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A set-up for contactless transient photoconductivity measurements on powders by the Time Resolved Microwave Photoconductivity (TRMC) method has been realized. These measurements have been used as a tool for the investigation of excess charge-carrier lifetimes in TiO2 (anatase and rutile) powders. The influence of laser wavelength and intensity on TRMC decay shows the importance of the fast-recombination processes. The presence of a long time tail in the TRMC signals of the anatase modification of TiO2 is attributed to quenching of this recombination by hole-trapping at the surface. The influence of surface treatment by ethanol and water on TRMC decay evidences that dominant effects are bulk recombination in rutile and surface trapping in anatase. The influence of doping in rutile shows that increasing the doping rate accelerates the decay whatever the doping type is. The doping element acts as an impurity favoring recombination by creation of structural defects. The influence of thermal treatment in anatase shows that increasing the thermal treatment temperature increases the lifetimes. High crystalline quality leads to long charge-carrier lifetimes. The results are discussed in view of their relevance for photocatalysis.

In this study, scale interaction between synoptic eddies and low‐frequency flow is investigated. The synoptic eddy feedback is a key process in sustaining the low‐frequency flow. We show clear evidence using NCEP reanalysis data that there is a general underlying rule—the “left‐hand rule”, governing the synoptic eddy feedback onto low‐frequency flow. This rule states that eddy‐vorticity fluxes are directed preferentially about 90 degrees toward their left‐hand side, so that they converge into cyclonic flow and diverge from anticyclonic flow. Therefore, the eddy vorticity flux plays a positive role in reinforcing low‐frequency flow.

Fil: Chacoff, Natacha Paola. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo; Argentina

We dress atoms with multiple-radiofrequency (RF) fields and investigate the spectrum of transitions driven by an additional probe field. A complete theoretical description of this rich spectrum is presented, in which we find allowed transitions and determine their amplitudes using the resolvent formalism. Experimentally, we observe transitions up to sixth order in the probe field using RF spectroscopy of Bose-Einstein condensates trapped in single- and multiple-RF-dressed potentials. We find excellent agreement between theory and experiment, including the prediction and verification of previously unobserved transitions, even in the single-RF case.

Few-shot object detection (FSOD) in remote sensing images (RSIs) faces challenges such as data scarcity, difficulty in detecting small objects, and underutilization of frequency-domain information. Existing methods often rely on spatial-domain features, neglecting the complementary insights from low- and high-frequency characteristics. Additionally, their performance in detecting small objects is hindered by inadequate feature extraction in cluttered backgrounds. To tackle these problems, we propose a novel detection framework of Spatial-Frequency Interaction and Distribution Matching (SFIDM), which significantly enhances FSOD performance in RSIs. SFIDM focuses on rapid adaptation to target datasets and efficient fine-tuning with limited data. First, to improve feature representation, we introduce the Spatial-Frequency Interaction (SFI) module, which leverages the complementarity between low-frequency and high-frequency information. By decomposing input images into their frequency components, the SFI module extracts features critical for classification and precise localization, enabling the framework to capture fine details essential for detecting small objects. Secondly, to resolve the limitations of traditional label assignment strategies when dealing with small bounding boxes, we construct the Distribution Matching (DM) module, which models bounding boxes as 2D Gaussian distributions. This allows for the accurate detection of subtle offsets and overlapping or non-overlapping small objects. Moreover, to leverage the learned base-class information for improved performance on novel class detection, we employ a feature reweighting module, which adaptively fuses features extracted from the backbone network to generate representations better suited for downstream detection tasks. We conducted extensive experiments on two benchmark FSOD datasets to demonstrate the effectiveness and performance improvements achieved by the proposed SFIDM framework.

Background Among the social determinants of health, social interaction is considered a modifiable factor and an essential component of the global active ageing strategy. This study examined the associations of various types and frequencies of social interaction with health outcomes among older adults in China, while accounting for potential simultaneity and heterogeneity biases. Methods This study used data from the Chinese Health and Retirement Longitudinal Study (CHARLS), a five-wave Panel survey conducted in 2011, 2013, 2015, 2018, and 2020, comprising 38,420 observations from 7,864 individuals aged 60 years and above. Social interaction was categorised into three types: leisure-based individual interaction, community-based organisational interaction, and responsibility-driven caregiving interaction, to capture its diversity. Descriptive statistics were used to summarise health status and social interaction. Generalised estimating equation regression models were used to examine the associations between one- or two-wave-lagged social interaction and health outcomes (self-rated health, mental health, cognitive function, and diagnosed diseases). Random-effects estimation addressed individual-level heterogeneity. The 2SLS model was applied to assess potential bidirectional associations between interaction frequency and health, followed by endogeneity test. Results Social interaction was associated with more favourable health outcomes among older adults, particularly in the medium to long term. One-wave-lagged interaction was linked to better self-rated health (β = 0.014, P  < 0.05), lower mental distress (β=-0.232, P  < 0.05), and better cognitive function (β = 0.233, P  < 0.001), with no significant association with diagnosed disease. Leisure-based and community-based interactions corresponded to more favourable physical and mental health, whereas responsibility-driven interactions were associated with better cognition but also greater mental distress. Interaction frequency was positively associated with health, and was higher among those with better access to facilities and public transport. Living with children or a spouse, being employed and having a higher income tended to report more favourable health outcomes. Conclusion Active social interaction, regular participation in leisure activities, organized social activities, and informal social interactions are associated with more favourable health outcomes among older adults. Policies should prioritize supportive environments and age-friendly community renovations, while families and society should strengthen internal and external support systems to help foster active and healthy aging.

Recent studies of plant-animal mutualistic networks have assumed that interaction frequency between mutualists predicts species impacts (population-level effects), and that field estimates of interaction strength (per-interaction effects) are unnecessary. Although existing evidence supports this assumption for the effect of animals on plants, no studies have evaluated it for the reciprocal effect of plants on animals. We evaluate this assumption using data on the reproductive effects of pollinators on plants and the reciprocal reproductive effects of plants on pollinators. The magnitude of species impacts of plants on pollinators, the reciprocal impacts of pollinators on plants, and their asymmetry were well predicted by interaction frequency. However, interaction strength was a key determinant of the sign of species impacts. These results underscore the importance of quantifying interaction strength in studies of mutualistic networks. We also show that the distributions of interaction strengths and species impacts are highly skewed, with few strong and many weak interactions. This skewed distribution matches the pattern observed in food webs, suggesting that the community-wide organization of species interactions is fundamentally similar between mutualistic and antagonistic interactions. Our results have profound ecological implications, given the key role of interaction strength for community stability.

Introduction: Do more friends and more frequent interactions on social media result in more social support? The impact of variables such as interaction size and frequency on the social support individuals receive via social platforms has been studied from the perspective of social networks, and some studies have focused on the role of interaction topics from the perspective of private engagement. Little research has been done on the impact of affect control embedded in social networks. The emotion-first nature of social media and the rise of affect control theory mean that this perspective deserves attention. Methods: This study examined 634 WeChat users by means of an online survey on variables related to social media use, such as social network size, interaction frequency, users' evaluation of network members, and personal topic involvement, and then tested the influencing mode of these variables on people's perceived social support through chain mediation analysis using Model 80 of the process in spss. Results: (1) Interaction size influences perceived social support by affecting personal topic involvement; (2) Interaction frequency does not directly mediate the relationship between interaction size and perceived social support, but mediates the relationship in a chain by affecting personal topic involvement; and (3) Social network evaluation not only directly mediates the relationship between interaction size and perceived social support, but also further mediates the relationship by influencing personal topic involvement. Conclusion: The study confirmed the role of affective control in people's perceived social support through social network interactions. Those people talk about personal matters with individuals who have greater evaluation, potency, and activity in social networks are more likely to get perceived social support. The study draws our attention to the role of affection control in interpersonal relationships in the era of social media mediating people's daily interactions. Keywords: social media, social interaction, social support, interaction frequency, EPA

Numerical simulations were carried out for microwave thawing of 2‐D cylinders of pure materials with internal convection in the liquid regions. Enthalpy formulation of the energy balance equation was used with a superficial mushy region around the melting point. Electric field, energy and momentum balance equations were solved using the Galerkin finite‐element method with the penalty finite‐element formulation of the momentum balance equation. Microwave power absorption, temperature, and stream functions were studied for various cases. For samples of diameter D, thawing was contrasted between samples for 0.032 < D/Dp < 3.73 and 0.10 < D/λm < 1.58. These ratios were computed based on the liquid‐phase penetration depth Dp and wavelength of microwave radiation in the medium λm. In all cases, Pr = 0.5 was used and the Rayleigh number varied from 1.067 × 103 for the smallest diameter to 1.33416 × 105 for the largest sample (D = 2 cm). Thawing was contrasted for MWs being incident from the top and bottom faces of the cylinder and with the thawing dynamics in the absence of convection in the liquid. Our simulations indicate that convection plays a small role for D/Dp ≪ 1 and thawing is independent of the direction of MWs. At intermediate values of D/Dp where a strong maximum occurs in the power, the influence of convection with primary and secondary cell formation in the liquid regions was a strong function of the direction of incident microwaves. In the presence of multiple connected thawed regions convection was suppressed.

In recent years, knowledge graphs (KGs) have attracted considerable attention in recommendation research based on auxiliary information. The rich semantic knowledge in a KG can enrich user and item representations and provide more accurate recommendations. Unfortunately, most previous studies failed to incorporate user/item interaction frequency, which plays a critical role in analyzing users’ historical behaviors, into their recommendation models. Furthermore, the importance levels of users’ historical preference features and users’ KG preference features for modeling user preferences are different. Therefore, we propose an approach for jointly modeling the preferences of users and items with interaction frequency and attention (JMPIA), which first leverages an attention network with interaction frequency to obtain users’ and items’ historical preference representations and conducts preference propagation in a KG to obtain users’ KG preference representations for each hop. Then, we leverage an attention aggregator with the ReLU activation function to aggregate these representations to capture more accurate user preferences, thereby promoting recommendation. Finally, we conducted a comprehensive performance evaluation on two real-world datasets. The experimental results obtained on these two datasets demonstrate that the proposed JMPIA approach outperforms the state-of-the-art KG-based methods. These results validate the effectiveness of using an attention network with interaction frequency to derive preferences from users’ historical interaction information and combining them with the rich information in a KG to integrate user preferences.