Complementary Parts Research Articles

Jewish exegesis and a vernacular translation of the Hebrew Bible

San Lorenzo de El Escorial, Real Biblioteca, MS. I.i.8 (=E8) and MS. I.i.6 (=E6) are complementary parts of an almost complete Bible, translated from Latin, and transmitting a Castilian version likely produced in the first half of the thirteenth century. Unlike the remaining books in this two-volume Bible, the Psalter’s heading indicates that the Psalms were translated from Hebrew, by Hermannus Allemanus, a scholar of German origin who took part in the projects sponsored by King Alfonso X. Both the attribution of the translation and its dependence on a Hebrew source have never convinced scholars entirely. In spite of the fact that the literature on the topic is vast, and that the text of the Psalter and its glosses have sparked renewed interest in recent years, the challenge of identifying Hebrew exegetical sources that might have influenced the translation has remained largely unaddressed. This article takes up that challenge and aims to contribute to furthering our understanding of the bearing of the Jewish medieval exegetical tradition on this translation of the Bible.

Embedded feature fusion for multi-view multi-label feature selection

With the explosive growth of data sources, multi-view multi-label learning (MVML) has garnered significant attention. However, the task of selecting informative features in MVML becomes more challenging as the dimensionality increase. Existing methods often extract information separately from the consensus part and the complementary part, potentially leading to noise attributed to ambiguous segmentation. In this paper, we propose an embedded feature selection model that combines with two aspects, which are the feature fusion between views and feature enhancement. Firstly, we calculate the adaptive weight of each view based on the local structure relations, and integrate it into one unified feature matrix. Subsequently, the mapping between unified feature matrix and ground-truth label matrix is established. Furthermore, a regularizer for the feature weight of each view is constructed to emphasize its characteristic, respectively. As a result, the relationship for inter-view and intra-view has been simultaneously considered, preserving comprehensive information of features by minimizing the difference between two types of feature weight. Experimental results demonstrate the superior performance of our method in coping with feature selection.

SMART: Supervised multi-class image retargeting generative model based on a long-range sampling strategy

Content-aware image retargeting (CAIR) techniques are crucial in multimedia processing for displaying images on various devices while preserving visually salient contents with desirable visual effects. There are discrete and continuous algorithms. For the former, the artefacts happen when the foreground proportion is larger than the retargeting ratio; for the latter, the salient regions are prone to be squeezed. In this paper, we reformulate the retargeting process into sampling the salient signal and reconstruction under aesthetic supervision, the supervised multi-class image retargeting reconstruction (SMART) framework. The target images can be represented into complementary parts, the masked and unmasked ones, according to the saliency influences in the encoder phrase. The long-range sampling algorithm is proposed to calculate similarities through an 8-connected planar path while considering spatial distance and feature correlation. The sampled embeddings in latent space reconstruct the retargeted images under supervised signals for aesthetic quality. The semantic loss Lsem from the pretrained CLIP model can maintain consistency for both content and semantics. The supervised loss, Lir, is introduced to ensure the retargeted qualities are close to the preferred labels. Then, we release a new retargeting dataset comprising seven image classes (animal, building, car, flower, indoor, landscape and people) with supervised labels collected from designers for further aesthetic retargeting study. The ablation studies are conducted to confirm the effectiveness of the new dataset, and comparative experiments with state-of-the-art baselines demonstrate the advantages of the proposed method.

Parametric Design of an Advanced Multi-Axial Energy-Storing-and-Releasing Ankle–Foot Prosthesis

The ankle joint is pivotal in prosthetic feet, especially in Energy-Storing-and-Releasing feet, favoured by individuals with moderate to high mobility (K3/K4) due to their energy efficiency and simple construction. ESR feet, mainly designed for sagittal-plane motion, often exhibit high stiffness in other planes, leading to difficulties in adapting to varied ground conditions, potentially causing discomfort or pain. This study aims to present a systematic methodology for modifying the ankle joint’s stiffness properties across its three motion planes, tailored to individual user preferences, and to decouple the sagittal-plane behaviour from the frontal and transverse ones. To integrate the multi-axial ankle inside the MyFlex-η, the designing of experiments using finite element analysis was conducted to explore the impact of geometric parameters on the joint’s properties with respect to design constraints and to reach the defined stiffness targets on the three ankle’s motion planes. A prototype of the multi-axial ankle joint was then manufactured and tested under FEA-derived load conditions to validate the final configuration chosen. Composite elastic elements and complementary parts of the MyFlex-η, incorporating the multi-axial ankle joint, were developed, and the prosthesis was biomechanically tested according to lower limb prosthesis ISO standards and guidelines from literature and the American Orthotic and Prosthetic Association (AOPA). Experimental tests showed strong alignment with numerical predictions. Moreover, implementing the multi-axial ankle significantly increased frontal-plane compliance by 414% with respect to the same prosthesis with only one degree of freedom on the sagittal plane without affecting the main plane of locomotion performance.

A review on Ayurvedic concept of Mind with emphasis on Medhya Rasayana

Ayurveda, a five-millennium-old science rooted in the Vedas, encompasses profound insights into health and healing. The traditional Indian medical system perceive the mind and body as complementary parts of one’s entity and purports to preserve the balance between the duo for enhanced quality of life. Moreover, the World Health Organization defines health as a condition of whole physical, mental, and social well-being rather than only the absence of illness or disability, indicating the significance of mind covering the mental health component. The term mind in Ayurveda is referred to as the Manas, and it is one among the Tristhuna, the three pillars quintessential for a healthy life. Acharya Caraka has included Manas in Adhyatama Dravya Guna Sangraha, since true perceptions occur only when Manas is actively engaged with the body and senses. Satva and Chetas are considered as synonyms of Manas. Also, Rashipurusha involved in Srishti Utpatti is depicted as an amalgamation of Atma, Buddhi, Indriya, Manas, Indriyaartha, and Mano-Vishyas. The Satva is considered as unique Guna entity of Manas while Rajas and Tamas are Mano- Doshas. Swastha Avastha of Sareera is invariably linked to Satva Guna where on the contrary Mano-Doshas manifest as diseases. Acharya Caraka emphasizes that whatever comes under the purview of Mana and its knowledge are all its Vishayas, Chintana being the most important. The use of Medhya Rasayana has been advocated in Ayurveda in this regard for its supreme functioning and to ward off diseases caused by Sareerika and Manasika Doshas.

Opportunities and challenges of community mental health centers in Türkiye

AbstractIn 2011, Türkiye restructured the mental health care system in community-based settings following the announcement of the National Mental Health Action Plan. Community mental health centers (CMHCs) are the major element of this approach. As of now, the total number of CMHC have reached 186, and the service users have almost reached 100.000. Mental health care system gained significant advantages through CMHCs, such as 1) improvement in the conditions of mental health services, 2) better follow-up of patients with chronic severe mental disorders, 3) capability of in-home services, 4) decrease in the number of hospitalizations, 5) increased social involvement of patients with severe mental disorder. CMHCs also played a significant role in promoting social rehabilitation, including employment status, development of social relationships, and redress of stigmatization. All these advantages were put into practice by community mental health teams comprising a psychiatrist, psychologists, nurses, social workers and ergotherapists, if available.Community mental health centers come with severe challenges and shortcomings despite their ameliorations. First, CMHCs need trained mental health professionals. However, only 52% of the CMHC teams completed the CMHC trainings currently. Second, standardized work flow algorithms should be developed for CMHCs. Third, there should be a strong relationship between CMHCs, primary health care system and inpatient units as a complementary part of essential mental health care. In addition, hospital administration should be trained in terms of CMHC policy since every CMHC is affiliated with a state hospital. For instance, the ongoing issue of defining quality standards for CMHCs contributes to a misconception, portraying these centers as profit-making units rather than dedicated rehabilitation facilities.In conclusion, community-based settings and CMHCs significantly advance mental health services despite the challenges confronted in practice. To optimize the effectiveness of community mental health care facilitated by CMHCs, it is imperative to review the implementation process with the active involvement and support of non-governmental organizations, including patient-driven organizations and national psychiatric associations.Disclosure of InterestNone Declared

LEO Satellite Access Network (LEO-SAN) Toward 6G: Challenges and Approaches

With the rapid development of satellite communication technologies, the space-based access network has been envisioned as a promising complementary part of the future 6G network. Aside from terrestrial base stations, satellite nodes, especially the low-earth-orbit (LEO) satellites, can also serve as base stations for Internet access, and constitute the LEOsatellite access network (LEO-SAN). LEO-SAN is expected to provide seamless massive access and extended coverage with high signal quality. However, its practical implementation still faces significant technical challenges, such as high mobility and limited budget for communication payloads of LEO satellite nodes. This paper aims at revealing the main technical issues that have not been fully addressed by the existing LEO-SAN designs, from three aspects namely random access, beam management and Doppler-resistant transmission technologies. More specifically, the critical issues of random access in LEO-SAN are discussed regarding low flexibility, long transmission delay, and inefficient handshakes. Then the beam management for LEOSAN is investigated in complex propagation environments under the constraints of high mobility and limited payload budget. Furthermore, the influence of Doppler shifts on LEO-SAN is explored. Correspondingly, promising technologies to address these challenges are also discussed, respectively. Finally, the future research directions are envisioned.

Rozwijanie kompetencji zawodowych kadry pedagogicznej w kontekście pracy w środowisku zróżnicowanym kulturowo na przykładzie II Szkoły Edukacji Międzykulturowej

The aim of the article is to present the 2nd School of Intercultural Education (IISEM) “Strengthening the potential of children and youth with a migrant background” as an example of a cyclical training activity addressed to people involved in educational practice. The paper is a voice in the discussion on the professional competences of teachers, educationalists, psychologists, intercultural assistants, etc. who work in dynamically changing conditions of cultural diversity. Therefore, their competences should be systematically developed in the dialogical relationship between pedagogical theory and practice, in the process of lifelong education, taking into account the specificity of the environment in which the school operates and the challenges and needs existing in it. The article consists of three complementary parts. The first outlines the socio-cultural contexts of contemporary education. Against this background, the goals and specificity of IISEM are shown. The third part presents the methodological package “Towards the integration of Polish and Ukrainian students”, which contains scenarios of educational activities being the result of the work of IISEM participants in culturally diverse environments. The content presented in the text is the result of my own experience and observations resulting from five months of cooperation with the School participants as a mentor and the work of the editor of the substantive methodological package. These activities were accompanied by systematic consultations with IISEM participants, observation of classes conducted during the School (including the implementation of some of them), the evaluation of IISEM (using surveys and interviews with its participants) and analysis of the collected data. The content comprised in the text can be useful both to people interested in intercultural education, both in its theoretical aspects and in educational practice.

Fortune favors the invariant: Enhancing GNNs’ generalizability with Invariant Graph Learning

Generalizable and transferrable graph representation learning endows graph neural networks (GNN) with the ability to extrapolate potential test distributions. Nonetheless, current endeavors recklessly ascribe the demoralizing performance on a single entity (feature or edge) distribution shift and resort to uncontrollable augmentation. By inheriting the philosophy of Invariant graph learning (IGL), which characterizes a full graph as an invariant core subgraph (rationale) and a complementary trivial part (environment), we propose a universal operator termed InMvie to release GNN’s out-of-distribution generation potential. The advantages of our proposal can be attributed to two main factors: the comprehensive and customized insight on each local subgraph, and the systematical encapsulation of environmental interventions. Concretely, a rationale miner is designed to find a small subset of the input graph — rationale, which injects the model with feature invariance while filtering out the spurious patterns, i.e., environment. Then, we utilize systematic environment intervention to ensure the out-of-distribution awareness of the model. Our InMvie has been validated through experiments on both synthetic and real-world datasets, proving its superiority in terms of interpretability and generalization ability for node classification over the leading baselines.

Fanon, the body schema, and white solipsism

AbstractFanon's conception of the body schema plays a central role in his philosophy. The body schema is the body's “grasp” or “sense” of itself. Fanon argues that in the encounter between the Black and white person the body schema “crumbles,” so that the Black person experiences herself as object‐like in various ways. Fanon's focus is the Black person's experience because his aim is to provide the Black person with tools for emancipation. Nevertheless, his account raises the question: What happens to white self‐awareness within the colonial system? I argue that a proper understanding of Fanon's notion of the body schema provides an answer. The body schema underpins awareness of other people, not just one's bodily self. It is the self‐other experiential system that crumbles in the colonial system. Thus, we can supplement Fanon's account of Black self‐experience as object‐like with a description of white experience as tending toward solipsism, where this is the other side of the Black self‐awareness that Fanon describes. Both forms of awareness result from degraded reciprocity. Whilst they are not the same, they are nevertheless complementary parts of a defective relation between people.

Re-purposing the built environment of urban China: Residential eldercare and David Harvey's capital switching in a new era

In urban China, institutional eldercare interacts with local land markets in ways that present special analytical problems in critical political economy. It is a new sector: home-based eldercare and childcare have formed complementary parts of intergenerational household strategies that are coming under system-wide pressure for the first time. Growth in Chinese institutional eldercare has increasingly contributed to the repurposing of a wide range of disused buildings, with noteworthy state encouragement. We read this post-reform feature of urban transformation to deploy David Harvey’s concept of ‘capital switching’ in new ways that are emerging in studies of China's urban geography. Harvey’s framework has already been used in analysing China’s multi-decade boom in the built environment. It exposed the stabilising effects of diverting capital from overaccumulation in single turnover and realisation cycles into deferred returns in the multi-cycle built environment albeit complicated by complex and distinctive interpenetrations of consumption fund and fixed capital, for-profit and not-for-profit sectors, state and non-state interests, and so on. This certainly speaks to the origins of contemporary Chinese urbanisation booms. But repurposing for institutional eldercare now appears to be playing a role in abating mounting overaccumulation and potential devalorisation in the built environment, pairing these unprofitable buildings with for-profit eldercare services operating and yielding profits in repeated single turnover cycles. We experiment with bundled commodity theory to understand repurposing buildings for residential eldercare in this new context.

How Integration of a Brain-Machine Interface and Obstacle Detection System Can Improve Wheelchair Control via Movement Imagery.

This study presents a human-computer interaction combined with a brain-machine interface (BMI) and obstacle detection system for remote control of a wheeled robot through movement imagery, providing a potential solution for individuals facing challenges with conventional vehicle operation. The primary focus of this work is the classification of surface EEG signals related to mental activity when envisioning movement and deep relaxation states. Additionally, this work presents a system for obstacle detection based on image processing. The implemented system constitutes a complementary part of the interface. The main contributions of this work include the proposal of a modified 10-20-electrode setup suitable for motor imagery classification, the design of two convolutional neural network (CNNs) models employed to classify signals acquired from sixteen EEG channels, and the implementation of an obstacle detection system based on computer vision integrated with a brain-machine interface. The models developed in this study achieved an accuracy of 83% in classifying EEG signals. The resulting classification outcomes were subsequently utilized to control the movement of a mobile robot. Experimental trials conducted on a designated test track demonstrated real-time control of the robot. The findings indicate the feasibility of integration of the obstacle detection system for collision avoidance with the classification of motor imagery for the purpose of brain-machine interface control of vehicles. The elaborated solution could help paralyzed patients to safely control a wheelchair through EEG and effectively prevent unintended vehicle movements.

Video-PSG: An Intelligent Contactless Monitoring System for Sleep Staging.

Polysomnography (PSG) is the gold standard for sleep staging in clinics, but its skin-contact nature makes it uncomfortable and inconvenient to use for long-term sleep monitoring. As a complementary part of PSG, the video cameras are not utilized to their full potential, only for manual check of simple sleep events, thereby ignoring the potential for physiological and semantic measurement. This leads to a pivotal research question: Can camera be used for sleep staging, and to what extent? We developed a camera-based contactless sleep staging system in the Institute of Respiratory Diseases and created a clinical video dataset of 20 adults. The camera-based feature set, derived from both physiological signals (pulse and breath) and motions all measured from a video, was evaluated for 4-class sleep staging (Wake-REM-Light-Deep). Three optimization strategies were proposed to enhance the sleep staging accuracy: using motion metrics to prune measurement outliers, creating a more personalized model based on the baseline calibration of waking-stage physiological signals, and deriving a specialized feature for REM detection. It achieved the best accuracy of 73.1% (kappa = 0.62, F1-score = 0.75) in the benchmark of five sleep-staging classifiers. Notably, the system exhibited high accuracy in predicting the overall sleep structure and subtle changes between different sleep stages. The study demonstrates that camera-based contactless sleep staging is a new value stream for sleep medicine, which also provides clinical and technical insights for future optimization and implementation.

Prompt-and-Transfer: Dynamic Class-aware Enhancement for Few-shot Segmentation.

For more efficient generalization to unseen domains (classes), most Few-shot Segmentation (FSS) would directly exploit pre-trained encoders and only fine-tune the decoder, especially in the current era of large models. However, such fixed feature encoders tend to be class-agnostic, inevitably activating objects that are irrelevant to the target class. In contrast, humans can effortlessly focus on specific objects in the line of sight. This paper mimics the visual perception pattern of human beings and proposes a novel and powerful prompt-driven scheme, called "Prompt and Transfer" (PAT), which constructs a dynamic class-aware prompting paradigm to tune the encoder for focusing on the interested object (target class) in the current task. Three key points are elaborated to enhance the prompting: 1) Cross-modal linguistic information is introduced to initialize prompts for each task. 2) Semantic Prompt Transfer (SPT) that precisely transfers the class-specific semantics within the images to prompts. 3) Part Mask Generator (PMG) that works in conjunction with SPT to adaptively generate different but complementary part prompts for different individuals. Surprisingly, PAT achieves competitive performance on 4 different tasks including standard FSS, Cross-domain FSS (e.g., CV, medical, and remote sensing domains), Weak-label FSS, and Zero-shot Segmentation, setting new state-of-the-arts on 11 benchmarks.

Analyzing Trophoblast Fusion Using Immunofluorescence and Split Protein Complementation Assays.

The fusion of cytotrophoblasts into a multinucleatedsyncytiotrophoblast is essential for placental development. For studies investigating syncytiotrophoblast formation, various methods are available to analyze the fusion efficiency of trophoblast cells in vitro. Here, we describe protocols for measuring trophoblast fusion using immunofluorescence and an assay employing complementary parts of a split green fluorescent protein that self-reassociates and generates a fluorescent signal following cell fusion. Together, these approaches allow for a comprehensive and robust analysis of the fusion index in trophoblast cells and can strengthen the accuracy and throughput of investigations into factors that may regulate syncytiotrophoblast development.

On Whether It Is and What It Is

This dialogue, taking place between Prof. Whether and Prof. What, focuses on the nature of the relationship between ontology, conceived as the branch of philosophy concerned with the question of what entities exist, and metaphysics, conceived as the complementary part of philosophy that seeks to explain, of those entities, what they are. Most philosophers claim that it is not possible to address the first question without at the same time addressing the second, since knowing whether an entity exists requires knowing what that entity is. Prof. Whether argues against this popular position and offers a detailed analysis of the idea according to which it is possible to do ontology without engaging in metaphysics. Prof. Whether and Prof. What agree that, rather than being merely possible, in some cases it is, for methodological reasons, even preferable to start with a metaphysics-free ontology, postponing any inquiry concerning the nature of the entities included in the ontological inventory to a later stage. However, Prof. What notes that it is not always possible to do ontology without metaphysics, because there are certain kinds of entities, such as universals and possible worlds, that necessarily need a prior metaphysical characterization.

Complementary Parts Contrastive Learning for Fine-Grained Weakly Supervised Object Co-Localization

The aim of weakly supervised object co-localization is to locate different objects of the same superclass in a dataset. Recent methods achieve impressive co-localization performance by multiple instance learning and self-supervised learning. However, these methods ignore the common part information shared by fine-grained objects and the influence of the complementary parts on the co-localization of the fine-grained objects. To solve these issues, we propose a complementary parts contrastive learning method for fine-grained weakly supervised object co-localization. The proposed method follows such an assumption that fine-grained object parts with the same/different semantic meaning should have similar/dissimilar feature representations in the feature space. The proposed method tackles two critical issues in this task: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</i> ) how to spread the model’s attention and suppress the complex background noise, and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ii</i> ) how to leverage the cross-category common parts information to mitigate the context co-occurrence problem. To address <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</i> ), we attempt to integrate local and context cues via three types of attention including self-supervised attention, channel, and spatial attention to spread the model’s attention toward automatically identifying and localizing most discriminative parts of objects in the fine-grained images. To solve <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ii</i> ), we propose a cross-category object complementarity part contrastive learning module to identify the extracted part regions with different semantic information by pulling the same part features closer and pushing different part features away, which can mitigate the confounding bias caused by the co-occurrence surroundings within specific classes. Extensive qualitative and quantitative evaluations demonstrate the effectiveness of the proposed method on four fine-grained co-localization datasets: CUB-200-2011, Stanford Cars, FGVC-Aircraft, and Stanford Dogs. Code and models are available at https://github.com/Zhao-fan/CPCL.

On maximal plane curves of degree $3$ over $\mathbb{F}_4$, and Sziklai's example of degree $q-1$ over $\mathbb{F}_q$

An elementary and self-contained argument for the complete determination of maximal plane curves of degree $3$ over $\mathbb{F}_4$ will be given, which complements Hirschfeld-Storme-Thas-Voloch's theorem on a characterization of Hermitian curves in $\mathbb{P}^2$. This complementary part should be understood as the classification of Sziklai's example of maximal plane curves of degree $q-1$ over $\mathbb{F}_q$. Although two maximal plane curves of degree $3$ over $\mathbb{F}_4$ up to projective equivalence over $\mathbb{F}_4$ appear, they are birationally equivalent over $\mathbb{F}_4$ each other.

Anti-Malassezia Drug Candidates Based on Virulence Factors of Malassezia-Associated Diseases.

Malassezia is a lipophilic unicellular fungus that is able, under specific conditions, to cause severe cutaneous and systemic diseases in predisposed subjects. This review is divided into two complementary parts. The first one discusses how virulence factors contribute to Malassezia pathogenesis that triggers skin diseases. These virulence factors include Malassezia cell wall resistance, lipases, phospholipases, acid sphingomyelinases, melanin, reactive oxygen species (ROS), indoles, hyphae formation, hydrophobicity, and biofilm formation. The second section describes active compounds directed specifically against identified virulence factors. Among the strategies for controlling Malassezia spread, this review discusses the development of aryl hydrocarbon receptor (AhR) antagonists, inhibition of secreted lipase, and fighting biofilms. Overall, this review offers an updated compilation of Malassezia species, including their virulence factors, potential therapeutic targets, and strategies for controlling their spread. It also provides an update on the most active compounds used to control Malassezia species.

Recent Advances and Adaptive Strategies in Image Guidance for Cervical Cancer Radiotherapy.

The standard of care for locally advanced cervical cancer is external beam radiotherapy (EBRT) with simultaneous chemotherapy followed by an internal radiation boost. New imaging methods such as positron-emission tomography and magnetic resonance imaging have been implemented into daily practice for better tumor delineation in radiotherapy planning. The method of delivering radiation has changed with technical advances in qualitative imaging and treatment delivery. Image-guided radiotherapy (IGRT) plays an important role in minimizing treatment toxicity of pelvic radiation and provides a superior conformality for sparing the organs at risk (OARs) such as bone marrow, bowel, rectum, and bladder. Similarly, three-dimensional image-guided adaptive brachytherapy (3D-IGABT) with computed tomography (CT) or magnetic resonance imaging (MRI) has been reported to improve target coverage and reduce the dose to normal tissues. Brachytherapy is a complementary part of radiotherapy treatment for cervical cancer and, over the past 20 years, 3D-image-based brachytherapy has rapidly evolved and established itself as the gold standard. With new techniques and adaptive treatment in cervical cancer, the concept of personalized medicine is introduced with an enhanced comprehension of the therapeutic index not only in terms of volume (three-dimensional) but during treatment too (four-dimensional). Current data show promising results with integrated IGRT and IGABT in clinical practice and, therefore, better local control and overall survival while reducing treatment-related morbidity. This review gives an overview of the substantial impact that occurred in the progress of image-guided adaptive external beam radiotherapy and brachytherapy.