Global land surface temperature influenced by vegetation cover and PM2.5 from 2001 to 2016

Land surface temperature (LST) is an important parameter to evaluate environmental changes. In this paper, time series analysis was conducted to estimate the interannual variations in global LST from 2001 to 2016 based on moderate resolution imaging spectroradiometer (MODIS) LST, and normalized difference vegetation index (NDVI) products and fine particulate matter (PM2.5) data from the Atmospheric Composition Analysis Group. The results showed that LST, seasonally integrated normalized difference vegetation index (SINDVI), and PM2.5 increased by 0.17 K, 0.04, and 1.02 �g/m3 in the period of 2001–2016, respectively. During the past 16 years, LST showed an increasing trend in most areas, with two peaks of 1.58 K and 1.85 K at 72�N and 48�S, respectively. Marked warming also appeared in the Arctic. On the contrary, remarkable decrease in LST occurred in Antarctic. In most parts of the world, LST was affected by the variation in vegetation cover and air pollutant, which can be detected by the satellite. In the Northern Hemisphere, positive relations between SINDVI and LST were found; however, in the Southern Hemisphere, negative correlations were detected. The impact of PM2.5 on LST was more complex. On the whole, LST increased with a small increase in PM2.5 concentrations but decreased with a marked increase in PM2.5. The study provides insights on the complex relationship between vegetation cover, air pollution, and land surface temperature

Hierarchical accompanying and inhibiting patterns on the spatial arrangement of taxis' local hotspots

Due to the large volume of recording, the complete spontaneity, and the flexible pick-up and drop-off locations, taxi data portrays a realistic and detailed picture of urban space use to a certain extent. The spatial arrangement of pick-up and drop-off hotspots reflects the organizational space, which has received attention in urban structure studies. Previous studies mainly explore the hotspots at a large scale by visual analysis or some simple indexes, where the hotspots usually cover the entire central business district, train stations, or dense residential areas, reaching a radius of hundreds or even thousands of meters. However, the spatial arrangement patterns of small-scale hotspots, reflecting the specific popular pick-up and drop-off locations, have not received much attention. Using two taxi trajectory datasets in Wuhan and Beijing, China, this study quantitatively explores the spatial arrangement of fine-grained pick-up and drop-off local hotspots with different levels of popularity, where the sizes are adaptively set as 90m*90m in Wuhan and 105m*105m in Beijing according to the local hotspot identification method. Results show that popular hotspots tend to be surrounded by less popular hotspots, but the existence of less popular hotspots is inhibited in regions with a large number of popular hotspots. We use the terms hierarchical accompany and inhibiting patterns for these two spatial configurations. Finally, to uncover the underlying mechanism, a KNN-based model is proposed to reproduce the spatial distribution of other less popular hotspots according to the most popular ones. These findings help decision-makers construct reasonable urban minimum units for precise traffic and disease control, as well as plan a more humane spatial arrangement of points of interest

Honey bee maternal effects improve worker performance and reproductive ability in offspring

Maternal effects are an evolutionary strategy used to improve offspring quality. In an example of maternal effects in honey bees (Apis mellifera), mother queens produce larger eggs in queen cells than in worker cells in order to breed better daughter queens. In our current study, morphological indexes, reproductive tissues, and the egg-laying ability of newly reared queens reared with eggs laid in queen cells (QE), eggs laid in worker cells (WE), and 2-day-old larvae in worker cells (2L) were evaluated. In addition, morphological indexes of offspring queens and working performance of offspring workers were examined. The thorax weight, number of ovarioles, egg length, and number of laid eggs and capped broods of QE were significantly higher than those of WE and 2L, indicating that the reproductive capacity of QE group was better than that of other groups. Furthermore, offspring queens from QE had larger thorax weights and sizes than those from the other two groups. Offspring worker bees from QE also had larger body sizes and greater pollen-collecting and royal jelly-producing abilities than those of other two groups. These results demonstrate that honey bees display profound maternal effects on queen quality that can be transmitted across generations. These findings provide a basis for improving queen quality, with implications in apicultural and agricultural production

The impact of digital literacy on learning outcomes among college students: the mediating effect of digital atmosphere, self-efficacy for digital technology and digital learning

Few studies have explored the specific internal mechanisms and links by which digital literacy impacts learning outcomes. This study investigates the complex relationship between digital literacy and learning outcomes among college students, using social cognitive theory (SCT) and structural equation modeling (SEM) as theoretical frameworks. Data were collected from 589 college students in China’s northwest region. The results reveal that digital literacy affected learning outcomes indirectly through the digital atmosphere, self-efficacy for digital technology, and digital learning. Specifically, digital atmosphere and digital learning mediate the relationship between digital literacy and learning outcomes. Self-efficacy for digital technology and digital learning jointly mediate the relationship between digital literacy and learning outcomes. Digital literacy has a positive and significant impact on the digital atmosphere and influences students’ self-efficacy for digital technology, thereby motivating them to participate in digital learning and ultimately having a positive impact on learning outcomes. Overall, the findings highlight the importance of developing digital literacy, optimizing digital learning atmospheres, and enhancing self-efficacy to fully leverage undergraduates’ learning potential in the digital age

Modelling seasonal household variation in harvested rainwater availability:a case study in Siaya County, Kenya

Rainwater harvesting reliability, the proportion of days annually when rainwater demand is fully met, is challenging to estimate from cross-sectional household surveys that underpin international monitoring. This study investigated the use of a modelling approach that integrates household surveys with gridded precipitation data to evaluate rainwater harvesting reliability, using two local-scale household surveys in rural Siaya County, Kenya as an illustrative case study. We interviewed 234 households, administering a standard questionnaire that also identified the source of household stored drinking water. Logistic mixed effects models estimated stored rainwater availability from household and climatological variables, with random effects accounting for unobserved heterogeneity. Household rainwater availability was significantly associated with seasonality, storage capacity, and access to alternative improved water sources. Most households (95.1%) that consumed rainwater faced insufficient supply of rainwater available for potable needs throughout the year, with intermittencies during the short rains for most households with alternative improved sources. Although not significant, stored rainwater lasts longer for households whose only improved water source was rainwater (301.8 ± 40.2 days) compared to those having multiple improved sources (144.4 ± 63.7 days). Such modelling analysis could enable rainwater harvesting reliability estimation, and thereby national/international monitoring and targeted follow-up fieldwork to support rainwater harvesting

Nanospheres as the delivery vehicle: novel application of Toxoplasma gondii ribosomal protein S2 in PLGA and chitosan nanospheres against acute toxoplasmosis

Toxoplasma gondii (T. gondii) is a zoonotic disease that poses great harm to humans and animals. So far, no effective T. gondii vaccine has been developed to provide fully protection against such parasites. Recently, numerous researches have focused on the use of poly-lactic-co-glycolic acid (PLGA) and chitosan (CS) for the vaccines against T. gondii infections. In this study, we employed PLGA and CS as the vehicles for T. gondii ribosome protein (TgRPS2) delivery. TgRPS2-PLGA and TgRPS2-CS nanospheres were synthesized by double emulsion solvent evaporation and ionic gelation technique as the nano vaccines. Before immunization in animals, the release efficacy and toxicity of the synthesized nanospheres were evaluated in vitro. Then, ICR mice were immunized intramuscularly, and immune protections of the synthesized nanospheres were assessed. The results showed that TgRPS2-PLGA and TgRPS2-CS nanospheres could induce higher levels of IgG and cytokines, activate dendritic cells, and promote the expression of histocompatibility complexes. The splenic lymphocyte proliferation and the enhancement in the proportion of CD4+ and CD8+ T lymphocytes were also observed in immunized animals. In addition, two types of nanospheres could significantly inhabit the replications of T. gondii in cardiac muscles and spleen tissues. All these obtained results in this study demonstrated that the TgRPS2 protein delivered by PLGA or CS nanospheres provided satisfactory immunoprotective effects in resisting T. gondii, and such formulations illustrated potential as prospective preventive agents for toxoplasmosis

Percolation transition of k-frequent destinations network for urban mobility

Urban spatial interactions are a complex aggregation of routine visits and random explorations by individuals. The inherent uncertainty of these random visitations poses significant challenges to understanding urban structures and socioeconomic developments. To capture the core dynamics of urban interaction networks, we analyze the percolation structure of the $k$-most frequented destinations of intracity place-to-place flows from mobile phone data of eight major U.S. cities at a Census Block Group (CBG) level. Our study reveals a consistent percolation transition at $k^* = 130$, a critical threshold for the number of frequently visited destinations necessary to maintain a cohesive urban network. This percolation threshold proves remarkably consistent across diverse urban configurations, sizes, and geographical settings over a 48-month study period, and can largely be interpreted as the joint effect of the emergence of hubness and the level of mixing of residents. Furthermore, we examine the socioeconomic profiles of residents from different origin areas categorized by the fulfillment level of $k^*=130$ principal destinations, revealing a pronounced distinction in the origins' socioeconomic advantages. These insights offer a nuanced understanding of how urban spaces are interconnected and the determinants of travel behavior. Our findings contribute to a deeper comprehension of the structural dynamics that govern urban spatial interactions

Emerging trends and research hotspots in atopic dermatitis-related itch over the past 10 years: a bibliometric and visual analysis

IntroductionAtopic dermatitis (AD) is a chronic inflammatory skin disorder that causes itching. While numerous studies on AD-related itch exist, a bibliometric analysis has not been performed on this topic. The study aimed to investigate research trends and hotspots in the field of AD-related itch over the last decade.MethodsWe retrieved publications relevant to AD-related itch published from 2014 to 2023, within the Science Citation Index-Expanded of Web of Science Core Collection. We conducted a bibliometric and visual analysis involving annual publications, nations, institutions, journals, authors, co-citation references, and keywords by utilizing VOSviewer, CiteSpace, and the bibliometric online analysis platform.Results and discussionA total of 2534 articles and reviews were retrieved. Overall, the number of publications on AD-related itch has risen steadily over the past decade. The USA was found to be the most influential nation. Simpson et al. were found to be the most prolific author. Over the past 10 years, research has primarily revolved around barrier function, itching mechanism, sensory neurons, and therapeutic drugs for AD. The mechanisms of AD-related itch and advanced drugs are the current research trends. This study can serve as a foundation for further research

Analysis of anisotropy anomalies identification in apparent resistivity observation

Since 1966, China has been using apparent resistivity observation to forecast strong aftershocks of the Xingtai earthquake. Retrospective studies of subsequent strong earthquakes have shown that anomalies in apparent resistivity observation before earthquakes usually exhibit anisotropic characteristics. In addition to the anisotropic changes in apparent resistivity before earthquakes, factors such as subway operation near the observation area, metal pipeline networks, and changes in water levels have also been found to cause anisotropic changes. These factors are called environmental interference factors. Therefore, distinguishing between anisotropic changes before earthquakes and anisotropic changes caused by interference and eliminating the effects of interference is crucial for using apparent resistivity observations for forecasting. Taking the observation of Hefei seismic station in Anhui Province as an example, a model is constructed using the finite element method to try to establish a method for analyzing anisotropy in apparent resistivity before earthquakes, and the data from other provincial stations are used for verification. In the modeling process, the influence coefficient is a measure of the relationship between the variation in apparent resistivity and the changes in the medium of the measurement area. The following results are obtained by calculating the influence coefficient using the finite element method: the influence coefficient between the power supply electrode and the measuring electrode of the apparent resistivity observation is negative, and the rest are positive, and the distribution of the influence coefficient shows obvious symmetry, with the axis of symmetry being the line connecting the electrodes and its midline, and the absolute value of the influence coefficient is inversely proportional to the distance from the electrodes. In addition, according to the constructed finite element model, the amplitude of anisotropic changes caused by interference can be quantitatively calculated. Given that interference is ubiquitous in various regions of the world, this study can provide a reference for international earthquake forecasters to quantitatively remove environmental interference in anisotropy. Moreover, when building apparent resistivity stations in seismic areas for earthquake prediction, it is best to avoid areas with larger local influence coefficients to ensure that the anomalous data before the earthquake is true and reliable