Representation In Order Research Articles

Spontaneously emerging internal models of visual sequences combine abstract and event-specific information in the prefrontal cortex

When exposed to sensory sequences, do macaque monkeys spontaneously form abstract internal models that generalize to novel experiences? Here, we show that neuronal populations in macaque ventrolateral prefrontal cortex jointly encode visual sequences by separate codes for the specific pictures presented and for their abstract sequential structure. We recorded prefrontal neurons while macaque monkeys passively viewed visual sequences and sequence mismatches in the local-global paradigm. Even without any overt task or response requirements, prefrontal populations spontaneously form representations of sequence structure, serial order, and image identity within distinct but superimposed neuronal subspaces. Representations of sequence structure rapidly update following single exposure to a mismatch sequence, while distinct populations represent mismatches for sequences of different complexity. Finally, those representations generalize across sequences following the same repetition structure but comprising different images. These results suggest that prefrontal populations spontaneously encode rich internal models of visual sequences reflecting both content-specific and abstract information.

Aesthetic analysis of the pattern of West queen mothers in the Shandong region during the Han dynasty

The West Queen Mother, as a comprehensive cultural phenomenon, has long been the subject of scholarly attention. In recent years, particularly with the rise of traditional Chinese culture, the cultural significance of the West Queen Mother has gained considerable popularity. In the realms of cultural creativity, animation, and gaming, the portrayal of the West Queen Mother has undergone further evolution and innovation, resulting in corresponding shifts in aesthetics. This research investigates the content classification and features of the West Queen Mother's pattern in the Shandong region during the Han Dynasty. By employing a combined approach of pattern analysis and Chinese aesthetics, the aim is to gain a deeper and multifaceted understanding of the culture surrounding the West Queen Mother. This study interprets the aesthetic style and factors associated with the Queen Mother from the perspective of traditional Chinese aesthetics. The conclusion drawn is that the pattern of the West Queen Mother in the Shandong region during the Han Dynasty exhibits aesthetic characteristics ranging from a flat abstraction with simplicity and naturalness to order, normativity, and symbolic representation of divinity. These characteristics demonstrate the richness of Han culture and reflect the Confucian aesthetic concept of the harmony between heaven and humanity, encompassing auspiciousness, loyalty, and filial piety as the highest moral standards, thereby aligning with the prevailing spirit and sociocultural context of the time.

The relationship between gender and pharmacology

The part of sexuality in pharmacology research was not acknowledged, and it was not thought-out to be a determinant that could impact strength and disease. For decades research has mainly contained male, women and animals, leading to a lack of news about syndromes in females. Still, it is critical to guarantee equal likeness so that determine the security, influence, and resistance of healing agents for all individuals. The underrepresentation of female models in preclinical studies over various decades has surpassed to disparities in the understanding, disease, and treatment of ailments 'tween genders. The closeness of sexuality bias has happened recognized as a contributing determinant to the restricted interpretation and replicability of preclinical research. Many demands operation have stressed the significance of including sexuality as a organic changeable, and this view is acquire growing support. Regardless of important progress in incorporating more female models into preclinical studies, differences prevail contemporary. The current review focuses on the part of sexuality and common in biomedical research and, therefore, their potential function in pharmacology and analyze the potential risks guide.

Deep Learning-based Knowledge Graph and Digital Twin Relationship Mining and Prediction Modeling

Abstract The era of big data produces massive data, and carrying out data mining can effectively obtain effective information in huge data, which provides support for efficient decision-making and intelligent optimization. The purpose of this paper is to establish a digital twin system, preprocess massive data using random matrix theory, and design the knowledge graph construction process based on digital twin technology. The BERT model, attention mechanism, BiLSTM model, and conditional random field of the joint deep learning technology are used to identify the knowledge entities in the digital twin system, extract the knowledge relations through the Transformer model, and utilize the TransE model for the knowledge representation in order to construct the knowledge graph. Then, the constructed knowledge graph is combined with the multi-feature attention mechanism to build an anomaly data prediction model in the digital twin system. Finally, the effectiveness of the methods in this paper is validated through corresponding experiments. The TransE model is used for knowledge representation. The accuracy of ternary classification is higher than 80% in all cases, and the MR value decreases by up to 64 compared to the TransR model. The F1 composite score of the anomaly data prediction model is 0.911, and the AUC value of the validation of knowledge graph effectiveness is 0.702. Combining deep learning with the knowledge graph, the knowledge information can be realized in the digital twin system’s accurate representation and enhance the data mining ability of the digital twin system.

Uticaj stereotipa na interkulturalnu komunikaciju

Broadly speaking, stereotyping is a cognitive mechanism that underlies all aspects of intercultural processes-the way individuals perceive members of other groups shapes their attitudes and behavior towards them and influence different types of intercultural interactions and worldviews Based on the assumption that positive stereotypes about people who come from other cultures are used in human communication as an expression of each person's need to simplify all impressions and representations in order to understand the world and the people around them, positive stereotypes can facilitate communication. On the other hand, negative stereotypes in intercultural communication can lead to complete misunderstandings because it is assumed that all people within a certain group have the same characteristics. Therefore, both positive and negative stereotypes in intercultural communication can result in unfounded generalisations, false evaluations and oversimplifications, thus forming the basis for unfair behavior and labelling towards those to whom they refer, in addition to discrimination and interpersonal conflicts. In the search for a model for successful intercultural communication, the principle that culturally specific information should not be applied to all members of a cultural group and that the uniqueness of each member of the group must be respected can be considered extremely important. Stereotypical classifications should not be resistant to change as they relate to relationships between people, which are highly susceptible to change. Successful intercultural communicators should be able to form an opinion based on their communication experience and independent observations, free from stereotypes that they may have consciously or unconsciously gained. Also, viewing the world from the prism of others, not only from our own egocentric and ethnocentric position, and not allowing stereotypes to act as "filters", which allow in only what is similar to our cultural behavior, are important in preventing the adverse effects of stereotypes on communication. Therefore, a recommendable model of successful and efficient intercultural communication is unburdened by bias and stereotypes towards the members of cultural groups different from our own.

Linear perspective as aesthetic form

Background. The article provides a theoretical reconstruction of the linear perspective functioning as more than just an artistic technique that emerged and became an attribute of paintings starting with the Italian Trecento, in particular, in the works of Giotto. The purpose of the article is to reveal the heuristic potential of aesthetic form not in reflecting the consequences of the economic landscape transformation, but in anticipating its transformation and directing the efforts of the subject in its reorganization. The research's methodology is focused on the dynamics of cultural forms through the optics of art history and aesthetic theory, as well as on socio-historical reconstruction of the context without trying to prevent vulgar sociological reductionism and economic determinism. This approach reveals the relationship between the aesthetic text and the context, and the former's potential in clarifying the subtext by articulating the serial principle's aesthetic value and promoting the modern historical type of cultural production and consumption. Methods. This artistic guideline transformed not only the order of the signifiers of the painting (in particular, it replaced the golden background, which had been mostly filled with geometric shapes, humanized the illusory space, and saturated it with mathematically verified figures and objects) but also the order of signifies in the logic of the "picture of the world" (rehabilitation of sensory perception, declaration of the infallibility eye, autonomization of vision, dominance of pictorial space, compression of time to the moment of now, unification of the status of a separate thing in the general order, legitimization of holistic anti-metaphysical programs). Results. The article reveals the connection between the antimetaphysical program of linear perspective in the artistic dimension and the Cartesian homology of space in the theoretical dimension. It also emphasizes the architectonic principle of linear perspective: the rhythmicity of geometric shapes, a stable balance of nodal points, and dynamics of basic forms' reproductions and repetitions. Conclusions. Conducted research substantiates the understanding of linear perspective not as a method of legitimizing the correct vision of things, but as a representation of the valid order and scale of the world through a clear coordinate system, aimed at unification of the system of things and equivalent exchange within it.

Gaussian Switch Sampling: A Second-Order Approach to Active Learning

In active learning, acquisition functions define informativeness directly on the representation position within the model manifold. However, for most machine learning models (in particular neural networks) this representation is not fixed due to the training pool fluctuations in between active learning rounds. Therefore, several popular strategies are sensitive to experiment parameters (e.g. architecture) and do not consider model robustness to out-of-distribution settings. To alleviate this issue, we propose a grounded second-order definition of information content and sample importance within the context of active learning. Specifically, we define importance by how often a neural network “forgets” a sample during training - artifacts of second order representation shifts. We show that our definition produces highly accurate importance scores even when the model representations are constrained by the lack of training data. Motivated by our analysis, we develop Gaussian Switch Sampling ( <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">GauSS</monospace> ). We show that <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">GauSS</monospace> is setup agnostic and robust to anomalous distributions with exhaustive experiments on three in-distribution benchmarks, three out-of-distribution benchmarks, and three different architectures. We report an improvement of up to 5% when compared against four popular query strategies. Our code is available at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/olivesgatech/gauss</uri> .

THE COLLECTIVE INTEREST AND THE UNIVERSALITY OF INTERNATIONAL LABOUR ORGANISATION STANDARDS

The creation of the International Labour Organisation in 1919 led to the setting up of a “world order” based on a set of values presented as universal. Today, it mobilises not only the figure of the worker, but also that of the person or Man. The reference to human rights is – like the reference to the worker a century ago – so many categories of thought structuring representations of a certain world order. One of the challenges for the ILO is certainly its ability to think in terms of social justice, while at the same time being the bearer of a social model whose universality cannot be postulated. Being able to take into account the existence of non-institutionalised forms of collective solidarity, so as to enable peoples not to subordinate their own culture, is certainly the main challenge of the forthcoming centenary.

Use ResNet50V2 Deep Learning Model to Classify Five Animal Species

This study employs the ResNet50V2 Deep Learning model for the purpose of classifying five distinct animal species. To gain insights into the model's proficiency in visual recognition, we conducted training and testing procedures on a dataset comprising diverse images of animal species. The utilization of ResNet50V2 in this classification task is intended to discern visual distinctions among these species by leveraging the distinctive characteristics present in the input images. A meticulous and comprehensive training procedure was undertaken on the model, employing fine-tuning techniques to adjust its internal representation in order to accommodate diverse animal characteristics. The experimental findings illustrate the model's capacity to effectively discern and categorize various animal species with a notable degree of precision, thereby presenting encouraging outcomes for the potential utilization of this model in broader animal classification contexts. This study emphasizes the significant potential of employing Deep Learning models, specifically ResNet50V2, for the purpose of comprehending and identifying diverse fauna through visual cues.

Proving Query Equivalence Using Linear Integer Arithmetic

Proving the equivalence between SQL queries is a fundamental problem in database research. Existing solvers model queries using algebraic representations and convert such representations into first-order logic formulas so that query equivalence can be verified by solving a satisfiability problem. The main challenge lies in "unbounded summations", which appear commonly in a query's algebraic representation in order to model common SQL features, such as projection and aggregate functions. Unfortunately, existing solvers handle unbounded summations in an ad-hoc manner based on heuristics or syntax comparison, which severely limits the set of queries that can be supported. This paper develops a new SQL equivalence prover called SQLSolver, which can handle unbounded summations in a principled way. Our key insight is to use the theory of LIA^*, which extends linear integer arithmetic formulas with unbounded sums and provides algorithms to translate a LIA^* formula to a LIA formula that can be decided using existing SMT solvers. We augment the basic LIA^* theory to handle several complex scenarios (such as nested unbounded summations) that arise from modeling real-world queries. We evaluate SQLSolver with 359 equivalent query pairs derived from the SQL rewrite rules in Calcite and Spark SQL. SQLSolver successfully proves 346 pairs of them, which significantly outperforms existing provers.

The spectacle of demonstration: visual representation of political imagination during the coronavirus crisis

ABSTRACT The coronavirus crisis revealed the vulnerability of shared space especially as a space for civic actions. The media, during lockdown and social distancing, become the main channel for maintaining social connections. The present article deals with demonstrations in Israel during the spring and summer of 2020 which sought to overcome policies through visual mediation and the affordances of digital media. The first part focuses on Guy Debord theory as a means of understanding the alienation of people from their everyday life and meaningful political existence. While his forceful argument about the Spectacle was established on television, there are now evident changes as can be traced in the practices of social movements utilizing new media. Images, with enchanting power, were perceived as numbing distancing people from real life; now, they can also act as channels for the political imagination. In addition, the internet and digital culture in general may connect people to political action rather than dissociate them from it. The second part examines photographs from three different demonstrations and shows how political imagination was figured as spectacle and how visual rhetoric mediated the social movements' reasoning. The first is drawn from the Black Flags movement, established in the face of the chaotic conduct of Israel's former leader, Benjamin Netanyahu, in the wake of corruption allegations. The demonstration's drone documentation, providing imagery taken from above, shows public gatherings grid as a representation of civil order. The second picture is from a Zoom-based demonstration in which a Zoom meeting, an event that enabled under-represented people to participate from their home. The third is from the Balfour demonstrations – a reenactment performance that was staged for the camera as an Instagram image, fashioning an ideal portrait of the protestors and of an idealistic vision of the state. The article uses these examples to demonstrate how the political agendas of the social movements are consolidated via visual technologies.

반 고흐의 신 표상(Representation of God) 변형에 관한 정신분석적 연구

This paper investigated the transformations of Vincent van Gogh’s god representation from a psychoanalytic perspective. The internal/external factors accounting for the transformation in god representation were examined and four themes were deduced. First, the god representation can be transformed due to the individual’s need for psychic equilibrium and defensive purposes. Second, if the object relationship which was the crucial foundation for the formation of the god representation is transformed, the individual’s god representation may accordingly be transformed. Third, an individual may transform one’s god representation in order to integrate his/her unconscious desires and conscious reality. Fourth, an individual may transform his/her god representation into a subjective and private one as an uncommunicated factor. The results substantiated that an individual’s god representation is connected with internal/external reality and can be dealt with clinically in order to develop a healthy religious life.

Person of Interest as Media Technology of Surveillance: A Cautionary Tale for the Future of the National Security State With Diegetic Big Data Surveillance, Algorithmic Security, and Artificial Intelligence

In this article, we examine the television series about global surveillance Person of Interest ( POI) (aired on CBS, 2011–2016) to reflect on popular understandings of surveillance and account for its representation of artificial intelligence (AI) and algorithmic surveillance. Drawing on television, media, and surveillance studies, we focus on the power of representations of social relations and diegetic technologies in possible and imagined futures to explore the role of cultural representations in shaping social order. Through the character of the AI Machine representing algorithmic surveillance, we evaluate the show’s critique of algorithmic autonomy and contend that, as a media technology of surveillance, the show participates in the hype of big data as a panacea while banalizing surveillance. We argue that POI could facilitate a comprehensive analysis of the politics of algorithmic surveillance but fails to do so due to its uncritical representation of artificial intelligence agencies in detecting security risks.

조지 엘리엇의 리얼리즘에서 관습과 스테레오타입의 문제

This paper examines the issue of stereotypes and conventions as constitutive elements of the realist form, focusing on chapter 17 of Adam Bede, which is most often cited when discussing the realist aesthetic of 19th-century English writer George Eliot. The emphasis on stereotypes and conventions is centered on Eliot’s observation of the still life. I argue that Eliot’s fiction aims for moral truth rather than mechanical objectivity in its representations in order to elicit reader’s sympathy. As such, Eliot’s realism emphasizes empirical observation while simultaneously embracing idealism. In addressing the often-debated “question of objectivity in the aesthetic representation of reality” in realism, the focus then needs to be on the word “aesthetic” as much as on “objectivity,” and this paper argues that Eliot’s aesthetic achievement is not sufficiently free from the constraints of convention and stereotype.

Data-driven inference of low order representations of observable dynamics for an airfoil model

Reduced order modeling of fluid flow systems can allow for the application of more sophisticated mathematical analysis and control techniques that would otherwise be computationally prohibitive. Existing reduction techniques often fail when nonlinear terms dominate the flow (e.g., at large Reynolds numbers) necessitating the development of new techniques. In this work, we implement an adaptive isostable reduction strategy to obtain a data-driven reduced order model that captures the dynamics of observables in a computational model for fluid flow over an airfoil at moderate Reynolds numbers. The resulting model characterizes the response to both time-varying inflow conditions and Dirichlet boundary conditions on the surface of the airfoil meant to represent suction or blowing through the action of surface jets. The resulting reduced order model behaviors agree well with the dynamics of the full order model simulations in response to both open loop and closed loop inputs. This study provides a proof of concept that reduced order modeling techniques using adaptive isostable coordinates can be successfully used in realistic fluid flow models using geometries with practical relevance.

'Qualitative' and 'quantitative' methods and approaches across subject fields: implications for research values, assumptions, and practices

There is considerable literature showing the complexity, connectivity and blurring of 'qualitative' and 'quantitative' methods in research. Yet these concepts are often represented in a binary way as independent dichotomous categories. This is evident in many key textbooks which are used in research methods courses to guide students and newer researchers in their research training. This paper analyses such textbook representations of 'qualitative' and 'quantitative' in 25 key resources published in English (supported by an outline survey of 23 textbooks written in German, Spanish and French). We then compare these with the perceptions, gathered through semi-structured interviews, of university researchers (n = 31) who work in a wide range of arts and science disciplines. The analysis of what the textbooks say compared to what the participants report they do in their practice shows some common features, as might be assumed, but there are significant contrasts and contradictions. The differences tend to align with some other recent literature to underline the complexity and connectivity associated with the terms. We suggest ways in which future research methods courses and newer researchers could question and positively deconstruct such binary representations in order to free up directions for research in practice, so that investigations can use both quantitative or qualitative approaches in more nuanced practices that are appropriate to the specific field and given context of investigations.

Identification of fractional Hammerstein model for electrical stimulated muscle: An application of fuzzy-weighted differential evolution

Fractional order representations model complex systems with less parameters, improved accuracy and enhanced robustness in control systems but the system identification of fractional order systems is highly complicated and challenging task because of substantial nonlinearity of the input, unknown linear/nonlinear parameters of the blocks, and unknown fractional order. In this paper, parameter estimation technique is proposed based on fuzzy-weighted differential evolution algorithm for fractional electrically stimulated muscle models, which is generalization of fractional Hammerstein controlled autoregressive model vital for rehabilitation of spinal cord injury (SCI) patients. The system identification problem of fractional electrically stimulated muscle models (FESMMs) is formulated via mean square error approximation between the true and estimated response of FESMMs. The parameters of FESMMs are identified by employing fuzzy weighted differential evolution algorithm optimization knacks of with polynomial, cubic spline and sigmoidal input nonlinearities on various noise variances in the system dynamics. Comparison of results from actual to calculated responses indicates closeness up to 4 decimal places of accuracy for FESMM with polynomial type nonlinearity, up to 6 decimal places for FESMM with sigmoidal type kernel, and up to 5 decimal for FESMM with cubic spline type nonlinearity for different low and high signal to noise scenarios i.e., σ2=0.0022,0.022,0.22, which verify the precision, efficacy, stability and reliability of the fuzzy weighted differential evolution algorithm for system identification of FESMMs in rehabilitation scenarios of SCI.

Roles of Political Orientation and Social Representations of Social Order on Socio-Representational Construction Towards Universal Basic Income in France

Abstract As an object which is new, complex and potentially challenging some of the foundations of the Social Order (SO), we sought to study the influence of the Political Orientation (PO) and Social Representations (SR) of the Social Order (Staerklé et al., 2007). Qui a droit à quoi ? Représentations et légitimation de l’ordre social. PUG) on the socio-representational construction of the Universal Basic Income (UBI) and stances towards this measure (attitude and estimated fair amount). Data were collected via Facebook from 264 French general population participants (Mage = 37.8; SD = 12.7; 174 women). Our Structural Equation Model revealed that the PO would be associated with the stances towards the UBI, mediated by the different ways of representing it and the representations of the SO. Results show two differents socio-representational logics in relation to being right-wing and one in relation to being left-wing. This leads to contrasting stances towards the UBI and seems to reflect different desires to maintain or change the SO.

Climatology of Tropical Cyclone Precipitation in the S2S Models

Abstract This study evaluates the representation of tropical cyclone precipitation (TCP) in reforecasts from the Subseasonal to Seasonal (S2S) Prediction Project. The global distribution of precipitation in S2S models shows relevant biases in the multimodel mean ensemble that are characterized by wet biases in total precipitation and TCP, except for the Atlantic. The TCP biases can contribute more than 50% of the total precipitation biases in basins such as the southern Indian Ocean and South Pacific. The magnitude and spatial pattern of these biases exhibit little variation with lead time. The origins of TCP biases can be attributed to biases in the frequency of tropical cyclone occurrence. The S2S models simulate too few TCs in the Atlantic and western North Pacific and too many TCs in the Southern Hemisphere and eastern North Pacific. At the storm scale, the average peak precipitation near the storm center is lower in the models than observations due to a too high proportion of weak TCs. However, this bias is offset in some models by higher than observed precipitation rates at larger radii (300–500 km). An analysis of the mean TCP for each TC at each grid point reveals an overestimation of TCP rates, particularly in the near-equatorial Indian and western Pacific Oceans. These findings suggest that the simulation of TC occurrence and the storm-scale precipitation require better representation in order to reduce TCP biases and enhance the subseasonal prediction skill of mean and extreme total precipitation.

Global semantic enhancement network for video captioning

Video captioning aims to briefly describe the content of a video in accurate and fluent natural language, which is a hot research topic in multimedia processing. As a bridge between video and natural language, video captioning is a challenging task that requires a deep understanding of video content and effective utilization of diverse video multimodal information. Existing video captioning methods usually ignore the relative importance between different frames when aggregating frame-level video features and neglect the global semantic correlations between videos and texts in learning visual representations, resulting in the learned representations less effective. To address these problems, we propose a novel framework, namely Global Semantic Enhancement Network (GSEN) to generate high-quality captions for videos. Specifically, a feature aggregation module based on a lightweight attention mechanism is designed to aggregate frame-level video features, which highlights features of informative frames in video representations. In addition, a global semantic enhancement module is proposed to enhance semantic correlations for video and language representations in order to generate semantically more accurate captions. Extensive qualitative and quantitative experiments on two public benchmark datasets MSVD and MSR-VTT demonstrate that the proposed GSEN can achieve superior performance than state-of-the-art methods.