Common Space Research Articles

NETWORK-CENTERED COMMAND AND CONTROL SYSTEM AND ITS IMPACT ON THE COMBAT CAPABILITIES OF INTERSPECIES ENGROUPMENTS

The article reveals the features of contemporary warfare conducting and the use of joint force engroupments in them, consisting of different units of the armed forces. The characteristics of high-tech armed forces and their joint force engroupments are given as highly mobile, well-armed units of the armed forces that can operate under common command and information space. Their directions of development as highly mobile, well-armed units of the armed forces operating under common command and information space are determined, as well as the need of network-centric control systems use for joint force engroupments is shown and their role in the contemporary warfare in aerospace (land, sea) and information space conducmentt is shown to increase. It is shown that the use of network-centric control systems for joint force engroupment is aimed at obtaining an information advantage over the enemy through the use of the capabilities of common command and information space by all its users. The article shows that the main today’s requirement to ensure the integrated use of all available forces and means (fire, information, electronic warfare) is synchronized in real time, following common command plan, as well as the presence of deep awareness of the command and control bodies about the situation, which combat zone is being formed. It is aimed at increasing the combat capabilities of joint force engroupments in the contemporary warfare conductment. The main combat capabilities components of the joint force engroupments are presented and the influence of the functioning of the network-centric control system of the joint force engroupment on its combat capabilities is shown. It occurs due to the creation of a single command and information space and the provision of integrated and synchronized use of all elements of the joint force engroupments in real time. This material should be used in determining ways to increase the combat capabilities of the joint force engroupment and the process in-depth study of the joint force engroupment network-centric control system functioning influence on its combat capabilities.

Peritonsillar Abscess Outcomes with and Without Computed Tomography: A Retrospective Cohort Study.

Peritonsillar abscess (PTA) is a common deep space head and neck infection, which can be diagnosed with or without computed tomography (CT). CT poses a risk for false positives, leading to unnecessary abscess drainage attempts without benefit, whereas needle or open aspiration without imaging could potentially lead to missed abscess in need of treatment. This study considered the utility and impact of obtaining CT scans in patients with suspected PTA by comparing outcomes between CT and non-CT usage. Retrospective cohort analysis using TriNetX datasets compared the outcomes of two cohorts: PTA without CT and PTA with CT. Measured outcomes included incision and drainage; quinsy adenotonsillectomy; recurrent PTA; airway emergency/obstruction; repeat emergency department (ED) visits; and need for antibiotics, opiates, or steroids. Odds ratios (OR) were calculated using a cohort analysis. The CT usage group had increased odds of receiving antibiotics (OR 3.043, [2.043-4.531]), opiates (OR 1.614, [1.138-1.289]), and steroids (OR 1.373, [1.108-1.702]), as well as a higher likelihood of returning to the ED (OR 5.900, [3.534-9.849]) and developing a recurrent PTA (OR 1.943, [1.410-2.677]). No significant differences were observed in the incidence of incision and drainage, quinsy adenotonsillectomy, or airway emergency/obstruction. Our study indicated that CT scans for PTA diagnosis were associated with increased prescription of antibiotics, opioids, steroids, return ED visits, and recurrent PTA. Future prospective trials are needed to determine if the use of CT scans indicates higher patient acuity that explains the potential negative outcomes. Level II Laryngoscope, 2024.

Knowing the unknowns: Network traffic detection with open-set semi-supervised learning

Network traffic classification plays a crucial role in network security and network quality of service. The new emerging traffic data in the real world is unlabeled and may contain unknown classes, which introduces the problem of identifying unknown-class traffic in unlabeled data. However, existing deep learning-based methods either rely on large amounts of labeled data or assume the labeled and unlabeled data share the common label space. Therefore, they are unable to identify unknown traffic, resulting in decreased detection accuracy. This paper introduces DivinEye, a novel method for unknown network traffic detection based on open-set semi-supervised learning. DivinEye utilizes a small quantity of labeled data and a large amount of unlabeled data to train the model, achieving the ability to identify known classes accurately while also detecting unknown ones. To leverage incoming unlabeled traffic, DivinEye employs open-set semi-supervised techniques to select known-class data from unlabeled data to optimize the known traffic detection model. To detect unknown traffic, DivinEye combines the known traffic classifier and multi-binary classifier to construct an unknown traffic detection model, generating auxiliary targets for all unlabeled data as supervision to train the model. Trace-driven experiments demonstrate that DivinEye outperforms state-of-the-art methods by a large margin.

Optimization of Information Resources Distribution in Common Information Space

Optimization of Information Resources Distribution in Common Information Space

Walking and expressing the city collectively, a teaching-learning experience in the Postgraduate Program in Architecture and Urbanism

The article experiments with methodologies for apprehending and cognizing city spaces. It shares the development of a discipline in the Postgraduate Program in Architecture and Urbanism at Universidade Estadual Paulista (Unesp) with the theoretical-methodological discussion complemented by the practice of Wandering and Cartography in a common space in the neighborhood of Vila Colonial in the city of Bauru, SP. It distances itself from the traditional representational methods of reading the city and approaches to those that express the subjective city, the traversal through the affections of bodies and environments in order to make existential territories visible and thus think about and build a city for and with the people who inhabit the place. In this methodological procedure of wandering, it recognizes the resistance to the functionalist and productivist city and expresses, through affective cartographies, which are still in the process of construction, a visual language, as a research tool that makes it possible to report on the real city.

Semantic Pre-Alignment and Ranking Learning With Unified Framework for Cross-Modal Retrieval

Cross-modal retrieval aims at retrieving highly semantic relevant information among multi-modalities. Existing cross-modal retrieval methods mainly explore the semantic consistency between image and text while rarely consider the rankings of positive instances in the retrieval results. Moreover, these methods seldom take into account the cross-interaction between image and text, which leads to the deficiency of learning their semantic relations. In this paper, we propose a Unified framework with Ranking Learning (URL) for cross-modal retrieval. The unified framework consists of three sub-networks, visual network, textual network, and interaction network. Visual network and textual network project the image feature and text feature into their corresponding hidden spaces respectively. Then, the interaction network forces the target image-text representation to align in the common space. For unifying both semantics and rankings, we propose a new optimization paradigm including pre-alignment for semantic knowledge transfer and ranking learning for final retrieval, which can decouple semantic alignment and ranking learning. The former focuses on the semantic pre-alignment optimized by semantic classification and the latter revolves around the retrieval rankings. For the ranking learning, we introduce a cross-AP loss which can directly optimize the retrieval metric average precision for cross-modal retrieval. We conduct experiments on four widely-used benchmarks, including Wikipedia dataset, Pascal Sentence dataset, NUS-WIDE-10k dataset, and PKU XMediaNet dataset respectively. Extensive experimental results show that the proposed method can obtain higher retrieval precision.

Multi-Modal Modality-Masked Diffusion Network for Brain MRI Synthesis With Random Modality Missing.

Synthesis of unavailable imaging modalities from available ones can generate modality-specific complementary information and enable multi-modality based medical images diagnosis or treatment. Existing generative methods for medical image synthesis are usually based on cross-modal translation between acquired and missing modalities. These methods are usually dedicated to specific missing modality and perform synthesis in one shot, which cannot deal with varying number of missing modalities flexibly and construct the mapping across modalities effectively. To address the above issues, in this paper, we propose a unified Multi-modal Modality-masked Diffusion Network (M2DN), tackling multi-modal synthesis from the perspective of "progressive whole-modality inpainting", instead of "cross-modal translation". Specifically, our M2DN considers the missing modalities as random noise and takes all the modalities as a unity in each reverse diffusion step. The proposed joint synthesis scheme performs synthesis for the missing modalities and self-reconstruction for the available ones, which not only enables synthesis for arbitrary missing scenarios, but also facilitates the construction of common latent space and enhances the model representation ability. Besides, we introduce a modality-mask scheme to encode availability status of each incoming modality explicitly in a binary mask, which is adopted as condition for the diffusion model to further enhance the synthesis performance of our M2DN for arbitrary missing scenarios. We carry out experiments on two public brain MRI datasets for synthesis and downstream segmentation tasks. Experimental results demonstrate that our M2DN outperforms the state-of-the-art models significantly and shows great generalizability for arbitrary missing modalities.

Can we aggregate voters’ perceptions of political parties’ left–right positions? Formal and probabilistic tests of the left–right scale as a unidimensional common space on cross-national and longitudinal data

Can we aggregate voters’ perceptions of political parties’ left–right positions? Formal and probabilistic tests of the left–right scale as a unidimensional common space on cross-national and longitudinal data

THE PECULIARITIES OF THE TRANSFORMATION OF PRIMARY SCHOOL TEACHERS VOCATIONAL TRAINING IN THE CONTEXT OF MODERN SOCIO-CULTURAL CHALLENGES

This article reveals the peculiarities of the transformation of the vocational training of future primary education specialists. Based on the theoretical and methodological analysis of normative documents, the authors note the importance of the transformation of higher education, in particular, the training of future teachers at both theoretical and practical levels, emphasize the features of innovations in the general education system and present options for training a "new" primary school teacher depending on modern socio-cultural challenges. The problem of the study is to establish a connection between updating the content of general education at the federal level and the system of vocational training of primary school teachers. Therefore, it is possible to assume that the existing modern socio-cultural challenges contribute to the transformation of higher education, in particular the training of primary school teachers. The purpose of the study is a theoretical study of the transformation of the vocational training of primary school teachers, taking into account modern socio-cultural challenges. The method and methodology of the research consists in the study and analysis of scientific psychological and pedagogical publications and the regulatory documents in the field of education of the Russian Federation, as well as summarizing the authors’ experience in training future primary school teachers and systematization of the research materials. Results. The article develops and presents the models of criteria-based assessment in primary school in a common educational space and the transformation of the vocational training of primary school teachers in the context of modern socio-cultural challenges. The features of the formation of new meta-professional competencies of primary school teachers are revealed. The opinions of scientists on the need to develop a set of pedagogical and methodological measures aimed at improving the quality of education in the Russian Federation are summarized and interpreted. The results obtained can be applied in the pedagogical activity of specialists in general, secondary vocational and higher education, as well as of those who are interested in the problems of modern education.

Gyneco-obstetric violence and its impact on the mental health of women with disabilities: a case study in Chile

ABSTRACT Although gyneco-obstetric violence (GOV) addresses the violation of sexual and reproductive rights, it is crucial to problematize its subjective aspects and effects on the mental health of women with disabilities, especially in the Global South. Our objective was to analyze GOV experiences and their mental health impact in women with disabilities through a case study in Chile, using in-depth interviews and documentary analysis of social networks and shadow/alternative reports. In their interactions with the biomedical model, women with disabilities are exposed to violation of their sexual and reproductive rights, infantilization, and objectification of their bodies. This negates their subjectivity, directly impacting their self-perception, autonomy, and trust in healthcare institutions. One strategy through which to address GOV involves the collectivization of subjective disaffection in common spaces. It is crucial that healthcare institutions have teams trained to attend persons with disabilities as well as strategies for the prevention and reparation of acts of GOV. It is paramount to foster the social participation of women with disabilities in healthcare matters in order to make their experiences visible in spaces of collaboration with professionals, institutions, and policymakers.

Конструктивное поведение в ситуации межличностного конфликта: сущностные свойства, функциональная структура и значимые индикаторы

The introduction justifies the topicality of studying and importance of conceptualization and operationalization of the social and psychological phenomenon of constructive behavior in conflict situations. The theoretical analysis involved three main stages. The first stage focused on identification of the subject matter and functional structure of constructive behavior in an interpersonal conflict situation. The conceptualized phenomenon is understood as a functional system of conscious, creative activity of an individual, the overall target and meaning focus of which is connected with searching for and formation ways and means of developing and implementing the program, integrated and arranged as a whole, of coordinated executive interactions with a partner to satisfy one’s own and the partner’s meaningful interests when contradictions arise within common, shared social and psychological space. The second stage dealt with consideration of the major characteristics of constructive behavior in an interpersonal conflict situation. The range of these characteristics includes subjectness, proactivity, purposefulness, creativity, eco-sensitivity, syntonicity, concordance, integrativeness, productivity, supra-situational supersubject non-opposition. The third stage of the scientific analysis sought to compare constructive behavior with other forms of reacting in an interpersonal conflict situation. The given qualitative comparative analysis yielded the indicators of constructive behavior in an interpersonal conflict situation that can be used as the basis of subsequent operationalization and development of appropriate psychodiagnostic tools. In conclusion, the author summarizes the scientific analysis undertaken and gives a complete definition of constructive behavior in an interpersonal conflict.

Continuous Invariant-Based Maps of the Cambridge Structural Database.

The Cambridge Structural Database (CSD) played a key role in the recently established crystal isometry principle (CRISP). The CRISP says that any real periodic crystal is uniquely determined as a rigid structure by the geometry of its atomic centers without atomic types. Ignoring atomic types allows us to study all periodic crystals in a common space whose continuous nature is justified by the continuity of real-valued coordinates of atoms. Our previous work introduced structural descriptors pointwise distance distributions (PDD) that are invariant under isometry defined as a composition of translations, rotations, and reflections. The PDD invariants distinguished all nonduplicate periodic crystals in the CSD. This paper presents the first continuous maps of the CSD and its important subsets in invariant coordinates that have analytic formulas and physical interpretations. Any existing periodic crystal has a uniquely defined location on these geographic-style maps. Any newly discovered periodic crystals will appear on the same maps without disturbing the past materials.

Predicting Cognitive Functioning for Patients with a High-Grade Glioma: Evaluating Different Representations of Tumor Location in a Common Space

Cognitive functioning is increasingly considered when making treatment decisions for patients with a brain tumor in view of a personalized onco-functional balance. Ideally, one can predict cognitive functioning of individual patients to make treatment decisions considering this balance. To make accurate predictions, an informative representation of tumor location is pivotal, yet comparisons of representations are lacking. Therefore, this study compares brain atlases and principal component analysis (PCA) to represent voxel-wise tumor location. Pre-operative cognitive functioning was predicted for 246 patients with a high-grade glioma across eight cognitive tests while using different representations of voxel-wise tumor location as predictors. Voxel-wise tumor location was represented using 13 different frequently-used population average atlases, 13 randomly generated atlases, and 13 representations based on PCA. ElasticNet predictions were compared between representations and against a model solely using tumor volume. Preoperative cognitive functioning could only partly be predicted from tumor location. Performances of different representations were largely similar. Population average atlases did not result in better predictions compared to random atlases. PCA-based representation did not clearly outperform other representations, although summary metrics indicated that PCA-based representations performed somewhat better in our sample. Representations with more regions or components resulted in less accurate predictions. Population average atlases possibly cannot distinguish between functionally distinct areas when applied to patients with a glioma. This stresses the need to develop and validate methods for individual parcellations in the presence of lesions. Future studies may test if the observed small advantage of PCA-based representations generalizes to other data.

Research on data security governance of smart city construction

In the post-epidemic era, the construction of smart cities has become an important link in the economic development of various countries. To improve the degree of urban smart, accelerate the construction of urban digital information infrastructure, and promote the safe sharing of network data is the meaning of smart city construction. At present, China’s smart city construction has made breakthrough progress, but the data flow still faces problems such as leakage, abuse and sharing obstruction. Therefore, we can learn from the mature experience adopted by Europe and the United States in the construction of smart cities, set up third-party institutions to actively promote data sharing, build high-value data sets open to the public, and adhere to the first trial reform. The introduction of regulatory sandbox and common data space mechanism to improve the level of smart city construction and export China’s template for smart city construction.

Functional architecture of the forebrain cholinergic system in rodents.

The basal forebrain cholinergic system (BFCS) participates in functions that are global across the brain, such as sleep-wake cycles, but also participates in capacities that are more behaviorally and anatomically specific, including sensory perception. To better understand the underlying organization principles of the BFCS, more and higher quality anatomical data and analysis is needed. Here, we created a "virtual Basal Forebrain", combining data from numerous rats with cortical retrograde tracer injections into a common 3D reference coordinate space and developed a "spatial density correlation" methodology to analyze patterns in BFCS cortical projection targets, revealing that the BFCS is organized into three principal networks: somatosensory-motor, auditory, and visual. Within each network, clusters of cholinergic cells with increasing complexity innervate cortical targets. These networks represent hierarchically organized building blocks that may enable the BFCS to coordinate spatially selective signaling, including parallel modulation of multiple functionally interconnected yet diverse groups of cortical areas.

Russian-Chinese financial and economic cooperation: Comparative identification of the impulse response function

Subject. This article discusses the integration of Russia and China and the convergence of the economic systems of the two countries. Objectives. The article aims to identify promising areas of cooperation between Russia and China to create a common financial market and common exchange space, and analyze the impulse responses of the Russian and Chinese economies to various external and internal shocks. Methods. For the study, I used a regression analysis. Results. The article assesses the impulse responses of the Russian and Chinese economies to external shocks and identifies a synergistic effect that makes it possible to increase the validity and effectiveness of economic policies. The article also identifies the most promising areas for the development of relations between the two countries. Conclusions. At the present stage, economic and financial cooperation between Russia and China gets strengthening. In general, the results of empirical analysis correspond to theoretical expectations.

Acoustic Analyses of L1 and L2 Vowel Interactions in Mandarin–Cantonese Late Bilinguals

While the focus of bilingual research is frequently on simultaneous or early bilingualism, the interactions between late bilinguals’ first language (L1) and second language (L2) have rarely been studied previously. To fill this research gap, the aim of the current study was to investigate the production of vowels in the L1 Mandarin and L2 Cantonese of Mandarin–Cantonese late bilinguals in Hong Kong. A production experiment was conducted with 22 Mandarin–Cantonese bilinguals, as well as with 20 native Mandarin speakers and 21 native Cantonese speakers. Acoustic analyses, including formants of and Euclidean distances between the vowels, were performed. Both vowel category assimilation and dissimilation were noted in the Mandarin–Cantonese bilinguals’ L1 and L2 vowel systems, suggesting interactions between the bilinguals’ L1 and L2 vowel categories. In general, the findings are in line with the hypotheses of the Speech Learning Model and its revised version, which state that L1–L2 phonetic interactions are inevitable, as there is a common phonetic space for storing the L1 and L2 phonetic categories, and that learners always have the ability to adapt their phonetic space. Future studies should refine the data elicitation method, increase the sample size and include more language pairs to better understand L1 and L2 phonetic interactions.

BrainTACO: an explorable multi-scale multi-modal brain transcriptomic and connectivity data resource

Exploring the relationships between genes and brain circuitry can be accelerated by joint analysis of heterogeneous datasets from 3D imaging data, anatomical data, as well as brain networks at varying scales, resolutions, and modalities. Generating an integrated view, beyond the individual resources’ original purpose, requires the fusion of these data to a common space, and a visualization that bridges the gap across scales. However, despite ever expanding datasets, few platforms for integration and exploration of this heterogeneous data exist. To this end, we present the BrainTACO (Brain Transcriptomic And Connectivity Data) resource, a selection of heterogeneous, and multi-scale neurobiological data spatially mapped onto a common, hierarchical reference space, combined via a holistic data integration scheme. To access BrainTACO, we extended BrainTrawler, a web-based visual analytics framework for spatial neurobiological data, with comparative visualizations of multiple resources. This enables gene expression dissection of brain networks with, to the best of our knowledge, an unprecedented coverage and allows for the identification of potential genetic drivers of connectivity in both mice and humans that may contribute to the discovery of dysconnectivity phenotypes. Hence, BrainTACO reduces the need for time-consuming manual data aggregation often required for computational analyses in script-based toolboxes, and supports neuroscientists by directly leveraging the data instead of preparing it.

Stability and Spread: Transition Metrics that are Robust to Time Interval Misspecification

Intensive longitudinal data collected via ecological momentary assessment (EMA) are often sampled with unequal time spacing between surveys. Given the popularity of EMA data, it is important to understand whether time series methods are robust to such time interval misspecification. The present study demonstrates via simulation that stability and spread—two metrics for quantifying different aspects of transitioning behavior within multivariate binary time series data—are unbiased when applied to data that are collected along an off/on burst sampling schedule, a between-person random sampling schedule, and a within-person random sampling schedule. These results held in randomly generated data with differing numbers of time series variables (k=10 and k=20) and in data simulated based on the proportions of observed data from a prior EMA study. Further, stability and spread demonstrated approximately 95% coverage for all between- and within-person random sampling schedules. However, coverage for stability and spread was poor in the off/on burst sampling schedules (around 67%). We also applied these transition metrics—which measure repetitiveness and diversity of transitions, respectively—to a foundational EMA dataset that was among the first to show that adults regularly use many different emotion regulation strategies throughout their daily life (Heiy & Cheavens, 2014). As hypothesized, we found a stronger positive relation between mood and higher stability/lower spread in emotion regulation among people with fewer depressive symptoms than those with more depressive symptoms. Taken together, stability and spread appear to be appropriate metrics to use with data collected using common unequal time spacing conditions and can be used to uncover theoretically consistent insights in real psychosocial data.

Reflections on walking and the disruptive experience

Our main interest is based on understanding spatial relationships from first-person experience, from our virtual and real body. Through the act of walking, movement in real time, we become cursors that dash across the interface of reality. A continuous process that brings us closer to the production of meanings, new relationships and representations, and also a dialogue with space and time, and the network. This article seeks to present a series of disruptive experiences, documented by the authors themselves, which constitute an exploratory framework of space to discover different symbolic interrelationships, and sketch out constructions of the common space in haptic, political, social and cultural mode. It offers a repository of unexpected, intersubjective encounters, from the empirical practice of walking, which arouses new perspectives to be able to interpret circumstantial spaces, to lose oneself in ‘non-places’, or reflect as to how to approach the landscape and/or the city by opening new imaginaries that add value to the ‘glocal’ place that we traverse and/or inhabit.