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In this secondary analysis of a light-intensity physical activity intervention, we hypothesized that older cancer survivors would self-select a faster walking cadence to meet their daily step goals. Average steps/day and free-living walking cadence were measured in 41 participants (age 69 ± 3.1 years) with an ActivPAL monitor worn 7 days pre- and post-intervention. Besides peak and average walking cadence, stepping patterns associated with ambulatory intensity were sorted in cadence bands of 20 steps/min from 40–59 (incidental movement) to ≥120 steps/min (fast locomotor movement). Compared to the waitlist Control group (n = 17), the Intervention group (n = 24) increased their peak 30-min cadence (4.3 vs. 1.9 steps/minute; p = 0.03), average 10-min cadence (4.1 vs. −6.6 steps/minute; p = 0.04), and average 30-min cadence (5.7 vs. −0.8 steps/minute, p = 0.03). Steps taken in cadence bands denoting moderate-intensity physical activity (100–119 steps/min) increased by 478 (interquartile range (IQR): −121 to 1844) compared to decreasing by 92 (IQR: −510 to 181) steps/day for the intervention and Control groups, respectively (p < 0.01). Evaluation of free-living walking cadence and patterns of ambulatory behavior can inform future interventions targeting behavior change, especially in those populations most at risk for reduced physical activity and vulnerable to mobility deficits and loss of independence.

We explore a sequence of 13 unique high‐cadence images of a dust storm, from the Emirates Mars Mission (EMM). The Emirates eXploration Imager camera took these images in less than 8 hr on 18 December 2022 (Martian Year 36, solar longitude 356°). Most of these images are separated by a time difference of half an hour. The region of interest extends from Lyot crater to the east. During the morning, the EMM images show lee waves (atmospheric gravity waves). In the late morning, the lee waves rapidly change into clearly distinct dust storm texture/convective features. We track the evolution of both lee waves and a local dust storm between sunrise and mid‐afternoon. Also, we relate our observations to atmospheric dynamics. Our analysis is supported by the Mars Climate Database and radio occultation measurement data. Plain Language Summary The Emirates Mars Mission (EMM) has an on‐board camera, whose images from 18 December 2022 show a dust storm near Lyot crater (a large crater in the northern hemisphere of Mars). An image was taken almost every half an hour. In total, this gave 13 camera images in less than 8 hr. This number of images in such a short time is unique. The images reveal clouds which form straight lines during the morning. Such straight clouds are known as “lee wave clouds.” In the late morning, the lee waves disappear quickly and a quite different dust cloud appears. The latter is a dust storm which grows quickly. We follow the lee waves and dust storm from sunrise to mid‐afternoon. Also, we put our observations into the context of physical processes in the Mars atmosphere. Our work is supported by external data and measurements. That is to say data from the Mars Climate Database and radio occultation measurements. Key Points The Emirates Mars Mission provided thirteen (sub‐)hourly images; they show variations in clouds and atmospheric dust on 18 December 2022 The image sequence tracks the evolution of both lee waves and a local dust storm between sunrise and mid‐afternoon, near Lyot Crater We relate our observations to atmospheric dynamics, supported by the Mars Climate Database and radio occultation measurements

Many sixteenth-century contrapuntal works include prominent “plagal” cadences—phrase- and section-ending passages with bass descent by fourth or ascent by fifth. But these plagal cadences lack the characteristic melodic formulas that were essential for defining other cadences. Accordingly, sixteenth-century theorists mostly declined to describe them, and they remain problematic for contemporary analysts who have not reached consensus on the origins, purpose, or tonal focus of these cadences. This article presents new evidence from the vocal music of William Byrd and the theoretical writings of Thomas Morley of a nascent theory of plagality in late-sixteenth-century England. Morley’s extensive catalog of cadences—famously copied from Tigrini—includes a number of plagal cadences that were not found in his source. Instead, Morley’s supplementary plagal cadences reflect the variety of cadential structures in contemporary practice, as exemplified by the music of Byrd, Morley’s teacher. The article identifies three distinct uses of plagality in Byrd’s corpus: terminal plagal cadences, terminal cadences to the fifth degree, and phrase-bisecting cadences to the fifth degree.

This study explores the underlying mechanisms responsible for the perception of cadential closure in Mozart’s keyboard sonatas. Previous investigations into the experience of closure have typically relied upon the use of abstract harmonic formulæ as stimuli. However, these formulæ often misrepresent the ways in which composers articulate phrase endings in tonal music. This study, on the contrary, examines a wide variety of cadential types typically found in the classical style, including evaded cadences, which have yet to be examined in an experimental setting. The present findings reveal that cadential categories play a pivotal role in the perception of closure, and for musicians especially, ratings of the cadential categories provide empirical support for a model of cadential strength proposed in music theory. A number of rhetorical features also affect participants' ratings of closure, such as formal context, the presence of a melodic dissonance at the cadential arrival, and the use of a trill within the penultimate dominant. Finally, the results indicate that expertise modulates attention, with musicians privileging bass-line motion and nonmusicians attending primarily to the soprano voice.

The main goal of this research was to design and implement a simple power meter for cycling. The designed power meter had to be affordable, so we chose to use the crank arm solution. In order to achieve the objectives, we had to measure the tangential force applied on the crank arm using tensometric stamps. Also, we had to measure the cadence based on zero-crossing of the applied force, and to transmit data to external applications using Bluetooth Low Energy (BLE). The hardware implementation is based on BF350-3AA tensometric stamps, HX711 amplifier and Seeed XIAO nRF52840 Sense microcontroller, while the software implementation is based on the HX711_MP.h and bluefruit.h libraries. Experiments prove that the proposed solution (cost approx. 29€) meets the requirements. After calibration, our system achieved a deviation of ~10% compared to Tacx virtual power data, confirming its feasibility for amateur training applications.

Distinguishing between half cadences, elided authentic cadences, and similar endpoints can be a surprisingly challenging task. Particular problems arise when more than one way of labeling a phrase ending (or possible phrase ending) is syntactically proper, and when the formal divisions in such instances are obscured by conflicting harmonic, textural, or rhythmic features; this is especially so when an ending (or potential ending) is demarcated by a dominant harmony. Recognizing the flexibility of cadential status in these cases in turn has implications for larger issues of form, voice-leading structure, and the interaction of analysis and performance.

Background Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validate DMOs estimated using real-world gait data from six different cohorts, focusing on gait sequence detection, foot initial contact detection (ICD), cadence (CAD) and stride length (SL) estimates. Methods Twenty healthy older adults, 20 people with Parkinson’s disease, 20 with multiple sclerosis, 19 with proximal femoral fracture, 17 with chronic obstructive pulmonary disease and 12 with congestive heart failure were monitored for 2.5 h in the real-world, using a single wearable device worn on the lower back. A reference system combining inertial modules with distance sensors and pressure insoles was used for comparison of DMOs from the single wearable device. We assessed and validated three algorithms for gait sequence detection, four for ICD, three for CAD and four for SL by concurrently comparing their performances (e.g., accuracy, specificity, sensitivity, absolute and relative errors). Additionally, the effects of walking bout (WB) speed and duration on algorithm performance were investigated. Results We identified two cohort-specific top performing algorithms for gait sequence detection and CAD, and a single best for ICD and SL. Best gait sequence detection algorithms showed good performances (sensitivity > 0.73, positive predictive values > 0.75, specificity > 0.95, accuracy > 0.94). ICD and CAD algorithms presented excellent results, with sensitivity > 0.79, positive predictive values > 0.89 and relative errors < 11% for ICD and < 8.5% for CAD. The best identified SL algorithm showed lower performances than other DMOs (absolute error < 0.21 m). Lower performances across all DMOs were found for the cohort with most severe gait impairments (proximal femoral fracture). Algorithms’ performances were lower for short walking bouts; slower gait speeds (< 0.5 m/s) resulted in reduced performance of the CAD and SL algorithms. Conclusions Overall, the identified algorithms enabled a robust estimation of key DMOs. Our findings showed that the choice of algorithm for estimation of gait sequence detection and CAD should be cohort-specific (e.g., slow walkers and with gait impairments). Short walking bout length and slow walking speed worsened algorithms’ performances. Trial registration ISRCTN – 12246987.

Quasars are bright and unobscured active galactic nuclei (AGN) thought to be powered by the accretion of matter around supermassive black holes at the centers of galaxies. The temporal variability of a quasar’s brightness contains valuable information about its physical properties. The UV/optical variability is thought to be a stochastic process, often represented as a damped random walk described by a stochastic differential equation (SDE). Upcoming wide-field telescopes such as the Rubin Observatory Legacy Survey of Space and Time (LSST) are expected to observe tens of millions of AGN in multiple filters over a ten year period, so there is a need for efficient and automated modeling techniques that can handle the large volume of data. Latent SDEs are machine learning models well suited for modeling quasar variability, as they can explicitly capture the underlying stochastic dynamics. In this work, we adapt latent SDEs to jointly reconstruct multivariate quasar light curves and infer their physical properties such as the black hole mass, inclination angle, and temperature slope. Our model is trained on realistic simulations of LSST ten year quasar light curves, and we demonstrate its ability to reconstruct quasar light curves even in the presence of long seasonal gaps and irregular sampling across different bands, outperforming a multioutput Gaussian process regression baseline. Our method has the potential to provide a deeper understanding of the physical properties of quasars and is applicable to a wide range of other multivariate time series with missing data and irregular sampling.

The limiting temporal resolution of a time-domain survey in detecting transient behavior is set by the time between observations of the same sky area. We analyze the distribution of visit separations for a range of Vera C. Rubin Observatory cadence simulations. Simulations from families v1.5–v1.7.1 are strongly peaked at the 22 minute visit pair separation and provide effectively no constraint on temporal evolution within the night. This choice will necessarily prevent Rubin from discovering a wide range of astrophysical phenomena in time to trigger rapid follow-up. We present a science-agnostic metric to supplement detailed simulations of fast-evolving transients and variables and suggest potential approaches for improving the range of timescales explored.

Transistor-level Integrated Circuit (IC) design is fundamental to modern electronics, yet it remains one of the most expertise-intensive and time-consuming stages of chip development. As circuit complexity continues to rise, the need to automate this low-level design process has become critical to sustaining innovation and productivity across the semiconductor industry. This study presents a fully automated methodology for transistor-level IC design using a novel framework that integrates Grammatical Evolution (GE) with Cadence SKILL code. Beyond automation, the framework explicitly examines how symmetry and asymmetry shape the evolutionary search space and resulting circuit structures. To address the time-consuming and expertise-intensive nature of conventional integrated circuit design, the framework automates the synthesis of both digital and analogue circuits without requiring prior domain knowledge. A specialised attribute grammar (AG) evolves circuit topology and sizing, with performance assessed by a multi-objective fitness function. Symmetry is analysed at three levels: (i) domain-level structural dualities (e.g., NAND/NOR mirror topologies and PMOS/NMOS exchanges), (ii) objective-level symmetries created by logic threshold settings, and (iii) representational symmetries managed through grammatical constraints that preserve valid connectivity while avoiding redundant isomorphs. Validation was carried out on universal logic gates (NAND and NOR) at multiple logic thresholds, as well as on a temperature sensor. Under stricter thresholds, the evolved logic gates display emergent duality, converging to mirror-image transistor configurations; relaxed thresholds increase symmetric plateaus and slow convergence. The evolved logic gates achieve superior performance over conventional Complementary Metal–Oxide–Semiconductor (CMOS), Transmission Gate Logic (TGL), and Gate Diffusion Input (GDI) implementations, demonstrating lower power consumption, a reduced Power–Delay Product (PDP), and fewer transistors. Similarly, the evolved temperature sensor exhibits improved sensitivity, reduced power, and Integral Nonlinearity (INL), and a smaller area compared to the conventional Proportional to Absolute Temperature (PTAT) or “gold” circuit, without requiring resistors. The analogue design further demonstrates beneficial asymmetry in device roles, breaking canonical structures to achieve higher performance. Across all case studies, the evolved designs matched or outperformed their manually designed counterparts, demonstrating that this GE-based approach provides a scalable and effective path toward fully automated, symmetry-aware integrated circuit synthesis.