Global Perception Research Articles

EfferDeepNet: An Efficient Semantic Segmentation Method for Outdoor Terrain

The recognition of terrain and outdoor complex environments based on vision sensors is a key technology in practical robotics applications, and forms the basis of autonomous navigation and motion planning. While traditional machine learning methods can be applied to outdoor terrain recognition, their recognition accuracy is low. In order to improve the accuracy of outdoor terrain recognition, methods based on deep learning are widely used. However, the network structure of deep learning methods is very complex, and the number of parameters is large, which cannot meet the actual operating requirements of of unmanned systems. Therefore, in order to solve the problems of poor real-time performance and low accuracy of deep learning algorithms for terrain recognition, this paper proposes the efficient EfferDeepNet network for pixel level terrain recognition in order to realize global perception of outdoor environment. First, this method uses convolution kernels with different sizes in the depthwise separable convolution (DSC) stage to extract more semantic feature information. Then, an attention mechanism is introduced to weight the acquired features, focusing on the key local feature areas. Finally, in order to avoid redundancy due to a large number of features and parameters in the model, this method uses a ghost module to make the network more lightweight. In addition, to solve the problem of pixel level terrain recognition having a negative effect on image boundary segmentation, the proposed method integrates an enhanced feature extraction network. Experimental results show that the proposed EfferDeepNet network can quickly and accurately perform global recognition and semantic segmentation of terrain in complex environments.

Influence of surface features on the perception of nonadjacent musical phrases.

Although temporally nonadjacent key relationships (e.g., Key X →Key Y→ Key X) are ubiquitous within tonal music, the full extent to which they are perceived is uncertain. Previous research suggests that memory for an initial key remains active up to 20 s after modulation; however, homophonic textures were used in these studies, leaving open the possibility that surface features such as figuration may contribute to nonadjacency effects. In two experiments, we investigated this issue by measuring goodness of completion ratings for stimuli in which musical surface features were manipulated. Two types of surface feature were tested: figuration and activity (total number of notes per stimulus). Stimuli were composed of three parts: (1) nonadjacent section (in either the same or a different key to the probe); (2) intervening section (in a different key to the probe); and (3) probe (a cadence in either the same or different key as the nonadjacent section). In Experiment 1, we tested whether the presence of surface features resulted in higher goodness of completion ratings for the probe; in Experiment 2, we manipulated nonadjacent key relationships to ascertain the effect of surface features on global perception of key. Results showed that figuration and activity contributed to goodness of completion ratings, particularly in stimuli where these features matched each other in the nonadjacent sections. Moreover, the presence of surface features strengthened the perceived relationships between the keys of nonadjacent sections, thereby appearing to contribute to the global perception of phrase. In sum, although from an analytical perspective surface features are often considered to be less important hierarchically, our results indicate that they contribute significantly to the perception of nonadjacent key relationships.

P185 Global perception of normal life by healthcare professionals and IBD patients: mind the gap

Abstract Background For patients living with inflammatory bowel diseases (IBD), the ultimate treatment goal is “normal life”. However, no patient-reported outcome measurement (PROM) exists to measure the level of life normality in IBD. We previously asked patients across the world (5 continents) to identify and rank-order items important to their “normal life”. The top-25 ranked items are being used for subsequent PROM development. In this study, we aimed to compare the perception of healthcare professionals (HCP) and patients with IBD on normal life. Methods IBD patients without an ostomy, pouch or significant comorbidities were interviewed in their mother tongue in 5 continents about “normal life” using a semi-structured interview guide. All items indicated as important were extracted from translated transcripts using directed content analysis (1) until saturation of items occurred. Categorisation was guided by the Wilson’s & Cleary’s Quality of Life model. (2) Second, in an online Delphi procedure, interviewed patients and HCP from each participating centre scored importance of each item on a 0-10 scale. Items scored 7 or higher by >75% were considered important to the respective group. Patient-ranked items were then presented to a patient focus group to clarify wording and merge similar items. Items merged in the patient focus group were merged similarly in HCP rankings. Third, HCP- and patient-rankings were compared. We compared top-25 items selected for PROM development and top-3 items per category. Results 45 CD and 40 UC patients spread over 6 countries were interviewed (median age 36, 56% male, 68% employed, median disease duration 7 years [IQR 4-15]) (table 1). Saturation occurred after 33 CD and 36 UC interviews, yielding 156 unique items. In the Delphi procedure, 54 patients considered 31 items important for normal life with IBD of which 25 remained after focus group discussion. 34 HCP (12 IBD nurses, 16 IBD gastroenterologists, 6 colorectal surgeons) considered 72 items important. Top-25 rankings overlapped in 15 items between patients and HCP, being 5 of 12 physical, 1 of 4 activities, 2 of 3 social, 4 of 11 psychological items and 3 of 5 circumstances (table 2). Top-3 rankings per category overlapped in 2 physical, 1 activities, 2 social, 1 psychological items and 2 circumstances (table 3). Conclusion We identified discrepancies in the perception of normal life with IBD between patients living with IBD and healthcare professionals (HCP). Of top-25 selected items for PROM development, 15 items overlapped between patients and HCP. Of top-3 items per category, the least overlap was seen in activities and psychological items. PROM development and international validation is ongoing.

A multilevel perspective on the role of job demands, job resources, and need satisfaction for employees' outcomes

This study investigates the mediator role of psychological need satisfaction for the effects of job demands and resources on turnover intentions, psychological distress, and work-to-family conflict, simultaneously at the employee and work unit levels. In doing so, we consider how need satisfaction, when considered at the work unit level, creates a context likely to play an additional role in the prediction of these outcomes. These questions were investigated using a combination of doubly latent multilevel confirmatory factor analyses and structural equation models applied to responses provided by a large sample (N = 5716 employees nested within 50 work units) of Canadian Armed Forces/Department of National Defence personnel. The results supported the idea that work environment effects on the outcomes considered in this study were mediated by psychological need satisfaction at the individual and work unit levels and demonstrated that these associations were driven by global work environment perceptions and global need satisfaction. Furthermore, need satisfaction was found to create a context, at the work unit level, leading employees working in units including more highly satisfied co-workers to present higher levels of turnover intentions but lower levels of work-to-family conflict than would be expected based on their individual levels of need satisfaction.

Gain-of-function variants in the ion channel gene TRPM3 underlie a spectrum of neurodevelopmental disorders.

TRPM3 is a temperature- and neurosteroid-sensitive plasma membrane cation channel expressed in a variety of neuronal and non-neuronal cells. Recently, rare de novo variants in TRPM3 were identified in individuals with developmental and epileptic encephalopathy, but the link between TRPM3 activity and neuronal disease remains poorly understood. We previously reported that two disease-associated variants in TRPM3 lead to a gain of channel function . Here, we report a further 10 patients carrying one of seven additional heterozygous TRPM3 missense variants. These patients present with a broad spectrum of neurodevelopmental symptoms, including global developmental delay, intellectual disability, epilepsy, musculo-skeletal anomalies, and altered pain perception. We describe a cerebellar phenotype with ataxia or severe hypotonia, nystagmus, and cerebellar atrophy in more than half of the patients. All disease-associated variants exhibited a robust gain-of-function phenotype, characterized by increased basal activity leading to cellular calcium overload and by enhanced responses to the neurosteroid ligand pregnenolone sulfate when co-expressed with wild-type TRPM3 in mammalian cells. The antiseizure medication primidone, a known TRPM3 antagonist, reduced the increased basal activity of all mutant channels. These findings establish gain-of-function of TRPM3 as the cause of a spectrum of autosomal dominant neurodevelopmental disorders with frequent cerebellar involvement in humans and provide support for the evaluation of TRPM3 antagonists as a potential therapy.

Using illusions to understand hallucinations: differences in perceptual performances on illusory figures may underscore specific visuoperceptual impairments in Parkinson's disease.

Visual hallucinations are prevalent, potentially disabling symptoms of Parkinson's Disease. Multiple impairments in bottom-up sensory processing and top-down perceptual modulation are implicated in the pathophysiology of these phenomena. In healthy individuals, visual illusions are elicited by illusory figures through parametric manipulations of geometrical configurations, contrast, color, or spatial relationships between stimuli. These illusory percepts provide insight on the physiologic processes subserving conscious and unconscious perception. In this exploratory, cross-sectional, controlled study, perceptual performance on illusory figures was assessed on 11 PD patients with hallucinations, 10 non-hallucinating PD patients, and 10 age-matched healthy individuals. In order to characterize potential neural substrates of perceptual performances, patients' brain metabolic patterns on FDG PET were also analyzed. Illusions relying on attentional modulation and global perception were attenuated in PD patients without hallucinations. This pattern was no longer recognizable in hallucinating patients. Conversely, illusory effects normally counteracted by figure to background segregation and overlapping figures recognition were enhanced in PD patients with hallucinations. FDG PET findings further suggest that perceptual differences between PD patients might be linked to abnormal top-down perceptual modulation.

Do amor ao ódio: alguns apontamentos sobre figuras maternas na narrativa cavaleiresca quinhentista portuguesa

This article focuses on the analysis of some outstanding maternal figures present in three chivalric texts of the Portuguese sixteenth century (Crónica do Imperador Clarimundo, Palmeirim de Inglaterra and Memorial das Proezas da Segunda Távola Redonda). It is intended to start from a typological approach to the representation of motherhood, analysing first the mothers of the main heroes, to, from there, highlight the figuration of two mothers who diverge from this typology: Zaraina and Ifranasa. These two figures present in the text of Jorge Ferreira de Vasconcelos stand out for their antagonistic relationship with their children, Florisbel and Masília. By combining dimensions that go beyond the simple maternal figuration, we will also draw attention to the way in which these two figures stand out in a global perception regarding the representation of female figures in chivalric texts from the 1500s

Transformer Based Conditional GAN for Multimodal Image Fusion

Multimodal Image fusion is becoming urgent in multi-sensor information utilization. However, existing end-to-end image fusion frameworks ignore a priori knowledge integration and long-distance dependencies across domains, which brings challenges to the network convergence and global image perception in complex scenes. In this paper, a conditional generative adversarial network with transformer (TCGAN) is proposed for multimodal image fusion. The generator is to generate a fused image with the source images content. The discriminators are adopted to distinguish the differences between the fused image and the source images. Adversarial training makes the final fused image to maintain the structural and textural details in the cross-modal images simultaneously. In particular, a wavelet fusion module makes the inputs contain image content from different domains as much as possible. The extracted convolutional features interact in the multiscale cross-modal transformer fusion module to fully complement the associated information. It makes the generator to focus on both local and global context. TCGAN fully considers the training efficiency of the adversarial process and the integrated retention of redundant information. Various experimental results of TCGAN have highlighted targets, rich details, and fast convergence properties on public datasets.

ЗАГРОЗИ ЕКОНОМІЧНІЙ БЕЗПЕЦІ ДЕРЖАВИ В УМОВАХ ГЛОБАЛЬНИХ ПЕРЕТВОРЕНЬ

Global transformations caused by the pandemic and the largest conventional war on the European continent in several decades determine the need to ensure the economic security of the state as the fundamental basis of the national security of each country. Threats to the economic security of the state that arose during the pandemic and whose residual impact is significant in the post-crisis period were identified. The prevailing influence of Russian aggression in generating threats to the economic security of the state was established. The most dangerous global risks in the short- and medium-term period were studied based on the results of the generalization of The Global Risks Perception Survey by the World Economic Forum, including the increase in the cost of living, natural disasters, and geo-economic confrontation. It was established the relationship and interdependence of the specified global risks with the most dangerous threats to the economic security of Ukraine, in particular, the Russian war against Ukraine, the acute crisis of commodity supply, large-scale forced migration, cyber risks in terms of information access, etc. It has been proven that in the conditions of globalization, threats to the economic security of a separate subject of international economic relations are a source of danger for the global political, economic and humanitarian environment. The ways of countering threats to the economic security of Ukraine at the international level were characterized, including lending, militarytechnical assistance, investment, guarantees of further support. The inflationary threat to the economic security of Ukraine was analyzed as a significant catalyst for a number of other risks and threats in war conditions. It was proven the prevailing influence of exogenous threats on the state economic security under global transformations, which is significantly strengthened by the presence of internal threats to the state economic security. Internal systemic threats to the economic security of Ukraine were highlighted. It was substantiated the need to improve and implement a proactive approach to ensuring the state economic security in the conditions of global transformations and a growing number of external and internal threats.

Practice patterns and considerations in liver transplantation from living donors with high BMI: A review.

Living Donor Liver Transplantation (LDLT) is a valuable solution to the shortage of donor organs for patients with end-stage liver disease. However, the eligibility of obese donors for LDLT remains a subject of debate. This literature review explores global practices and perceptions of LDLT, identifies donor eligibility criteria, and discusses special considerations and ethical caveats. The review highlights the need for standardized guidelines for donor selection, considering the global distribution of Body mass index and variations in population-specific criteria. It also emphasizes the importance of non-invasive testing and pre-operative optimization of liver steatosis for select obese donors. Furthermore, the review examines the outcomes and complications associated with obese donors in LDLT. The findings of this review contribute to the ongoing discussion on the inclusion of obese donors in LDLT and provide insights for future research and guideline development.

Full-Scene Defocus Blur Detection With DeFBD+ via Multi-Level Distillation Learning

Existing defocus blur detection (DBD) methods generally perform well on a single type of unfocused blur scene ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</i> , foreground focus), thereby suffering from the performance degradation for the other types of unfocused blur scenes. In this paper, we present the first exploration on full-scene DBD, and propose a separate-and-combine framework to achieve excellent performance for diverse defocus blur scenes. We firstly structure full-scene DBD dataset (named as DeFBD+) through collecting more types of unfocused blur scenes ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e.g.</i> , background focus, full focus and full out of focus) with pixel-level annotations. Then, to avoid performance degradation caused by mutual interference from local feature representation and global content perception, we implement a pixel-level DBD network and an image-level DBD classification network to learn these two abilities separately. After that, we propose an isomeric distillation mechanism to combine these two abilities. Extensive experiments show that the proposed approach achieves superior performance compared with state-of-the-art methods. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Models and DeFBD+ are publicly available:</i> <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/wdzhao123/MLDBD</uri> .

Asymmetric Cross-Attention Hierarchical Network Based on CNN and Transformer for Bitemporal Remote Sensing Images Change Detection

As an important task in the field of remote sensing image processing, remote sensing image change detection (CD) has made significant advances through the use of convolutional neural networks (CNN). The Transformer has recently been introduced into the field of CD due to its excellent global perception capabilities. Some works have attempted to combine CNN and Transformer to jointly harvest local-global features. However, these works have not paid much attention to the interaction between the features extracted by both. Also, the use of the Transformer has resulted in significant resource consumption. In this paper, we propose the Asymmetric Cross-attention Hierarchical Network (ACAHNet) by combining CNN and Transformer in a series-parallel manners. The proposed Asymmetric Multi-headed Cross Attention (AMCA) module reduces the quadratic computational complexity of the Transformer to linear, and the module enhances the interaction between features extracted from the CNN and the Transformer. Different from the early and late fusion strategies employed in previous work, the effectiveness of the mid-term fusion strategy employed by ACAHNet shows a new choice of timing for feature fusion in the CD task. Our experiments on the proposed method on three public datasets show that our network has better performance in terms of effectiveness and computational resource consumption compared to other comparative methods.

R-YOLOv5: A Lightweight Rotational Object Detection Algorithm for Real-Time Detection of Vehicles in Dense Scenes

A lightweight rotational object detection algorithm, R-YOLOv5, is proposed to address the limitations of traditional object detection algorithms that do not consider the diversity of vehicle scales in drone images and fail to obtain information on rotation angles. The proposed algorithm incorporated an angle prediction branch and introduced a circular smooth label (CSL) angle classification method to make it suitable for detection scenarios based on rotational boxes. A cascaded Swin Transformer block (STrB) is used to reduce computational complexity during feature fusion in the backbone network, further enhancing semantic information and global perception capabilities for small objects. A feature enhancement attention module (FEAM) is proposed to improve the utilization of detailed information through local feature self-supervision. An adaptive spatial feature fusion structure (ASFF) is introduced, which employs features extracted from different levels of the backbone network to perform multi-scale feature fusion. The experimental results show that the detection accuracy reaches 84.91% on the Drone-Vehicle dataset and 90.23% on the UCAS-AOD remote sensing dataset. The lightweight model has a parameter count of only 2.02 million and can achieve 82.6 FPS for high-resolution images, which is significantly better than existing lightweight models and more suitable for real-time detection of rotating vehicles in dense scenes, making it suitable for deployment on a large majority of embedded platforms.

Perception-and-Regulation Network for Salient Object Detection

Effective fusion of different types of features is the key to salient object detection (SOD). The majority of the existing network structure designs are based on the subjective experience of scholars, and the process of feature fusion does not consider the relationship between the fused features and the highest-level features. In this paper, we focus on the feature relationship and propose a novel global attention unit, which we term the “perception-and-regulation” (PR) block, that adaptively regulates the feature fusion process by explicitly modelling the interdependencies between features. The perception part uses the structure of the fully connected layers in the classification networks to learn the size and shape of the objects. The regulation part selectively strengthens and weakens the features to be fused. An imitating eye observation module (IEO) is further employed to improve the global perception capabilities of the network. The imitation of foveal vision and peripheral vision enables the IEO to scrutinize highly detailed objects and to organize a broad spatial scene to better segment objects. Sufficient experiments conducted on the SOD datasets demonstrate that the proposed method performs favourably against the 29 state-of-the-art methods.

Global perceptions of plastic pollution: The contours and limits of debate

AbstractPlastic pollution is central to policy and public debates about anthropogenic damage to the environment. Negotiations for an international binding treaty to end plastic pollution provide a timely opportunity to analyse peer-reviewed papers concerning public perceptions of plastic pollution (n = 39). These focused on the impact of plastic pollution solely on the marine ecosystem, single-use plastics, barriers to recycling and risks of microplastics. Research studies explored public perceptions of ‘plastic pollution’, ‘marine plastic litter’, ‘marine plastic pollution’ and ‘plastic marine debris’. These terms are not interchangeable and frame the problem. Awareness links to media representations and personal ‘choices’ are limited by lack of options (extended producer responsibility schemes). There was limited discussion of reducing the aggregate global volume of plastics produced. Future research could explore perceptions of risk (toxic chemicals, bioplastics) plastics and climate change or plastics and global biodiversity loss (beyond turtles). The social meaning of plastics, the heterogeneity of audiences and the role of media in framing risks can help inform plastics-related policy. Social Sciences and media scholars are well placed to unpack the socio-cultural context in which plastics are intertwined in people’s everyday lives and how social meanings of plastics may change in response to global crises.

O AMBIENTE EDUCACIONAL PELAS LENTES DE UM GRUPO DE MENTORIA ENTRE PARES PARA ESTUDANTES DE MEDICINA

ABSTRACT: The perception of the learning process is shaped by individual experiences and related to the academic environment. This article aimed to evaluate the perception of the educational environment of medical students linked to the peer-mentoring group GEDAAM (Study Group on Didactics Applied to Medical Learning) at the Federal University of Minas Gerais. The data come from a cross-sectional study with 129 members of GEDAAM. The Dundee Ready Education Environment Measure (DREEM) scale was used to assess the perception of the educational environment. Descriptive and comparative analyses were performed (Chi-square test). For almost all assessed domains, the students' perception was more positive than negative (Global score = 108.41). The longer the length of stay at GEDAAM, the worse the Global perception of the educational environment. It is suggested that participating in GEDAAM contributes to a more critical view of the medical teaching environment.

Perception of Globalization on the Learning Strategies among Higher Education Studies Students

This study explores the changing contexts of the globalized world and their impact on the learning strategies in higher education classrooms. Globalization has influenced educational philosophy and classroom practices all over the world. The forces associated with globalization have altered the context in which educators operate, and intensely changed ones experience in both formal and informal education. The purpose of this study was to examine the quality of existing online education courses that utilize the internet as the primary instructional delivery method. The focus of this study was to find out students’ perceptions on the impact of online learning on MPhil level classes in TU Kirtipur. It highlights the challenges facing in use of ICT in higher education of in Nepal. Problems such as lack of resources (viz. qualified teachers, hardware, software, electricity and poor project implementation strategies militate against these efforts. This study recommends university authority should help to facilitate skilled manpower, stabilized electricity supply, hardware resources and software resources to enhance the use of ICT in higher education classrooms. It is argued that, to realize the policy in practice, more sustainable mechanisms need to be developed to provide ICT facilities for teachers and to train them how to use ICT in teaching activities. The study also includes some of the implications to connect on virtual classroom used in an online learning environment affected students’ active participation in learning activities.

Food system transformation: Urban perspectives

Recent years have witnessed an intensification of scientific debates on food system transformation, which, however, continue to unfold mostly at the macro-level, with little empirical backing. To begin to fill the gap between theory and practice surrounding food system transformation, this paper focuses on the governance scale that has been more actively engaging with the complexity of food systems: the urban. Based on a critical review of the academic literature on food system transformation, the paper analyses data collected through interviews with actors involved with the urban food agenda at two levels of governance. These include representatives from high-level organisations operating at the global scale and urban food coordinators from the UK — a country where cities have collectively mobilised to change national food priorities. Findings from the analysis highlight a discrepancy between global and local perceptions of the feasibility of systemic approaches, the lack of an evidence-base to support urban food policies and the inertia of national governments as crucial links between global and local food system governance. As the paper concludes, this raises the need for a re-orientation of research and policy agendas on food system transformation towards the development of a polycentric and plurivocal governance context.

MetaExplorer: Collaborative development of urban metabolism platform for decision making support

Cities need to improve sustainability levels demanded by climate change mitigation efforts. The use of big data analytics is crucial for understanding its dynamics and deploying solid public policies. Nevertheless, data availability poses great challenges, being difficult to produce reliable analyses. Delivering trustable cross-sectorial energy datasets with high spatial and temporal resolution is thus critical to provide valuable insights for informed policymaking.This paper describes the MetaExplorer, a GIS-platform, which gathers trustable energy-related datasets, at municipal level for Portugal, providing a user-friendly georeferenced visualisation tool that can be used to derive statistical models, and support policymaking. Publicly available data was collected and cleaned, divided on five thematic areas: energy demand, buildings, mobility, waste management, and socio-economic, while a visualisation tool was developed to provide the possibility to further explore relations between indicators and support the energy transition at local level, delivering customised analyses with a global perception.

Shared-Weight-Based Multi-Dimensional Feature Alignment Network for Oriented Object Detection in Remote Sensing Imagery.

Arbitrarily Oriented Object Detection in aerial images is a highly challenging task in computer vision. The mainstream methods are based on the feature pyramid, while for remote-sensing targets, the misalignment of multi-scale features is always a thorny problem. In this article, we address the feature misalignment problem of oriented object detection from three dimensions: spatial, axial, and semantic. First, for the spatial misalignment problem, we design an intra-level alignment network based on leading features that can synchronize the location information of different pyramid features by sparse sampling. For multi-oriented aerial targets, we propose an axially aware convolution to solve the mismatch between the traditional sampling method and the orientation of instances. With the proposed collaborative optimization strategy based on shared weights, the above two modules can achieve coarse-to-fine feature alignment in spatial and axial dimensions. Last but not least, we propose a hierarchical-wise semantic alignment network to address the semantic gap between pyramid features that can cope with remote-sensing targets at varying scales by endowing the feature map with global semantic perception across pyramid levels. Extensive experiments on several challenging aerial benchmarks show state-of-the-art accuracy and appreciable inference speed. Specifically, we achieve a mean Average Precision (mAP) of 78.11% on DOTA, 90.10% on HRSC2016, and 90.29% on UCAS-AOD.