19 papers · ranked by Valyu relevance
Kristen M. Martinet, Brea Dace, Luke J. Harmon, Shaelyn Pearson + 4 more
The outcome of evolution sometimes appears to be predictable, as in the evolution of the same characteristics independently in convergent evolution. Other times, evolution’s path depends on starting conditions or chance events, and some forms evolve just once and never appear again. Is convergence, and by implication…
Innocent Sibanda, Geoff Nitschke
The goal of bioengineering in synthetic biology is to redesign, reprogram, and rewire biological systems for specific applications using standardized parts such as promoters and ribosomes. For example, bioengineered micro-organisms capable of cleaning up environmental pollution or producing antibodies de novo to defend…
Rong Zhou, Dongping Chen, Zihan Jia, Yao Su + 23 more
Rong Zhou 1 \* Dongping Chen 2 ∗ Zihan Jia 3 ∗ Yao Su 4 ∗ Yixin Liu 1 ∗ Yiwen Lu 5 ∗ Dongwei Shi 1 ∗ Yue Huang 6 ∗ Tianyang Xu 7 ∗ Yi Pan 8 Xinliang Li 8 Yohannes Abate 8 Qingyu Chen 9 Zhengzhong Tu 10 Yu Yang 1 Yu Zhang 11 Qingsong Wen 12 Gengchen Mai 13 Sunyang Fu 14 Jiachen Li 15 Xuyu Wang 16 Ziran Wang 17 Jing…
Tianyu Jiang, Yonghe Wang, Caiyu Wang, Zan Zhou
With the development of generative artificial intelligence (AI), human-computer interaction has shifted from a primarily instrumental function to a more human-like symbiotic relationship. However, current research on digital addiction (DA) remains limited to the compulsive consumption characteristic of the Web 2.0 era…
Haugen, Øystein, Klikovits, Stefan + 10 more
—The new SysMLv2 adds mechanisms for the built-in specification of domain-specific concepts and language extensions. This feature promises to facilitate the creation of Domain-Specific Languages (DSLs) and interfacing with existing system descriptions and technical designs. In this paper, we review these features and…
Kangbien Park
Humans have long employed directed evolution (DE) to engineer desired biological traits. In this paper, I introduce an algebraic framework that provides a quantitative representation of the general phenotypic traits of asexual populations, enabling the systematic modeling of DE processes. Within this framework, key…
Oleg Sobchuk, Mason Youngblood
In this paper, we chart an emerging academic terrain: cultural evolution of the arts, which is a theory-driven exploration of artistic dynamics, often done with large datasets of music, literature, movies, paintings, or games. This field has grown at the intersection of cultural evolution theory and several academic…
Sen Jia, Khai Wah Khaw, Yiqi Zhou
Purpose This study addresses the fragmented understanding of how digitalization shapes organizational capabilities by identifying and synthesizing the underlying mechanisms. Methods A mechanism-based systematic literature review was conducted on 116 core studies published in Q1 journals between 2015 and 2024. A…
Naveh Eskinazi, Moti Zwilling, Adilson Marques, Riki Tesler + 1 more
Background Advances in artificial intelligence (AI) have revolutionized digital wellness by providing innovative solutions for health, social connectivity, and overall well-being. Despite these advancements, the older population often struggles with barriers such as accessibility, digital literacy, and infrastructure…
Turgut Karaköse, Mehmet Ozdogru, Bünyamin Han, Tijen Tülübaş + 3 more
Introduction Digital addiction, the problematic or addictive use of digital devices and platforms such as the internet, smartphone, or social media, harms people, including their mental health. Rapid developments in digital technologies have increased research interest in this relationship in diverse fields of study…
Anne Richelle, David Andersson, Athanasios Antonakoudis, Jesper Jakobsson + 3 more
Digital twins of mammalian cell cultures hold great potential for predictive bioprocess modeling, yet their development is challenged by the nonlinear dynamics and metabolic complexity of these systems. We present a hybrid computational framework that integrates mechanistic and data-driven modeling to construct…
Iain G. Johnston
Evolutionary accumulation models (EvAMs) are an emerging class of machine learning methods designed to infer the evolutionary pathways by which features are acquired. Applications include cancer evolution (accumulation of mutations), anti-microbial resistance (accumulation of drug resistances), genome evolution…
Roman Lukyanenko, Ron Weber
As human reliance on information technology (IT) increases, having a clear, precise, and comprehensive understanding of the nature of digital objects, digital systems, and digitalized systems becomes more critical. Otherwise, our ability to research, manage, control, and make reliable predictions about them will be…
Authors not listed
Designing efficient photoreactors remains challenging due to the complex interplay of light transport phenomena, shaped by reflection, scattering and absorption processes. Here, we introduce a workflow that integrates ray-tracing digital twins with multi-objective Bayesian optimization to autonomously design…
Authors not listed
Finding the most stable adsorption geometry of a flexible molecule on a catalytic surface remains a key challenge due to the high dimensionality and ruggedness of the potential energy surface. We present a Gradient-Enhanced Genetic Algorithm (GE-GA) for the global optimization of adsorbate–surface configurations…
Mauricio González-Forero
Mathematically integrating genetics, development, and evolution is a longstanding challenge. Here I develop general mathematical theory that integrates sexual, discrete, multilocus genetics, development, and evolution. This yields an exact method to describe the evolutionary dynamics of allele frequencies and linkage…
Jakob Fernø, Michelle B. Verstraaten, Lila Gravellier, Ellen C. Røyrvik + 2 more
In this note we describe a method for comparing inferred dynamics in evolutionary accumulation models (EvAMs). These models involve the acquisition of multiple, potentially codependent, binary features over time -- for example, mutations in cancer development, or phenotypes in evolutionary biology. As the set of…
Authors not listed
Chemistry curricula often separate “wet” experimental work from “dry” computation, yet modern discovery increasingly demands both. This Perspective offers an instructor-ready roadmap to train “hybrid chemists” within existing courses. We distill recent advances in machine learning, automation, and real-time analytics…
Lena J. Skalaban, Ashley A. Murray, Jason M. Chein
Research on the relationship between digital media and neurocognitive function has blossomed with the rising digital age and advent of social media, producing a growing literature focused on how technological developments may be affecting users’ brains. Much of the science has focused on the involvement of specific…