Organic Matter and Heavy Metals Leachate Effect on Soils of Selected Dumpsites in Selected North Central States of Nigeria

This research was conducted to assess the presence  of some heavy metals Chromium (Cr), Iron (Fe), Copper (Cu), Manganese (Mn), Lead (Pb), Zinc (Zn) and Aluminum (Al) in municipal solid waste dumps. Heavy metals in the soils were determined at varying depths of 0-5cm, 5-15cm and 15-30cm to assess the extent of pollution and the effects of pH and organic matter in the soil. Heavy metals concentrations were analysed using Atomic Absorption Spectrophotometer. The results revealed a significant difference (p < 0.05) in the concentrations of heavy metals across varying depth at the dumpsites when compared with control points in the same location. Mn had the highest mean 131.22 ± 25.98 mgkg-1 followed by Fe, which is 69 ± 11.02 mgkg-1 at the dumpsites. Mean concentration of all the Heavy metals investigated at the various dumpsites studied were significantly higher than at the control point and below the maximum standard levels set by FAO and WHO for agricultural soils. Result of particle distribution indicated higher sand content (> 80.0%) and lower clay and silt contents in both dumpsite and control site which implies the ease of movement of dissolved metals in the soil environment. Organic Matter (OM) content at dumpsites was observed to be slightly higher than at the control sites. The data also signifies that as pH decreases and %OM decreases the concentration of these heavy metals decreases down the soil profile. It is, therefore, concluded that accumulation of heavy metals in depth was highly correlated with pH and organic matter content

Analysis of the Impact of Relative Humidity and Mineral Nuclei Mode Aerosols Particle Concentration on the Visibility of Desert Aerosols

This paper presents the results of the Analysis of the Impact of relative humidity and water-soluble aerosol particle concentrations on the visibility and particle size distribution of desert aerosols based on microphysical properties of desert aerosols. The microphysical properties (the extinction coefficients, volume mix ratios, dry mode radii and wet mode radii) were extracted from Optical Properties of Aerosols and Clouds (OPAC 4.0) at eight relative humidities (00 to 99%RH) and at the spectral range of 0.4-0.8 mm. the concentrations of mineral nuclie component (MINN) were varied to obtain five different models. The angstrom exponent (a), the turbidity (b), the curvature (a2), humidification factor (g), the mean exponent of aerosol growth curve (µ) and the mean exponent of aerosol size distributions (n) were determined from the regression analysis of some standard equations. It was observed that the values of (a) are less than 1 throughout the 5 models which signifies the dominance of coarse mode particles over fine mode particles. It was observed that the curvature (a2) has both monomodal and bimodal types of distributions all through the 5 models and this signifies the dominance of coarse mode particles with some traces of fine mode particles. The visibility was observed to decrease with the increase in RH and increased with wavelength. The analysis further found that there is an inverse power law relationship between humidification factor, the mean exponent of the aerosol size distribution with the mean exponent of the aerosol growth curve (as the magnitude of (µ) decreases across the five models, the magnitudes of (g) and (n) increase, but the magnitude of both (g) and (n) increases for a given (µ) across the individual models). The mean exponent of aerosol size distribution (µ) being less than 3 indicate hazy condition of the desert atmosphere

Shape recognition through multi-level fusion of features and classifiers

Shape recognition is a fundamental problem and a special type of image classification, where each shape is considered as a class. Current approaches to shape recognition mainly focus on designing low-level shape descriptors, and classify them using some machine learning approaches. In order to achieve effective learning of shape features, it is essential to ensure that a comprehensive set of high quality features can be extracted from the original shape data. Thus we have been motivated to develop methods of fusion of features and classifiers for advancing the classification performance. In this paper, we propose a multi-level framework for fusion of features and classifiers in the setting of gran-ular computing. The proposed framework involves creation of diversity among classifiers, through adopting feature selection and fusion to create diverse feature sets and to train diverse classifiers using different learn-Xinming Wang algorithms. The experimental results show that the proposed multi-level framework can effectively create diversity among classifiers leading to considerable advances in the classification performance

COVAD survey 2 long-term outcomes: unmet need and protocol

Vaccine hesitancy is considered a major barrier to achieving herd immunity against COVID-19. While multiple alternative and synergistic approaches including heterologous vaccination, booster doses, and antiviral drugs have been developed, equitable vaccine uptake remains the foremost strategy to manage pandemic. Although none of the currently approved vaccines are live-attenuated, several reports of disease flares, waning protection, and acute-onset syndromes have emerged as short-term adverse events after vaccination. Hence, scientific literature falls short when discussing potential long-term effects in vulnerable cohorts. The COVAD-2 survey follows on from the baseline COVAD-1 survey with the aim to collect patient-reported data on the long-term safety and tolerability of COVID-19 vaccines in immune modulation. The e-survey has been extensively pilot-tested and validated with translations into multiple languages. Anticipated results will help improve vaccination efforts and reduce the imminent risks of COVID-19 infection, especially in understudied vulnerable groups

Evaluation of Irrigation Application Efficiency: Case Study of Chanchaga Irrigation Scheme

Water is an integral issue needed to attain the desired targets but good quality water for irrigation purpose is gradually become scarce. The seasonal nature of rainfall can give rise to water stress at critical periods of growth. This research attempts to evaluate the irrigation application efficiency of Chanchaga irrigation scheme, Minna, Niger state. A hand auger was used to bore to a desired depth to remove samples of the moist soil. Samples of the moist soil removed was placed in a can, covered and taken to the laboratory. The specific gravity (apparent) of the soil particle and the depth of water applied were determined using volumetric method, water application efficiency is determined using Gravimetric Method of Soil Moisture Content (Pw) Determination. The moisture content of the field after irrigation water is applied falls between the ranges of 51.1% and 51.5%, with an average of 51.28%, in this case the average amount of water applied is about 4.68%, this shows a little increase in the moisture content of the soil in the field. It was concluded that the efficiency of water application obtained is adequate and a good result considering the available management practice in terms of system operation, monitoring and evaluation

Novel radio link buffer management schemes for end-user multi-class traffic in high speed packet access networks

The requirement to provide multimedia services with QoS support in mobile networks has led to standardization and deployment of high speed data access technologies such as the High Speed Downlink Packet Access (HSDPA) system. HSDPA improves downlink packet data and multimedia services support in WCDMA-based cellular networks. As is the trend in emerging wireless access technologies, HSDPA supports end-user multi-class sessions comprising parallel flows with diverse Quality of Service (QoS) requirements, such as real-time (RT) voice or video streaming concurrent with non real-time (NRT) data service being transmitted to the same user, with differentiated queuing at the radio link interface. Hence, in this paper we present and evaluate novel radio link buffer management schemes for QoS control of multimedia traffic comprising concurrent RT and NRT flows in the same HSDPA end-user session. The new buffer management schemes—Enhanced Time Space Priority (E-TSP) and Dynamic Time Space Priority (D-TSP)—are designed to improve radio link and network resource utilization as well as optimize end-to-end QoS performance of both RT and NRT flows in the end-user session. Both schemes are based on a Time-Space Priority (TSP) queuing system, which provides joint delay and loss differentiation between the flows by queuing (partially) loss tolerant RT flow packets for higher transmission priority but with restricted access to the buffer space, whilst allowing unlimited access to the buffer space for delay-tolerant NRT flow but with queuing for lower transmission priority. Experiments by means of extensive system-level HSDPA simulations demonstrates that with the proposed TSP-based radio link buffer management schemes, significant end-to-end QoS performance gains accrue to end-user traffic with simultaneous RT and NRT flows, in addition to improved resource utilization in the radio access network