Search Results (10,947)

The environmental problems caused by carbon emission have become the focus of worldwide attention. Effective control of carbon emissions cannot be achieved without the protection of the rule of law. Environment public interests litigation is a prominent innovation in the judicial system, and its role in supervising the government to perform its regulatory duties on carbon reduction and regulating the carbon emission behaviors of enterprises and the public deserves discussion. The paper selected the panel data from 274 prefecture-level cities from 2013 to 2021 and analyzed the impact of a procuratorial public interest litigation pilot policy on carbon emission control by using the double difference method. The research found that the procuratorial public interest litigation pilot policy can effectively curb carbon emissions. Heterogeneity analysis showed that in cities with relatively low level of green innovation, the negative correlation between procuratorial public interest litigation pilot policies and carbon emissions is more significant. Compared with the eastern region, in the central and western regions, especially in the central region, where the concept, policy, and funding of carbon emission governance are relatively weak, the implementation of the pilot policy of procuratorial public interest litigation had a more obvious effect on carbon emission governance. Mechanism tests showed that procuratorial public interest litigation policies reduce carbon emissions by reducing energy consumption and increasing public participation in environmental protection. The study will provide an empirical basis for the carbon emission reduction effect on pilot policy of procuratorial public interest litigation and will offer certain theoretical recommendations for improving the procuratorial public interest litigation system in the ecological environment field. Full article

Urban green infrastructure (UGI) plays a vital role in mitigating climate change risks, including urban development-induced warming. The effective maintenance and monitoring of UGI are essential for detecting early signs of water stress and preventing potential fire hazards. Recent research shows that plants close their stomata under limited soil moisture availability, leading to an increase in leaf temperature. Multi-spectral cameras can detect thermal differentiation during periods of water stress and well-watered conditions. This paper examines the thermography of five characteristic green wall and green roof plant types (Pachysandra terminalis, Lonicera nit. Hohenheimer, Rubus tricolor, Liriope muscari Big Blue, and Hedera algeriensis Bellecour) under different levels of water stress compared to a well-watered reference group measured by thermal cameras. The experiment consists of a (1) pre-test experiment identifying the suitable number of days to create three different levels of water stress, and (2) the main experiment tested the suitability of thermal imaging with a drone to detect water stress in plants across three different dehydration stages. The thermal images were captured analyzed from three different types of green infrastructure. The method was suitable to detect temperature differences between plant types, between levels of water stress, and between GI types. The results show that leaf temperatures were approximately 1–3 °C warmer for water-stressed plants on the green walls, and around 3–6 °C warmer on the green roof compared to reference plants with differences among plant types. These insights are particularly relevant for UGI maintenance strategies and regulations, offering valuable information for sustainable urban planning. Full article

The optimization of photovoltaic (PV) systems is vital for enhancing efficiency and economic viability, especially under Partial Shading Conditions (PSCs). This study focuses on the development and comparison of traditional and advanced algorithms, including Perturb and Observe (P&O), Incremental Conductance (IC), Fuzzy Logic Control (FLC), Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and Artificial Neural Networks (ANN), for efficient Maximum Power Point Tracking (MPPT). Simulations conducted in the MATLAB/Simulink software package evaluated these algorithms’ performances under various shading scenarios. The results indicate that, while traditional methods like P&O and IC are effective under uniform conditions, advanced techniques, particularly ANN-based MPPT, exhibit superior efficiency and faster convergence under PSCs. This study concludes that integrating Artificial Intelligence (AI) and Machine Learning (ML) into MPPT algorithms significantly enhances the reliability and efficiency of PV systems, paving the way for a broader adoption of solar energy technologies in diverse environmental conditions. These findings contribute to advancing renewable energy technology and supporting green energy transition. Full article

Background: As early as 1995, the Institute of Medicine suggested that nurses were inadequately prepared for and educated about climate change and its health consequences. The aim of this systematic review is to identify the most reliable, robust, and valid instruments for measuring nurses’ knowledge and awareness of climate change and climate-associated diseases. Methods: Included studies were appraised using the Mixed-Methods Appraisal Tool and the Appraisal tool for Cross-Sectional Studies. The psychometrics and clinimetrics of the instruments were evaluated using the COSMIN Risk of Bias checklist and the COSMIN methodology for assessing content validity. Results: Medline, PubMed, Embase, CINAHL Ebesco, Cochrane Library Wiley, Web of Science Core Collection, Trip Database, JBI OVID SP, GreenFILE EBSCO, Google Scholar, ProQuest Dissertations and Theses Global, and DART-EU were consulted. The 14 studies retained identified eight different instruments evaluating attitudes, perceptions, environmental awareness, environmental sensitivity, environmental attitudes, behaviours, motivation, concern, optimism, and experience. This review is reported according to the PRISMA guidelines. Conclusions: The New Ecological Paradigm Scale (NEPS) and the Climate, Health, and Nursing Tool (CHANT) are the most reliable, robust, and valid instruments for measuring nurses’ knowledge and awareness of climate change and climate-associated diseases. Full article

Furoviruses are bipartite viruses causing mosaic symptoms and stunting in cereals. Infection with these viruses can lead to severe crop losses. The virus species Furovirus tritici with soil-borne wheat mosaic virus (SBWMV), Furovirus cerealis with soil-borne cereal mosaic virus (SBCMV) and Furovirus japonicum with Japanese soil-borne wheat mosaic virus (JSBWMV) and French barley mosaic virus (FBMV) as members are biologically and genetically closely related. Here, we develop SYBR green-based real-time quantitative RT-PCR assays to detect and quantify the RNA1 and RNA2 of the three virus species. Using experimental data in combination with Tm-value prediction and analysis of primer and amplicon sequences, we determine the capacity of our method to discriminate between the different viruses and evaluate its genericity to detect different isolates within the same virus species. We demonstrate that our method is suitable for discriminating between the different virus species and allows for the detection of different virus isolates. However, JSBWMV RNA1 primers may amplify SBWMV samples, bearing a risk for false positive detection with this primer. We also test the efficiency of polyclonal antibodies to detect the different viruses by ELISA and suggest that ELISA may be applied as a first screening to identify the virus. The real-time qRT-PCR assays developed provide the possibility to screen for quantitative disease resistance against SBCMV, SBWMV and JSBWMV. Moreover, with our method, we hope to promote research to unravel yet unresolved questions with respect to furovirus–host interaction concerning host range and resistance as well as regarding the role of multipartite genomes. Full article

All over the world, teenagers suffer from stress-related mental illness, and research shows that being in natural environments can bring about recovery. However, centrally located areas in cities where teenagers like to hang out are being densified at the expense of green spaces. The health-promoting function of small, centrally located parks is thus becoming increasingly important. This study examines Iranian teenagers’ assessment of the restorative potential of small, centrally located parks. Such parks include attributes typical of city centers, such as trees, lighting, park benches and flowers. A discrete sampling method was used to collect responses from a sample of 265 Iranian teenagers. They were asked to randomly rate the perceived recovery potential of digitally designed models of green spaces. The results show that the teenagers evaluated the presence of water in waterbeds to have a strong positive effect on recovery possibilities. The entire green area should also be screened off from the rest of the city and convey a soft impression. It should have lighting from tall lampposts, contain plant beds and, not least, have distinctive cultural attributes such as crescent arches and fountains. In the discussion of the article, we address the practical and theoretical implications of the findings. Full article

The cuticle covering the outer surface of an eggshell functions as both a physical and chemical barrier against invading microorganisms. Contamination of eggs by microbial pathogens progresses in four stages: bacterial attachment to the egg surface, penetration through the cuticle and eggshell, multiplication within the underlying membranes, and the final stage of contaminating the egg contents. Therefore, it is important to study bacterial count at the first point of contact, i.e., on the surface of the eggs. In this study, we have evaluated the impact of differences in cuticle quality (due to egg washing and hen age) on bacterial load. We compared bacterial adherence on the eggshell surface of white eggs which were either washed (graded) or unwashed (ungraded), collected from Lohmann laying hens of different ages: early (24–28 weeks), mid-lay (44–48 weeks), and late (66–70 weeks). We aimed to determine the impact of hen age and egg washing on differences in cuticle quality and bacterial adherence. Our results indicate that hen age (up to 70 weeks) and commercial egg washing do not significantly impact bacterial adherence on eggshell surfaces. We have developed a novel method using green fluorescent protein (GFP)-expressing Salmonella typhimurium to estimate adherence of bacteria to the eggshell surface, with independent measurement of autofluorescence to quantitate cuticle deposition. S. typhimurium were localized, adhering to cracks visible on the outer cuticle in ungraded eggs, indicating that egg-associated pathogens usually enter the egg interior either through respiratory pores in eggshells or through shell micro-cracks. The results of this study can be utilized to optimize innovative methods for predictive microbiology in order to achieve egg safety. Full article

To date, scholars have increasingly focused on the reduction in crop yields caused by cultivated land fragmentation, yet its effects on the ecological efficiency of cultivated land use are often overlooked. This oversight leads to land resource waste and environmental pollution. It is essential to explore this problem to achieve moderate-scale farming operations and promote the green transformation of agricultural land. This study theoretically analyzed the mechanisms by which cultivated land fragmentation and management scales influence the ecological efficiency of cultivated land use. Based on 2023 household data from Changde and Shaoyang, China, empirical tests were conducted using the stochastic frontier analysis method, Tobit model, and structural equation model. The research results indicate that: (1) The mean ecological efficiency of cultivated land use among the total sample households was 0.822, and the eco-efficiency in the plains was slightly lower than that in the hilly areas. (2) The scale of cultivated land management played a moderating role in the impact of cultivated land fragmentation on ecological efficiency, with differences observed between topographical types. The scale of management can offset part of the negative impact of cultivated land fragmentation on the ecological efficiency of cultivated land use. (3) Regarding the impact of cultivated land fragmentation on the ecological efficiency of cultivated land use, cultivated land management scale changes play a complete mediating role. These findings help provide policy implications to improve the ecological efficiency of cultivated land use. Policy support should be strengthened by promoting moderate-scale cultivated land operations, enhancing the comprehensive remediation of cultivated land fragmentation, and developing skilled farmers for long-term environmental sustainability. Full article

Background/Objectives: The development of polymer–lipid hybrid nanoparticles (PLNs) is a promising area of research, as it can help increase the stability of cationic lipid carriers. Hybrid PLNs are core–shell nanoparticle structures that combine the advantages of both polymer nanoparticles and liposomes, especially in terms of their physical stability and biocompatibility. Natural polymers such as polyhydroxyalkanoate (PHA) can be used as a matrix for the PLNs’ preparation. Methods: In this study, we first obtained stable cationic hybrid PLNs using a cationic liposome (CL) composed of a polycationic lipid 2X3 (1,26-bis(cholest-5-en-3β-yloxycarbonylamino)-7,11,16,20-tetraazahexacosane tetrahydrochloride), helper lipid DOPE (1,2-dioleoyl-sn-glycero-3-phosphoethanolamine), and the hydrophobic polymer mcl-PHA, which was produced by the soil bacterium Pseudomonas helmantisensis P1. Results: The new polymer-lipid carriers effectively encapsulated and delivered model mRNA-eGFP (enhanced green fluorescent protein mRNA) to BHK-21 cells. We then evaluated the role of mcl-PHA in increasing the stability of cationic PLNs in ionic solutions using dynamic light scattering data, electrophoretic mobility, and transmission electron microscopy techniques. Conclusions: The results showed that increasing the concentration of PBS (phosphate buffered saline) led to a decrease in the stability of the CLs. At high concentrations of PBS, the CLs aggregate. In contrast, the presence of isotonic PBS did not result in the aggregation of PLNs, and the particles remained stable for 120 h when stored at +4 °C. The obtained results show that PLNs hold promise for further in vivo studies on nucleic acid delivery. Full article

This study develops a Convolutional Autoencoder (CAE) and deep neural network (DNN)-based model optimized for real-time signal processing and high accuracy in motor fault diagnosis. This model learns complex patterns from voltage and current data and precisely analyzes them in combination with DNN through latent space representation. Traditional diagnostic methods relied on vibration and current sensors, empirical knowledge, or harmonic and threshold-based monitoring, but they had limitations in recognizing complex patterns and providing accurate diagnoses. Our model significantly enhances the accuracy of power data analysis and fault diagnosis by mapping each phase (R, S, and T) of the electrical system to the red, green, and blue (RGB) channels of image processing and applying various signal processing techniques. Optimized for real-time data streaming, this model demonstrated high practicality and effectiveness in an actual industrial environment, achieving 99.9% accuracy, 99.8% recall, and 99.9% precision. Specifically, it was able to more accurately diagnose motor efficiency and fault risks by utilizing power system analysis indicators such as phase voltage, total harmonic distortion (THD), and voltage unbalance. This integrated approach significantly enhances the real-time applicability of electric motor fault diagnosis and is expected to provide a crucial foundation for various industrial applications in the future. Full article

A systematic investigation of optical, electrochemical, photophysical, and electrooptical properties of printable green color-emitting polymer (poly(9,9-dioctylfluorene-alt-bithiophene)) (F8T2) and spiro-copolymer (SPG-01T) was conducted to explore their potentiality as an emissive layer for wearable polymer light-emitting diode (PLED) applications. We compared the two photoactive polymers in terms of their spectral characteristics and color purity, as these are the most critical factors for wearable lighting sources and optical sensors. Low-cost, solution-based methods and facile architecture were applied to produce rigid and flexible light-emitting devices with high luminance efficiencies. Emission bandwidths, color coordinates, operational characteristics, and luminance were also derived to evaluate the device’s stability. The tuning of emission’s spectral features by layer thickness variation was realized and was correlated with the interplay between H-aggregates and J-aggregates formations for both conjugated polymers. Finally, we applied the functional green light-emitting PLED devices based on the two studied materials for the detection of Rhodamine 6G. It was determined that the optical detection of the R6G photoluminescence is heavily influenced by the emission spectrum characteristics of the PLED and changes in the thickness of the active layer. Full article

Genetic transformation is a critical tool for gene manipulation and functional analyses in plants, enabling the exploration of key phenotypes and agronomic traits at the genetic level. While dicotyledonous plants offer various tissues for in vitro culture and transformation, monocotyledonous plants, such as rice, have limited options. This study presents an efficient method for genetically transforming rice (Oryza sativa L.) using seed-derived embryogenic calli as explants. Two target genes were utilized to assess regeneration efficiency: green fluorescent protein (eGFP) and the apple FLOWERING LOCUS T (FT)-like gene (MdFT1). Antisense MdFT1 was cloned into a vector controlled by the rice α-amylase 3D (Ramy3D) promoter, while eGFP was fused to Cas9 under the Ubi promoter. These vectors were introduced separately into rice embryogenic calli from two Korean cultivars using Agrobacterium-mediated transformation. Transgenic seedlings were successfully regenerated via hygromycin selection using an in vitro cultivation system. PCR confirmed stable transgene integration in the transgenic calli and their progeny. Fluorescence microscopy revealed eGFP expression, and antisense MdFT1-expressing lines exhibited notable phenotypic changes, including variations in plant height and grain quality. High transformation efficiency and regeneration frequency were achieved for both tested cultivars. This study demonstrated the effective use of seed-derived embryogenic calli for rice transformation, offering a promising approach for developing transgenic plants in monocot species. Full article

This study introduces a novel multi-criteria group evaluation approach grounded in the theory of basic uncertain information (BUI) to facilitate the selection of green recycling suppliers for shared electric bikes. Firstly, a comprehensive index system of green recycling suppliers is established, encompassing recycling capacity, environmental sustainability, financial strength, maintenance capabilities, and policy support, to provide a solid foundation for the scientific selection process. Secondly, the basic uncertain information generalized power weighted average (BUIGPWA) operator is proposed to aggregate group evaluation information with BUI pairs, and some related properties are investigated. Furthermore, the basic uncertain information-based best–middle–worst TOPSIS (BUI-BMW-TOPSIS) model incorporating the best, middle, and worst reference points to enhance decision-making accuracy is proposed. Ultimately, by integrating the BUIGPWA operator for group information aggregation with the BUI-BMW-TOPSIS model to handle multi-criteria decision information, a novel multi-criteria group decision-making (MCGDM) method is constructed to evaluate green recycling suppliers for shared electric bikes. Case analyses and comparative analyses demonstrate that compared with the BUIWA operator, the BUIGPWA operator yields more reliable results because of its consideration of the degree of support among decision-makers. Furthermore, in contrast to the traditional TOPSIS method, the BUI-BMW-TOPSIS model incorporates the credibility of information provided by decision-makers, leading to more trustworthy outcomes. Notably, variations in attribute weights significantly impact the decision-making results. In summary, our methods excel in handling uncertain information and complex multi-criteria group decisions, boosting scientific rigor and reliability, and supporting optimization and sustainability of shared electric bike green recycling suppliers. Full article

Marginal areas (MAs) can show scarce disaster resilience in the context of climate change. Proactive adaptation to climate change (ACC) based on green infrastructure (GI) has the potential to increase the disaster resilience of the MAs. The scientific literature has scarcely addressed research on methods and guidelines for promoting ACC and GI to increase the resilience of MAs. No previous research has focused on a method to set a reference scheme for implementation guidelines concerning the use of GI as an ACC approach to deal with the effects of a changing climate in Italian MAs. In this regard, this study aims to provide planners and public administrations with an appropriate scheme to foster the mainstreaming of ACC and GI into the planning of MAs. To do so, we proposed and applied a methodological approach consisting of the scrutiny of the scientific and grey literature with the purpose of distilling a set of key elements (KEs) that need to be considered as a reference scheme for implementation guidelines. As main findings, we identified ten KEs relevant to drafting guidelines for integrating ACC and GI into planning tools, e.g., a clear definition of GI, participative approaches, public–private cooperation, and others, that will be tested in ongoing research. Full article

The use of green roofs, a low-impact development practice, can be an effective means of reducing direct runoff in urban centers. Green roof modeling can enable efficient design by preliminarily grasping the behavior of the green roof system according to specific configurations. In this study, we aimed to find appropriate evapotranspiration and parameter optimization schemes for HYDRUS-1D, a commonly used modeling tool for green roofs. Comparative studies of this sort in the context of green roof runoff modeling have not been conducted previously and are important in guiding users to overcome the difficulties of choosing the right numerical schemes for an accurate prediction of runoff from a green roof. As a study site, the Portland Building Ecoroof in Portland, Oregon, USA, was chosen, as green roof configurations and observed data for climate and runoff were available. From the simulation results of the runoff volume, the Blaney–Criddle method, which was considered an alternative, was found to be appropriate for calculating evapotranspiration from a green roof (R² = 0.82) relative to the Hargreaves method built in HYDRUS-1D (R² = 0.46). In addition, this study showed that the optimization method using the harmony search algorithm, which was proposed as an alternative optimizer, was better (R² = 0.95) than that of the HYDRUS-1D’s own optimization module (R² = 0.82) in calibrating HYDRUS-1D for green roof runoff. The findings are thought to be useful in guiding modelers who are considering using HYDRUS-1D for green roof runoff simulations. Full article