Variety Of Environmental Conditions Research Articles

Hygrothermal Properties of Tibetan Paper: The Effects of Air Pressure and Printed Scriptures

To determine the optimal preservation environment for Tibetan paper artifacts at high altitudes, it is essential to characterize the hygrothermal properties of the Tibetan paper material, which have not been previously reported. To fill this gap, the thermal conductivity test, static gravimetric test and cup test were carried out on Tibetan paper with and without scriptures (TPWS/TPWOS) under varying pressures (1.00, 0.80, and 0.60 atm). Results indicated that while air pressure did not affect thermal conductivity, it significantly influenced vapor permeability and equilibrium moisture content (EMC). A reduction of 0.1 atm air pressure resulted in an approximate 0.0045 kg/kg increase in equilibrium moisture content (EMC) and a 2.6 × 10−11kg/(m·s·Pa) increase in vapor permeability. Scriptures printed on the paper with ink affected the composition and pore structure of the paper, resulting in a higher thermal conductivity of 12.2% of the TPWS as compared to TPWOS. The TPWS had lower EMC performance and vapor permeability as compared to TPWOS. Furthermore, TPWS exhibited lower EMC and vapor permeability than TPWOS, with the difference in EMC decreasing and the difference in vapor permeability increasing as air pressure decreased. The fundamental hygrothermal data provided in this study are crucial for assessing the stability and durability of Tibetan paper artifacts under varied environmental conditions, thereby informing scientific preservation strategies to mitigate the potential environmental damage to the Tibetan paper artifacts.

What is left in miombo woodlands? Rarity and commonness of woody species, commercial timber species, and lawful harvestable diameter classes.

Mozambican miombo woodlands (MWs) have been experiencing severe anthropogenic threats, recognized to have an impact on plant species distribution, occurrence, diversity, and rarity patterns. Based on 3725 0.1ha plots distributed across the country's MWs, this study aimed to assess the species rarity and commonness, protection status, and availability of commercial timber in MWs under varied environmental conditions. Results show that, out of the 515 tree and shrub species found, 45% were rare, while just 10% were highly protected. Nine of the 112 commercial miombo species were not observed, and 15 were rare. Commercial-sized trees of the top nine desired species were extremely rare, some species had only 1 tree per 20ha and stem forms unsuitable for sawmilling. Selective overharvesting has also affected trees with no minimum felling diameter. Brachystegia spiciformis, B. boehmii, and Julbernardia globiflora stood out among the few timber species with commercially viable populations. MWs in the semi-arid ecoregion have lower species richness, fewer commercially viable populations, and a higher number of poorly protected species (51%). The rainy ecoregion has the highest percentage of poorly protected species (61%). Based on the results obtained, it was recommended that (1) timber harvesting should be restricted to the humid ecoregion, prohibited for the timber species that were either absent or rare, and halted for the top nine desired species; (2) except B. spiciformis, B. boehmii, and J. globiflora, MWs should preferably undergo a forest closure period corresponding to at least one cutting cycle; (3) to ensure long-term viability, a minimum harvestable density for commercial-sized trees should be determined for each species.

The Influence of Dietary Supplements on Exercise-Induced Gut Damage and Gastrointestinal Symptoms: A Systematic Review and Meta-Analysis

Endurance exercise, especially under heat stress, temporarily compromises the integrity of the intestinal barrier in healthy individuals. Consequently, there is growing interest in developing effective dietary strategies to alleviate exercise-induced gastrointestinal symptoms and gut damage. This meta-analysis investigated the effects of dietary supplements on mitigating these challenges. The search was performed in November 2024 following PRISMA guidelines, and 26 peer-reviewed studies were included across three meta-analyses: (1) gastrointestinal symptoms, (2) circulating intestinal fatty acid-binding protein (i-FABP), and (3) exercise performance. The moderating effect of variables was assessed via sub-group analysis and meta-regression. Overall, there was no pooled effect of supplement interventions on gastrointestinal symptoms (Hedges’ g = 0.42, 95% CI −0.17: 1.02, p = 0.15), and probiotics had a moderate significant effect for gastrointestinal symptoms (Hedges’ g = −0.62, 95% CI −1.01; 1.01, p = 0.05). There was a significant increase in i-FABP concentrations pre- to post exercise (∆ 106%; Hedges’ g = 1.01, 95% CI 0.63; 1.38, p = 0.01). There were no pooled or sub-group differences for exercise performance for any supplements (p = 0.53). Moderate-to-large heterogeneity was observed across studies (I2 ≥ 58.6%), and candidate moderators (exercise duration, modality, and environmental temperature) had no significant effect on any outcomes (p > 0.05). A significant increase in circulating i-FABP during exercise was observed. However, when examining the effects of different supplement categories, although significance was observed for a select few supplements, the changes in i-FABP, gastrointestinal symptoms, and exercise performance were outside of clinical relevance. Although probiotics showed a moderate significant effect for gastrointestinal symptoms, the conflicting findings across studies may have been due to inadequate control of confounding variables across studies. Further research is required to assess the alternative dietary supplements’ effects on gastrointestinal health and exercise performance, particularly under varied environmental conditions, where more rigorous control for cofounding factors is implemented.

An Improved Gaussian Mixture Model-Based Data Normalization Method for Removing Environmental Effects on Damage Detection of Structures

In structural health monitoring, effectively eliminating the influence of variable environmental conditions on modal frequencies remains a critical challenge for accurate damage identification. Nonstationary and nonlinear variations in modal frequencies, commonly induced by environmental changes, tend to overshadow the effects caused by structural damage. An improved Gaussian mixture model (GMM) is proposed in this paper to normalize nonlinear and nonstationary frequency data, enabling effective structural damage detection under variable environmental conditions. As the effectiveness of the GMM is highly influenced by the initial parameter values used in the expectation-maximization (EM) algorithm, a subdomain division strategy is first presented to determine the unique initial values of the GMM parameters. Through the application of the EM algorithm, the GMM is constructed simply and efficiently through the determined initial parameters. Next, on the basis of the constructed GMM, the modal frequency data are normalized to extract damage features that remain unaffected by environmental variations. Subsequently, Hotelling’s T2 statistic and its cumulative form are calculated for the damage features and designated as the damage indicators; meanwhile, the corresponding damage thresholds are also calculated according to the kernel density estimation technique. To validate the proposed method, two case studies are conducted: one with a numerical mass-spring system and the other with a real bridge structure. Results show that environmental influences no longer impact the normalized frequency data, and the cumulative statistic demonstrates outstanding accuracy in identifying structural damage.

Key environmental predictors as drivers of avifauna assemblages in Ghana’s coastal ecosystems

Avian assemblages are not only influenced by spatial factors but also by temporal variations in environmental conditions, creating dynamic patterns of bird presence in a given area. This study examined environmental elements affecting bird assemblages in Ghana's coastal ecosystems. We conducted point transect sampling along a 15-km coastal stretch, analyzing bird abundance, richness, and diversity in relation to microclimate and urbanization. Humidity and wind speed had a significant negative relationship with bird abundance as well as time of day (morning) having a negative relationship. Mean bird richness, diversity, were significantly higher in natural shoreline areas compared to urbanized ones. Bird abundance and seasonality were positive related where wet season was characterized by higher bird numbers which can be attributed to the favorability of the wet season in terms of food availability and habitat suitability. Indicator Species Analysis identified nineteen species significantly associated specific habitat characterization, with eleven species linked to lagoon adjacent shorelines. These results show the relationship between environmental factors and avian assemblages in coastal ecosystems, highlighting impacts of human disturbance and climate-related factors and the importance of pristine ecosystems in biodiversity conservation.

Quercus cerris Leaf Functional Traits to Assess Urban Forest Health Status for Expeditious Analysis in a Mediterranean European Context.

In the Mediterranean basin, urban forests are widely recognized as essential landscape components, playing a key role in nature-based solutions by enhancing environmental quality and providing a range of ecosystem services. The selection of woody plant species for afforestation and reforestation should prioritize native species that align with the biogeographical and ecological characteristics of the planting sites. Among these, Quercus cerris L. (Turkey oak) is considered a promising candidate for urban reforestation. However, its fitness within urban forest environments remains poorly understood. This study aimed to identify suitable leaf functional traits for assessing the response of Q. cerris in urban forests and to analyze the main climatic variables influencing its performance in urban contexts. We also proposed practical, rapid monitoring tools to compare urban and natural forests across different seasons. The results demonstrated that Q. cerris experiences significant water stress in urban forests due to the combined effects of drought and high temperatures. To find the tools to mitigate this stress, the differences between leaf traits such as specific leaf area, thickness, and the contents of chlorophyll, anthocyanins, and flavonols in urban and natural forests were analyzed. Our findings underscore the high adaptability of Q. cerris to varied climatic and environmental conditions. This study provides a practical method for rapidly assessing the responses of tree species to climate change. In the future, this approach will be tested on other native species that are characteristic of Mediterranean forest ecosystems to help with choosing afforestation and reforestation strategies.

Climate Change Effects on Agricultural Pests: Aphids, Diabrotica Balteata, and Asian Corn Borer in Plant-Pest Interactions and Pest Dynamics in the Context of Achieving SDGs

Objective: This study found that climate change affects pest biology and plant relationships through changes in temperature, precipitation, CO2 concentration, and wind patterns. Learn about these consequences and monitor their evolution to reduce their potential harm to farming and environmental sustainability. Method: The research incorporates recent experiments involving different pest families. These studies investigate the influence of climate change on pests in relation to their body size, geographic distribution, synchronization with predators, and survival during overwintering periods. Data collection involves observations of pest behavior, plant interactions, and reproductive success across varied environmental conditions. Results and Discussion: The findings reveal that elevated CO2 concentrations lead to changes in the carbon-to-nitrogen (C:N) ratio of plants, affecting the size of certain pests, while others show no significant size alteration. Altered precipitation patterns contribute to pest washout from plants and reduce overwintering survival rates. Furthermore, disruptions in the survival of pest generations have been observed. However, these results are mixed; some pest types benefit from climate changes, while others suffer, alongside corresponding impacts on plant health. Research Implications: The report recommends adaptive agricultural management and pest monitoring to protect crop production from climate change. We must understand these relationships to create solutions to reduce climate change's harmful effects on ecosystems and ensure long-term food security. Originality/Value: This research adds to climate change and pest control literature by revealing how environmental changes affect pest species and their biological interactions with plants. Results show need for customized pest control tactics that account for climatic change.

Next-Generation Point-of-Care Diagnostics: Silver Nanoparticle-Enhanced 3D-Printed Multiplex Electrochemical Biosensor for Detecting Dengue and Chikungunya Viruses.

In recent years, the increasing prevalence of viral infections such as dengue (DENV) and chikungunya (CHIKV) has emphasized the vital need for new diagnostic techniques that are not only quick and inexpensive but also suitable for point-of-care and home usage. Existing diagnostic procedures, while useful, sometimes have limits in terms of speed, mobility, and price, particularly in resource-constrained environments and during epidemics. To address these issues, this study proposes a novel technique that combines 3D printing technology with electrochemical biosensors to provide a highly sensitive, user-friendly, and customizable diagnostic platform. This study focuses on a unique 3D-printed electrode cassette made with fused deposition modeling technology, which ensures strong structural alignment and improved performance under a variety of environmental conditions. When combined with paper-based electrodes loaded with silver nanoparticles, the platform dramatically enhances the detection sensitivity and reliability. The biosensor uses cyclic voltammetry and electrochemical impedance spectroscopy to detect DENV and CHIKV antigens within a linear range of 1 × 102 to 1 × 106 ng/mL. Results were delivered in 20 s and stable for 30 days. The device's performance was verified by testing with blood serum samples containing both DENV and CHIKV antigens, demonstrating its capacity to properly identify coinfections. This novel diagnostic tool represents a huge step forward in accessible and efficient healthcare solutions, bridging important gaps in the global battle against arboviral infections.

Tree-volume and forest age increase bat species diversity in boreal urban landscape

ContextGiven the rate at which humankind is changing habitats, it is essential to understand its impact on the surrounding nature and biota. The intensification of human activities and the fragmentation of forested habitats now affect many taxonomic groups, such as bats, which are largely dependent on forests (e.g. roosting sites and feeding areas). Northern Europe is generally considered very forested but intensive land-use changes, caused by urbanization and forestry, contribute to forest fragmentation and loss of biodiversity. Land-use changes are classified as the biggest threats for bats, but especially in the boreal zone, the impact of these environmental changes is not yet known at a sufficient level.ObjectivesWe explored how bats (species occurrences and activity) were influenced by forestry and urbanization, and by landscape variables (tree volume, percentage of deciduous trees, vicinity of water bodies and built areas).MethodsWe used a bioacoustic dataset on bats from Finnish capital area (20 × 20 km, 51 sites) recorded during the summer season (May – September) to evaluate how different habitat classes (old forest, young economical forest, rural area, suburban and urban) and landscape variables influence activity and species richness of bats across this region. We used Hierarchical Modelling of Species Communities (HMSC) approach to characterize the responses of species. We investigated with two different models: one focusing on species occurrences and the second one focusing on relative activity.ResultsOur findings indicate a distinct pattern, with the highest species richness in old forests, followed by a gradual decline with increased land-use intensity. Species-specific responses to habitat classes were evident in both presence and activity. Most of the species showed negative responses to built area, either by their presence or activity. Key landscape variables further underscored species-specific variations in different environmental conditions. Additionally, our study observed temporal dynamics, revealing species-specific variations in occurrences across the bats’ active season.ConclusionOur study sheds light on the complex dynamics of bats in diverse landscapes, emphasizing the crucial role of both habitats and specific environmental factors in conservation. Old natural forests emerge as vital for bats, while land-use changes, especially urbanization, pose challenges highlighting the need for continuous monitoring and strategic conservation actions.

Classifying crash causation patterns in 2-vehicle collisions between autonomous and conventional vehicles.

This study aims to investigate the causes of 2-vehicle collisions involving an autonomous vehicle (AV) and a conventional vehicle (CV). Prior research has primarily focused on the causes of crashes from the perspective of AVs, often neglecting the interactions with CVs. To address this limitation, the study proposes a classification framework for crash causation patterns in 2-vehicle collisions involving an AV and a CV, considering their interactions. The framework categorizes the crash causation patterns into 5 distinct types: (1) failure of the AV system, (2) failure of takeover control, (3) driver error after takeover, (4) CV failure to adapt to unforeseen changes in AV behaviors, and (5) other factors related to the CV. Utilizing the AV crash data set proposed by Zheng etal., this study extracted 450 two-vehicle collisions involving AVs and CVs for our analysis. Our analysis reveals that the majority of 2-vehicle collisions are triggered by CVs, specifically identified in patterns 4 and 5. Pattern 4 is the primary crash causation factor, accounting for 55% of total collisions. The leading contributing factor to pattern 4 is the improper response of CVs to AVs stopping. There are notable variations in crash injury severity, collision type, and environmental conditions across different causation patterns. Crashes stemming from human drivers' errors (patterns 3, 4, and 5) are more likely to result in moderate to severe injuries. Specifically, pattern 4 notably exhibits the highest likelihood of causing rear-end collisions, whereas patterns 1 and 5 are more prone to causing side collisions. Additionally, crashes associated with pattern 4 are more frequently observed in locations with traffic controls or obstacles. Based on our findings, we propose several recommendations for manufacturers to enhance AV safety performance. These include minimizing planning errors in autonomous driving algorithms, improving communication abilities between AVs and other road users for smoother interactions and better anticipation of actions, and providing specialized driver training for navigating mixed environments with both AVs and CVs.

Prediction of coastal barren plant species richness and functional diversity by environmental variability across scales

AbstractQuestionsThe relationships between environmental heterogeneity and plant diversity may be negative or neutral at fine spatial scales but positive across broader areas. How do the relationships between spatial environmental variability and mean environmental conditions, plant species richness and functional diversity change across spatial scales?LocationCoastal barrens landscape in Nova Scotia, eastern Canada.MethodsWe sampled plant species composition and environmental variables in nested areas at three scales: 0.25 m2, 1 m2 and 50 m2. At each scale, subsamples of environmental variables (including elevation, soil moisture and depth) were used to calculate average and standard deviation; plant species richness was also determined for each sample. Plant traits at the species level were used to calculate functional dispersion for each of five traits (specific leaf area, leaf dry matter content, leaf thickness, plant height and canopy width) and a combined index of total functional dispersion. Functional dispersion and species richness were predicted at each scale by environmental variables using linear mixed models.ResultsEnvironmental heterogeneity had low predictive power for plant diversity at the 0.25‐m2 scale but was unimodally related to species richness and functional‐diversity variables at the 1‐m2 scale. The shape of the unimodal relationships suggested a leveling off of diversity at higher levels of environmental variability rather than a decline in diversity (monotonic or asymptotic). There was a strong positive relationship between elevation (topographic) variability and species richness at the 50‐m2 scale. Functional dispersion was most strongly related to environmental variables at the 1‐m2 scale.ConclusionsPositive or non‐linear asymptotic relationships between environmental heterogeneity, richness and functional diversity at the 1‐m2 scale provide some support for niche‐based explanations of species coexistence in plant neighborhoods. At broader sampling extents, greater topographic heterogeneity may allow distinct plant communities to co‐occur within a sample, increasing richness but not functional diversity because functional diversity in leaf and canopy traits are already high within each plant community.

Biochar in the Remediation of Organic Pollutants in Water: A Review of Polycyclic Aromatic Hydrocarbon and Pesticide Removal.

This review explores biochar's potential as a sustainable and cost-effective solution for remediating organic pollutants, particularly polycyclic aromatic hydrocarbons (PAHs) and pesticides, in water. Biochar, a carbon-rich material produced from biomass pyrolysis, has demonstrated adsorption efficiencies exceeding 90% under optimal conditions, depending on the feedstock type, pyrolysis temperature, and functionalization. High surface area (up to 1500 m2/g), porosity, and modifiable surface functional groups make biochar effective in adsorbing a wide range of contaminants, including toxic metals, organic pollutants, and nutrients. Recent advancements in biochar production, such as chemical activation and post-treatment modifications, have enhanced adsorption capacities, with engineered biochar achieving superior performance in treating industrial, municipal, and agricultural effluents. However, scaling up biochar applications from laboratory research to field-scale wastewater treatment poses significant challenges. These include inconsistencies in adsorption performance under variable environmental conditions, the high cost of large-scale biochar production, logistical challenges in handling and deploying biochar at scale, and the need for integration with existing treatment systems. Such challenges impact the practical implementation of biochar-based remediation technologies, requiring further investigation into cost-effective production methods, long-term performance assessments, and field-level optimization strategies. This review underscores the importance of addressing these barriers and highlights biochar's potential to offer a sustainable, environmentally friendly, and economically viable solution for large-scale wastewater treatment.

Adapting cucurbits to diverse environments: Insights from GEI studies

Recently, there has been increasing concern about crop failures and yield gaps attributed to climate change, as certain genotypes fail to achieve the desired yields or quality due to variations in external temperatures. To address this issue, breeders are working to develop climate-resilient varieties by incorporating relevant genes into cultivars or genotypes or by utilizing desirable source plants in the breeding process. Additionally, management practices are being implemented to mitigate environmental impacts. Multi-environmental trials (METs) are commonly employed by breeders to assess the adaptability of specific genotypes or cultivars across different locations and time periods. The data collected from these trials is then analyzed using stability statistical models designed for stability analysis, which allows for the evaluation of cultivar or genotype performance under varied environmental conditions. Over the past six decades, there has been a significant focus on modeling genotype-environment interactions (GEI), leading to the development of various mathematical methods and models to decipher GEI in METs, often referred to as "stability analyses." In the era of omics, phenomics techniques have emerged as valuable tools for screening morphological and physiological variations in genotypes resulting from environmental factors. This review emphasizes the importance of GEI in cucurbits, highlighting how environmental stress can alter physiological traits such as stomatal conductance, single leaf area, rooting depth, and membrane composition. Furthermore, it notes the accumulation of stress-related proteins under stress conditions, underscoring the significance of understanding GEI for effective crop management and breeding programs.

Temporal resolution trumps spectral resolution in UAV-based monitoring of cereal senescence dynamics

BackgroundSenescence is a complex developmental process that is regulated by a multitude of environmental, genetic, and physiological factors. Optimizing the timing and dynamics of this process has the potential to significantly impact crop adaptation to future climates and for maintaining grain yield and quality, particularly under terminal stress. Accurately capturing the dynamics of senescence and isolating the genetic variance component requires frequent assessment as well as intense field testing. Here, we evaluated and compared the potential of temporally dense drone-based RGB- and multispectral image sequences for this purpose. Regular measurements were made throughout the grain filling phase for more than 600 winter wheat genotypes across three experiments in a high-yielding environment of temperate Europe. At the plot level, multispectral and RGB indices were extracted, and time series were modelled using different parametric and semi-parametric models. The capability of these approaches to track senescence was evaluated based on estimated model parameters, with corresponding parameters derived from repeated visual scorings as a reference. This approach represents the need for remote-sensing based proxies that capture the entire process, from the onset to the conclusion of senescence, as well as the rate of the progression.ResultsOur results indicated the efficacy of both RGB and multispectral reflectance indices in monitoring senescence dynamics and accurately identifying key temporal parameters characterizing this phase, comparable to more sophisticated proximal sensing techniques that offer limited throughput. Correlation coefficients of up to 0.8 were observed between multispectral (NDVIred668-index) and visual scoring, respectively 0.9 between RGB (ExGR-index) and visual scoring. Sub-sampling of measurement events demonstrated that the timing and frequency of measurements were highly influential, arguably even more than the choice of sensor.ConclusionsRemote-sensing based proxies derived from both RGB and multispectral sensors can capture the senescence process accurately. The sub-sampling emphasized the importance of timely and frequent assessments, but also highlighted the need for robust methods that enable such frequent assessments to be made under variable environmental conditions. The proposed measurement and data processing strategies can improve the measurement and understanding of senescence dynamics, facilitating adaptive crop breeding strategies in the context of climate change.

Heterogeneous conservation corridors of remnant vegetation protect biodiversity in South African timber mosaics

AbstractIt is urgent now to place greater emphasis on harmonising conservation of indigenous biodiversity with food and fibre production. This is especially important in countries like South Africa which support high levels of irreplaceable biodiversity. The local timber industry has responded to this challenge by retaining large-scale networks of conservation corridors of historic ecosystems in the forestry landscape. The corridors consist mostly of grassland, with patches of indigenous forest, thickets, wetlands, ponds, and rivers. The motivation is to future proof compositional and functional biodiversity for ecological resilience in these production environments in a rapidly changing world. We synthesise here the substantial evidentiary research on the effectiveness of conservation corridors in plantation forestry-dominated landscapes in the Maputaland-Pondoland-Albany biodiversity hotspot. We focus on six emergent themes: 1. corridor dimensions, orientation, and connectivity, 2. heterogeneity at different spatial scales, 3. maintaining aquatic and terrestrial habitat quality in the conservation corridors, 4. biodiversity value of conservation corridors relative to protected areas, 5. the plantation matrix, and 6. assessment of corridor network performance. Results show the importance of prioritising large, high quality conservation corridors, especially those with a high number of natural features and variety of environmental conditions, both terrestrial and aquatic. Alien clearing, grazing control, and appropriate fire regimes should be prioritised in these corridors. Where possible we need to retain, restore, or replicate the natural ecological regimes. Overall, this conservation approach in commercial forestry landscapes helps to conserve indigenous biodiversity and ecosystem integrity, improves connectivity across afforested landscapes while also having sustainable timber production, thereby safeguarding the resilience of these working landscapes well into the future.

Invasion stress mitigates climate stress in a brackish marsh amphipod

Abstract Organisms in coastal brackish ecosystems face not only highly variable environmental conditions, but the intensity and stochasticity of these environmental conditions are anticipated to increase due to climate change. While environmental changes are often presented unilaterally as stressors, there are some anthropogenic environmental transformations, such as the introduction of habitat forming plant species, that may mitigate physiological stress imposed by warming. In Suisun Marsh in the California Delta, native plant canopies allow light and heat to penetrate to the understory yet the canopies of the introduced Phragmites australis reed block out sunlight and heat for organisms living below. We set out to understand the physiological performance of mud‐dwelling invertebrates in this context: can invasion stress mitigate climate stress? We raised field collected Gammarus amphipods in the laboratory under simulated ‘native canopy’ and ‘Phragmites canopy’ temperature/light conditions based on data from our field environmental loggers. We assessed survival, body mass, fecundity, glycogen and protein content every 2 weeks from our lab population of amphipods. We found that amphipods raised under the Phragmites conditions had better survival, greater stores of protein, and similar body mass and stores of glycogen, which could positively impact available food resource quality for juvenile fishes. We support this with field data showing higher use of Phragmites canopies by amphipods, especially in the water column, across the year of sampling. Synthesis and applications: Understanding the potential benefits of Phragmites as climate stress refugia can inform management decisions around its mitigation in future restoration.

Enhancing IoNT performance with fog computing: A hybrid architecture for real-time data processing

<p>The rapid evolution of the Internet of Nano Things (IoNT) and Fog Computing presents new opportunities for creating advanced smart systems that are both efficient and responsive. Integrating IoNT with Fog Computing offers a powerful paradigm that can address the limitations of cloud-centric architectures, particularly in terms of latency, bandwidth, and real-time processing. The paper explores the synergistic combination of IoNT and Fog Computing, focusing on the development of a hybrid architecture that leverages the proximity and computational capabilities of fog nodes to process data generated by nanoscale devices. Key challenges such as resource management, data processing efficiency, and security concerns are addressed in this study. The proposed architecture not only enhances the performance of smart systems by reducing latency and optimizing resource utilization but also ensures robust security and privacy for the vast amounts of generated data. A comprehensive dataset was generated to assess the integration of the IoNT with Fog Computing, focusing on environmental parameters such as Temperature, Humidity, and Wind Speed, as collected from five IoNT sensors. Python was employed to generate and augment this dataset, ensuring the accurate representation of varied environmental conditions. The data transmission between IoNT sensors and FogNode_1 successfully demonstrated the framework’s ability to capture and process real-time environmental information. Aggregated data from the fog and cloud layers confirmed the system’s efficiency in reducing latency and maintaining data integrity. Furthermore, the implementation of advanced communication protocols and effective resource management highlights the robustness of the integration, contributing to the real-time monitoring and decision-making processes in environmental applications. As well as, this study compares Fog Computing and Cloud Computing, concluding that Fog Computing offers significant advantages in areas like latency, bandwidth utilization, resource efficiency, security, privacy, real-time processing, and edge intelligence. These benefits make Fog Computing particularly suitable for applications requiring low latency, local data processing, enhanced security, and the ability to leverage edge intelligence. While Cloud Computing may have advantages in certain areas, Fog Computing’s overall performance and versatility make it a compelling choice for those seeking to optimize their computing infrastructure. This research aims to pave the way for more resilient and intelligent smart systems that can operate effectively in various domains, including healthcare, environmental monitoring, and industrial automation.</p>

Facial Detection and Recognition Analysis using Ontology-Driven Machine Learning Model

Facial detection and recognition technologies have achieved remarkable advancements through the integration of ontology-driven machine learning (ML). This study examines how ontology structured framework for representing domain-specific knowledge to enhance the robustness, accuracy, and interpretability of ML models, particularly Convolutional Neural Networks (CNNs), in the field of facial detection and recognition. Acknowledging the limitations of traditional ML methods, such as data inefficiency, inadequate generalization, and insufficient interpretability, this research addresses critical challenges, including semantic discrepancies, variations in environmental conditions, and ethical considerations. By leveraging ontology, the study aims to provide semantic enrichment, contextual adaptation, and data augmentation for ML models. A hybrid methodology is introduced that effectively integrates ontology with CNNs, in conjunction with the Viola-Jones and Eigenfaces algorithms, to improve performance in facial recognition tasks. The study utilizes comprehensive datasets such as CelebA and MegaFace, employing rigorous preprocessing and training processes that incorporate ontology-based feedback mechanisms. The results demonstrated significant improvements in accuracy, robustness, and explainability. Ontology-CNN models outperform traditional approaches in managing variations in facial attributes and environmental conditions. This study concludes that ontology-based frameworks present a promising avenue for developing efficient and ethically responsible facial recognition systems. Future research should focus on exploring the scalability of these models across diverse demographic contexts and further addressing ethical considerations related to privacy and fairness.

Short‐Term Responses of Native (Perna viridis, Linnaeus 1758) and Non‐Native (Mytella strigata, Hanley 1843) Mussels to Independent and Combined Effects of Lowered pH Level and Elevated Temperature

ABSTRACTChanges in environmental conditions can influence the success of marine biological invasions. This study assessed the independent and combined acute short‐term effects of increased temperature (OW) and lowered pH (OA) simulating future ocean conditions on a native, Perna viridis, and non‐native, Mytella strigata, mussel species. There were four treatment combinations: Future (combination of ocean warming and ocean acidification), Ambient conditions, ocean acidification (OA), and ocean warming (OW). Survival and byssus thread regeneration in all treatments were measured daily for 7 days, while net calcification rate was calculated from the start and end of the experiment. Net calcification rate (NCR) was lowest under OA treatment. Likewise the low total alkalinity at the start of the experiment under OA suggests that the mussels experienced greater physiological stress. The higher survival rate of green mussels and the increase in the byssus regeneration rate over time in all treatments demonstrated that it can acclimate better to acute short‐term temperature and pH stress. The very low survival of M. strigata in OA compared to other treatments indicates its high sensitivity to low pH stress. However, surviving charru individuals maintained high byssus thread regeneration in all treatments. Overall, results suggest that M. strigata may not displace the native green mussels', P. viridis, higher tolerance to acute short‐term exposure to elevated temperatures and low pH, but can co‐exist in lower densities. This is the first study to compare the short‐term physiological responses of a sympatric non‐native and native mussel species under experimentally induced stress conditions. Longer‐term studies on the population dynamics of these species are essential to assess the potential success of these species under changing and variable environmental conditions.

Flexible Mechanical Sensors for Plant Growth Monitoring: An Emerging Area for Smart Agriculture.

The last decade has seen significant progress in the development of flexible electronics and sensors, particularly for display technologies and healthcare applications. Advancements in scalable manufacturing, miniaturization, and integration have further extended the use of this new class of devices to smart agriculture, where multimodal sensors can be seamlessly attached to plants for continuous and remote monitoring. Among the various types of sensing devices for agriculture, flexible mechanical sensors have emerged as promising candidates for monitoring vital parameters, including growth rates and water flow, providing a new avenue for understanding plant health and growth under varied environmental conditions. This perspective provides a snapshot of recent progress in this exciting and unconventional area of research and highlights potential opportunities for the future.