Partial Representation Research Articles

Identifying patient subgroups in MASLD and MASH-associated fibrosis: molecular profiles and implications for drug development

The incidence of MASLD and MASH-associated fibrosis is rapidly increasing worldwide. Drug therapy is hampered by large patient variability and partial representation of human MASH fibrosis in preclinical models. Here, we investigated the mechanisms underlying patient heterogeneity using a discovery dataset and validated in distinct human transcriptomic datasets, to improve patient stratification and translation into subgroup specific patterns. Patient stratification was performed using weighted gene co-expression network analysis (WGCNA) in a large public transcriptomic discovery dataset (n = 216). Differential expression analysis was performed using DESeq2 to obtain differentially expressed genes (DEGs). Ingenuity Pathway analysis was used for functional annotation. The discovery dataset showed relevant fibrosis-related mechanisms representative of disease heterogeneity. Biological complexity embedded in genes signature was used to stratify discovery dataset into six subgroups of various sizes. Of note, subgroup-specific DEGs show differences in directionality in canonical pathways (e.g. Collagen biosynthesis, cytokine signaling) across subgroups. Finally, a multiclass classification model was trained and validated in two datasets. In summary, our work shows a potential alternative for patient population stratification based on heterogeneity in MASLD-MASH mechanisms. Future research is warranted to further characterize patient subgroups and identify protein targets for virtual screening and/or in vitro validation in preclinical models.

Does interlanguage grammar project intermediate categories? Evidence of partial representation from one‐substitution by Chinese learners of English

AbstractThis study investigates how prepositional phrases within English noun phrases (e.g., the student of physics from Italy) are represented and processed by advanced Chinese‐speaking learners of English (henceforth L2ers). Using grammaticality judgment tasks and self‐paced reading tasks, we aim to examine the offline performance and the real‐time processing of English NP‐internal PPs in relation to the head nouns. To this end, two groups of participants were instructed to provide judgments of testing materials and to respond on‐line to experimental stimuli containing the proform one. Results indicate that highly proficient L2ers processed English NP‐internal PPs utterly differently from English controls in that they demonstrated almost no sensitivity to the existence of PPs as complements following one, mostly without consciously distinguishing them from PP adjuncts. To account for L2ers’ response patterns, we propose a partial representation hypothesis (PRH), claiming that L2ers tend to disregard intermediate categories containing PP‐complements in English NPs, thus only partially representing syntactic constituents of the target language. As a structural explanation, PRH awaits further corroboration and/or falsification from more empirical studies.

The representation of noun-verb distinction in left posterior middle temporal gyrus: evidence from representation similarity analyses.

Nouns and verbs are fundamental grammatical building blocks of languages. A key question is whether and where the noun-verb division was represented in the brain. Previous studies mainly used univariate analyses to examine this issue. However, the interpretation of activated brain regions in univariate analyses may be confounded with general cognitive processing and/or confounding variables. We addressed these limitations by using partial representation similarity analysis (RSA) of Chinese nouns and verbs with different levels of imageability. Participants were asked to complete the 1-back grammatical class probe (GCP; an explicit measure) and the 1-back word probe (WP; an implicit measure) tasks while undergoing functional magnetic resonance imaging. RSA results showed that the activation pattern in the left posterior middle temporal gyrus (LpMTG) was significantly correlated with the grammatical class representational dissimilarity matrix in the GCP task after eliminating the potential confounding variables. Moreover, the LpMTG did not overlap with the frontal-parietal regions that were activated by verbs vs. nouns or the task effect (CRP vs. WP) in univariate analyses. These results highlight the role of LpMTG in distinguishing nouns from verbs rather than general cognitive processing.

Powers and roots of partial isometric covariant representations

Powers and roots of partial isometric covariant representations

India’s G20 Presidency and IBSA Troika – Reaffirming Southern Leadership

India's G20 presidency has been a successful moment in global governance deliberations in the backdrop of geopolitical fragmentation and ongoing conflicts. With the unanimous adoption of the New Delhi Leaders' Declaration on the first day of the Leaders’ Summit, India was able to showcase its diplomatic effectiveness; which generated goodwill for India as a trusted partner of the Global South given the fact that G20 so far had partial representation of developing countries.

KLSANet: Key local semantic alignment Network for few-shot image classification

Few-shot image classification involves recognizing new classes with a limited number of labeled samples. Current local descriptor-based methods, while leveraging consistent low-level features across visible and invisible classes, face challenges including redundant adjacent information, irrelevant partial representation, and limited interpretability. This paper proposes KLSANet, a few-shot image classification approach based on key local semantic alignment network, which aligns key local semantics for accurate classification. Furthermore, we introduce a key local screening module to mitigate the influence of semantically irrelevant image parts on classification. KLSANet demonstrates superior performance on three benchmark datasets (CUB, Stanford Dogs, Stanford Cars), outperforming state-of-the-art methods in 1-shot and 5-shot settings with average improvements of 3.95% and 2.56% respectively. Visualization experiments demonstrate the interpretability of KLSANet predictions. Code is available at: https://github.com/ZitZhengWang/KLSANet.

Exploring the Extended Beta-Logarithmic Function: Matrix Arguments and Properties

The beta-logarithmic function substantially generalizes the standard beta function, which is widely recognized for its significance in many applications. This article is devoted to the study of a generalization of the classical beta-logarithmic function in a matrix setting called the extended beta-logarithmic matrix function. The proofs of some essential properties of this extension, such as convergence, partial derivative formulas, functional relations, integral representations, inequalities, and finite and infinite sums, are established. Moreover, an application of the extended beta-logarithmic function in matrix arguments is proposed in probability theory. Further, numerical examples and graphical presentations of the new generalization are obtained.

Morita equivalence and globalization for partial Hopf actions on nonunital algebras

In this work, we investigate partial actions of a Hopf algebra [Formula: see text] on nonunital algebras and the associated partial smash products, with the objective of providing a framework where one may obtain results for both [Formula: see text]-algebras with local units and [Formula: see text]-categories. We show that our partial actions correspond to nonunital algebras in the category of partial representations of [Formula: see text]. The central problem of existence of a globalization for a partial action is studied in detail, and we provide sufficient conditions for the existence (and uniqueness) of a minimal globalization for associative algebras in general. Extending previous results by Abadie, Dokuchaev, Exel and Simon, we define Morita equivalence for partial Hopf actions, and we show that if two symmetrical partial actions are Morita equivalent then their standard globalizations are also Morita equivalent. Particularizing to the case of a partial action on an algebra with local units, we obtain several strong results on equivalences of categories of modules of partial smash products of algebras and partial smash products of [Formula: see text]-categories.

Efficacy of Digital Pricing Strategies on Customer Buying Decisions in the E-Commerce Industry: A PLS-SEM Approach

E-commerce is a vital component of global retail sustainability, expanding at a rate of 14% annually, fuelled by increased internet adoption (55%), with over five billion users worldwide. In Africa, e-commerce revenues have surged to $31.18 million, with Nigeria’s Business to Consumer (B2C) index hitting 53.2 points and boasting a 55% internet penetration rate in 2023, ranking fourth highest on the continent. The globalisation of markets has exposed ecommerce companies to economic downturns, compelling them to adopt strategic pricing approaches to ensure sustained profitability and competitiveness. Consumers have become more price-sensitive, emphasising the need for firms to accurately gauge pricing sensitivity to influence purchasing decisions effectively. This research explores how ecommerce stores utilise digital pricing strategies to impact the purchasing behaviour of Gen Z consumers in Nigeria. By employing an exploratory research design, the study utilised an online survey distributed through Google Form, targeting tech-savvy Gen Z consumers, who represent over 85% of the 384-sample size derived using the Borden sampling model. By being guided by the theory of planned behaviour, the PLS-SEM model indicates that special event pricing (0.433, 91.8% effect), sample product pricing (0.236, 85.0% effect), and loss leader pricing (0.236, 93% effect) significantly impact Gen Z’s consumer patronage (62.4%). Furthermore, product lining pricing (0.457, 93.7% high effect), captive pricing (0.161, 96.21% high effect), and optional pricing strategy (0.252, 96.0% medium effect) influence Gen Z’s online purchase satisfaction (67.2%). This underscores the importance of digital pricing strategies in shaping Gen Z’s online purchase behaviour. The research recommends the need for online stores to incorporate promotional and product mix strategies in business tactics; governments should monitor fair pricing practices, and online retailers should educate consumers about pricing strategies to foster informed purchasing decisions. The research acknowledges potential biases in data collection, stemming from unequal online access among Gen Z consumers, resulting in a partial representation of the diverse range of Gen Z behaviours across the continent, as various cultural, economic, and social factors can influence purchasing behaviours.

(Co)homology of partial smash products

Given a cocommutative Hopf algebra H over a commutative ring K and a symmetric partial action of H on a K-algebra A, we obtain a first quadrant Grothendieck spectral sequence converging to the Hochschild homology of the smash product A#H, involving the Hochschild homology of A and the partial homology of H. An analogous third quadrant cohomological spectral sequence is also obtained. The definition of the partial (co)homology of H under consideration is based on the category of the partial representations of H. A specific partial representation of H on a subalgebra B of the partial “Hopf” algebra Hpar is involved in the definition and we construct a projective resolution of B.

Extending Partial Representations of Circle Graphs in Near-Linear Time

The partial representation extension problem generalizes the recognition problem for geometric intersection graphs. The input consists of a graph G, a subgraph H⊆G\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$H \\subseteq G$$\\end{document} and a representation R′\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathcal R'$$\\end{document} of H. The question is whether G admits a representation R\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathcal R$$\\end{document} whose restriction to H is R′\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathcal R'$$\\end{document}. We study this question for circle graphs, which are intersection graphs of chords of a circle. Their representations are called chord diagrams. We show that for a graph with n vertices and m edges the partial representation extension problem can be solved in O((n+m)α(n+m))\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$O((n + m) \\alpha (n + m))$$\\end{document} time, thereby improving over an O(n3)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$O(n^3)$$\\end{document}-time algorithm by Chaplick et al. (J Graph Theory 91(4), 365–394, 2019). The main technical contributions are a canonical way of orienting chord diagrams and a novel compact representation of the set of all canonically oriented chord diagrams that represent a given circle graph G, which is of independent interest.

Inflation correlators with multiple massive exchanges

The most general tree-level boundary correlation functions of quantum fields in inflationary spacetime involve multiple exchanges of massive states in the bulk, which are technically difficult to compute due to the multi-layer nested time integrals in the Schwinger-Keldysh formalism. On the other hand, correlators with multiple massive exchanges are well motivated in cosmological collider physics, with the original quasi-single-field inflation model as a notable example. In this work, with the partial Mellin-Barnes representation, we derive a simple rule, called family-tree decomposition, for directly writing down analytical answers for arbitrary nested time integrals in terms of multi-variable hypergeometric series. We present the derivation of this rule together with many explicit examples. This result allows us to obtain analytical expressions for general tree-level inflation correlators with multiple massive exchanges. As an example, we present the full analytical results for a range of tree correlators with two massive exchanges.

A comonadicity theorem for partial comodules

We show that the category of partial comodules over a Hopf algebra H is comonadic over Vectk and provide an explicit construction of this comonad using topological vector spaces. The case when H is finite-dimensional is treated in detail. A study of partial representations of linear algebraic groups is initiated; we show that a connected linear algebraic group does not admit partiality.

Partial groupoid representations and a relation with the Birget–Rhodes expansion

We introduce partial groupoid representations of a finite groupoid \mathcal{G} on an algebra \mathcal{A} . We also show that the partial groupoid representations of \mathcal{G} are in one-to-one correspondence with the representations of the algebra generated by the Birget–Rhodes expansion \mathcal{G}^{\mathrm{BR}} of \mathcal{G} .

Probing the Nonlinear Interactions of Supertidal Internal Waves Using a High-Resolution Regional Ocean Model

Abstract The internal wave (IW) continuum of a regional ocean model is studied in terms of the vertical spectral kinetic energy (KE) fluxes and transfers at high vertical wavenumbers. Previous work has shown that this model permits a partial representation of the IW cascade. In this work, vertical spectral KE flux is decomposed into catalyst, source, and destination vertical modes and frequency bands of nonlinear scattering, a framework that allows for the discernment of different types of nonlinear interactions involving both waves and eddies. Energy transfer within the supertidal IW continuum is found to be strongly dependent on resolution. Specifically, at a horizontal grid spacing of 1/48°, most KE in the supertidal continuum arrives there from lower-frequency modes through a single nonlinear interaction, whereas at 1/384° and with sufficient vertical resolution KE transfers within the supertidal IW continuum are comparable in size to KE transfer from lower-frequency modes. Additionally, comparisons are made with existing theoretical and observational work on energy pathways in the IW continuum. Induced diffusion (ID) is found to be associated with a weak forward frequency transfer within the supertidal IW continuum. ID is also limited to the highest vertical wavenumbers and is more sensitive to resolution relative to spectrally local interactions. At the same time, ID-like processes involving high-vertical-wavenumber near-inertial and tidal waves as well as low-vertical-wavenumber eddy fields are substantial, suggesting that the processes giving rise to a Garrett–Munk-like spectra in the present numerical simulation and perhaps the real ocean may be more varied than in idealized or wave-only frameworks.

Video-based person re-identification with complementary local and global features using a graph transformer.

In recent years, significant progress has been made in video-based person re-identification (Re-ID). The key challenge in video person Re-ID lies in effectively constructing discriminative and robust person feature representations. Methods based on local regions utilize spatial and temporal attention to extract representative local features. However, prior approaches often overlook the correlations between local regions. To leverage relationships among different local regions, we have proposed a novel video person Re-ID representation learning approach based on a graph transformer, which facilitates contextual interactions between relevant region features. Specifically, we construct a local relation graph to model intrinsic relationships between nodes representing local regions. This graph employs the architecture of a transformer for feature propagation, iteratively refining region features and considering information from adjacent nodes to obtain partial feature representations. To learn compact and discriminative representations, we have further proposed a global feature learning branch based on a vision transformer to capture the relationships between different frames in a sequence. Additionally, we designed a dual-branch interaction network based on multi-head fusion attention to integrate frame-level features extracted by both local and global branches. Finally, the concatenated global and local features, after interaction, are used for testing. We evaluated the proposed method on three datasets, namely iLIDS-VID, MARS, and DukeMTMC-VideoReID. Experimental results demonstrate competitive performance, validating the effectiveness of our proposed approach.

Analytic properties and numerical representations for constructing the extended beta function using logarithmic mean

<abstract><p>This paper aimed to obtain generalizations of both the logarithmic mean ($ \text{L}_{mean} $) and the Euler's beta function (EBF), which we call the extended logarithmic mean ($ \text{EL}_{mean} $) and the extended Euler's beta-logarithmic function (EEBLF), respectively. Also, we discussed various properties, including functional relations, inequalities, infinite sums, finite sums, integral formulas, and partial derivative representations, along with the Mellin transform for the EEBLF. Furthermore, we gave numerical comparisons between these generalizations and the previous studies using MATLAB R2018a in the form of tables and graphs. Additionally, we presented a new version of the beta distribution and acquired some of its characteristics as an application in statistics. The outcomes produced here are generic and can give known and novel results.</p></abstract>

Partial Multiview Representation Learning With Cross-View Generation.

Multiview learning has made significant progress in recent years. However, an implicit assumption is that multiview data are complete, which is often contrary to practical applications. Due to human or data acquisition equipment errors, what we actually get is partial multiview data, which existing multiview algorithms are limited to processing. Modeling complex dependencies between views in terms of consistency and complementarity remains challenging, especially in partial multiview data scenarios. To address the above issues, this article proposes a deep Gaussian cross-view generation model (named PMvCG), which aims to model views according to the principles of consistency and complementarity and eventually learn the comprehensive representation of partial multiview data. PMvCG can discover cross-view associations by learning view-sharing and view-specific features of different views in the representation space. The missing views can be reconstructed and are applied in turn to further optimize the model. The estimated uncertainty in the model is also considered and integrated into the representation to improve the performance. We design a variational inference and iterative optimization algorithm to solve PMvCG effectively. We conduct comprehensive experiments on multiple real-world datasets to validate the performance of PMvCG. We compare the PMvCG with various methods by applying the learned representation to clustering and classification. We also provide more insightful analysis to explore the PMvCG, such as convergence analysis, parameter sensitivity analysis, and the effect of uncertainty in the representation. The experimental results indicate that PMvCG obtains promising results and surpasses other comparative methods under different experimental settings.

Missing Poetry: A historiography of Albanian Literature during the Communist Regime

The paper aims at a panoramic view of the partial representation of Albanian poetry in the texts of the history of Albanian literature published during the dictatorship period (1945–1990). The fragmentary presentation of Albanian poetry and poets in informative scholarly and university texts on literature highlights the complications and the problems derived from this one-sided representation. The information gained only after the fall of the dictatorship, changed the situation regarding the literary values specifically related to poetry. What crucial representative texts on Albanian literary history were published during the dictatorship? Who were the most noticeable authors and poets, and why were they set aside, censored, imprisoned, executed, and not published? The answers suggest that only thanks to political change and awareness of literature can the reader today reassess this missing part of Albanian literature in historical texts published during the communist regime.
 The methodology relies on a historical, analytical, and critical approach to the most representative authors and their texts that is intertwined with factual data. The conclusions reinforce the idea that any evaluation of the literary process dictated by extra-literary principles damages the natural literary process. The revitalisation of literature after the 1990s, although with much delay, restored the natural process of aesthetic assessment. Now we can reassess the best part of that missing poetry.

Path to modeling dynamic performance shaping factors in nuclear power plants operation – A review

AbstractThe evolution of the mechanism of human behavior formation analysis has significantly influenced the development of human reliability analysis (HRA), which aims to calculate human error probability (HEP) with performance shaping factors (PSFs). This paper reviews the typical HRA methods in different generations, the role of PSFs, and their interrelation‐ships in human risk modeling, with the background of nuclear power plants (NPPs). In a retrospective of typical HRA methods, PSF plays a fundamental role in assessing human performance during task operation. However, the subjectivity in defining and evaluating PSFs often leads to a partial representation of human behavior characteristics and human risk evolution, resulting in the neglect of PSF inter‐relationships and conservative HEP estimation. Recent studies have emphasized employing simulation platforms to simulate the task process and obtain data relevant to PSFs that can enable the exploration of the mutual effects to support the calculation of HEP more accurately. Compared to certain previous methods involving over‐simplification and inappropriate assumptions resulting in inaccurate results, current HRA methods are prone to the construction of HEP models based on objective data acquisition and dynamic calculations with process models. This shift enables a better illustration of the intricate relationships among PSFs. Reflecting on the current trend of HRA methodology, this paper proposes a possible PSF quantification based on physiological measurement providing accessible and objective data. It improves the shortcomings in data scarcity and time‐invariance of HEP calculation, thus more accurately and realistically responds to the accumulation and fluctuation of human risks throughout a task.