spatial awareness

INTRODUCTION: A study on the quality of drinking water was conducted at Air Kuning Treatment Plant In Perak, Malaysia, based on a sanitary survey in 14 sampling points stations from the intake area to the auxiliary points. This was to ensure the continuous supply of clean and safe drinking water to the consumers for public health protection. The objective was to examine the physical, microbiological, and chemical parameters of the water, classification at each site based on National Drinking Water Standards (NDWQS) and to understand the spatial variation using environmetric technique; principal component analysis (PCA)...

3D image reconstruction from a limited number of 2D images has been a long-standing challenge in computer vision and image analysis. While deep learning-based approaches have achieved impressive performance in this area, existing deep networks often fail to effectively utilize the shape structures of objects presented in images. As a result, the topology of reconstructed objects may not be well preserved, leading to the presence of artifacts such as discontinuities, holes, or mismatched connections between different parts...

This study attempts to explore the lived experiences of sexual abuse during COVID-19 in a big metropolitan city in India, with a special interest in understanding the contemporary problems faced by teenagers. Any Phenomenological enquiry begins with identifying and determining the suitability of the participants. In this case, the participants are teenage girls and boys, who have experienced one or other forms of sexual abuse during the COVID-19 pandemic. By restricting the act of sexual abuse that happened during a pandemic, this research brings attention to the medium (material), social conditions, and the role of the cultural world in the act of sexual abuse...

PURPOSE: Stereotactic radiosurgery/radiation therapy (SRS/SRT) increasingly has been used to treat brain metastases. However, the development of distant brain metastases (DBMs) in the untreated brain remains a serious complication. We sought to develop a spatially aware radiomic signature to model the time-to-DBM development in a cohort of patients leveraging pretreatment magnetic resonance imaging (MRI) and radiation therapy treatment planning data including radiation dose distribution maps...

Radar data can provide additional depth information for monocular depth estimation. It provides a cost-effective solution and is robust in various weather conditions, particularly when compared with lidar. Given the sparse and limited vertical field of view of radar signals, existing methods employ either a vertical extension of radar points or the training of a preprocessing neural network to extend sparse radar points under lidar supervision. In this work, we present a novel radar expansion technique inspired by the joint bilateral filter, tailored for radar-guided monocular depth estimation...

This paper conducts a comprehensive study on intermittent computing within IoT environments, emphasizing the interplay between different dataflows-row, weight, and output-and a variety of non-volatile memory technologies. We then delve into the architectural optimization of these systems using a spatial architecture, namely IDEA, with their processing elements efficiently arranged in a rhythmic pattern, providing enhanced performance in the presence of power failures. This exploration aims to highlight the diverse advantages and potential applications of each combination, offering a comparative perspective...

With timely intervention from a bystander, drug overdose victims are more likely to survive. To characterize the frequency of bystander presence and identify overdose response barriers, we analyzed data from overdose fatalities occurring in Rhode Island from 2016 to 2021. Overall, about half (n=1,039; 48.7%) of all overdose deaths in Rhode Island had at least one bystander present. Among decedents who had at least one bystander who was unable to respond (n=338), top reasons of non-response were because they were spatially separated (64...

Graph convolutional networks (GCN) have recently been studied to exploit the graph topology of the human body for skeleton-based action recognition. However, most of these methods unfortunately aggregate messages via an inflexible pattern for various action samples, lacking the awareness of intra-class variety and the suitableness for skeleton sequences, which often contain redundant or even detrimental connections. In this paper, we propose a novel Deformable Graph Convolutional Network (DeGCN) to adaptively capture the most informative joints...

Automated classification of breast cancer subtypes from digital pathology images has been an extremely challenging task due to the complicated spatial patterns of cells in the tissue micro-environment. While newly proposed graph transformers are able to capture more long-range dependencies to enhance accuracy, they largely ignore the topological connectivity between graph nodes, which is nevertheless critical to extract more representative features to address this difficult task. In this paper, we propose a novel connectivity-aware graph transformer (CGT) for phenotyping the topology connectivity of the tissue graph constructed from digital pathology images for breast cancer classification...

Despite the vast advantages of making antenatal care visits, the service utilization among pregnant women in Nigeria is suboptimal. A five-year monitoring estimate indicated that about 24% of the women who had live births made no visit. The non-utilization induced excessive zeroes in the outcome of interest. Thus, this study adopted a zero-inflated negative binomial model within a Bayesian framework to identify the spatial pattern and the key factors hindering antenatal care utilization in Nigeria. We overcome the intractability associated with posterior inference by adopting a Pólya-Gamma data-augmentation technique to facilitate inference...

Among the available diagnostic techniques, antibody detection in bulk tank milk (BTM) represents a useful tool to estimate and monitor Neospora caninum herd prevalence. To evaluate the prevalence of N. caninum and the effect of parasite infection on herd performances, BTM samples collected from 586 dairy herds located in one of the largest dairy production areas in Italy (Lombardy) were analyzed by an indirect ELISA to detect anti-N. caninum specific antibodies. Generalized linear models (GLMs) were developed...

Modern detectors commonly employ classification scores to reflect the localization quality of detection results. However, there exists an inconsistency between them, misguiding the selection of high-quality predictions and providing unreliable results for downstream applications. In this paper, we find that the root of this confidence inconsistency lies in the inaccurate IoU estimation and the spatial misalignment of the learned features between the classification and localization tasks. Therefore, a Confidence-Consistent Detector (CCDet) which includes the Distribution-based IoU Prediction (DIP) and Consistency-aware label assignment (CLA), is proposed...

Spatially resolved omics technologies are transforming our understanding of biological tissues. However, the handling of uni- and multimodal spatial omics datasets remains a challenge owing to large data volumes, heterogeneity of data types and the lack of flexible, spatially aware data structures. Here we introduce SpatialData, a framework that establishes a unified and extensible multiplatform file-format, lazy representation of larger-than-memory data, transformations and alignment to common coordinate systems...

Visual field loss and visuospatial neglect are frequent consequences of cerebral stroke. They often have a strong impact on independence in many daily activities. Rehabilitation aiming to decrease these disabilities is therefore important, and several techniques have been proposed to foster awareness, compensation, or restitution of the impaired visual field. We here describe a rehabilitation intervention using adapted boxing therapy that was part of a pluridisciplinary intervention tailored for a particular case...

In this commentary we reflect on the potential and power of geographical analysis, as a set of methods, theoretical approaches, and perspectives, to increase our understanding of how space and place matter for all . We emphasize key aspects of the field, including accessibility, urban change, and spatial interaction and behavior, providing a high-level research agenda that indicates a variety of gaps and routes for future research that will not only lead to more equitable and aware solutions to local and global challenges, but also innovative and novel research methods, concepts, and data...

Generating virtual organ populations that capture sufficient variability while remaining plausible is essential to conduct in silico trials (ISTs) of medical devices. However, not all anatomical shapes of interest are always available for each individual in a population. The imaging examinations and modalities used can vary between subjects depending on their individualized clinical pathways. Different imaging modalities may have various fields of view and are sensitive to signals from other tissues/organs, or both...

INTRODUCTION: Somatosensory function can be reduced in children with Upper Motor Neuron (UMN) lesions. Therefore, we investigated relationships between somatosensory functions of the foot and motor outcomes in children with UMN lesions. METHOD: In this cross-sectional study, we assessed the Tactile Threshold (TT) with monofilaments and body awareness with Tactile Localisation Tasks for spatial-related action (TLTaction ) and structural-related perception (TLTperception ) body representation at the foot sole...

Cardiac cine magnetic resonance imaging (MRI) is a commonly used clinical tool for evaluating cardiac function and morphology. However, its diagnostic accuracy may be compromised by the low spatial resolution. Current methods for cine MRI super-resolution reconstruction still have limitations. They typically rely on 3D convolutional neural networks or recurrent neural networks, which may not effectively capture long-range or non-local features due to their limited receptive fields. Optical flow estimators are also commonly used to align neighboring frames, which may cause information loss and inaccurate motion estimation...

It has been recently demonstrated that hand stimuli presented in a first-, with respect to a third-, person perspective were prioritized before awareness independently from their identity (i.e., self, or other). This pattern would represent an unconscious advantage for self-related bodily stimuli rooted in spatial perspective. To deeper investigate the role of identity, we employed a breaking-Continuous Flash Suppression paradigm in which a self- or other-hand presented in first- or third-person perspective was displayed after a conscious identity-related prime (i...

Understanding tissue architecture and niche-specific microenvironments in spatially resolved transcriptomics (SRT) requires in situ annotation and labeling of cells. Effective spatial visualization of these data demands appropriate colorization of numerous cell types. However, current colorization frameworks often inadequately account for the spatial relationships between cell types. This results in perceptual ambiguity in neighboring cells of biological distinct types, particularly in complex environments such as brain or tumor...