Autonomous University of Madrid

Purpose : To examine the effect of an activity wristband-based intermittent teaching unit (TU) combined with other behavior modification strategies in the physical education setting on high school students’ weekly steps. Method : Seventy-one high school students (49.3% girls) aged 12–16 years performed an 8-week intermittent TU (last 15 min of each session) twice a week. The TU consisted of the following strategies: activity wristband (24 hr), educational counseling, and progressive step goals, among others. Results : The students improved their weekly steps from Week 1 to Weeks 4–8 ( p ≤ .001; d = 0.45–0.58). There was a higher percentage of students who did at least an average of 10,000 steps per day at Week 8 compared with Week 1 ( p = .031; Cramer’s V = 0.246). Conclusion : The studied intermittent TU increased students’ weekly steps and the proportion of students who did at least an average of 10,000 steps per day.

Under the current global biodiversity crisis, there is a need for automated and noninvasive monitoring techniques that can gather large amounts of data cost-effectively at various ecological scales, from local to large spatial scales. These data can then be analyzed to inform stakeholders and decision-makers. One such technique is passive acoustic monitoring, which is commonly coupled with automatic identification of animal species based on their sound. Automated sound analyses usually require the training of sound detection and identification algorithms. These algorithms are based on annotated acoustic datasets which mark the occurrence of sounds of species inside sound recordings. However, compiling large annotated acoustic datasets is time-consuming and requires experts, and therefore, they normally cover reduced spatial, temporal, and taxonomic scales. This data paper presents WABAD, the World Annotated Bird Acoustic Dataset for passive acoustic monitoring. WABAD is designed to provide the public, the research community, and conservation managers with a novel and globally representative annotated acoustic dataset. This database includes 5047 min of audio files annotated to species-level by local experts with the start and end time and the upper and lower frequencies of each identified bird vocalization in the recordings. The database has a wide taxonomic and spatial coverage, including information on 91,931 vocalizations from 1192 bird species recorded at 72 recording sites in 29 recording locations (mainly countries) and distributed across 13 biomes. WABAD can be used, for example, for developing and/or validating automatic species detection algorithms, answering ecological questions, such as assessing geographical variations on bird vocalizations, or comparing acoustic diversity indices with species-based diversity indices. The dataset is published under a Creative Commons Attribution 4.0 International license that permits redistribution and reuse on the condition that the original work is properly credited.

The combination of superconductivity and magnetic textures leads to unconventional superconducting phenomena, including new correlated and topological phases. Van der Waals (vdW) materials emerge as a versatile platform for exploring the interplay between these two competing orders. Here, we report on individual / / Josephson junctions behaving as superconducting quantum interference devices (SQUIDs), which we attribute to the interplay between the superconductivity of and the spin texture of the vdW antiferromagnetic insulator . This behavior persists for in-plane magnetic fields of at least 6 T and is the result of interference between separated transport channels. Microscopic modeling of the antiferromagnet insulator/superconductor (AFI/S) interface reveals the formation of localized states at the edges of the junction that can lead to channels that dominate transport. Our findings highlight AFI/S heterostructures as a platform for engineering novel superconducting phenomena and establish a new route for lithography-free SQUIDs that operate in high magnetic fields.

A classical state-preparation device cannot generate states in relative superposition. We introduce classical models in which devices that are individually unable to generate states with relative superposition can be stochastically coordinated to simulate sets of quantum states. These models have natural operational interpretation in prepare-and-measure scenarios and they can account for many non-commuting quantum state sets. We develop systematic methods both for classically simulating quantum sets and for showing that no such simulation exists, thereby certifying quantum coherence. In particular, we determine the exact noise rates required to classically simulate the entire state space of quantum theory. We also reveal connections between the operational classicality of sets and the well-known fundamental concepts of joint measurability and Einstein-Podolsky-Rosen steering. Here, we present an avenue to understand how and to what extent quantum states defy generic models based on classical devices, which also has relevant implications for quantum information applications.

How internal forces are transduced into motion through soft, fluid membranes remains a fundamental question in the study of active systems. This is investigated using a minimal system: a ferromagnetic particle encapsulated inside a lipid vesicle with controlled membrane composition and phase behavior. A rotating magnetic field drives particle rotation, generating internal flow. This flow propels the particle along the inner membrane leaflet and induces local membrane slip, with regions closer to the particle exhibiting faster motion relative to the substrate. When the particle approaches the vesicle bottom, this slip produces a shear gradient across the lubrication gap, resulting in vesicle propulsion through a stick-slip cycle. Vesicle motion depends on membrane elasticity, excess area, and phase coexistence. Deformations and fluctuations dissipate stress, while line tension deflects the particle and reorients membrane structure. The results demonstrate how lipid membranes mediate force transduction and motion, offering new avenues for the bottom-up design of soft, membrane-based activesystems.

The complex between pyrazole and carbon dioxide has been generated in a supersonic jet and characterized using Fourier transform microwave spectroscopy and state of the art CCSD(T) theoretical calculations. The complex presents a planar configuration showing a simultaneous N⋯C=O n → π* tetrel bond and a NH⋯O hydrogen bond. The TS internal rotation barrier that interconverts the oxygen atoms of CO2 has been calculated to be 10 kJ mol-1 at the CCSD(T) level. The electronic characteristics of the minimum and TS have been analyzed. Machine learning methods have been applied to predict the potential energy surface of the pyrazole⋯carbon dioxide complex.

Inflammation is a biological phenomenon beneficial for homeostasis, but it is unfavorable if dysregulated. Although major progress has been made in characterizing inflammation in specific diseases, a global, holistic understanding is still elusive. This is particularly intriguing, considering its function for human health and the potential for modern medicine if fully deciphered. In this study, we leveraged advances in single-cell transcriptomics to delineate inflammatory processes of circulating immune cells during infection, immune-mediated inflammatory diseases and cancer. Our single-cell atlas of more than 6.5 million peripheral blood mononuclear cells from 1,047 patients (56% female, 43% male) and 19 diseases allowed us to learn a comprehensive model of inflammation in circulating immune cells. The atlas expands current knowledge of the biology of inflammation of immune-mediated diseases, acute and chronic inflammatory diseases, infections and solid tumors and lays the foundation to develop a disease classification framework using unsupervised as well as explainable machine learning. Beyond a disease-centered analysis, we charted altered activity of inflammatory molecules in peripheral blood cells, depicting discriminative inflammation-related genes to further understand mechanisms of inflammation. We present a rich resource for the community and lay the groundwork for learning a classifier for inflammatory diseases, presenting cells in circulation as living biomarkers.

Clodronate-loaded liposomes (CL liposomes) have been widely employed to deplete different macrophage subpopulations to assess their role in homeostatic, repair, regulatory, defense, autoimmune and inflammatory processes. Administration of CL liposomes, while promoting macrophage killing, can have long-term anti-inflammatory effects or cause inflammation in several mouse disease models. Therefore, the collateral effects of CL liposome treatment need to be explored when designing experiments involving macrophage depletion by CL liposomes. In this regard, the effect of a standard (high) versus low CL liposome dose on peritoneal macrophage kinetics and the structural integrity of the omentum has been investigated. High-dose clodronate treatment led to a long-lasting resMØ depletion but induced peritoneal inflammation and caused a severe and persistent omental milky spot disorganization, precluding drawing definitive conclusions on peritoneal resMØs function. In contrast, low-dose clodronate led to a transient depletion of resMØs but did not promote significant milky spot alterations or peritoneal inflammation, thus ensuring an efficient resMØ depletion in the absence of severe collateral effects, yet during a limited time window. These results have important implications for the design of experimental models aiming at addressing the role of peritoneal macrophages in peritoneal bacterial infection and tumor metastasis based on their depletion by CL liposomes.

Soil microorganisms constitute the largest portion of Earth's biodiversity. However, soil microorganisms are also highly sensitive to on-going global change, and the influence of an increasing number of stressors on common, rare, and unknown taxa across large environmental gradients remains virtually unknown. Here, we combined a large-scale spatial field survey across multiple different ecosystems and found that the diversity and abundance of soil rare taxa were significantly reduced under high environmental stressor number (i.e., a high number of stressors passing a 75% stressor threshold). Strikingly, the abundance of unknown soil taxa and unknown genes increased with increasing environmental stress number. We further identified the metagenome-assembled genomes (MAGs) that were considered as relatively common taxa using metagenomics. Compared to 9% of negative responders, 32% of common MAGs were resistant or positively responsive to multiple stress, displaying a reduced potential for cellular processes and an enhanced potential for environmental, genetic, and metabolic processes. Our study suggests that as stress increases, we would have less rare, but more unknown microorganisms and unique genomes of resistant common taxa, suggesting major changes in the soil microbiome in a world subjected to multiple global change stressors.