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Porcelain and plastic materials constitute bulk of household wastes. Owing to resistibility and slow degradability that accounts for higher residence time, these materials qualify as potential hazardous wastes. Retention of water permits these wastes to form a congenial biotope for the breeding of different vector mosquitoes. Thus porcelain and plastic wastes pose a risk from public health viewpoint. This proposition was validated through the study on the porcelain and plastic household wastes as larval habitats of Dengue vectors (Aedes spp.) in rural and urban areas around Kolkata, India. The wastes were characterized in terms of larval productivity, seasonal variation and a comparison between urban and rural areas was made using data of two subsequent years. The number of wastes positive as larval habitats and their productivity of Aedes spp. varied among the types of household wastes with reference to months and location. Multivariate analysis revealed significant differences in the larval productivity of the household wastes based on the materials, season, and urban-rural context. Results of Discriminant Analysis indicated differences in abundance of Ae. aegypti and Ae. albopictus for the urban and rural areas. The porcelain and plastic wastes were more productive in urban areas compared to the rural areas, indicating a possible difference in the household waste generation. A link between household wastes with Aedes productivity is expected to increase the risk of dengue epidemics if waste generation is continued without appropriate measures to limit addition to the environment. Perhaps, alternative strategies and replacement of materials with low persistence time can reduce this problem of waste and mosquito production.

Bioturbation is recognized as a deterministic process that sustains the physicochemical properties of the freshwater ecosystem. Irrigation, ventilation, and particle reworking activities made by biotic components on sediment beds influence the flow of nutrients and transport of particles in the sediment–water interface. Thus, the biogenic disturbances in sediment are acknowledged as pivotal mechanism nutrient cycling in the aquatic system. The macroinvertebrates of diverse taxonomic identity qualify as potent bioturbators due to their abundance and activities in the freshwater. Of particular relevance are the bioturbation activities by the sediment-dwelling biota, which introduce changes in both sediment and water profile. Multiple outcomes of the macroinvertebrate-mediated bioturbation are recognized in the form of modified sediment architecture, changed redox potential in the sediment–water interface, and elicited nutrient fluxes. The physical movement and physiological activities of benthic macroinvertebrates influence organic deposition in sediment and remobilize sediment-bound pollutants and heavy metals, as well as community composition of microbes. As ecosystem engineers, the benthic macroinvertebrates execute multiple functional roles through bioturbation that facilitate maintaining the freshwater as self-sustaining and self-stabilizing system. Graphical abstract The likely consequences of bioturbation on the freshwater ecosystems facilitated by various macroinvertebrates — the ecosystem engineers. Among the macroinvertebrates, varied species of molluscs, insects, and annelids are the key facilitators for the movement of the nutrients and shaping of the sediment of the freshwater ecosystem.

Using the snails Filopaludina bengalensis and Gabbia orcula , along with tubificid worms and Chironomus sp., one monospecific and one combinatorial experiment were conducted in microcosms over 28 days to explore the direct and indirect interactive effects of non-predatory snails and tubificid worms on the bioturbation activity of chironomid larvae. These experiments examined how the species, whether alone or in combinations of two or three, influenced nutrient cycling in freshwater environments. On a comparative scale, the snails demonstrated higher N and P efflux than the tubificid worms and chironomid larvae, with the values normalized to biomass. At the community level, the chironomid, in combination with F. bengalensis and tubificid worms, showed a significant increase in N and P flux compared to the control. Unlike the two-species treatments, only the chironomid combined with F. bengalensis displayed higher N flux relative to the three-species treatment. Additionally, the indirect interactions of grazer snails more effectively inhibited the tube-dwelling behaviour of larvae than gallery-diffuser oligochaetes. Thus, the study reveals that species-specific functional traits and their interactions have a stronger effect on nutrient dynamics than species richness alone.

In this study, we aimed to find biomarkers of autism in young children. We recorded magnetoencephalography (MEG) in thirty children (4–7 years) with autism and thirty age, gender-matched controls while they were watching cartoons. We focused on characterizing neural oscillations by amplitude (power spectral density, PSD) and phase (preferred phase angle, PPA). Machine learning based classifier showed a higher classification accuracy (88%) for PPA features than PSD features (82%). Further, by a novel fusion method combining PSD and PPA features, we achieved an average classification accuracy of 94% and 98% for feature-level and score-level fusion, respectively. These findings reveal discriminatory patterns of neural oscillations of autism in young children and provide novel insight into autism pathophysiology.

Intraguild predation (IGP) is common in the freshwater insect communities, involving a top predator, intraguild prey (IG prey) and a shared prey. Influence of the habitat complexity on the prey-predator interactions is well established through several studies. In the present instance, the IGP involving the heteropteran predators and the dipteran prey were assessed in the background of the habitat complexity. The three predators Diplonychus rusticus , Ranatra filiformis , and Laccotrephes griseus , one intraguild prey Anisops bouvieri and two dipteran prey Culex quinquefasciatus and Chironomus sp. were used in different relative density against the complex habitat conditions to deduce the impact on the mortality on the prey. In comparison to the open conditions, the presence of the macrophytes and pebbles reduced the mortality of the shared prey under intraguild system as well as single predator system. The mortality of the shared prey was however dependent on the density of the predator and prey. Considering the shared prey mortality, predation on mosquito larvae was always higher in single predator system than chironomid larvae irrespective of identity and density of predators. However, for both the shared prey, complexity of habitat reduced the prey vulnerability in comparison to the simple habitat condition. Higher observed prey consumption depicts the higher risk to predation of shared prey, though the values varied with habitat conditions. Mortality of IG prey ( A . bouvieri ) in IGP system followed the opposite trend of the shared prey. The lower mortality in simple habitat and higher mortality in complex habitat conditions was observed for the IG prey, irrespective of shared prey and predator density. In IGP system, the shared prey mortality was influenced by the habitat conditions, with more complex habitat reducing the vulnerability of the shared prey and increased mortality of the IG prey. This implies that the regulation of the mosquitoes, in the IGP system will be impeded by the habitat conditions, with the heteropteran predators as the top predator.

Dengue outbreaks are common in tropical or temperate countries, and climate change can exacerbate the problem by creating conditions conducive to the spread of mosquitoes and prolonging the transmission season. Warmer temperatures can allow mosquitoes to mature faster and increase their ability to spread disease. Additionally, changes in rainfall patterns can create more standing water, providing a breeding ground for mosquitoes. The objective of this study is to investigate the correlation between environmental and demographic factors and the dissemination of dengue fever. The study will use yearly data from 2000 to 2021 from 11 countries highly affected by dengue, considering multiple factors such as dengue cases, temperatures, precipitation, and population to better understand the impact of these variables on dengue transmission. In this research, Poisson regression (PR) and negative binomial regression (NBR) models are used to model count data and estimate the effect of different predictor variables on the outcome. Also, histogram plots and pairwise correlation plots are used to provide an initial overview of the distribution and relationship between the variables. Moreover, Goodness-of-fit tests, t-test analysis, diagnostic plots, influence plots, and residual vs. leverage plots are used to check the assumptions and validity of the models and identify any outliers or influential observations that may be affecting the results. The findings indicate that mean temperature and log(Urban) had a positive impact on dengue infection rates, while maximum temperature, log(Precipitation), and population density had a negative impact. However, minimum temperature, log(Rural), and log(Total population) did not demonstrate any significant effects on the incidence of dengue. The impact of demographic-environmental factors on dengue outbreaks in 11 Asian countries is illuminated by this study. The results highlight the significance of mean temperature (Tmean), maximum temperature (Tmax), log(Urban), log(Precipitation), and population density in influencing dengue incidence rates. However, further research is needed to gain a better understanding of the role of additional variables, such as immunity levels, awareness, and vector control measures, in the spread of dengue.

Usage of effective classification techniques on Magnetic Resonance Imaging (MRI) helps in the proper diagnosis of brain tumors. Previous studies have focused on the classification of normal (nontumorous) or abnormal (tumorous) brain MRIs using methods such as Support Vector Machine (SVM) and AlexNet. In this paper, deep learning architectures are used to classify brain MRI images into normal or abnormal. Gender and age are added as higher attributes for more accurate and meaningful classification. A deep learning Convolutional Neural Network (CNN)-based technique and a Deep Neural Network (DNN) are also proposed for effective classification. Other deep learning architectures such as LeNet, AlexNet, ResNet, and traditional approaches such as SVM are also implemented to analyze and compare the results. Age and gender biases are found to be more useful and play a key role in classification, and they can be considered essential factors in brain tumor analysis. It is also worth noting that, in most circumstances, the proposed technique outperforms both existing SVM and AlexNet. The overall accuracy obtained is 88% (LeNet Inspired Model) and 80% (CNN-DNN) compared to SVM (82%) and AlexNet (64%), with best accuracy of 100%, 92%, 92%, and 81%, respectively.

The transition to clean energy has accelerated the pursuit of hydrogen as a sustainable fuel. Among various production methods, proton exchange membrane electrolysis cells (PEMECs) stand out due to their ability to generate ultra-pure hydrogen with efficiencies exceeding 80% and current densities reaching 2 A/cm2. Their compact design and rapid response to dynamic energy inputs make them ideal for integration with renewable energy sources. This review provides a comprehensive assessment of PEMEC technology, covering key internal components, system configurations, and efficiency improvements. The role of catalyst optimization, membrane advancements, and electrode architectures in enhancing performance is critically analyzed. Additionally, we examine state-of-the-art numerical modelling, comparing zero-dimensional to three-dimensional simulations and single-phase to two-phase flow dynamics. The impact of oxygen evolution and bubble dynamics on mass transport and performance is highlighted. Recent studies indicate that optimized electrode architectures can enhance mass transport efficiency by up to 20%, significantly improving PEMEC operation. Advancements in two-phase flow simulations are crucial for capturing multiphase transport effects, such as phase separation, electrolyte transport, and membrane hydration. However, challenges persist, including high catalyst costs, durability concerns, and scalable system designs. To address these, this review explores non-precious metal catalysts, nanostructured membranes, and machine-learning-assisted simulations, which have demonstrated cost reductions of up to 50% while maintaining electrochemical performance. Future research should integrate experimental validation with computational modelling to improve predictive accuracy and real-world performance. Addressing system control strategies for stable PEMEC operation under variable renewable energy conditions is essential for large-scale deployment. This review serves as a roadmap for future research, guiding the development of more efficient, durable, and economically viable PEM electrolyzers for green hydrogen production.

Understanding fluid dynamics and heat transfer is crucial for designing and improving various engineering systems. This study examines the heat transfer characteristics of a buoyancy-driven natural convection flow that is laminar and incompressible. The investigation also considers entropy generation (Egen) within an octagonal cavity subject to a cold cylinder inside the cavity. The dimensionless version of the governing equations and their corresponding boundary conditions have been solved numerically using the finite element method, employing triangular mesh elements for discretization. The findings indicated that incorporating a cold cylinder inside the octagonal cavity resulted in a higher heat transfer (HT) rate than in the absence of a cold cylinder. Furthermore, using the heat flux condition led to a higher average Nusselt number (Nuavg) and a lower Bejan number (Be) than the isothermal boundary condition. The results also showed that HT and Egen were more significant in the Al2O3-H2O nanofluid than the basic fluids such as air and water, and HT increased as χ increased. The current research demonstrates that employing the heat flux condition and incorporating nanoparticles can enhance the rate of HT and Egen. Furthermore, the thermo-fluid system should be operated at low Ra to achieve greater HT effectiveness for nanofluid concerns.

The bioturbation potential of three freshwater operculate snails, Filopaludina bengalensis , Gabbia orcula and Melanoides tuberculata, was compared, using water column depth and sediment surface area as the explanatory variables. Assessment of nutrient fluxes from sediment to overlying water was estimated in glass microcosms, that varied in height (tall, medium, short) and base (narrow, wide), resulting in six habitat conditions. In course of movement and grazing, all the three snail species modified surface architecture of the sediment. Besides, the snails modulated NO X ˉ (NO 2 ˉ-N + NO 3 ˉ-N), NH 4 + -N and PO 4 3− -P concentrations and other parameters (TDS, conductivity) of the water column in significantly varying proportions. Snail-induced changes in the rate of nutrient flux were highest for F. bengalensis. Periphytic chlorophyll- a concentration was reduced in all snail-treated microcosms compared to the control. Grazing, scraping and movement of snails on sediment facilitated the release of the nutrients in a species-specific manner depending on sediment surface area and water column depth of the microcosm. Apparently, snails may be useful in mobilizing the sediment content in freshwater lakes and ponds, facilitating ecosystem processes.