Blurred Boundaries Research Articles

Mamba- and ResNet-Based Dual-Branch Network for Ultrasound Thyroid Nodule Segmentation.

Accurate segmentation of thyroid nodules in ultrasound images is crucial for the diagnosis of thyroid cancer and preoperative planning. However, the segmentation of thyroid nodules is challenging due to their irregular shape, blurred boundary, and uneven echo texture. To address these challenges, a novel Mamba- and ResNet-based dual-branch network (MRDB) is proposed. Specifically, the visual state space block (VSSB) from Mamba and ResNet-34 are utilized to construct a dual encoder for extracting global semantics and local details, and establishing multi-dimensional feature connections. Meanwhile, an upsampling-convolution strategy is employed in the left decoder focusing on image size and detail reconstruction. A convolution-upsampling strategy is used in the right decoder to emphasize gradual feature refinement and recovery. To facilitate the interaction between local details and global context within the encoder and decoder, cross-skip connection is introduced. Additionally, a novel hybrid loss function is proposed to improve the boundary segmentation performance of thyroid nodules. Experimental results show that MRDB outperforms the state-of-the-art approaches with DSC of 90.02% and 80.6% on two public thyroid nodule datasets, TN3K and TNUI-2021, respectively. Furthermore, experiments on a third external dataset, DDTI, demonstrate that our method improves the DSC by 10.8% compared to baseline and exhibits good generalization to clinical small-scale thyroid nodule datasets. The proposed MRDB can effectively improve thyroid nodule segmentation accuracy and has great potential for clinical applications.

A descriptive and interpretive theory of ethical responsibility in public health nursing.

This article presents a descriptive, interpretive theory of ethical responsibility in public health nursing. The theory is based on qualitative empirical studies, a purposeful literature review and meta-ethnography of public health nurses' experiences of ethical responsibility, interpreted within a philosophical framework. Levianasian philosophy provides the main direction for the authors' interpretations. The path for theory development consists of three phases: an inspirational phase, an explorative phase and the third phase 'joining the dots'. The theory illustrates that ethical responsibility in public health nursing is related to the life existentials of temporality and human relationships. Due to blurred boundaries in these essential life structures, public health nurses can experience a sense of satisfaction but also worries, uncertainties and loneliness. The study reveals paradoxical connections between fear and courage, and between freedom, autonomy and a sense of entrapment in responsible relationships. The authors purport that the results of this study are relevant for education and practice and can provide direction for further studies on developing theories of ethical responsibility in other nursing specialities.

Acute Idiopathic Blind Spot Enlargement and Multiple Evanescent White Dot Syndrome

Acute idiopathic blind spot enlargement syndrome (AIBSES) and Multiple evanescent white dot syndrome (MEWDS) are diseases that fall within the same spectrum. They share common characteristics such as affecting young and middle-aged individuals, being mostly unilateral, causing damage to the outer layers of the retina, and leading to blind spot enlargement in the visual field. In AIBSES, lesions are more frequently located in areas adjacent to the optic disc, whereas in MEWDS, they are observed around the central and peripheral vascular arcades. Unlike MEWDS, in AIBSES, visual field improvement is not expected over time. Multimodal imaging methods, including optical coherence tomography, fundus autofluorescence, fundus fluorescein angiography, and indocyanine green angiography, play an important role in diagnosis and follow-up. In both conditions, the optic nerve can appear normal, but it can also be seen with slightly blurred boundaries and edema, and it should be considered in the differential diagnosis of optic neuropathy.

Polyp-Mamba: A Hybrid Multi-Frequency Perception Gated Selection Network for polyp segmentation

Accurate segmentation of polyps in the colorectal region is crucial for medical diagnosis and the localization of polyp areas. However, challenges arise from blurred boundaries due to the similarity between polyp edges and surrounding tissues, variable polyp morphology, and speckle noise. To address these challenges, we propose a Hybrid Multi-Frequency Perception Gated Selection Network (Polyp-Mamba) for precise polyp segmentation. First, we design a dual multi-frequency fusion encoder that employs Mamba and ResNet to quickly and effectively learn global and local features in polyp images. Specifically, we incorporate a novel Hybrid Multi-Frequency Fusion Module (HMFM) within the encoder, using discrete cosine transform to analyze features from multiple spectral perspectives. This approach mitigates the issue of blurred polyp boundaries caused by their similarity to surrounding tissues, effectively integrating local and global features. Additionally, we construct a Gated Selection Decoder to suppress irrelevant feature regions in the encoder and introduce deep supervision to guide decoder features to align closely with the labels. We conduct extensive experiments using five commonly used polyp test datasets. Comparisons with 14 state-of-the-art segmentation methods demonstrate that our approach surpasses traditional methods in sensitivity to different polyp images, robustness to variations in polyp size and shape, speckle noise, and distribution similarity between surrounding tissues and polyps. Overall, our method achieves superior mDice scores on five polyp test datasets compared to state-of-the-art methods, indicating better performance in polyp segmentation.

The Juncture Of Musical Theatre And Theatrical Music: A Literature Review

This paper is a position paper that highlights the intersection of musical theatre and theatrical music, two art forms within the Ghanaian context that blend music and drama but with distinct orientations. The essence is to clarify blurred boundaries and lack of clear distinction between these two art forms, which often leads students of music to confusion or misinterpretation in composition and performance discourse, performance practices, and artistic production. The approach used is a review of some topical issues related to the topic to unravel the distinction to make contribution to knowledge in music composition and performance as well as other cognate disciplines such as ethnomusicology and theatre studies. It is seen that while musical theatre integrates music as a vehicle for storytelling within a staged performance, theatrical music emphasises music's dramatic qualities without necessarily conforming to theatrical conventions. The two concepts have shared elements such as narrative, emotional expression, and performance as well as some differences in structure. Understanding the two Chiasmus is key to composing works that identify the key juncture where these art forms converge, offering insights into their mutual influence in contemporary performance.

Within the Hypha: The Deconstruction of the Anthropocentric Perspective in László Sepsi’s Novel Fruiting Bodies

In my study, I interpret one of the most outstanding stories of Hungarian fiction, László Sepsi’s weird, body- and biohorror novel, Fruiting Bodies [Termőtestek]. The narrative depicts the rivalry between gangster families who fight for the hallucinogenic mushrooms, an important commodity in their town Höksring. As the novel progresses, the rivalry of the crime families fades into the background against the disease spread by the mushrooms, and thus the story presents the beginning of an eco-dystopia and apocalypse. As the title suggests, one of the central motifs of the text is the mushroom, which is both a drug (essentially food) and the basis of the city and houses (living space). In this paper, I will show how the metaphors and similes in the narrative, through the compared things, represent the blurred boundaries between the human body, nature, disease, food and the city, which are central to the novel’s narrative. In my view, the narrative and the parts of the story that focus on the relationship between humans and environment/nature are themed around the breakdown of binary oppositions. The boundaries between culturally distinct categories, the Great Divide (to use Bruno Latour’s term), are dissolved, and the ecological viewpoint, the circulation of matter and reciprocity predominate. I will show that Fruiting Bodies dismantles hierarchies at the narrative level of both the action and the storytelling, offering a more universal perspective rather than a purely anthropocentric one, by situating humanity in the relationships of natural cycles. I will build on the main terms of plant studies (such as plant blindness and plant will), and through the concepts of phytosemiology, Object-Oriented Ontology, flat ontology, hyperobject and dark ecology, I will show how the fungus as metaphor and motif organizes the narrative, and thus offers a posthuman perspective instead of an anthropocentric one.

Cultivating A Culture Of Continuous Improvement And Teamwork In An ICPOP Hub

Abstract Background The Integrated Care for Older Person’s (ICPOP) Hub is one 3 Hubs in the healthcare region. The success of the ICPOP Hub has been the adaptability, motivation, dedication of the multi-disciplinary team (MDT) using inter-disciplinary methods to achieve best outcomes for people with frailty and complex multi-morbidity in the Community. Referrals have increased - 406 in 2023. There were 2,754 direct patient MDT contacts in 2023. Medical capacity for new patients is limited. Alternative ways of working were needed to meet increasing demand. Methods Quality improvement methodologies were employed to enhance efficiency. Existing practices were mapped, deficits highlighted. New practices were trialled in plan-do-study-act format. Results The MDT collaborated to develop structured pathways for Falls and Memory. Criteria were established for triaging referrals, assessment standards, management, post diagnostic support using national/international guidelines (Model of Care for Dementia in Ireland, World Falls Guidelines). More patients were seen via direct-to-MDT pathways and discussed at bi-weekly meetings. Direct referral pathway was instituted from the acute hospital Emergency Department (ED) Frailty Front Door Team to the Hub MDT. ‘One-stop-shop’, multiple, consecutive assessments, while comprehensive, resulted in significant patient fatigue. Moving to parallel assessment reduced appointment frequency and time in the Hub. Staff learned from other disciplines and translated knowledge/skills to tailored patient plans. Case management has prevented ED attendance, particularly for patients with delirium and/or dementia with non-cognitive symptoms. Early integration with Community/Voluntary groups was crucial. Visits from these groups promoted education and relationship building. The Community Connector role has been instrumental in linking people with wellbeing activities in their community. Challenges: Blurring boundaries between roles. Insufficient medical cover represents a barrier to timely patient assessment/management, obstacle to early hospital discharge. Demands on MDT intensify daily. Conclusion Enthusiasm, flexibility, ownership, teamwork, distributed leadership were essential in developing pathways and overcoming difficulties.

Dataset-level color augmentation and multi-scale exploration methods for polyp segmentation

Automatic segmentation of polyps from colonoscopy images plays a critical role in early screening and treatment of colorectal cancer. Although deep learning methods have made significant progress, precise polyp segmentation faces two challenges: (1) the imbalance of color appearances in the limited training dataset hinders the generalization of the model, and (2) polyps have the diverse scales, locations and shapes with blurred boundary. To address the issues, Dataset-Level Color Augmentation (DLCA) and Convolutional Multi-scale Attention Module (CMAM) are proposed. DLCA employs the dataset-level color knowledge and generate new color appearances, to avoid the model learning false associations with colors. Meanwhile, CMAM simultaneously explores the region and boundary clues and model multi-scale context, which improves the accuracy of polyp localization and fine-grained segmentation. We conduct comprehensive experiments and compare our network with state-of-the-art methods. The proposed model is superior on multiple polyp datasets, especially on ETIS, where mDice and mIoU reach 0.839 and 0.766. Furthermore, it is validated that DLCA can be widely applied to most polyp segmentation methods, and CMAM is practical and plug-and-play. Finally, the model demonstrates promising generalization to breast ultrasound and skin lesion segmentation.

Lidio Cipriani, Attilio Gatti, and the shooting of Siliva Zulu (1927)

This essay examines the 1927 documentary film Siliva Zulu, directed by Attilio Gatti with the support of anthropologist Lidio Cipriani, filmed in South Africa. While the existing academic research primarily focuses on the blurred boundaries between fiction and documentary genres within the film, this study introduces new sources concerning the film’s production. Through an analysis of archival documents, personal correspondence, and contemporary reviews, the essay reveals new aspects of Siliva Zulu. Furthermore, it traces the dissemination and reception of these materials from their inception to the present day, and how Siliva Zulu has been reinterpreted over time. This investigation not only enriches the understanding of early ethnographic filmmaking but also highlights the enduring impact of Siliva Zulu on cinematic, anthropological, and colonial discourses.

Blurring the Boundaries of Governance: China’s Work Teams in Comparative Perspective

A notable feature of Chinese Communist rule, from revolutionary days on, has been the blurred boundaries of its governance mechanisms. The lines separating formal from informal, legal from illegal, and state from societal have – at least until quite recently – proven exceptionally permeable. This paper focuses on an especially fluid and flexible means of Chinese Communist governance: the deployment of mobile task forces, or “work teams,” for both routine and crisis policy implementation. Directed by higher-levels of the party-state to advance a specific mission at the grassroots, work teams mobilize society in a manner that reflects the continuing influence of China’s revolutionary experience. The paper assesses the contributions and costs of this “campaign-style” of governance in comparison to the practices of other Communist and non-Communist systems, past and present.

Multiple-ResNet GAN: An enhanced high-resolution image generation method for translation from fundus structure image to fluorescein angiography.

Fluorescein angiography (FA) is a diagnostic method for observing the vascular circulation in the eye. However, it poses a risk to patients. Therefore, generative adversarial networks have been used to convert retinal fundus structure images into FA images. Existing high-resolution image generation methods employ complex deep network models that are challenging to optimize, which leads to issues such as blurred lesion boundaries and poor capture of microleakage and microvessels. In this study, we propose a multiple-ResNet generative adversarial network (GAN) to improve model training, thereby enhancing the ability to generate high-resolution FA images. First, the structure of the multiple-ResNet generator is designed to enhance detail generation in high-resolution images. Second, the Gaussian error linear unit (GELU) activation function is used to help the model converge rapidly. The effectiveness of the multiple-ResNet is verified using the publicly available Isfahan MISP dataset. Experimental results show that our method outperforms other methods, achieving better quantitative results with a mean structural similarity of 0.641, peak signal-to-noise ratio of 18.25, and learned perceptual image patch similarity of 0.272. Compared with state-of-the-art methods, the results showed that using the multiple-ResNet framework and GELU activation function can improve the generation of detailed regions in high-resolution FA images.

Between Representation and Reality: Zhao Chuan’s World Factory as Social Theatre

ABSTRACT Zhao Chuan’s play World Factory continuously introduces reality into the theatre by resorting to the creative techniques of documentary theatre, epic theatre, and theatre of the oppressed in left-wing theatre, thus constituting a blurred boundary between the reality and the representation, and also forming a mode of discussion of social issues in theatre. The tension between reality and representation allows Zhao Chuan’s theatrical production to be understood not only as aesthetic theatre but also as social theatre. With the help of sociological methods, Zhao Chuan’s social theatre creates a “theatrical public sphere,” and the reality of this sphere constitutes a Habermasian place of prudent and equal public opinion. At the same time, the representation of the theatrical public sphere creates the emotional space of physical presence. It imaginatively constructs another reality, and its representation quality can avoid the direct criticism of the reality, which makes the relatively free public sphere speech possible.

In-depth analysis of music structure as a text network

Music, enchanting and poetic, permeates every corner of human civilization. Although music is not unfamiliar to people, our understanding of its essence remains limited, and there is still no universally accepted scientific description. This is primarily due to music being regarded as a product of reason and emotion, making it difficult to define. This article treats musical texts as a complex system. This view echoes linguist John Rupert Firth's insight that understanding a word involves defining it through its surrounding relationships. To construct the network we first build a linear regression model with threshold values to assign conditions to the links among note, time, and volume. Then a clustering coefficient representing regional characteristics is utilized to define the word. Finally, the statistical distribution of the text is strictly required to adhere to the grammatical properties of statistical linguistics, such as Zipf's law, to adjust the weights of the linear regression model and achieve optimal results. These processes enable us to comprehend the structural differences in music across different periods with scientific rigor. Relying on the advantages of structuralism, we concentrate on the relationships and order between the physical elements of music, rather than getting entangled in the blurred boundaries of science and philosophy. Aside from serving as a bridge connecting music to natural language processing and knowledge graphs, the technical methods developed in this work offer a more intuitive approach to elucidate the relationships among elements of a complex network. Published by the American Physical Society 2024

The Hierarchical Coevolutionary Units of Ecological Networks.

In ecological networks, cohesive groups of species may shape the evolution of interactions, serving as coevolutionary units. Ranging across network scales, from motifs to isolated components, elucidating which cohesive groups are more determinant for coevolution remains a challenge in ecology. We address this challenge by integrating 376 empirical mutualistic and antagonistic networks and coevolutionary models. We identified cohesive groups at four network scales containing a significant proportion of potential direct coevolutionary effects. Cohesive groups displayed hierarchical organisation, and potential coevolutionary effects overflowing lower-scale groups were contained by higher-scale groups, underscoring the hierarchy's impact. However, indirect coevolutionary effects blurred group boundaries and hierarchy, particularly under strong selection from ecological interactions. Thus, under strong selection, indirect effects render networks themselves, and not cohesive groups, as the likely coevolutionary units of ecological systems. We hypothesise hierarchical cohesive groups to also shape how other forms of direct and indirect effects propagate in ecological systems.

A differential network with multiple gated reverse attention for medical image segmentation

UNet architecture has achieved great success in medical image segmentation applications. However, these models still encounter several challenges. One is the loss of pixel-level information caused by multiple down-sampling steps. Additionally, the addition or concatenation method used in the decoder can generate redundant information. These limitations affect the localization ability, weaken the complementarity of features at different levels and can lead to blurred boundaries. However, differential features can effectively compensate for these shortcomings and significantly enhance the performance of image segmentation. Therefore, we propose MGRAD-UNet (multi-gated reverse attention multi-scale differential UNet) based on UNet. We utilize the multi-scale differential decoder to generate abundant differential features at both the pixel level and structure level. These features which serve as gate signals, are transmitted to the gate controller and forwarded to the other differential decoder. In order to enhance the focus on important regions, another differential decoder is equipped with reverse attention. The features obtained by two differential decoders are differentiated for the second time. The resulting differential feature obtained is sent back to the controller as a control signal, then transmitted to the encoder for learning the differential feature by two differential decoders. The core design of MGRAD-UNet lies in extracting comprehensive and accurate features through caching overall differential features and multi-scale differential processing, enabling iterative learning from diverse information. We evaluate MGRAD-UNet against state-of-theart (SOTA) methods on two public datasets. Our method surpasses competitors and provides a new approach for the design of UNet.

Litigation Jurisdiction of China International Commercial Court under the "Belt and Road" Initiative

The China International Commercial Court (CICC) plays a crucial role in the context of the "Belt and Road" initiative, providing a platform for the fair and efficient resolution of international commercial disputes. Despite its strategic importance, the CICC faces significant jurisdictional challenges. These include blurred boundaries of case acceptance, insufficient innovation in distinguishing international cases, overly broad applicability due to exclusionary practices, and inadequate consideration of international investment disputes. This article thoroughly examines these issues and offers comprehensive solutions to enhance the CICC's functionality. Key recommendations include clarifying the CICC's positioning as a one-stop platform integrating mediation, arbitration, and litigation; refining the boundaries of case acceptance through detailed legal provisions and judicial interpretations; strengthening the standards for determining international cases to better reflect the complexity of international commercial activities; and enhancing the mechanisms for resolving international investment disputes. Addressing these challenges will improve the CICC's operational efficiency, bolster its international credibility, and better support the "Belt and Road" initiative.

Questions of conscience in a confessional state: From ‘Freedom of conscience’ to ‘Objections of conscience’ in Malta

ABSTRACT While there is an ample body of literature in the anthropology of moralities there is a surprising dearth of research on conscience per se. In Malta over the last ten years there has been a proliferation of a public discourse of ‘conscience’ – its affordances, freedoms and its legal safeguards. This has been the result of debates over reforms leading to the liberalization of sexual and family life, including most recently debates over the legalization of abortion. While the language of conscience in various human rights instruments claims a universal character its meanings, inflections and significance can vary in important ways. There is a blurred boundary between conscience and religion. This paper examines the ways in which conscience is deployed and the significance of the appeals to a national conscience in a European confessional state. It looks at the specific meanings of conscience in Malta and a brief lexical and political history It then moves on to look at the ways objections of conscience are framed in contemporary Malta in light of theological debates and their ramifications in Catholic Malta.

Reverse cross-refinement network for camouflaged object detection

Due to the high intrinsic similarity between camouflaged objects and the background, camouflaged objects often exhibit blurred boundaries, making it challenging to distinguish the boundaries of objects. Existing methods still focus on the overall regional accuracy but not on the boundary quality and are not competent to identify camouflaged objects from the background in complex scenarios. Thus, we propose a novel reverse cross-refinement network called RCR-Net. Specifically, we design a diverse feature enhancement module that simulates the correspondingly expanded receptive fields of the human visual system by using convolutional kernels with different dilation rates in parallel. Also, the boundary attention module is used to reduce the noise of the bottom features. Moreover, a multi-scale feature aggregation module is proposed to transmit the diverse features from pixel-level camouflaged edges to the entire camouflaged object region in a coarse-to-fine manner, which consists of reverse guidance, group guidance, and position guidance. Reverse guidance mines complementary regions and details by erasing already estimated object regions. Group guidance and position guidance integrate different features through simple and effective splitting and connecting operations. Extensive experiments show that RCR-Net outperforms the existing 18 state-of-the-art methods on four widely-used COD datasets. Especially, compared with the existing top-1 model HitNet, RCR-Net significantly improves the performance by ∼16.4% (Mean Absolute Error) on the CAMO dataset, showing that RCR-Net could accurately detect camouflaged objects.

From home to health: Telerehabilitation's contribution to physical activity and quality of life in young adult teleworkers.

The global implementation of full-time telework became widespread during the new normal conditions following the pandemic, resulting in reduced physical activity (PA) among teleworkers and young adults. It is vital to comprehend how telehealth interventions favorably impact PA levels and overall well-being of young adults who face increasingly blurred boundaries between work and home life. The aim of this study is to examine the effect of telerehabilitation (TR) on PA levels and quality of life (QoL) in young adult teleworkers. A quasi-experimental study was conducted on 82 teleworkers (54 females and 28 males). Levels of PA and QoL were assessed using the International Physical Activity Questionnaire-Short Form (IPAQ-SF) and the Health-Related Quality of Life (HRQOL-14) questionnaire. TR was provided to all participants for four weeks, three times a week, for 40 minutes per session. Levels of PA and QoL were evaluated at baseline and after four weeks of the intervention. Data were analyzed using descriptive and inferential statistics. After four weeks of TR, there has been a significant improvement in the scores of IPAQ and HRQOL-14 (p < 0.05). In regards to IPAQ-SF results, TR had a significant effect on the sitting or sedentary behavior of the teleworkers. The results showed that a short-term TR intervention improved both the level of PA and QoL in young adult teleworkers. Therefore, TR may be an effective treatment approach to improve PA and QoL and promote a healthy lifestyle in teleworkers.

Boundary-Aware Gradient Operator Network for Medical Image Segmentation.

Medical image segmentation is a crucial task in computer-aided diagnosis. Although convolutional neural networks (CNNs) have made significant progress in the field of medical image segmentation, the convolution kernels of CNNs are optimized from random initialization without explicitly encoding gradient information, leading to a lack of specificity for certain features, such as blurred boundary features. Furthermore, the frequently applied down-sampling operation also loses the fine structural features in shallow layers. Therefore, we propose a boundary-aware gradient operator network (BG-Net) for medical image segmentation, in which the gradient convolution (GConv) and the boundary-aware mechanism (BAM) modules are developed to simulate image boundary features and the remote dependencies between channels. The GConv module transforms the gradient operator into a convolutional operation that can extract gradient features; it attempts to extract more features such as images boundaries and textures, thereby fully utilizing limited input to capture more features representing boundaries. In addition, the BAM can increase the amount of global contextual information while suppressing invalid information by focusing on feature dependencies and the weight ratios between channels. Thus, the boundary perception ability of BG-Net is improved. Finally, we use a multi-modal fusion mechanism to effectively fuse lightweight gradient convolution and U-shaped branch features into a multilevel feature, enabling global dependencies and low-level spatial details to be effectively captured in a shallower manner. We conduct extensive experiments on eight datasets that broadly cover medical images to evaluate the effectiveness of the proposed BG-Net. The experimental results demonstrate that BG-Net outperforms the state-of-the-art methods, particularly those focused on boundary segmentation.