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This paper describes ASTER, a novel procedure for collecting Screen Time data from iOS, iPadOS, watchOS, and devices using their built-in Apple Screen Time features. Traditional methods of studying digital behavior often rely on self-reported data, which are prone to inaccuracies (i.e., recall bias), limiting their validity and granularity. While Android devices have long facilitated real-time and granular behavior tracking through third-party applications, similar tools are not available on Apple devices due to Apple's restrictions. This is problematic because there are significant differences between the user populations of iOS and Android. To address this gap, this study developed a data donation procedure that leverages the synchronization of screentime, enabling the extraction of comprehensive usage data of iPhones, iPads, Apple Watches, and Macs linked to the same Apple ID. The process involves donating system-level files used to generate Screen Time metrics on Mac, containing anonymized use data of all linked devices. We developed a tool that enables researchers to process these files into a usable dataset (e.g., JSON). This dataset provides granular insights into app usage without requiring substantial technical expertise or financial investment. While this approach enables the integration of Apple cross-device behavior into digital media research, it is limited to users with a Mac and can only capture data from the previous 4 weeks. Additionally, the method is vulnerable to changes in Apple's software structure, echoing the moving target problem. Nonetheless, this method marks an important step forward in current approaches to the passive sensing of smartphone behavior.

Low-level near-infrared light-induced transcranial photobiomodulation (NIR-TPBM) is a promising technology for improving cerebral blood flow and metabolism. However, the effects of NIR-TPBM on the visual pathway's function remain poorly understood. The aim was to assess the visual pathway's function changes in response to NIR-TPBM in young, healthy volunteers. This single-center, randomized, controlled clinical trial included 98 healthy volunteers with a median age of 23.2 years. Participants were randomly assigned to two groups: NIR-TPBM (18 men and 30 women) and sham NIR-TPBM (19 men and 31 women). Eye-tracking procedures were conducted in both groups before and after either PBM or sham intervention. In the NIR-TPBM group, low-fluence NIR-TPBM was applied to the left and right fronto-temporal regions using a NIR-TPBM device (Elmedlife H&#xae;, Nizhny Novgorod, Russian Federation). In the sham group, participants wore the NIR-TPBM helmet, but the NIR-TPBM mode remained deactivated. The duration of the sessions was identical for both groups. Changes in visual pathway function were evaluated by analyzing the dynamics of vertical and horizontal ocular vergence reactivity indices (VRx) using the EyeTracker application (BVG Software Group LLC, San Francisco, California, United States) on iPadOS 16 before and after the intervention. Statistical analysis was performed using nonparametric methods, with a significance level set at p < 0.05 . NIR-TPBM procedures led to a significant increase in both vertical and horizontal VRx values. Post-procedure vertical VRx was significantly higher than pre-procedure values (0.879 [0.761; 0.918] versus 0.774 [0.721; 0.929], p < 0.001 ). Similarly, horizontal VRx increased significantly after NIR-TPBM compared with baseline (0.943 [0.848; 0.969] versus 0.772 [0.651; 0.890], p < 0.001 ). No adverse effects were observed during or after the NIR-TPBM sessions. NIR-TPBM enhances visual pathways function by increasing both vergence reactivity indices in young healthy volunteers.

With increasingly large genomic datasets, even routine bioinformatic tasks can be arduous, computationally demanding, and time-consuming. Additionally, most bioinformatic programs do not have a graphical user interface (GUI) and thus, require users to be minimally competent in command-line. These impediments present significant economic and technological barriers for practitioners who do not have access to advanced computational resources and support. In this issue of Molecular Ecology Resources, Handika and Esselstyn (2024) developed an ultrafast and memory-efficient bioinformatic tool, SEGUL, that performs common manipulations and calculations of summary statistics on phylogenomic datasets. SEGUL has two main features that distinguish it from other bioinformatic programs: (1) it is based on the recently emergent, high-performance programming language Rust, and (2) it has a GUI written using Flutter, a cross-platform programming framework that also supports mobile operating systems (mobile iOS, iPadOS and Android). By leveraging and combining the power of Rust and Flutter, SEGUL achieves significantly faster computation times and lower memory usage across different platforms and CPU architectures compared to similar programs. The unique and innovative features of SEGUL pave the way for a new era of bioinformatics that can be more energy-efficient, inclusive, and available to a broader swathe of users.

Phylogenetic studies now routinely require manipulating and summarizing thousands of data files. For most of these tasks, currently available software requires considerable computing resources and substantial knowledge of command-line applications. We develop an ultrafast and memory-efficient software, SEGUL, that performs common phylogenomic dataset manipulations and calculates statistics summarizing essential data features. Our software is available as standalone command-line interface (CLI) and graphical user interface (GUI) applications, and as a library for Rust, R and Python, with possible support of other languages. The CLI and library versions run native on Windows, Linux and macOS, including Apple ARM Macs. The GUI version extends support to include mobile iOS, iPadOS and Android operating systems. SEGUL leverages the high performance of the Rust programming language to offer fast execution times and low memory footprints regardless of dataset size and platform choice. The inclusion of a GUI minimizes bioinformatics barriers to phylogenomics while SEGUL's efficiency reduces economic barriers by allowing analysis on inexpensive hardware. Our support for mobile operating systems further enables teaching phylogenomics where access to computing power is limited.

Teaching and learning chemical formulas and structures is challenging. In many cases students understand chemical formulas only at a superficial level and poorly comprehend and retain the underlying chemical processes. Teaching methods still follow historically evolved principles, which are briefly summarized in this article. Difficulties and misconceptions that students encounter are presented and discussed. Didactic principles are proposed to help overcome the main challenge of connecting learned concepts and models to chemical formulas. The macOS and iPadOS application MoleculeSketch for drawing chemical structures is presented.

Psychophysical tests are commonly carried out using software applications running on desktop or laptop computers, but running the software on mobile handheld devices such as smartphones or tablets could have advantages in some situations. Here, we present StimuliApp, an open-source application in which the user can create psychophysical tests on the iPad and the iPhone by means of a system of menus. A wide number of templates for creating stimuli are available including patches, gradients, gratings, checkerboards, random-dots, texts, tones or auditory noise. Images, videos and audios stored in files could also be presented. The application was developed natively for iPadOS and iOS using the low-level interface Metal for accessing the graphics processing unit, which results in high timing performance.

Introduction: For supervised deep learning (DL) tasks, researchers need a large annotated dataset. In medical data science, one of the major limitations to develop DL models is the lack of annotated examples in large quantity. This is most often due to the time and expertise required to annotate. We introduce Lirot. ai, a novel platform for facilitating and crowd-sourcing image segmentations. Methods: Lirot. ai is composed of three components; an iPadOS client application named Lirot. ai-app, a backend server named Lirot. ai-server and a python API name Lirot. ai-API. Lirot. ai-app was developed in Swift 5.6 and Lirot. ai-server is a firebase backend. Lirot. ai-API allows the management of the database. Lirot. ai-app can be installed on as many iPadOS devices as needed so that annotators may be able to perform their segmentation simultaneously and remotely. We incorporate Apple Pencil compatibility, making the segmentation faster, more accurate, and more intuitive for the expert than any other computer-based alternative. Results: We demonstrate the usage of Lirot. ai for the creation of a retinal fundus dataset with reference vasculature segmentations. Discussion and future work: W

With the popularity of mobile devices, mobile applications have become an essential part of people's lives. To provide secure mobile application download channels for users, various modern app markets are maintained by different companies. For example, Google maintains Google Play for Android users, while Apple maintains App Store for iOS, iPadOS, and MacOS users. Though app markets have come up with strict policies which impose restrictions on developers to avoid the potential harmful applications, we still have quite limited knowledge on the process of app vetting and the status of potential harmful apps. To fill this gap, this paper takes the initiative to conduct a large-scale and longitudinal study of removed apps in the iOS app store. Our analysis reveals that although most of the removed apps are low-quality apps, a number of them are quite popular. Furthermore, the mis-behaviors of these apps are reflected on app metadata, which makes it possible to distinguish potential harmful apps.

A stunning spiral galaxy called Messier 88 is racing through the crowded Virgo Cluster on a journey that will dramatically reshape its future。 At its heart lies a supermassive black hole about 100 million times the mass of the Sun, while its graceful spiral arms sparkle with young star clusters and dark clouds of dust。 But as M88 plunges deeper int

What if our biggest idea about reality is built on a hidden misunderstanding。 A new philosophical look at space-time challenges the popular view that the past, present, and future all exist together in a timeless "block universe。" The argument suggests that physicists may be blurring the difference between things that exist and things that merely o

Researchers have finally resolved a key problem in a 100-year-old theory of color, showing that the qualities we perceive in colors are intrinsic to the mathematics of color space itself。 The discovery sharpens our understanding of human vision and could lead to more precise color technologies and visualizations

Scientists have successfully tested an AI-designed universal coronavirus vaccine in humans for the first time, finding it to be safe and well tolerated。 The vaccine generated immune responses against multiple coronaviruses, including SARS-CoV-2, SARS, and related bat viruses with pandemic potential。 By targeting features shared across an entire vir

For more than a century, pianists and music teachers have argued over whether a performer’s touch can actually change the tone color of a piano note — and now scientists say the answer is yes。 Using a cutting-edge sensor system that tracked piano key movements at 1,000 frames per second, researchers discovered that elite pianists subtly manipulate

Researchers discovered a way to reverse the direction of energy flow in turbulence, challenging a theory that has stood for more than 80 years。 The finding could open new possibilities for controlling ocean currents, improving medical technologies, and enhancing climate forecasting

NASA's James Webb Space Telescope has uncovered unusual chemistry in interstellar comet 3I/ATLAS, including the first direct detection of methane on a visitor from another star system。 The comet also contains exceptionally high levels of carbon dioxide, making it unlike most comets born in our solar system。 Scientists believe the methane was hidden

Astronomers have finally cracked the mystery behind a strange class of repeating cosmic signals that has baffled scientists for years。 Using Australia’s ASKAP radio telescope, researchers traced the bursts to a rare stellar duo in which a dense white dwarf is relentlessly siphoning material from a nearby red dwarf companion。 As the stolen matter sp

By stacking custom-designed silver nanoparticles like nanoscale LEGO bricks, scientists stabilized a mysterious crystal phase that had never been observed before。 The material not only solves a longstanding puzzle in materials science but also exhibits promising quantum properties at room temperature