Hasil untuk "Modern"

G. Covic, J. Boys

Alberto Bacchelli, C. Bird

N. Genova

E. Anslyn, D. Dougherty

N. C. Veitch

G. Marcoulides

María Lugones

Charles Taylor

One of the most influential philosophers in the English-speaking world, Charles Taylor is internationally renowned for his contributions to political and moral theory, particularly to debates about identity formation, multiculturalism, secularism, and modernity. In Modern Social Imaginaries, Taylor continues his recent reflections on the theme of multiple modernities. To account for the differences among modernities, Taylor sets out his idea of the social imaginary, a broad understanding of the way a given people imagine their collective social life. Retelling the history of Western modernity, Taylor traces the development of a distinct social imaginary. Animated by the idea of a moral order based on the mutual benefit of equal participants, the Western social imaginary is characterized by three key cultural forms—the economy, the public sphere, and self-governance. Taylor’s account of these cultural formations provides a fresh perspective on how to read the specifics of Western modernity: how we came to imagine society primarily as an economy for exchanging goods and services to promote mutual prosperity, how we began to imagine the public sphere as a metaphorical place for deliberation and discussion among strangers on issues of mutual concern, and how we invented the idea of a self-governing people capable of secular “founding” acts without recourse to transcendent principles. Accessible in length and style, Modern Social Imaginaries offers a clear and concise framework for understanding the structure of modern life in the West and the different forms modernity has taken around the world.

G. Bowen, J. Revenaugh

S. Eddy

E. B. McCollum

I. Chorkendorff, J. Niemantsverdriet

A. Yariv, P. Yeh

R. Mokken

J. Herd, M. Conway

Araj Sekh

Women’s rights in Islam are often debated and frequently misunderstood due to cultural practices and selective interpretations. This paper examines the historical evolution of women’s rights in Islam from pre-Islamic Arabia to modern times. It aims to show how Islamic teachings brought significant reforms in the social, legal, and moral status of women. Before Islam, women faced severe discrimination, denial of inheritance, and lack of personal choice. Islam addressed these injustices by granting women rights to inheritance, consent in marriage, education, religious responsibility, and participation in social life. The study also highlights the important contributions of Muslim women scholars, jurists, and educators during the prophetic and medieval periods. In addition, the paper briefly discusses Muslim feminism and contrasts it with Western feminist thought to clarify key ideological differences. Based on Qur’anic teachings, Hadith, and historical evidence, the paper argues that Islam fundamentally supports dignity, justice, and equity for women. The study concludes that many contemporary challenges faced by Muslim women arise from cultural misuse of religion rather than Islamic principles themselves. Understanding Islam through authentic sources is essential for an accurate view of women’s rights.

Muhammad Qamar, Ghulam Abbas, Meiyong Liao et al.

Abstract Control over plasmonic properties and local electric field enhancement has become an essential aspect of many modern technologies. Here we investigate these phenomena in graphene / hexagonal boron nitride (G/h-BN) heterostructures positioned on silicon (Si) and silicon dioxide (SiO2) substrates. Using finite element method for physics-based simulations of radio-frequency (RF) fields in optical range, we analyze electric field at the edges, on the flakes, and in the surrounding regions of the G/h-BN heterostructures. The results demonstrate that the electric field distribution around and within the heterostructure is strongly dependent on the thickness of graphene and h-BN flakes. The highest electric field amplification and focusing occurs at the G/h-BN edge for h-BN thicknesses between 80 and 100 nm on the Si substrate. In contrast, the SiO2 substrate substantially reduces overall field intensity in the G/h-BN heterostructures in comparison to the Si and reference structure without h-BN. These findings provide a consistent theoretical explanation for previously reported experimental Raman spectroscopy data on G/h-BN heterostructures and corroborate the model of localized charge carrier accumulation at the nanoscale G/h-BN edges on Si substrates. Furthermore, the study provides predictions for optimal excitation frequencies and for tailoring graphene plasmonic features in visible spectral range with the use of diamond and other CMOS compatible materials.

Dmitry Krotov, Benjamin Hoover, Parikshit Ram et al.

Associative Memories like the famous Hopfield Networks are elegant models for describing fully recurrent neural networks whose fundamental job is to store and retrieve information. In the past few years they experienced a surge of interest due to novel theoretical results pertaining to their information storage capabilities, and their relationship with SOTA AI architectures, such as Transformers and Diffusion Models. These connections open up possibilities for interpreting the computation of traditional AI networks through the theoretical lens of Associative Memories. Additionally, novel Lagrangian formulations of these networks make it possible to design powerful distributed models that learn useful representations and inform the design of novel architectures. This tutorial provides an approachable introduction to Associative Memories, emphasizing the modern language and methods used in this area of research, with practical hands-on mathematical derivations and coding notebooks.

Yongqiang Chen

In the past decades, machine learning with Empirical Risk Minimization (ERM) has demonstrated great capability in learning and exploiting the statistical patterns from data, or even surpassing humans. Despite the success, ERM avoids the modeling of causality the way of understanding and handling changes, which is fundamental to human intelligence. When deploying models beyond the training environment, distribution shifts are everywhere. For example, an autopilot system often needs to deal with new weather conditions that have not been seen during training, An Al-aided drug discovery system needs to predict the biochemical properties of molecules with respect to new viruses such as COVID-19. It renders the problem of Out-of-Distribution (OOD) generalization challenging to conventional machine learning. In this thesis, we investigate how to incorporate and realize the causality for broader tasks in modern machine learning. In particular, we exploit the invariance implied by the principle of independent causal mechanisms (ICM), that is, the causal mechanisms generating the effects from causes do not inform or influence each other. Therefore, the conditional distribution between the target variable given its causes is invariant under distribution shifts. With the causal invariance principle, we first instantiate it to graphs -- a general data structure ubiquitous in many real-world industry and scientific applications, such as financial networks and molecules. Then, we shall see how learning the causality benefits many of the desirable properties of modern machine learning, in terms of (i) OOD generalization capability; (ii) interpretability; and (iii) robustness to adversarial attacks. Realizing the causality in machine learning, on the other hand, raises a dilemma for optimization in conventional machine learning, as it often contradicts the objective of ERM...

Gregor Corbin

Version 3.0 of the Message-Passing Interface (MPI) standard, released in 2012, introduced a new set of language bindings for Fortran 2008. By making use of modern language features and the enhanced interoperability with C, there was finally a type safe and standard conforming method to call MPI from Fortran. This highly recommended use mpi_f08 language binding has since then been widely adopted among developers of modern Fortran applications. However, tool support for the F08 bindings is still lacking almost a decade later, forcing users to recede to the less safe and convenient interfaces. Full support for the F08 bindings was added to the performance measurement infrastructure Score-P by implementing MPI wrappers in Fortran. Wrappers cover the latest MPI standard version 4.1 in its entirety, matching the features of the C wrappers. By implementing the wrappers in modern Fortran, we can provide full support for MPI procedures passing attributes, info objects, or callbacks. The implementation is regularly tested under the MPICH test suite. The new F08 wrappers were already used by two fluid dynamics simulation codes -- Neko, a spectral finite-element code derived from Nek5000, and EPIC (Elliptical Parcel-In-Cell) -- to successfully generate performance measurements. In this work, we additionally present our design considerations and sketch out the implementation, discussing the challenges we faced in the process. The key component of the implementation is a code generator that produces approximately 50k lines of MPI wrapper code to be used by Score-P, relying on the Python pympistandard module to provide programmatic access to the extracted data from the MPI standard.