Microplastic pollution is a significant global environmental issue, and impacts span from individual organisms to the entire ecosystems. This study investigated the properties of microplastics in amphibian larvae, shedding light on their environmental interactions and potential ecological consequences. We examined microplastics extracted from amphibian larvae of 10 taxa, sampled from sites experiencing different levels of human impact. Our findings revealed a predominance of blue microplastics and fibres, each comprising 53% of the total microplastics in amphibian larvae. Microplastic fibres were also notably longer than other morphological types of microplastics. Furthermore, we observed variations in the surface area of microplastics among different amphibian families. An interesting observation from our research is the apparent positive relationship between the size of amphibian larvae and the length of granular and flake-shaped microplastics. Conversely, we observed a negative relationship between the length of these microplastics and human environmental impact. These insights significantly contribute to the understanding of microplastic pollution in freshwater environments, highlighting its complexities beyond marine ecosystems. Our research emphasises the intricate relationships between microplastics and freshwater organisms, underscoring the need for comprehensive strategies to mitigate microplastic pollution.

Shadow, a natural phenomenon resulting from the absence of light, plays a pivotal role in agriculture, particularly in processes such as photosynthesis in plants. Despite the availability of generic shadow datasets, many suffer from annotation errors and lack detailed representations of agricultural shadows with possible human activity inside, excluding those derived from satellite or drone views. In this paper, we present an evaluation of a synthetically generated top-down shadow segmentation dataset characterized by photorealistic rendering and accurate shadow masks. We aim to determine its efficacy compared to real-world datasets and assess how factors such as annotation quality and image domain influence neural network model training. To establish a baseline, we trained numerous baseline architectures and subsequently explored transfer learning using various freely available shadow datasets. We further evaluated the out-of-domain performance compared to the training set of other shadow datasets. Our findings suggest that AgroSegNet demonstrates competitive performance and is effective for transfer learning, particularly in domains similar to agriculture.

The Qinghai-Tibet Plateau, located at the Third Pole and known as the \"Asian water tower,\" serves as a crucial ecological barrier for China. Grasping the soil quality on the Qinghai-Tibet Plateau holds paramount importance for the rational and scientific exploitation of soil resources within the region and is essential for vegetation restoration and ecological reconstruction. This study, conducted in Maqin County, Qinghai Province, collected 1647 soil samples (0-20 cm) within a study area of 6300 km2. Sixteen soil indicators were selected that were split into beneficial (N, P, S, and B), harmful (Cr, Hg, As, Pb, Ni, and Cd), and essential (Cu, Zn, Se, Ga, K, and Ca) elements. The Soil Quality Index (SQI) was computed to assess soil quality across diverse geological contexts, land cover classifications, and soil profiles. The results indicate that the overall SQI in the study area was comparatively high, with most regions having an SQI between 0.4 and 0.6, categorized as moderately to highly satisfactory. Among the different geological backgrounds, the highest SQI was found in the Quaternary alluvium (0.555) and the lowest in the Precambrian Jinshuikou Formation (0.481). Regarding different land-use types, the highest SQI was observed in glacier- and snow-covered areas (0.582) and the lowest in other types of grassland (0.461). The highest SQI was recorded in typical alpine meadow soil (0.521) and the lowest in leached brown soil (0.460). The evaluation results have significant reference value for the sustainable utilization and management of soil in Maqin County, Qinghai Province, China.

The widespread use of devices like mobile phones and wearables allows for automatic monitoring of human daily activities, generating vast datasets that offer insights into long-term human behavior. A structured and controlled data collection process is essential to unlock the full potential of this information. While wearable sensors for physical activity monitoring have gained significant traction in healthcare, sports science, and fitness applications, securing diverse and comprehensive datasets for research and algorithm development poses a notable challenge. In this proof-of-concept study, we underscore the significance of semantic representation in enhancing data interoperability and facilitating advanced analytics for physical activity sensor observations. Our approach focuses on enhancing the usability of physical activity datasets by employing a medical-grade (CE certified) sensor to generate synthetic datasets. Additionally, we provide insights into ethical considerations related to synthetic datasets. The study conducts a comparative analysis between real and synthetic activity datasets, assessing their effectiveness in mitigating model bias and promoting fairness in predictive analysis. We have created an ontology for semantically representing observations from physical activity sensors and conducted predictive analysis on data collected using MOX2-5 activity sensors. Until now, there has been a lack of publicly available datasets for physical activity collected with MOX2-5 activity monitoring medical grade (CE certified) device. The MOX2-5 captures and transmits high-resolution data, including activity intensity, weight-bearing, sedentary, standing, low, moderate, and vigorous physical activity, as well as steps per minute. Our dataset consists of physical activity data collected from 16 adults (Male: 12; Female: 4) over a period of 30-45 days (approximately 1.5 months), yielding a relatively small volume of 539 records. To address this limitation, we employ various synthetic data generation methods, such as Gaussian Capula (GC), Conditional Tabular General Adversarial Network (CTGAN), and Tabular General Adversarial Network (TABGAN), to augment the dataset with synthetic data. For both the authentic and synthetic datasets, we have developed a Multilayer Perceptron (MLP) classification model for accurately classifying daily physical activity levels. The findings underscore the effectiveness of semantic ontology in semantic search, knowledge representation, data integration, reasoning, and capturing meaningful relationships between data. The analysis supports the hypothesis that the efficiency of predictive models improves as the volume of additional synthetic training data increases. Ontology and Generative AI hold the potential to expedite advancements in behavioral monitoring research. The data presented, encompassing both real MOX2-5 and its synthetic counterpart, serves as a valuable resource for developing robust methods in activity type classification. Furthermore, it opens avenues for exploration into research directions related to synthetic data, including model efficiency, detection of generated data, and considerations regarding data privacy.

Change of land use have important impacts on ecosystem services (ESs) and human well-being (HWB), yet the trade-off/synergy among land use, ESs, and HWB has still not received sufficient attention at city regional scales level. Weinan City in the southern of the Loess Plateau of China was taken as the study area. Based on ArcGIS, InVEST model, and RUSLE model, the characteristics of spatial and temporal variations of land use and ESs from 2000 to 2020 were analyzed, and the trade-off/synergy relationship between land use, ESs, and HWB was quantified using correlation analysis. The results indicated that the area of cultivated land decreased significantly and the area of built-up land increased significantly from 2000 to 2020 in Weinan City. The grain production, soil conservation, and water yield functions showed an increasing trend, which was a synergistic relationship with HWB. Carbon storage and habitat quality functions showed a decreasing trend, which was a trade-off relationship with HWB. The index value of HWB has increased significantly, mainly in the added value of agricultural and rural per capita income. Land use intensity has a trade-off relationship with GP, WY functions, and HWB. There are many factors that affect this trade-off/synergy relationship, such as land use patterns, economic development, and population growth. The study can provide a theoretical basis for the sustainable development of regional economy and nature.

UNASSIGNED: The goals for staff in Supported Housing for people with psychiatric disabilities include helping to develop the residents\' independence and self-confidence in activities. However, staff have expressed frustration about providing this type of support when motivating residents to engage in meaningful activities and also about the difficulty in finding suitable levels of independence within a housing setting with limitations.
UNASSIGNED: The aim is to explore the views and experiences of housing staff in Supported Housing on how they can stimulate and support engagement in activities for people with psychiatric disabilities.
UNASSIGNED: Twenty-six members of staff from 20 supported housing units in 10 municipalities in Sweden were interviewed in five focus groups. A semi-structured interview guide was used, and the transcribed material was analyzed using qualitative content analysis.
UNASSIGNED: Three main categories emerged from the analysis: Multi-faceted factors influencing the staff\'s provision of activity support, Staff\'s approach for supporting activities, and Staff\'s struggles to develop their work. Obstacles to participating in activities in the community were identified. Many contrasting factors were found, such as spontaneous or structured activities and individual or group activities, which affected the staff\'s ability to motivate to activity.
UNASSIGNED: A broad approach encompassing in-house training including a focus on values, recruitment policies, staff supervision and interventions focusing on both residents and staff are ways to support staff in motivating residents toward being more active within Supported Housing.

OBJECTIVE: Self-perception of aging (SPA) and social functioning are two important variables in the process of healthy aging, but the relationship between them is still unclear. This study aimed to explore the association between SPA and social functioning in older adults.
METHODS: We conducted a longitudinal study utilizing data from the Health and Retirement Study. The sample comprised individuals aged 50 and above. Socio-demographic, psychosocial, and lifestyle information of study participants was systematically collected at baseline (2012 and 2014) and during follow-up four years later (2016 and 2018). SPA was measured using a scale assessing individuals\' attitudes toward their aging process. Social functioning was evaluated through 22 questions, reflecting individuals\' abilities to engage in and perform various roles and tasks in their daily lives. Multilevel modeling was employed to analyze the relationship between SPA and social functioning. Differences in social functioning changes among various SPA groups were assessed through the Generalized Estimating Equations methodology.
RESULTS: The study included 8,454 participants with an average age of 68.3 years (SD = 9.92). The multilevel model revealed a significant correlation between SPA and social functioning (β = 0.131; P < 0.001). This relationship persisted after adjusting the model (β = 0.088; P < 0.001). Generalized Estimating Equations indicated noteworthy differences in social functioning changes among distinct SPA groups (P = 0.034).
CONCLUSIONS: Positive SPA is associated with the healthy social functioning of older adults. Healthcare providers could target modifiable aspects of SPA to enhance the social function of older adults and promote successful aging.

Wetlands serve many functions, including conserving water, providing habitats for animals and plants, and regulating climate change. Their unique ecological effects on the natural environment are indispensable in the whole ecosystem. Dianchi Lake Basin is located in Yunnan-Guizhou Plateau, China, and mainly in Kunming. It is a typical plateau urban wetland area. Based on spatio-temporal hotspot mining, spatio-temporal geographically weighted regression, and adaptive multidimensional grey prediction, we conducted correlation analyses of the wetland changes in Dianchi Lake Basin from 1993 to 2020 under the influence of human activities and natural conditions. The results show that (1) the active wetland change zone in Dianchi Lake Basin is mainly located around Dianchi Lake, and (2) the wetlands in some areas on the north and south of Dianchi Lake declined in the early 21st century, but under the protection policy in recent years, the wetlands in these areas gradually recovered. Meanwhile, the wetlands in most areas around Dianchi Lake showed a significant growth trend from 2018 to 2020. The results suggest that the wetland change in Dianchi Lake Basin is mainly related to the urbanization of Kunming, and it can be divided into five regions (strong negative correlation, weak negative correlation, weak correlation, weak positive correlation, and strong positive correlation) according to the different correlation of human activity intensity, among which the main factors affected by nature are different, but they are all related to temperature. This study shows that, although wetlands in plateau cities can be properly restored under proper protection, wetland protection should be kept in step with the development of plateau cities to support sustainable urban development and carbon neutrality.

Sediment cores are optimal mediums for investigating the historical presence of offshore microplastics (MPs). In this study, two sediment cores were collected at varying water depths, i.e., XS2 (10 m) and XS3 (20 m), from the Xiangshan offshore (XSO) in Ningbo. We focused on the spatiotemporal distribution characteristics of MPs within two sediment cores and explored the response differences of MPs abundance to natural factors and human activities. The results showed that the MPs abundance in sediments has gradually increased since the late 1960s, but with interannual fluctuations. MPs abundance in XS2 and XS3 were 1133-8700 and 633-11433 items/kg dry weight, respectively. The predominant polymers were PA, PU, PET and ACR, with fragmented particles being the most prevalent shape of MPs. The MPs abundance in XS2 and XS3 had a similar response to natural factors, mainly including (i) MPs abundance significantly correlated with the sediment load of the Qiantang River (p < 0.01), indicating that sediment load might be an important factor affecting the MPs abundance and that MPs transported by rivers had characteristics of near-source sedimentation; (ii) typhoons had the effect of weakening the MPs abundance; and (iii) geological activities might be potential contributing factors to variations in MPs\' abundance in deep sediments. Correlation analyses demonstrated that MPs in XSO was the result of multiple sources, stemming from plastic production, sewage discharge, marine fisheries and shipping activities. Notably, XS3 exhibited higher sensitivity to human activities compared to XS2, owing to differences in sampling locations. This study underscores the significance of employing two sediment cores, rather than a single core, as it provides a more comprehensive insight into the overarching trends and disparities in the historical pollution of MPs. Our findings contribute to a deeper understanding of the history of offshore MPs pollution, shedding new light on this critical environmental issue.

Direct sewage discharge can cause severe damage to the water environment of the river. However, the impacts of dissolved organic matter (DOM) in the discharge on the original pattern of DOM and the distribution of heavy metals (HMs) in the river are little known. How to monitor such areas in a long-term and systematic manner also needs to be urgently addressed. In this paper, we characterized the DOM of the sediments in the WWTPs (wastewater treatment plants)-river integrated zone by ultraviolet-visible absorption spectroscopy (UV-vis), three-dimensional excitation-emission matrix (3D-EEM) combined with parallel factor (PARAFAC) method. The effects of WWTP on receiving waters were investigated, and the potential link between DOM and HM pollution was explored. Hg (Igeo: 3.94 ± 0.65; EF: 44.83 ± 31.11), Cd (Igeo: 1.81 ± 0.69; EF: 8.02 ± 2.97), Cu (Igeo: 1.61 ± 0.83; EF: 6.85 ± 2.37), Zn (Igeo: 1.55 ± 0.54; EF: 7.24 ± 3.58), and Ni (Igeo: 1.46 ± 0.56; EF: 6.12 ± 1.99) in rivers were the primary risk sources of HM. The combined pollution risk indicates that the WWTPs-river integrated area is in a high pollution risk state. Moreover, α(254) has a significant correlation with pollution indicators and can be used as a proxy indicator. These results help to understand better the impact of WWTPs on receiving water bodies and the potential connection between DOM and HM pollution and provide new ideas for monitoring the water environment in highly polluted areas.