Record 10072026 · captured 2026-08-25
The world looked up Bonnie Tyler. 30 tracked subjects, 25 discussions, 25 papers. This record is frozen and will not change.
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What the most people looked up, ranked by Wikipedia pageviews for that day.
Gaynor Sullivan, known professionally as Bonnie Tyler, was a Welsh singer. Known for her distinctive husky voice, she came to prominence with the release of her debut studio album The World Starts Tonight (1977) and its singles "Lost in France" and "More Than
Erling Braut Haaland is a Norwegian professional footballer who plays as a striker for Premier League club Manchester City and the Norway national team. Regarded as one of the best players in the world and the greatest Norwegian player of all time, he is known
Kylian Mbappé Lottin is a French professional footballer who plays as a forward for La Liga club Real Madrid and captains the France national team. Widely regarded as one of the best players in the world and one of the greatest French players of all time, he i
On August 9, 2025, Schlep, a Roblox-focused YouTuber known for conducting sting operations against sexual predators, was permanently banned from Roblox due to his alleged violations of terms of service. Roblox Corporation sent him a cease and desist letter, th
The 2026 FIFA World Cup was the 23rd FIFA World Cup, the quadrennial international men's soccer championship contested by the national teams of the member associations of FIFA. The tournament began on June 11, 2026, and concluded on July 19 with Spain winning
Count Binface is a novelty candidate persona adopted by the British writer and comedian Jon Harvey to contest British elections. Binface is presented as an "intergalactic space warrior" who wears a dustbin-shaped helmet.
.xyz is a top-level domain name that was proposed in ICANN's new generic top-level domain (gTLD) Program for consisting of the last three letters of the Latin-script alphabet. XYZ.com and CentralNic are the registries for the domain, which was created by entre
Arthur Fery is a British professional tennis player. He has a career-high ATP singles ranking of world No. 36 achieved on 13 July 2026 and a doubles ranking of No. 201 achieved on 29 July 2024. His breakthrough came at the 2026 Wimbledon Championships, reachin
Graham Cunningham Platner is an American oyster farmer, Marine Corps veteran, and politician. Platner was the Democratic nominee in the 2026 US Senate election in Maine until he ended his campaign in July.
The Odyssey is a 2026 epic action fantasy film written and directed by Christopher Nolan, who produced it with his wife Emma Thomas. An adaptation of Homer's ancient Greek epic poem the Odyssey, it stars an ensemble cast including Matt Damon, Tom Holland, Anne
John Robert Sullivan is a British former judoka. He competed in the men's half-middleweight event at the 1972 Summer Olympics. In 1973 he married Welsh singer Bonnie Tyler.
Morocco, officially the Kingdom of Morocco, is a country in the Maghreb region of North Africa. It has coastlines on the Mediterranean Sea to the north and the Atlantic Ocean to the west, and has land borders with Algeria to the east; the Spanish exclaves of C
Karolína Muchová is a Czech professional tennis player. She has a career-high singles ranking of world No. 6 by the WTA, achieved in July 2026, and a best doubles ranking of No. 156, reached in January 2026. Muchová has won three WTA Tour singles titles, inclu
Yassine Bounou, also known mononymously as Bono, is a Moroccan professional footballer who plays as a goalkeeper for Saudi Pro League club Al Hilal and the Morocco national team.
The FIFA World Cup is an international association football competition among the senior men's national teams of the members of the Fédération Internationale de Football Association (FIFA), the sport's global governing body. The tournament has been held every
Cristiano Ronaldo dos Santos Aveiro is a Portuguese professional footballer who plays as a forward for and captains the Saudi Pro League club Al-Nassr and the Portugal national team. Nicknamed CR7, he is widely regarded as one of the greatest players in histor
Addison Mitchell McConnell III is an American politician and attorney who has been a United States senator from Kentucky since 1985 and has been Kentucky's senior U.S. senator since 1999. A member of the Republican Party, McConnell is in his seventh Senate ter
Lionel Andrés "Leo" Messi is an Argentine professional footballer who plays as a forward for and captains both Major League Soccer (MLS) club Inter Miami and the Argentina national team. Widely regarded as one of the greatest players in history, Messi has set
The following notable deaths occurred in 2026. Names are reported under the date of death, in alphabetical order. A typical entry reports information in the following sequence:Name, age, country of citizenship at birth, subsequent nationality, what subject was
Michael Akpovie Olise is a professional footballer who plays as a winger or attacking midfielder for Bundesliga club Bayern Munich and the France national team. Widely regarded as one of the best players in the world, he is known for his creative playmaking, t
Obsession is a 2025 American supernatural horror film written, directed, and edited by Curry Barker. The film follows Bear, a music store employee who buys a supernatural toy that grants his wish for his friend Nikki to fall in love with him, which makes her b
Achraf Hakimi Mouh is a professional footballer who plays as a right-back for Ligue 1 club Paris Saint-Germain and captains the Morocco national team. Known for his attacking prowess and strong defensive contribution, he is widely regarded as one of the best r
Masour Ousmane Dembélé is a French professional footballer who plays as a forward and right winger for Ligue 1 club Paris Saint-Germain and the France national team. Regarded as one of the best players in the world, he is one of eleven players to have won the
Giovanni Vincenzo "Gianni" Infantino is a Swiss football administrator who has served as the president of FIFA since 2016. He was previously Secretary General of UEFA from 2009 to 2016, where he formalised the body's financial regulations and oversaw tournamen
The FIFA World Cup is an international association football competition contested by the senior men's national teams of the Fédération Internationale de Football Association (FIFA), the sport's global governing body. The championship has been awarded every fou
Cori Dionne "Coco" Gauff is an American professional tennis player. She has a career-high ranking of world No. 2 in singles and of world No. 1 in doubles by the WTA. Gauff has won twelve career singles titles, including two majors at the 2023 US Open and 2025
Morocco national football team
The Morocco national football team has represented Morocco in men's international football since their first international match in 1957. It is controlled by the Royal Moroccan Football Federation (FRMF), the governing body for football in Morocco. It has been
List of FIFA World Cup top goalscorers
Players have scored more than 3,000 goals in the 23 men's FIFA World Cup tournaments, the goal record includes own goals scored, but not counting penalty shoot-outs. Since the first goal, by French player Lucien Laurent in 1930, nearly 1,300 footballers have s
A by-election for the United Kingdom parliamentary constituency of Clacton was held on 13 August 2026, following the resignation of Nigel Farage, its member of Parliament. Farage, who is the leader of Reform UK, had represented Clacton since the 2024 general e
Evil Dead Burn is a 2026 American supernatural horror film written and directed by Sébastien Vaniček, who co-wrote it with Florent Bernard, and produced by Rob Tapert and series creator Sam Raimi. It serves as a sequel to Evil Dead Rise (2023) and is the sixth
What the people building things argued about, from Hacker News.
Papers submitted to arXiv cs.AI that day.
A smartphone application to measure the quality of pest control spraying machines via image analysis
The need for higher agricultural productivity has demanded the intensive use of pesticides. However, their correct use depends on assessment methods that can accurately predict how well the pesticides' spraying covered the intended crop region. Some methods have been proposed in the literature, but their high cost and low portability harm their widespread use. This paper proposes and experimentally evaluates a ne
Pay Attention to Evolution: Time Series Forecasting with Deep Graph-Evolution Learning
Time-series forecasting is one of the most active research topics in artificial intelligence. Applications in real-world time series should consider two factors for achieving reliable predictions: modeling dynamic dependencies among multiple variables and adjusting the model's intrinsic hyperparameters. A still open gap in that literature is that statistical and ensemble learning approaches systematically present
DropLeaf: a precision farming smartphone application for measuring pesticide spraying methods
Pesticide application has been heavily used in the cultivation of major crops, contributing to the increase of crop production over the past decades. However, their appropriate use and calibration of machines rely upon evaluation methodologies that can precisely estimate how well the pesticides' spraying covered the crops. A few strategies have been proposed in former works, yet their elevated costs and low porta
This paper derives the generalized extreme value (GEV) model with implicit availability/perception (IAP) of alternatives and proposes a variational autoencoder (VAE) approach for choice set generation and implicit perception of alternatives. Specifically, the cross-nested logit (CNL) model with IAP is derived as an example of IAP-GEV models. The VAE approach is adapted to model the choice set generation process, in w
Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution Priors
A key challenge of real-world image super-resolution (SR) is to recover the missing details in low-resolution (LR) images with complex unknown degradations (e.g., downsampling, noise and compression). Most previous works restore such missing details in the image space. To cope with the high diversity of natural images, they either rely on the unstable GANs that are difficult to train and prone to artifacts, or resort
The oceans are a source of an impressive mixture of complex data that could be used to uncover relationships yet to be discovered. Such data comes from the oceans and their surface, such as Automatic Identification System (AIS) messages used for tracking vessels' trajectories. AIS messages are transmitted over radio or satellite at ideally periodic time intervals but vary irregularly over time. As such, this pape
Accurate Portraits of Scientific Resources and Knowledge Service Components
With the advent of the cloud computing era, the cost of creating, capturing, and managing information has gradually decreased. The amount of data on the Internet is showing explosive growth, and more scientific and technological resources are being uploaded to the network. Different from news and social media data, scientific and technological resources are mainly composed of academic-style resources or entities, suc
In recent years, with the continuous progress of science and technology, the number of scientific research achievements has increased rapidly. As an exchange platform and medium for scientific research achievements, scientific and technological academic conferences have become increasingly abundant. The convening of academic conferences brings large numbers of papers, researchers, institutions, projects, and research
Retrieval of Scientific and Technological Resources for Experts and Scholars
Institutions of higher learning, research institutes and other scientific research units have abundant scientific and technological resources of experts and scholars, and these talents with great scientific and technological innovation ability are an important force to promote industrial upgrading. The scientific and technological resources of experts and scholars are mainly composed of basic attributes and scientifi
Graphs have often been used to answer questions about the interaction between real-world entities by taking advantage of their capacity to represent complex topologies. Complex networks are known to be graphs that capture such non-trivial topologies; they are able to represent human phenomena such as epidemic processes, the dynamics of populations, and the urbanization of cities. The investigation of complex networks
Computation, Condensation, and the Incompleteness Between Them: A Coupled Foundation of Intelligence
The theory of computation was built to answer Turing's question: what is effectively calculable by an unbounded, immortal, disembodied agent following rules? Intelligence answers a different question (nature's): what can a \emph{finite}, mortal, energy-limited agent do quickly enough to survive in a non-stationary world? We argue that a complete answer requires two operators: \emph{computation} and \emph{memo
Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents
We introduce \emph{Calibrated Stackelberg Games (CSGs)}, a generalization of the standard Stackelberg Games (SGs) framework. In CSGs, a principal repeatedly interacts with an agent who (contrary to standard SGs) does not have direct access to the principal's action but instead best-responds to calibrated forecasts about it. This framework provides a powerful and realistic modeling tool that goes beyond assuming t
The storage, management, and application of massive spatio-temporal data are widely used in practical scenarios, including public safety. However, due to the unique spatio-temporal distribution characteristics of real-world data, existing methods still face limitations in preserving spatio-temporal proximity and achieving load balancing in distributed storage. This paper proposes an efficient partitioning method for
Machine Learning for maximizing the memristivity of single and coupled quantum memristors
We propose machine learning (ML) methods to characterize the memristive properties of single and coupled quantum memristors. We show that maximizing the memristivity leads to large values in the degree of entanglement of two quantum memristors, unveiling the close relationship between quantum correlations and memory. Our results strengthen the possibility of using quantum memristors as key components of neuromorphic
This paper presents a method to efficiently classify the gastroenterologic section of images derived from Video Capsule Endoscopy (VCE) studies by exploring the combination of a Convolutional Neural Network (CNN) for classification with the time-series analysis properties of a Hidden Markov Model (HMM). It is demonstrated that successive time-series analysis identifies and corrects errors in the CNN output. Our appro
This paper addresses the challenge of boosting the precision of multi-path long-term vessel trajectory forecasting on engineered sequences of Automatic Identification System (AIS) data using feature fusion for problem shifting. We have developed a deep auto-encoder model and a phased framework approach to predict the next 12 hours of vessel trajectories using 1 to 3 hours of AIS data as input. To this end, we fuse th
Because most scientific literature data are unlabeled, semantic representation learning based on unsupervised graphs has become crucial. To enrich scientific-literature features, this paper proposes a semantic representation learning method based on adaptive features and graph neural networks. By introducing adaptive feature processing, scientific-literature features are considered globally and locally. The graph att
Statistical inverse learning problems with random observations
We provide an overview of recent progress in statistical inverse problems with random experimental design, covering both linear and nonlinear inverse problems. Different regularization schemes have been studied to produce robust and stable solutions. We discuss recent results in spectral regularization methods and regularization by projection, exploring both approaches within the context of Hilbert scales and present
Enhancing Global Maritime Traffic Network Forecasting with Gravity-Inspired Deep Learning Models
Aquatic non-indigenous species (NIS) pose significant threats to biodiversity, disrupting ecosystems and inflicting substantial economic damages across agriculture, forestry, and fisheries. Due to the fast growth of global trade and transportation networks, NIS has been introduced and spread unintentionally in new environments. This study develops a new physics-informed model to forecast maritime shipping traffic bet
Conformal Predictive Programming for Chance Constrained Optimization
We propose conformal predictive programming (CPP), a framework to solve chance constrained optimization problems, i.e., optimization problems with constraints that are functions of random variables. CPP utilizes samples from these random variables along with the quantile lemma - central to conformal prediction - to transform the chance constrained optimization problem into a deterministic problem with a quantile refo
XOV-Action: Towards Generalizable Open-Vocabulary Action Recognition
Inspired by the impressive success of image-text foundation models, recent works have proposed to adapt these foundation models to video data, leading to efficient and effective video models for open-vocabulary action recognition. However, through a comprehensive evaluation, our work finds that state-of-the-art open-vocabulary action recognition models still struggle with generalization to video domains that they hav
Seaports play a crucial role in the global economy, and researchers have sought to understand their significance through various studies. In this paper, we aim to explore the common characteristics shared by important ports by analyzing the network of connections formed by vessel movement among them. To accomplish this task, we adopt a bottom-up network construction approach that combines three years' worth of AI
Data Alchemy: Mitigating Cross-Site Model Variability Through Test Time Data Calibration
Deploying deep learning-based imaging tools across various clinical sites poses significant challenges due to inherent domain shifts and regulatory hurdles associated with site-specific fine-tuning. For histopathology, stain normalization techniques can mitigate discrepancies, but they often fall short of eliminating inter-site variations. Therefore, we present Data Alchemy, an explainable stain normalization method
The Contribution of XAI for the Safe Development and Certification of AI: An Expert-Based Analysis
Developing and certifying safe - or so-called trustworthy - AI has become an increasingly salient issue, especially in light of upcoming regulation such as the EU AI Act. In this context, the black-box nature of machine learning models limits the use of conventional avenues of approach towards certifying complex technical systems. As a potential solution, methods to give insights into this black-box - devised in the
Joint Bayesian Parameter and Model Order Estimation for Low-Rank Probability Mass Tensors
Obtaining a reliable estimate of the joint probability mass function (PMF) of a set of random variables from observed data is a significant objective in statistical signal processing and machine learning. Modelling the joint PMF as a tensor that admits a low-rank canonical polyadic decomposition (CPD) has enabled the development of efficient PMF estimation algorithms. However, these algorithms require the rank (model
Notable events recorded on this day and month across all years.