Defining Development Outside and Beyond the Boundary of Urban Local Body

Analyzing the Terminologies Defining Development Outside and Beyond the Boundary of Urban Local Body

Creative reflections on embodied filmmaking: in, through and between the senses and spaces of the medicalized body

ABSTRACT This artist’s reflection further explores the imagined and sensorial encounters of the body in medicine through a creative practice-led feminist, embodied, and intersubjective approach to filmmaking. It uses “corporeal parenthesis” as form and content to destabilize conventional readings associated with medicalization. The sensations we feel on the inside of the body shape our imagined anatomical understanding. This extension of proprioception is a sensorial way of seeing and experiencing the inside of one’s own body. The visceral body, which entwines our real and imagined bodily inside, is positioned as a site for sense-making. This emphasizes knowledge as imaginative, intuitive, and lived to resist the standardization experienced within medicine. However, the passive horizontal body in the clinical encounter and the presumed intimacy of the therapeutic space, assumes the body to be accessible and consenting. This alters the ways in which we experience senses associated with pleasure and non-pleasure. By focusing on the artist’s moving image work O (Symptom), creative practice is used to examine in, through, and between the spatial and sensorial boundaries of the medicalized body.

A general framework to optimize fracture parameters in tight gas reservoir of heterogeneous channel sand bodies

Optimizing fracture parameters can unlock the potential of tight gas reservoirs. Various frameworks have been proposed as efficient optimization tools. However, current frameworks are mostly aimed at regular rectangular oil or gas reservoirs. The effect of heterogenous channel sand bodies on fracture parameter optimization has not been discussed. Here, we proposed a general optimization framework. The first step is to establish a heterogeneous channel sand bodies model based on image processing and data interpolation methods. The second step is to couple optimization algorithm and reservoir simulator to optimize fracture parameters. Then the framework is applied to two actual wells in Shaximiao Formation in Sichuan Basin in China. Results show that, the effect of channel sand body on the fracture optimization cannot been ignored. The optimal fractures tend to be concentrated in areas with good physical properties and large control areas. The sand body boundary has a significant control effect on the fracture half-length. For both fracture length and conductivity, double dumbbell shape is better than uniform shape. Our general framework serves as an efficient tool to optimize fracture design in heterogeneous channel sand body, which plays a growing role in enhancing tight gas recovery.

Intelligent classification of water bodies with different turbidity levels based on Gaofen-1 multispectral imagery

The turbidity of water is crucial for the health of river and lake ecosystems, necessitating efficient monitoring for effective water management. Existing methods for studying water turbidity's spatial and temporal distribution rely mostly on measured data. There is limited research on the classification of water bodies with different turbidity levels. The main challenge lies in determining the boundaries of liquid water bodies at various turbidity levels, making it challenging to classify them accurately using traditional remote sensing image classification methods. This paper proposes and validates an intelligent turbidity classification method based on deep learning using GaoFen-1 multispectral remote sensing imagery. An adaptive threshold water extraction method based on the Normalized Difference Water Index is proposed to capture water boundaries more accurately to improve the accuracy of extracting nearshore water bodies. A semi-automatic semantic annotation method for water turbidity is introduced to reduce manual labeling costs. The paper applies mode filtering to address edge noise issues and establishes a high-quality training sample dataset. After comparing the accuracy of various neural network models, DeepLab V3+ is selected for intelligent turbidity classification. The results show high accuracy, with mean intersection over union (MIoU), mean F1 score (MF1), and overall accuracy (OA) reaching 94.73%, 97.29%, and 97.54%, respectively. The proposed method and experiments demonstrate the feasibility of intelligent classification of water bodies with different turbidity levels using deep learning networks. This provides a new approach for large-scale and efficient remote sensing water turbidity monitoring.

Transient Electromagnetic Field Response Analysis Considering Dam Boundary Conditions

Abstract The transient electromagnetic (TEM) method has outstanding advantages in detecting depth and response information and can be used to detect anomalies hidden deep inside dams. However, the current data analysis method based on geological exploration is inapplicable to the interpretation of dam detection data, the main reason being the lack of consideration of the influence of dam boundary conditions on the diffusion of the TEM field. In this work, by establishing a numerical model of a dam for TEM detection, the effects of the dam slope ratio, upstream water body, overburden, and other dam boundary conditions on the TEM field were studied. The results showed that the slope ratio made the propagating TEM field to exhibit a constraining behavior, and a negative deviation could be seen in the attenuation curve, indicating a false high-resistance anomaly. The upstream water body distorted the diffusion of the electromagnetic field, and the low-resistance covering layer caused a low-retardation retention phenomenon in the magnetic field, leading to a positive deviation in the attenuation curve, indicating a false low-resistance anomaly. The influence of the boundary conditions was present throughout the entire observation window in which the detection was performed, and the sensitivity of the magnetic field to these boundary conditions was significantly higher than that of the change rate of the magnetic field. With the increase in the observation time, the main influencing factors were the slope ratio, overburden layer, and upstream water body.

Amplitude reconstruction of acoustic emission signals on the base of its mathematical modeling as a stochastic process

The problem of random oscillations generated by inner defect within the neighborhood of the boundary of the elastic massive body under the pre-failure stage is considered. The investigation is based on results of the invariants’ method in acoustic emission (AE) theory consisting in the stability conditions of the mean of statistic distribution parameters of signal characteristics under the same pre-failure stage. The mathematical model of arising wave process of displacement oscillations in the massive body is constructed and the correctness of its using is studied. The problem in question is reduced to the investigation of a boundary integral equation in special stochastic process classes. The task of reconstructing from AE signals and describing the nature of the random process of defect radiation at the free boundary of the body is set. Some numerical are presented.

On the Kinematics of Growth of Regular Boundaries of Bodies into Fractals

Generalizing smooth volumetric growth to the singular case, using de Rham currents and flat chains, we demonstrate how regular boundaries of bodies may evolve to fractals.

A comparative study of remotely sensed reservoir monitoring across multiple land cover types

Continuous monitoring of reservoirs and dams is essential for efficient water management. Synthetic Aperture Radar (SAR) imagery offers the potential for continuous monitoring of surface water through all-weather ground observation. The objective of this study is to enhance the accuracy of water body detection and water quantity estimation by applying 64 combinations of speckle filtering and object detection techniques to Sentinel-1 imagery. For speckle filtering, the Median, Gaussian, Lee, and Frost techniques were used with various window sizes (3, 5, 7, and 9). For water body detection, the Otsu, Kittler-Illingworth (KI), Chan-Vese (CV), and K-means methods were employed. The study area included three reservoirs and two dams in Korea, encompassing a variety of water surface sizes and types of land cover. To validate the accuracy of each water body detection combination, manual delineation-based water mask images from Sentinel-2 were employed. Furthermore, a regression equation (y=axb) between water surface area and storage was used to estimate water storage based on SAR imagery, followed by time-series validation using in-situ data. The research results indicate that the optimal detection technique varies significantly depending on the type of surrounding land cover and the size of the water body. The highest performance was observed for the CV technique combination for waterfront pixels, and for the KI technique combination for other land cover pixels. In speckle filtering techniques using a large window size, the false detection rate caused by vegetation and buildings was low; however, the boundaries of water bodies were blurred. Consequently, using smaller window sizes in SAR imagery and leveraging optimal water body detection combinations specific to land cover types, along with post-processing using masking data, would enhance the performance of water surface area and storage estimation.

Mechanism of radial chain rockbursts in a deep granite TBM tunnel under the influence of weak band

Radial chain rockbursts (RCRs) in deep-buried TBM tunnels have prolonged durations and can pose significant safety risks. Further research is needed to deepen our understanding of the mechanisms of recurrence of rockbursts under the influence of structure plane. In this study, the geological characteristics, occurrence characteristics, microseismic (MS) activity laws, and rock mass fracture mechanism of several RCRs influenced by weak band were summarized to reveal the mechanism of recurrence of RCRs. Research shows that under the influence of weak band, (1) RCRs tends to occur in the area where the dip angle is large, and the strike intersects with the tunnel direction at a large angle and forms a small angle with the maximum principal stress. The width of the weak band typically ranges from 0.01 to 1 m, which is positively correlated with the final depth of rockburst pit. The strength of the weak band is relatively “soft” compared to the surrounding bedrock. (2) The depth of each rockburst pit in RCRs gradually decreases, the time interval between adjacent rockbursts gradually increases, and the maximum thickness of rock block in each rockburst gradually increases. (3) The maximum MS energy of MS events and the maximum apparent stress gradually decreased in the development process of RCRs. The region of stress concentration gradually extended to deeper zone, and the distance difference between stress concentration region and sidewall during each rockburst occurrence stage gradually decreased. (4) The effect of weak band on RCRs attributes to the excavation induced local stress concentration near the weak band, and the interface between the weak band and surrounding rock controls the boundary of the rockburst body. The “chain effect” of RCRs mainly shows that the promotion effect of the previous rockburst on the subsequent rockburst, by promoting the stress and rock fracture transferring to the deep zone, and the proportion of shear fractures increases.

Induction of altered states of consciousness during Floatation-REST is associated with the dissolution of body boundaries and the distortion of subjective time

Floatation-REST (Reduced Environmental Stimulation Therapy) minimizes stimulation of the nervous system by immersing subjects in an environment without sound or light while they effortlessly float in thermoneutral water supersaturated with Epsom salt. Here we investigated the relationship between altered states of consciousness (ASC) and its association with the affective changes induced by Floatation-REST. Using a within-subject crossover design, 50 healthy subjects were randomized to 60 min of Floatation-REST or 60 min of Bed-REST (an active control condition that entailed lying supine on a warm waterbed in a dark and quiet room). Following Floatation-REST, subjects felt significantly more relaxed, less anxious, and less tired than after Bed-REST. Floatation-REST also induced significantly more pronounced ASC characterized by the dissolution of body boundaries and the distortion of subjective time. The loss of body boundaries mediated the loss of anxiety, revealing a novel mechanism by which Floatation-REST exerts its anxiolytic effect.

Spatiotemporal Land Use/Land Cover Changes and Impact on Urban Thermal Environments: Analyzing Cool Island Intensity Variations

This study pioneers the comprehensive evaluation of the spatiotemporal evolution of land use/land cover (LULC) in Hangzhou city, introducing the novel water body shape index (WBSI) to analyze its seasonal impacts on the urban thermal environment and urban cool island (UCI) effects, uncovering distinct patterns of thermal regulation. It particularly investigates how distance gradients and the water body shape index (WBSI) influence land surface temperature (LST) in the urban core. The region’s climate, featuring hot summers and cold winters, highlights significant seasonal LST variations. Addressing a gap in existing UCI research, the analysis extends beyond the typical large-scale planning focus to include small-scale, high-resolution aspects. Employing remote sensing and geographic information system (GIS) analysis techniques, this study analyzes the seasonal dynamics in Hangzhou’s central urban area. High-resolution LST data, obtained through single-channel inversion and resolution enhancement algorithms, are crucial to this analysis. This study employs the maximum likelihood classification method to analyze land use and land cover changes from 1990 to 2020. This analysis reveals potential drivers of urban thermal environment changes, such as the expansion of residential and commercial areas and the reduction in green spaces. Different regions in LST data are delineated to assess the cool island effect, and the complexity of water body boundaries is quantified using the water body shape index. Spatial and temporal patterns of LST changes are investigated using multivariate regression and time-series analysis models. We identified significant changes in LULC over the past 30 years in Hangzhou, closely correlating with a continuous rise in LST. This observation underscores a clear finding: the strategic importance of blue–green infrastructure in mitigating urban heat, a novel insight that extends the current understanding of urban thermal dynamics. A clear and novel finding of this study is that the intensity of the cool island effect from large water bodies not only diminishes with distance but is intricately influenced by the complexity of their shapes, as quantified by the WBSI, whereas the complexity of their boundaries enhances this effect. Additionally, the regulatory role of the cool island effect is observed to vary seasonally, being most pronounced in summer and less so in autumn and winter, thereby demonstrating a positive impact. In conclusion, our findings innovatively highlight how the specific shapes of water bodies, quantified through the water body shape index (WBSI), emerge as critical, yet previously underappreciated, drivers in modulating the urban thermal environment. This underscores a new avenue for urban planning, advocating for the strategic design of water bodies within urban landscapes. It also finds that spatial factors and seasonal variations significantly affect the intensity of the cool island effect. These findings offer valuable evidence for urban planning and climate change adaptation, emphasizing balancing natural elements with the built environment in urban design.

3D Monte Carlo geometry inversion using gravity data

Diverse Monte Carlo methods have gained widespread use across a broad range of applications. However, the challenge of 3D Monte Carlo sampling remains due to the curse of dimensionality. To date, only a few works have been published regarding 3D Monte Carlo sampling. This study aims to develop an efficient 3D transdimensional Monte Carlo framework for reconstructing the spatial geometry of an anomalous body using gravity data. Our framework also can quantify the uncertainty of the shape of an anomalous body recovered from geophysical measurements. To improve the computational efficiency of 3D Monte Carlo sampling, we develop a sparse geometry parameterization strategy. This approach adequately approximates the shape of a complex 3D anomalous body using a set of simple geometries, such as ellipsoids. Each ellipsoid can be characterized by a few parameters, such as the centroid, axes, and orientations, significantly reducing the number of parameters to be sampled. During the sampling, we randomly perturb the number, locations, sizes, and orientations of the ellipsoids. To impose prior structural constraints from other geophysical methods, such as seismic imaging, we design a new method by placing a fixed layer oriented along the top boundary of the anomalous body. The fixed layer is then connected to the randomly sampled ellipsoids using an alpha shape, allowing us to estimate the geometry of the anomalous source body. The current work focuses on the reconstruction of salt bodies. We start with a synthetic spherical salt model and then conduct a more realistic study using a simplified 3D SEG/EAGE salt model, which has a much more complex geometry than the synthetic spherical model. Finally, we apply our method to the Galveston Island salt dome, offshore Texas. The numerical results demonstrate that our framework can effectively recover the shape of an anomalous body and quantify the uncertainty of the reconstructed geometry.

MACHINE LEARNING FOR AUTOMATIC EXTRACTION OF WATER BODIES USING SENTINEL-2 IMAGERY

Context. Given the aggravation of environmental and water problems, there is a need to improve automated methods for extracting and monitoring water bodies in urban ecosystems. The problem of efficient and automated extraction of water bodies is becoming relevant given the large amount of data obtained from satellite systems. The object of study is water bodies that are automatically extracted from Sentinel-2 optical satellite images using machine learning methods.
 Objective. The goal of the work is to improve the efficiency of the process of extracting the boundaries of water bodies on digital optical satellite images by using machine learning methods.
 Method. The paper proposes an automated information technology for delineating the boundaries of water bodies on Sentinel-2 digital optical satellite images. The process includes eight stages, starting with data download and using topographic maps to obtain basic information about the study area. Then, the process involved data pre-processing, which included calibrating the images, removing atmospheric noise, and enhancing contrast. Next, the EfficientNet-B0 architecture is applied to identify water features, facilitating optimal network width scaling, depth, and image resolution. ResNet blocks compress and expand channels. It allows for optimal connectivity of large-scale and multi-channel links across layers. After that, the Regional Proposal Network defines regions of interest (ROI), and ROI alignment ensures data homogeneity. The Fully connected layer helps in segmenting the regions, and the Fully connected network creates binary masks for accurate identification of water bodies. The final step of the method is to analyze spatial and temporal changes in the images to identify differences, changes, and trends that may indicate specific phenomena or events. This approach allows automating and accurately identifying water features on satellite images using machine learning.
 Results. The implementation of the proposed technology is development through Python software development. An assessment of the technology’s accuracy, conducted through a comparative analysis with existing methods, such as water indices and K-means, confirms a high level of accuracy in the period from 2017 to 2023 (up to 98%). The Kappa coefficient, which considers the degree of consistency between the actual and predicted classification, confirms the stability and reliability of our approach, reaching a value of 0.96.
 Conclusions. The experiments confirm the effectiveness of the proposed automated information technology and allow us to recommend it for use in studies of changes in coastal areas, decision-making in the field of coastal resource management, and land use. Prospects for further research may include new methods that seasonal changes and provide robustness in the selection and mapping of water surfaces.

Spears and Spikes: Illness, Emotion and Bodily Invasion in Old Norse Abscess Narratives

Abstract The Old Norse medical corpus, both manuscript and epigraphic, illuminates understandings of the body and of the relationship between sickness, somatic emotion and the perceived integrity of the individual self in Viking and medieval Scandinavia. This essay argues that Old Norse medical texts and charms understand illness not only as an imbalance of humours but also as an invasive, anthropomorphised agent that seeks to breach the boundaries of the human body. Falling victim to illness is understood as a zero-sum power exchange, visualised through images of martial defeat and sexualised submission. Strong emotion can be rendered as physical illness in Old Norse literature because both forces threaten the integrity of the contained and individualised self. As a thematic case study, this essay examines runic healing charms, late medieval medical manuscripts and saga episodes dealing with boils and abscesses, which are attributed both to the surging of vital spirits and to the action of supernatural disease agents, to examine the way these texts understand the embodied self.

Examining the association between depersonalisation traits and the bodily self in waking and dreaming

Depersonalisation (DP) is characterized by fundamental alterations to the sense of self that include feelings of detachment and estrangement from one’s body. We conducted an online study in healthy participants (n = 514) with DP traits to investigate and quantify the subjective experience of body and self during waking and dreaming, as the vast majority of previous studies focussed on waking experience only. Investigating dreams in people experiencing DP symptoms may help us understand whether the dream state is a ‘spared space’ where people can temporarily ‘retrieve’ their sense of self and sense of bodily presence. We found that higher DP traits—i.e. higher scores on the Cambridge Depersonalisation Scale (CDS)—were associated with more frequent dream experiences from an outside observer perspective (r = 0.28) and more frequent dream experiences of distinct bodily sensations (r = 0.23). We also found that people with higher CDS scores had more frequent dream experiences of altered bodily perception (r = 0.24), more frequent nightmares (r = 0.33) and higher dream recall (r = 0.17). CDS scores were negatively correlated with body boundary scores (r = − 0.31) in waking states and there was a negative association between CDS scores and the degree of trust in interoceptive signals (r = − 0.52). Our study elucidates the complex phenomenology of DP in relation to bodily selfhood during waking and dreaming and suggests avenues for potential therapeutic interventions in people with chronic depersonalisation (depersonalisation -derealisation disorder).

Impact load identification of high-speed train scale carbody based on multi-objective optimisation and TwIST sparse regularisation

ABSTRACT Effective identification of dynamic loads on vehicle systems is crucial for evaluating the structural integrity of railway vehicles. The inverse problem method has been proposed for dynamic load identification to determine the impact load on the carbody. Due to the sparse nature of the impact load, the combination of the l 1-norm and TwIST (two-step iterative threshold shrinkage method) methods is used to reconstruct the impact load, taking into account the influence of sensor placement on the identification results. The MOHBA (Multi-objective Optimisation Honey Badger Algorithm) was proposed to simultaneously select the regularisation and iteration parameters. This algorithm aims to improve the accuracy of subsequence load reconstruction by considering the influence of noise levels when selecting the measured data. The impact load experiment was conducted on the scale carbody, and the single-point impact load and multi-point impact load matched well with the actual load. Satisfactory load identification results can still be achieved when the noise level is within 15%. When arranging measurement points on the boundary of the vehicle body, satisfactory load identification results can also be achieved.

The experience of bearing a child: implications on body boundaries and their link to preterm birth.

Preterm birth, which occurs when a baby is born before 37 weeks, has enormous implications for public health. It is the leading cause of infant death and mortality in children under the age of five. Unfortunately, the multifaceted causes of preterm birth are not fully understood. One construct that has received increasing attention in women's transition to motherhood is body boundaries, i.e., the metaphorical barriers that separate the self from the outer, surrounding "not self." This study aims to examine the role of well-defined and disturbed body boundaries in predicting preterm birth. A sample of 655 Israeli pregnant women reported their sense of body boundaries (BBS, as measured by the Sense of Body Boundaries Survey) pre- and postnatally. We performed a General Linear Model (GLM) testing the effect of the BBS total score on the days women delivered before their due date and controlling for whether it was the women's first child. Our GLMs controlling for whether it was the women's first child showed that the BBS total mean exhibited a significant predictive effect on the number of days delivered before the due date (F(57,313) = 3.65, p < .001). These results demonstrate heterogeneity in women's sense of body boundaries during pregnancy and are the first to disentangle a link between disturbed body boundaries and preterm birth. Mediating mechanisms in this relation, e.g., psychosocial stress, as well as clinical implications are discussed in detail.

Studying the theoretical basis and advantages and disadvantages of Logistic methods of the total horizontal Gradient

Edge detection is one of the most important steps in interpretation of magnetic and gravity data. In magnetic and gravity maps, it is difficult to distinguish adjacent sources due to their field superposition. Many different techniques have been used to determine the edges of sources. These techniques are based on vertical or horizontal gradients of magnetic and gravity data or combinations of them, and the edges of the geological structures are determined by maximum, minimum, or zero values in the output maps. One of the most popular techniques is the total horizontal gradient which is based on horizontal gradients of magnetic and gravity data. The capability of the total horizontal gradient technique in mapping the boundaries of deep bodies is very limited when competing with large-amplitude shallow bodies. Some enhanced modifications of the total horizontal gradient technique have been introduced to improve the boundary estimation results. These techniques are based on logistic functions and derivatives of the total horizontal gradient. In this study, we aim to estimate the effectiveness of the logistic filters of the total horizontal gradient. To obtain optimum results, these filters were tested on synthetic gravity and magnetic data and real magnetic data from the Zhurihe region (China). The findings show that the logistic filters can provide more accurate and sharper boundaries without false source edges than the total horizontal gradient. These techniques can determine the edges of shallow and deep structures at the same time. These results demonstrate that the logistic filters are useful tools for the qualitative interpretation of potential field data.