Search Results (19,144)

Background: Developments in biology, genetics, soil science, plant breeding, engineering, and agricultural microbiology are driving advances in soil microbiology and microbial biotechnology. Material and methods: The literature for this review was collected by searching leading scientific databases such as Embase, Medline/PubMed, Scopus, and Web of Science. Results: Recent advances in soil microbiology and biotechnology are discussed, emphasizing the role of microorganisms in sustainable agriculture. It has been shown that soil and plant microbiomes significantly contribute to improving soil fertility and plant and soil health. Microbes promote plant growth through various mechanisms, including potassium, phosphorus, and zinc solubilization, biological nitrogen fixation, production of ammonia, HCN, siderophores, and other secondary metabolites with antagonistic effects. The diversity of microbiomes related to crops, plant protection, and the environment is analyzed, as well as their role in improving food quality, especially under stress conditions. Particular attention was paid to the diversity of microbiomes and their mechanisms supporting plant growth and soil fertility. Conclusions: The key role of soil microorganisms in sustainable agriculture was highlighted. They can support the production of natural substances used as plant protection products, as well as biopesticides, bioregulators, or biofertilizers. Microbial biotechnology also offers potential in the production of sustainable chemicals, such as biofuels or biodegradable plastics (PHA) from plant sugars, and in the production of pharmaceuticals, including antibiotics, hormones, or enzymes. Full article

The increasing demand for rapid, sensitive, and eco-friendly methods for the detection of trace heavy metals in environmental samples, attributed to their serious threats to health and the environment, has spurred considerable interest in the development of sustainable sensor materials. Toxic metal ions, namely, lead (Pb²⁺), cadmium (Cd²⁺), mercury (Hg²⁺), arsenic (As³⁺), and chromium, are potential hazards due to their non-biodegradable nature with high toxicity, even at trace levels. Acute health complications, including neurological, renal, and developmental disorders, arise upon exposure to such metal ions. To monitor and mitigate these toxic exposures, sensitive detection techniques are essential. Pre-existing conventional detection methods, such as atomic absorption spectroscopy (AAS) and inductively coupled plasma-mass spectrometry (ICP-MS), involve expensive instrumentation, skilled operators, and complex sample preparation. Electrochemical sensing, which is simple, portable, and eco-friendly, is foreseen as a potential alternative to the above conventional methods. Carbon-based nanomaterials play a crucial role in electrochemical sensors due to their high conductivity, stability, and the presence of surface functional groups. Biochar (BC), a carbon-rich product, has emerged as a promising electrode material for electrochemical sensing due to its high surface area, sustainability, tunable porosity, surface rich in functional groups, eco-friendliness, and negligible environmental footprint. Nevertheless, broad-spectrum studies on the use of biochar in electrochemical sensors remain narrow. This review focuses on the recent advancements in the development of biochar-based electrochemical sensors for the detection of toxic heavy metals such as Pb²⁺, Cd²⁺, and Hg²⁺ and the simultaneous detection of multiple ions, with special emphasis on BC synthesis routes, surface modification methodologies, electrode fabrication techniques, and electroanalytical performance. Finally, current challenges and future perspectives for integrating BC into next-generation sensor platforms are outlined. Full article

Photocatalytic redox processes significantly contribute to shaping Earth’s surface environment. Semiconductor minerals exhibiting favorable photocatalytic properties are ubiquitous on rock and soil surfaces. However, the sunlight-responsive characteristics and functions of TiO₂, an excellent photocatalytic material, within natural systems remain incompletely understood, largely due to its wide bandgap limiting solar radiation absorption. This study analyzed surface coating samples, determining their elemental composition, distribution, and mineralogy. The analysis revealed enrichment of anatase TiO₂ and β-carotene. Informed by these observations, laboratory simulations were designed to investigate the synergistic effect of β-carotene on the sunlight-responsive behavior of anatase. Results demonstrate that β-carotene-sensitized anatase exhibited a 64.4% to 66.1% increase in photocurrent compared to pure anatase. β-carotene sensitization significantly enhanced anatase’s electrochemical activity, promoting rapid electron transfer. Furthermore, it improved interfacial properties and acted as a photosensitizer, boosting photo-response characteristics. The sensitized anatase displayed a distinct absorption peak within the 425–550 nm range, with visible light absorption increasing by approximately 17.75%. This study elucidates the synergistic mechanism enhancing the sunlight response between anatase and β-carotene in natural systems and its broader environmental implications, providing new insights for research on photocatalytic redox processes within Earth’s critical zone. Full article

Systems thinking (ST) is a foundational cognitive skillset to advance sustainability education but has not been well examined for learners prior to higher education. This case study research in rural middle schools in the Midwestern U.S. examines systems thinking outcomes of a place-based energy literacy unit focused on energy-efficient building design. The unit employs the science of energy-efficient, green buildings to illuminate the ways in which energy flows between natural and built environments. The unit emphasized electrical, light, and thermal energy systems and the ways these systems interact to create functional and energy-efficient buildings. This study focuses on three case study classrooms where students across schools (n = 89 students) created systems models as part of pre- and post-unit tests (n = 162 models). The unit tests consisted of student drawings, annotations, and writings, culminating into student-developed systems models. Growth from pre- to post-test was observed in both the identification of system elements and the linkages between elements. System elements included in the models were common classroom features, such as windows, lights, and temperature control, suggesting that rooting the unit in place-based teaching may support ST skills. Full article

Piano fingering estimation remains a complex problem due to the combinatorial nature of hand movements and no best solution for any situation. A recent model-free reinforcement learning framework for piano fingering modeled each monophonic piece as an environment and demonstrated that value-based methods outperform probability-based approaches. Building on their finding, this paper addresses the more complex polyphonic fingering problem by formulating it as an online model-free reinforcement learning task with a novel training strategy. Thus, we introduce a novel Elite Episode Replay (EER) method to improve learning efficiency by prioritizing high-quality episodes during training. This strategy accelerates early reward acquisition and improves convergence without sacrificing fingering quality. The proposed architecture produces multiple-action outputs for polyphonic settings and is trained using both elite-guided and uniform sampling. Experimental results show that the EER strategy reduces training time per step by 21% and speeds up convergence by 18% while preserving the difficulty level and result of the generated fingerings. An empirical study of elite memory size further highlights its impact on training performance in solving piano fingering estimation. Full article

In response to the stress commonly experienced by young people in high-pressure daily environments, a music-based stress-relief interactive system was developed by integrating music-assisted care with emotion-sensing technology. The design principles of the system were established through a literature review on stress, music listening, emotion detection, and interactive devices. A prototype was created accordingly and refined through interviews with four experts and eleven users participating in a preliminary experiment. The system is grounded in a four-stage guided imagery and music framework, along with a static activity model focused on relaxation-based stress management. Emotion detection was achieved using a wearable EEG device (NeuroSky’s MindWave Mobile device) and a two-dimensional emotion model, and the emotional states were translated into visual representations using seasonal and weather metaphors. A formal experiment involving 52 users was conducted. The system was evaluated, and its effectiveness confirmed, through user interviews and questionnaire surveys, with statistical analysis conducted using SPSS 26 and AMOS 23. The findings reveal that: (1) integrating emotion sensing with music listening creates a novel and engaging interactive experience; (2) emotional states can be effectively visualized using nature-inspired metaphors, enhancing user immersion and understanding; and (3) the combination of music listening, guided imagery, and real-time emotional feedback successfully promotes emotional relaxation and increases self-awareness. Full article

Wound care in military and combat environments poses distinct challenges that set it apart from conventional medical practice in civilian settings. The nature of injuries sustained on the battlefield—often complex, contaminated, and involving extensive tissue damage—combined with limited access to immediate medical intervention, significantly increases the risk of infection, delayed healing, and adverse outcomes. Traditional wound dressings frequently prove inadequate under such extreme conditions, as they have not been designed to address the specific physiological and logistical constraints present during armed conflicts. This review provides a comprehensive overview of recent progress in the development of advanced wound dressings tailored for use in military scenarios. Special attention has been given to multifunctional dressings that go beyond basic wound coverage by incorporating biologically active macromolecules such as collagen, chitosan, thrombin, alginate, therapeutic peptides, and growth factors. These compounds contribute to properties including moisture balance control, exudate absorption, microbial entrapment, and protection against secondary infection. This review highlights the critical role of advanced wound dressings in improving medical outcomes for injured military personnel. The potential of these technologies to reduce complications, enhance healing rates, and ultimately save lives underscores their growing importance in modern battlefield medicine. Full article

The Set Coverage Problem (SCP) is an important combinatorial optimization problem known to be NP-complete. The use of metaheuristics to solve the SCP includes different algorithms. In particular, binarization techniques have been explored to adapt metaheuristics designed for continuous optimization problems to the binary domain of the SCP. In this work, we present a new approach to solve the SCP based on the Secretary Bird Optimization Algorithm (SBOA). This algorithm is inspired by the natural behavior of the secretary bird, known for its ability to hunt prey and evade predators in its environment. Since the SBOA was originally designed for optimization problems in continuous space and the SCP is a binary problem, this paper proposes the implementation of several binarization techniques to adapt the algorithm to the discrete domain. These techniques include eight transfer functions and five different discretization methods. Taken together, these combinations create multiple SBOA adaptations that effectively balance exploration and exploitation, promoting an adequate distribution in the search space. Experimental results applied to the SCP together with its variant Unicost SCP and compared to Grey Wolf Optimizer and Particle Swarm Optimization suggest that the binary version of SBOA is a robust algorithm capable of producing high quality solutions with low computational cost. Given the promising results obtained, it is proposed as future work to focus on complex and large-scale problems as well as to optimize their performance in terms of time and accuracy. Full article

This study presents a semi-random mobility model called Semi-Random Elliptical Movement (SREM), developed for relay-oriented Flying Ad Hoc Networks (FANETs). In FANETs, node distribution has a major impact on network performance, making the mobility model a critical design element. While random models offer simplicity and path diversity, they often result in unstable relay paths due to inconsistent node placement. In contrast, planned path models provide alignment but lack the flexibility needed in dynamic environments. SREM addresses these challenges by enabling nodes to move along elliptical trajectories, combining autonomous movement with alignment to the relay path. This approach encourages natural node concentration along the relay path while maintaining distributed mobility. The spatial characteristics of SREM have been analytically defined and validated through the Monte Carlo method, confirming stable node distributions that support effective relaying. Computer simulation results show that SREM performs better than general mobility models that do not account for relaying, offering more suitable performance in relay-focused scenarios. These findings suggest that SREM provides both structural consistency and practical effectiveness, making it a strong candidate for improving the realism and reliability of FANET simulations involving relay-based communication. Full article

Under the dual challenges of global energy crisis and climate change, the building sector, as a major carbon emitter consuming 33% of global primary energy, has seen its energy efficiency optimization become a critical pathway towards achieving carbon neutrality goals. The Window-to-Wall Ratio (WWR), serving as a core parameter in building envelope design, directly influences building energy consumption, with its optimized design playing a decisive role in balancing natural daylighting, ventilation efficiency, and thermal comfort. This study focuses on the traditional One-Seal dwellings (Yikeyin) in Kunming, China, establishing a dynamic wind field-thermal environment coupled analysis framework to investigate the impact mechanism of window dimensions (WWR and aspect ratio) on indoor thermal comfort under natural wind conditions in transitional climate zones. Utilizing the Grasshopper platform integrated with Ladybug, Honeybee, and Butterfly plugins, we developed parametric models incorporating Kunming’s Energy Plus Weather meteorological data. EnergyPlus and OpenFOAM were employed, respectively, for building heat-moisture balance calculations and Computational Fluid Dynamic (CFD) simulations, with particular emphasis on analyzing the effects of varying WWR (0.05–0.20) on temperature-humidity, air velocity, and ventilation efficiency during typical winter and summer weeks. Key findings include, (1) in summer, the baseline scenario with WWR = 0.1 achieves a dynamic thermal-humidity balance (20.89–24.27 °C, 65.35–74.22%) through a “air-permeable but non-ventilative” strategy, though wing rooms show humidity-heat accumulation risks; increasing WWR to 0.15–0.2 enhances ventilation efficiency (2–3 times higher air changes) but causes a 4.5% humidity surge; (2) winter conditions with WWR ≥ 0.15 reduce wing room temperatures to 17.32 °C, approaching cold thresholds, while WWR = 0.05 mitigates heat loss but exacerbates humidity accumulation; (3) a symmetrical layout structurally constrains central ventilation, maintaining main halls air changes below one Air Change per Hour (ACH). The study proposes an optimized WWR range of 0.1–0.15 combined with asymmetric window opening strategies, providing quantitative guidance for validating the scientific value of vernacular architectural wisdom in low-energy design. Full article

One of the fundamental goals of contemporary mobility is to optimize transport processes in urban areas. The solution in this area seems to be the implementation of the idea of sustainable transport systems based on the Smart City concept. The article presents a case study—an assessment of the possibilities of changing mobility habits based on the idea of sustainable urban transport, taking into account the criterion of energy consumption of individual means of transport. The analyses are based on a comparison of selected means of transport occurring in the urban environment according to several key parameters for the optimization and efficiency of transport processes, i.e., cost, time, travel comfort, and impact on the natural environment, while simultaneously linking them to the criterion of energy consumption of individual means of transport. The analyzed parameters currently constitute the most important group of challenges in the area of shaping and planning optimal and sustainable urban transport. The presented research was used to indicate the connections between various areas of optimization of the transport process and the energy efficiency of individual modes of transport. Analyses have shown that the least time-consuming process of urban mobility is associated with the highest level of CO₂ emissions and, at the same time, the highest level of energy efficiency. However, combining public transport with other means of transport can meet most of the transport expectations of city residents, also in terms of energy optimization. The research results presented in the article can contribute to the creation of a strategy for the development of the transport network based on the postulates of increasing the optimization and efficiency of individual means of transport in urban areas. At the same time, recognizing the criterion of energy intensity of means of transport as leading in the development of sustainable urban mobility. Thus, confirming the important role of existing transport systems in the process of shaping and planning sustainable urban mobility in accordance with the idea of Smart City. Full article

Bacterial communities within the female upper genital tract may influence the risk of ovarian cancer. In this retrospective cohort pilot study, we aim to detect different communities of bacteria between ovarian cancer and normal controls using topic modeling, a natural language processing tool. RNA was extracted and analyzed using the VITCOMIC2 pipeline. Topic modeling assessed differences in bacterial communities. Idatuning identified an optimal latent topic number and Latent Dirichlet Allocation (LDA) assessed topic differences between high-grade serous ovarian cancer (HGSOC) and controls. Results were validated using The Cancer Genome Atlas (TCGA) HGSOC dataset. A total of 801 unique taxa were identified, with 13 bacteria significantly differing between HGSOC and normal controls. LDA modeling revealed a latent topic associated with HGSOC samples, containing bacteria Escherichia/Shigella and Corynebacterineae. Pathway analysis using KEGG databases suggest differences in several biologic pathways including oocyte meiosis, aldosterone-regulated sodium reabsorption, gastric acid secretion, and long-term potentiation. These findings support the hypothesis that bacterial communities in the upper female genital tract may influence the development of HGSOC by altering the local environment, with potential functional implications between HGSOC and normal controls. However, further validation is required to confirms these associations and determine mechanistic relevance. Full article

Autumn fern, Dryopteris erythrosora, is the most marketed temperate fern in the world. The rapid increase and spread of this recently naturalized fern in North America was determined and mapped using 76 herbarium specimen records and 2553 Research Grade iNaturalist posts. In 2008, it was recorded in two states, but by 2025, it was found in 25 states in the eastern United States and Ontario, Canada. At the end of 2017, there had been only 23 iNaturalist posts, but this grew to 511 by the end of 2020 and 2553 by May 2025. The great increase in the number of iNaturalist posts is thought to be due to the real geographic spread and an actual increase in the abundance of the fern, as well as recognition of the fern by iNaturalists, and the increase in the number of iNaturalists. The spread and great increase are probably related to the high level of marketing, which introduces plants to the environment, and to biological characteristics of the fern, including apogamy and polyploidy, and possibly natural enemy release, which allows it to flourish in new environments and to displace native plants. This novel study demonstrated citizen science’s (iNaturalist’s) great value in detecting the naturalization and spread of alien plants. Full article

Microplastic (MP) pollution is an emerging concern in ruminant production, as animals are exposed to MPs through air, water, and feeds. Ruminants play a key role in MP transmission to humans via animal products and contribute to MP return to agricultural soil through excreta. Identifying effective strategies to mitigate MP pollution in the ruminant sector is crucial. A promising yet understudied approach involves the potential ability of rumen microbiota to degrade MPs. This study investigated the in vitro ruminal degradation of three widely distributed MPs—low-density polyethylene (LDPE), polyethylene terephthalate (PET), and polyamide (PA)—over 24, 48, and 72 h. PET MP exhibited the highest degradation rates (24 h: 0.50 ± 0.070%; 48 h: 0.73 ± 0.057%; and 72 h: 0.96 ± 0.082%), followed by LDPE MP (24 h: 0.03 ± 0.020%; 48 h: 0.25 ± 0.053%; and 72 h: 0.56 ± 0.066%) and PA MP (24 h: 0.10 ± 0.045%; 48 h: 0.02 ± 0.015%; and 72 h: 0.14 ± 0.067%). These findings suggest that the ruminal environment could serve as a promising tool for LDPE, PET, and PA MPs degradation. Further research is needed to elucidate the mechanisms involved, potentially enhancing ruminants’ natural capacity to degrade MPs. Full article

In rapidly urbanizing environments, environmental stressors—such as air pollution, noise, heat, and green space depletion—substantially exacerbate public health burdens, contributing to the global rise of non-communicable diseases, particularly hypertension, cardiovascular disorders, and mental health conditions. Despite expanding research on green spaces and health (+76.9%, 2019–2025) and optimization and algorithmic approaches (+63.7%), the compounded and synergistic impacts of these stressors remain inadequately explored or addressed within current urban planning frameworks. This study presents a Mixed Methods Systematic Review (MMSR) to investigate the potential of AI-driven urban design optimizations in mitigating these multi-scalar environmental health risks. Specifically, it explores the complex interactions between urbanization, traffic-related pollutants, green infrastructure, and architectural intelligence, identifying critical gaps in the integration of computational optimization with nature-based solutions (NBS). To empirically substantiate these theoretical insights, this study draws on longitudinal 24 h dynamic blood pressure (BP) monitoring (3–9 months), revealing that chronic exposure to environmental noise (mean 79.84 dB) increases cardiovascular risk by approximately 1.8-fold. BP data (average 132/76 mmHg), along with observed hypertensive spikes (systolic > 172 mmHg, diastolic ≤ 101 mmHg), underscore the inadequacy of current urban design strategies in mitigating health risks. Based on these findings, this paper advocates for the integration of AI-driven approaches to optimize urban environments, offering actionable recommendations for developing adaptive, human-centric, and health-responsive urban planning frameworks that enhance resilience and public health in the face of accelerating urbanization. Full article