Hasil untuk "Modern"

D. Pellow

J. Ruggie

Morroe Berger, T. Abel, C. Page et al.

G. Whittington, A. Berle, G. Means

G. F. Simmons

Cédric Manouan, Miquilina Anagbah, N'guessan Yves-Roland Douha et al.

Africa's participation in modern AI development is constrained by severe infrastructural and policy gaps. Important barriers include limited access to high-performance computing (HPC), restricted cloud access due to payment system mismatches, volatile exchange rates, and strict data sovereignty laws that fragment regional collaboration between African Union (AU) member states. Although initiatives such as Cassava AI's network of AI factories to be deployed across the continent signal the growing interest in adopting AI in Africa, these projects remain very targeted, while continental adoption still requires better coordination between African stakeholders. Drawing on official declarations on AI adoption across the continent, this paper offers both qualitative and quantitative evidence that sustainable AI adoption requires robust digital foundations through balanced access to compute, data, and the energy that makes it possible. We refer to these foundations as the "right enablers", considering them as crucial components for success within the current context of the global AI race. We also introduce the \textit{Africa AI Compute Tracker (ACT)}, an interactive map to monitor the availability of AI-ready HPC systems throughout the continent. This tool represents the first open-source effort to consolidate data on Africa's evolving HPC landscape, and aims to encourage more transparency from local AI stakeholders while facilitating broader access for AI developers. The work presented in this paper underscores the urgency of tangible actions aimed at closing the AI divide and allowing Africa to actively shape its AI future.

Lasse Borgholt, Jakob Havtorn, Christian Igel et al.

Modern neural networks have greatly improved performance across speech recognition benchmarks. However, gains are often driven by frequent words with limited semantic weight, which can obscure meaningful differences in word error rate, the primary evaluation metric. Errors in rare terms, named entities, and domain-specific vocabulary are more consequential, but remain hidden by aggregate metrics. This highlights the need for finer-grained error analysis, which depends on accurate alignment between reference and model transcripts. However, conventional alignment methods are not designed for such precision. We propose a novel alignment algorithm that couples dynamic programming with beam search scoring. Compared to traditional text alignment methods, our approach provides more accurate alignment of individual errors, enabling reliable error analysis. The algorithm is made available via PyPI.

Vihan Lakshman, Blaise Munyampirwa, Julian Shun et al.

Modern vector databases enable efficient retrieval over high-dimensional neural embeddings, powering applications from web search to retrieval-augmented generation. However, classical theory predicts such tasks should suffer from the curse of dimensionality, where distances between points become nearly indistinguishable, thereby crippling efficient nearest-neighbor search. We revisit this paradox through the lens of stability, the property that small perturbations to a query do not radically alter its nearest neighbors. Building on foundational results, we extend stability theory to three key retrieval settings widely used in practice: (i) multi-vector search, where we prove that the popular Chamfer distance metric preserves single-vector stability, while average pooling aggregation may destroy it; (ii) filtered vector search, where we show that sufficiently large penalties for mismatched filters can induce stability even when the underlying search is unstable; and (iii) sparse vector search, where we formalize and prove novel sufficient stability conditions. Across synthetic and real datasets, our experimental results match our theoretical predictions, offering concrete guidance for model and system design to avoid the curse of dimensionality.

Dmitry Mikhaylyuk / Дмитрий Павлович Михайлюк, Amir Kader / Амир Святославович Кадер

The aim of the research is to identify the evolutionary scenario and the specifics of the transformation of the child's image in Russian art, primarily using Soviet cinema as an example, taking into account the experience of world art development and the connection between the "Sixtiers" and the aesthetics of neorealism. The article analyzes the causes and nature of significant changes in the image of the child in 20th-century art, considering large-scale social, cultural, and ideological transformations. One of the prominent movements that shaped original perceptions of childhood was Italian neorealism, in which the image of the "orphan child" became a symbol of the tragic consequences of historical cataclysms and socio-economic crises. Soviet art, from its very inception, actively used images of young characters. For instance, the films "Kino-glaz" (1924), "The Desperate Battalion" (1933), and "Golden Honey" (1928) presented children as active participants in social life. Children were often depicted as miniature adults, actively involved in labor and patriotic processes. The article shows how, in the 1960s, Russian art, influenced by the aesthetics of neorealism, began to re-evaluate the image of the child. The "Sixtiers" paid more attention to child psychology, themes of socialization, friendship, and growing up. The relevance of studying the image of the child in contemporary art is linked to the need to support and assist children in the process of socialization. Modern cinema about children and for children not only showcases young heroes but also transmits important moral and ethical lessons to them and to society as a whole. The research results have demonstrated that realistic art, which rejects fantastical elements, offers children an experience based on real-life situations, helping them develop critical thinking and emotional perception of the world. / Цель исследования состоит в выявлении сценария эволюции и специфики трансформации образа ребенка в отечественном искусстве, преимущественно на примере советского кинематографа с учетом опыта развития мирового искусства и взаимосвязи «шестидесятников» с эстетикой неореализма. Статья анализирует причины и характер значительных изменений образа ребенка в искусстве XX века с учетом масштабных общественных, культурных и идеологических трансформаций. Одним из ярких направлений, сформировавших оригинальные представления о детстве, выступил итальянский неореализм, в котором образ «ребенка-сироты» стал символом трагических последствий исторических катаклизмов и социально-экономических кризисов. Советское искусство, начиная с первых своих шагов, активно использовало образы юных персонажей. Так фильмы «Кино-глаз» (1924), «Отчаянный батальон» (1933), «Золотой мед» (1928) представляли детей как активных участников социальной жизни. Часто дети изображались как миниатюрные взрослые, активно вовлеченные в трудовые и патриотические процессы. В статье показано, как в 1960-е годы отечественное искусство под влиянием эстетики неореализма начинает переосмысливать образ ребенка. Шестидесятники в большей мере уделяли внимание психологии ребенка, темам социализации, дружбы, взросления. Актуальность изучения образа ребенка в современном искусстве связана с необходимостью поддержки и помощи детям в процессе социализации. Современное кино о детях и для детей не только показывает юных героев, но и транслирует им и всему обществу важные уроки нравственности и морали. Результаты исследования продемонстрировали, что реалистическое искусство, отказывающееся от фантастических элементов, предлагает ребенку опыт, основанный на реальных жизненных ситуациях, помогающий развивать критическое мышление и эмоциональное восприятие мира.

T. A. Balina , L. S. Batalova , M. A. Pospishenko

Light industry is one of the oldest sectors of the world economy, which has developed rapidly under the influence of industrial revolutions, the introduction of technological innovations, the development of trade, increased competition in consumer goods markets and other factors, which formed special areas of the industry with its centers. Global trends and features of the development of light industry are of interest for spatio-temporal analysis necessary for understanding the problems of domestic production. The relevance of the study is due to the need for a scientific analysis of the development of key sectors of the light industry in the context of modern geopolitical and macroeconomic realities in the context of constituent entities and federal districts. Having a relatively small share in the structure of manufacturing, light industry plays an important role in the country’s economy, provides all its spheres with various types of products, and the population with consumer goods. Russia’s modern light industry has complex technological chains, relies on a diverse raw material base, it is focused on the growth of consumer demand, which requires the modernization of production. Radical changes in the sectoral and spatial structure of light industry in the world, as well as import substitution requirements have had a great impact on the state of the industry in the regions of Russia. Geopolitical challenges have shown that it is necessary to make maximum use of the existing potential by creating new production facilities, introducing modern technologies, forming our own raw material bases, and training personnel for the sustainable development of the industry. The post-Soviet crisis slowed down the development of light industry for a long time, but at present it is being renovated and transformed into a creative industry. The retrospective analysis reveals positive dynamics in the development of key sectors of light industry, despite the aggravation of a number of problems. Changes in the sectoral and territorial structure of the industry were identified, a typology of the subjects of the Russian Federation was made up by the share of light industry in the economy of the regions. Measures are proposed to bring the industry to a qualitatively new level of development.

Nahida Aktary, Yerim Jeong, Seungji Oh et al.

Alzheimer’s disease (AD) is a multifactorial neurodegenerative disorder described as progressive cognitive decline and neuronal dysfunction, affecting millions globally. While current pharmacological treatments provide symptomatic relief and modestly slow disease progression, they fail to address the underlying pathophysiology and are often accompanied by severe adverse effects. This underscores the urgent need for innovative, multi-target therapeutic strategies that can effectively step in AD’s complex pathogenesis. Emerging evidence highlights the therapeutic potential of natural products, particularly herbal medicines, as versatile modulators of key pathogenic processes in AD. These compounds exert neuroprotective effects by mitigating oxidative stress, suppressing neuroinflammation, inhibiting tau hyperphosphorylation, and reducing amyloid-beta aggregation. Additionally, they strengthen synaptic plasticity and stabilize mitochondrial function, offering a holistic approach to disease control. This comprehensive review synthesizes findings from network pharmacology, in vitro and in vivo studies, and clinical trials to evaluate the role of natural products in AD treatment. Advances in bioinformatics and systems biology facilitate the mapping of intricate protein-protein interactions, the identification of potential biomarkers, and the clarification of molecular mechanisms underlying AD progression. Integrating phytochemicals with conventional AD medications may improve therapeutic efficacy through synergistic mechanisms; however, pharmacokinetic interactions and safety considerations must be rigorously assessed. Notably, clinical trials investigating compounds such as curcumin, resveratrol, and ginsenosides suggest promising adjunctive benefits when incorporated into established treatment regimens. Furthermore, the convergence of herbal therapeutics with modern pharmacology presents an avenue for customized and integrative AD management. This review also emphasizes advancements in experimental models, including brain organoids and transgenic animals, which serve as crucial platforms for mechanistic studies and therapeutic validation. Ongoing trials on plant-derived compounds continue to pave the way for translational applications, reinforcing the viability of natural product-based interventions. By advocating a multidisciplinary framework that merges traditional medicine, modern pharmacology, and precision medicine, this work contributes to reshaping the AD landscape of therapy. It provides a roadmap for future research, fostering novel treatment paradigms that prioritize efficacy, safety, and sustainability in combating this disastrous disorder.

Sen GAO, Jazmin Binti Mohamad JAAFAR, S. Siti SUHAILY et al.

Purpose: This study aims to explore the continuity of Han Dynasty aesthetics in modern Chinese art and its influence on contemporary urban landscapes. Han Dynasty, being the foundation of China history, was founded by Emperor Gaozu, whom also stabiized and unified the land of China, similar to modern territory. By investigating the historical achievements and artistic legacy of the Han Dynasty, the study seeks to identify key aesthetic principles, motifs, and techniques that continue to shape modern Chinese art and urban design. Moreover, the research aims to understand the role of Confucianism and Daoism in shaping Han Dynasty aesthetics and their enduring impact on cultural practices and urban development in China. Method: This qualitative study conducted 17 semi-structured interviews with stakeholders, including urban planners, artists, policymakers, and cultural practitioners in China. The interviews were analyzed using thematic analysis, focusing on identifying patterns, themes, and relationships related to Han Dynasty aesthetics, contemporary public art characteristics, cultural continuity, urban development factors, and urban aesthetics. Findings: The findings of this study highlight the enduring influence of Han Dynasty aesthetics on contemporary Chinese art and urban landscapes. Key themes include the integration of traditional motifs and techniques into modern artistic expressions, the role of cultural continuity in shaping urban aesthetics, and the moderating influence of urban development factors on the preservation and integration of Han Dynasty aesthetics within contemporary urban environments. Implications/Originality: This research contributes to theoretical frameworks in art history, cultural studies, and urban studies by providing new insights into the continuity of Han Dynasty aesthetics and its implications for modern Chinese culture and society. Moreover, the findings have practical implications for policymakers, urban planners, artists, and cultural practitioners involved in the development and management of urban environments in China. Overall, this study shows the farreaching impacts of Han Dynasty, spanning across time to affect the current society in the form of urban asthetics, cultures, and even to the policymakers ; while adds to the understanding of the dynamic relationship between tradition and innovation in Chinese art and culture and its significance for contemporary urban landscapes.

Rajesh Kumar, Yuhan Wang, Nikolas Cruz Camacho et al.

We explore the Quantum Chromodynamics (QCD) phase diagram's complexities, including quark deconfinement transitions, liquid-gas phase changes, and critical points, using the chiral mean-field (CMF) model that is able to capture all these features. We introduce a vector meson renormalization within the CMF framework, enabling precise adjustments of meson masses and coupling strengths related to vector meson interactions. Performing a new fit to the deconfinement potential, we are able to replicate recent lattice QCD results, low energy nuclear physics properties, neutron star observational data, and key phase diagram features as per modern constraints. This approach enhances our understanding of vector mesons' roles in mediating nuclear interactions and their impact on the equation of state, contributing to a more comprehensive understanding of the QCD phase diagram and its implications for nuclear and astrophysical phenomena.

Alessio Rocci, Thomas Van Riet

This paper analyzes the effective field theory perspective on modern physics through the lens of the quantum theory of gravitational interaction. The historical part argues that the search for a theory of quantum gravity stimulated the change in outlook that characterizes the modern approach to the Standard Model of particle physics and General Relativity. We present some landmarks covering a long period, i.e., from the beginning of the 1930s until 1994, when, according to Steven Weinberg, the modern bottom-up approach to General Relativity began. Starting from the first attempt to apply the quantum field theory techniques to perturbatively quantize Einstein's theory, we explore its developments and interaction with the top-down approach encoded by String Theory. In the last part of the paper, we focus on this last approach to describe the relationship between our modern understanding of String Theory and Effective Field Theory in today's panorama. To this end, the non-historical part briefly explains the modern concepts of moduli stabilization and Swampland to understand another change in focus that explains the present framework where some string theorists move.

Guglielmo Campus, John Yun Niu, Berkant Sezer et al.

Abstract The 2017 Global Disease Study revealed 2.3 billion untreated cavities and 139 million other oral conditions like dental erosion. Modern treatments prioritise controlling etiological factors and preventing related diseases. This Editorial invites researchers to contribute to the collection, ‘Prevention and management of dental erosion and decay’.

R. Scheffold

Mustafa Jarrar, Ahmet Birim, Mohammed Khalilia et al.

This paper presents the ArBanking77, a large Arabic dataset for intent detection in the banking domain. Our dataset was arabized and localized from the original English Banking77 dataset, which consists of 13,083 queries to ArBanking77 dataset with 31,404 queries in both Modern Standard Arabic (MSA) and Palestinian dialect, with each query classified into one of the 77 classes (intents). Furthermore, we present a neural model, based on AraBERT, fine-tuned on ArBanking77, which achieved an F1-score of 0.9209 and 0.8995 on MSA and Palestinian dialect, respectively. We performed extensive experimentation in which we simulated low-resource settings, where the model is trained on a subset of the data and augmented with noisy queries to simulate colloquial terms, mistakes and misspellings found in real NLP systems, especially live chat queries. The data and the models are publicly available at https://sina.birzeit.edu/arbanking77.

M. Jay, H. Blumenberg, R. M. Wallace

M. Anand, M.A. Panteleev, F.I. Ataullakhanov

The history of studies on blood clotting goes back to the emergence of civilized society itself. The foundations of the modern scientific study of hemostasis are based on the discovery of erythrocytes in blood in 1674 and, later, that of platelets in 1842. The causes of thrombosis are encapsulated in the Virchow Triad (dated to 1856), which refers, in modern terms, to hypercoagulability, alterations of hemodynamics (stasis), and endothelial injury. The understanding of coagulation, the network of reactions that underlies hemostasis and thrombosis, has evolved from a cascade (in 1964) into spatially distinct sets of reactions dependent on co-factors occurring on different cells in different tissues and linked together by diffusion and flow (as of 2015). Correspondingly, mathematical/computational models for hemostasis and thrombosis (which involve coagulation along with platelet aggregation in the presence of flow) have evolved in design complexity from Continuum temporal (or “homogeneous”) models to Continuum spatio-temporal models (with or without the flow) and lately into Discrete-Continuum spatio-temporal models with the flow. After a brief listing of the discoveries and historical personae that contributed to the understanding of hemostasis up to the present, the development of mathematical/computational models is traced from the late 1980s when they started gaining importance. Influential models are then highlighted. The models are reviewed in increasing order of design complexity (one of four possible methods of classification). The physiological significance of each and the insights they offer into hemostasis regulation are explained.

N. Yu. Kaufman, S. Yu. Zelentsova

The article explores the principles of building a competitive specialist in adigitally transformed economy, and presents the prerequisites that justify the development of staff training through the automation of HR technologies. The interpretation of the concepts «digital economy», «EdTech», «staff training», «gamification» is given. The main barriers preventing the implementation of HR Tech solutions in organisations are showed. The use of statistical analysis and comparison methods made it possible to present the areas of HR Tech, where digitalisation most actively improves and automates processes. It has been revealed that the main drivers of efficiency in the HR sphere can be modern tools and platforms that contribute to the introduction of automation in the personnel training system. The events of recent years have led to the understanding that it will no longer be possible to work effectively without the use of new technologies, therefore, the advantages of automating learning processes are highlighted. The role and area of responsibility of the training and development manager in the process of staff training has been established. Scenarios for solving the problem of a shortage of a digital specialist have been determined.