National Center for Science and Technology Evaluation

Soil microplastics (MPs) pollution is becoming more serious, and symbiotic microorganisms in soil-plant systems may influence the environmental behavior and related plant responses to MPs stress. In this study, common primary plastic products were broken down into MPs to investigate the toxic effects and migration behavior of MPs on lettuce (Lactuca sativa L.) in the presence of arbuscular mycorrhizal fungi (AMF). Our findings show that symbiotic AMF reduce the uptake and toxic effects of polyethylene terephthalate (PET) by increasing nucleotide metabolism and zeatin biosynthesis, resulting in a 20.64 % drop in PET uptake and an 11.43 % increase in lettuce biomass. In contrast, AMF promoted the absorption of polypropylene (PP) and polystyrene (PS) by lettuce, inhibiting ascorbate metabolism and lysine biosynthesis, and causing poorer lettuce growth. The positive regulatory effect of AMF on the nutritional quality and health status of plants under PET stress shows that AMF have the potential to alleviate the toxicity of MPs to lettuce in farmland and to remediate the MPs-related pollution in agricultural areas.

Human-centered wireless sensing has been significantly advanced by artificial intelligence (AI) technologies. To enhance AI model performance, signal preprocessing, as a fundamental procedure, is widely employed for improving signal quality. However, existing methods are time-consuming, labor-intensive, and exhibit limited generalization. To address this issue, we first investigate the frequency spectrum of various signals. The results demonstrate that, in human-centered wireless applications, human activities significantly affect the low-frequency components in the signal spectrum. Motivated by this observation, we propose Sense+, a concise and versatile signal preprocessing module that can be seamlessly integrated into existing models to enhance sensing performance. Specifically, we transform the raw signals into a unified frequency domain, apply a learnable filter to process their frequency spectra, and then convert them back to the original signal domain. To accurately extract low-frequency features, we further propose a low-pass weight initialization method for the filter. Extensive experiments are conducted across various sensing tasks and signal types, including IR-UWB signals for person identification, mmWave radar signals for gesture recognition, and Wi-Fi signals for action recognition. The results highlight the effectiveness of Sense+ in enabling preprocessing across diverse wireless signals. Specifically, when equipped with Sense+, the average accuracy improves by 21.84% compared to conventional preprocessing methods. Additionally, Sense+ accelerates convergence and exhibits consistent generalization across different neural network models.

Constructing a performance evaluation model for national international science and technology (S&T) cooperation programs helps comprehensively summarize program implementation outcomes and provides a scientific basis for government authorities and management agencies to improve program management. This study takes Intergovernmental International Science and Technology Innovation Cooperation Key Program as a case. Through the Delphi method, the indicator system and framework were optimized and screened, combined with the Analytic Hierarchy Process (AHP) to determine indicator weights. Ultimately, a performance evaluation model for international S&T cooperation programs was established and practically applied, offering theoretical guidance and practical references for decision-making by government authorities.

Abstract Cooperation in science and technology offers an important way in which countries can establish mutually beneficial, win–win partnerships. Science, Technology and Innovation (STI) has been a consistent and important component of China–Africa cooperation, and is playing an increasingly prominent role in South-South cooperation and the development of China–Africa relations. As China–Africa relations continue to develop, China–Africa STI cooperation has flourishing and borne fruit, providing strong impetus to both sides’ economic and social development, and there will be even more space for improvement in the future. This study is a systematic review of the progress, mechanisms and effectiveness of China–Africa STI cooperation, which summarizes its evolution into four stages and will help to improve the understanding of China–Africa STI cooperation and promote to more aspects and fields.

El propósito de este artículo es presentar una breve reseña sobre el estado de la evaluación docente en las universidades francesas. De acuerdo con este autor, la evaluación de la enseñanza universitaria arrojó un reflejo -que hoy en día puede estar mejor orientado desde un punto de vista sistémico- sobre la naturaleza institucional de la universidad. El documento finaliza con una evaluación pragmática del proceso de evaluación.Autores:André Staropoli. Comité National d'EvaluationDescriptores: calidad de la enseñanza enseñanza universitaria evaluación del profesor

a) | k ( w ) | ≥ 0 is a piecewise continuous and bounded function in R = ( - ∞ , ∞ ) . The coefficients b ( w ) and q ( w ) are continuous functions in R and can be unbounded at infinity. The operator L admits closure in the space L 2 ( Ω ) and the closure is also denoted by L. Taking into consideration certain constraints on the coefficients b ( w ) q ( w ) , apart from the above-mentioned conditions, the existence of a bounded inverse operator is proved in this paper; a condition guaranteeing compactness of the resolvent kernel is found; and we also obtained two-sided estimates for singular numbers ( s-numbers). Here we note that the estimate of singular numbers ( s-numbers) shows the rate of approximation of the resolvent of the operator L by linear finite-dimensional operators. It is given an example of how the obtained estimates for the s-numbers enable to identify the estimates for the eigenvalues of the operator L. We note that the above results are apparently obtained for the first time for a mixed-type operator in the case of an unbounded domain with rapidly oscillating and greatly growing coefficients at infinity.

ObjectiveWe aimed to explore factors affecting family health management during home quarantine as well as the effects of variations in family health management (FHM) on individuals’ health status.MethodsUsing stratified random sampling, 618 families in Wuhan as well as cities within its surrounding provinces were recruited and surveyed online. Latent class variables were extracted from four modules: disinfection, space layout, physical exercise, and food reserves. The analysis was conducted using the poLCA package in R software (v.4.1.0). Chi-squared tests, Fisher’s exact tests, and non-parametric Kruskal–Wallis tests were used to compare groups as appropriate.ResultsWe found an overall questionnaire reliability of 0.77 and a total omega of 0.92, indicating that the survey results were credible. The Bayesian information criterion and Akaike information criterion were used to identified four latent class variables, namely latent non-family health management (18.9%) and latent low, medium, and advanced FHM (30.93%, 29.49%, and 20.59%, respectively). Gender, household income level, body mass index, the presence of a nearby community hospital, and self-rated health status showed statistically significant differences with respect to latent FHM. Moreover, we found a statistically significant difference in emotional reactions when comparing latent advanced and low to mid-level latent FHM. Compared with latent non-family health managers, we detected statistically significant differences in individual energy levels between potential family health managers at latent low and medium levels. Additionally, we found statistically significant differences in individual energy levels between latent advanced and low level family health managers.ConclusionsWe found that multiple factors, including gender, household income, and body mass index, were correlated with latent FHM during home quarantine. We conclude that FHM can meaningfully improve individuals’ health. Thus, increasing social support for individuals can improve FHM as well as individuals’ health during home quarantine.