Natural Representation Research Articles

워즈워스의 「폐허가 된 오두막」과 영국 낭만주의

This paper explores how Wordsworth’s “The Ruined Cottage” embodies and directs the course that Romantic poetry will take, predating his poetic world, the meaning of his poetry, and the essence of poetic theory proclaimed in the Preface to his poetry collection, Lyrical Ballads. In doing so, this paper shall focus on the representation of nature and suffering, considering the dramatic frame as the focal point through which we can glimpse the transformation of Wordsworth’s thought. In “The Ruined Cottage” Wordsworth chooses an ordinary person, Margaret, as the subject matter for a tragic poem, and undertakes the work of mourning. This approach overturns or deviates from the dominant principles of Neo-classicism, allowing Wordsworth to implement his empathy for common people within the realms of literature and criticism. I shall argue that this choice represents novelty and poetic experimentation, serving as a revolutionary declaration about poetry, and impling a subdued form of political engagement. The attitude towards nature and humanity displayed by the wandering peddler and his meditative mind is similar to Wordsworth's perception of nature and humanity revealed through the ruined monastery in “Tintern Abbey”.

The Construction of Agonistic and Strategic Landscape in Chinese Painting of the 1920s and 1930s

This paper discusses the construction of nature in Chinese painting during the period of the late 1920s and 1930s. In this period, in the context of nationalism, in order to arouse people’s national sentiments, artists constructed, or even distorted nature as a threatening “other” of human beings or as a strategic landscape to be controlled by human beings. Both convey the idea of agonistic relationship between human beings and nature. This idea was new, betraying the traditional idea of “harmony between man and nature” and the traditional image of nature as an idealized utopia without any political associations. Most scholars argue that in the 1950s Chinese painting began to produce representations of nature and people in a new ideology with all kinds of “struggle” as the main theme. However, this phenomenon actually began as early as the late 1920s and 1930s. In this new construction, the appearance of nature was portrayed as destructive or as a battlefield, while human beings were represented as battlers, which is the result of social context and ideology.

Unparalleled Intimacy with Nature in Wordsworth's Poetries

This study delves at William Wordsworth's unique relationship with nature as it appears in his poetry. Wordsworth's poetry is defined by a deep and personal connection to nature that goes beyond simple poetic adoration. This research examines Wordsworth's lyrical ballads and love rhymes to show how nature functions in his poetry as an allegory, a reflection of the self, a guide to morality, and a reflection of the human condition. Wordsworth's representation of nature is what sets him apart from his contemporaries and makes him a forerunner of the Romantic movement, which is explored in depth here. Wordsworth's contribution in establishing modern environmental consciousness is also highlighted, as is the influence of his lyrical connection with nature on following generations of poets and environmental philosophers. Our study aims to honor Wordsworth's literary legacy by illuminating the timeless truth of his words in an urbanized, technological age. In doing so, we attest to the perennial relevance of the natural world as both muse and metaphor for the intricacies of the human experience.

Promoting the formation of environmental awareness in children: the representation of nature in Chinese language textbooks

Abstract The main purpose of this study is to investigate the integration of environmental education into language education. Drawing inspiration from Systemic Functional Linguistics (SFL), our focus lies on examining the kinds of participants in material processes in texts carefully chosen from a collection of widely utilized primary school Chinese language textbooks. We pay particular attention to the power and activity hierarchy of participants, to understand how these texts represent nature and the interconnections between fundamental elements in nature. Our findings reveal that these textbooks, through age-appropriate content, are deliberately crafted to instill environmental knowledge in young learners, nurture their ecological awareness and inspire actions aimed at safeguarding the delicate ecosystems that sustain all life forms.

Burnout, a nature walk.

The author expresses themselves through poetry about their burnout experience as a medical professional using nature and natural representations. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Sub-disciplinary variation of metadiscursive verb patterns in English research articles: a functional analysis of medical discourse

Abstract As a cover term for the negotiation of propositional information and reader engagement, metadiscourse has gained considerable attention from scholars of academic discourse. Recent studies have extended to previously unexplored structures that realize metadiscourse, such as ‘metadiscursive nouns’ (Jiang and Hyland 2018. Nouns and academic interactions: A neglected feature of metadiscourse. Applied Linguistics 39. 508–531). Among various linguistic resources, verbs are often regarded as a linguistic element undertaking multiple discourse acts and functions in different contexts, with some acts and functions being metadiscursive. Based on previous studies on reporting verbs and functional sentence stems, this study proposes the concept of metadiscursive verb patterns (MVPs) and examines this linguistic resource in a self-built MedDEAP corpus of five million words, a clinical medicine English research article corpus consisting of 18 sub-disciplines. We conducted an intradisciplinary investigation into MVPs to analyze their structural and functional variations across the sub-disciplines of medical academic English. The findings revealed that most MVPs exhibit a preference for some sub-disciplines, and a few sub-disciplines reflect certain characteristic genre features in the use of certain MVPs. It is shown that medical academic discourse is characterized by methodological and conceptual cross-fertilization. Hence, variation in MVPs is a natural linguistic representation of interdisciplinary synergy. Based on our findings, we conclude by addressing the pedagogical implications for proper use of MVPs in academic writing.

No Effect of Forest Representations on State Anxiety, Actual and Perceived Noise

Abstract Previous research indicates that nature and nature representations might have positive effects and noise negative effects on various facets of life, such as performance, perceived life quality, and physical and mental health. In this intervention, we observed whether posters showing a representation of nature (forests) can be used to reduce actual noise, perceived noise, and state anxiety in university library users. Measurements were taken twice daily for a 5-day period pre-intervention (before posters were installed) and again during the intervention, when posters were installed. No significant differences were found for perceived or actual noise levels or for self-report state anxiety levels between pre-intervention and intervention phase. Correlations between actual and perceived noise, and actual noise and state anxiety, were small in their magnitude and non-significant, with the exception of state anxiety and perceived noise during the intervention phase, suggesting a weak positive relationship. Finally, in hierarchical linear regression models, actual and perceived (overall and talking) noise and intervention phase were non-significant predictors of state anxiety. Small effect sizes of nature representations on state anxiety, as well as actual and perceived noise, suggest posters of forests to not be an effective intervention for anxiety and actual and perceived noise reduction in a university library.

Invariant subalgebras of von Neumann algebras arising from negatively curved groups

Using an interplay between geometric methods in group theory and soft von Neuman algebraic techniques we prove that for any icc, acylindrically hyperbolic group Γ its von Neumann algebra L(Γ) satisfies the so-called ISR property: any von Neumann subalgebraN⊆L(Γ)that is normalized by all group elements in Γ is of the formN=L(Σ)for a normal subgroupΣ◁Γ. In particular, this applies to all groups Γ in each of the following classes: all icc (relatively) hyperbolic groups, most mapping class groups of surfaces, all outer automorphisms of free groups with at least three generators, most graph product groups arising from simple graphs without visual splitting, etc. This result answers positively an open question of Amrutam and Jiang from [2].In the second part of the paper we obtain similar results for factors associated with groups that admit nontrivial (quasi)cohomology valued into various natural representations. In particular, we establish the ISR property for all icc, nonamenable groups that have positive first L2-Betti number and contain an infinite amenable subgroup.

Differential Operators on Sketches via Alpha Contours

A vector sketch is a popular and natural geometry representation depicting a 2D shape. When viewed from afar, the disconnected vector strokes of a sketch and the empty space around them visually merge into positive space and negative space , respectively. Positive and negative spaces are the key elements in the composition of a sketch and define what we perceive as the shape. Nevertheless, the notion of positive or negative space is mathematically ambiguous: While the strokes unambiguously indicate the interior or boundary of a 2D shape, the empty space may or may not belong to the shape's exterior. For standard discrete geometry representations, such as meshes or point clouds, some of the most robust pipelines rely on discretizations of differential operators, such as Laplace-Beltrami. Such discretizations are not available for vector sketches; defining them may enable numerous applications of classical methods on vector sketches. However, to do so, one needs to define the positive space of a vector sketch, or the sketch shape. Even though extracting this 2D sketch shape is mathematically ambiguous, we propose a robust algorithm, Alpha Contours , constructing its conservative estimate: a 2D shape containing all the input strokes, which lie in its interior or on its boundary, and aligning tightly to a sketch. This allows us to define popular differential operators on vector sketches, such as Laplacian and Steklov operators. We demonstrate that our construction enables robust tools for vector sketches, such as As-Rigid-As-Possible sketch deformation and functional maps between sketches, as well as solving partial differential equations on a vector sketch.

An interpretable ensemble method for deep representation learning

AbstractIn representation learning domain, the mainstream methods for model ensemble include “implicit” ensemble approaches, such as using techniques like dropout, and “explicit” ensemble methods, such as voting or weighted averaging based on multiple model outputs. Compared to implicit ensemble techniques, explicit ensemble methods allow for more flexibility in combining models with different structures to obtain different perspectives on representations. However, the representations obtained from different models do not guarantee a linear relationship, and simply linearly combining multiple model outputs may result in a degraded performance. Meanwhile, employing non‐linear fusion mechanisms such as distillation and meta‐learning can be uninterpretable and time‐consuming. To this end, we propose the hypothesis of linear fusion based on the output representations of deep learning models, and design a interpretable linear fusion method based on this hypothesis. This method applies a transform layer to map the output representations of different models to the same classification center. Experimental results demonstrate that compared to directly averaging the representations, our method achieves better performance. Additionally, our method retains the convenience of direct averaging while offering improved performance in terms of time and computational efficiency compared to non‐linear fusion. Furthermore, we test the applicability of our method in both computer vision and natural language processing representation tasks using supervised and semi‐supervised approaches.

Generalizing Multiple Object Tracking to Unseen Domains by Introducing Natural Language Representation

Although existing multi-object tracking (MOT) algorithms have obtained competitive performance on various benchmarks, almost all of them train and validate models on the same domain. The domain generalization problem of MOT is hardly studied. To bridge this gap, we first draw the observation that the high-level information contained in natural language is domain invariant to different tracking domains. Based on this observation, we propose to introduce natural language representation into visual MOT models for boosting the domain generalization ability. However, it is infeasible to label every tracking target with a textual description. To tackle this problem, we design two modules, namely visual context prompting (VCP) and visual-language mixing (VLM). Specifically, VCP generates visual prompts based on the input frames. VLM joints the information in the generated visual prompts and the textual prompts from a pre-defined Trackbook to obtain instance-level pseudo textual description, which is domain invariant to different tracking scenes. Through training models on MOT17 and validating them on MOT20, we observe that the pseudo textual descriptions generated by our proposed modules improve the generalization performance of query-based trackers by large margins.

Geometry-Based Deep Learning in the Natural Sciences

Nature is composed of elements at various spatial scales, ranging from the atomic to the astronomical level. In general, human sensory experience is limited to the mid-range of these spatial scales, in that the scales which represent the world of the very small or very large are generally apart from our sensory experiences. Furthermore, the complexities of Nature and its underlying elements are not tractable nor easily recognized by the traditional forms of human reasoning. Instead, the natural and mathematical sciences have emerged to model the complexities of Nature, leading to knowledge of the physical world. This level of predictiveness far exceeds any mere visual representations as naively formed in the Mind. In particular, geometry has served an outsized role in the mathematical representations of Nature, such as in the explanation of the movement of planets across the night sky. Geometry not only provides a framework for knowledge of the myriad of natural processes, but also as a mechanism for the theoretical understanding of those natural processes not yet observed, leading to visualization, abstraction, and models with insight and explanatory power. Without these tools, human experience would be limited to sensory feedback, which reflects a very small fraction of the properties of objects that exist in the natural world. As a consequence, as taught during the times of antiquity, geometry is essential for forming knowledge and differentiating opinion from true belief. It not only provides a framework for understanding astronomy, classical mechanics, and relativistic physics, but also the morphological evolution of living organisms, along with the complexities of the cognitive systems. Geometry also has a role in the information sciences, where it has explanatory power in visualizing the flow, structure, and organization of information in a system. This role further impacts the explanations of the internals of deep learning systems as developed in the fields of computer science and engineering.

Perceptions and representations of biodiversity in Lausanne, Switzerland: Acknowledging the importance of residential environments

While the ecological mechanisms involved in biodiversity loss within urban environments are widely studied, the literature often overlooks its social-ecological drivers. One of these drivers is the relationship between perceptions and representations of ecosystems and species within specific residential contexts. This study therefore aims to address the following questions: how do residents perceive biodiversity in relation to their social representation of nature within specific residential environments? Are there differences in the social representation and perception of greenspace types and species based on residents' demographic attributes (gender and age) and characteristics of their place of residence (district and housing types)? Through a quantitative survey and the analysis of 148 responses from Lausanne residents using textometry, cartography, and inferential statistics, this research demonstrates two main findings. Firstly, it confirms that the perception of species remains limited, which aligns with previous scholarly work. Secondly, it reveals that the social representations of nature and biodiversity can either correlate with or be disconnected from the perceptual process at the ecosystem level, depending on the residents' living environments. The impact of residential environments on biodiversity perception and representations is discussed, along with the implications of iconic biodiversity traps for raising public awareness about biodiversity preservation in cities.

GFMRC: A machine reading comprehension model for named entity recognition

Recent advances in natural language representation have enabled the internal state of an upstream trained model to migrate to downstream tasks such as named entity recognition (NER). To better utilize pretrained models to perform NER tasks, the latest approach implements NER using the machine reading comprehension (MRC) framework. However, existing MRC approaches do not consider the limited performance of reading comprehension models due to the absence of contextual information in a single sample. Moreover, only word-level features are employed in the feature extraction phase in existing approaches. In this paper, a novel MRC model named GFMRC is proposed to realize NER. GRMRC enhances the MRC model with contextual information and hybrid features. In the preprocessing stage, the samples of the initial MRC dataset are spliced with N-gram information. In the feature extraction stage, global features are extracted for each token using a CNN, and local features are extracted using LSTM. Experiments are carried out on both Chinese datasets and English datasets, and the results demonstrated the effectiveness of the proposed model. The improvements on the English CoNLL 2003, English OntoNotes 5.0, Chinese MSRA, and Chinese OntoNotes 4.0 datasets are 0.07%, 0.23%, 0.04%, and 0.26%, respectively, compared to BERT-MRC+DSC.

From Symbolic to Agential: The Evolution of Natural Representation in Indian Eco-Sensitive Films

From Symbolic to Agential: The Evolution of Natural Representation in Indian Eco-Sensitive Films

Communicating science in the COVID-19 news in the UK during Omicron waves: exploring representations of nature of science with epistemic network analysis

News media plays a vital role in communicating scientific evidence to the public during the COVID-19 pandemic. Such communication is important for convincing the public to follow social distancing guidelines and to respond to health campaigns such as vaccination programmes. However, newspapers were criticised that they focus on the socio-political perspective of science, without explaining the nature of scientific works behind the government’s decisions. This paper examines the connections of the nature of science categories in the COVID-19 era by four local newspapers in the United Kingdom between November 2021 to February 2022. Nature of science refers to different aspects of how science works such as aims, values, methods and social institutions of science. Considering the news media may mediate public information and perception of scientific stories, it is relevant to ask how the various British newspapers covered aspects of science during the pandemic. In the period explored, Omicron variant was initially a variant of concern, and an increasing number of scientific evidence showed that the less severity of this variant might move the country from pandemic to endemic. We explored how news articles communicate public health information by addressing how science works during the period when Omicron variants surge. A novel discourse analysis approach, epistemic network analysis is used to characterise the frequency of connections of categories of the nature of science. The connection between political factors and the professional activities of scientists, as well as that with scientific practices are more apparent in left-populated and centralist outlets than in right-populated news outlets. Among four news outlets across the political spectrum, a left-populated newspaper, the Guardian, is not consistent in representing relations of different aspects of the nature of scientific works across different stages of the public health crisis. Inconsistency of addressing aspects of scientific works and a downplay of the cognitive-epistemic nature of scientific works likely lead to failure in trust and consumption of scientific knowledge by the public in the healthcare crisis.

On the First Natural Triangular Representations of the Symmetric Groups

On the First Natural Triangular Representations of the Symmetric Groups

Comparative Study of Type-1 and Interval Type-2 Fuzzy Logic Systems in Parameter Adaptation for the Fuzzy Discrete Mycorrhiza Optimization Algorithm

The Fuzzy Discrete Mycorrhiza Optimization (FDMOA) Algorithm is a new hybrid optimization method using the Discrete Mycorrhiza Optimization Algorithm (DMOA) in combination with type-1 or interval type-2 fuzzy logic system. In this new research, when using T1FLS, membership functions are defined by type-1 fuzzy sets, which allows for a more flexible and natural representation of uncertain and imprecise data. This approach has been successfully applied to several optimization problems, such as in feature selection, image segmentation, and data clustering. On the other hand, when DMOA is using IT2FLS, membership functions are represented by interval type-2 fuzzy sets, which allows for a more robust and accurate representation of uncertainty. This approach has been shown to handle higher levels of uncertainty and noise in the input data and has been successfully applied to various optimization problems, including control systems, pattern recognition, and decision-making. Both DMOA using T1FLS and DMOA using IT2FLS have shown better performance than the original DMOA algorithm in many applications. The combination of DMOA with fuzzy logic systems provides a powerful and flexible optimization framework that can be adapted to various problem domains. In addition, these techniques have the potential to more efficiently and effectively solve real-world problems.

Disaster mitigation and forest preservation in marind-anim literature

This paper analyzes the myths of the marind-anim community and the representation of nature in these myths through an eco-literacy approach. The eco-literary approach is a method used in investigating nature representation through a literary work. The eco-literary approach aims to bring the new perspective of having a literary work, it focuses on the idea of how the environment and the interaction of the characters toward the environment. The use of the literary work as the Marind-Anim fundamental belief in intervening the policy can be powerful, therefore In this research, the literary work will be specified into the oral literature since Marind-Anim did not have any written literature. In verifying the findings and their relation to ancestral beliefs. Through the representation of nature that emerged in the myths of the marind anim community, two main findings were obtained, namely the awareness of disaster mitigation and figures of Dema in myths who have a major role in teaching about balancing the use of natural resources. The findings on the potential of the Dema figure who appears as a forest guardian figure can be continued as a role model or figure in raising the awareness of forest conservation and can be used as a means of making policy through campaigning forest guards in literary works.

From 2D to 3D video conferencing: modular RGB-D capture and reconstruction for interactive natural user representations in immersive extended reality (XR) communication

With recent advancements in Virtual Reality (VR) and Augmented Reality (AR) hardware, many new immersive Extended Reality (XR) applications and services arose. One challenge that remains is to solve the social isolation often felt in these extended reality experiences and to enable a natural multi-user communication with high Social Presence. While a multitude of solutions exist to address this issue with computer-generated “artificial” avatars (based on pre-rendered 3D models), this form of user representation might not be sufficient for conveying a sense of co-presence for many use cases. In particular, for personal communication (for example, with family, doctor, or sales representatives) or for applications requiring photorealistic rendering. One alternative solution is to capture users (and objects) with the help of RGBD sensors to allow real-time photorealistic representations of users. In this paper, we present a complete and modular RGBD capture application and outline the different steps needed to utilize RGBD as means of photorealistic 3D user representations. We outline different capture modalities, as well as individual functional processing blocks, with its advantages and disadvantages. We evaluate our approach in two ways, a technical evaluation of the operation of the different modules and two small-scale user evaluations within integrated applications. The integrated applications present the use of the modular RGBD capture in both augmented reality and virtual reality communication application use cases, tested in realistic real-world settings. Our examples show that the proposed modular capture and reconstruction pipeline allows for easy evaluation and extension of each step of the processing pipeline. Furthermore, it allows parallel code execution, keeping performance overhead and delay low. Finally, our proposed methods show that an integration of 3D photorealistic user representations into existing video communication transmission systems is feasible and allows for new immersive extended reality applications.