Microplastics and nanoplastics have become emerging particulate anthropogenic pollutants and rapidly turned into a field of growing scientific and public interest. These tiny plastic particles are found in the environment all around the globe as well as in drinking water and food, raising concerns about their impacts on the environment and human health. To adequately address these issues, reliable information on the ambient concentrations of microplastics and nanoplastics is needed. However, micro- and nanoplastic particles are extremely complex and diverse in terms of their size, shape, density, polymer type, surface properties, etc. While the particle concentrations in different media can vary by up to 10 orders of magnitude, analysis of such complex samples may resemble searching for a needle in a haystack. This highlights the critical importance of appropriate methods for the chemical identification, quantification, and characterization of microplastics and nanoplastics. The present article reviews advanced methods for the representative mass-based and particle-based analysis of microplastics, with a focus on the sensitivity and lower-size limit for detection. The advantages and limitations of the methods, and their complementarity for the comprehensive characterization of microplastics are discussed. A special attention is paid to the approaches for reliable analysis of nanoplastics. Finally, an outlook for establishing harmonized and standardized methods to analyze these challenging contaminants is presented, and perspectives within and beyond this research field are discussed.
The contamination of urban soils can affect the health of people living in urban areas, and the surrounding ecosystems. Urbanization in China has taken place at an unprecedented pace in the last three decades. This paper provides an overview of studies on the quality of urban soils in China with special reference to trace metal contamination. It summarizes the characteristics of accumulation, spatial and temporal distribution, and major sources of various toxic or potentially toxic trace metals in urban soils as reported in recent literature. Levels of pollution in urban soil and road dust were discussed using the concentrations, enrichment factors, pollution indexes, and chemical fractionation of trace metals in major cities of China, and compared with other countries. In future studies, more pollutants in urban environments need to be included in multi-compartmental environmental surveillance for potential risk assessments. In addition to routine urban soil surveys by a harmonized methodology, a comprehensive assessment of soil quality is needed for the control and management of many urban brownfield sites. Taking into consideration pathways of exposure and site characteristics, risk assessment frameworks for major pollutants in urban soils, which integrate land use type and environmental availability, may be developed in the future.
Context: As part of vocational education and training, learning factories are a new, hands-on learning setting in which students can create products with realistic digital manufacturing equipment while still in vocational school. Given their novelty, learning factories have not yet been studied with respect to whether special classroom management may be needed. One key aspect of classroom management for teachers is the dealing with classroom disruptions. The aim of this study is to investigate what types of classroom disruptions occur in learning factories and how teachers deal with them.
Methods: To close the existing research gap, a guideline-based, semi-structured interview study with seven teachers from the federal state of Baden-Württemberg, Germany, was conducted. The interviews were analyzed with a qualitative content analysis using the software MAXQDA.
Findings: The findings show that in this new setting, established strategies for mitigating classroom disruptions can be adapted and applied. Teachers were found to use and optimize their existing abilities to ensure learning success and were able to protect the monetary value of the factory against certain disruptions. Mutual trust between teachers and students, as well as teachers utilizing strategies according to their personality, were mentioned as the most important factors in ensuring success in this context.
Conclusion: Learning factories as a new learning environment in vocational schools do not seem to require specific classroom management approaches. As a result, their use can be safely expanded. Teachers value the possibility of teaching in this special setting while seeing that there are new possible ways of disruptions. Nevertheless, the interviewees feel themselves prepared for these new challenges, using their already established repertoire of strategies, adapting them, if necessary, to this new setting. To do this, teachers need to systemize and understand disruptions inside their classrooms. So far, research is lacking systemizations for classroom disruptions in digital settings like learning factories. This study extends the research landscape with an adaption of an already existing construct.
Shyam Sudhakar Gomte, T. Agnihotri, Shivani Khopade
et al.
Abstract The pH-sensitive polymers have attained significant attention in the arena of targeted drug delivery (TDD) because of their exceptional capability to respond to alteration in pH in various physiological environments. This attribute aids pH-sensitive polymers to act as smart carriers for therapeutic agents, transporting them precisely to target locations while curtailing the release of drugs in off-targeted sites, thereby diminishing side effects. Many pH-responsive polymers in TDD have revealed promising results, with increased therapeutic efficacy and decreased toxic effects. Several pH-sensitive polymers, including, hydroxy-propyl-methyl cellulose, poly (methacrylic acid) (Eudragit series), poly (acrylic acid), and chitosan, have been broadly studied for their myriad applications in the management of various types of diseases. Additionally, the amalgamation of pH-sensitive polymers with, additive manufacturing techniques like 3D printing, has resulted in the progression of novel drug delivery systems that regulate drug release in a controlled manner. Herein, types of pH-sensitive polymers in TDD are systemically reviewed. We have briefly discussed the nanocarriers employed for the delivery of various pH-sensitive polymers in TDD. Finally, miscellaneous applications of pH-sensitive polymers are discussed thoroughly with special attention to the implication of 3D printing in pH-sensitive polymers. Graphical Abstract
Purpose – In 2002, Pakistan made a notable advancement toward inclusive education by approving the national policy for people with disabilities (Durrani et al., 2017). This policy, advised by the Ministry of Women’s Development, Social Work, and Special Education, aimed to integrate students with special needs into mainstream schools, emphasizing the significance of inclusive learning environments (Ashfaq and Rana, 2015). Despite these efforts, the practical application of this policy in high schools has encountered numerous obstacles. Effective integration of students with special needs requires more than just policy implementation; it demands effective educational practices. Teachers are crucial in this process as they are the primary facilitators of learning and significantly influence these students’ academic and social adaptation. Administrative support is essential in fostering an environment conducive to including and adapting students with special needs. This study aims to investigate these dynamics in high schools, focusing on the role of teacher interactions and administrative frameworks in supporting or hindering the adaptation process for students with special needs. Understanding these relationships is crucial for identifying gaps, challenges and opportunities within the current educational system, thereby contributing to the development of more effective strategies for inclusive education in Pakistan. Design/methodology/approach – This study used a correlational research strategy to investigate the effects of administrative and teacher support on the adaptation capabilities of high school students with special needs. The correlational design was chosen to explore the relationships between different types of support and students’ adaptation capabilities without manipulating any variables (Seeram, 2019). The study involved 230 participants, comprising 170 educators and 60 support staff. Stratified random sampling ensured that the sample represented various school types and experience levels (Sharma et al., 2017). This sampling method helps provide a more accurate and comprehensive understanding of the population under study. The demographic characteristics of the sample are summarized in Table 1. Participants were categorized based on sex, level of education, age and experience level to ensure a comprehensive understanding of the sample’s diversity. Findings – This study reveals that teacher and administrative support significantly impact students’ adaptation capabilities. Teacher support emerged as a strong predictor (ß = 0.502, p < 0.001), highlighting its crucial role in enhancing students’ adaptability. Administrative support also showed a positive and significant effect (ß = 0.211, p < 0.001), and its interaction with teacher support (ß = 0.102, p < 0.001) suggests that administrative support amplifies the positive effects of teacher support. These findings underscore the importance of a holistic support system within schools. While teachers provide direct instructional support and foster an inclusive learning environment, administrative support ensures teachers have the necessary resources and institutional backing to support students effectively (Carter et al., 2022). The interaction between these forms of support suggests that administrative efforts to support teachers can significantly enhance the overall adaptation capabilities of students (Gibbs, 2023b). Research limitations/implications – Several limitations should be considered when interpreting the findings of this study. First, the data were collected using self-reported questionnaires, which may be subject to biases such as social desirability or recall bias. Second, the study’s cross-sectional design limits the ability to establish causality between the variables. Longitudinal studies would be beneficial in exploring the causal relationships between teacher and administrative support and students’ adaptation capabilities. In addition, the study was conducted within a specific context and population, which may limit the generalizability of the findings to other settings. Future research should aim to replicate this study in different educational contexts to validate and extend the findings. Practical implications – The practical implications of these findings are significant. Schools should prioritize developing comprehensive support systems that include robust teacher support mechanisms and strong administrative backing. Professional development programs should focus on enhancing teachers’ skills in differentiated instruction, formative assessment and the use of technology in the classroom. Moreover, administrative policies should aim to provide continuous support for teachers through resources, training and collaborative opportunities. This dual approach ensures that teachers are well-equipped to address the diverse needs of students with special needs and that students receive consistent, high-quality support across their educational experience. Originality/value – This study uniquely explores the combined effects of administrative and teacher support on the adaptation of high school students with special needs in mainstream education, highlighting the synergistic relationship between these support systems. Using a robust correlational design and stratified random sampling, it provides valuable insights into the dynamics of inclusive education within a Pakistani context. The findings emphasize the critical role of holistic support systems, offering practical implications for enhancing educational policies and practices. By addressing gaps in existing research, this study contributes significantly to the discourse on inclusive education and the development of effective support frameworks for special needs students.
Kaisa Vainio, Aino Korrensalo, Tuomo Takala
et al.
Abstract Trees are natural objects that carry practical, cultural and spiritual meanings to humans. Trees are an elemental part of human daily life, both in urban and rural environments, and even in locations where forests are distant. Conflicts related to tree removal in the close environments of humans indicate that individual trees may have special significance. Despite that, we have little knowledge of the ways these relationships are formed and the meanings they carry. To examine how the properties of trees and humans influence the type of relationships that are formed between them, we conducted a large‐scale survey (n = 1758). We used cluster analysis to identify typical groups of trees and human–tree relationships and conducted cross‐tabulation to correlate human and tree types in the relationships. In studying the human–tree relationship, we applied the framework of natureculture to address how the lives of humans and trees are bound together in interspecies relationships. Our results show that the strongest influence on tree–human relationships originates from human lifestyles and nature connections. Consequently, we identified three main types of human–tree relationships: (1) Admiring relationships towards large, old and charismatic trees, primarily grounded in sensory and emotional experiences, are common among urban nature‐loving people. (2) Nurturing relationships that occur with young trees in people's own gardens, which is most typical for rural outdoorspeople owning houses. (3) Nostalgic relationships are associated with trees with symbolic value in the memories of people who no longer have a material connection to an important environment. Our study revealed that the affection of humans for trees in their close environment strongly varied in emotional intensity and practical actions related to trees. We provide new knowledge of the correlations between human and tree characteristics in forming their interspecies relationship and how this relationship affects human emotional well‐being. Based on our findings, we suggest that understanding human–nature interdependence helps to sustain and create emotionally supportive multispecies environments through green design and management. Read the free Plain Language Summary for this article on the Journal blog.
The playing field of a tennis competition is a dynamic and complex formative environment given the following preliminary knowledge: (a) the basic technical, tactical, situational, and special types of shots used by the opponent; (b) the hitting area of the tennis player; (c) the place of service; (d) the ball drop position; and (d) batting efficiency and other related information that may improve the chances of victory. In this study, we propose an AI classification model for tennis serve scores. Using a deep learning algorithm, the model automatically tracks and classifies the serve scores of professional tennis players from video data. We first defined the players’ techniques, volleys, and placements of strokes and serves. Subsequently, we defined the referee's tennis terms and the voice in deciding on a serve score. Finally, we developed a deep learning model to automatically classify the serving position, landing position, and use of tennis techniques. The methodology was applied in the context of 10 matches played by Roger Federer and Rafael Nadal. The proposed deep learning algorithm achieved a 98.27% accuracy in the automatic classification of serve scores, revealing that Nadal outscored Federer by 2.1% in terms of serve-scoring efficiency. These results are expected to facilitate the automatic comparison and classification of shots in future studies, enabling coaches to adjust tactics in a timely manner and thereby improve the chances of winning.
One of the fundamental open questions in QFT is what kind of functions appear as Feynman integrals. In recent years this question has often been considered in a geometric context by interpreting the polynomials that appear in these integrals as defining algebraic varieties. One focal point of the past decade has in particular been the class of Calabi-Yau varieties that arise in some types of Feynman integrals. A class of manifolds that includes CYs as a special case are varieties of special Fano types. These varieties were originally introduced because the class of CY spaces is not closed under mirror symmetry. Their Hodge structure is of a more general type and the middle cohomology in particular is determined by two integers, the dimension of the manifold and a charge $Q$. In the present paper this class of manifolds is considered in the context of Feynman integrals.
We consider a special class of Galton-Watson theta-processes in a varying environment fully defined by four parameters, with two of them $(θ,r)$ being fixed over time $n$, and the other two $(a_n,c_n)$ characterizing the altering reproduction laws. We establish a sequence of transparent limit theorems for the theta-processes with possibly defective reproduction laws. These results may serve as a stepping stone towards incisive general results for the Galton-Watson processes in a varying environment.
Reinforcement learning (RL) agents are commonly trained and evaluated in the same environment. In contrast, humans often train in a specialized environment before being evaluated, such as studying a book before taking an exam. The potential of such specialized training environments is still vastly underexplored, despite their capacity to dramatically speed up training. The framework of synthetic environments takes a first step in this direction by meta-learning neural network-based Markov decision processes (MDPs). The initial approach was limited to toy problems and produced environments that did not transfer to unseen RL algorithms. We extend this approach in three ways: Firstly, we modify the meta-learning algorithm to discover environments invariant towards hyperparameter configurations and learning algorithms. Secondly, by leveraging hardware parallelism and introducing a curriculum on an agent's evaluation episode horizon, we can achieve competitive results on several challenging continuous control problems. Thirdly, we surprisingly find that contextual bandits enable training RL agents that transfer well to their evaluation environment, even if it is a complex MDP. Hence, we set up our experiments to train synthetic contextual bandits, which perform on par with synthetic MDPs, yield additional insights into the evaluation environment, and can speed up downstream applications.
ABSTRACT Pervious concrete is a special type of concrete consisting of cement, coarse aggregate and water. Cement is a widely used raw material for construction including pervious concrete and had led to the release of huge amounts of CO2 to the environment. Therefore, there is lot of research interest in finding supplementary cementitious materials. The present study examined and compared the feasibility of using industrial waste fly ash (FA) and agricultural waste rice husk ash (RHA) for sustainable pervious concrete production. An experimental program was performed with substitution of FA and RHA contents of 5%, 10%, 15% and 20% as cement replacement and water to binder ratio of 0.3, 0.35, 0.4 and 0.45. The characteristics of pervious concrete and sustainability analysis were compared for both FA and RHA replacement with control concrete mortar. The results showed that both FA and RHA have a negative effect on permeability. The compressive strength was optimum for FA content lies between 10% and 15% replacement level and RHA content of 5% replacement level. Furthermore, the utilisation of FA and RHA decreased production cost, the total embodied energy and carbon emission, resulting in cost-effective and eco-friendly pervious concrete.
ABSTRACT Enterococci are natural inhabitants of the intestinal tract in humans and many animals, including food-producing and companion animals. They can easily contaminate the food and the environment, entering the food chain. Moreover, Enterococcus is an important opportunistic pathogen, especially the species E. faecalis and E. faecium, causing a wide variety of infections. This microorganism not only contains intrinsic resistance mechanisms to several antimicrobial agents, but also has the capacity to acquire new mechanisms of antimicrobial resistance. In this review we analyze the diversity of enterococcal species and their distribution in the intestinal tract of animals. Moreover, resistance mechanisms for different classes of antimicrobials of clinical relevance are reviewed, as well as the epidemiology of multidrug-resistant enterococci of animal origin, with special attention given to beta-lactams, glycopeptides, and linezolid. The emergence of new antimicrobial resistance genes in enterococci of animal origin, such as optrA and cfr, is highlighted. The molecular epidemiology and the population structure of E. faecalis and E. faecium isolates in farm and companion animals is presented. Moreover, the types of plasmids that carry the antimicrobial resistance genes in enterococci of animal origin are reviewed.
D. L. Almeida-Nunes, Ana Mendes-Frias, Ricardo Silvestre
et al.
Ovarian cancer (OC) has a specific type of metastasis, via transcoelomic, and most of the patients are diagnosed at advanced stages with multiple tumors spread within the peritoneal cavity. The role of Malignant Ascites (MA) is to serve as a transporter of tumor cells from the primary location to the peritoneal wall or to the surface of the peritoneal organs. MA comprise cellular components with tumor and non-tumor cells and acellular components, creating a unique microenvironment capable of modifying the tumor behavior. These microenvironment factors influence tumor cell proliferation, progression, chemoresistance, and immune evasion, suggesting that MA play an active role in OC progression. Tumor cells induce a complex immune suppression that neutralizes antitumor immunity, leading to disease progression and treatment failure, provoking a tumor-promoting environment. In this review, we will focus on the High-Grade Serous Carcinoma (HGSC) microenvironment with special attention to the tumor microenvironment immunology.
Microplastics (MPs), a class of emerging contaminants, are ubiquitous in the environment, but limited information is known about them in remote terrestrial environment at high-altitude areas with inconvenient traffic and sparsely populated. In this study, 54 soil samples were collected from various land use patterns (greenhouse, ordinary farmland, grassland, and bare land) in western area of the Tibetan Plateau to determine the influence of land use type, altitude, meteorological parameters, and distance from the road edge on MP distribution. The MP abundance ranged from 0 (not detected) to 190 items/kg, with an average number of 64.8 items/kg. The concentration of MPs was slightly negatively correlated with altitude because of less human activities in high-altitude areas (especially agricultural activities). The random forest (RF) models showed that altitude was the most important driving factor that affected the MP distribution. Small-sized MPs were more abundant at higher altitudes than at low ones, and the special natural environment of the high-altitude areas (tall vegetation scarcely, UV, and strong wind speed) may be conducive to the degradation of MPs in surface soils. The special source of MPs in non-agricultural soils was associated with traffic behavior: parking and rest behavior beside roads at high altitude areas, which filled an important source of MPs in the plateau area. This study emphasized the need to investigate the effects of traffic activities on MPs in remote areas at high altitudes.