Article
Psychology, Multidisciplinary
Przemyslaw Tomalski, David Lopez Perez, Alicja Radkowska, Anna Malinowska-Korczak
Summary: The study found that infants produce more complex patterns of fixations, including longer fixation sequences, when observing social scenes, especially in static social scenes. These developmental changes seem to be related to infants' visual scanning skills.
FRONTIERS IN PSYCHOLOGY
(2021)
Article
Geography, Physical
Antonio Molina-Almansa, Mercedes Conde-Valverde, Ana Isabel Ortega, Rebeca Garcia-Gonzalez, Laura Rodriguez, Alfonso Alday, Eneko Iriarte, Salvador Domingo, Juan Luis Arsuaga, Jose Maria Bermudez de Castro, Eudald Carbonell, Jose Miguel Carretero, Ignacio Martinez
Summary: This study presents new datings and a new anthropological study of Early Neolithic human remains found in Galeria del Silex in 1979. The fossils from this cave are among the oldest Neolithic human remains in the interior of the Iberian Peninsula. The findings suggest that Galeria del Silex may have been a burial ground during the Early Neolithic period.
QUATERNARY SCIENCE REVIEWS
(2023)
Article
Urban Studies
Stefano Cozzolino, Stefano Moroni
Summary: This article provides an exploratory lens for interpreting and assessing the propensity of urban areas to rely on self-adaptive processes of change, taking into account the impact of planning rules and property ownership patterns. It highlights the importance of these structural-institutional aspects in defining the degree of self-adaptability of urban areas.
Article
Environmental Studies
Ian Carter, Stefano Moroni
Summary: Individual choice is the foundation of adaptability, and the analysis of adaptability and anti-adaptability should consider the combination of individual freedoms and normative powers. Adaptability is seen in a positive light and helps explain the common features of 'anti-adaptive' neighbourhoods.
ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE
(2022)
Article
Engineering, Electrical & Electronic
Ying-Ren Chien, Sheng-Teng Wu, Hen-Wai Tsao, Paulo S. R. Diniz
Summary: This paper presents a novel correntropy-based data selection method, which mitigates the impact of noise by maximizing the instantaneous correntropy function. In simulations, the proposed method outperforms other error-based data selection schemes.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2023)
Article
Mathematics, Interdisciplinary Applications
Chao Zhang
Summary: This paper discusses the conflicts between reductionism and complexity theory in language research and proposes an adaptive weight model as a unified interpretation approach.
Article
Computer Science, Artificial Intelligence
Rohit Salgotra, Urvinder Singh, Sriparna Saha, Amir H. Gandomi
Summary: Cuckoo search (CS) algorithm is efficient in problem-solving, but its performance degrades with increasing complexity. A new version named self-adaptive CS (SACS) has been proposed to improve performance by employing adaptive parameters and other enhancements. Comparative evaluations show that SACS outperforms several algorithms while maintaining comparability with others, validating its effectiveness.
SWARM AND EVOLUTIONARY COMPUTATION
(2021)
Article
Multidisciplinary Sciences
Thomas F. Varley, Olaf Sporns, Stefan Schaffelhofer, Hansjoerg Scherberger, Benjamin Dann
Summary: The study found that information processing was high within all areas during all cognitive and behavioral states, but there was significant variability in interareal processing. The researchers also discovered that the fine-scale network structure reconfigured at the neuron level in response to different grasping conditions, despite no differences in the overall amount of information present. These findings suggest that the brain dynamically forms higher-order processing units according to the cognitive or behavioral demand and that the information-processing network is hierarchically organized at the neuron level.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
Article
Computer Science, Artificial Intelligence
Xiaowei Zhao, Feiping Nie, Weizhong Yu, Xuelong Li
Summary: Neighborhood reconstruction is a hot topic in data analysis for capturing local manifold information of data. Existing methods have the drawback of separating reconstruction weights learning and feature extraction, impacting learning performance due to noisy and redundant features. To solve this, a Fast and Adaptive Neighborhood Reconstruction (FANR) model is proposed, which expresses each sample with representative points from the same class. By using a bipartite graph instead of a fully connected graph, the time complexity is reduced and heterogeneous samples' adverse impact is avoided. Experimental results demonstrate the efficiency and superiority of the proposed model.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Chemistry, Multidisciplinary
Li-Bo Huang, Arthur Hardiagon, Istvan Kocsis, Cristina-Alexandra Jegu, Mihai Deleanu, Arnaud Gilles, Arie van der Lee, Fabio Sterpone, Marc Baaden, Mihail Barboiu
Summary: This study presents a new type of artificial water channels capable of self-assembling into hydrophilic channels with high water permeability, with the adaptiveness playing a crucial role in channel efficiency. By modulating the head group type and concentration, control over water transport permeability can be achieved.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2021)
Article
Multidisciplinary Sciences
Evan Kiefl, Ozcan C. Esen, Samuel E. Miller, Kourtney L. Kroll, Amy D. Willis, Michael S. Rappe, Tao Pan, A. Murat Eren
Summary: Comprehensive sampling of natural genetic diversity with metagenomics enables highly resolved insights into the interplay between ecology and evolution. Analyzing genetic variation in the context of predicted protein structures reveals a tight association between genetic variation and protein structure. This approach provides insights into the governing principles of evolution and enables structure-aware investigations of microbial population genetics.
Article
Multidisciplinary Sciences
Xiaofei Kuang, Lingyi Meng, Can-Zhong Lu
Summary: The interactive and responsive materials mentioned in the text are capable of adapting to their environment autonomously. Photochromic materials, specifically those using electron-rich N,N-dimethylacetamide (DMA) and electron-deficient naphthalenediimide (NDI), demonstrate dynamic photochromic responses in both solution and crystalline aggregated states, making them promising for use in optoelectronic devices.
Article
Automation & Control Systems
Keke Huang, Yiming Wu, Cheng Long, Hongquan Ji, Bei Sun, Xiaofang Chen, Chunhua Yang
Summary: The study introduces an online dictionary learning method that outperforms traditional methods by adapting to time-varying processes, having lower computational complexity, and more reliably resolving issues in principal component analysis.
Article
Computer Science, Artificial Intelligence
Jinyang Guo, Dong Xu, Guo Lu
Summary: In this paper, a new deep image compression framework called CBANet is proposed, aiming to learn a single network that supports variable bitrate coding under various computational complexity levels. Unlike existing state-of-the-art learning-based image compression frameworks, our CBANet considers the complex rate-distortion-complexity trade-off, introducing a new network design strategy to achieve complexity and bitrate adaptive image compression. Comprehensive experiments demonstrate the effectiveness of CBANet for deep image compression. Code is released at https://github.com/JinyangGuo/CBANet-release.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2023)
Article
Green & Sustainable Science & Technology
Ru Guo, Yunyang Li, Li Shang, Cuiyang Feng, Xin Wang
Summary: Agriculture is heavily impacted by climate change, particularly in developing countries where farmers are both key players in adaptation and highly vulnerable. This study used a binary logistic regression model to examine local farmers' perceptions and behaviors towards climate change, finding that factors such as agricultural training, perceived temperature change, and education level significantly influence adaptive behavior. Key measures to enhance local climate adaptation include tailored training programs and improvement of scientific research.
JOURNAL OF CLEANER PRODUCTION
(2021)