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The service environment of urban polyethylene (PE) pipes has a crucial influence on their long-term safety and performance. Based on the application and structural performance analysis of PE pipe failure cases, this study aims to investigate the impact of organic substances in the soil on the aging behavior of PE pipes by designing organic solutions with different concentrations, which are based on the composition of organic substances in the soil environment, and periodic immersion tests.

Soil samples in the vicinity of the failed pipes were analyzed by gas chromatography-mass spectrometry, sensitive organic substances were screened and soaking solutions of different concentrations were designed. After the soaking test, the PE pipe samples were analyzed using differential scanning calorimetry, Fourier-transform infrared spectroscopy and other testing methods.

The performance difference between the outer surface and the middle of the cross section of PE pipes highlights the influence of the soil service environment on their aging. Different organic solutions can have varying impacts on the aging behavior of PE pipes when immersed. For instance, when exposed to amine organic solutions, PE pipes may have an increased weight and decreased material yield strength, although there is no reduction in their thermal or oxygen stability. On the contrary, when subjected to ether organic solutions, the surface of PE pipe specimens may be affected, leading to a reduction in material fracture elongation and a decrease in their thermal and oxygen stability. Furthermore, immersion in either amine or ether organic solutions may result in the production of hydroxyl and other aging groups on the surface of the material.

Understanding the potential impact of organic substances in the soil environment on the aging of PE pipe ensures the long-term performance and safety of urban PE pipe. This research approach will provide valuable insights into improving the durability and reliability of urban PE pipes in soil environments.

Human actions on natural ecosystems have not only jeopardized human well-being but also threatened the existence of other species. On the other hand, the benefits resulting from a greater integration between the logic of nature and human occupations have been seen as motivating factors for the prevention and mitigation of environmental impacts in landscape planning, since it provides human well-being through the grant of resources, regulation of the environment and socio-cultural services called ecosystem services. This article highlights the relevance of using ecosystem integrity indicators related to the functioning of ecological support processes for landscape planning.

The research used the photosynthetic performance of vegetation through carbon fluxes in the landscape, defining areas where different approaches to green infrastructure can be applied, gaining over the majority of work in this area, in which low degrees of objectivity on measurement and consequent ecological recovery still prevail. Thus, using the conceptual support of restoration ecology and remote sensing, the work identified different vegetation performances in relation to the supporting ecological processes using the multispectral CO₂flux index, linked to the carbon flux to identify the photosynthetic effectiveness of the vegetation and the Topographic Wetness Index (TWI).

With a study in the Distrito Federal (DF), the results of the different performances of vegetation for ecological support, through electromagnetic signatures and associated vegetation formations, allowed for the identification of hotspots of greater integrity that indicate multifunctional areas to be preserved and critical areas that deserve planning actions using green infrastructure techniques for their restoration and integration into the landscape.

This approach could be the initial step towards establishing clear and assertive criteria for selecting areas with greater potential for the development of supporting ecological processes in the territorial mosaic.

Smart farming technologies (SFTs) can increase yields and reduce the environmental impacts of farming by improving the efficient use of inputs. This paper is to estimate farmers' preference and willingness to pay (WTP) for a well-defined SFT, smart drip irrigation (SDI) technology.

This study conducted a discrete choice experiment (DCE) among 1,300 maize farmers in North China to understand their WTP for various functions of SDI using mixed logit (MIXL) models.

The results show that farmers have a strong preference for SDI in general and its specific functions of smart sensing and smart control. However, farmers do not have a preference for the function of region-level agronomic planning. Farmers' preferences for different functions of SDI are heterogeneous. Their preference was significantly associated with their education, experience of being village cadres and using computers, household income and holding of land and machines. Further analysis show that farmers' WTP for functions facilitated by hardware is close to the estimated prices, whereas their WTP for functions wholly or partially facilitated by software is substantially lower than the estimated prices.

Findings from the empirical study lead to policy implications for enhancing the design of SFTs by integrating software and hardware and optimizing agricultural extension strategies for SFTs with digital techniques such as videos.

This study provides initial insights into understanding farmers' preferences and WTP for specific functions of SFTs with a DCE.

This paper's purpose is to explore the current interest and knowledge that UK consumers hold around agroforestry. Despite the many reported benefits of agroforestry systems, uptake in the UK, as well as other temperate nations, has been low. As the consumer has a role to play in the transition of agriculture to methods that are more environmentally friendly it is vital to have an understanding of their perceptions. Yet to date no work has looked at agroforestry from the perspective of the UK consumer.

An online survey was conducted using a convenience sample accessed by floating a link through social media and messaging apps. The survey was also shared to the members of a private Facebook group associated with an organic vegetable box service. A mix of multiple choice and open text boxes were used. The survey received 139 responses.

Non-parametric tests indicate that this sample of UK consumers would be mostly likely to buy, and willing to pay more for, agroforestry produce; and the sample showed a split group regarding familiarity. Inductive thematic analysis of the qualitative data highlighted some important barriers to the purchase as well as capturing a snapshot of this sample's perceptions.

This paper presents, to the authors knowledge, the first set of data regarding a sample of UK consumers' perspective of agroforestry produce. The findings could bolster producers' confidence in adopting agroforestry practices, but also highlight the need for policymakers to bolster consumer support through parallel means.

This paper aims to study the application of high-tolerance and flexible indigenous bacteria and fungi, along with the co-metabolism in recycled paper and cardboard mill (RPCM) wastewater treatment (WWT).

The molecular characterization of isolated indigenous bacteria and fungi was performed by 16S rRNA and 18S rRNA gene sequencing, respectively. Glucose was used as a cometabolic substrate to enhance the bioremediation process.

The highest removal efficiency was achieved for both chemical oxygen demand (COD) and color [78% COD and 45% color removal by Pseudomonas aeruginosa RW-2 (MZ603673), as well as approximately 70% COD and 48% color removal by Geotrichum candidum RW-4 (ON024394)]. The corresponding percentages were higher in comparison with the efficiency obtained from the oxidation ditch unit in the full-scale RPCM WWT plant.

Indigenous P. aeruginosa RW-2 and G. candidum RW-4 demonstrated effective capability in RPCM WWT despite the highly toxic and low biodegradable nature, especially with the assistance of glucose.

Current evidence indicates that humans and animals are at increased risk of multiple health challenges due to microplastic (MP) profusion. However, mitigation is constrained by inadequate scientific data, further aggravated by the lack of evidence in many African countries. This review therefore synthesized evidence on the current extent of MP pollution in Africa and the analytical techniques for reporting.

A literature search was undertaken in research databases. Medical subject headings (MeSH) terms and keywords were used in the literature search. The authors found 38 studies from 10 countries that met the inclusion criteria.

Marine organisms had MPs prevalence ranging from 19% to 100%, whereas sediments and water samples had between 77 and 100%. The most common and dominant polymers included polypropylene and polyethylene.

This review shows that most studies still use methods that are prone to human errors. Therefore, the concentration of MPs is likely underestimated, even though the authors’ prevalence evaluations show MPs are still largely pervasive across multiple environmental matrices. Also, the study reveals significant spatial disparity in MP research across the African continent, showing the need for further research in other African countries.

Even though some reviews have assessed MPs pollution in Africa, they have not evaluated sample prevalence, which is necessary to understand not only concentration but pervasiveness across the continent. Secondly, this study delves deeper into various methods of sampling, extraction and analysis of MPs, as well as limitations and relevant recommendations.

The purpose of this paper is to develop an appropriate machine learning model for predicting soil compaction degree while also examining the contribution rates of three influential factors: moisture content, electrical conductivity and temperature, towards the prediction of soil compaction degree.

Taking fine-grained soil A and B as the research object, this paper utilized the laboratory test data, including compaction parameter (moisture content), electrical parameter (electrical conductivity) and temperature, to predict soil degree of compaction based on five types of commonly used machine learning models (19 models in total). According to the prediction results, these models were preliminarily compared and further evaluated.

The Gaussian process regression model has a good effect on the prediction of degree of compaction of the two kinds of soils: the error rates of the prediction of degree of compaction for fine-grained soil A and B are within 6 and 8%, respectively. As per the order, the contribution rates manifest as: moisture content > electrical conductivity >> temperature.

By using moisture content, electrical conductivity, temperature to predict the compaction degree directly, the predicted value of the compaction degree can be obtained with higher accuracy and the detection efficiency of the compaction degree can be improved.

In the field of heritage science, especially applied to buildings and artefacts made by organic hygroscopic materials, analyzing the microclimate has always been of extreme importance. In particular, in many cases, the knowledge of the outdoor/indoor microclimate may support the decision process in conservation and preservation matters of historic buildings. This knowledge is often gained by implementing long and time-consuming monitoring campaigns that allow collecting atmospheric and climatic data.

Sometimes the collected time series may be corrupted, incomplete and/or subjected to the sensors' errors because of the remoteness of the historic building location, the natural aging of the sensor or the lack of a continuous check of the data downloading process. For this reason, in this work, an innovative approach about reconstructing the indoor microclimate into heritage buildings, just knowing the outdoor one, is proposed. This methodology is based on using machine learning tools known as variational auto encoders (VAEs), that are able to reconstruct time series and/or to fill data gaps.

The proposed approach is implemented using data collected in Ringebu Stave Church, a Norwegian medieval wooden heritage building. Reconstructing a realistic time series, for the vast majority of the year period, of the natural internal climate of the Church has been successfully implemented.

The novelty of this work is discussed in the framework of the existing literature. The work explores the potentials of machine learning tools compared to traditional ones, providing a method that is able to reliably fill missing data in time series.

Indoor air quality monitoring is extremely important in urban, industrial areas. Considering the devastating effect of declining quality of air in major part of the countries like India and China, it is highly recommended to monitor the quality of air which can help people with respiratory diseases, children and elderly people to take necessary precautions and stay safe at their homes. The purpose of this study is to detect air quality and perform predictions which could be part of smart home automation with the use of newer technology.

This study proposes an Internet-of-Things (IoT)-based air quality measurement, warning and prediction system for ambient assisted living. The proposed ambient assisted living system consists of low-cost air quality sensors and ESP32 controller with new generation embedded system architecture. It can detect Indoor Air Quality parameters like CO, PM2.5, NO2, O3, NH3, temperature, pressure, humidity, etc. The low cost sensor data are calibrated using machine learning techniques for performance improvement. The system has a novel prediction model, multiheaded convolutional neural networks-gated recurrent unit which can detect next hour pollution concentration. The model uses a transfer learning (TL) approach for prediction when the system is new and less data available for prediction. Any neighboring site data can be used to transfer knowledge for early predictions for the new system. It can have a mobile-based application which can send warning notifications to users if the Indoor Air Quality parameters exceed the specified threshold values. This is all required to take necessary measures against bad air quality.

The IoT-based system has implemented the TL framework, and the results of this study showed that the system works efficiently with performance improvement of 55.42% in RMSE scores for prediction at new target system with insufficient data.

This study demonstrates the implementation of an IoT system which uses low-cost sensors and deep learning model for predicting pollution concentration. The system is tackling the issues of the low-cost sensors for better performance. The novel approach of pretrained models and TL work very well at the new system having data insufficiency issues. This study contributes significantly with the usage of low-cost sensors, open-source advanced technology and performance improvement in prediction ability at new systems. Experimental results and findings are disclosed in this study. This will help install multiple new cost-effective monitoring stations in smart city for pollution forecasting.

The purpose of the paper is to showcase the significant achievements of Egypt's scientists in the 20th century across various fields of study such as medicine, physics, chemistry, biology, math, geology, astronomy and engineering. The paper highlights the struggles and successes of these scientists, as well as the cultural, social and political factors that influenced their lives and work. The aim is to inspire young people to pursue careers in science and make their own contributions to society by presenting these scientists as role models for hard work and dedication. Ultimately, the paper seeks to promote the importance of science and its impact on society.

The purpose of this review is to present the scientific biographies of Egypt's most distinguished scientists, primarily in the field of Natural Sciences, in a balanced and comprehensive manner. The work is objective, honest and abstract, avoiding any bias or exaggeration. The author provides a clear and concise methodology, including a brief introduction to the scientist and their field of study, an explanation of their major contributions, the impact of their work on society, any challenges or obstacles faced during their career and their lasting legacy. The aim is to showcase the important achievements of these scientists, their impact on their respective fields and to inspire future generations to pursue scientific careers.

The group of outstanding scientists in 20th century Egypt were shaped by various factors, including familial upbringing, education, society, political and cultural atmosphere and state support for scientific research. These scientists made significant contributions to various academic disciplines, including medicine, physics, chemistry, biology, mathematics and engineering. Their impact on their communities and cultures has received international acclaim, making them role models for future generations of scientists and researchers. The history of these scientists highlights the importance of educational investments and supporting scientific research to foster innovation and social progress. The encyclopedia serves as a useful tool for students, instructors and education professionals, preserving Egypt's scientific heritage and honouring the scientists' outstanding accomplishments.

The encyclopedia preserves Egypt's scientific heritage, which has been overlooked for political or other reasons. It is a useful tool for a variety of readers, including students, instructors and education professionals, and it offers insights into universally relevant scientific success factors as well as scientific research methodologies. The encyclopedia honours the outstanding scientific accomplishments of Egyptian researchers and their contributions to the world's scientific community.

The practical implications of this paper are several. First, it highlights the importance of education, family upbringing and societal support for scientific research in fostering innovation and social progress. Second, it underscores the need for continued funding and support for scientific research to maintain and build upon the accomplishments of past generations of scientists. Third, it encourages young people to pursue scientific careers and make their own contributions to society. Fourth, it preserves the scientific heritage of Egypt and honors the contributions of its outstanding scientists. Finally, it serves as a useful tool for students, instructors and education professionals seeking to understand the factors underlying scientific success and research methodologies.

The social implications of the paper include promoting national pride and cultural identity, raising awareness of the importance of education and scientific research in driving social progress, inspiring future generations of scientists and researchers, reducing socioeconomic disparities and emphasizing the role of society, politics and culture in shaping scientific researchers' personalities and interests.

The paper's originality/value lies in its comprehensive documentation of the scientific biographies of Egypt's most prominent scientists in the 20th century, providing unique insights into the factors that contributed to their development and their impact across various academic disciplines. It preserves Egypt's scientific heritage and inspires future generations of scientists and researchers through the promotion of educational investments and scientific research. The encyclopedia serves as a useful tool for education professionals seeking to understand scientific success factors and research methodologies, emphasizing the importance of supportive and inclusive environments for scientific development.