Background and Objective:The majority of ferns inhabit a wide range of habitats (from terrestrial, arboreal to aquatic) with either species being obligatory or facultative in their preference for ecological niche adaptation and tolerance to varying landscape physiognomy.This work was carried out at the three sub-ecological stations of International Institute of Tropical Agriculture, Onne, Rivers state, Nigeria and the objective is to assess the distribution and arrangement of fern in space using geospatial techniques in rainforest vegetation.Materials and Methods: Ground trothing ecological sampling methods, GPS for species georeferencing and ArcGIS software, (version 10.8 2021) for Nearest Neighbourhood Ratio and Autocorrelation analyses within sampling plots and among species across sampling plots of stations.Results: Nine species (Nephrolepis biserrata, Marattia fraxinea, Selaginella myosurus, Bubophyllum barbigerum, Pteris captoptera, Pteris pacifica, Nephrolepis pumicicola, Pteris burtonii and Diplazium sommatii) under six families existed in diverse niche habitation (one obligatory arboreal, six obligatory terrestrial forest floor and two facultative terrestrial/arboreal habitat).Phytospatial distribution in station I had Nephrolepis biserrata (random); Marattia fraxinea, Seleginella myosurus, Pteris pacifica and Pteris burtonii (clustered); in station II Pteris pacifica, (dispersed) and Pteris burtonii and Seleginella myosurus (clustered) and Seleginella myosurus (dispersed).Conclusion: This study has identified fern species across the various modes of habitation besides the variation while in their spatial distribution pattern.However, a clustered distribution pattern for all ferns was recorded with the spatial autocorrelation analysis.
Background and Objective:The uptake of chemical nutrients by oil palm for bunch production is influenced by physical properties such as bulk density, texture and moisture content of the soils and some climatic variables like rainfall, temperature and solar radiation.The objective was to examine the influence of these properties and some climatic variables on the weight and number of harvested bunches. Materials and Methods:The experiment was laid out in a Randomized Complete Block Design (RCBD) and consisted of soil sampling using AfSIS protocol and cores of known volume.Frond leaf 17 was also sampled while climatic variables were obtained from the Statistics Division of the Nigerian Institute for oil palm.Research data generated were subjected to One-way Analysis of Variance (ANOVA) using Genstat statistical software at a 5% level of probability.Results: The except for soil pH and moisture content, the applied fertilizers had no direct effects on soil chemical properties.Person's correlation analysis showed a relationship between leaf nitrogen and solar radiation; bunch weight and number of harvested bunches as well as bunch organic matter content of the soils.Conclusion: Though the applied inorganic fertilizers had no direct effects on soil chemical properties, they however improved soil moisture content and uptake of nitrogen as revealed by leaf total N.
Cyber-attacks today are a source of great concern due to the increase in the use of the Internet in many areas, which has allowed increasing intrusion on networks and attempts to damage systems and others.Therefore, to stay up with the evolution of cyber-attacks, intrusion detection systems must be constantly improved.Intrusion detection system is a technique that may be applied to track both known and unidentified breaches before one of them damages network hardware.One of the very important things that has a big role in the strength of the system is the selection of good features in training the system.In this research paper, intrusion detection systems are proposed based on reducing and selecting features through the use of a "double feature selection" with the random forest algorithm.Experiments were performed on a data set NSL-KDD (it dataset from the Canadian Institute for Cybersecurity).By evaluating the performance, a system accuracy of 0.9981, a training time of 3.47 sec and a detection time of 0.24 sec were obtained.The proposed work was compared with related work using the same algorithm and dataset.The system proved superior to many of the proposed systems in terms of accuracy of the system, recall, precision, the time spent in training the system and the time of detection.
Background and Objective:The rapid urban development has caused various pollution in Hong Kong.However, the current measures adopted are aimed at controlling the surface level emission, while the vertical dispersion of pollutants is less investigated.This research project aims to identify the vertical dispersion patterns of particulate matter and noise emitted from road traffic and their decay rates with increasing vertical distance from the source and examine the possible correlation between traffic noise frequency levels and vehicle-emitted particulate.Materials and Methods: Three sets of equipment have been installed at three different heights on building facades perpendicular to the road surface, facing traffic to monitor PM concentrations (PM 1 , PM 2.5 , PM 4.25 and PM 10 ), noise frequencies and other environmental data namely temperature, relative humidity and wind speed.Results: The study anticipates uncovering a positive relationship between vehicular particulate matter emissions and traffic-related noise on lower floors, specifically at an 800 Hz noise frequency.Analysis of the three-dimensional plots indicates that pollutant concentrations are highest at lower levels.Notably, PM 1 , PM 2.5 and PM 4.25 demonstrate relatively high R-squared values (PM 1 = 0.674, PM 2.5 = 0.649 and PM 4.25 = 0.538), indicating a satisfactory fit of these models to the data.Conclusion: By highlighting the often-overlooked vertical transmission of particulate matter and noise from vehicles, this research contributes to a deeper understanding of air and noise pollution levels in high-rise urban environments.These insights hold the potential to inform future urban planning initiatives aimed at enhancing public health outcomes.
Background and Objective: Fatty acids have been utilized to trace organic matter source, fate and fluxes transmitted between estuaries, rivers, tributaries and their drainage basins worldwide.However, such correspondence is scarce in Sub-Saharan African region, particularly in sediment cores of Cross River system.A comparative evaluation of recent sediment cores (50 cm long) from the upper and lower Cross River system, was undertaken to characterize the sources, distributions and fate of fatty acids.Materials and Methods: These were achieved by solvent extraction, purification, identification/quantification using gas chromatography-mass spectrometry and principal component analysis-multiple linear regression statistics.Dispersion of fatty acid classes followed the trends short-chain>long-chain>branched-chain>monounsaturated fatty acids for the upper system and short-chain>branched-chain>long-chain>monounsaturated for the lower.Results: Principal component analysis-multiple linear regression apportioned 53.14% to a mixed source of phytoplankton (dinoflagellate), heterotrophic bacteria and terrestrial plant (Rhizophora avicennia) and 48.86% to a mixed source of phytoplankton (diatom) and photosynthetic bacteria in the case of the upper system.For the lower, a mixed source of phytoplankton (dinoflagellate), heterotrophic bacteria and terrestrial plant Nypa fruticans made the larger contribution of 93.32%, while photosynthetic bacteria and terrestrial plant metabolites contributed 6.68% to the total fatty acids flux.The irregular fatty acids distribution patterns observed down cores were attributed to differences in the water depth, sediment texture, biodegradation and depositional environmental conditions.Conclusion: Detection of considerable levels of bacterial fatty acids suggested the involvement of an essential aerobic/anaerobic microbial activity and operation of varying biogeochemical processes at these sites.
